prevalence and molecular detection of gastrointestinal

Prevalence and Molecular Detection of

Gastrointestinal Pathogens in Sheep, Goats and

Fish from Papua New Guinea

Submitted by Melanie Koinari (BiomedSc Honours)

This thesis is presented for the degree of Doctor of Philosophy of Murdoch

University

School of Veterinary and Life Sciences

Abstract Gastrointestinal pathogens in sheep, goats and fish in PNG

Abstract

Gastrointestinal parasites of livestock cause diseases of important socio-

economic concern worldwide. The two main types of intestinal parasites are helminths

and protozoa. They can cause high mortality, reduce production and lead to significant

overall economic losses. In tropical and subtropical areas, parasitic nematodes are

recognised as a limiting factor to the expansion and improvement of smallholder

production of small ruminants. In addition to their veterinary importance, some

parasites of domesticated livestock can also be transmitted to companion animals and

wildlife, and are a threat to public health.

Little is known of the prevalence of internal pathogens in domesticated animals

or wildlife in Papua New Guinea (PNG). There have been various reports on

gastrointestinal helminth and Eimeria infections in sheep and goats in PNG. However,

those surveys have been restricted in their geographical range and have only been

performed on animals raised in government or institutional (either university or

agriculture research institution) farms. There is insufficient information on the

epidemiology of gastrointestinal parasites infecting sheep and goats in smallholder

farms. Fish, both cultured and wild caught, are an important food source in PNG, but

there have been few previous surveys of parasite infection in fish. Therefore, the aim of

this study was to investigate the prevalence of various pathogens including

gastrointestinal nematodes, Eimeria, Cryptosporidium, Giardia and Chlamydia in sheep

and goats; and Cryptosporidium, Giardia and anisakids in fish in PNG. A total of 504

faecal samples were collected from sheep (n = 276) and goats (n = 228) in smallholder,

government and institutional farms, and a total of 614 fish (25 species) (cultured

freshwater n = 132, wild freshwater n = 206 and wild marine n = 276) were sampled

from February to August 2011. The study sites for sheep and goats covered a wide

geographical area, representing the major sheep and goat farming regions of PNG.

Samples were screened using microscopy and molecular techniques.

The overall prevalence of gastrointestinal parasites in sheep and goats in 165

small ruminants (110 sheep and 55 goats) using a modified McMaster technique was

77.6 % (128/165), with 72 % (79/110) of sheep and 89 % (49/55) of goats having one or


4

more species of gastrointestinal parasite. The gastrointestinal parasites found and

their prevalences in sheep (S) and in goats (G) were: trichostrongylids 67.3 % (S),

85.5 % (G); Eimeria 17.3 % (S), 16.4 % (G); Strongyloides 8.2 % (S), 23.6 % (G); Fasciola

5.5 % (S), 18.2 % (G); Trichuris 1.8 % (S), 3.6 % (G); and Nematodirus 1.8 % (S), 3.6 %

(G). Two additional genera were found in goats: Moniezia (9.1 %) and Dictyocaulus

(3.6 %). To identify the pathogenic trichostrongylids, further analysis using a species-

specific qPCR was performed on genomic DNA from faeces of 263 sheep and 228

goats. The prevalence of each nematode in sheep (S) and goats (G) were: Haemonchus

contortus 41.1 % (S) and 41.7 % (G), Teladorsagia circumcincta 21.3 % (S) and 24.1 %

(G) and Trichostrongylus spp. 14.8 % (S) and 14 % (G). In addition, a total of 94 samples

(mostly Eimeria-positives by microscopy), which included 57 faecal samples from

sheep and 37 faecal samples from goats, were screened by qPCR. The prevalence of

Eimeria was 64.9 % (37/57) for sheep and 91.9 % (34/37) for goats. This is the first

study to quantitatively examine the prevalence of gastrointestinal parasites in goats in

PNG. The high rates of parasitism observed in the present study are likely to be

associated with poor farming management practises including lack of pasture recovery

time, lack of parasite control measures and poor quality feed.

Using molecular tools (nested PCRs), genomic DNA samples from sheep

(n = 276), goats (n = 228) and fish (n = 614) were screened for Cryptosporidium spp.

and positives were genotyped at the 18S rRNA, 60 kDa glycoprotein (gp60) and actin

loci. The overall prevalence for Cryptosporidium at the 18S rRNA locus was 2.2 %

(6/276) in sheep, 4.4 % (10/228) in goats and 1.14 % (7/614) in fish. In sheep,

C. parvum (subtypes IIaA15G2R1 and IIaA19G4R1), C. andersoni and C. scrofarum were

identified. In goats, C. hominis (subtype IdA15G1), C. parvum, C. xiaoi and rat genotype

II were identified. In fish, C. hominis (subtype IdA15G1), C. parvum (IIaA14G2R1,

IIaA15G2R1 and IIaA19G4R1) and a novel genotype were identified in cultured

freshwater (n = 2), wild freshwater (n = 1), and wild marine (n = 4) fish hosts.

Cryptosporidium was found in four different fish species; Nile tilapia (Oreochromis

niloticus), silver barb (Puntius gonionotus), mackerel scad (Decapterus macarellus) and

oblong silver biddy (Gerres oblongus). A novel piscine genotype in fish (piscine

genotype 8) was identified in two marine oblong silver biddies and it exhibited a 4.3 %


5

genetic distance from piscine genotype 3 (its closest relative) at the 18S locus. The

three subtypes of C. parvum identified in sheep and fish (IIaA14G2R1, IIaA15G2R1 and

IIaA19G4R1) were all zoonotic. This is the first report of Cryptosporidium spp. in sheep,

goats and fish in PNG. Identification of Cryptosporidium in livestock warrants better

care of farm animals to avoid contamination and illness in vulnerable populations. The

detection of zoonotic Cryptosporidium in livestock suggests these animals may serve as

reservoirs for human infection. Zoonotic Cryptosporidium were identified in fish

samples from all three groups (cultured and wild freshwater fish and wild marine fish).

The identification of zoonotic Cryptosporidium genotypes in fish is important to public

health in PNG and should be further investigated. In particular, detection of

Cryptosporidium among fingerlings from aquaculture farms warrants further research

to gain a better understanding of the epidemiology of Cryptosporidium infection in

cultured fish.

Giardia duodenalis was screened in sheep (n = 276), goats (n = 228) and fish

(n = 272) using qPCR targeting the glutamate dehydrogenase (gdh) gene. The overall

prevalence of G. duodenalis was 9.1 % (25/256) in sheep, 12.3 % (28/228) in goats and

7 % (19/272) in fish. Although the present study found a low prevalence for

G. duodenalis in adult small ruminants and fish, these animals can be considered as

sources of contamination for susceptible hosts in PNG, because low numbers of

Giardia cysts can cause infection. This is the first study to identify Giardia spp. in

sheep, goats and fish in PNG. It demonstrates that G. duodenalis is prevalent in small

ruminants and fish in PNG. Giardia duodenalis assemblage E (livestock genotype) was

more prevalent in sheep and goats than zoonotic assemblages A and B. Further

research into the characterisation of G. duodenalis assemblages in livestock, fish and

humans in PNG is required to better understand its zoonotic potential.

The prevalence of anisakid nematode larvae in marine fish collected on the

coastal shelves off the townships of Madang and Rabaul in PNG was investigated using

microscopy and molecular techniques. The third-stage larvae of several genera of

anisakid nematodes are important etiological agents for zoonotic human anisakidosis.

Nematodes were found in seven fish species including Decapterus macarellus, Gerres


6

oblongus, Pinjalo lewisi, Pinjalo pinjalo, Selar crumenophthalmus, Scomberomorus

maculatus and Thunnus albacares. They were identified by both light and scanning

electron microscopy as Anisakis Type I larvae. Sequencing and phylogenetic analysis of

the internal transcribed spacers (ITS) and the mitochondrial cytochrome C oxidase

subunit II (cox2) gene identified all nematodes as Anisakis typica. This study represents

the first in-depth characterization of Anisakis larvae from seven new fish hosts in PNG.

The overall prevalence of larvae was low (7.6 %) and no recognised zoonotic Anisakis

species were identified, suggesting a low threat of anisakidosis in PNG.

Finally, the prevalence of Chlamydia abortus and C. pecorum in sheep (n = 221)

and goats (n = 128) were investigated using two species-specific qPCR assays, targeting

the outer membrane protein cell surface antigen gene (ompA). The overall prevalence

of C. abortus was 12.2 % (27/221) in sheep and 8.6 % (11/128) in goats, while for

C. pecorum, it was 7.7 % (17/221) in sheep and 8.6 % (11/128) in goats. This is the first

study to identify C. abortus and C. pecorum in sheep and goats in PNG. It also

demonstrates that C. abortus and C. pecorum are prevalent in sheep and goats in PNG,

highlighting a need for further research to quantify the production impacts of these

bacteria. Furthermore, the results of the present study indicate that C. abortus could

pose a risk of transmission to humans, especially, in PNG, where small ruminants in

villages are cared for by women on a daily basis.

In summary, the present study represents the most detailed investigation of

gastrointestinal parasites using molecular tools in sheep, goats and fish in PNG to date.

A variety of gastrointestinal pathogens were identified. This provides an important

update on internal pathogens of sheep and goats from previous studies (Quartermain,

2004b). Future investigations should include longitudinal studies and larger cohorts to

further assess parasite epidemiology in the diverse agro-climatic zones in the country.

Declaration Gastrointestinal pathogens in sheep, goats and fish in PNG

Declaration

I declare this thesis is my own account of my research and contains as its main

content, work which has not been previously submitted for any degree and is not

currently being submitted for any other degree or qualification. I declare that I have

conducted the research described except where otherwise acknowledged.

………………………………………………………………………….

Melanie Koinari

May 2014

Acknowledgements Gastrointestinal pathogens in sheep, goats and fish in PNG

Acknowledgements

I would like to acknowledge my supervisors Professor Una Ryan and Associate

Professor Alan Lymbery for their guidance, sharing their experience and the time they

dedicated to my work.

I would also like to thank my other friends and colleagues at Murdoch

University for their assistance over the years, especially Dr. Rongchang Yang, Josephine

Ng-Hublin, Eileen Elliot, Dr. Andrea Paparini and Louise Pallant.

Many thanks to my friends and colleagues from the National Agriculture

Research Institute of Papua New Guinea, without who, sample collection in PNG

described in Chapter 2, could not have been conducted. I sincerely thank Dr. Workneh

Ayalew for providing the opportunity for me to collaborate with NARI and also for

assistance with the execution of this study. I am very grateful to the staffs at Labu and

Tambul, who were friendly, fun and willing to assist me wherever they could during my

time at NARI. My special thanks goes to Atmaleo Aguyanto for her friendship, helpful

discussions on sheep and goats in the country, organising sample collection at Labu

and for showing me her technique for faecal worm egg counts. I also would like to

thank Densley Tapat who organised fish sampling at aquaculture sites in Mumeng and

Martin Lobao and Johaness Pakatel for organising sampling from sheep and goats at

Baisu and Tambul. Furthermore, many thanks to the driver, Awatang Naru.

I acknowledge the staff of Department of Agriculture and Livestock in Goroka,

Papua New Guinea, especially, many thanks to Igu Yawani and Mr Farope for their

assistance during sampling in smallholder farms.

I am very grateful for subsistence sheep and goat farmers in Menifo, Benabena,

Goroka, Korefeigu, Daulo, in Eastern Highlands Province and Chuave in Simbu Province

for allowing me and my team to take samples from their animals. In addition, I thank

the fish farmers in Kundiawa, Asaro, Mumeng and Bathem for allowing me to take fish

samples from their farms.

I would like to thank Dr. Pascal Michon at Divine Word University in Madang for

organising a light microscope, which I used to perform work described in Chapter 3.

Acknowledgements Gastrointestinal pathogens in sheep, goats and fish in PNG

9

I would like to acknowledge my husband, Stephan, at the University of Western

Australia, for his assistance with scanning electron microscopy on anisakid nematodes

described in Chapter 2.

I would like to acknowledge financial support through international postgraduate

scholarship provided by Murdoch University.

Most importantly, I am very grateful to my family in PNG and also in Germany, for

their endless support. This work would not exist without my husband, Stephan and my

son Michael, who have been my steadfast companions throughout these very exciting

years of my life.

Table of Contents Gastrointestinal pathogens in sheep, goats and fish in PNG

Table of Contents

Abstract .................................................................................................................... 3

Declaration ............................................................................................................... 7

Acknowledgements .................................................................................................. 8

Table of Contents ................................................................................................... 10

List of Figures ......................................................................................................... 16

List of Tables ........................................................................................................... 18

List of Abbreviations .............................................................................................. 20

Statement of candidate contribution .................................................................... 22

1. General Introduction .......................................................................................... 23

1.1 Background ...................................................................................................... 24

1.1.1 Papua New Guinea: sheep, goats and fish. .............................................. 24

1.1.2 The impact of gastrointestinal parasites on sheep and goats ................. 26

1.1.3 Gastrointestinal pathogens of sheep and goats ...................................... 27

1.1.4 Gastrointestinal parasites of fish ............................................................. 30

1.2 Gastrointestinal parasitic nematodes of sheep and goats .............................. 31

1.2.1 Distribution and taxonomy ...................................................................... 31

1.2.2 Life cycle and morphology ....................................................................... 33

1.2.3 Pathogenicity and clinical signs ................................................................ 35

1.2.4 Diagnosis .................................................................................................. 36

1.2.5 Treatment and control ............................................................................. 38

1.3 Eimeria ............................................................................................................. 39


1.3.2 Life cycle and morphology ....................................................................... 40


1.3.4 Diagnosis .................................................................................................. 42



11

1.4 Cryptosporidium ............................................................................................... 43


1.4.2 Life cycle and morphology........................................................................ 47


1.4.4 Diagnosis ................................................................................................... 50


1.5 Giardia .............................................................................................................. 53




1.5.4 Diagnosis ................................................................................................... 57


1.6 Anisakids........................................................................................................... 59




1.6.4 Diagnosis ................................................................................................... 64


1.7 Chlamydia ......................................................................................................... 66




1.7.4 Diagnosis ................................................................................................... 71


1.8 Aims of the present study ................................................................................ 74

2. Materials and Methods ...................................................................................... 75

2.1 General background of the study .................................................................... 76

2.2 Human and animal ethics approval ................................................................. 76


12

2.3 Sampling ........................................................................................................... 76

2.3.1 Study locations for sheep and goats ........................................................ 76

2.3.2 Study locations for fish ............................................................................. 78

2.4 Survey questionnaire ....................................................................................... 79

2.5 Animals ............................................................................................................. 82

2.5.1 Sheep and goats ....................................................................................... 82

2.5.2 Fish ........................................................................................................... 83

2.6 Shipment of biological samples ....................................................................... 86

2.7 Parasitology ...................................................................................................... 86

2.7.1 Faecal worm egg count ............................................................................ 86

2.7.2 Morphological analysis of anisakid nematodes ....................................... 87

2.8 DNA isolation.................................................................................................... 88

2.8.1 Isolation of genomic DNA from faeces ..................................................... 88

2.8.2 Isolation of genomic DNA from anisakid larvae ....................................... 89

2.8.3 Isolation of genomic DNA from fish gut scrapings ................................... 90

2.9 DNA amplification ............................................................................................ 90

2.9.1 Molecular detection of trichostrongylid nematodes by qPCR ................. 91

2.9.2 Molecular detection of Eimeria spp. by qPCR and nested PCR. .............. 92

2.9.3 Molecular detection of Cryptosporidium spp. using nested PCR ............. 93

2.9.4 Molecular detection of Giardia spp. using qPCR and nested PCR ........... 96

2.9.5 Molecular detection of anisakid nematodes using PCR ......................... 100

2.9.6 Molecular detection of Chlamydia spp. by qPCR ................................... 101

2.10 Agarose gel electrophoresis ......................................................................... 102

2.11 PCR product extraction from gel .................................................................. 103

2.12 DNA sequencing PCR with dye terminator kit ............................................. 103

2.13 Post reaction purification ............................................................................. 103

2. 14 DNA Sequencing .......................................................................................... 104

2.15 Phylogenetic analysis ................................................................................... 104


13

2.16 Statistics .......................................................................................................105

3. Prevalence and infection levels of helminth and coccidian parasites in sheep and goat in PNG ..........................................................................................................107

3.1 Introduction ...................................................................................................109

3.2 Methods .........................................................................................................109

3.2.1 Sample collection ...................................................................................109

3.2.2 Parasitology ............................................................................................111

3.2.3 DNA isolation ..........................................................................................111

3.2.4 Screening of trichostrongyles and Eimeria species by qPCR ..................111

3.2.5 Data analysis ...........................................................................................112

3.3 Results ............................................................................................................113

3.3.1 Infection levels of gastrointestinal parasites by microscopy .................113

3.3.2 Prevalence of trichostrongylid nematodes by qPCR ..............................118

3.3.3 Prevalence of Eimeria in sheep and goats by qPCR ...............................120

3.4 Discussion .......................................................................................................121

3.5 Conclusions ....................................................................................................125

4. Molecular characterisation of Cryptosporidium in sheep, goats and fish from PNG ..............................................................................................................................127

4.1 Introduction ...................................................................................................128

4.2 Methods .........................................................................................................129


4.2.2 DNA isolation ..........................................................................................130

4.2.3 Cryptosporidium genotyping and subtyping ..........................................130

4.2.4 GenBank nucleotide accession numbers ...............................................131

4.2.5 Histological analysis ................................................................................131

4.2.6 Analysis of prevalence ............................................................................132

4.3 Results ............................................................................................................132

4.3.1 Prevalence of Cryptosporidium in sheep, goats and fish. ......................132


14

4.3.2 Molecular characterisation of Cryptosporidium species identified in sheep, goats and fish at the 18S, gp60 and actin locus .............................................. 133

4.3.3 Microscopy ............................................................................................. 135

4.4 Discussion ....................................................................................................... 139

4.5 Conclusions .................................................................................................... 143

5. Prevalence of Giardia duodenalis in sheep, goats and fish from PNG by quantitative PCR ....................................................................................................................... 145

5.1 Introduction ................................................................................................... 146

5.2 Methods ......................................................................................................... 147

5.2.1 Sample collection ................................................................................... 147

5.2.2 DNA isolation and qPCR amplification ................................................... 147

5.2.3 Data analysis ........................................................................................... 147

5.3 Results ............................................................................................................ 147

5.4 Discussion ....................................................................................................... 150

5.5 Conclusions .................................................................................................... 151

6. Morphological and molecular characterisation of Anisakis species in fish from PNG .............................................................................................................................. 153

6.1 Introduction ................................................................................................... 154

6.2 Methods ......................................................................................................... 157

6.2.1 Parasite collection .................................................................................. 157

6.2.2 Morphological analysis ........................................................................... 157

6.2.3 Genetic characterisation and phylogenetic analysis .............................. 158

6.3 Results ............................................................................................................ 160

6.3.1 Prevalence of Anisakis spp. .................................................................... 160

6.3.2 Morphology of Anisakis Type I larvae .................................................... 160

6.3.3 Phylogenetic analysis of the ITS region .................................................. 161

6.4 Discussion ....................................................................................................... 165

6.5 Conclusions .................................................................................................... 167

7. Prevalence of Chlamydia in sheep and goats from PNG by quantitative PCR . 169


15

7.1 Introduction ...................................................................................................170

7.2 Methods .........................................................................................................170


7.2.2 DNA isolation and qPCR amplification ...................................................170

7.2.3 Data analysis ...........................................................................................171

7.3 Results ............................................................................................................171

7.4 Discussion .......................................................................................................173

7.5 Conclusions ....................................................................................................175

8. General discussion and concluding remarks ....................................................177

8.1 General discussion .........................................................................................178

8.2 Future directions ............................................................................................181

8.3 Concluding remarks........................................................................................183

Bibliography .........................................................................................................184

Appendices ...........................................................................................................227

List of Figures Gastrointestinal pathogens in sheep, goats and fish in PNG

List of Figures

Figure 1-1: Generalised life cycle of parasitic nematodes (order Strongylida) of the alimentary tract of livestock. .......................................................................................... 34

Figure 1-2: Life cycle of Eimeria species. ........................................................................ 41

Figure 1-3: A scanning electron micrograph of Cryptosporidium ................................... 48

Figure 1-4: Life cycle of Cryptosporidium parvum and C. hominis.................................. 49

Figure 1-5: Life cycle of Giardia duodenalis .................................................................... 55

Figure 1-6: Electron photomicrograph of Giardia duodenalis ........................................ 55

Figure 1-7: Complex life cycle of anisakid nematodes. ................................................... 62

Figure 1-8: Chlamydial development cycle ..................................................................... 69

Figure 2-1: Study locations for sheep, goats and fish in the present study. .................. 77

Figure 2-2: Pictures of sheep and goat farming in PNG. ................................................. 81

Figure 2-3: Pictures of fishing activities in PNG. ............................................................. 84

Figure 2-4: Trichostrongylid egg (left) and Eimeria oocyst (right) at 40x magnification. ......................................................................................................................................... 87

Figure 3-1: Flow chart of methods used for screening gastrointestinal parasites from faecal samples of sheep and goats. .............................................................................. 110

Figure 3-2: qPCR amplification plot for H. contortus as an example at the ITS-1 locus. ....................................................................................................................................... 113

Figure 4-1: Flow chart of the methodology for molecular detection of Cryptosporidium spp. in the present study. ............................................................................................. 129

Figure 4-2: Evolutionary relationships of Cryptosporidium isolates from sheep and goats inferred by neighbour-joining analysis of p distances calculated from pairwise comparison of 18S rRNA sequences. ............................................................................ 136

Figure 4-3: Evolutionary relationships of Cryptosporidium piscine-derived isolates inferred by neighbour-joining analysis of p distances calculated from pairwise comparison of 18S rRNA sequences. ............................................................................ 137

Figure 4-4: Phylogenetic relationships of Cryptosporidium isolates inferred by neighbor-joining analysis of the actin gene based on genetic distances calculated by the p distance model. ................................................................................................... 138

Figure 6-1: Type 1 and Type II Anisakis species belonging to the genus Anisakis. ....... 155

Figure 6-2: Schematic representation of diagnostic features for differentiating anisakids. ....................................................................................................................... 156

List of Figures Gastrointestinal pathogens in sheep, goats and fish in PNG

17

Figure 6-3: Overview of the methods for collection and screening of anisakid nematodes in the present study. .................................................................................. 158

Figure 6-4: Anisakis Type I larvae from Selar crumenophthalmus. .............................. 161

Figure 6-5: Phylogenetic relationships between Anisakis species from the present study (*) and other Anisakis species as inferred by neighbour-joining analysis of ITS rDNA. 163

Figure 6-6: Phylogenetic relationships between Anisakis species from the present study (*) and other Anisakis species inferred using the neighbour-joining analysis of cox2 genes. ............................................................................................................................ 164

List of Tables Gastrointestinal pathogens in sheep, goats and fish in PNG

List of Tables

Table 1-1: Common gastrointestinal helminths in sheep and goats ....................... 28

Table 1-2: Previously reported gastrointestinal parasites in sheep and goats from PNG .......................................................................................................................... 30

Table 1-3: Species/genotypes of Cryptosporidium reported in fish in previous studies. ..................................................................................................................... 46

Table 1-4: Molecular techniques for characterising Cryptosporidium. ................... 52

Table 1-5: Molecular techniques for characterising Giardia ................................... 58

Table 2-1: Sampling locations and farm information for the chosen sheep and goat flocks in the present study. .............................................................................. 78

Table 2-2: Number (N) of sheep and goat samples collected in the present study. .................................................................................................................................. 83

Table 2-3: Cultured freshwater, wild freshwater and marine fish species collected in the present study. ................................................................................................ 85

Table 3-1: Gastrointestinal parasite prevalence and mean ± SD EPG counts stratified by gastrointestinal parasite type for sheep and goats. .......................... 114

Table 3-2: Gastrointestinal parasite prevalence and mean EPG counts stratified for agro-ecology, farm management and sheep breed. ............................................. 116

Table 3-3: Gastrointestinal parasite prevalence and mean ± SD EPG counts for gastrointestinal parasite type and farm type. ....................................................... 117

Table 3-4: Prevalence of trichostrongylid nematodes for sheep and goats. ......... 119

Table 3-5: Comparisons of prevalences for H. contortus in sheep among the farm types. ...................................................................................................................... 119

Table 3-6: Comparisons of prevalences for Trichostrongylus spp. in sheep among the farm types. ....................................................................................................... 120

Table 3-7: Overall prevalence of Eimeria in sheep and goats by qPCR. ................ 120

Table 4-1: Prevalence of Cryptosporidium spp. in different farm types in sheep and goats in the present study. ............................................................................. 132

Table 4-2: Prevalence of Cryptosporidium spp. in fish in the present study. ........ 133

Table 4-3: Species and subtypes of Cryptosporidium identified in sheep and goats in the present study. .............................................................................................. 134

Table 4-4: Species, genotypes and subtypes of Cryptosporidium identified in fish in the present study. .................................................................................................. 135

List of Tables Gastrointestinal pathogens in sheep, goats and fish in PNG

19

Table 4-5: Percentage genetic differences between piscine genotype 8 and other Cryptosporidium species/genotypes at the 18S rRNA and actin loci. .................... 135

Table 5-1: Prevalence of G. duodenalis in sheep and goats in different farm types in the present study. .............................................................................................. 148

Table 5-2: Comparisons of prevalences for G. duodenalis in sheep and goats between farm types. .............................................................................................. 149

Table 5-3: Prevalence of G. duodenalis in fish from the three groups of aquatic environments in the present study. ....................................................................... 149

Table 5-4: Prevalence of G. duodenalis in different fish hosts in the present study. ................................................................................................................................ 149

Table 6-1: Common zoonotic anisakids-geographic distribution, hosts, common food dishes and diseases. ...................................................................................... 156

Table 6-2: Prevalence of anisakid larvae in different fish hosts in the present study as determined by PCR. ........................................................................................... 160

Table 6-3: Percentage similarity of the Anisakis species analysed in the present study and their closest relatives. ........................................................................... 162

Table 7-1: Prevalence of Chlamydia in sheep and goats in the present study. ..... 172

Table 7-2: Comparisons of prevalences for Chlamydia in sheep and goats between farm types. ............................................................................................................. 172

List of Abbreviations Gastrointestinal pathogens in sheep, goats and fish in PNG

List of Abbreviations

18S rRNA 18S ribosomal RNA

bg beta (β) giardin

BLAST basic local alignment search tool

CFT complement fixation test

CI confidence interval

Ct threshold cycle

cox2 cytochrome c oxidase subunit II

DAL Department of Agriculture and Livestock

DMSO dimethyl sulfoxide

dNTPs deoxynucleotide triphosphates

EB elementary body

EPG eggs per gram

EHP Eastern Highlands Province

EAE enzootic abortion of ewes

ELISA enzyme-linked immunosorbent assay

FECRT faecal egg count reduction test

FET Fisher’s exact test

gdh glutamate dehydrogenase

GI gastrointestinal parasites

gp60 60 kDA glycoprotein

IAC internal amplification control

IFA immunofluorescent assay

ITS internal transcribed spacer

ML maximum likelihood

MP maximum parsimony

mt-DNA mitochondrial DNA

NARI National Agriculture Research Institute

NJ neighbour joining

OEA ovine enzootic abortion

PCR polymerase chain reaction

PNG Papua New Guinea

qPCR quantitative polymerase chain reaction

RB reticulate body

rRNA ribosomal ribonucleic acid

List of Abbreviations Gastrointestinal pathogens in sheep, goats and fish in PNG

21

SSU rRNA small subunit of nuclear ribosomal RNA

Syn. synonym

tpi triose phosphate isomerase

WHP Western Highlands Province

Candidate Contribution Gastrointestinal pathogens in sheep, goats and fish in PNG

Statement of candidate contribution

Chapter Title Contribution

2 Materials and Methods M Koinari: 80 %

U Ryan: 10 %

W Ayalew: 5 %

R Yang: 5 %

3 Prevalence and infection levels of M Koinari: 80 %

gastrointestinal parasites in sheep and A Lymbery: 10 %

goats in PNG. U Ryan: 5 %

S Karl: 5 %

4 Molecular characterisation of M Koinari: 75 %

Cryptosporidium in sheep, goats and fish U Ryan: 10 %

from PNG A Lymbery: 5 %

S Karl: 5 %

J. Ng Hublin: 5 %

5 Prevalence of Giardia duodenalis from. M Koinari: 85 %

sheep, goats and fish from PNG U Ryan: 5 %

A Lymbery: 5 %

R Yang: 5 %

6 Morphological and molecular M Koinari: 80 %

characterisation of anisakid nematodes U Ryan: 5 %

in fish from PNG. A Lymbery: 5 %

S Karl: 5 %

R Elliot: 5 %

7 Prevalence of Chlamydia from sheep M Koinari: 85 %

and goats from PNG. U Ryan: 5 %

A Lymbery: 5 %

R Yang: 5 %

Chapter 1

1. General Introduction

Chapter 1 Gastrointestinal pathogens in sheep, goats and fish in PNG

1.1 Background

1.1.1 Papua New Guinea: sheep, goats and fish.

Papua New Guinea (PNG) lies north of Australia between latitudes 1° and 12°

south and longitudes 140° and 160° east. It consists of a mainland and a number of

islands of varying sizes. The centre of the mainland consists of a series of mountain

ranges with thickly frosted mountains in the centre, lowlands along the coast and

swampy alluvial plains in the southwest. The climate in the coastal areas is generally

hot and humid, with average temperatures ranging from 25 - 35 °C, while the valleys of

the central highlands are warm in the daytime but cooler in the night (18 - 20 °C) and

at the higher altitudes, frost occurs during certain times of the year. The rainfall varies

from 1000 mm to over 4000 mm (Bourke, 2010).

PNG’s population in 2012 was approximately 6.3 million with an annual growth

rate of 2.7 % (2011 census) and the majority (87 %) live in rural areas (CIA, 2012). As in

other developing countries, agriculture dominates the economy in rural villages. About

50 % of the agricultural output comes from production of food items, of which

livestock contributes about 13 % (Quartermain, 2004a). Livestock production has not

increased in the recent past, but meat consumption is increasing steadily and is

predicted to increase at 5 % per annum commensurate with the growth of the

population (Quartermain, 2004a). The shortfall in local supply is met with importation

of meat, especially, sheep (100 %) and beef (80 %), with the cost of imported livestock

products exceeding US$50 million (Quartermain, 2004a). In 1998, imports of sheep

meat and beef reached 41, 800 tons (shipped weight), involving an outlay of around

PGK130 million (Igua, 2001). Thus, sheep account for 38 % of meat consumption,

poultry meat 39 % and beef 17 % (Igua, 2001). In order to reduce its reliance on

imported sheep meat, the PNG government has attempted to increase production of

small ruminants and also to promote self-sufficiency (Vincent and Low, 2000; Igua,

2001).

The country is self-sufficient with poultry and pig products, which are produced

in either commercial or subsistence systems (Quartermain, 2004a). There are,

however, few commercial cattle farms and no commercial sheep and goats farms.


25

Sheep and goats are raised in government institutions (semi-commercial) or more

commonly in subsistence systems, where animals are kept primarily for household

consumption, but any animals not used for household consumption are sold for cash

or exchanged for other livestock or crops produced. In subsistence production

systems, the animals graze or scavenge unattended and are housed at night.

There are an estimated 20, 000 goats and 10, 000 sheep in PNG (Quartermain,

2004b). Initially, tropical sheep from Southeast Asia and a variety of dairy goats were

introduced by colonial administrators and post-colonial settlers in the 1800s

(Quartermain, 2004a). Many of the tropical sheep introduced were lost during the

Second World War, but a flock was gathered by the government livestock officers at

Erap in the 1970s for the purpose of breeding and distribution to smallholder farmers.

Those sheep then became known as Priangan, although they do not resemble the

Indonesian Priangan sheep, but instead resemble the Javanese thin-tailed sheep

(Quartermain, 2004a). In addition, the government attempted to farm temperate

sheep in the highlands (at Aiyura and Nondugal), but high mortality and low fertility

made that venture unsuccessful. In the 1980s, a research and breeding station for

sheep was established in Menifo in the Eastern Highlands Province (EHP) by the PNG

Department of Agriculture and Livestock (DAL), with technical assistance from New

Zealand (Quartermain, 2004a). The aims of the station were to develop suitable sheep

breeds that would perform well in the highlands of PNG, to increase sheep numbers

rapidly and to supply other provincial sheep centres for distribution to smallholder

farmers, especially, in the highlands provinces. The temperate sheep (Corriedale and

Perendale) were imported from New Zealand and crossed with PNG Priangan sheep,

which resulted in a new breed called Highland Halfbred (Quartermain, 2004b). The

Highlands Halfbred now dominates the cooler highlands areas while the PNG Priangan

sheep are raised on warm lowland areas.

Of the various dairy goats introduced during the early colonial period, few

survived in the villages. From those surviving goats, a flock was gathered at the PNG

University of Technology and on DAL stations at Erap and Benabena in 1975; those

goats are now referred to as PNG genotype goats (Quartermain, 2004a). Since then,


26

there were small introductions of goats derived from Australian and New Zealand feral

populations to reinforce the highland flocks (Quartermain, 2004a).

Apart from livestock, fish is one of the major economic sources in PNG (Smith,

2007). Many rural villagers living along the coast and major rivers earn their income by

selling fish at local markets. Because of the nutritional value of the fish, recent efforts

of national and international collaborators have encouraged the development of

aquaculture in PNG (Smith, 2007). Freshwater fish farming began in the 1960s with the

introduction of carp (Cyprinus carpio) and rainbow trout (Oncorhynchus mykiss) and

later in 2002, a genetically improved farmed strain of tilapia (Nile tilapia; Oreochromis

niloticus) was introduced (Smith, 2007). Several major hatcheries were set up,

including the Highlands Aquaculture Development Centre (HAQDEC) and Erap

Aquaculture Centre (EAC) to distribute fingerlings to smallholder farmers throughout

the country (Smith, 2007). HAQDEC produces common carp, Nile tilapia and to a lesser

extent, Java carp (Puntius gonionotus). EAC produces tilapia fingerlings. Trout farmers

obtain their stock from Lake Pindi hatchery or from other smallholder hatcheries and

wild caught trout. There are over 300 smallholder inland fish farms in the country

(Smith, 2007). There is very little known about diseases or pathogens of fish in PNG.

1.1.2 The impact of gastrointestinal parasites on sheep and goats

Parasites are commonly found in sheep and goats and they cause diseases of

major socio-economic importance worldwide. Infections can result in irreversible

damage or even death to the infected sheep and goats (Hepworth et al., 2010). In

addition, animals which are overburdened with parasites can be hindered in their

reproductive performance, experience reduced growth rates and become less

productive overall whether their purpose is meat, fibre or milk (Hepworth et al., 2010).

Furthermore, parasites can cause considerable financial loss. For example, the annual

cost associated with parasitic diseases in sheep and cattle in Australia has been

estimated at more than 1 billion dollars (McLeod, 1995; Sackett and Holmes, 2006). In

tropical and subtropical areas, parasitic nematodes are recognised as a limiting factor

to the expansion and improvement of smallholder production of small ruminants (Al-

Quaisy et al., 1987). In PNG, limiting factors associated with production of sheep and


27

goats are generally attributed to lack of management skills and parasitic diseases,

however, studies assessing the economic cost of endemic diseases on profitability of

cattle, sheep or goat producers are lacking.

1.1.3 Gastrointestinal pathogens of sheep and goats

Most species of nematodes and protozoa cause parasitic gastritis and enteritis

in sheep and goats. The most pathogenic (disease causing) nematodes are the stomach

worms (Haemonchus contortus, Teladorsagia (Ostertagia) circumcincta, and

Trichostrongylus axei) and intestinal worms (Trichostrongylus colubriformis,

Trichostrongylus vitrinus, Nematodirus sp., Bunostomum trigonocephalum, and

Oesophagostomum columbianum) (Table 1-1) (Lichtenfels and Hoberg, 1993; Aiello et

al., 2012b). Cooperia curticei, Strongyloides papillosus, Trichuris ovis, and Charbertia

ovina also may be pathogenic in sheep (Table 1-1) (Lichtenfels and Hoberg, 1993; Aiello

et al., 2012b). In addition, lung worms (Dictyocaulus spp. or Muellerius capillaries), liver

flukes (Fasciola hepatica) and cestodes (Moniezia expansia) are also pathogenic to

small ruminants (Villarroel, 2013).

Typical signs of gastrointestinal helminth infections include weight loss,

diarrhoea, rough hair coat, depression, weakness, fever, anaemia, and bottle jaw

(Villarroel, 2013). Parasitic nematodes of livestock are controlled mainly through

anthelmintic treatment. In some areas, optimally-timed (strategic) treatments, are

used, however, this type of control is expensive and in most cases only partially

effective (Gasser et al., 2008). Resistance to anthelmintics has emerged as a major

economic problem (Woodgate and Besier, 2010), despite the development of new

drugs (Kaminsky et al., 2008).

Infection with Eimeria is one of the most economically important diseases of

sheep and goats due to disease (diarrhoea) but also because of subclinical infections

(especially, poor weight gain) (Chartier and Paraud, 2012). The disease caused by

Eimeria is called coccidiosis, which is usually due to acute invasion and destruction of

intestinal mucosa (Aiello et al., 2012a). Eimeria infections can be treated with

coccidiostats (Villarroel, 2013).

Table 1-1: Common gastrointestinal helminths in sheep and goats (Aiello et al., 2012b and Lichtenfels and Hoberg, 1993).

Parasite Superfamily Distribution Organ Damage Clinical signs

Haemonchus contortus Trichostrongyloidea Tropical, subtropical and summer rainfall.

Abomasum Invade tissue, suck blood Submandibular oedema (bottle jaw), anaemia, poor condition

Teladorsagia circumcincta

Trichostrongyloidea Subtropical and winter rainfall

Abomasum Hypertrophy of gastric mucosa

Submandibular oedema, diarrhoea, emaciation

Trichostrongylus spp. Trichostrongyloidea Tropical, subtropical and winter rainfall.

Abomasum, small intestine

Localised necrosis, erode mucosa, minor haemorrhages

Anorexia, diarrhoea, weight loss, depressed growth

Nematodirus spp. Trichostrongyloidea Worldwide Small intestine Disrupts mucus membrane

Unthriftiness, diarrhoea, dehydration

Bunostomum trigocephalum

Ancylostomatidae Worldwide Small intestine Suck blood, penetrate skin Dermatitis, local lesions, diarrhoea, anaemia

Cooperia curticei Trichostrongyloidea Worldwide Small intestine Disrupts mucus membrane

Diarrhoea, anorexia, emaciation

Strongyloides papillosus

Strongyloidae Worldwide Small intestine Suck blood, penetrate skin Dermatitis, local lesions, diarrhoea, anaemia

Trichuris ovis Trichuridae Worldwide Caecum, colon Disrupts mucus membrane

Caecal mucosa oedema, diarrhoea, anaemia

Oesophagostomum columbianum

Strongyloidae Worldwide Caecum, colon Nodules with small abscesses

Diarrhoea, weakness, loss weight

Charbertia ovina Strongyloidae Worldwide Caecum, colon Severe damage to mucosa Unthrifty, soft faeces with streaks of blood

http://en.wikipedia.org/w/index.php?title=Strongyloididae&action=edit&redlink=1


Cryptosporidium and Giardia are important intestinal protozoa, which cause

acute or chronic enteric disease in young or immunosuppressed animals. The clinical

symptoms of Cryptosporidium infections in lambs and goat kids are diarrhoea, weight

loss and mortality (de Graaf et al., 1999), while Giardia infections can result in

diarrhoea and impaired weight gain (Aloisio et al., 2006). For both cryptosporidiosis

and giardiasis, the disease is usually mild and self-limited, and supportive care,

primarily hydration, is important (Foreyt, 1990). Only one drug, nitazonaxide, can be

used to treat diarrhoea caused by Cryptosporidium in humans (White, 2004; Fox and

Saravolatz, 2005) and several drugs (metronidazole, tinidazole and nitazoxanide) can

be used to treat Giardia infection in humans (Escobedo and Cimerman, 2007). In

livestock, the following drugs have been used: halofuginone and paromomycin for

treatment of cryptosporidiosis (Fayer and Ellis, 1993; Johnson et al., 2000), and

benzimidazoles (fenbendazole, mebendazole and albendazole) for treatment of

giardiasis (O'Handley et al., 1997; Geurden et al., 2006a; Geurden et al., 2006b;

Geurden et al., 2010a). Control involves strict sanitation and quarantining of infected

animals. In addition to their veterinary importance, Cryptosporidium and Giardia are

well known as zoonotic pathogens and small ruminants have long been considered as

reservoirs for human infections (Geurden et al., 2008b).

Members of the genus Chlamydia cause disease in humans and animals and

most are zoonotic (Everett et al., 1999; Vlahovic et al., 2006). Two species of

Chlamydia have been reported to cause infections in sheep, Chlamydia abortus and

Chlamydia pecorum (Berri et al., 2009; Lenzko et al., 2011). Both are known to cause

abortions in sheep with C. pecorum also known to cause enteritis in sheep (Berri et al.,

2009). Chlamydia abortus, which is the causative agent of enzootic abortion of ewes

(EAE), is also potentially zoonotic (Longbottom and Coulter, 2003; Baud et al., 2008;

Rodolakis and Yousef Mohamad, 2010).

In PNG, previous studies have found a variety of gastrointestinal parasites

including cestodes, nematodes and Eimeria species in sheep and goats (Table 1-2)

(Anderson, 1960; Egerton and Rothwell, 1964; Varghese and Yayabu, 1985; Asiba, 1987;

Owen, 1988, 1989, 1998; Quartermain, 2004b). In the lowlands, H. contortus,

Trichostrongylus spp., Strongyloides, Oesophagostomum and Cooperia were found to

http://europepmc.org/abstract/MED/2245367/?whatizit_url_Species=http://www.ncbi.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=33208&lvl=0


30

be dominant, while in the highlands, H. contortus and T. colubriformis were dominant

(Quartermain, 2004b).

Table 1-2: Previously reported gastrointestinal parasites in sheep and goats from PNG (Quartermain, 2004b). * = the presence of a particular parasite in the sheep and goat.

Gastrointestinal Parasite Sheep Goat References

Cestoda

Moniezia expansia * * Anderson, 1960; Egerton and Rothwell, 1964.

Nematoda

Bunostomum trigonocephalum * * Anderson, 1960; Egerton and Rothwell, 1964.

Cooperia curticei * Owen, 1988; Owen, 1998.

Cooperia sp. * * Owen, 1988; Owen, 1998.

Haemonchus contortus * * Anderson, 1960; Egerton and Rothwell, 1964.

Mecistocirrus sp. * Asiba, 1987.

Nematodirus sp. * * Anderson, 1960; Egerton and Rothwell, 1964.

Nematodirus spathiger * Anderson, 1960; Egerton and Rothwell, 1964.

Oesphagostomum venulosum * Anderson, 1960; Egerton and Rothwell, 1964.

Oesphagostomum asperum * Anderson, 1960; Egerton and Rothwell, 1964.

Oesphagostomum columbianum * * Anderson, 1960; Egerton and Rothwell, 1964.

Strongyloides papillosus * * Anderson, 1960; Egerton and Rothwell, 1964.

Trichostrongylus axei * Owen, 1988; Owen, 1998.

Trichostrongylus colubriformis * * Anderson, 1960; Egerton and Rothwell, 1964.

Trichuris globulosa * * Anderson, 1960; Egerton and Rothwell, 1964.

Trichuris ovis * * Owen, 1988; Owen, 1998.

Coccidia

Eimeria ahsata * Varghese and Yayabu, 1985.

Eimeria crandallis * Varghese and Yayabu, 1985.

Eimeria faurei * Varghese and Yayabu, 1985.

Eimeria granulosa * Varghese and Yayabu, 1985.

Eimeria intricata * Varghese and Yayabu, 1985.

Eimeria ovina * Varghese and Yayabu, 1985.

Eimeria ovinoidalis * Varghese and Yayabu, 1985.

Eimeria parva * Varghese and Yayabu, 1985.

1.1.4 Gastrointestinal parasites of fish

All of the major groups of animal parasites are found in fish and healthy, wild

fish often carry heavy parasite burdens. Protozoa such as internal flagellates and

coccidia cause anorexia, weight loss and mortality; cestodes cause sterility;

acanthocephalids cause enteritis and mortality and nematodes such as Capillaria,


31

Camillanus, Philometra, Eustrongylides cause weight loss and pot belly (Aiello et al.,

2012c). Worms are often visualised protruding from the anus of the infected fish or

within the viscera of the fish without causing any symptoms in fish (Aiello et al.,

2012c). In farmed fish, poor health management practices, such as high stocking

density and inadequate sanitation has led to a high incidence of parasitic diseases

(Seng et al., 2006). Mass mortalities of juvenile fish due to protozoan and metazoan

parasites are frequently reported (Burkholder et al., 1995; Scholz, 1999). The farm

production loss in 1990 to fish diseases in a variety of fish in both freshwater pond

culture and marine cage culture in developing Asian countries has been estimated to

cost US$1.36 million (ADB/NACA, 1991). In PNG, there is a lack of information on the

effect of disease on fish in cultured systems.

While numerous parasites have been reported in fish, only few are capable of

infecting people. The most important are anisakid nematodes, cestodes and

trematodes, and parasitic infections are associated with the consumption of raw or

undercooked seafood (Chai et al., 2005). Species of the anisakids, particularly, Anisakis

simplex and Pseudoterranova decipiens cause anisakidosis in humans, which is

characterised by abdominal pain, nausea, vomiting and allergy (Bouree et al., 1995;

Hochberg and Hamer, 2010). There has been a marked increase in the prevalence of

anisakidosis throughout the world in the last thirty years, due in part to the growing

consumption of raw or lightly cooked seafood (Lymbery and Cheah, 2007). In addition,

Cryptosporidium and Giardia which are known to cause diarrhoea in humans have also

been identified in fish (further details are provided in subsections 1.4.1 and 1.5.1).

1.2 Gastrointestinal parasitic nematodes of sheep and goats

1.2.1 Distribution and taxonomy

The members of the superfamily Trichostrongyloidea are principal parasites of

ruminants. In tropical and subtropical regions, the most economically important

parasitic gastrointestinal nematode of sheep and goats is the abomasal worm

Haemonchus contortus (Waller and Chandrawathani, 2005). Of significance are also


32

Teladorsagia (Ostertagia) circumcincta and Trichostrongylus spp. (O'Connor et al.,

2006).

Species belonging to the genus Haemonchus (barber’s pole worm) are the

major abomasal pathogens of ruminants and they have a global distribution (O'Connor

et al., 2006). Haemonchus contortus was first described in 1803 by Karl Rudolphi

(Soulsby, 1982). Twelve species are described within the genus Haemonchus, of which

H. contortus, H. placei and H. similis are found in the abomasa of domesticated

ruminants (Hochberg and Hamer, 2010). Haemonchus contortus is mainly a parasite of

sheep and goats (Love and Hutchinson, 2003). Its principal pathogenic features are its

fourth-stage larvae and adults that feed on host blood and high parasite numbers can

cause fatal anaemia (Love and Hutchinson, 2003).

Species belonging to the genus Teladorsagia (Ostertagia) (small brown stomach

worm) are found in the abomasum of ruminants throughout the world. There are six

described species in this genus of which two, Teladorsagia (Ostertagia) circumcincta

and T. trifurcata, are found in sheep and goats (Lichtenfels et al., 1997). Heavy

infections, if accompanied by Trichostrongylus spp., can cause profuse scouring, ill

thrift and possibly deaths in sheep and goats (Love and Hutchinson, 2003).

Species of the genus Trichostrongylus (black scour worms) are parasites of

birds, ruminants and rodents and are distributed worldwide (Anderson, 2000). There

are 43 known species in this genus of which three species Trichostrongylus axei,

T. colubriformis, and T. vitrinus are commonly found in sheep and goats (Lichtenfels et

al., 1997; Love and Hutchinson, 2003; Rossin et al., 2006). Trichostrongylus axei infects

the abomasum, while T. colubriformis and T. vitrinus infect the intestines and occur in

mixed infections with Ostertagia and produce similar clinical signs (inappetence,

weight loss and scouring) (Love and Hutchinson, 2003).

The overall prevalence rates of gastrointestinal trichostrongylid infections

reported in sheep and goats from tropical and sub-tropical areas are usually very high

(> 20 %) (Dorny et al., 1995; Cheah and Rajamanickam, 1997; Faizal and Rajapakse,


33

2001; Maichomo et al., 2004; Regassa et al., 2006; Tariq et al., 2008; Gadahi et al.,

2009; Abebe et al., 2011; Dagnachew et al., 2011).

1.2.2 Life cycle and morphology

Most trichostrongyles have a direct life cycle, which is composed of preparasitic

(free living) and parasitic stages (Fig. 1-1.) (Gasser et al., 2008). Female worms inside

their host produce relatively large numbers of eggs, which are excreted in the faeces

into the external environment. The first-stage larva (L1) develops inside the egg, which

hatches (within 1-2 days, depending on environmental conditions) and develops into

second-stage larva (L2). Both L1 and L2 larvae feed on bacteria and other

microorganisms in the external environment (faeces). L2 in turn moults into the

ensheathed third-stage larva (L3). Sheep and goats become infected when they graze

and eat grasses containing infective L3 larvae. After L3 is ingested by the animal and

passes through the stomach (s), it exsheaths (xL3) and (after a tissue phase) develops

through to fourth-stage larva (L4) and subsequently into the adult at the predilection

site in the alimentary tract (Gasser et al., 2008). The maturation of the worms takes

place on the surface of the mucous membrane. The male and female adults mate and

live in the abomasum or small intestine. Worms can be found attached to the mucosa

or free in the lumen.

The length of time that infective larvae can survive on the pasture is important

for control, especially pasture management programs (Zajac, 2006). The length of time

required for development to the L3 stage varies with temperature and moisture. The

minimum length of time required for the development of H. contortus larvae is about 3

to 4 days (Zajac, 2006). At its early life cycle stages (egg to L3), H. contortus is highly

susceptible to cold and desiccation, high mortality occurs below 10 °C and L3 larvae

require warmth and moisture for transmission (O'Connor et al., 2006). The free living

stages of Trichostrongylus colubriformis however, have intermediate susceptibility to

cold and desiccation with high mortality occurring below 5 °C; survival of L3 larvae

require cool or warm moist weather (O'Connor et al., 2006). In addition, the free living

stages of Teladorsagia circumcincta have low susceptibility to cold and desiccation,

hatching below 5 °C; L3 stages require cool, moist weather and sub-freezing winters


34

(O'Connor et al., 2006). The free living stages of Trichostrongylus spp. can develop at

lower temperatures and the larvae may remain dormant until conditions become

favourable for transmission (Aiello et al., 2012b).

The L4 larvae of Haemonchus and Teladorsagia may undergo a period of

arrested development (hypobiosis) in the host, which can be influenced by conditions

in the environment which are unfavourable for development and the survival of eggs

and larvae or immune status of the host (Eysker, 1997).

Figure 1-1: Generalised life cycle of parasitic nematodes (order Strongylida) of the alimentary tract of livestock. (Image from Gasser et al., 2008). Adult female nematodes within the gastrointestinal tract of host animals produce eggs, which are passed out in the faeces. The larvae hatch from the eggs and develop through larval stages L1, L2 and L3 of development. Sheep and goats become infected when they graze and eat grasses containing infective L3 larvae. After the L3 is ingested by the animal and passes through the stomach (s), it exsheaths (xL3) and (after a tissue phase) develops through to fourth-stage (L4) and subsequently into the adult. Specific features of the development of such strongylid nematodes include embryogenesis (E), sexual differentiation (S), sexual reproduction (R), microbial feeding phase (F1), feeding phase inside the alimentary tract (F2), rapid growth phases (G) and the potential to undergo conditional arrested development ( = hypobiosis)(L4*).


35

Female H. contortus worms are 18 - 30 mm long and are easily recognised by

the ‘barbers pole’ appearance of the white ovaries and uteri twisting for the length of

the worm around a red blood-filled intestine, while the males are 10 - 20 mm long and

uniformly reddish-brown (Love and Hutchinson, 2003). Teladorsagia are small

brownish worms, of which adult females measure 8 - 12 mm and males 7 - 9 mm (Love

and Hutchinson, 2003). Trichostrongylus axei are very small, slender, hair-like and

reddish-brown worms (females are 5 - 8 mm long and males 4 - 7 mm long) (Love and

Hutchinson, 2003). Intestinal Trichostrongylus spp. (T. columbriformis and T. vitrines)

are small, hair-like reddish brown worms (females 6 - 8 mm and males 6 - 7 mm long)

(Love and Hutchinson, 2003).

1.2.3 Pathogenicity and clinical signs

Haemonchus contortus has a tooth or lancet in its poorly developed oral cavity

to perforate the gastric mucosa and suck blood (Angulo-Cubillan et al., 2007). Both the

L4 larvae and adult H. contortus cause punctiform haemorrhages at feeding sites on

the abomasal mucosa, which may be oedematous (Love and Hutchinson, 2003).

Clinical signs of haemonchosis include anaemia, digestion-absorption syndromes and

weight loss but no diarrhoea (Aiello et al., 2012b).

There are two types of Teladorsagia (Ostertagia) infections in ruminants. In

type I ostertagiosis, which results from recent infection, most worms present are

adults. As the larvae develop and emerge from gastric glands, hyperplasia of gastric

epithelium may cause enlargement and coalescing of nodules, thus mucosal

congestion and oedema is evident with thickening of abomasal folds (Love and

Hutchinson, 2003). Clinical signs include inappetence, scours and rapid weight loss

(Love and Hutchinson, 2003). Type II ostertagiosis, consists of adult worms arising from

simultaneous maturation of many inhibited early L4 larvae, with glandular hyperplasia,

loss of gastric structure, abomasitis, impairment of protein digestion, and leakage of

plasma proteins, especially albumin, into the gut lumen (Love and Hutchinson, 2003).

The mucosa appears thickened and oedematous.


36

In Trichostrongylus axei infections, the mucosa of the abomasum may show

congestion and superficial erosions, which are sometimes covered with a

fibrinonecrotic exudate. Intestinal Trichostrongylus spp. (T. columbriformis and

T. vitrines) larvae burrowing in the crypts of intestinal mucosa result in damage of the

mucosa and villus atrophy. The clinical signs of intestinal Trichostrongylus spp. are

similar to those of abomasal Teladorsagia, which include anorexia, persistent

diarrhoea, weight loss, impaired digestion and malabsorption, and protein loss (Love

and Hutchinson, 2003).

1.2.4 Diagnosis

Techniques presently used for the diagnosis of strongylid nematodes infecting

livestock can be presumptive or based on laboratory aids including parasitological,

serological/immunological and DNA-based approaches. Presumptive diagnosis based

on clinical signs including diarrhoea, anaemia, mortality or decreased fertility, reduced

body weight, meat, milk and/or wool production in the host alone is unreliable, can be

complicated in cases of mixed species infections and does not specifically detect or

identify the causative agent (Gasser et al., 2008).

A diagnostic tool called FAffa MAlan CHArt (FAMACHA) method is sometimes

used, in which only certain sheep or goats in the flock are selected for treatment

against H. contortus (van Wyk and Bath, 2002). FAMACHA is a standard colour chart

that is used for assessing or scoring the level of anaemia by comparison of the colour

of the inner lower eyelid and then deciding which individuals in a flock should be

selectively treated for haemonchosis (van Wyk and Bath, 2002).

Serological and immunological (e.g., coproantigen detection) approaches have

been assessed for the specific diagnosis of nematode infections, however cross-

reactivity using antigens of related parasites can occur, reducing the specificity of

these methods as a diagnostic test (Johnson et al., 1996; Larsen et al., 1997; Johnson

et al., 2004).

Parasitological approaches involve the identification of strongylid nematodes

(at any developmental stage) on the basis of morphological characters. This approach


37

includes direct faecal smears, faecal flotations and post-mortem. A direct faecal smear

can be examined to indicate the presence of parasite eggs. However, faecal flotations

techniques are the primary laboratory test used for detection of nematode eggs and

for determination of the parasite load of an animal by quantification of the worm egg

per gram (EPG) of faeces. Faecal flotation techniques involve separation and

concentration of eggs from faecal samples and identification based on egg morphology

using light microscope (Dryden et al., 2005). The drawback of faecal worm egg counts

is that EPG does not represent an accurate indication of the number of adult worms

present and specific identification of strongylid nematode eggs is impractical due to

close similarities in the morphology of ova (Gasser et al., 2008). EPG counts can be

negative or low in the presence of large numbers of immature and adults worms,

which are suppressed by host immune reactions or recent anthelmintic treatment

(Aiello et al., 2012b). Also, variations in the egg-producing capability of different

worms (significantly lower for Teladorsagia and Trichostrongylus than Haemonchus)

may misrepresent the true worm burden (Aiello et al., 2012b). To achieve genus-level

identification, L3 larvae can be produced from eggs in the faeces using the method of

larval culture. For these, faecal samples are processed and incubated to hatch eggs and

the resulting larva identified (Corner and Bagust, 1993). The disadvantage of larval

cultures is that the yields are never 100 % (Eysker and Ploeger, 2000); it is unreliable

for establishing the relative abundance of eggs from different species present in the

faecal sample as their survival rates and development can vary, depending on culture

conditions (Dobson et al., 1992). Also, it is time-consuming, (requiring 1-2 weeks for

eggs to hatch and larvae to develop to L3 stage, depending on conditions) and requires

an experienced microscopist to identify and distinguish L3 larvae (Gasser et al., 2008).

Routine post-mortem examinations can provide valuable data about the status of the

rest of the herd or flock (Aiello et al., 2012b). It can be performed on “traces”

(parasite-naïve fully susceptible animals that graze with the herd/flock for a short

period) or selecting sentinel animals from the herd/flock (Eysker and Ploeger, 2000).

The faecal egg count reduction test (FECRT) is used to assess the efficacy of

anthelmintic against gastrointestinal strongylids, but it is not suitable for confirmation

of clinical diagnosis (Eysker and Ploeger, 2000).


38

A wide range of molecular approaches, based on polymerase chain reaction

(PCR) techniques, are used for the specific diagnosis of nematodes including restriction

fragment length polymorphism (RFLP), mutation scanning, PCR and DNA sequencing

(Gasser et al., 2008). More recently, molecular methods including quantitative PCR

(qPCR) for the genus- or species-specific diagnosis of strongylid infections in livestock

have been developed (Zarlenga et al., 2001; Siedek et al., 2006; Harmon et al., 2007a;

Harmon et al., 2007b; Bott et al., 2009; Learmount et al., 2009; von Samson-

Himmelstjerna et al., 2009; Roeber et al., 2011; Sweeny et al., 2011a; Burgess et al.,

2012; Roeber et al., 2012a; Roeber et al., 2012b; Demeler et al., 2013; McNally et al.,

2013). Some of these studies have used copro-culture of larvae or eggs purified from

faecal samples and then used PCR analysis to determine the presence/absence of

selected strongylid species (Zarlenga et al., 2001; von Samson-Himmelstjerna et al.,

2002; Harmon et al., 2006; Siedek et al., 2006; Harmon et al., 2007b; Bott et al., 2009;

Burgess et al., 2012). However, the time and labour required for egg or larvae

purification is time-consuming and is subject to the limitations described above.

1.2.5 Treatment and control

Clinically affected animals due to infections with parasitic worms can be

treated with drugs (chemotherapy agents), commonly known as anthelmintics.

Anthelmintics either kill egg-laying adults, or kill larvae before they become adults and

become capable of laying eggs. Three families of anthelmintic drugs; (i) benzimidazoles

(fenbendazole and albendazole), (ii) nicotinic agonist consisting of imidazothiaoles and

tetrahydropyrimidines (levamisole, pyrantel and morantel), and (iii) macrocylic

lactones comprising avermectins (ivermectin, doramectin and eprinomectin) and

milbemycins (moxidectin) are available for deworming small ruminants (Schoenian,

2010).

The main goal in attempting to control gastrointestinal parasites is to break the

life cycle, which can be done in a variety of ways including the use of anthelmintics,

animal management and pasture management. Anthelmintics are predominantly used

to control internal parasitic worms and they can be used to reduce pasture

contamination. It is recommended that after treating animals for parasites, they


39

should be left in the original pasture for a couple of days before rotating or keep them

on a dry lot for 12 - 24 h after deworming, to ensure the eggs and larvae that survived

the anthelmintics are not deposited on safe pasture (Hepworth et al., 2010). In some

areas, optimally-timed (strategic) treatments, are used, however, this type of control is

expensive and in most cases are partially effective (Gasser et al., 2008). Anthelmintic

drugs have to be used sparingly to control parasites in sheep and goats as frequent use

may enable the worms to become resistant to drugs and also they are costly.

Resistance to anthelmintics has emerged as a major economic problem in many parts

of the world (Wolstenholme et al., 2004; Coles, 2006; Woodgate and Besier, 2010).

Pasture management is a non-chemical way to control nematodes. Pastures are

allowed enough time to rest so that lower numbers of larvae are infective and will not

be a problem to the grazing animal (Hepworth et al., 2010). However, good pasture

management cannot entirely eliminate the parasite problem and therefore good

rotational grazing techniques combined with an anthelmintic program are required;

the success of which will depend on the level of anthelmintic resistance in a particular

flock (Hepworth et al., 2010).

1.3 Eimeria


Apicomplexan parasites that belong to the genus Eimeria, infect a wide range

of vertebrate hosts, worldwide (McDonald and Shirley, 2009). The taxonomy of species

in this genus is controversial due to phenotypic characters traditionally used for the

classification of eimeriid coccidia (including the morphology of available parasite

stages and host specificity) (Tenter et al., 2002). Eimeria spp. are thought to be host-

specific and are not transmitted from sheep to goats (McDougald, 1979). In temperate

areas, twelve species have been reported in sheep; E. ovinoidalis and E. weybridgensis

(syn. E. crandallis) are most prevalent, followed by, E. ahsata, E. bakuensis, E. faurei, E.

granulosa, E. intricata, E. marsica, E. parva and E. pallida (Reeg et al., 2005; Dittmar et

al. 2010). Nine species are commonly reported in goats with E. ninakohlyakimovae, E.

arloingi, and E. alijevi being the most frequent species, followed by E. caprina, E.


40

christenseni, E. jolchijevi, E. caprovina, E. hirci and E. apsheronica (Norton, 1986;

Koudela and Bokova, 1998; Balicka-Ramisz, 1999; Harper and Penzhorn, 1999; Ruiz et

al., 2006; Chartier and Paraud, 2012). Eimeria have been found in sheep and/or goats

in tropical and subtropical areas including PNG (Varghese and Yayabu, 1985), Senegal

(Vercruysse, 1982), Ghana (Nuvor et al., 1998), Nigeria (Woji et al., 1994), Kenya

(Kanyari, 1993; Maingi and Munyua, 1994), Zimbabwe (Chhabra and Pandey, 1991), Sri

Lanka (Faizal and Rajapakse, 2001), Turkey (Abdurrahman, 2007) and Brazil

(Cavalcante et al., 2011). The prevalence of Eimeria can reach up to > 85 % in both

sheep and goats (Wang et al., 2010a).

Of all the Eimeria species, the most pathogenic in sheep are E. ovinoidalis and

E. crandallis (usually in 1-6 month old lambs) with E. ovina being less pathogenic (Aiello

et al., 2012c). In goats, E. arloingi, E. christenseni and E. ovinoidalis are highly

pathogenic, especially, in kids (Aiello et al., 2012c).


Eimeria has a complex life cycle (which includes three stages, sporogony,

schizogony/merogony and gamogony) and requires only one host (Fig. 1-2). Sporogony

is the maturation of the oocyst, which occurs outside the host, while schizogony (the

asexual proliferation) and gamogony (sexual multiplication) are parasitic endogenous

phases that occur within the host (Soulsby, 1982). The infected host excretes

unsporulated oocysts (not infective) into the environment with the faeces. After 2 - 7

days, depending on the species of Eimeria and the environmental conditions (such as

moisture, oxygen and temperature), the oocysts sporulate (sporogony) (Chartier and

Paraud, 2012).

Once the sporulated oocyst is ingested by a suitable host, the oocyst excyst and

releases sporozoites in the intestine. Each sporozoite then penetrates an epithelial cell

of the small intestine, where it transforms into a schizont (Chartier and Paraud, 2012).

The schizont undergoes schizogony to produce merozoites. The merozoites released

from the schizont can either re-initiate asexual reproduction or develop into sexual

stages called micro (male) and macro (female) gametocytes (Chartier and Paraud,

2012).


41

Figure 1-2: Life cycle of Eimeria species. Top (1): Schematic representation of the life cycle of Eimeria in an infected mammal. Once oocysts are ingested by a host (a), they release sporozoites (b), which invade the epithelial cells lining the intestine (c-e). This invasion may occur from 1 - 6 h after the ingestion occurs. After invasion, the sporozoites undergo replication, which leads to a rapid increase in another stage of the parasite called merozoites (f). The merozoites invade more cells of the gut, multiplying once again (g-i). The effects of coccidiosis are generally associated with the lysing of host epithelial cells by merozoites. Some merozoites develop into the sexual stages called micro (male) and macro (female) gametocytes (j). These develop into micro- and macrogametes, which fuse to form a zygote (o-r). The zygote develops into an oocyst that is eventually released in the faeces (t). The oocysts first undergo further development (sporulation) in the litter to become infectious (u-x). Bottom (2): Illustration of a fully-formed (sporulated) oocyst (a, c) and sporocyst (b, d). (Adapted from Entzeroth et al., 1998; Lindsay and Todd Jnr., 1993; Sam-Yellowe, 1996).


42

A zygote is formed when micro and macro gametes fuse together (gamogony)

and develops into an oocyst (non-sporulated), which is eventually released in the

faeces. The oocysts first undergo further development (sporulation) in the litter and

are resistant to environmental extremes. Once sporulation is completed, the

sporozoites within the oocysts are immediately infective to the next suitable host

animals that may ingest them.

For pathogenic species, such as E. ninakohlyakimovae and E. ovinoidalis, the

first schizogony takes place in the ileum (10 days post infection), the second in the

crypt cells of the caecum (12 days post infection) and the colon, and eventually

gamogony occurs in the large intestine (13 days post infection), with a prepatent

period of 15 days (Chartier and Paraud, 2012).

The oocysts of Eimeria from sheep and goats are generally ovoid to ellipsoid in

shape, their length ranges from 13 - 51 µm and width from 11 - 37 µm, and may

contain specialized structures, such as polar caps, micropyles, residual and crystalline

bodies (Vercruysse, 1982).


In sheep, Eimeria mostly affects the ileum, cecum and upper colon, which may

be thickened, oedematous and inflamed; sometimes, there is mucosal haemorrhage

(Aiello et al., 2012a). Clinical signs include diarrhoea (sometimes, containing blood or

mucus), dehydration, fever, inappetence, weight loss, anaemia, wool breaking and

death (Aiello et al., 2012a). In goats, stages and lesions are usually confined to the

small intestine, which may appear congested, haemorrhagic or ulcerated, and have

pale, yellow to white macroscopic plaques in the mucosa (Aiello et al., 2012a).

1.3.4 Diagnosis

Coccidiosis is suspected when there are digestive troubles in young animals

bred under poor hygienic conditions, intensive breeding or sudden mortality. In

epidemiological settings, a poor growth rate can suggest a diagnosis of subclinical

coccidiosis (Chartier and Paraud, 2012). Traditional diagnosis of Eimeria species is

based on oocyst morphology, host specificity, and pathology or examination of the gut


43

after necropsy (Tenter et al., 2002; Chartier and Paraud, 2012). Coproscopical

examination also includes quantitation of oocysts using sodium chloride (NaCl) or

magnesium sulphate (MgSO4) flotation (Chartier and Paraud, 2012). In recent years,

there have been numerous studies, which have used molecular data based on 18S

ribosomal RNA (18S rRNA) sequences to discriminate the species of Eimeria (Power et

al., 2009; Gibson-Kueh et al., 2011).


The control of coccidiosis relies on preventative measures such as good

hygienic conditions, reduction of stressors, an adequate nutrition and the use of

anticoccidial drugs (Chartier and Paraud, 2012). Anticoccidial products belong to a

number of chemical families with different modes of action on the endogenous phase

of life cycle and these include sulphonamides, amprolium, ionophores, decoquinate,

toltrazuril and diclazuril (Chartier and Paraud, 2012).

The greatest risk for transmission of oocysts for young lambs and goat kids (1 -

6 months old) include lambing pens, intensive grazing areas, feedlots, ration change,

crowding stress, severe weather, and contamination of the environment with oocysts

from infected ewes and does (Aiello et al., 2012a). Under management systems where

coccidiosis is predictable, it is recommended to administer anticoccidials

prophylactically for 28 consecutive days beginning a few days after the lambs or goat

kids are introduced into the area (Aiello et al., 2012a).

1.4 Cryptosporidium


Cryptosporidium is an apicomplexan protozoan parasite, which invades the

gastrointestinal and respiratory epithelium of a wide range of vertebrate species, and

may cause considerable economic losses in livestock (Sreter and Varga, 2000; Fayer,

2008). Infections in immunocompetent individuals are usually self-limiting, but they

can be life-threatening in immunocompromised individuals (O'Donoghue, 1995).

Cryptosporidium developmental stages were first discovered in the gastric

glands of laboratory mice by Ernest Edward Tyzzer (Tyzzer, 1907, 1910). The species,


44

which was given the name Cryptosporidium muris, was later found to infect the gastric

glands of several other mammals, but not humans. Tyzzer identified a second species

(C. parvum) in 1912, which was found to infect the small intestine of laboratory mice

(Tyzzer, 1912). The impact of Cryptosporidium on animal health was not recognised

until its association with diarrhoea in 1950s in young turkeys due to C. meleagridis and

in the 1970s in calves due to C. parvum (Slavin, 1955; Panciera et al., 1971).

Cryptosporidium infection has been implicated in numerous waterborne and

foodborne outbreaks associated with human and livestock diseases (Smith and Rose,

1998; Smith et al., 2007; Budu-Amoako et al., 2011). Since the first description of

C. muris, numerous species of the genus Cryptosporidium were described based on the

animal hosts from which they were isolated, however, subsequent morphological,

cross-transmission and genetic studies have invalidated many species (Egyed et al.,

2003; Xiao et al., 2004). The taxonomic status and naming of this genus is constantly

changing as new information based on molecular data is published. At present, there

are at least 27 valid species of the genus Cryptosporidium and over 40 different

isolates or genotypes (Fayer et al., 2008; Robertson, 2009; Xiao, 2010; Ryan and Xiao,

2013).

In sheep, eight species and several genotypes have been identified including

C. parvum, C. ubiquitum, C. xiaoi, C. andersoni, C. hominis, C. fayeri, C. suis and

C. scrofarum with C. xiaoi, C. ubiquitum and C. parvum most prevalent (Ryan et al.,

2005; Goma et al., 2007; Karanis et al., 2007; Santin et al., 2007; Soltane et al., 2007;

Fayer et al., 2008; Geurden et al., 2008b; Mueller-Doblies et al., 2008; Quilez et al.,

2008; Fayer and Santin, 2009; Giles et al., 2009; Paoletti et al., 2009; Yang et al., 2009;

Diaz et al., 2010a; Robertson et al., 2010; Wang et al., 2010b; Xiao, 2010; Fiuza et al.,

2011; Shen et al., 2011; Sweeny et al., 2011b; Caccio et al., 2013; Connelly et al., 2013;

Imre et al., 2013; Yang et al., 2013). Three of these species (C. parvum, C. hominis and

C. xiaoi) have also been identified in goats (Giles et al., 2009; Diaz et al., 2010b; Fayer

et al., 2010; Robertson et al., 2010).

Cryptosporidium has a global distribution. Cryptosporidium infections in sheep

have been reported in numerous studies in Europe (Belgium, Czech Republic, Italy,


45

Poland, Portugal, Spain and UK), Americas (Brazil, Mexico, Trinidad, Tobago, USA and

Canada), Australia, Asia (Iraq, Iran, Oman, Sri Lanka and Taiwan) and Africa (Egypt and

Zambia) with cross-sectional prevalence range from < 5 % to > 70 % (mean ~30 %,

n = 20) (Robertson, 2009; Fiuza et al., 2011). Although, fewer epidemiological studies

have examined Cryptosporidium spp. in goats, it appears that prevalence is similarly

variable, with values of < 10 % to > 40 % reported (Robertson, 2009). Cryptosporidium

infections in goats have been reported in Europe (Belgium, France, Spain and UK), the

Americas (Brazil, Trinidad, and Tobago), Asia (Iraq, Sri Lanka and Taiwan) and Africa

(Zambia) (Giles et al., 2009; Robertson, 2009). It has been diagnosed in outbreaks of

diarrhoea and often deaths in goat kids and lambs (< 6 months old) in Australia and

several European countries (de Graaf et al., 1999).

Cryptosporidium has been described in more than 17 species of both

freshwater and marine fish, with prevalence rates of < 1 % to 100 % (Alvarez-Pellitero

and Sitja-Bobadilla, 2002; Alvarez-Pellitero et al., 2004; Ryan et al., 2004; Murphy et

al., 2009; Reid et al., 2010; Zanguee et al., 2010; Morine et al., 2012). Parasitic stages

have been reported to be located deep within and on the surface of the stomach or

intestinal epithelium (Alvarez-Pellitero and Sitja-Bobadilla, 2002; Alvarez-Pellitero et

al., 2004; Ryan et al., 2004; Murphy et al., 2009; Reid et al., 2010; Zanguee et al., 2010;

Morine et al., 2012). Currently, the only recognised species infecting fish is

Cryptosporidium molnari, which was identified in gilthead sea bream (Sparus aurata)

and European sea bass (Dicentrarchus labarx) (Alvarez-Pellitero and Sitja-Bobadilla,

2002) and was characterised genetically in 2010 (Palenzuela et al., 2010).

Cryptosporidium molnari primarily infects the epithelium of the stomach and seldom

the intestine (Alvarez-Pellitero and Sitja-Bobadilla 2002). In 2004, C. scophthalmi was

described in turbot (Psetta maxima. sny. Scopthalmus maximus) (Alvarez-Pellitero and

Sitja-Bobadilla, 2002; Alvarez-Pellitero et al., 2004). However, no genetic sequences

are available for C. scophthalmi and it can thus not be considered a valid species due to

the high genetic heterogeneity and morphological similarity among Cryptosporidium

species in fish. In addition to C. molnari, a total of 3 species and 10 genotypes have

been characterised genetically in fish (Table 1-3).

Table 1-3: Species/genotypes of Cryptosporidium reported in fish in previous studies. N = the number of specimens in which each species/genotype of Cryptosporidium was identified. Fish host scientific name in italics and common name in brackets.

Species/genotype N Fish host Reference

C. molnari > 100 Sparus aurata (Gilt head sea bream) and Dicentrarchus labarx (European seabass)

Alvarez-Pellitero and Sitja-Bobadilla, 2002; Palenzuela et al., 2010

C. scophthalmi 49 Scopthalmus maximus (Turbot) Alvarez-Pellitero and Sitja-Bobadilla, 2002; Alvarez-Pellitero et al., 2004

C. molnari -like 7 Monodactylus argenteus (Butter bream), Pseudanthias dispar (madder seaperch), Ctenochaetus tominiensis (bristle tooth tang), Synodontis nigriventris (upsidedown catfish), Paracanthurus hepatus (wedgetailed blue tang), Chromis viridis (green chromis) and Gyrinocheilus aymonieri (golden algae eater).

Zanguee et al., 2010

Piscine genotype 1 2 Poecilia reticulate (Guppy) and Paracheirodon innesi (neon tetra) Ryan et al., 2004; Zanguee et al., 2010

Piscine genotype 2 > 5 Pterophyllum scalare (Angelfish), Paracheirodon innesi (neon tetra) and Astronatus ocellatis (Oscar fish).

Murphy et al., 2009; Zanguee et al., 2010

Piscine genotype 3 2 Mugil cephalus (Sea mullet) Reid et al., 2010

Piscine genotype 4 4 aymonieri (Golden algae eater), Chrysiptera hemicyanes (kupang damsel), Astronatus ocellatis (Oscar fish) and Paracheirodon innesi (neon tetra)

Zanguee et al., 2010; Morine et al., 2012

Piscine genotype 5 3 Pterophyllum scalare (Angelfish), Monodactylus argenteus (butter bream) and Gyrinocheilus aymonieri (golden algae eater).

Zanguee et al., 2010

Piscine genotype 6 1 Poecilia reticulate (Guppy) Zanguee et al., 2010

Piscine genotype 6-like 1 Trichogaster trichopterus (Gold gourami) Morine et al., 2012 Piscine genotype 7 3 Moenkhausia sanctaefilomenae (Red-eye tetra) Morine et al., 2012

Rat genotype 3-like 1 Carassius auratus (Goldfish) Morine et al., 2012

C. scrofarum 2 Sillago vittata (School whiting) Reid et al., 2010

C. parvum 1 Sillago vittata (School whiting Reid et al., 2010

C. xiaoi 1 Sillago vittata (School whiting Reid et al., 2010


Approximately 15 species of Cryptosporidium have been identified in humans,

but 5 species including C. hominis, C. parvum, C. meleagridis, C. felis and C. canis are

responsible for most human cryptosporidiosis cases (Xiao and Feng, 2008). Prevalence

rates of Cryptosporidium infections in humans ranged as low as 1 % in Europe and

North America to 30 % in other countries and pooled data from developed countries

showed an average of 2.1 %, while in developing countries, the average prevalence

was 6.1 % (Franzen and Muller, 1999). Recently, Cryptosporidium was identified as one

of the main causes of serious diarrhoea in children in developing countries (Kotloff et

al., 2013).


Transmission occurs via an environmentally robust oocyst (Fig. 1-3), which is

excreted in the faeces of the infected host (Franzen and Muller, 1999).

Cryptosporidium is capable of completing all stages of its life cycle within an individual

host (Fig. 1-4). Once ingested, the oocyst excysts in the gastrointestinal tract and

releases infective sporozoites, which subsequently attach to the epithelial cells of the

small intestine and they become enclosed within parasitophorous vacuoles

(O'Donoghue, 1995). The sporozoites develop into trophozoites, which then undergo

asexual proliferation by merogony into two types of meronts (type I and type II

meronts). Type I meronts form 8 merozoites, which are liberated from the

parasitophorous vacuole when mature and type II meronts form 4 merozoites, which

produce sexual reproductive stages (called gamonts) (O'Donoghue, 1995). Type I

merozoites can cause autoinfection by attaching to epithelial cells or developing into

Type II merozoites, which initiate sexual multiplication (Chen et al., 2002). Type II

merozoites attach to the epithelial cells, where they become either macrogamonts or

microgamonts (Chen et al., 2002). Microgamonts develop into microgametocytes,

which produce up to 16 non-flagellated microgametes (O'Donoghue, 1995).

Macrogamonts develop into uninucleate macrogametocytes, which are fertilized by

mature microgametes (sexual reproduction) (O'Donoghue, 1995). The resultant

zygotes undergo further asexual development (sporogony) leading to the production

of sporulated oocysts (O'Donoghue, 1995). While most oocysts are thick-walled and

are excreted in the faecal material, some are thin-walled and have been reported to


48

encyst within the same host animal. These auto-infective oocysts and recycling type I

meronts are believed to be the means by which persistent chronic infections may

develop in hosts without further exposure to exogenous oocysts (O'Donoghue, 1995).

The entire life cycle may be completed in 2 days in many hosts and infections may be

short-lived or may persist for several months (O'Donoghue, 1995). The prepatent

period, which is, the time between infection and oocysts excretion, ranges from 2 - 14

days.

The oocysts are spherical to ovoid and measure 3 - 8 µm in diameter (Fig. 1-3)

(World Organisation for Animal Health-OIE, 2008; Ryan, 2010). Each sporulated oocyst

contains four, flat, thin, motile, crescent-shaped sporozoites and a residuum

composed of numerous small granules and a spherical or ovoid membrane-bound

globule (Fayer and Ungar, 1986). Trophozoites are round or oval intracellular forms

which are found within a parasitophorous vacuole surrounded by host cell membrane

(Fayer and Ungar, 1986).

Figure 1-3: A scanning electron micrograph of Cryptosporidium parasites lining the intestinal tract (Photo courtesy U.S. Department of Agriculture) (Gardiner et al., 1988).


49

Figure 1-4: Life cycle of Cryptosporidium parvum and C. hominis (Image from CDC http://www.cdc.gov/ Retrieved 26th October 2013). Sporulated oocysts with 4 sporozoites each are excreted by infected host (either human or animal) through faeces (1). Cryptosporidium oocyst is generally transmitted through contact with contaminated drinking or recreational water (2). After the parasite is ingested (3), excystation occurs and the sporozoites are released from oocysts (a, b). The sporozoites infect epithelial cells of the gastrointestinal tract. In these cells, the parasite undergoes asexual multiplication (schizogony or merogony) (d, e, f) and then sexual multiplication, or gametogony, producing microgamonts (males) (g) and macrogamonts (h). When the macrogamont is fertilized by the microgametes (i), oocysts (j, k) develop that sporulate in the infected hosts. Two different types of oocysts are produced, the thick-walled, which is commonly excreted from the host (j), and the thin-walled oocyst (k), which is primarily involved in autoinfection.

http://www.cdc.gov/



Cryptosporidium spp. attach intimately to the microvillus membrane of surface

epithelia of the intestinal tract and cause a range of histologic abnormalities in crypt

and villous structure, including villous atrophy and crypt hyperplasia, which are usually

accompanied by inflammatory responses (Chen et al., 2002).

The main clinical sign of cryptosporidiosis is diarrhoea accompanied by the

shedding of a large number of oocysts (de Graaf et al., 1999). High morbidity and

mortality have been reported in lambs and goat kids, especially, the neonates (Fayer

and Ungar, 1986; de Graaf et al., 1999). Clinical signs of ovine cryptosporidiosis include

diarrhoea, which can last from 2 - 12 days and is sometimes accompanied by anorexia,

poor growth, stiffness, hyperpnoea, slow gait, limb muscle fasciculations and

depression (Fayer and Ungar, 1986). In fish, Cryptosporidium can cause high morbidity

with clinical signs including variable levels of emaciation, poor growth rates, swollen

coelomic cavities, anorexia, listlessness and increased mortality (Murphy et al., 2009).

In humans, although infections can be asymptomatic, most patients have profuse

watery diarrhoea and the duration and severity of clinical symptoms depend largely on

the immune status of infected person (Chen et al., 2002). It can result in life-

threatening diseases in immunodeficient people, especially, AIDS patients (Current et

al., 1983).

1.4.4 Diagnosis

A variety of laboratory tests have been developed for the differential diagnosis

of cryptosporidiosis. These include microscopic, immunologic and molecular detection

of the parasite in the faeces and histological examination of autopsy or biopsy

material. Endogenous developmental stages of Cryptosporidium can be diagnosed

from autopsy or biopsy material after staining with haematoxylin and eosin or Giemsa

and examined under light and/or scanning electron microscopes (O'Donoghue, 1995).

In addition, histological techniques may be used to investigate pathological and

cytological changes accompanying infections, however, these are not recommended

for routine diagnosis (O'Donoghue, 1995).


51

Oocysts in faecal material can be detected by examining stained faecal smears.

There are numerous staining methods available including direct, differential, acid-fast,

fluorochrome and negative staining techniques, which have been described to stain

the walls and/or contents of mature oocysts (O'Donoghue, 1995). Acid-fast staining is

the simplest and a widely used method for detecting oocysts in faecal material,

however, like other conventional microscopic examination methods, the drawback is

that oocysts can be difficult to recover and identify because of their small size and

frequent similarities of their morphological features (i.e. size, shape and internal

structures) (O'Donoghue, 1995; Chen et al., 2002). The sensitivity and specificity of

microscopic examination methods can be improved with sedimentation and flotation

techniques prior to microscopy, and immunological-based techniques such as

immunofluorescent antibody tests and antigen-capture ELISAs (Chen et al., 2002).

However, antibody techniques suffer from lack of specificity and in the last two

decades, numerous molecular techniques have been developed for detection and

differentiation of Cryptosporidium at species/genotype and subtype level.

Molecular tools are widely used in epidemiological studies of cryptosporidiosis

in endemic and epidemic areas, in which they have improved the understanding of

transmission of cryptosporidiosis in humans and animals (Xiao, 2010). Different types

of molecular tools have been used for the differentiation of Cryptosporidium

species/genotypes or subtypes. 18S rRNA-based tools are extensively used in

genotyping Cryptosporidium in humans, animals and water samples (Xiao, 2010). The

widespread use of the 18S rRNA gene in genotyping Cryptosporidium is largely due to

the multi-copy nature of the gene and the presence of semi-conserved and hyper-

variable regions, which facilitate the design of genus-specific primers (Xiao, 2010).

Other genes are also used in combination with 18S rRNA-based tools including oocysts

the actin gene, the heat shock protein 70 (Hsp70) gene, and the 60 kDA glycoprotein

gene (gp60) (Table 1-4) (Caccio et al., 2005).

The typing and subtyping methods used for veterinary samples are important

for veterinary and public health applications. Currently, subtyping tools are only

applicable to C. parvum, C. hominis, C. cuniculus, C. ubiquitum, C. tyzzeri and C. fayeri


52

and have been used extensively in studies of the transmission of C. hominis in humans

and C. parvum in humans and ruminants (Xiao, 2010; Li et al., 2014). One gene that is

popular for subtyping Cryptosporidium is gp60. The gp60 gene has variations in the

number of trinucleotide repeats and extensive sequence differences in the non-repeat

regions, which categorize C. parvum and C. hominis to several subtype families (Xiao,

2010). It is similar to a microsatellite sequence by having tandem repeats of the serine-

coding trinucleotide TCA, TCG or TCT at the 5’ end of the gene (Xiao, 2010).

Table 1-4: Molecular techniques for characterising Cryptosporidium. RFLP = restriction fragment length polymorphism; Hsp70 = heat shock protein 70; COWP = Cryptosporidium oocyst wall protein gene; gp60 = 60 kDa glycoprotein gene. (Adapted from Caccio et al., 2005).

Amplification target Assay type Identification for

18S rDNA PCR, nested PCR, sequencing, PCR-RFLP, qPCR, microarray

Species & genotype

Hsp70 PCR, nested PCR, sequencing, PCR-RFLP, microarray

Species & genotype

COWP PCR, nested PCR, sequencing, PCR-RFLP, microarray

Species & genotype

Actin PCR, nested PCR, sequencing Species & genotype

β-Tubulin PCR, nested PCR, sequencing, PCR-RFLP Species & genotype

gp60 PCR, nested PCR, sequencing Subtype

Microsatellites PCR, nested PCR, sequencing, fragment typing

Subtype

Minisatellites PCR, nested PCR, sequencing, fragment typing

Subtype

Extra-chromosomal double stranded RNA

Reverse transcriptase PCR, sequencing, heteroduplex mobility assays

Subtype


There is no effective specific treatment for cryptosporidiosis in sheep and

goats, however, because the disease is usually self-limiting, supportive therapy, such

as rehydration and maintenance of energy requirements, is usually sufficient.

Preliminary results obtained in calves, lambs and goat kids infected by Cryptosporidium

sp. have indicated a partial prophylactic efficacy of halofuginone lactate when

administered at 100 μg/kg body weight (BW) (De Waele et al., 2010). Recently, an

efficacy demonstration study showed that halofuginone lactate, which when given as a

prophylactic treatment at 100 μg/kg BW, reduced oocyst shedding, diarrhoea and

mortality in goat kid cryptosporidiosis (Petermann et al., 2014).


53

1.5 Giardia


Giardia is a flagellated protozoan parasite and is one of the most common

nonviral causes of diarrhoea in humans and livestock worldwide (Thompson et al.,

2000). The parasite was first observed by Van Leeuwenhoek in 1681 (Dobell, 1920) and

more fully described by Lamb in 1859 (Lamb, 1859). There are six recognised species in

the genus Giardia (1952-2007); Giardia duodenalis (syn. G. intestinalis, G. lamblia) in

mammals, G. agilis in amphibians, G. muris and G. microti in rodents, and G. ardeae

and G. psittaci in birds (Monis et al., 2009). Giardia duodenalis is frequently found in

livestock, companion animals and humans (Xiao and Fayer, 2008). Within this species,

there are eight morphologically identical but genetically distinct genotypes or

assemblages designated A – H (Thompson, 2004; Lasek-Nesselquist et al., 2010) with

assemblages A and B known to infect a wide range of hosts including humans,

livestock, cats, dogs and other mammals (Thompson, 2004; Xiao and Fayer, 2008).

Assemblages C and D infect dogs, assemblage E infects livestock (cattle, sheep, pigs),

assemblage F infects cat, assemblage G infects domestic rats and assemblage H infects

marine vertebrates (Thompson, 2004; Lasek-Nesselquist et al., 2010).

In small ruminants, especially, lambs and goat kids, giardiasis can cause

significant economic losses (O'Handley et al., 2001; Aloisio et al., 2006). The prevalence

of Giardia ranged from 2.7 - 68.8 % in sheep and 4.0 - 42.2 % in goats (Robertson,

2009). Based on genotyping analyses in the last decade, G. duodenalis assemblage E

was found to be the most prevalent genotype in sheep and goats, with assemblage A

and B less prevalent in Australia (Ryan et al., 2005; Yang et al., 2009; Sweeny et al.,

2011b), USA (Santin et al., 2007), Belgium (Geurden et al., 2008b), Italy (Giangaspero

et al., 2005; Aloisio et al., 2006), The Netherlands (van der Giessen et al., 2006) and

Spain (Castro-Hermida et al., 2006; Ruiz et al., 2008; Gomez-Munoz et al., 2009).

Although Giardia has been reported in seals, sea lions, a shark and clams, very

little is known about the prevalence, genetic diversity and effect of Giardia species in

marine or freshwater systems and the role that aquatic animals play in transmission of

these parasites to human (Yang et al., 2010). In fish, prevalences of 3.8 % and 3.3 %


54

have been reported and G. duodenalis assemblages A, B, E and G. microti have been

found (Yang et al., 2010; Ghoneim et al., 2011).

In humans, giardiasis is a well-recognised waterborne disease in both

developed and undeveloped countries (Levine et al., 1990; Thompson, 2000; Leclerc et

al., 2002; Dawson, 2005; Baldursson and Karanis, 2011; Budu-Amoako et al., 2011).

The reported prevalence of G. duodenalis assemblages A and B ranged from 20 - 100 %

in at least 14 countries including Italy, Wales, England, The Netherlands, USA, Canada,

Australia, China, Korea, Laos, India, Peru, Uganda and Turkey (Caccio et al., 2005).

Although, little epidemiological evidence exist that strongly supports the importance

of zoonotic transmission of giardiasis to humans, the occurrence of zoonotic

G. duodenalis assemblages A and B in sheep and goats suggest that these animals may

act as reservoirs for human infection (Xiao and Fayer, 2008).


The life cycle of Giardia is composed of two major stages: cysts and

trophozoites (Fig. 1-5). Cysts are environmentally stable and responsible for

transmission. Infection is initiated when the cyst is ingested with contaminated water

or, less commonly, food or through direct faecal-oral contact (Adam, 2001). Following

ingestion and exposure to the acidic environment of the stomach, cysts excyst and

develop into trophozoites in the proximal small intestine (Adam, 2001; Ankarklev et al.,

2010). The trophozoites then attach to the surface of the intestinal epithelium in the

crypts of the duodenum and upper jejunum and reproduce asexually by binary fusion,

causing intestinal tissue damage (characterised by diarrhoea and malabsorption)

(Ortega and Adam, 1997). After exposure to host specific-factors such as high levels of

bile, low levels of cholesterol and a basic pH, some trophozoites form cysts in the

jejunum and are passed in the faeces, allowing completion of the life cycle by infecting

a new host (Lauwaet et al., 2007).

Giardia cysts are either round or oval and measure 11 - 14 x 7 - 10 µm (Fig. 1-6)

(Ortega and Adam, 1997). Each cyst has four nuclei and contains axonemes and

median bodies (Ortega and Adam, 1997). The cysts are metabolically inactive and have


55

a hard wall (consisting of 60 % carbohydrate and 40 % protein) that protect them from

hypotonic lysis in the environment (Ankarklev et al., 2010).

Figure 1-5: Life cycle of Giardia duodenalis (Image from Ankarklev et al., 2010). Giardia cysts are exposed to gastric acid during their passage through the host’s stomach, triggering excystation. This causes differentiation of the cyst into the vegetative trophozoite, which attaches to the intestinal epithelium via its adhesive disc and replicates. After exposure to bile salts, some trophozoites form non-motile, infective cysts (a process known as encystation) in the lower intestine and are passed in the faeces.

Figure 1-6: Electron photomicrograph of Giardia duodenalis cysts (A) and trophozoites (B). (Bar = 10 µm) (Image from Ortega and Adam, 1997).


56

Giardia trophozoites measure 10 - 20 µm in length and 5 - 15 µm in width (Fig.

1-6) (Ortega and Adam, 1997). The shape of the trophozoites varies among species:

G. duodenalis is pear shaped and has one or two transverse, claw-shaped median

bodies; G. agilis is long and slender and has a teardrop-shaped median body, and

G. muris trophozoites are shorter and rounder and have a small, rounded median body

(Adam, 2001). Giardia duodenalis trophozoites are bilaterally symmetrical, measure

12 - 15 µm x 6 - 8 µm, and have a convex dorsal surface and a large unique adhesive or

‘sucking disc’ on the ventral surface (Thompson, 2004). They have two nuclei, four

pairs of flagellae and a pair of distinctive median bodies with a simple vesicular

secretory system, but no mitochondria or peroxisomes (Marti et al., 2003; Ankarklev et

al., 2010). The flagellae and adhesive disc are used for adhesion to the upper intestinal

walls, while the role of median body is unknown (Ankarklev et al., 2010).


The pathogenesis of Giardia is not clearly understood, however, several

mechanisms have been proposed based on studies on human epithelial cell lines, on

laboratory animals, goat kids and calves that indicate that pathogenesis of giardiasis is

a combination of both parasite and host factors (Ankarklev et al., 2010; Geurden et al.,

2010b). The main virulence factors include the trophozoite’s adhesive disc and the four

flagellae, which when they interact with host cells can induce apoptosis, loss of

epithelial-barrier function, diffuse shortening of microvillus (which leads to

malabsorption of electrolytes, solutes and water), mucosal inflammation (after

infiltration of lymphocytes and mast cells) and interference with bile salts metabolism

(Ankarklev et al., 2010).

The clinical signs of giardiasis include acute and chronic diarrhoea, dehydration,

abdominal pain and weight loss. Giardia duodenalis infections have been reported in

lambs in which abnormal faeces, impairment in feed efficiency, a decreased rate of

weight gain and severe weight loss have been observed (Olson et al., 1995); Aloisio et

al., 2006). In histological sections, mild to severe infiltrative enteritis with eosinophils,

lymphocytes and plasma cells have been reported (Aloisio et al., 2006). In humans,

symptoms include watery diarrhoea, epigastric pain, nausea, vomiting and weight loss,


57

which appear 6 - 15 days after the infection (Ankarklev et al., 2010). The clinical impact

is more severe in young children and undernourished or immunodeficient individuals.

1.5.4 Diagnosis

As the symptoms of giardiasis are similar to other gastrointestinal diseases,

clinical diagnosis in production animals is mainly based on clinical history, data on farm

management and the exclusion of other infectious disease, such as coccidiosis, and

confirmed by detection of the parasite in a faecal sample by microscopic examination,

antigen detection and PCR-based tools (Geurden et al., 2010b).

Traditional microscopic methods include the application of faecal concentration

techniques, especially, zinc sulphate flotation and centrifugation (Zajac et al., 2002)

and followed by stains such as iodine or trichrome (Geurden et al., 2010b). It is

cheaper to perform a microscopic examination but it has relatively low sensitivity and

requires a skilled and experienced person to discriminate the parasite (Xiao and Herd,

1993; Amar et al., 2002; Geurden et al., 2010b).

For detection of parasite antigen, immunofluorescence assays (IFAs) (Xiao and

Herd, 1993), enzyme-linked immunosorbent assays (ELISAs) (Boone et al., 1999) and

rapid solid-phase qualitative immunochromatography assays (Garcia et al., 2003) are

available. IFAs and ELISA use monoclonal antibodies against cyst wall proteins.

Immunochromatographic techniques also target cyst wall proteins as well as

trophozoite proteins and unlike, IFA and ELISA; they allow on-site and quick diagnosis

of infection (Garcia et al., 2003). Antigen detection tests are more sensitive and

specific than microscopic examination for diagnosis of infection, however, they too

require trained personnel and are expensive (Geurden et al., 2010b). These tests have

been developed and evaluated using human stool samples, and used in calves

(Geurden et al., 2004), however, they have not been used in sheep (Geurden et al.,

2010b).

Molecular tools are mainly used for differentiating Giardia at species and

genotype level for taxonomical and epidemiological research, but can be used for

diagnosis. Most studies have relied on the analysis of the well conserved eukaryotic


58

genes such as the 18S rRNA, glutamate dehydrogenase (gdh), triose phosphate

isomerase (tpi), elongation factor 1-alpha gene (ef-1α) or genes uniquely associated

with the parasite such as the β-giardin gene (Table 1-5) (Ryan and Caccio, 2013). Other

genes used for characterising Giardia include G. lamblia open reading frame (GLORF)-

C4 and the inter-genomic rRNA spacer region (IGS) (Caccio et al., 2005; Lee et al., 2006)

(Table 1-5).

Table 1-5: Molecular techniques for characterising Giardia(Adapted from Caccio et al. 2005). gdh = glutamate dehydrogenase, tpi = triose phosphate isomerase, EF-1α = elongation factor 1-alpha gene, GLORF-C4 = G.doudenalis open reading frame C4, IGS = inter-genomic rRNA spacer region.

Amplification target Assay type Main application

18S rDNA PCR, nested PCR, sequencing, microarray

Species and genotype identification

gdh PCR, nested PCR, sequencing, PCR-RFLP


tpi PCR, nested PCR, sequencing, qPCR, microarray


β-giardin PCR, nested PCR, sequencing, PCR-RFLP, q PCR, microarray

Genotype identification

EF-1α PCR, nested PCR, sequencing Species and genotype identification

GLORF-C4 PCR, sequencing, PCR-RFLP Genotype identification

IGS PCR, sequencing Genotype identification


Several compounds, specifically, benzimidazoles and paromomycin, have a

known efficacy against Giardia both in vitro and in laboratory animals, yet there are no

drugs registered for the treatment of giardiasis in sheep and goats (Geurden et al.,

2010b). Several benzimidazole compounds and paromycin were shown to be

efficacious in experimental conditions, especially, in calves (O'Handley et al., 1997;

O'Handley et al., 2000; O'Handley et al., 2001; Geurden et al., 2006b; Geurden et al.,

2010a). Fenbendazole has been shown to effectively clear Giardia infection in natural

infections in lambs (Aloisio et al., 2006). In humans, nitroimidazoles and

benzimidazoles are used for treating giardiasis (Thompson, 2004).

To control Giardia infection in sheep and goats, a combined approach

consisting of chemotherapy and hygienic measures could be taken (Geurden et al.,


59

2006b). Preventive measures should include low stocking rate, isolation of infected

lambs from animal housing, regular cleaning and disinfection of the housing facilities

(Geurden et al., 2010b).

1.6 Anisakids


Anisakid nematodes are economically significant in fish farming and are

medically important to humans. The presence of anisakid larvae on and in the viscera

and flesh or free in the body cavity of many economically important cephalopod and

fish species is an aesthetic problem, which leads to notable adverse effects on

marketing (Abollo et al., 2001). In addition, removing parasites adds appreciably to the

costs of packaging, reducing the value of the product and representing a financial loss

in marketing value (Abollo et al., 2001).

Anisakidosis refers to infection of people with larval stages of anisakid

nematodes belonging to the family Anisakidae or Rhaphidascarididae and its clinical

symptoms include acute abdominal pain, nausea, vomiting and allergic responses (Chai

et al., 2005; Audicana and Kennedy, 2008). The first case of human infection by an

anisakid was reported in the Netherlands by Van Thiel (1960), who described the

presence of a marine nematode in a patient suffering from acute abdominal pain (Van

Thiel et al., 1960). Anisakidosis occurs throughout the world. Approximately 20, 000

cases of human anisakidosis are reported each year with majority of the cases (> 90)

from Japan, followed by Europe and then the rest of the world (the Americas, South-

east Asia, Egypt and New Zealand) (Lymbery and Cheah, 2007; Hochberg and Hamer,

2010).

Anisakids are ascarid nematodes, which utilise aquatic vertebrate (fish, reptiles,

piscivorous birds, or mammals) as definitive hosts and whose transmission depends on

water and usually involves aquatic invertebrates and fish as intermediate or paratenic

hosts (Lymbery and Cheah, 2007). The nematode superfamily Ascaridoidea contains >

50 genera. There are controversies in taxonomic classification in this superfamily; few

classification schemes exist due to inconsistencies in the key morphological structures


60

or life history features (Mattiucci et al., 2003; Mattiucci and Nascetti, 2008). Recent

reported phylogenetic relationships based on molecular data have not fully resolved

taxonomic uncertainty within this superfamily, however, they tend to support the

classification proposed by Fagerholm (1991) (Lymbery and Cheah, 2007). The two

genera most often associated with anisakidosis are Anisakis and Pseudoterranova.

The genus Anisakis consists of nine described species in two clades. The first

clade includes 6 species; Anisakis simplex complex (which comprised A. simplex sensu

stricto (s.s.), A. pegreffi and A. simplex C), A. typica and the sister species A. nascettii

and A. ziphidarum, while the second clade consists 3 species; A. brevispiculata,

A. paggiae and A. physeteris (Mattiucci and Nascetti, 2008; Mattiucci et al., 2009).

Currently, only A. simplex s.s., A. pegreffii and A. physeteris have been shown to cause

infection in humans (Asato et al., 1991; Hochberg and Hamer, 2010; Mattiucci et al.,

2011; Arizono et al., 2012). The distribution patterns of Anisakis species are likely to be

a consequence of dispersal through the faeces of infested oceanic delphinids (Kuhn et

al., 2011). Anisakis simplex s.s. is found in the northern hemisphere in Atlantic and

Pacific Oceans from 20 °N to 80 °N (the Artic polar circle) (Mattiucci and Nascetti,

2006; Kuhn et al., 2011). Anisakis pegreffi is distributed in southern oceans from

Mediterranean waters through to East Atlantic Ocean and down to the Antarctic

Peninsula and also in Japanese and Chinese waters (Mattiucci and Nascetti, 2006; Kuhn

et al., 2011). Anisakis physeteris is distributed throughout the central Atlantic Ocean

(Mattiucci and Nascetti, 2006; Kuhn et al., 2011). In the tropics and subtropics,

A. typica is the most dominant species between 45 °N and 25 °N (Mattiucci and

Nascetti, 2006; Kuhn et al., 2011). Anisakis typica is a common parasite of various

dolphin species of warmer temperate waters, such as Tucuxi (Sotalia fluviatilis), the

Common Bottlenose Dolphin (Tursiops truncates) and the Pantropical Spotted Dolphin

(Stenella attenuate) (Kuhn et al., 2011).

The genus Pseudoterranova consists of three species: Pseudoterranova kogiae,

P. cetiola and P. decipiens. To date, only P. decipiens (seal worms) have been reported

to cause infection in humans (Hochberg and Hamer, 2010). Based on genetic analysis,

P. decipiens represents a species complex comprising 6 different species, namely,


61

P. azarasi, P. bulbosa, P. cattani, P. decipiens sensu stricto (s.s.), P. decipiens E and

P. krabbei (Mattiucci and Nascetti, 2008). Pseudoterranova decipiens s.s. has a wider

distribution including the North East Atlantic (NEA), the North West Atlantic (NWA),

arctic and sub-arctic areas (Mattiucci and Nascetti, 2008). The main geographic

distribution of P. krabbei is NEA, P. bulbosa is NWA and North West Pacific (NWP),

P. azarasi is NWP and waters of Japan, P. decipiens E is Antartica and P. cattani is

South-East Pacific (Mattiucci and Nascetti, 2008).


Anisakid nematodes have a complex life cycle involving a free-living stage and

multiple host species (Fig. 1-7). The definitive hosts for Anisakis species are cetaceans

(dolphins, porpoises and whales) and for Pseudoterranova are pinnipeds (seals,

walruses, and sea lions) (Hochberg and Hamer, 2010). Adult nematodes living in the

gut of marine mammals produce unembryonated eggs, which are shed with the faeces

of their hosts. The egg embryonate in the sea and develops into first stage larva (L1)

and then free- living L2 or L3 larvae (Lymbery and Cheah, 2007; Hochberg and Hamer,

2010). Free-living larvae are ingested by small crustaceans (e.g. krills, first intermediate

host), in which L2 can develop into L3 for some anisakid nematodes (Lymbery and

Cheah, 2007; Hochberg and Hamer, 2010). Infected crustaceans are eaten by fish and

squid (second intermediate hosts), in which the L3 migrates into the viscera and

peritoneal cavity (Hochberg and Hamer, 2010). L3 larvae are often transferred from

fish to fish along the food chain, as a result, large numbers of larvae may accumulate in

piscivorous fish (Hochberg and Hamer, 2010). Upon ingestion by a definitive host, L3

develop into L4 then adult. Humans can only be considered accidental hosts in this life

cycle, and have no influence on the transmission of these parasites (since L3 larvae do

not develop any further and the cycle cannot be completed).

Like other nematodes, anisakid are cylindrical (or round in cross section) and

non-segmented. They have both an oral and anal opening and a complete digestive

tract, which includes an oesophagus, a ventriculus and an intestine (Berland, 1961). In

addition, the mouth of third stage larvae of Anisakis is surrounded by three relatively

small, inconspicuous lips with a prominent boring tooth, an excretory pore and a


62

mucron (Cannon, 1977). Anisakis larvae are white, usually coil in a characteristic

watch-spring shape and can grow up to 40 mm in length and 0.6 mm in width (Cannon,

1977; Hurst, 1984).

Figure 1-7: Complex life cycle of anisakid nematodes. Image from CDC, (http://www.cdc.gov/parasites/anisakiasis/biology.html), retrieved 30th October 2013. Adult nematodes living in the stomach of marine mammals produce unembryonated eggs, which are shed by their hosts (1). Eggs become embryonated, hatched and develop into free-living third stage larvae (L3) (2a, b). The free-living L3 are ingested by planktonic crustaceans (e.g. euphausiid oceanic krill and copepods) (intermediate/paratenic hosts) (3). Infected crustaceans are eaten by fish and cephalods (e.g. squid) and through predation the larvae are transferred from fish to fish (4, 5). When fish or squid containing L3 larvae are ingested by marine mammals, the larvae molt twice and develop into adult worms (6). Adult worms produce eggs to continue the life cycle. Humans become infected through eating L3-infected raw or undercooked fish or cephalods. Humans act as accidental hosts, since L3 usually do not develop any further and the cycle cannot be completed (7).

http://www.cdc.gov/parasites/anisakiasis/biology.html


63

The L3 larvae of Pseudoterranova spp. have three well-defined lips, a boring

tooth, an excretory pore ventral between ventral lips, no ventricular appendages, a

well-developed intestinal caecum and a bluntly rounded tail with little mucron (Hurst,

1984). They are dark red in colour and measure 25 - 36 mm in length and up to 1.2 mm

in width (Hurst, 1984).


Anisakid larvae found inside the fish are usually tightly coiled and found on the

mesenteries, liver, and gonads and in the musculature of the body wall of infected fish.

Studies have demonstrated that the presence of larvae in fish induces various

pathophysiological changes including host cell necrosis in liver and muscle, reduced

cell size, organ compression, gastrointestinal eosinophilic granulomas, proliferation of

host cellular immune responses during hours of invasion and chronic inflammatory

responses near the site of infected liver and muscles (Hauck and May, 1977; Elarifi,

1982; Heckmann, 1985).

In marine mammals, anisakids cause gastric lesions, ulceration, connective

tissue proliferation, granulation, peritonitis and erode the gastric lining, which results

in auto digestion of the stomach wall by the host (Spraker et al., 2003).

Human anisakidosis can take several forms depending on the location and

histopathological lesions caused by the larva. In non-invasive infections, larvae remain

in the alimentary canal without penetrating the mucosa wall and are only discovered

when the worms are expelled by coughing, vomiting or defecating (Lymbery and

Cheah, 2007). This form of infection is usually asymptomatic but occasionally produces

a “tingling throat” syndrome when worms migrate back up the oesophagus into the

oropharynx (Sakanari and McKerrow, 1989). Non-invasive infections are often due to

Pseudoterranova sp. (Lymbery and Cheah, 2007).

In the invasive form of anisakidosis, larvae penetrate the alimentary tract and

associated organs in infected people. Penetration of the buccal mucosa and

pharyngeal mucosa occurs only rarely, by the larvae of both Anisakis and

Pseudoterranova (Amin et al., 2000; Lymbery and Cheah, 2007). Symptoms of


64

oropharyngeal anisakidosis include slight pain, feelings of discomfort, and difficulty in

swallowing (Amin et al., 2000). Penetration of the gastric or intestinal mucosa is the

most common form of anisakidosis. It is associated with four major clinical signs

including gastric anisakidosis, intestinal anisakidosis, ectopic (or extra-gastrointestinal)

anisakidosis, and allergic diseases in infected people. Infections with Anisakis can

result in both gastric and intestinal anisakidosis, while Pseudoterranova causes gastric

invasions (Bouree et al., 1995). The symptoms of gastric anisakidosis occur 1 - 12 h

after ingestion of infected fish and is associated with severe epigastric pain, nausea,

vomiting, low grade fever and occasionally, a rash (Lymbery and Cheah, 2007;

Hochberg and Hamer, 2010). Blood is often observed in gastric juices and stool

(Sakanari and McKerrow, 1989). Acute gastric anisakidosis is often misdiagnosed and

can become a chronic disease with clinical features, which are similar to peptic ulcers,

gastric tumours, acute gastritis, and cholecystitis (Lymbery and Cheah, 2007). Intestinal

anisakiasis usually manifests as an acute disease, occurring 5 - 7 days after ingestion of

the anisakid larvae and is characterised by intermittent or constant abdominal pain,

nausea, vomiting, fever, diarrhoea with blood (Lymbery and Cheah, 2007; Hochberg

and Hamer, 2010). Ectopic (extra-alimentary) anisakidosis is less common and results

from larval penetration of the gastrointestinal tract and migration in the body cavity

where they usually lodge in the peritoneum or subcutaneous tissues, forming tumour-

like, eosinophilic granulomas or abscesses (Lymbery and Cheah, 2007; Hochberg and

Hamer, 2010). Associated symptoms include abdominal pain, vomiting and bloody

stools (Lymbery and Cheah, 2007). Anisakidosis is often associated with strong allergic

responses, with clinical symptoms ranging from isolated swellings to urticarial and life-

threatening anaphylactic shock (Audicana and Kennedy, 2008; Alonso et al., 1999;

Hochberg and Hamer, 2010).

1.6.4 Diagnosis

As symptoms (acute epigastric or abdominal pain) of gastrointestinal

anisakidosis are nonspecific, clinical diagnosis requires careful examination of clinical

symptoms and patient history of recent consumption of raw or incompletely cooked

fish. Gastric anisakidosis is often misdiagnosed as peptic ulcer or stomach tumour,


65

while intestinal anisakidosis as appendicitis or peritonitis (Sakanari and McKerrow,

1989). Diagnosis of gastric anisakidosis includes endoscopy, which allows larvae to be

removed and identified morphologically or genetically, and radiology, which can detect

morphological changes in the host, such as thickened, narrowed and obstructed areas

(Hochberg and Hamer, 2010). Intestinal anisakidosis is more complicated to diagnose

and differential diagnosis is recommended (Hochberg and Hamer, 2010).

Worms isolated from fish samples can be identified on the basis of gross

morphological features, which may be observed microscopically in live or preserved

specimens. For examination, the use of clearing agents such as xylene may be

necessary to make the nematode cuticle more transparent and a slide mount can be

prepared. The morphological characters are used to distinguish adult worms include:

(i) structures of labiae and ventriculus, (ii) the shape of a tail, (iii) the shape of lobes

(Berland, 1961; Cannon, 1977; Olson et al., 1983).

Molecular tools such as PCR, PCR-based RFLP and single-strand conformation

polymorphism are widely used for characterisation of anisakid species. The two most

common targets are the rDNA ITS regions (Zhu et al., 1998; D'Amelio et al., 2000;

Nadler et al., 2000; Pontes et al., 2005; Abe et al., 2006; Umehara et al., 2006; Zhu et

al., 2007; Umehara et al., 2008; Kijewska et al., 2009b;) and the mt-DNA cytochrome

oxidase subunit II (cox2) gene (Valentini et al., 2006; Mattiucci et al., 2009; Cavallero et

al., 2011; D'Amelio et al., 2011; Murphy et al., 2010; Setyobudi et al., 2011). The rDNA

ITS region is a more conserved target and provides a useful approach for the

identification of both distantly and closely related ascaroid species as these spacers

show interspecific sequence differences in the presence of low-level intraspecific

variation (Zhu et al., 1998). On the other hand, mitochondrial DNA evolve at a faster

rate than the rDNA ITS and therefore, provide useful information for phylogenetic

reconstruction of closely related species of nematodes or for identification of cryptic

species (Blouin, 1998, 2002).


Anisakis and Pseudoterranova cannot survive in humans and will eventually die

(Nakaji, 2009). Endoscopic treatment is the definitive treatment for gastric anisakidosis


66

(Hochberg and Hamer, 2010). Endoscopy allows the physician to remove the larva with

the biopsy forceps and identify the worm morphologically. Early removal of worm may

prevent the formation of eosinophilic granulomas caused by allergic reaction to the

degenerating worm in chronic infections (Sakanari and McKerrow, 1989). For intestinal

anisakiasis, recommended treatments include anthelmintics, isotonic glucose solutions

and removal of tissue by surgery (Moschella et al., 2005, Pacios et al., 2005). Control

measures for anisakidosis should focus on postharvest handling, storage and cooking

procedures for fish (Lymbery and Cheah, 2007) and educating the public about the

dangers of eating raw or inadequately cooked, marinated, or salted marine fish or

squid (Hochberg and Hamer, 2010).

1.7 Chlamydia


Members of the genus Chlamydia are gram-negative obligate intracellular

bacteria, which are distributed globally and cause a variety of diseases including

pneumonia, gastroenteritis, encephalomyelitis, conjunctivitis, arthritis, sexually

transmitted diseases and abortion in man, other mammals and birds (Longbottom and

Coulter, 2003). The first descriptions of chlamydial organisms were provided by

Halberstaedter and von Prowazek in 1907, who described the transmission of

trachoma from man to orangutans by inoculating their eyes with conjunctival scrapings

(Halberstädter and von Prowazek, 1907a, b). It was thought that those organisms were

protozoa and they were named ‘chlamydozoa’ after the Greek word ‘chlamys’ for

mantle, because the reddish elementary bodies of the bacterium appeared to be

embedded in a blue matrix or mantle (Longbottom and Coulter, 2003). Chlamydial

infections in domestic mammals was first reported in 1936 following abortions in

sheep in Scotland (Grieg, 1936). The aetiological agent was identified in 1950 by Stamp

et al., and subsequently, the disease was termed enzootic abortion of ewes (EAE,

synonym, ovine enzootic abortion or OEA) (Stamp et al., 1950; Stamp et al., 1952).

The taxonomy of Chlamydiaceae has recently undergone several

reclassifications based on sequence analysis of the 16S and 23S ribosomal RNA and

was divided into two genera, Chlamydia and Chlamydophila (Everett et al., 1999).


67

However, the use of the two-genus classification system, while initially helpful in

distinguishing animal species in the genus Chlamydia, has not been widely adopted

and indeed caused considerable confusion. Efforts are underway to confirm the

"reunification" of the genus Chlamydia and in 2010, the subcommittee on the

taxonomy of the Chlamydiae proposed the return to the combined genus Chlamydia

(Greub, 2010). There are nine species in the genus Chlamydia; Chlamydia trachomatis,

C. muridarum, C. suis, C. pecorum, C. abortus (formerly known as Chlamydia psittaci

serotype 1), C. pneumonia, C. psittaci, C. caviae and C. felis (Everett et al., 1999). Of

these, two species, C. abortus and C. pecorum, infect sheep and goats (Berri et al.,

2009; Rodolakis and Yousef Mohamad, 2010; Lenzko et al., 2011;). Both C. abortus and

C. pecorum are known to cause abortion in small ruminants with C. pecorum also

known to cause enteric diseases in these animals (Berri et al., 2009; Rodolakis and

Yousef Mohamad, 2010).

Chlamydia abortus, in particular, efficiently colonizes the placenta, leading to

abortion or premature births in sheep and goats and financial losses in the affected

flocks (Longbottom and Coulter, 2003). It is a most common cause of reproductive loss

in sheep and goats worldwide due to abortion, especially, in Northern Europe (Stuen

and Longbottom, 2011). In the United Kingdom, OEA is responsible for approximately

45 % of all diagnosed infectious cause of abortion (Stuen and Longbottom, 2011).

Globally, the prevalence (mostly seroprevalence) of C. abortus in sheep and goats can

vary drastically from < 5 % to > 50 % (Wang et al., 2001; Borel et al., 2004; Szeredi et

al., 2006; Bagdonas et al., 2007; Cislakova et al., 2007; Masala et al., 2007; Czopowicz

et al., 2010; Pinheiro Junior et al., 2010; Lenzko et al., 2011; Runge et al., 2012).

In addition to its effect on sheep and goat production, C. abortus is hazardous

for pregnant women due to its zoonotic potential (Rodolakis and Yousef Mohamad,

2010). Zoonotic abortion due to C. abortus infection has been confirmed by genetic

analysis of isolates from a woman who worked with sheep (Herring et al., 1987).

Confirmed cases of abortions in people have also been reported in several countries

including France (Villemonteix et al., 1990), the US (Jorgensen, 1997), the Netherlands


68

(Kampinga et al., 2000), Switzerland (Pospischil et al., 2002) and Italy (Walder et al.,

2005).

Chlamydia pecorum was first associated with disease (sporadic bovine

encephalomyelitis) in cattle in 1940 (McNutt, 1940). The name Chlamydia pecorum

was given by Fukushi and Hirai in 1992 on the basis of genetic data when they isolated

the organism from diseased cattle and sheep with clinical signs including sporadic

encephalitis, infectious polyarthritis, pneumonia and diarrhoea (Fukushi and Hirai,

1992). Chlamydia pecorum infects a wide range of mammals including sheep, goats,

cattle, pigs and koalas and causes a wide range of diseases such as enteritis,

polyarthritis, conjunctivitis, pneumonia, encephalomyelitis, metritis, salpingitis,

mastitis and infertility (Mohamad and Rodolakis, 2010). Its involvement in small

ruminant abortion cases have been reported in France and in North African countries

(Rodolakis and Souriau, 1989; Berri et al., 2009). Several studies have reported the

prevalence of C. pecorum; in Germany, it was 47 % in sheep (Lenzko et al., 2011), while

in Egypt, it was 6.7 % in sheep and 50 % in goats (Osman et al., 2011). The zoonotic

potential of C. pecorum is unknown (Longbottom and Coulter, 2003; Robertson et al.,

2010).


Species of Chlamydia have a unique life cycle, with alteration between two

morphological forms, an elementary body (EB) and a reticulate body (RB) (Fig. 1-8)

(Longbottom and Coulter, 2003). The EBs are small (approximately, 0.3 µm in

diameter), round, electron dense, non-replicating, extracellular infectious forms of the

organism (Matsumoto, 1973; Eb et al., 1976). The RBs are larger (0.5 - 1.6 µm in

diameter) and their cytoplasm appears granular with diffuse, fibrillar nucleic acids

(Plaunt and Hatch, 1988). RBs are non-infectious and they are bounded by an inner

and outer-membrane resembling other gram-negative bacteria. Their surfaces are

covered with projections and rosettes that extend from the bacterial surface through

the inclusion membrane, similar to those on EBs but at a higher density (Matsumoto,

1982; Abdelrahman and Belland, 2005).


69

Figure 1-8: Chlamydial development cycle (Adapted from Longbottom and Coulter, 2003). In pregnant animals, elementary bodies (EBs) enter the placental cells by endocytosis, inside a vacuole or inclusion body, which is formed out of the placental cell wall. EBs transformed into metabolically active reticulate bodies (RBs) that replicate by binary fission inside the inclusion body. When the inclusion body occupies most of the cell volume, the RBs transformed back to EBs, which are then released upon cell lysis and infect other cells.

The life cycle is initiated with the endocytosis of EBs by eukaryotic cells. On

entering the host cell, RBs develop from EBs via numerous morphologically

intermediate stages so that by 8 - 12 h after infection, almost pure RB populations are

seen (Moulder, 1991). The mature RBs undergo multiplication by binary fission. The

phagocytic membrane surrounding the ingested EB becomes the inclusion membrane,

which now encloses the micrology of dividing RBS (Moulder, 1991). After division (12 -

24 h depending on the species), RBs revert back to metabolically inactive, infectious

EBs, which are released by the cell through exocytosis (Longbottom and Coulter, 2003).

Species of Chlamydia are shed in faeces, urine, respiratory secretions, birth

fluids or placentas of infected animals (Rodolakis and Yousef Mohamad, 2010).


70

Transmission of C. abortus in ruminants can occur from ingestion of placenta or grass

contaminated by vaginal discharge and placenta (Rodolakis and Yousef Mohamad,

2010). The transmission of C. abortus to people generally occurs via inhalation of

infectious dust and aerosols inducing infection of the mucosal epithelial cells and

macrophages of the respiratory tract and eventually spread through blood stream to

various organs (Rodolakis and Yousef Mohamad, 2010).


Chlamydial abortions in small ruminants are primarily caused by C. abortus and

sometimes by C. pecorum, in combination with other co-factors such as nutrition,

parasites or animal breed (Mohamad and Rodolakis, 2010). After C. abortus infects its

host, it enters a latent phase where it causes no clinical signs and is undetectable

(Jones, 1995). The animal host produces cytokines in response to chlamydial infection,

specifically, interferon-gamma, which restricts the growth of the bacteria in host cells

in a dose dependant manner (Entrican et al., 2001). During latency, it is thought that

bacteria reside in the tonsils, from which they are spread by blood or lymph to other

lymphoid tissues (Jones and Anderson, 1988). During pregnancy, it is thought that

immune modulation releases the organisms from latency, allowing them to multiply,

which in turn initiates placental infection (Longbottom and Coulter, 2003). Placental

infection occurs at around day 60 of gestation, although pathological changes are not

seen until after day 90 of gestation (Buxton et al., 1990). The chlamydial invasion of

the placentome leads to aggressive inflammatory response, thrombotic vasculitis and

necrotic damage to the cotyledons and intercotyledonary membranes of the

placentome (Buxton et al., 1990; Longbottom and Coulter, 2003). Pathological changes

in the foetus consist of focal necrosis of the liver, lung, spleen and less frequently,

brain and lymph nodes (Buxton et al., 1990). The destruction of chorionic epithelium,

associated lesions and impairment to the placentome are enough to compromise the

maternal-foetal exchange of oxygen and nutrients, leading to foetal death

(Longbottom and Coulter, 2003). In addition, placental chlamydial infection induces

significant changes in hormone concentration, which can also contribute to premature

labour (Longbottom and Coulter, 2003). The abortion of the foetus occurs around 2 - 3


71

weeks prior to the expected term (Longbottom and Coulter, 2003). Following abortion,

the aborting females develop protective immunity that prevents them from aborting

due to chlamydial organism in subsequent pregnancies (Kerr et al., 2005).

Clinical signs associated with C. abortus infection in ewes and does include

abortion, stillbirth and retained placenta, which may lead to metritis (Rodolakis and

Yousef Mohamad, 2010). Infected ewes and does show no clinical signs prior to

abortion, although vaginal discharge is sometimes observed (Rodolakis and Yousef

Mohamad, 2010). Lambs and kids born live from infected females may have arthritis,

conjunctivitis and pneumonia (Rodolakis and Yousef Mohamad, 2010). In male

animals, C. abortus can reach the seminal vesicles and cause epididymitis, while in

non-pregnant female animals, infections generally develop into an asymptomatic form

(Waldhalm et al., 1971). In people, clinical signs of C. abortus infection include malaise,

influenza-like illness, mild dry cough and dyspnoea (Rodolakis and Yousef Mohamad,

2010). Pregnant women may experience lower abdominal pain, followed by abortion

and sometimes severe complications such as acute renal failure, disseminated

intravascular coagulation, or respiratory distress, necessitating mechanical ventilation

(Rodolakis and Yousef Mohamad, 2010).

Chlamydia pecorum is commonly found in the digestive tract of healthy

ruminants (Clarkson and Philips, 1997), however, some have been isolated from ovine

and caprine abortion cases in Morocco, Egypt and France (Rekiki et al., 2004; Osman et

al., 2011). The common clinical signs of C. pecorum are diarrhoea, conjunctivitis,

arthritis, encephalitis, orchitis, and pneumonia in small ruminants (Fukushi and Hirai,

1992; Berri et al., 2009; Mohamad and Rodolakis, 2010). Also, C. pecorum can be

spread from the intestines through blood circulation, as a result of unknown physio-

pathological changes, and may reach the placenta, where they induce abortion

(Osman et al., 2011).

1.7.4 Diagnosis

There are two main approaches for diagnosing Chlamydia species in mammals:

(i) by identification of the agent using smears, antigen detection, DNA, tissue sections


72

and isolation of the agent by cell culture, and (ii) by serological tests such as

complement fixation test and ELISA. The choice of the test depends on the type of

sample received (blood, placental membranes, foetal tissues, swabs), organism

viability, presumptive diagnosis and clinical history (Sachse et al., 2009). A presumptive

diagnosis of infection can be made if the abortion occurs in the last 2 to 3 weeks of

gestation and by the presence of gross pathology of both the intercotyledonary

membranes and the cotyledons upon examination of fresh placenta (Stuen and

Longbottom, 2011). This can be confirmed by microscopic examination of smears

made from infected cotyledons prepared using a modified Ziehl-Neelsen, Giemsa,

Gimenez, or Machiavello procedure (Longbottom and Coulter, 2003; Sachse et al.,

2009). Smears can also be made from vaginal swabs of females, which have aborted

within the previous 24 h, or from the moist fleece of a freshly aborted or stillborn lamb

(Longbottom and Coulter, 2003). Chlamydia abortus and rickettsia (Coxiella burnettii)

have similar morphology and staining characteristics and therefore, further tests such

as fluorescent antibody tests using a specific antiserum or monoclonal antibody are

useful for identification of C. abortus in smears (Longbottom and Coulter, 2003).

Antigen detection methods also include immunohistochemical staining of tissue

sections using specific monoclonal antibodies against dominant chlamydial surface

antigens (Stuen and Longbottom, 2011).

Serological tests based on complement fixation tests (CFT) may be used to

detect a rise in antibody titre to C. abortus after abortion or stillbirth (Longbottom and

Coulter, 2003). For this, paired blood samples taken at the time of abortion and then at

least 3 weeks later is used for detection. However, because C. abortus shares common

antigens with C. pecorum and some Gram-negative bacteria, detection using CFT can

be problematic due to antigenic cross-reactivity (Longbottom and Coulter, 2003).

DNA-based techniques provide an alternative approach for verifying the

presence of chlamydial organism. Over recent years, a variety of molecular tools

including conventional PCR, qPCRs and DNA microarray technology, have been

developed and used for specific detection of chlamydial organisms (Sachse et al.,

2009). qPCR assays have been the preferred method in diagnostic laboratories because


73

of their rapidity, high throughput and ease of standardisation (Sachse et al., 2009). The

targets of these tools include 16S rRNA, 16-23S intergenic spacer region, 23S rRNA,

and the outer membrane protein gene (ompA) (Sachse et al., 2009).


Chlamydiosis is usually treated with tetracyline. If ovine enzootic abortion is

suspected to be present in a flock of pregnant ewes, long-acting oxytetracycline (20

mg/kg body weight, intramuscularly) may be given to reduce severity of infection and

losses resulting from abortion (Longbottom and Coulter, 2003; Stuen and Longbottom,

2011). Treatment should be given soon after day 95 - 100 of gestation, when

pathological changes start to occur in the placenta, with subsequent treatment given

at 2 week intervals until the time of lambing (Longbottom and Coulter, 2003; Stuen

and Longbottom, 2011). Tetracyline does not effectively eliminate the infection nor

reverse any pathological damage in the animals, but reduces the disease in the flock

(Longbottom and Coulter, 2003).

In people with chlamydial infections, treatment includes supportive therapy

(fluids, oxygen), measures to combat toxic shock and administration of tetracylines,

erythromycin and clarithromycin (orally or parenterally) depending on clinical severity

(Stuen and Longbottom, 2011).

For control, good hygiene such as hand washing is essential before tending to

other animals. Chlamydia is shed in faeces, urine, respiratory secretions, birth fluids,

and placentas of infected symptomatic and asymptomatic animals and as EBs do not

survive very long, they require close contact for transmission (Rodolakis and Yousef

Mohamad, 2010). After abortion, the infected ewes or does should be immediately

isolated, all dead newborns, placentals and bedding safely disposed of and lambing

pens cleaned and disinfected to limit the risk of spreading contamination (Longbottom

and Coulter, 2003). Pregnant women should avoid contact with pregnant or aborting

ruminants and, if possible, sheep or goats if OEA is suspected in a flock.


74

1.8 Aims of the present study

Given the lack of knowledge of parasitic infections in sheep, goats and fish in

PNG, the main objectives of this thesis were to:

(i) Investigate the prevalence of gastrointestinal parasites in faecal samples from

sheep and goats by light microscopy;

(ii) Detect Haemonchus contortus, Teladorsagia circumcincta, and Trichostrongylus

spp. in faecal samples of sheep and goats using molecular tools;

(iii) Detect Eimeria spp. in faecal samples of sheep and goats using molecular tools;

(iv) Investigate the prevalence and perform molecular characterisation of

Cryptosporidium spp. and Giardia spp. in sheep, goats and fish;

(v) Investigate the prevalence and characterise the species of anisakid nematodes in

fish using morphological and molecular tools; and

(vi) Investigate the prevalence of Chlamydia abortus and C. pecorum in faecal

samples of sheep and goats using molecular tools.

Chapter 2

2. Materials and Methods


2.1 General background of the study The samples for the present study were collected in various locations in PNG

(Fig. 2-1). Most of the laboratory components of this study were conducted at

Murdoch University, but some analyses were carried out at Divine Word University

(DWU) in Madang, PNG and at the University of Western Australia, Perth, Australia.

Specifically, coprological analyses of faecal samples from sheep and goats were

performed at DWU in April 2011 and scanning electron microcopy of anisakid larvae

was conducted at the Centre for Microscopy Characterisation and Analysis (CMCA) at

the University of Western Australia in May 2012. Light microscopy analysis of anisakid

larvae and histological analysis of fish tissues were conducted at the School of

Veterinary and Life Sciences at Murdoch University. All molecular work was conducted

in the State Agriculture and Biotechnology Centre (SABC) laboratory at Murdoch

University between September 2011 and October 2013.

2.2 Human and animal ethics approval

A questionnaire survey for sheep and goat farmers was approved by Murdoch

University Human Research Ethics committee (Permit/Project no: 2010/174). Faecal

sample collection from sheep and goats and collection of fish was approved by

Murdoch University Animal Ethics Committee (Permit no: R2368/10).

2.3 Sampling

2.3.1 Study locations for sheep and goats

PNG has extremely variable agro-ecological conditions, although, it is located in

the tropics. It has at least three broad climatic zones, namely, wet lowland (< 1, 200

m), dry lowland (< 1, 200 m) and moderately wet highland (> 1, 200 m) areas

(Quartermain, 2004b). The wet lowland areas receive from 2, 000 - 5, 000 mm of

rainfall annually, while dry lowland areas receive less than 2, 000 mm of rainfall and

are characterized by pronounced dry periods of up to six months of the year

(Quartermain, 2004b). The highland areas exhibit temperate climate with occasional

frosts above 1, 800 m and rainfall between 2, 000 and 2, 300 mm with high seasonality

(Quartermain, 2004b).


77

The study locations for sheep and goats were chosen because they represented

the largest flocks in the country (Fig. 2-1). As there was no available demographic

information on the small ruminant farms, the farms were chosen based upon

consultation with agricultural scientists at the National Agricultural Research Institute

(NARI).

Figure 2-1: Study locations for sheep, goats and fish in the present study. The dots on the map represent sites where sheep and goats were collected. Research institutional farms were in Labu (insert 1) and Tambul (insert 6). The public institutional farm was in Baisu (insert 6). The government farm was in Menifo (insert 5). Smallholder farms were in Chuave (insert 4); Daulo, Goroka, Benabena and Korefeigu (insert 5). The stars represent sites where fish were collected. Cultured freshwater fish were obtained from ponds in Bathem (insert 2), Kundiawa (insert 4), Asaro (insert 5) and Mumeng (insert 1). Wild freshwater fish were collected in Ramu River near Sausi (insert 3) and Sepik River near Pagwi (insert 2). Wild marine fish were collected in Bilbil and Madang (insert 3), and Pilapila and Tavana (insert 7).


78

The chosen study locations were located in two broad agro-climatic regions:

the warm and wet lowland area. Specific study site is Labu in Morobe Province.

the cool and moderately wet highlands region. Specific study sites are

Korefeigu, Benabena, Menifo, Goroka and Daulo in Eastern Highlands Province

(EHP); Chuave in Simbu Province; and Baisu and Tambul in Western Highlands

Province (WHP).

The study locations were divided into 5 groups based on the farm management

systems (Table 2-1). These include:

(i) Lowland research institutional farm (Labu),

(ii) Highland research institutional farm (Tambul),

(iii) Public institutional farm (Baisu),

(iv) Government station farm (Menifo),

(v) Smallholder farms (Benabena, Korefeigu, Goroka, Daulo and Chuave).

Table 2-1: Sampling locations and farm information for the chosen sheep and goat flocks in the present study. The combined numbers of sheep and goats at the time of sampling in Labu, Baisu, Tambul and Menifo were 125, 70, 143 and 55, respectively. Smallholder farmers kept 3 - 19 animals per herd. The asterisk (*) refers to flocks that graze free range over a wide area near road-sides, gardens, hills etc. References for climate data: Quartermain, 2004b and Bourke, 2010. S = sheep, G = goats, O = others (such as pigs, dogs, chickens, or cattle).

Study locations

Mean altitude (m)

Mean annual temperature (°C)

Mean annual rainfall (mm)

Farm ownership

Farm size (ha)

Animals on property

Labu 0 26 > 4000 Research 20 - 60 S, G, O

Tambul 2320 13.8 3000 Research 20 - 60 S, G

Menifo 1608 20.1 1000 - 1500 Government 20 - 60 S, G, O

Baisu 1730 18.3 3000 Public 20 - 60 S, G

Chuave 1530 20.4 2000 Smallholder Varies* G, O

Daulo 2000 20.1 2000 Smallholder Varies* S, G, O

Goroka 1600 20.1 1500 Smallholder Varies* S, G, O

Korefeigu 1600 20.1 1500 Smallholder Varies* S, G, O

Benabena 1600 20.1 1500 Smallholder Varies* S, G, O

2.3.2 Study locations for fish

Fish were collected from four cultured freshwater ponds, two large river

systems and marine environments in various locations throughout PNG (Fig. 2-1). Both


79

of the river systems are widely used by people for transportation and for sourcing fish.

For marine fish, waters near the township of Madang (Madang province) and Rabaul

(East New Britain province) were chosen, as they are centrally located and relatively

easily accessible.

Specifically, these locations included:

Mumeng in Morobe Province - a cultured freshwater pond and hatchery that

actively distributes fingerlings to local customers,

Kundiawa in Simbu Province - a cultured freshwater fish-pond, which was built

in the centre of the town,

Asaro in EHP - a cultured freshwater fish-pond, which was set up in a forested

area just outside the village,

Betham in East Sepik Province - a cultured freshwater fish-pond, which was

built in the grassland area near the village,

Sepik River near Pagwi in East Sepik Province for wild freshwater fish,

Ramu River near Sausi in Madang Province for wild freshwater fish,

Madang-coastal areas near Madang town, Madang Province for wild marine

fish,

Bilbil, Madang Province for wild marine fish,

Pilapila, East New Britain (ENB) Province in for wild marine fish, and

Tavana, ENB Province for wild marine fish.

2.4 Survey questionnaire

The sheep and goat owners/managers completed questionnaires regarding

farm management and animal health programs for their flocks (sample questionnaire

form is attached in Appendix A).

Farm management

The flocks from the three institutional farms (Labu, Baisu and Tambul) and the

government farm (Menifo) grazed pasture in fenced areas (20 - 60 ha) at daytime. At

night-time, the flocks were kept in houses with wooden, slatted floors in institutional


80

farms and on the ground in the government farm. At the time of sample collection, the

combined numbers of sheep and goats in Labu, Tambul, Baisu and Menifo were 125,

143, 70 and 55, respectively. The subsistence farmers kept few animals, usually less

than 20, which grazed free range or were tethered and housed at night on slatted

floors or on the ground underneath the farmer’s house (Fig. 2-2).

Feeding system

Most animals grazed on native grasses and shrubs. Smallholder farmers also

fed their animals with starchy vegetables, mostly sweet potatoes. The interviewed

farmers also indicated that there were feed shortages due to shortage of pasture for

grazing, fires or drought. The animals drank from troughs, sourced from main water

supplies or rainwater tanks, rainwater run-off or ponds.

Herd health programs

Hygiene and management levels for animal housing were sub-optimal. For

example, the floors of the houses where animals were kept at night-time were

unclean. The animals were penned on dirty floors, bare ground or on bare concrete

floors. The smallholder farmers did not shear their sheep as they did not have the

resources for it. Most farm managers reported that the most common signs of illness

in their animals were diarrhoea and coughing, followed by itching and hair loss. Most

smallholder farmers did not know about causes of diseases in their sheep and goats or

know about or use anthelmintic drugs for controlling gastrointestinal parasite

infections. For instance, a farmer in Benabena reported the death of his entire flock of

sheep (n = 25) and noticed nematode worms in the gut of a dead sheep. The three

large institutional flocks were drenched with benzimidazole (Panacur) nominally at

bimonthly intervals. At the time of sampling animals had been drenched two months

previously in Labu, four months previously in Baisu and Tambul and six months

previously in Menifo.


81

Figure 2-2: Pictures of sheep and goat farming in PNG. A. Staffs of National Agriculture Research Institute (NARI) in Tambul. B. Lambing pens at NARI, Tambul. C. Sheep tethered and housed under the owner’s house in Goroka. D. A subsistence farmer tethering her goats in Daulo. E. A wooden slatted floored night house for sheep and goats in Korefeigu. F. Sheep and goats housed together in a smallholder farm in Benabena.


82

Farm types

The flocks at Labu and Tambul are managed by the NARI. Both had relatively

high numbers of animals (Labu = 125, Tambul = 143). Labu is in Morobe Province,

which is located in a humid lowland area with very high rainfall. The flocks in Labu are

made up of PNG Priangan sheep and PNG goat genotype, which possibly came from

the PNG University of Technology in Lae and Erap in Markham, which were established

in 1970-80s. Tambul’s climate is wet and cool with high rainfall per annum (2500 mm).

The Highlands Halfbred sheep flock in Tambul was thought to have been established

from flocks from Aiyura and Menifo and PNG genotype goats from Simbu Province.

The flocks at Baisu are managed by a correctional service (a government

institution). The foundation flock for Baisu was provided from Tambul. There were

approximately 70 sheep and goats available during sample collection.

Menifo is a government research and breeding station for sheep. It was

established in 1975. It had 55 sheep and 15 goats at the time of sampling.

The flocks in Benabena, Goroka, Korefeigu, Daulo and Chuave are owned by

smallholder farmers. These flocks were thought to have been established from flocks in

Menifo and Aiyura government breeding stations. Smallholder flocks were established

much earlier than those in research institutional farms (Labu and Tambul) and

consisted of Highlands Halfbred sheep and PNG genotype goats.

2.5 Animals

2.5.1 Sheep and goats

For the present study, a total of 504 faecal samples were collected directly

from the rectum of sheep (n = 276) and goats (n = 228) and stored in 25 mL screw top

plastic containers (Table 2-2). Most animals sampled were adults. No lambs or goat

kids were sampled as only a few were present during the sampling period and it was

difficult to obtain faecal samples from them. During sampling, the following factors

were recorded for each animal; faecal moisture and consistency and clinical symptoms

such as active versus lethargic, bright pink versus pale mucous membranes, coughing,


83

chest congestion and diarrhea. Almost all the faeces collected were hard, dry pellets or

soft moist pellets. On a few occasions, liquid/fluid faeces were encountered but they

were either too small in quantity or too watery and difficult to collect.

Table 2-2: Number (N) of sheep and goat samples collected in the present study.

Type of farm Sheep (N) Goat (N)

Research Institute (Labu) 40 43

Research Institute (Tambul) 115 35

Public Institution (Baisu) 27 39

Government Station (Menifo) 40 6

Smallholder 54 105

Total 276 228

Handling of faecal samples

All faecal samples were processed in a NARI laboratory in Labu, Morobe

Province. Samples that were collected from the flocks in Labu were taken directly to

the laboratory and processed within a day. In contrast, samples collected from the rest

of the study sites were kept in ice-filled Coleman Coolers (for up to 10 days), until

transported to the laboratory for processing. At Labu, each faecal sample from a 25 mL

screw top container was placed into a 2 mL Eppendorf tubes and preserved in 70 %

ethanol for molecular screening. Excess samples were left in the 25 ml container for

morphological analyses by a faecal flotation technique (Whitlock, 1948). All samples

were kept at 4 °C until shipment or analysis.

2.5.2 Fish

A total of 614 fish from cultured freshwater, wild freshwater and wild marine

environments were collected (Fig. 2-3). Cultured fish (n = 133) included three species,

which were collected from four smallholder cultured freshwater fish-ponds in

Mumeng, Asaro, Kundiawa and Bathem (Table 2-3).


84

Figure 2-3: Pictures of fishing activities in PNG. A. A fish-pond in Bathem village. B. A fish farmer in Sausi. C. Freshwater fish market in Pagwi near the Sepik River. D. The field team processing fish near a river in Bathem. E & F, Toilet huts over the sea and the estuary, respectively, in Madang.


85

Wild freshwater fish (n = 205) included six species and were collected from

Ramu and Sepik Rivers, while 276 fresh marine fish, consisting of 16 species were

bought from local fishermen in Bilbil, Madang, Pilapila and Tavana (Table 2-3).

Table 2-3: Cultured freshwater, wild freshwater and marine fish species collected in the present study.

Cultured freshwater fish Locations

Kundiawa Asaro Mumeng Bathem Total

Nile tilapia (Oreochromis niloticus) 36 20 27 - 83

Common carp (Cyprinus carpio) - 11 32 - 43 Mozambique tilapia (Oreochromis mossambicus) - - - 7 7

Total 36 31 59 7 133

Wild freshwater fish Ramu River Sepik River Total

Silver barb (Puntius gonionotus)

13 39

52

Highfin catfish (Neoarius berneyi)

- 20

20 Mozambique tilapia (Oreochromis mossambicus)

- 15

15

Pacu (Colossoma bidens)

- 34

34 Indo-Pacific tarpon (Megalops cyprinoides)

- 70

70

Redtail catfish (Phractocephalus hemioliopterus)

- 14

14

Total

13 192 205

Wild marine fish Bilbil Madang Pilapila Tavana Total

Bigeye scad (Selar crumenophthalmus) 46 - 60 - 106

Bigeye trevally (Caranx sexfasciatus) 4 - - - 4

Blackfin barracuda (Sphyraena qenie) 9 - - - 9 Coachwhip trevally (Carangoides oblongus) - - - 1 1 Indo-Pacific tarpon (Megalops cyprinoides) 4 - - - 4

Mackerel scad (Decapterus macarellus) 5 - 24 - 29

Oblong silver biddy (Gerres oblongus) 1 - - 54 55

Oriental bonito (Sarda orientalis) - 4 - - 4

Pinjalo snapper (Pinjalo pinjalo) - - 1 - 1

Rainbow runner (Elagatis bipinnulatus) - 5 - - 5

Reef needlefish (Strongylura incisa) - 4 - - 4

Slender pinjalo (Pinjalo lewisi) - - - 14 14 Spanish mackerel (Scomberomorus maculatus) - 3 - - 3

Talang queenfish (Scomberoides commersonnianus) - 2 - 2

Wahoo (Acanthocybium solandri) - 1 - - 1

Yellow fin tuna (Thunnus albacares) - 34 - - 34

Total 69 51 87 69 276


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On average, the time when fish were at the stalls before being sold and the

time lag between purchasing and processing the fish was approximately 4 h. The only

live fish collected were from the aquaculture farms. These were euthanized by ice

slurry. Length and weight of each fish were measured. Fish were necropsied, checked

for worms under white light and further dissected. The stomach and intestinal walls

were removed using a scalpel blade. Parts of the gut (stomach and intestinal walls)

tissues were placed into 2 mL Eppendorf tubes and preserved in 70 % ethanol for

molecular screening. Remaining stomach and intestinal tissues were fixed in 10 %

buffered formalin for histological analysis. The stomach and intestinal walls were

collected because protozoan parasites (Cryptosporidium and Giardia) attach to the

surface epithelia of these regions of the gut and cause a range of histological

abnormalities (Chen et al., 2012). All samples were stored at 4 °C in PNG until sample

collection was completed.

2.6 Shipment of biological samples

Preserved samples were packaged according to the International Air Transport

Association (IATA) standard of shipment of biological samples and transported by air to

Perth, Western Australia. Appropriate permits were obtained in PNG for export and in

Australia for import.

2.7 Parasitology

2.7.1 Faecal worm egg count

All faecal worm egg counts were performed in Madang, PNG, using a modified

McMaster technique (Whitlock, 1948). For this method, approximately, 2 g of faeces

were weighed and placed in a 60 mL mixing jar and 2.5 mL of tap water was added to

soften the faecal pellets. The faeces were mashed up using a pair of forceps and

allowed to soak for more than 1 h. A flotation salt solution (saturated sodium chloride

solution with specific gravity 1.20 – 1.25) was added to the sample to make a final

volume of 50 mL solution. The faecal suspension was mixed vigorously using a tongue

depressor until a homogenous solution was obtained. Using a pipette, 0.6 mL of

solution were drawn out from the center of the mixed faecal suspension and added to


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the counting chamber of a Whitlock Paracytometer slide. The eggs were allowed 10

minutes (maximum time) to float up under the glass before counting at 40x

magnification using a light microscope (Zeiss Axio Scope). All visible eggs within the

double line boundaries of the Whitlock Paracytometer counting chamber were

identified and recorded.

Parasites were identified morphologically to genus, or (in the case of

pathogenic trichostrongyles) to superfamily level (superfamily = Trichostrongyloidea)

using published keys (Soulsby, 1965) (Fig. 2-4). Parasite egg load was expressed as eggs

per gram faeces (EPG). The volume of the flotation fluid used in the examinations was

50 mL and the fluid volume examined in the counting chamber was 0.3 mL. Since EPG

is calculated using Equation [1], the minimum EPG count in our analyses was 83 eggs

per gram and occurred when only one egg was observed in the counting chamber.

[1]

Figure 2-4: Trichostrongylid egg (left) and Eimeria oocyst (right) at 40x magnification.

2.7.2 Morphological analysis of anisakid nematodes

Whole nematodes were cleared in lactophenol for more than 48 h and

individually mounted onto microscope slides. The body lengths of the nematodes were

directly measured. Images were taken with an Olympus BX50 light microscope

equipped with Olympus DP70 Camera at 40x and 100x magnification. The following

features were measured: body width, oesophagus length, ventriculus length and

mucron length. Morphological identification was conducted according to keys

previously reported (Berland, 1961; Cannon, 1977; Shamsi et al., 2009a, b).

Scanning electron micrographs (SEMs) were taken for representative

specimens to study further morphological details. SEMs were obtained on a Phillips

total volume [mL]EPG eggs counted

( examined volume [mL] weight of faeces [g])


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XL30 scanning electron microscope at the Centre for Microscopy Characterisation and

Analysis (CMCA) at the University of Western Australia. For SEM, parasite samples

were fixed in 2 % glutaraldehyde and 1 % paraformaldehyde in phosphate buffer saline

(PBS) for 60 minutes at 4 °C and washed twice with PBS (pH = 7.4) in 1.5 mL Eppendorf

tubes. Samples were dehydrated using a PELCO Biowave microwave processor

(TedPella Inc., Redding, CA, USA) by passage through increasing ethanol

concentrations in water (33 %, 50 %, 66 % and 100 %), followed by two washes in dry

acetone. Samples were then dried in a critical point dryer (Emitech 850, Quorum

Technologies, Ashford, UK), attached to aluminium sample holders and coated with a 5

nm thick platinum coating to enable surface electrical conduction.

2.8 DNA isolation

2.8.1 Isolation of genomic DNA from faeces

Genomic DNA was extracted directly from faeces using a PowerSoil® DNA

isolation kit (MO BIO laboratories, Carlsbad, California, USA). The kit is designed to

remove faecal PCR inhibitors, which potentially increases the DNA quality.

Approximately, 0.25 grams of each faecal sample were placed in a Powerbead tube

and then mixed by vortexing. To ensure complete lysis of any Cryptosporidium oocysts

that may have been present, five freeze thaw cycles were conducted, which consisted

of dipping the sample into liquid nitrogen for approximately 10 seconds until frozen

and then incubating at 95 °C until thawed. Sixty microliters of solution C1 were then

added to the Powerbead tubes containing the sample and the mixture was again

mixed by vortexing. The Powerbead tube was secured horizontally onto a flat-bed

vortex pad with tape and vortexed at maximum speed for 10 minutes and then

centrifuged at 10, 000 x g for 30 seconds at room temperature. The supernatant was

then transferred to a clean 2 mL collection tube. To this, 250 µL of solution C2 were

added and the contents were mixed by vortexing for 5 seconds and incubated at 4 °C

for 5 minutes. After incubation, the tube was centrifuged at room temperature for 1

minute at 10, 000 x g and approximately 600 µL of supernatant was transferred to a

clean 2 mL collection tube and 200 µL of solution C3 were added to it. The tubes were

vortexed briefly and incubated at 4 °C for 5 minutes. Following incubation, the tubes


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were centrifuged at room temperature for 1 minute at 10, 000 x g. Up to 750 µL of

supernatant were collected in a clean 2 mL collection tube and 1, 200 µL of solution C4

were added to the supernatant. The solutions were mixed by vortexing for 5 seconds.

Approximately, 675 µL of the supernatant mixture were loaded onto a spin filter,

which captures the DNA. The tube was centrifuged at 10, 000 x g for 1 minute at room

temperature. The flow-through was discarded. An additional 675 µL of supernatant

mixture were loaded onto the spin filter and the process was repeated until all the

remaining supernatant were loaded onto the spin filter and centrifuged. This was

followed by an addition of 500 µL of solution C5 (ethanol wash solution) to rinse the

captured DNA by centrifugation at room temperature for 30 seconds at 10, 000 x g.

The flow-through was discarded. The spin filter tubes were centrifuged again and the

spin filter was placed in a clean 2 mL collection. To concentrate the DNA, 50 µL of

solution C6 (sterile DNA elution buffer) (instead of the recommended 100 µL) was then

added to the centre of the white filter membrane of the spin filter, and the tube was

centrifuged at room temperature for 30 seconds at 10, 000 x g to elute the DNA. The

spin filter was discarded and the tube containing the DNA was stored at -20 °C.

2.8.2 Isolation of genomic DNA from anisakid larvae

A Qiagen DNeasy® blood and tissue kit (Catalogue number: 69504, Qiagen,

Hilden, Germany) was used to isolate DNA from the anisakid nematodes analysed in

the present study. The kit contains InhibitEX® tablets that remove PCR inhibitors from

the DNA. Also, the kit includes a tissue lysis step using the enzyme, Proteinase K, to

digest protein and remove contamination from preparations of DNA. The protocol

(spin-column protocol) for the purification of total DNA from animal tissues on page 28

of the DNeasy® blood and tissue handbook was followed with minor modifications.

Prior to DNA extraction, each nematode larva was cut into small pieces to

enable more efficient lysis. Approximately, 25 mg of cut sample was placed in a 1.5 mL

microcentrifuge tube and 180 μL Buffer ATL and 20 μL Proteinase K were added. The

sample was mixed thoroughly by vortexing and incubated at 56 °C for 3 h for complete

tissue lysis. Several times during incubation, the tube was vortexed briefly to disperse

the sample. After incubation, the tube was vortexed for 15 seconds followed by

http://en.wikipedia.org/wiki/Nucleic_acid


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addition of 200 μL Buffer AL and thorough mixing by vortexing. The mixture was

pipetted into the DNeasy® Mini spin-column within a 2 mL collection tube. The tube

was centrifuged at 10, 000 x g for 1 minute. The flow-through and collection tube was

discarded. The DNeasy® Mini spin-column was placed in a clean 2 mL collection tube.

Five hundred µL of buffer AW1 were loaded onto the DNeasy® Mini spin-column and

centrifuged at 10, 000 x g for 1 minute. Again, the flow-through and the collection tube

were discarded. The DNeasy® Mini spin-column was placed in another clean 2 mL

collection tube and 500 μL of buffer AW2 were loaded onto it. The column was

centrifuged at 20, 000 x g for 3 minutes. Again the flow-through and the collection

tube were discarded. The DNeasy® Mini spin-column was placed in a clean 1.5 mL

collection tube and 50 μL (instead of the recommended 200 µL) of buffer AE were

loaded directly onto the DNeasy® Mini spin-column membrane. The tube was

incubated at room temperature for 1 minute, and then centrifuged at 10, 000 x g for 1

minute to elute the DNA. All extracted samples were stored at -20 °C until screening.

2.8.3 Isolation of genomic DNA from fish gut scrapings

Preserved intestines and stomachs were washed 5 times with water to remove

the ethanol and scraped using a scalpel blade. DNA was isolated from 0.25 grams of

the tissue scrapings using a PowerSoil® DNA isolation kit (MO BIO laboratories,

Carlsbad, California, USA) as described in Section 2.8.1. DNA was eluted in 50 µL of

elution buffer. All extracted samples were stored at -20 °C until screening.

2.9 DNA amplification

As a precaution and to avoid contamination with PCR product, the PCR

reactions were prepared in a designated pre-PCR area (separated from amplification

areas). PCR contamination controls were used including negative controls (no DNA).

Quantitative PCRs were performed on a Rotor-Gene 6000 thermocycler (Corbett

Research, Victoria, Australia) for detection of trichostrongyles, Giardia and Chlamydia

and on a Roche LightCycler® 480 thermocycler (Roche, Castle Hill, NSW, Australia) for

Eimeria. All single step and nested PCRs were performed in a Perkin Elmer Gene Amp

PCR 2400 thermocycler (Perkin Elmer, Foster City, CA, USA). The magnesium chloride

(MgCl2) and deoxynucleotide triphosphates (dNTPs) were ordered from (Fisher


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Biotech, Wembley, WA, Australia). All probes were synthesised by Biosearch

Technologies (Novato, CA, USA) and primers were ordered from InvitrogenTM

(http://www.lifetechnologies.com/au/en/home/brands/invitrogen.html).

2.9.1 Molecular detection of trichostrongylid nematodes by qPCR

A previously developed multiplex quantitative PCR (qPCR) assay was used (Yang

et al., 2014e). Primers and probe for Haemonchus were modified from Harmon et al.

(2007a). A fragment (92 bp) of the Haemonchus rRNA ITS1 region was amplified using

the forward primer HC-ITS F1 (5’-CATATACATGCAACGTGATGTTATGAA-3’), the reverse

primer HC-ITS R1 (5’-GCTCAGGTTGCATTATACAAATGATAAA-3’) and the probe (5’-FAM-

ATGGCGACGATGTTC-BHQ1-3’). The Haemonchus probe was prepared by substitution

of C-5 propynyl-dC (pdC) for dC and C-5 propynyl-dU (pdU) for dT to enhance base

pairing and duplex stability. A fragment (143 bp) of the Teladorsagia ITS2 region was

amplified using the primers TC-ITS2 F1 (5’-TCTGGTTCAGGGTTGTTAATGAAACTA-3’) and

TC-ITS2R1 (5’-CCGTCGTACGTCATGTTGCAT-3’) and the probe (5’- CAL Fluor Orange 560

– TGTGGCTAACATATAACACTGTTTGTCGA- BHQ1-3’). A fragment of Trichostrongylus

ITS1 region (114 bp) was amplified using TS ITS1 F1 (5’-AGTGGCGCCTGTGATTGTTC-3’),

TS ITS1 R1 (5’-TGCGTACTCAACCACCACTA-3’) and the probe (5’-CAL Fluor Red 610–

TGCGAAGTTCCCATCTATGATGGTTGA-BHQ2-3’).

An internal amplification control (IAC) was included in this qPCR assay to

monitor faecal inhibition. An IAC is a non-target DNA sequence present in the same

sample reaction tube which is co-amplified simultaneously with the target sequence

(Hoorfar et al., 2003). Inhibition can be due to malfunction of the thermal cycler,

incorrect PCR mixture, poor polymerase activity and the presence of inhibitory

substances in the sample matrix (Hoorfar et al., 2003). Thus, in a PCR with an IAC, a

control signal will always be produced even when there is no target sequence present

and when neither IAC signal nor target signal is produced, the PCR has failed.

In this PCR assay, an IAC consisting of a fragment of a coding region from

Jembrana Disease Virus (JDV) cloned into a pGEM-T vector (Promega, Madison, WI,

USA) was used, as previously described (Yang et al., 2013). The IAC primers were JDVF

(5’-GGTAGTGCTGAAAGACATT-3’) and JDVR (5’-ATGTAGCTTGACCGGAAGT-3’) and the

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probe was 5’-Cy5-TGCCCGCTGCCTCAGTAGTGC-BHQ2-3’ (Yang et al., 2013). Inhibition

in faecal samples was measured using the IAC, as the IAC was added to all faecal DNA

samples to detect any PCR inhibitors present in the extracted DNA. If any inhibition is

present in a sample, the IAC will not produce a signal.

The total volume of this assay was 15 μL and contained 3 mM MgCl2, 1μL of

2.5nM dNTPs, 1x PCR buffer, 1.0 U Kapa DNA polymerase (Kapa Biosystems, Cape

Town, South Africa), 0.2 μM each of forward and reverse primers, 0.1 mM probe, 0.2

μM each of forward and reverse IAC primers, 50 nM of the probe, 50 nM of IAC probe,

10 copies of IAC template and 1 μL of sample DNA. The PCR cycling conditions

consisted of a pre-melt at 95 °C for 3 minutes and then 45 cycles of 95 °C for 30

seconds, and a combined annealing and extension step of 60 °C for 45 seconds.

2.9.2 Molecular detection of Eimeria spp. by qPCR and nested PCR.

For molecular detection of Eimeria, a subset of samples from sheep and goats

were initially screened at the 18S rRNA locus by qPCR and then genotyped using a

nested PCR.

qPCR for Eimeria

A qPCR assay was used to screen for Eimeria species in faecal samples of sheep

and goats at the 18S rRNA locus as previously described (Yang et al., 2014d). The assay

consisted of a forward primer, Eim F1 (5’-CGAATGGCTCATTAAAACAGTTATAGTT-3’), a

reverse primer, Eim R1 (5’-CGCATGTATTAGCCATAGAATTACCA-3’) and a probe (5’-Joe-

ATGGTCTCTTCCTACATGGA-BHQ1-3’), which produced an 85 bp product (Yang et al.,

2014d). An internal amplification control (IAC) was included to check if any inhibition

was occurring in the sample (Yang et al., 2013) (see Section 2.9.1).

The total reaction volume in this assay was 15 μL. The reaction mixture

contained 5 mM MgCl2, 1 mM dNTP, 1x PCR buffer, 1.0 U Kapa DNA polymerase (Kapa

Biosystems, Cape Town, South Africa). 0.2 μM each of forward and reverse primers,

0.2 μM each of forward and reverse IAC primers, 50 nM of the probe, 50 nM of IAC

probe, 10 copies of IAC template and 1 μL of sample DNA (Yang et al., 2014d). The PCR

cycling conditions consisted of a pre-melt at 95 °C for 3 minutes and then 45 cycles of


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95 °C for 30 seconds, and a combined annealing and extension step of 60 °C for 45

seconds.

Eimeria 18S rDNA PCR-Sequencing

A nested PCR technique was used to amplify a subset of samples, which were

positive for Eimeria by qPCR at the 18S rRNA locus. The primers used for the

amplification of the 18S rRNA were those developed by Relman et al. (1996). For the

primary PCR, the forward primer was CYCF1E (5’-GGAATTCCTACCCAATGAAAACAGTTT-

3’) and reverse primer was CYCR2B (5’-CGGGATCCAGGAGAAGCCAAGGTAGG-3’)

(Relman et al., 1996). For the secondary PCR, the forward primer was CYCF3E (5’-

GGAATTCCTTCCGCGCTTCGCTGCGT-3’) and the reverse primer was CYCR4B (5’-

CGGGATCCCGTCTTCAAACCCCCTACTG-3’) (Relman et al., 1996).

The total reaction volume of the primary PCR assay was 25 µL, which contained

1 µL of genomic DNA, 2 mM MgCl2, 200 µM of each dNTP, 12.5 pmol each of forward

and reverse primers, 1x Kapa Taq buffer and 0.05 U/µL of Kapa Taq DNA polymerase

(Kapa Biosystems, Cape Town, South Africa). PCR was performed as previously

described (Pieniazek et al., 1996), with an initial denaturation of 95 °C for 4 minutes,

followed by 45 cycles of 95 °C for 30 seconds (denaturation), 55 °C for 30 seconds

(annealing), 72 °C for 90 seconds (extension) and a final extension at 72 °C for 10

minutes.

In the secondary PCR, a product of approximately 497 - 498 bp in length was

amplified using 1 µL of primary PCR product and nested forward CYCF3E and reverse

CYCR4B primers. The conditions were the same as for the primary PCR, except that the

annealing temperature was 60 °C.

2.9.3 Molecular detection of Cryptosporidium spp. using nested PCR

In the present study, nested PCRs were performed to screen for

Cryptosporidium species in faecal samples from sheep and goats and in guts of fish at

the 18 rRNA, actin and gp60 loci. A positive control (C. parvum) was included in all sets

of reactions.


94

Cryptosporidium 18S rRNA PCR

For the primary PCR, the forward primer, 18SiCF2 (5’-

GACATATCATTCAAGTTTCTGACC-3’) and the reverse primer, 18SiCR2 (5’-

CTGAAGGAGTAAGGAACAACC-3’) were used to produce a product with an approximate

length of 763 bp as previously described (Ryan et al., 2003). The total reaction volume

for this assay was 25 µL, which contained 1 µL of genomic DNA, 1.5 mM MgCl2, 200 µM

of each dNTP, 12.5 pmol each of forward and reverse primers, 1x Kapa Taq buffer and

0.05 U/µL of Kapa Taq DNA polymerase (Kapa Biosystems, Cape Town, South Africa).

The cycling conditions consisted of an initial hot start (94 °C for 5 minutes), followed by

48 cycles of 95 °C for 40 seconds (denaturation), 58 °C for 30 seconds (annealing) and

72 °C for 45 seconds (extension), and a final extension at 72 °C for 7 minutes.

In the secondary PCR, 1 µL of primary PCR product were included in the

reaction mixture containing forward primer 18SiCF1 (5’-CCTATCAGCTTTAGACGGTAGG-

3’) and reverse primer 18SiCR1 (5’-TCTAAGAATTTCACCTCTGACTG-3’) to produce a

product of approximately 587 bp in length. The conditions of the secondary PCR were

identical to those in the primary PCR.

For the samples that failed to amplify using the nested PCR described above, a

smaller fragment (298 bp) was amplified using the forward primer, 18SiF (5’-

AGTGACAAGAAATAACAATACAGG-3’) and reverse primer, 18SiR (5’-

CCTGCTTTAAGCACTCTAATTTTC-3’) as previously described (Morgan et al., 1997). PCR

amplification was performed in 25 µL volumes with 1 µL of genomic DNA, 10 pmol

each of forward and reverse primers, 200 µM concentration of each dNTP, 2 mM

MgCl2, 1x Kapa Taq buffer 0.05 U/µL of Kapa Taq DNA polymerase (Kapa Biosystems,

Cape Town, South Africa). The cycling conditions consisted of an initial hot start (94 °C

for 5 minutes), followed by 48 cycles of 95 °C for 30 seconds (denaturation), 60 °C for

30 seconds (annealing) and 72 °C for 40 seconds (extension) and a final extension at

72 °C for 7 minutes.

Cryptosporidium actin PCR


95

Attempts were made to screen Cryptosporidium-positive samples from piscine

hosts at the actin locus using a previously described assay (Ng et al., 2006), however,

amplifications were unsuccessful.

Piscine-derived Cryptosporidium actin PCR

A new set of semi-nested actin primers were designed using the software,

Primer 3 (http://frodo.wi.mit.edu/), based on actin gene sequences of piscine-derived

Cryptosporidium. Those primers were used in a semi-nested PCR protocol to amplify

samples from fish, which were Cryptosporidium-positive at the 18S rRNA locus.

For the primary PCR, the forward primer, Actinall F1 (5’-

GTAAAATACAGGCAGTT-3’) and the reverse primer, Actinall R1 (5’-

GGTTGGAACAATGCTTC-3’) were used to produce a product with an approximate

length of 392 bp. The total reaction volume for this assay was 25 µL, which contained

1 µL of genomic DNA, 2.0 mM MgCl2, 200 µM of each dNTP, 12.5 pmol each of forward

and reverse primers, 1x Kapa Taq buffer and 0.05 U/µL of Kapa Taq DNA polymerase

(Kapa Biosystems, Cape Town, South Africa). The cycling conditions consisted of an

initial denaturation step at 95 °C for 4 minutes followed by 45 PCR cycles, 95 °C for 30

seconds (extension), 46 °C for 30 seconds (annealing), and 72 °C for 30 seconds

(extension), with a final extension at 72 °C for 7 minutes.

In the secondary PCR, a product of approximately 278 bp in length was

amplified using 1 µL of primary PCR product and forward primer, Actinall F2 (5’-

CCTCATGCTATAATGAG-3’) and the Actinall R1 reverse primer described above. The

conditions for the secondary PCR were identical to those used in the primary PCR.

Cryptosporidium gp60 PCR

Cryptosporidium parvum and C. hominis positive samples were further

subtyped at the 60kDa glycoprotein (gp60) locus using a nested PCR assay as

previously described (Sulaiman et al., 2005). In the primary PCR, a fragment of the

gp60 gene (approximately 800 bp in length) was amplified using the forward AL3531

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96

(5’-ATAGTCTCCGCTGTATTC-3’) and reverse AL3533 (5’-GAGATATATCTTGGTGCG-3’)

primers (Peng et al., 2001; Sulaiman et al., 2005).

The total reaction volume for this assay was 25 µL, which contained 1 µL of

genomic DNA, 3.0 mM MgCl2, 200 µM of each dNTP, 12.5 pmol each of forward and

reverse primers, 1x Kapa Taq buffer and 0.05 U/µL of Kapa Taq DNA polymerase (Kapa

Biosystems, Cape Town, South Africa). PCR was performed under the following

conditions: 95 °C for 4 minutes followed by 40 PCR cycles, 95 °C for 48 seconds

(extension), 50 °C for 45 seconds (annealing), and 72 °C for 30 seconds (extension),

with a final extension at 72 °C for 10 minutes.

In the secondary PCR, a product of approximately 400 bp in length was

amplified using forward primer AL3532 (5’-TCCGCTGTATTCTCAGCC-3’), reverse primer

LX0029 (5’-CGAACCACATTACAAATGAAGT-3’) and 1 µL of the primary PCR product

(Sulaiman et al., 2005). The conditions of the secondary PCR assay were identical to

those in the primary PCR assay except that the annealing time was reduced to 45

seconds.

2.9.4 Molecular detection of Giardia spp. using qPCR and nested PCR

Samples from sheep, goats and fish were initially screened at the glutamate

dehydrogenase (gdh) locus using a qPCR assay, followed by attempts to genotype

Giardia by PCR and sequencing at the gdh, triphosphate isomerase gene (tpi) and beta

(β) giardin (bg) loci. However, amplifications using nested PCRs were unsuccessful.

Positive control DNA samples of G. duodenalis assemblage A, B and/or E were included

in all sets of reaction runs.

qPCR at the Giardia glutamate dehydrogenase (gdh) locus

For the qPCR assay, the forward primer, gdhF1 (5’-GGGCAAGTCCGACAACGA-

3’), the reverse primer gdhR1 (5’-GCACATCTCCTCCAGGAAGTAGAC-3’) and the probe

(5’-Quasar 670-TCATGCGCTTCTGCCAG-BHQ2-3’) were used to produce a product of

approximately 261 bp in length as previously described (Yang et al., 2014b). IAC was

included to check if any inhibition was occurring in the sample (Yang et al., 2013) (see

Section 2.9.1).


97

The total volume of the PCR mixture was 15 μL, which contained 5 mM MgCl2,

1 mM dNTPs, 1x PCR buffer, 1.0 U Kapa Taq DNA polymerase (Kapa Biosystems, Cape

Town, South Africa), 0.2 μM each of forward and reverse primers, 0.2 μM each of

forward and reverse IAC primers, 50 nM of the probe, 50 nM of IAC probe, 10 copies of

IAC template and 1 μL of sample DNA. The PCR cycling conditions consisted of a pre-

melt at 95 °C for 3 minutes and then 45 cycles of 95 °C for 30 seconds, and a combined

annealing and extension step at 60 °C for 45 seconds.

Semi-nested PCR at the Giardia gdh locus

Attempts were made to amplify Giardia-positive samples at the gdh locus as

previously described (Read et al., 2004). The semi-nested PCR assay involved an

external forward primer, GDHeF (5’-TCAACGTYAAYCGYGGYTTCCGT-3’), an internal

forward primer, GDHiF (5’-CAGTACAACTCYGCTCTCGG-3’) and a reverse primer, GDHiR

(5’-GTTRTCCTTGCACATCTCC-3’), which produced a product of approximately 432 bp in

length (Read et al., 2004).

In the primary PCR, the primers GDHeF and GDHiR were used. The total

reaction volume for this assay was 25 µL, which contained 1 µL of genomic DNA, 1.5

mM MgCl2, 200 µM of each dNTP, 12.5 pmol each of forward and reverse primers, 1x

Kapa Taq buffer and 0.05 U/µL of Kapa Taq DNA polymerase (Kapa Biosystems, Cape

Town, South Africa). The cycling conditions consisted of an initial hot start at 95 °C for

4 minutes, followed by 55 PCR cycles, 95 °C for 30 seconds (denaturation), 56 °C for 20

seconds (annealing), and 72 °C for 45 seconds (extension) and then a final extension at

72 °C for 7 minutes.

In the secondary PCR, 1 µL of primary PCR product and nested forward GDHiF

and reverse GDHiR primers were included to produce a product of 432 bp in length

(Read et al., 2004). The conditions for the secondary PCR were identical to the primary

PCR. However, the amplifications were not successful, even with variations to the

initial assay conditions. Those variations included:

[1] the addition of dimethyl sulfoxide (DMSO) at a final concentration of 5 %,

[2] the use of fresh aliquots of dNTPs, primers or Kapa Taq DNA polymerase,


98

[3] Kapa Taq DNA polymerase was replaced with Tth Plus DNA Polymerase

(Fisher Biotech Catalogue number: TP-1), and

[4] Testing a range of different PCR thermocyclers.

Nested PCR at the Giardia tpi locus

A nested PCR was used to amplify the triphosphate isomerase (tpi) gene of

Giardia positive isolates using primers complementary to the conserved sequences of

various Giardia parasites in the primary PCR and assemblage-specific primers in the

secondary PCR. Positive controls for G. duodenalis assemblages A, B and E were

included in all reaction runs.

In the primary PCR, primers AL3543 (5’-AAATIATGCCTGCTCGTCG-3’) and

AL3546 (5’-CAAACCTTITCCGCAAACC-3’) were used to amplify a product of

approximately 605 bp in length as previously described (Sulaiman et al., 2003). The

total reaction volume for this assay was 25 µL, which contained 1 µL of genomic DNA,

3 mM MgCl2, 200 µM of each dNTP, 12.5 pmol each of forward and reverse primers, 5

% DMSO, 1x Kapa Taq buffer and 0.05 U/µL of Kapa Taq DNA polymerase (Kapa

Biosystems, Cape Town, South Africa). The cycling conditions were 95 °C for 4 minutes,


(annealing) and 72 °C for 60 seconds (extension). The cycle was followed by a final

extension at 72 °C for 10 minutes.

In the secondary PCR, assemblage-specific primers and 1 µL of the primary PCR

product were used to screen for G. duodenalis assemblages A, B and E as previously

described (Geurden et al., 2008a; 2009). Listed below are the primers and their

annealing temperatures:

For the amplification of the tpi gene of assemblage A, primers Af 5’-

CGCCGTACACCTGTCA 3’ and Ar (5’-AGCAATGACAACCTCCTTCC-3’) were used to

amplify a product of approximately 332 bp in length. The annealing

temperature for this primer set was 64 °C (Geurden et al., 2008a).

For assemblage B, primers Bf (5’-GTTGTTGTTGCTCCCTCCTTT-3’) and Br (5’-

CCGGCTCATAGGCAATTACA-3’) were used to amplify a product of


99

approximately 400 bp in length. The annealing temperature for this primer set

was 62 °C (Geurden et al., 2009).

For assemblage E, primers Ef (5’-CCCCTTCTGCCGTACATTTAT-3’) and Er (5’-

GGCTCGTAAGCAATAACGACTT-3’) were used to amplify a PCR product of

approximately 388 bp in length. The annealing temperature for this primer set

was 67 °C (Geurden et al., 2008a).

The total reaction volume for each assemblage-specific PCR assay was 25 µL, which

contained 1 µL of genomic DNA, 3 mM MgCl2, 200 µM of each dNTP, 12.5 pmol each of

forward and reverse primers, 1x Kapa Taq buffer and 0.05 U/µL of Kapa Taq DNA

polymerase (Kapa Biosystems, Cape Town, South Africa). The cycling conditions were

95 °C for 5 minutes, followed by 45 cycles of 95 °C for 45 seconds (denaturation), 64 °C

for 45 seconds (annealing) for the assemblage A-specific primer or 62 °C for

assemblage B-specific primer or 64 °C for assemblage E-specific primer and 72 °C for 45

seconds (extension). The final extension was at 72 °C for 7 minutes.

Nested PCR at the Giardia β-giardin locus

Attempts were made to amplify the β-giardin gene using different nested PCR

protocols. Initially primers designed by Caccio et al. (2002) and Lalle et al. (2005b) were

used. Specifically, forward primer, G7 (5’-AAGCCCGACGACCTCACCCGCAGTGC-3’) and

reverse primer, G759 (5’-GAGGCCGCCCTGGATCTTCGAGACGAC-3’) were used in the

primary PCR (Caccio et al., 2002). For the secondary PCR, forward primer, βGiarF (5’-

GAACGAACGAGATCGAGGTCCG-3’) and the reverse primer, βGiarR (5’-

CTCGACGAGCTTCGTGTT-3’) were used (Lalle et al., 2005a).

In the primary PCR reaction, primers G7 and G759 were used to produce a

product of approximately 753 bp in length as previously described (Caccio et al., 2002).

The total reaction volume of this assay was 25 µL, which contained 1 µL of genomic

DNA 1.5 mM MgCl2, 200 µM of each dNTP, 12.5 pmol each of forward and reverse

primers, 1x Kapa Taq buffer and 0.05 U/µL of Kapa Taq DNA polymerase (Kapa

Biosystems, Cape Town, South Africa). The cycling condition consisted of an initial hot

start (95 °C for 4 minutes), followed by 45 cycles of 95 °C for 30 seconds


100

(denaturation), 65 °C for 30 seconds (annealing) and 72 °C for 60 seconds (extension),

and a final extension at 72 °C for 7 minutes. In the secondary PCR, a product of

approximately 511 bp in length was produced using 1 µL of primary PCR product and

nested primers βGiarF and βGiarR (Lalle et al., 2005b). The conditions of the secondary

PCR were identical to those used in primary PCR except that the annealing

temperature was 55 °C.

Amplification at the β-giardin was also attempted using primers designed by Dr.

Rongchang Yang, Murdoch University in a semi-nested PCR. Primers BGexF (5’-

CCCGACGACCTCACCCGCAGT-3’) and BGRev (5’-GCTCGGCCTTCTCGCGGTCG-3’) were

used in the primary PCR assay to produce a product of 682 bp in length. Primers BGinF

(5’-CCTTGCGGAGATGGGCGACACA-3’) and BGRev were used in the secondary PCR

assay to amplify a product of approximately 380 bp in length.

The total reaction volume for this PCR assay was 25 µL, which contained 1 µL of

genomic DNA in the primary PCR (1 µL of primary PCR product in the secondary PCR), 3

mM MgCl2, 200 µM of each dNTP, 5 % DMSO, 12.5 pmol each of forward and reverse


Biosystems, Cape Town, South Africa). The cycling conditions for both primary and

secondary PCR assays consisted of an initial denaturation at 95 °C for 3 minutes,

followed by 45 cycles of 95 °C for 30 seconds, 55 °C for 30 seconds and 72°C for 60

seconds and a final extension at 72 °C for 7 minutes.

2.9.5 Molecular detection of anisakid nematodes using PCR

To determine the species of anisakid nematodes isolated from fish, two single

step PCR assays were performed. The first assay involved the amplification of the

nuclear ribosomal DNA (rDNA) region spanning the first internal transcribed spacer,

the 5.8S gene and the second internal transcribed spacer (ITS-1, 5.8S, ITS-2). The

second assay involved the amplification of the mitochondrial cytochrome oxidase

subunit 2 gene (mt-DNA cox2). Positive (genomic DNA from L3 Anisakis typica larvae)

controls were included in all PCR reactions.


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Anisakid ITS region PCR

The ITS rDNA region of the anisakid nematodes were amplified using the

forward primer NC5 (5’-GTAGGTGAACCTGCGGAAGGATCAT-3’) and the reverse primer

NC2 (5’-TTAGTTTCTTTTCCCTCCGCT-3’) by Zhu et al. (1998) in a single step PCR assay.

The total reaction volume for this assay was 25 µL, which contained 1 µL of genomic

DNA, 1.5 mM MgCl2, 200 µM of each dNTP, 12.5 pmol each of forward and reverse


Biosystems, Cape Town, South Africa). The cycling conditions were an initial

denaturation at 95 °C for 5 minutes, followed by 30 cycles of 95 °C for 30 seconds

(denaturation), 60 °C for 30 seconds (annealing) and 72 °C for 45 seconds (extension),

then a final extension at 72 °C for 10 minutes (Kijewska et al., 2009b).

Anisakid mitochondrial cytochrome oxidase II (cox2) PCR

A 629 bp fragment of the mitochondrial DNA cytochrome oxidase II (cox2) gene

was amplified using primers 210 (5’-CACCAACTCTTAAAATTATC-3’) and 211 (5’-

TTTTCTAGTTATATAGATTGRTTYAT-3’) (Nadler and Hudspeth, 2000). The total reaction

volume for this assay was 25 µL, which contained 1 µL of genomic DNA, 2.5 mM MgCl2,

200 µM of each dNTP, 12.5 pmol each of forward and reverse primers, 1x Kapa Taq

buffer and 0.05 U/µL of Kapa Taq DNA polymerase (Kapa Biosystems, Cape Town,

South Africa). The conditions were an initial denaturation at 95 °C for 4 minutes,


(annealing) and 72 °C for 90 seconds (extension), then a final extension at 72 °C for 10

minutes (Valentini et al., 2006).

2.9.6 Molecular detection of Chlamydia spp. by qPCR

A multiplex qPCR assay was used to detect Chlamydia abortus and Chlamydia

pecorum in faecal samples from sheep and goats as previously described (Yang et al.,

2014c). This assay targets the outer membrane protein cell surface antigen gene

(ompA) using species-specific primers, which were originally designed as singleplex

qPCRs by Pantchev et al. (2009, 2010). IAC was included to check if any inhibition was

occurring in the sample (Yang et al., 2013) (see Section 2.9.1).


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A C. abortus species-specific qPCR, which produces an 86 bp product, was

amplified using the forward primer CpaOMP1-F (5’-GCAACTGACACTAAGTCGGCTACA-

3’), the reverse primer CpaOMP1-R (5’-ACAAGCATGTTCAATCGATAAGAGA-3’) and the

probe CpaOMP1-Sb (5’-dFAM-TAAATACCACGAATGGCAAGTTGGTTTAGCG-BHQ-1-3’) as

previously described (Pantchev et al., 2009). A species-specific 76 bp product was

amplified from C. pecorum using the forward primer CpecOMP1 F (5’-

CCATGTGATCCTTGCGCTACT-3’), the reverse primer CpecOMP1 (5’-

TGTCGAAAACATAATCTCCGTAAAAT-3’) and the probe CpecOMP1-S (5’-CAL-Fluor

Orange -560-TGCGACGCGATTAGCTTACGCGTAG-TAMARA-3’) as previously described

(Pantchev et al., 2010).

The total volume of this assay was 15 μL and contained 4 mM MgCl2, 1 mM

dNTPs, 1x PCR Buffer, 1.0 U Kapa DNA polymerase (Kapa Biosystems, Cape Town,

South Africa)0.2 μM each of forward and reverse primers, 0.2 μM each of forward and

reverse IAC primers, 50 nM of the probe, 50 nM of IAC probe, 10 copies of IAC

template and 1 μL of sample DNA (Yang et al., 2014c). The reaction was performed

under the following conditions: a pre-melt at 95 °C for 3 minutes, followed by 45 cycles

of 95 °C for 20 seconds (denaturation), and a combined annealing and extension step

of 60 °C for 45 seconds.

2.10 Agarose gel electrophoresis

PCR products were allowed to run on 1 % agarose (Fisher Biotech cat. No.

901b) dissolved in 1x TAE buffer (40 mM Tris-HCl, 20 mM acetate, 2 mM EDTA, pH

adjusted to 8.0 with water) and stained with 0.025 µL/mL SYBR® safe DNA gel stain

(Invitrogen, Carlsbad, USA). A 1kb Plus DNA ladder (Promega, Madison, WI, USA) was

added on a single lane along with PCR products to determine the size of PCR products.

Post electrophoresis products were visualized by UV transillumination using a

BIO Rad Gel Doc 1000 transilluminator (Bio-Rad laboratories, Gladesville, NSW,

Australia). Bands with correct lengths were cut out from the gel using a scalpel blade.

Each cut-out band was placed in a separate 1.5 mL Eppendorf tube with appropriate

labels.


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2.11 PCR product extraction from gel

Two methods were used to extract the DNA from the gel after electrophoresis.

A commercial, Ultra Clean® DNA purification, kit (MolBio, West Carlsbad, CA, USA), was

used to purify all PCR products generated for anisakid nematodes in Chapter 6

according to the manufacturer’s instructions. For products described in chapters 3 and

4, a simple tip elution method was used to purify DNA amplicons from the sliced gels

(Yang et al., 2013). Briefly, positive bands were cut from the gel and the gel fragment

were transferred to a 100 µL filter tip (with the end cut off) (Axygen, Fisher Biotech,

Wembley, WA, Australia) and then placed in a 1.5 mL Eppendorf tube and centrifuged

at 20, 000 x g for 1 minute. The filter tip was then discarded and the eluent was

retained and used for sequencing without any further purification.

2.12 DNA sequencing PCR with dye terminator kit

The purified PCR products were subjected to sequencing PCR using an ABI

Prism™ Dye Terminator Cycle Sequencing kit (Applied Biosystems, Foster City, CA, USA)

according to the manufacturer’s instruction, with the exception that the annealing

temperatures varied (depending on the annealing temperature of individual primers).

Briefly, the reaction volume for sequencing PCR was 10 µL, which contained 1. 5 µL of

5x sequencing buffer (Applied Biosystems), 1 µL BigDye® Terminator (Applied

Biosystems), 3.2 pmol primer (either forward or reverse primer), 5 - 20 ng PCR product

and deionised water. Both forward and reverse primers were used; each primer was

used in a separate reaction. The reactions were performed on a Perkin Elmer Gene

Amp PCR 2400 thermal cycler (Perkin Elmer, Foster City, CA, USA) under the following

conditions: 96 °C for 2 minutes (initial denaturation) followed by 25 cycles of 96 °C for

10 seconds (denaturation), 50 - 60 °C for 5 seconds (annealing) and 60 °C for 4 minutes

(extension).

2.13 Post reaction purification

After thermal cycling, the reaction products were purified to remove salts and

unincorporated dye terminators. For purification, the products were transferred from

their original 0.2 mL tubes to 0.6 mL tubes and ethanol precipitation was performed as

described below. Briefly, DNA was precipitated by adding 1 μL of 125 mM EDTA, 1 μL


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of 3 M sodium acetate (pH = 5.2) and 25 μL of 100 % ethanol (Sigma-Aldrich Pty Ltd,

Castle Hill, NSW, Australia). The solution was mixed gently by using a pipette and

incubated at room temperature for 20 minutes. After incubation, the DNA precipitate

was centrifuged for 30 minutes at 20, 000 x g. The supernatant was discarded and 125

μL of 70 % ethanol was added to the remaining precipitate to rinse the DNA pellet. This

was followed by further centrifugation for 5 minutes at 20, 000 x g. The resulting

supernatant was discarded and the purified DNA pellet was dried using a Savant

SpeedVac® Concentrator (Thermo Fisher Scientific, Waltham, MA, USA) for 10 minutes

and submitted for sequencing.

2. 14 DNA Sequencing

DNA sequencing was performed on an Applied Biosystems 3730 DNA Analyser

Instrument (Applied Biosystems, Foster City, California, USA) by a specialist (Frances

Brigg) in the State Agricultural Biotechnology Centre (SABC) at Murdoch University, WA

(http://www.sabc.murdoch.edu.au/).

2.15 Phylogenetic analysis

The nucleotide sequences obtained were analysed using FinchTV 1.4.0

(Geospiza, Inc.; Seattle, WA, USA; http://www.geospiza.com) and compared with

published sequences for identification using the for Biotechnology Information Basic

Local Alignment Search Tool (BLAST) (http://blast.ncbi.nlm.nih.gov) for species

identification, developed by the National Institute of Health’s National Centre.

Sequences were aligned with known reference sequences using both the

Clustal Omega alignment tool (http://www.ebi.ac.uk/Tools/msa/clustalo/) and

MUSCLE alignment (Edgar, 2004), in the MEGA5 software (Tamura et al., 2011). The

resultant alignments were adjusted manually using the MEGA5 software.

Phylogenetic trees were constructed using additional sequences retrieved from

GenBank (http://www.ncbi.nlm.nih.gov/genbank/). Distance estimation was

conducted using MEGA5 (Tamura et al., 2011) based on evolutionary distances

calculated using p-distance method (Nei and Kumar, 2000), the Kimura two-parameter

model (Kimura, 1980) or the Tamura-Nei model (Tamura and Nei, 1993) and grouped

http://www.sabc.murdoch.edu.au/

http://blast.ncbi.nlm.nih.gov/

http://www.ebi.ac.uk/Tools/msa/clustalo/


105

using neighbour-joining (NJ) (Saitou and Nei, 1987). Parsimony and maximum

likelihood (ML) analyses were also conducted using MEGA5 (Tamura et al., 2011).

More details of the individual phylogenetic analyses conducted are provided in the

specific chapters of this thesis. Reliabilities for the trees were tested using 1000

bootstrap replications (Felsenstein, 1985) and bootstrap values exceeding 70 were

considered well supported (Hills and Bull, 1993).

2.16 Statistics

Prevalences were expressed as percentage of positive samples with 95 %

confidence intervals calculated assuming a binomial distribution using the software

Quantitative Parasitology 3.0 (Rozsa et al., 2000). Differences in prevalence among

groups were compared by Fisher’s Exact Test (for two groups) or Chi-square analysis

(for three or more groups). P values < 0.05 were considered significant. Greater details

of the individual statistical analyses conducted are provided in specific chapters.

Statistical analyses were performed using GraphPad Prism GraphPad Prism version 4

for Windows, GraphPad Software, San Diego, California, USA (www.graphpad.com).

http://www.graphpad.com/

Chapter 3

3. Prevalence and infection levels of helminth

and coccidian parasites in sheep and goat in

PNG

The contents of this chapter, specifically, the microscopy analyses have been

published in the Journal of Helminthology. The article is listed below and can be found

in Appendix B.

Koinari, M., Karl, S., Ryan, U., Lymbery, A.J., 2013. Infection levels of gastrointestinal

parasites in sheep and goats in Papua New Guinea. Journal of Helminthology 87, 409-

415.

This chapter describes the analyses of faecal samples from sheep and goats for

helminths and coccidian parasites. Two methods were used: (1) faecal flotation and

microscopic analysis (results of which have been published in the Journal of

Helminthology) and (2) qPCR detection for trichostrongylid nematodes and Eimeria sp.

Research highlights:

The overall parasite prevalence by microscopy was 72 % (79/110) in sheep and

89 % (49/55) in goats. (one or more species of gastrointestinal parasite detected)

(Note this does not include Cryptosporidium and Giardia. Cryptosporidium

requires specific stains. Also, microscopic examinations have a relatively low

sensitivity for these parasites due to their small size were only screened for by

PCR).

The gastrointestinal parasites found by microscopy in both sheep and goats were

trichostrongylid nematodes, Eimeria, Strongyloides, Fasciola, Trichuris and

Nematodirus. (Note: trichostrongylids/trichostrongyles refers to the superfamily

Trichostrongyloidea and not the genus Trichostrongylus).

Two additional genera were found in goats: Moniezia and Dictyocaulus.

The prevalence of each trichostrongyles by qPCR in sheep (S) and goats (G) were;

Haemonchus contortus 41.1 % (S) and 41.7 % (G); Teladorsagia circumcincta 21.3

% (S) and 24.1 % (G) and Trichostrongylus spp. 14.8 % (S) and 14 % (G).

The prevalence of Eimeria spp. by qPCR was 64.9 % (37/57) for sheep and 91.9 %

(34/37) for goats.

This is the first study to report Eimeria in goats and Dictyocaulus in small

ruminants in PNG.


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3.1 Introduction

Gastrointestinal parasites are recognised as a major threat to the production of

sheep and goats in both small and large scale-farms as described in Chapter 1.

In PNG, the distribution and productivity of small ruminants are hindered

mainly by poor health, nutrition and management (Quartermain, 2004a). There have

been various reports on the infections of sheep and goats with gastrointestinal

parasites including nematodes, cestodes and Coccidia (listed in Table 1-2, Chapter 1),

(Varghese & Yayabu, 1985; Owen, 1988a; 1989b; 1998c and reviewed by Quartermain,

2004b). However, those surveys have been performed on animals raised in

government or institutional farms and there is a lack of information on the

epidemiology of gastrointestinal parasites infecting sheep and goats in smallholder

farms. Such information is essential for understanding the economic impact these

parasites can have on farmers and to support decision-making regarding the treatment

and prevention of parasitic diseases in these animals.

The aims of the present study were to obtain data on the prevalence, infection

levels and species of gastrointestinal parasites in different farm management types

over a wide geographic area. Specifically, the parasites were identified in fresh faecal

samples based on the morphology of their eggs or oocysts using the McMaster

technique (Whitlock, 1948) and light microscopy. Furthermore, molecular tools were

used to identify trichostrongyles (H. contortus, T. circumcincta and Trichostrongylus

spp.) and Eimeria spp.

3.2 Methods

This section summarises only the most important methods used to obtain the

results described in this chapter (Fig. 3-1). A detailed description of all the methods can

be found in Chapter 2 of this thesis.

3.2.1 Sample collection

Sampling was conducted from February to April 2011 in two broad agro-climatic

zones, the highlands (all study sites, except Labu) and lowlands (Labu) in the central

region of mainland PNG (Fig. 2-1 in Chapter 2). These sites are located in a wet tropic


110

environment and receive high annual rainfall predominantly during the wet season,

which lasts from October to May (Quartermain, 2004b). Specific details of the study

sites including the climate data are presented in Chapter 2, Section 2.3.1 and Table 2-1.

Figure 3-1: Flow chart of methods used for screening gastrointestinal parasites from faecal samples of sheep and goats. After sample collection, a subset of faecal samples was analysed using parasitological methods involving faecal flotation and light microscopy in PNG. The rest of the samples was preserved in 70 % ethanol and transported to Murdoch University, WA, for molecular screening. DNA was extracted using a commercial kit and qPCR assays were performed using established methods.

For the comparison of prevalence of gastrointestinal parasites among study

sites, the study sites were divided into farm types:

Research institutions: Tambul in high altitude and Labu in lowland

Public institutions: Baisu

Government farms: Menifo

Smallholder farms: Korefeigu, Benabena, Goroka, Daulo and Chuave

Furthermore, for comparison of farm management systems, data from the institutional

farms (Labu, Tambul and Baisu) were pooled because in institutional farms,

anthelmintics were given to animals regularly to control gastrointestinal parasites,


111

whereas no anthelmintics were administered to the smallholder flocks. Also, there

were high stocking rates at institutional farms but not in the smallholder farms.

Fresh faecal samples were obtained directly from the rectum of sheep and

goats and put into 25 mL (screw top) containers in ice-filled Coleman coolers until

processing at a NARI laboratory in Labu. Each faecal sample from the 25 mL container

was placed into 2 mL Eppendorf tubes and preserved in 70 % ethanol for molecular

screening. Excess samples were left in the 25 ml tubes for morphological analyses by a

faecal flotation technique (the time lag between sample collection and microscopic

examination was 15 - 20 days). All samples were stored at 4 °C. Samples for molecular

analyses were transported to Murdoch University, WA.

3.2.2 Parasitology

A subset of faecal samples consisting of 110 from sheep and 55 from goats

were used for microscopic examinations. Approximately two grams of each faecal

sample were examined using a modified McMaster technique (Whitlock, 1948). The

detailed procedure is described in Chapter 2, Section 2.7.1 ‘Faecal worm egg count’.

3.2.3 DNA isolation

Total DNA was extracted from 250 mg of faeces using a PowerSoil® DNA

isolation kit (MO BIO laboratories, Carlsbad, California, USA) as described in Chapter 2,

Section 2.8.1. All extracted samples were stored at -20 °C until required for screening.

3.2.4 Screening of trichostrongyles and Eimeria species by qPCR

A species-specific qPCR assay was performed to detect H. contortus,

T. circumcincta and Trichostrongylus spp. in faecal samples of sheep (n = 263) and

goats (n = 228) as described in Chapter 2, Section 2.9.1.

A qPCR was also used to screen for Eimeria in faecal samples of sheep (n = 57)

and goats (n = 37) at the small subunit rRNA locus (Yang et al., 2014d), while a nested

PCR was used to amplify samples, which were positive for Eimeria by qPCR for

genotyping (Pieniazek et al., 1996) as described in Chapter 2, Section 2.9.2. Only two


112

Eimeria-positive samples from goats were successfully sequenced at the 18S rRNA

locus.

3.2.5 Data analysis

Prevalence was calculated as the percentage of positive samples in the total

number of samples examined. Apart from the overall prevalence (i.e. infection with

gastrointestinal parasites) in each flock, prevalence was also calculated for each

parasite type, stratified by animal species (Table 3-1); sheep breed, agro-ecological

zone and farm management type (Table 3-2) and different farm types (Table 3-3). For

comparison of agro-ecology and farm management systems, data for sheep and goats

were combined (Table 3-2). Differences in prevalence among groups were compared by

Fisher’s exact test (FET) (for two groups) (specifically, Tables 3-1 and 3-2) or chi-square

analysis (for more than two groups) (Table 3-3). FET were used where sample sizes

were relatively small (n ranged from 27 to 127) as FET is more accurate for smaller

sample sizes. Where multiple pairwise comparisons were made among groups, a

Bonferroni correction was applied to maintain an experiment-wide Type I error rate of

5 %.

EPG counts were transformed to their decadic logarithms to obtain a normal

distribution of values prior to statistical testing for significant differences between

animal species, sheep breed, agro-ecological zones and farm types. Differences

between two groups were compared by t-tests (Table 3-1 and Table 3-2) and among

more than two groups by one-way analysis of variance (1-way ANOVA); followed by a

post-hoc, Tukey’s HSD, test (Table 3-3).

For qPCR amplification, the threshold cycle (Ct) values obtained from the

amplification plots were used to determine whether the sample was positive for each

of the trichostrongylid nematodes (Fig. 3-2). Differences in prevalence between farm

types (Table 3-5 to Table 3-7) were compared by Fisher’s exact test (FET) and a

Bonferroni correction was applied as described above.


113

Figure 3-2: qPCR amplification plot for H. contortus as an example at the ITS-1 locus. Data was acquired at FAM channel for H. contortus, at JOE channel for T. circumcincta and at ROX channel for Trichostrongylus species. A threshold (red horizontal line) was adjusted manually in the exponential phase of PCR. The threshold cycle (Ct) is the cycle number at which the fluorescent signal of the reaction crosses the threshold (arrow) and was used to determine the presence of each gastrointestinal parasite in the sample. For example, where the yellow line crosses the threshold (arrow), the corresponding Ct value is 18. Ct threshold values were automatically set by the real time PCR software (Rotor-Gene 6.1.93, Corbett Research, Mortlake, NSW, Australia).

3.3 Results

3.3.1 Infection levels of gastrointestinal parasites by microscopy

From a total of 165 faecal samples from small ruminants (110 from sheep and

55 from goats) examined by microscopy, gastrointestinal parasites were found in 128

(77.6 %) animals, with 71.8 % (79/110) of sheep and 89.1 % (49/55) of goats having

one or more species of gastrointestinal parasites. The overall prevalence of

gastrointestinal parasites in goats was significantly higher than in sheep (FET: p =

0.017). Of the 128 positives, 39 % (50/128) had two or more types of gastrointestinal

parasites; 32.9 % (26/79) of sheep and 49 % (24/49) of goats (not significantly different

by FET: p = 0.09).

The gastrointestinal parasites found and their prevalences in sheep (S) and in

goats (G) were as follows: trichostrongylids 67.3 % (S), 85.5 % (G); Eimeria 17.3 % (S),

16.4 % (G); Strongyloides, 8.2 % (S), 23.6 % (G); Fasciola, 5.5 % (S), 18.2 % (G); Trichuris,

1.8 % (S), 3.6 % (G); and Nematodirus, 1.8 % (S), 3.6 % (G). Two additional genera were


114

found in goats: Moniezia (9.1 %) and Dictyocaulus (3.6 %). The prevalence of

trichostrongylids (FET: p = 0.0002), Strongyloides (FET: p = 0.013) and Fasciola (FET: p =

0.013) were significantly higher in goats than in sheep. In addition, the mean EPG

counts for trichostrongylids were significantly higher in goats than in sheep (t-test: p =

0.014). Prevalences and mean EPG counts in all the sampling sites, stratified by the

type of host animal (sheep or goat) and the type of parasite are listed in Table 3-1.

Table 3-1: Gastrointestinal parasite prevalence and mean ± SD EPG counts stratified by gastrointestinal parasite type for sheep and goats. N = the total number of faecal samples. P = the number of animals, which were positive for one or more gastrointestinal parasites. Given in parentheses are percent prevalences and 95 % confidence intervals (CI). EPG counts are given as means ± SD. Where no SD value is given on the mean EPG count, there was only a single or few positive observations with the same values so that SD could not be calculated. * = values are significantly different between sheep and goats by either FET or t-test.

Goat (N = 55) Sheep (N = 110)

Parasite P (%, 95 % CI) EPG P (%, 95 % CI) EPG

Trichostrongylids 20* (36.7, 24.0 - 50.5) 745 ± 622* 74 (67.3, 57.6 - 75.4)* 762 ± 1264*

Strongyloides sp. 13 (23.6, 13.7 - 37.3) 277 ± 437 9 (8.2, 4.1 - 15.4) 323 ± 377

Eimeria sp. 9 (16.4, 8.2-2.9) 203± 103 19 (17.3, 11 - 25.9) 633 ± 1467

Fasciola sp. 10 (18.2, 9.5 - 31.4) 257± 275 6 (5.5, 2.2 - 12) 125 ± 46

Trichuris sp. 2 (3.6, 0.6 -1 3.6) 125 ± 59 2 (1.8, 0.3 - 7.1) 111 ± 48

Moniezia sp. 5 (9.1, 3.4 - 20.7) 116 ± 46 0 0

Dictyocaulus sp. 2 (3.6, 0.6 - 13.6) 83 ± 0 0 0

Nematodirus sp. 2 (3.6, 0.6 - 13.6) 249 ± 117 2 (1.8, 0.3 - 7.1) 111 ± 48

Total 49/55 (89.1)* 927 ± 821* 79/110 (72.8)* 909 ± 1795*

Prevalence and mean EPG counts for gastrointestinal parasites stratified by

agro-ecology, farm management systems (institutional vs smallholder) and sheep

breed are given in Table 3-2. The prevalence of gastrointestinal parasites in the two

agro-ecological zones ranged from 2.4 % (Moniezia and Trichuris) to 75 %

(trichostrongyles) in the highlands, while it ranged from 4.9 % (Moniezia and Trichuris)

to 68.3 % (trichostrongyles) in the lowlands (Table 3-2). For the farm management

systems, the prevalence of gastrointestinal parasites ranged from 1.7 % (Trichuris) to

74.8 % (trichostrongyles) in institutional farms and 2 % (Moniezia) to 70 %

(trichostrongyles) in smallholder farms (Table 3-2). Similarly, in sheep breeds, the


115

prevalence ranged from 3.7 % (Strongyloides) to 66.7 % (trichostrongyles) for Priangan

sheep and from 3.6 % (Fasciola, Trichuris, Nematodirus,) to 67.5 % (trichostrongyles)

for Highlands Halfbred sheep (Table 3-2).

No statistically significant differences were found in the prevalence of each

gastrointestinal parasite type between the agro-ecological zones (FET: p > 0.05), the

farm management systems (FET: p > 0.05), or the sheep breeds (FET: p > 0.05), with

one exception. That is, the prevalence of Fasciola was higher in the lowland than the

highland (FET: p = 0.028) agro-ecological zone. Similarly, there were no differences in

EPG for most of the parasite types between the specific groups with the exception of

Eimeria. The mean EPG for Eimeria was higher in the highlands than in the lowlands

(Labu) (t-test: p = 0.045). In addition, the mean EPG for Eimeria was higher in the

smallholder farms than in institutional flocks (t-test: p = 0.004) and the mean EPG for

Eimeria in the Highlands Halfbred sheep was higher than in the Priangan sheep (t-test:

p = 0.045).

The prevalence and the mean EPG counts for each parasite in different farm

types (research and public institutions, government and smallholder) are given in Table

3-3. Trichostrongylid nematodes, Strongyloides and Eimeria were prevalent in both

sheep and goats in all 5 farm types except where no data were obtained (as for goats in

the government farm). There were no statistically significant differences in the

prevalence, but there were several significant differences in EPG counts for different

gastrointestinal parasite types across the different farms types. The mean EPG counts

for goats infected with Strongyloides sp. in Tambul (highland research institution) were

significantly higher than the ones in Labu (lowland research institution) (1-way ANOVA:

F = 3.91, p = 0.05, Tukey’s test: p < 0.05). For sheep, the mean EPG count for Eimeria in

Labu was significantly lower than in Menifo (1-way ANOVA: F = 3.41, p = 0.045; Tukey’s

test: p < 0.05). No significant differences were observed for the other genera of

gastrointestinal parasites. Fasciola was found in sheep in the research institutes (Labu

and Tambul) and in smallholder farms and in goats from Labu, Baisu and smallholder

farms (Table 3-3). Trichuris occurred in sheep from smallholder and government farms

and in goats only in Labu (Table 3-3).

Table 3-2: Gastrointestinal parasite prevalence and mean EPG counts stratified for agro-ecology, farm management and sheep breed. N = the number of animals examined. Prevalence = animals infested with one or more gastrointestinal parasite type. (%) = percent prevalence. EPG counts are given as mean ± SD. Where no SD value is given on the mean EPG count, there was only a single or few positive observations with the same EPG values so that SD could not be calculated. * = values are significantly different between sheep and goats by either FET or t-test. Institution = both research (Labu and Tambul) and the public (Baisu), H/Halfbred = Highlands Halfbred sheep.

Agro-ecology Farm Management Sheep Breed

Highlands Lowlands Institutional Smallholder Priangan H/Halfbred

N = 124 N = 41 N = 115 N = 50 N = 27 N = 83

Prevalence (% P)

Trichostrongyles 93 (75) 28 (68.3) 86 (74.8) 35 (70) 18 (66.7) 56 (67.5)

Strongyloides 18 (14.5) 4 (9.8) 14 (12.2) 8 (16) 1 (3.7) 8 (9.6)

Eimeria 18 (14.5) 10 (24.4) 15 (13.1) 13 (26) 7 (25.9) 12 (14.5)

Fasciola 8 (6.5)* 8 (19.5)* 12 (10.4) 4 (8) 3 (11.1) 3 (3.6)

Trichuris 3 (2.4) 2 (4.9) 2 (1.7) 3 (6) 0 3 (3.6)

Moniezia 3 (2.4) 2 (4.9) 4 (3.5) 1 (2) 0 0

Dictyocaulus 0 2 (4.9) 2 (1.7) 0 0 0

Nematodirus 5 (4) 0 5 (4.3) 0 0 3 (3.6)

EPG (mean ± SD)

Trichostrongyles 818±1156 551±605 748±942 775±1316 405±570 889±1412

Strongyloides 278±375 374±582 357±491 189±151 1246 208±160

Eimeria 696±1492* 133±80* 133±69* 913±1723* 95±32* 948±1796*

Fasciola 228±283* 187±165 152±141 374±362 166 83

Trichuris 111±48 126±59 125±59 111±48 0 111±48

Moniezia 138±48 83 104±42 166 0 0

Dictyocaulus 0 83 83 0 0 0

Nematodirus 166±102 0 166 0 0 111±48

Table 3-3: Gastrointestinal parasite prevalence and mean ± SD EPG counts for gastrointestinal parasite type and farm type. NS and NG are the total number of faecal samples collected at each study site for sheep and goats, respectively. P = the number of animals infested with one or more gastrointestinal parasite type. Given in parentheses (%) is the percent prevalence. EPG counts are given as means ± SD. Where no SD value is given on the mean EPG count, there was only a single or few positive observations with the same EPG values so that SD could not be calculated. * = values are significantly different by 1-way ANOVA/Tukey’s HSD testing.

Research (Labu) Research (Tambul) Public institution Government Smallholder

(NS=27, NG=14) (NS=29, NG=4) (NS=19, NG =22,) (NS=19, NG=0) (NS=16, NG=15)

Sheep P (%) EPG P (%) EPG P (%) EPG P (%) EPG P (%) EPG

Trichostrongyles 18 (66.7) 406 ± 570 20 (69) 1216 ± 1585 15 (78.9) 603 ± 389 10 (52.6) 1087 ± 2303 11 (68.8) 445 ± 677

Strongyloides 1 (3.7) 1246 5 (17.2) 266 ± 180 1 (5.3) 83 1 (5.3) 166 1 (6.3) 83

Eimeria 7 (25.9) 95 ± 31* 2 (6.9) 125 ± 59 0 0 6 (31.6) 1605 ± 2453* 4 (25) 374 ± 220

Fasciola 3 (11.1) 166 2 (6.9) 83 0 0 0 0 1 (6.3) 83

Trichuris 0 0 0 0 0 0 1 (5.3) 166 2 (12.5) 83

Moniezia 0 0 0 0 0 0 0 0 0 0

Dictyocaulus 0 0 0 0 0 0 0 0 0 0

Nematodirus 0 0 2 (6.9) 125 ± 59 1 (5.3) 83 0 0 0 0

Goat

Trichostrongyles 10 (71.4) 813 ± 603 3 (75) 478 ± 212 20 (90.9) 706 ± 713 no data 14 (93.3) 810 ± 582

Strongyloides 3 (21.4) 831 2 (50) 960 ± 996* 2 (9.1) 83 6 (40) 210 ± 170

Eimeria 3 (21.4) 221 ± 95 0 0 3 (13.6) 138 ± 48 3 (20) 249 ± 143

Fasciola 5 (35.7) 199 ± 216 0 0 2 (9.1) 83 3 (20) 470 ± 374

Trichuris 2 (14.3) 125 ± 59 0 0 0 0 0 0

Moniezia 2 (14.3) 83 0 0 2 (9.1) 125 ± 59 2 (6.7) 166

Dictyocaulus 2 (14.3) 83 0 0 0 0 0 0

Nematodirus 0 0 0 0 9.1 249 ± 117 0 0


Nematodirus was found in sheep in two sites (Baisu and Tambul) and in goats only

from Baisu (Table 3-3). Moniezia was only found in goats from flocks in Labu, Baisu and

smallholder farms (Table 3-3). Dictyocaulus was only found in goats from Labu (Table

3-3). There was also a trend for goats to be more heavily infected than sheep in all

areas. Specifically, in Labu, mean EPG for trichostrongyles (t-test: p = 0.021) and

Eimeria (t-test: p = 0.004) were higher in goats than in sheep. Also, in smallholder

farms, the prevalence of Strongyloides sp. was higher in goats than in sheep (FET: p =

0.037) and mean EPG for trichostrongyles in goats was higher than in sheep (t-test: p =

0.006).

3.3.2 Prevalence of trichostrongylid nematodes by qPCR

Genomic DNA from faeces of 263 sheep and 228 goats were screened using

qPCR to detect H. contortus, T. circumcincta and Trichostrongylus spp. The prevalence

of each nematode in sheep (S) and goats (G) were: H. contortus 41.1 % (S) and 41.7 %

(G); T. circumcincta 21.3 % (S) and 24.1 % (G) and Trichostrongylus spp. 14.8 % (S) and

14 % (G) (Table 3-4). There were significant differences among H. contortus,

T. circumcincta and Trichostrongylus spp. for both sheep (Chi-square = 51.4, df = 2, p <

0.0001) and goats (Chi-square = 19.26, df = 2, p < 0.0001).

Differences in the prevalence of H. contortus in sheep between the different

types of farms were statistically significant. Statistical data for comparison of

prevalences for H. contortus in sheep between two farm types are given in Table 3-5.

Specifically, the prevalence of H. contortus in Tambul (research institute) was higher

than Labu (research institute), Baisu (public institute) and Menifo government farm

(FET: p values < 0.005) (Table 3-5). In addition, the prevalence of H. contortus in Baisu

was higher than in Labu, Menifo and smallholder farms (Table 3-5). There was,

however, no significant difference in the prevalence of H. contortus in goats between

farm types for all pairs of farm (FET: p values > 0.005).

There were no significant differences in the prevalence of T. circumcincta in

sheep or goats between farm types for all pairs of farms (FET: p values > 0.005).

There were significant differences in the prevalence of Trichostrongylus spp. in

sheep among the different types of farms (Table 3-6). The prevalence of


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Trichostrongylus spp. in sheep from the public institution (Baisu) was significantly

higher than in Tambul, government (Menifo) and smallholder farms (Table 3-6).

However, there were no significant differences in the prevalence of Trichostrongylus

spp. in goats for all pairs of farms (FET: p values > 0.005).

Table 3-4: Prevalence of trichostrongylid nematodes for sheep and goats. N = the total number of animals examined in each farm type. P = the number of animals, which were positive for one of the trichostrongyles. Given in parentheses are the per cent prevalence (%) and 95 % confidence interval (CI). RI (Labu) = lowland research institute, RI (Tambul) = highland research institute, PI = Public Institute.

Type of farm N P (%, 95 % CI) P (%, 95 % CI) P (%, 95 % CI)

Sheep H. contortus T. circumcincta Trichostrongylus

RI (Labu) 40 10 (25.0; 13.3-41.5) 4 (10.0; 3.3-24.6) 6 (15.0; 6.3-30.1)

RI (Tambul) 109 64 (58.7; 48.9-67.9) 33 (30.3; 22-39.9) 15 (13.8; 7.2-20.3)

PI (Baisu) 27 19 (70.4; 52.0-88.9) 3 (11.1;2.9-30.3) 12 (44.4; 24.4-64.5)

Government 37 4 (10.8; 3.5-26.4) 6 (16.2; 6.8-32.7) 2 (5.4; 1.5-17.7)

Smallholder 50 11 (22.0; 10.1-33.9) 10 (20.0; 8.5-31.5) 4 (8.0; 0.2-15.8)

Total 263 108 (41.1; 35.1-47.1) 56 (21.3; 16.3-26.3) 39 (14.8; 10.5-19.2)

Goat

RI (Labu) 43 20 (46.5; 31.0-62.0) 14 (32.6; 18.0-47.2) 5 (11.6; 1.7-21.6)

PI (Tambul) 35 19 (54.3; 37.0-71.7) 10 (28.6; 12.8-44.3) 5 (14.3; 2.1-26.5)

PI (Baisu) 39 15 (38.5; 22.5-54.4) 6 (15.4; 3.5-27.3) 4 (10.3; 0.3-20.2)

Government 6 3 (50; 14-86.1) 3 (50; 14-86.1) 1 (16.7; 0.8-63.5)

Smallholder 105 38 (36.2; 26.9-45.5) 22 (21.2; 13.2-29.1) 17 (16.2; 9.0-23.4)

Total 228 95 (41.7; 35.2-48.1) 55 (24.1; 18.5-29.7) 32 (14.0; 9.5-19.6)

Table 3-5: Comparisons of prevalences for H. contortus in sheep among the farm types.All pairs of farms were compared by Fisher’s exact test. A Bonferroni correction was used to determine significance at p values < 0.005. RI = Research Institute, PI = Public Institute.

Data set 1 Data set 2 Significant p values

Lowland RI (Labu) Highland RI (Tambul) Yes p = 0.0004

Lowland RI (Labu) PI (Baisu) Yes p = 0.0004

Lowland RI (Labu) Government (Menifo) No p = 0.1429

Lowland RI (Labu) Smallholder No p = 0.8047

Highland RI (Tambul) PI (Baisu) No p = 0.3782

Highland RI (Tambul) Government (Menifo) Yes p < 0.0001

Highland RI (Tambul) Smallholder Yes p < 0.0001

PI (Baisu) Government (Menifo) Yes p < 0.0001

PI (Baisu) Smallholder Yes p < 0.0001

Government (Menifo) Smallholder No p = 0.2521


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Table 3-6: Comparisons of prevalences for Trichostrongylus spp. in sheep among the farm types. All pairs of farms were compared by Fisher’s exact test (FET). A Bonferroni correction was used to determine significance at p values < 0.005. RI = Research Institute, PI = Public Institute.

Data set 1 Data set 2 Significant p values

Lowland RI (Labu) Highland RI (Tambul) No p = 1

Lowland RI (Labu) PI (Baisu) No p = 0.0102

Lowland RI (Labu) Government (Menifo) No p = 0.2715

Lowland RI (Labu) Smallholder No p = 0.5034

Highland RI (Tambul) PI (Baisu) Yes p = 0.0009

Highland RI (Tambul) Government (Menifo) No p = 0.2399

Highland RI (Tambul) Smallholder No p = 0.4308

PI (Baisu) Government (Menifo) Yes p = 0.0004

PI (Baisu) Smallholder Yes p = 0.0003

Government (Menifo) Smallholder No p = 1

3.3.3 Prevalence of Eimeria in sheep and goats by qPCR

The prevalence of Eimeria was 64.9 % (37/57) for sheep and 91.9 % (34/37) for

goats (Table 3-7). There was a significant difference in prevalence between sheep and

goats (FET: p = 0.030).

Table 3-7: Overall prevalence of Eimeria in sheep and goats by qPCR. N = the total number of faecal samples. P = the number of animals, which were positive for Eimeria. Given in parentheses are the percent prevalence (% P) and 95 % confidence interval (CI). * = values are significantly different between sheep and goats by FET. RI = Research Institute.

Type of farm N P (% P; 95 % CI)

Sheep

Lowland RI (Labu) 7 5 (71.4; 30.3-94.9)

Highland RI (Tambul) 19 13 (68.4; 43.5-86.4)

Public Institute (Baisu)

Not analysed

Government (Menifo) 10 7 (70, 35.4-91.9)

Smallholder 21 12 (57.1; 34.4-37.4)*

Total 57 37 (64.9; 51.1-76.8)*

Goats

Lowland RI (Labu) 8 8 (100; 59.8-100)

Highland RI (Tambul) 4 3 (75; 21.9-98.7)

Public Institute (Baisu) 3 3 (100; 31-100)

Government (Menifo) 2 2 (100; 19.8-100)

Smallholder 20 18 (90; 66.9-98.3)*

Total 37 34 (91.9; 77-98.3)*


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No significant associations were found between sheep and goats in each farm

types with the exception that the prevalence of Eimeria for goats was higher than for

sheep in smallholder farms (FET: p = 0.0325).

Molecular typing of Eimeria

Positive samples from goats were genotyped at the 18S rRNA locus and two

isolates (GE62 and GE72) from smallholder farms were typed as Eimeria zuernii.

Unfortunately, samples from sheep could not be genotyped because chromatogram

sequences were unreadable.

3.4 Discussion

Overall, 77.6 % (128/165) of the examined farm animals in PNG were infected

with one or more types of gastrointestinal parasites by microscopy. This high rate of

gastrointestinal parasitism has also been observed in other tropical countries such as

Ethiopia and Kenya (Maichomo et al., 2004; Regassa et al., 2006). Trichostrongyles has

the highest prevalence (67.3 % in sheep and 85. 5 % in goats), followed by Eimeria

(16.4 - 17.3 %), Strongyloides (8.2 - 23.6 %), Fasciola (5.5 - 18.2 %), Trichuris (1.8 - 3.6

%) and Nematodirus (1.8 - 3.6 %) (Table 3-1). A similar trend in prevalence for these

species have also been reported in other countries (Gadahi et al., 2009; Dagnachew et

al., 2011). This high parasite prevalence may be attributed to poor farm management

practises, such as short pasture rest times, poor nutrition and lack of anthelmintic

treatment. In all the farms studied, mixed-species flocks grazed or browsed on natural

forage on the same land for most of the time or were moved to other areas with only

short pasture rest times. In smallholder farms, sheep and goats were allowed to graze

freely or were tethered in available communal pasture during the day and housed at

night on daily basis. In institutional and government farms, the flocks were also

allowed to graze at daytime and housed at night but the pastures were divided into

paddocks (n = 3 to 5). Sheep and goats were allowed to graze in one paddock for up to

2 weeks and then changed to the next one. Studies in Fiji, Tonga, Malaysia and the

Philippines found that nematodes (especially, H. contortus and T. colubriformis) have

short survival times (3 to 4 days) on pasture and suggested rotational grazing as an

effective measure for parasite control (Banks et al., 1990; Barger et al., 1994; Cheah


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and Rajamanickam, 1997; Baker and Gray, 2004). PNG has similar climate as those

countries, and therefore if rotational grazing is proposed, 3.5 days would be suitable

for sheep and goats to graze in one paddock, after which the animals can be moved to

another paddock.

Natural pasture and shrubs in PNG are often not very nutritious and may

contain anti-nutritive factors such as tannin types, which restrict rather than enhance

protein availability to the ruminant (Macfarlane, 2000). Signal grass, for example, may

cause hepatic dysfunctions in farm animals (Macfarlane, 2000). Low quality feed may

result in subsequent malnutrition, which may negatively affect the development of

acquired immunity against gastrointestinal parasites (Kyriazakis and Houdijk, 2006).

In the present study, however, significantly lower gastrointestinal parasite

prevalence at study sites, which had more frequent anthelmintic treatments, was not

observed. This could be due to anthelmintic resistance or treatments not being given

correctly, however, further studies are needed to confirm this.

The overall infection levels of gastrointestinal parasites in goats were higher

than in sheep. Goats were also infected with a wider spectrum of gastrointestinal

parasites. This contradicts some previous studies, which found a lower overall

prevalence of gastrointestinal parasites in goats (Kanyari et al., 2009; Khan et al., 2010;

Abebe et al., 2011) but is in agreement with a number of other studies, which reported

a higher parasite prevalence in goats (Regassa et al., 2006; Nwosu et al., 2007; Gadahi

et al., 2009; Dagnachew et al., 2011). Goats do not develop resistance as efficiently as

sheep (Hoste et al., 2008) and this may explain the findings of the present study.

Trichostrongylid nematodes were the most abundant parasites detected in the

present study by microscopy. Quantitative PCR analyses revealed a higher prevalence

of H. contortus (41.1 - 41.7 %) compared to T. circumcincta (21.3 - 24.1 %) and

Trichostrongylus spp. (14 - 14.8 %) (Table 3-4). The results of this study were similar to

those found in a study in adult goats in Malaysia, which reported that H. contortus

prevalence ranged from 35 - 46 % and Trichostrongylus spp. from 14 - 21 %, although

in sheep, prevalence of H. contortus (35 – 68 %) and Trichostrongylus (39.6 %) were


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slightly higher (Dorny et al., 1995). Another study in Ethiopia also found higher

prevalences of H. contortus (56.3 %) and Trichostrongylus spp. (39.6 %) (Abebe et al.,

2011). The observed differences in prevalence between the present and previous

studies could be due to variations in geographical and climatic conditions. However,

the trends are similar, which is H. contortus occurring at a higher frequency than the

other trichostrongylid nematodes.

Haemonchus species are highly fecund, laying up to 5000 eggs per day, where

environmental factors are favourable (Gupta et al., 1987; Le Jambre, 2006). The pre-

parasitic stages of H. contortus develop and survive better at mean monthly maximum

temperatures ≥ 18.3 °C (Gupta et al., 1987). The study sites in the present study had

mean maximum annual temperatures that ranged from 18.9 °C to 31.1 °C, with only

little variation throughout the year due to their proximity to the equator. Additionally,

most study sites were very humid and therefore, likely to sustain the survival of the

free-living stages of H. contortus, leading to high pasture contamination. Free-living

stages of Teladorsagia and Trichostrongylus, however survive better at < 10 °C

(O'Connor et al., 2006). Thus, the fact that the prevalence of H. contortus was higher

than T. circumcincta and Trichostrongylus spp. is likely due to adult nematodes

releasing more eggs in their faeces and well as optimal environmental conditions in

favour of H. contortus development.

The overall prevalence of Eimeria for sheep was 17.3 % (19/110) by microscopy

(Table 3-1) and 64.9 % (35/57) by qPCR (Table 3-7). A previous study in PNG reported

that 89 % (67/75) of sheep were positive for Eimeria from three locations (in Erap and

Lae, Morobe Province and in Mt. Hagen, Western Highlands Province) (Varghese and

Yayabu, 1985). The low prevalence of Eimeria observed in the present study by

microscopy may be due to the different methodology used for parasite identification.

In the present study, a simple flotation procedure was used, while in previous studies,

a centrifugation/flotation method was used (Varghese and Yayabu, 1985). Methods

involving centrifugation are more sensitive than just faecal flotation techniques for

detection of oocytes in faecal samples (Dryden et al., 2005). The overall prevalence of

Eimeria in goats was higher by qPCR (91.1 %) (Table 3-7). Previous studies in other


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countries have also reported such high prevalences in goats (Kusilukaa et al., 1996;

Balicka-Ramisz, 1999). Furthermore, Eimeria zuernii was identified in two adult goats in

the present study. Eimeria zuernii is highly pathogenic in calves; causing diarrhoea

(Bangoura et al., 2012), enteric lesions and death of infected calves (Stockdale, 1977).

The smallholder goat farms where E. zuernii was found shared feeding grounds with

cattle and other animals. Whether the presence of E. zuernii identified herein

represents actual or mechanical infections remains to be determined, as the oocysts

may have been passing through rather than infecting these goats. Notwithstanding,

this is the first study to report Eimeria in goats in PNG. Adult sheep and goats shed

eimerid oocysts in their faeces, which could lead to contamination of pasture and

therefore they could be regarded as a source of infection for lambs and kids.

The EPG counts for Eimeria in PNG Priangan sheep (n = 27) were significantly

lower than that in the Highlands Halfbred sheep (n = 83). It is difficult to ascertain the

mechanisms behind the observed difference, especially as coincidentally, most PNG

Priangan sheep samples were collected in Labu, where anthelminthic drug treatment

was conducted more regularly. Nevertheless, previous studies have shown that some

indigenous sheep breeds exhibit higher levels of resistance against gastrointestinal

parasites and this might partially explain the present findings (Baker and Gray, 2004).

PNG Priangan sheep are native to tropical climates, as they originated from Southeast

Asia and have been exposed to gastrointestinal parasites in PNG for over a century

(Quartermain, 2004a). In contrast, Highlands Halfbred sheep, which are crossbreeds of

the PNG Priangan sheep and the temperate Corriedale and Perendale breeds have only

a fraction of this resistance and will therefore be more susceptible to infection. More

detailed studies on immunology and feeding behaviour of the different sheep breeds

are required to elucidate this problem further.

The trematode, Fasciola, was present in sheep and goats in research institutes

(Labu and Tambul), smallholder farm (Benabena), and the public institution (Baisu). A

previous study in PNG found Fasciola in the area of Aiyura (Eastern Highlands

province) and showed that the sheep there were exposed to continual (low-level)

pasture contamination leading to chronic fasciolosis at all times (Owen, 1989). In PNG,


125

in all areas where the intermediate snail host, Lymnaea species, exists, acute

fasciolosis can occur in the wet season especially in areas where the land is not well-

drained and the grazing pressure is high (Owen, 1989).

This is the first study reporting the prevalence of the lungworm, Dictyocaulus,

in small ruminants in PNG. Some studies have found that goats are more susceptible to

Dictyocaulus than sheep (Sharma, 1994; Berrag and Urquhart, 1996; Alemu et al.,

2006). This study found a low prevalence (3.6 %) of Dictyocaulus in goats from Labu

(lowland) whereas, previous studies reported a high prevalence (12 – 60 %) (Alemu et

al., 2006). The observed difference between the present and previous studies could be

due to the life cycle stages of the parasite. In the prepatent or post-patent phases or

during hypobiosis, it is impossible to detect these parasites by faecal examinations

(Frasser, 1991).

3.5 Conclusions

In conclusion, the information collected in this study is an important update on

the presence of gastrointestinal parasites in sheep and goats in PNG. Future

investigations should include longitudinal studies and larger cohorts to further assess

parasite epidemiology in the diverse agro-climatic zones in the country. In addition,

further research is necessary to characterise the prevalence of various Eimeria species

in young lambs, goat kids and cattle to more fully understand the transmission

dynamics of Eimeria among ruminants in PNG.

Chapter 4

4. Molecular characterisation of

Cryptosporidium in sheep, goats and fish

from PNG


The contents of in this chapter have been published as journal articles and they

can be found in Appendix C and D.

[1] Koinari M, Lymbery AJ and Ryan UM, 2014. Cryptosporidium in sheep and goats

from Papua New Guinea. Experimental Parasitology 141, 134-137.

[2] Koinari M., Karl S., Ng-Hublin J., Lymbery A.J. and Ryan U.M., 2013. Identification

of novel and zoonotic Cryptosporidium species in fish from Papua New Guinea.

Veterinary Parasitology 198, 1-9.

This chapter describes molecular screening and genotyping of Cryptosporidium

species and subtypes in sheep, goats and fish.


The overall prevalences for Cryptosporidium was 2.2 % (6/276), 4.4 % (10/228),

1.14 % (7/614) in sheep, goats and fish, respectively, at the 18S rRNA locus.

In sheep, C. parvum (subtypes IIaA15G2R1 and IIaA19G4R1), C. andersoni and

C. scrofarum were identified.

In goats, C. hominis (subtype IdA15G1), C. parvum, C. xiaoi and rat genotype II

were identified.

In fish, C. hominis (subtype IdA15G1) and C. parvum (IIaA14G2R1, IIaA15G2R1

and IIaA19G4R1) and a novel genotype (which we have named,

Cryptosporidium sp. piscine genotype 8) were identified.

4.1 Introduction

Species of Cryptosporidium are globally distributed, zoonotic intestinal

protozoan parasites that cause diarrheal disease in animals and are one of the main

causes of serious diarrhoea in children (Kotloff et al., 2013). Clinical effects of

Cryptosporidium infection, which include diarrhoea, weight loss and often death in

lambs and goat kids, can severely impact the economy of sheep and goat farming (de

Graaf et al., 1999). In fish, Cryptosporidium can cause high morbidity with clinical signs

including variable levels of emaciation, poor growth rates, swollen coelomic cavities,


129

anorexia, listlessness and increased mortality (Murphy et al., 2009). Further details on

Cryptosporidium are described in Chapter 1, Section 1.4.

Little is known of the prevalence of Cryptosporidium spp. in humans,

domesticated animals or wildlife in PNG. Therefore, the aim of the present study was

to screen sheep, goats and fish for Cryptosporidium using molecular tools.

4.2 Methods

This section summarises the most important methods used to obtain the

results described in this chapter. A detailed description of all the methods is given in

Chapter 2 of this thesis. A schematic representation of methods used for molecular

detection is shown in Figure 4-1.

Figure 4-1: Flow chart of the methodology for molecular detection of Cryptosporidium spp. in the present study. DNA was extracted using commercial kits. Nested PCRs were performed and the amplified products were visualized on the gel. Amplification of the 18S rRNA, gp60 and actin loci produced approximately 298 bp, 400 bp and 278 bp products in length, respectively. The PCR products were sequenced and phylogenetic analyses were conducted.


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Faecal samples from a total of 276 sheep and 228 goats were collected from

February 2011 to April 2011 in a variety of agro-economic zones in PNG. The details of

the study sites, sheep and goats, and type of farms are described in Chapter 2, Sections

2.3 - 2.5.1.

A total of 614 fish from three different groups of fish; cultured freshwater

fingerlings (juveniles), wild freshwater and wild marine were collected between

February and August 2011. The species and numbers of fish are listed in Table 2-3

(Chapter 2, Section 2.5.2). On average, the time when fish were caught and at the stalls

before being sold was 2 h and the time lag between purchasing and processing the fish

was up to 4 h. The fish were weighed, measured (length and weight) and dissected.

Sections of intestine and stomach were cut using a fresh scalpel blade for each fish and

preserved in 70 % ethanol for molecular screening. The remaining stomach and

intestine were fixed in 10 % buffered formalin for histological analysis.

4.2.2 DNA isolation

Genomic DNA were extracted from 250 mg of faecal sample and fish tissue

scrapings using a PowerSoil® DNA isolation kit (MO BIO laboratories, Carlsbad, CA,

USA) according to manufacturer’s instructions and stored at -20 °C until screening. The

methods used are described in Chapter 2, Sections 2.8.1 and 2.8.3.

4.2.3 Cryptosporidium genotyping and subtyping

Identification of Cryptosporidium species and subtypes in faecal samples from

sheep and goats and from fish gut scrapings were performed using PCR and sequence

analyses of the 18S rRNA region, and gp60 and actin genes (Fig. 4-1). Details of the

molecular techniques used are described in Chapter 2, Sections 2.9.3. and 2.10 - 2.15.

After sequencing, the nucleotide sequences were analysed using FinchTV 1.4.0

(Geospiza, Inc., Seattle, WA, USA). Each sequence was entered into GenBank using

BLAST (http://blast.ncbi.nlm.nih.gov) to search for matching known sequences.

Sequences generated as part of the present study were aligned with 35 18S, 10 gp60

and 23 actin reference sequences representing selected Cryptosporidium species and



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genotypes available in GenBank. Sequences were aligned using both Clustal Omega

(http://www.ebi.ac.uk/Tools/msa/clustalo/) and MUSCLE alignment (Edgar, 2004)

using MEGA5 software (Tamura et al., 2011) and the resultant alignments were

adjusted manually using the MEGA5 program.

Phylogenetic analyses were conducted in MEGA5 software (Tamura et al.,

2011) using neighbour joining (NJ), maximum parsimony (MP) and maximum likelihood

(ML) models for the 18S and actin loci only. Distance estimation was conducted using

MEGA5 (Tamura et al., 2011) based on evolutionary distances calculated using the p-

distance model (Nei and Zhang, 2006) and grouped using neighbour-joining.

Parsimony and maximum likelihood analyses were also conducted using the MEGA5

(Tamura et al., 2011). The MP trees were obtained using the close-neighbour-

interchange (CNI) algorithm (Nei and Kumar, 2000) with search level 3 in which the

initial trees were obtained with the random addition of sequences (1 replicate).

Evolutionary history was inferred using maximum likelihood. Reliabilities for the trees

were tested using 1000 bootstrap replications (Felsenstein, 1985) and bootstrap values

exceeding 70 were considered well supported (Hills and Bull, 1993).

4.2.4 GenBank nucleotide accession numbers

The partial 18S and gp60 nucleotide sequences for Cryptosporidium derived

from sheep and goats were deposited in GenBank under the accession numbers

KJ584567 - KJ584584. The unique partial 18S rRNA and actin sequences of piscine

genotype 8 (from silver biddies) were deposited in GenBank under the accession

numbers KC807985 - KC807988.

4.2.5 Histological analysis

Sections of intestinal and stomach tissues of fish were fixed in 10 % formalin

and were embedded in paraffin. Histological sections were cut at 5 µm thicknesses,

stained with haematoxylin and eosin and examined with an Olympus BX50 light

microscope at 400 and 1000 fold magnifications.

http://www.ebi.ac.uk/Tools/msa/clustalo/


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4.2.6 Analysis of prevalence

Prevalences (isolates positive at 18S locus) were expressed as a percentage of

positive samples with 95 % confidence intervals calculated assuming a binomial

distribution, using the software Quantitative Parasitology 3.0 (Rozsa et al., 2000).

4.3 Results

4.3.1 Prevalence of Cryptosporidium in sheep, goats and fish.

Cryptosporidium was detected in 2.2 % (6/276; 95 % CI 2.8 % – 6.2 %) of sheep,

4.4 % (10/228; 95 % CI = 2.8 % - 6.2 %) of goats and 1.14 % (7/614; 95 % CI 0.7 % - 1.6

%) of fish at the 18S rRNA locus. Among sheep, Cryptosporidium was detected in two

animals from research institutes, one from the government station and three from

smallholder flocks (Table 4-1). Among goats, Cryptosporidium was identified in four

animals from research institutional farms and six from smallholder farms (Table 4-1).

Of the seven positive isolates from fish, two (1.5 %, 95 % CI 0.4 % - 2.8 %) were

cultured fingerlings, one (0.5 %, 95 % CI 0.0 % - 1.1 %) was a wild freshwater species

and four (1.5 %, 95 % CI 0.7 % - 2.3 %) were wild marine species. The prevalence of

Cryptosporidium for specific species of fish in each study location is given in Table 4-2.

Table 4-1: Prevalence of Cryptosporidium spp. in different farm types in sheep and goats in the present study. N = the total number of faecal samples for sheep and goats. P = the prevalence, which is the number of animals, which were positive for Cryptosporidium at the 18S locus. Given in parentheses are the percent prevalence and 95 % confidence interval (CI).

Type of farms N P (%, 95 % CI)

Sheep

Research Institute 156 2 (1.28, 0.22-5.03)

Public Institute 26 0

Government 40 1 (2.5, 0.13-14.73)

Smallholder 54 3 (5.56, 1.45-16.35)

Total 276 6 (2.2, 0.8-4.9)

Goat

Research Institute 78 4 (5.13, 1.66-13.31)

Public Institute 39 0

Government 6 0

Smallholder 105 6 (5.71, 2.34-12.52)

Total 228 10 (2.25-8.16)


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Table 4-2: Prevalence of Cryptosporidium spp. in fish in the present study. N = the total number of fish sampled. P = the prevalence, which is the number of animals, which were positive for Cryptosporidium at the 18S locus. Given in parentheses are the percent prevalence and 95 % confidence interval (CI). Cultured = all fish were from freshwater fish-ponds.

Study locations Host Group N P (%, 95 % CI

Kundiawa Nile tilapia Cultured 36 1 (2.78, 0.15-16.21

Mumeng Nile tilapia Cultured 26 1 (3.85, 1.2-21.59)

Pagwi Silver barb Wild freshwater 39 1 (2.56, 0.13-15.07)

Bilbil Mackerel scads Wild marine 5 1 (20, 1.05-70.12)

Pilapila Mackerel scads Wild marine 24 1 (4.17, 0.22-23.12)

Tavana Silver biddy Wild marine 29 2 (6.9, 1.2-24.22)

4.3.2 Molecular characterisation of Cryptosporidium species identified

in sheep, goats and fish at the 18S, gp60 and actin locus

Based on comparison with 18S rRNA nucleotide sequences available in

GenBank database, three species of Cryptosporidium were detected in sheep, namely

C. parvum (n = 4), C. andersoni (n = 1) and C. scrofarum (n = 1). Four species/genotypes

were detected in goats; C. hominis (n = 6), C. parvum (n = 2), C. xiaoi (n = 1) and rat

genotype II (n = 1) (Table 4-3). Rat genotype II, C. xiaoi, C. scrofarum and C. andersoni

isolates were detected in animals from smallholder farms. The C. hominis isolates were

from smallholder (n = 4) and institutional (n = 2) farms, while C. parvum was identified

in animals from three types of farms; government (n = 1), institutional (n = 3) and

smallholder (n = 2). Analysis of the gp60 gene identified the presence of two C. parvum

subtypes; IIaA15G2R1 (n = 3) and IIaA19G4R1 (n = 2) in sheep and goats and a

C. hominis subtype (IdA15G1) (n = 1) in a goat (Table 4-3). The phylogenetic

relationship between sequences obtained from sheep and goats in the present study

and other Cryptosporidium species or genotypes is shown in Figure 4-2.

In fish, sequence analyses identified C. parvum (5 isolates: Nile tilapia ON36

and ON68, mackerel scad DM17 and DM18, and silver barb PG37) and a novel piscine

genotype (2 isolates: silver biddy GO18 and GO55), hereafter referred to as piscine

genotype 8 at the 18S rRNA locus (Table 4-4). At the gp60 locus, three subtypes


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belonging to C. parvum (IIaA14G2R1, IIaA15G2R1, IIaA19G4R1) and one subtype

belonging to C. hominis (IdA15G1) were identified (Table 4-4).

The two piscine genotype 8 isolates from silver biddies were genetically

identical to each other, but distinct from all isolates previously characterised at the 18S

rRNA locus. Analyses of the 18S rRNA nucleotide sequences revealed that piscine

genotype 8 is closely related to piscine genotype 3 from a sea mullet with 4.3 %

genetic difference (i.e. 95.4 % genetic similarity) (Table 4-5). Neighbour-joining,

parsimony and maximum likelihood analyses produced similar results and indicated

that piscine 8 genotype, clustered most closely with the piscine 3 genotype from a sea

mullet, while the other five isolates clustered with C. parvum (85 % bootstrap support)

(Fig. 4-3). Sequences were also obtained for the two piscine genotype 8 isolates at the

actin locus. At this locus, sequence information was only available for C. molnari and

piscine genotype 1 and piscine genotype 8 grouped more closely with C. molnari

genotypes (Fig. 4-4) with 7.3 % - 8.5 % genetic differences (91.5 % to 92.7 % genetic

similarities) (Table 4-5).

Table 4-3: Species and subtypes of Cryptosporidium identified in sheep and goats in the present study.

Sample Host Species identified at the 18S locus

Type of farm gp60 subtype

GE51 Goat C. hominis Smallholder _



GE78 Goat C. hominis Smallholder IdA15G1

GM14 Goat C. hominis Research Institution _

GW10 Goat C. hominis Research Institution _

GM35 Goat C. parvum Research Institution IIaA19G4R1

GW19 Goat C. parvum Research Institution IIaA15G2R1

SW29 Sheep C. parvum Research Institution _

SE03 Sheep C. parvum Government IIaA15G2R1

SE83 Sheep C. parvum Smallholder IIaA15G2R1

SW106 Sheep C. parvum Research Institution IIaA19G4R1

SE67 Sheep C. scrofarum Smallholder _

SE79 Sheep C. andersoni Smallholder _

GE102 Goat C. xiaoi Smallholder _

GE01 Goat Rat genotype II Smallholder _


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Table 4-4: Species, genotypes and subtypes of Cryptosporidium identified in fish in the present study. Sample DM18 was typed as C. parvum at the 18S locus but at gp60 locus it was typed as C. hominis (IdA15G1) indicating a mixture of C. parvum/C. hominis in this sample. Cultured = all fish were from freshwater fish-ponds.

Sample Host species Group 18S GP60 Actin

ON36 Nile tilapia Cultured C. parvum IIaA19G4R1 -

ON68 Nile tilapia Cultured C. parvum IIaA14G2R1 -

PG37 Silver barb Wild freshwater

C. parvum IIaA19G4R1 -

DM17 Mackerel scad Wild marine C. parvum IIaA15G2R1 -

DM18 Mackerel scad Wild marine C. parvum, IdA15G1 -

GO18 Silver biddy Wild marine Piscine genotype 8

- Piscine genotype 8

GO55 Silver biddy Wild marine Piscine genotype 8

- Piscine genotype 8

Table 4-5: Percentage genetic differences between piscine genotype 8 and other Cryptosporidium species/genotypes at the 18S rRNA and actin loci. * = Actin sequences were not available for these genotypes.

Species/subtypes 18S locus Actin locus

Piscine genotype 1 13.0 17.4

Piscine genotype 2 5.1 Not analysed*






C. molnari 10.8 7.3-8.5

C. parvum 15.4 21.4

C. hominis 15.4 21.4

C. bovis 17.7 19.0

C. baileyi 14.7 19.4

C. muris 15.0 19.4

C. andersoni 13.8 20.1

4.3.3 Microscopy

No parasites were observed during microscopic examination of the intestinal or

stomach tissues due to substantial autolysis of tissues.


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Figure 4-2: Evolutionary relationships of Cryptosporidium isolates from sheep and goats inferred by neighbour-joining analysis of p distances calculated from pairwise comparison of 18S rRNA sequences. The percentage of replicate trees, in which associated taxa clustered together in the bootstrap test (1000 replicates) are shown at the internal nodes (> 50 % only) for distance, parsimony and maximum likelihood approaches (n.s. = not supported). Accession numbers are given in parentheses. Isolates from the present study are marked with an asterisk (*).


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Figure 4-3: Evolutionary relationships of Cryptosporidium piscine-derived isolates inferred by neighbour-joining analysis of p distances calculated from pairwise comparison of 18S rRNA sequences. The percentage of replicate trees, in which associated taxa clustered together in the bootstrap test (1000 replicates) are shown at the internal nodes (> 50 % only) for distance, ML and parsimony (n.s. = not supported). Accession numbers are


138

given in parentheses. Isolates from the present study are marked with asterisk (*).

Figure 4-4: Phylogenetic relationships of Cryptosporidium isolates inferred by neighbor-joining analysis of the actin gene based on genetic distances calculated by the p distance model. The percentage of replicate trees, in which associated taxa clustered together in the bootstrap test (1000 replicates) are shown at the internal nodes (> 50 % only) for distance, ML and parsimony (n.s. = not supported). Accession numbers are given in parentheses. Isolates from the present study are marked with asterisk (*).


4.4 Discussion

Cryptosporidium in sheep and goats

This is first study to identify and molecularly characterise Cryptosporidium in

sheep and goats in PNG and analysis revealed a high diversity of Cryptosporidium

parasites within these animal populations. The only other previous study of

Cryptosporidium in PNG identified Cryptosporidium antibodies in 24 % of young

children from Goroka (Groves et al., 1994).

Although point prevalences were low for Cryptosporidium in the present study,

the true prevalence may be underestimated as only single faecal samples were

screened at one time point and intermittent shedding and seasonal variation are

common (O'Handley et al., 1999). In addition, only adult animals were screened and

prevalences are known to be much higher in younger animals (Santin et al., 2007).

Most importantly, the identification of Cryptosporidium in livestock warrants better

care of farm animals to avoid contamination and illness in vulnerable populations, as

Cryptosporidium spp. are known to cause diarrhoea and mortality in lambs and goat

kids (de Graaf et al., 1999; Quilez et al., 2008; Giles et al., 2009).

The three species (C. parvum, C. andersoni and C. scrofarum) identified in

sheep from the present study have also been reported in sheep in previous studies

(Ryan et al., 2005; Santin et al., 2007; Quilez et al., 2008; Giles et al., 2009). In addition,

C. andersoni is frequently reported in cattle and occasionally in humans, while

C. scrofarum is commonly identified in pigs (Xiao, 2010). Cryptosporidium ubiquitum is

a common species found in sheep in other countries (Ryan et al., 2005; Santin et al.,

2007; Yang et al., 2009; Wang et al., 2010b), however, it was not identified in the

present study.

Three species, C. hominis, C. parvum and C. xiaoi, detected in goats in the

present study have also been reported in goats in other studies (Goma et al., 2007;

Geurden et al., 2008b; Quilez et al., 2008; Giles et al., 2009; Diaz et al., 2010b;). For

example, molecular analyses confirmed infections with C. hominis and C. parvum in

diarrheic goat kids in the UK (Giles et al., 2009) and C. parvum in goats in Spain (Quilez

et al., 2008). Cryptosporidium xiaoi is commonly reported in sheep (Fayer and Santin,


140

2009) and occasionally in goats (Diaz et al., 2010b). This is the first report of rat

genotype II in goats. Rat genotype II has been reported in house rats in China (Lv et al.,

2009) and in the Philippines (Ng-Hublin et al., 2013), brown rats in the Philippines (Ng-

Hublin et al., 2013), and in wild black rats in Northern Australia (Paparini et al., 2012).

The goat in which rat genotype II was identified was from a smallholder farm in

Benabena. Smallholders usually keep their goats in night houses, which are built very

close to their own homes in order to avoid theft. The goat could have acquired this

genotype from the house rats; however, further studies are required to confirm this

and to determine if the goat was actually infected or just passing oocysts from

ingestion of rat faeces. Identification of species such as C. andersoni, C. scrofarum and

C. xiaoi in smallholder flocks probably reflects the management system. Typically,

these small ruminants are tethered and/or allowed to graze freely on shrubs and

grasses along road sides, near homes and gardens, where they share the feeding

grounds with other livestock, especially cattle and pigs.

Cryptosporidium hominis and C. parvum are the most common causes of

cryptosporidiosis in humans worldwide (Xiao, 2010). In the present study, C. hominis

(subtype IdA15G1) was found in goats and C. parvum (subtypes IIaA15G2R1 and

IIaA19G4R1) was found in both sheep and goats. The C. parvum subtype, IIaA15G2R1,

has been reported in sheep and goats in previous studies in Belgium, Spain, Brazil,

China and Australia (Geurden et al., 2008b; Diaz et al., 2010a; Paz et al., 2014; Yang et

al., 2014a; Ye et al., 2014). The C. parvum subtype, IIaA15G2R1, is a common subtype

in cattle and humans ( Xiao, 2010; Feng et al., 2013) in the Americas, Europe, Northern

Africa and Asia (Quilez et al., 2008; Santin et al., 2008; Soba and Logar, 2008; Brook et

al., 2009; Geurden et al., 2009; Amer et al., 2010; Diaz et al., 2010a; Meireles et al.,

2011; Iqbal et al., 2012; Alyousefi et al., 2013; Helmy et al., 2013; Rahmouni et al.,

2014; Rieux et al., 2013). It has also been found in yaks in China (Mi et al., 2013) and in

buffalo in Egypt (Helmy et al., 2013). The C. parvum subtype, IIaA19G4R1, was

identified in both a goat and a sheep in the present study. Previously, C. parvum

subtype IIaA19G4R1 was identified in cattle in Northern Ireland (Thompson et al.,

2007) and Australia (Ng et al., 2008).


141

Cryptosporidium in fish

In fish, the overall prevalence of Cryptosporidium sp. was low (1.14 %, 7/614).

Previous studies have also reported low prevalences in similar groups of fish (0.8 %,

6/709) (Reid et al., 2010) and in ornamental fish (3.5 %, 6/171) (Morine et al., 2012),

while others have reported higher prevalences (10 - 100 %) mostly among juvenile fish

(Alvarez-Pellitero et al., 2004; Sitja-Bobadilla et al., 2005; Murphy et al., 2009; Zanguee

et al., 2010).

The present study identified three new fish hosts for Cryptosporidium; silver

barb (P. gonionotus), mackerel scad (D. macarellus) and oblong silver biddy

(G. oblongus). The fourth host Nile tilapia (O. niloticus) could also be a new host since

previous studies have detected Cryptosporidium in the same genus but did not

identified the species (Landsberg and Paperna, 1986; Paperna and Vilenkin, 1996).

No oocysts or life cycle stages were observed in the infected fish hosts in the

present study due to substantial autolysis of tissues, which has been reported as an

issue for Cryptosporidium detection in piscine hosts (Zanguee et al., 2010). Fish are

known to have a very rapid rate of tissue autolysis compared to homeotherms

(Roberts, 2012) and many of the fish were dead for up to 4 hours prior to being

processed, which contributed to the problem. Previous studies have provided

histological and electron microscopic evidence of considerable cellular damage

associated with several Cryptosporidium species/genotypes that infect fish; C. molnari

in the stomach of fingerlings and juveniles of gilt-head sea bream (Alvarez-Pellitero

and Sitja-Bobadilla, 2002), piscine genotype 1 in the stomach of a guppy (Ryan et al.,

2004) and piscine genotype 3 in the intestine of a mullet (Reid et al., 2010). Piscine

genotype 2 was associated with gastric infections in angelfish, with the greatest

morbidity and mortality seen in larval and juvenile fish (Murphy et al., 2009). Whether

the C. parvum and C. hominis identified in the present study represents actual or

mechanical infections remains to be determined as the oocysts may have been passing

through rather than infecting these fish and further research using histological analysis

of rapidly preserved tissue specimen is required to confirm this.


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The zoonotic Cryptosporidium genotypes identified in this study are of

significance to public health. Cryptosporidium parvum subtypes IIaA14G2R1,

IIaA15G2R1 and IIaA19G4R1 were found in cultured freshwater (Nile tilapia), wild

freshwater (silver barb) and a marine (mackerel scad) fish. The zoonotic C. parvum IIa

subtype family has predominantly been found in calves and in humans in North

America, Europe and Australia (Xiao, 2010). Only one study has previously detected

zoonotic C. parvum (subtype IIaA18G3R1) in a marine fish (Reid et al., 2010). The

presence of IIa subtypes in the fish samples from the present study could be due to

waterborne contamination with human and animal wastes. Human sewage

management systems in PNG villages typically involve dugout toilets near the homes

and toilets built over the rivers or seas. No cattle farms were seen in close vicinity to

where the samples were collected, whereas dugout toilets, companion animals and/or

domesticated poultry and pigs were seen in the environment. Fish-ponds, rivers and

seas could be contaminated from rainwater runoff and from humans and/or animals

bathing in them. A previous study has detected antibodies against Cryptosporidium

among children from PNG (Groves et al., 1994), however, no molecular work has been

done to confirm the species or genotypes present.

One marine fish (mackerel scad DM18) was identified as C. parvum at the 18S

locus, while at the gp60 locus it was subtyped as C. hominis IdA15G1R1, indicating that

a mixed C. parvum/C. hominis infection was present. This is the first report of

C. hominis in fish. The only other marine organism, in which C. hominis has been

reported was a dugong (Dugong dugon) (Morgan et al., 2000), and its presence

probably reflects human sewage contamination of the water.

The novel piscine genotype 8 was identified in two marine silver biddies. At the

18S locus, piscine genotype 8 exhibited 4.3 % genetic difference with piscine genotype

3 and 13.8 % - 17.7 % genetic difference with other Cryptosporidium spp. (Table 4-5).

At the actin locus, piscine genotype 8 exhibited 7.3 % genetic difference with

C. molnari 2 and 19.0 % - 21.4 % with other Cryptosporidium spp. (Table 4-5). Based on

the differences in the genetic sequences, piscine genotype 8 is unique and may

represent a new species; however, further research is required to confirm this.


143

4.5 Conclusions

These findings suggest that sheep and goats may be important reservoirs of

C. hominis and zoonotic C. parvum subtypes in PNG. The detection of C. hominis in

goats presumably reflects the very close association between humans and goats.

Further research is necessary to characterise the prevalence of various

Cryptosporidium species and genotypes in young lambs, goats and cattle and other

hosts such as humans to more fully understand the transmission dynamics of

Cryptosporidium in PNG.

The present study identified zoonotic C. parvum subtypes in fish species, which

are frequently eaten in PNG. Previous studies have not identified conclusive evidence

for transmission of Cryptosporidium from fish to humans but one study reported that

urban anglers are at a risk for contracting cryptosporidiosis from exposures received,

while fishing and consuming caught fish (the mean probability of infection was nearly

one) (Roberts et al., 2007). It is therefore essential that fish for human consumption

are handled appropriately to avoid contamination. In addition, a novel

Cryptosporidium sp. (piscine genotype 8) was identified based on molecular data but

lacks histological details of infection or morphological features of the oocysts, thus

future work is required to establish this genotype as a species.

Chapter 5

5. Prevalence of Giardia duodenalis in sheep,

goats and fish from PNG by quantitative

PCR


This chapter describes work conducted using a qPCR assay to screen for Giardia

duodenalis in sheep, goats and fish from PNG.


The overall prevalence for G. duodenalis in sheep, goats and fish were 9.1 %

(25/276), 12.3 % (28/228) and 7 % (19/272), respectively.

Giardia duodenalis was found in sheep and goats in all farm types and in fish in

all three groups (cultured freshwater, wild freshwater and wild marine).

5.1 Introduction

Giardiasis is a re-emerging infectious disease of worldwide significance caused

by Giardia duodenalis (Thompson, 2000). Giardia-induced diarrhoea is common in

sheep and goats. It can cause significant economic loss to farmers (O'Handley et al.,

2001; Aloisio et al., 2006). See further details on Giardia in Chapter 1, Section 1.5.

Little is known about Giardia infections in fish. A recent study in Australia

identified a low prevalence of Giardia (3.8 % - 27/709) in fish hosts (Yang et al., 2010)

with G. microti and both zoonotic (A and B) and non-zoonotic (E) assemblages of

G. duodenalis detected. Whether the fish in the latter study were truly infected with

those Giardia species or simply served as mechanical vectors for the dissemination of

waterborne Giardia cysts is unclear (Feng and Xiao, 2011). Another study, in Egypt,

identified G. duodenalis (assemblage A) in farmed and wild freshwater fish host with a

prevalence of 3.3 % (Ghoneim et al., 2011).

Giardia duodenalis is common in sheep and goats, but there are no records of

infection or prevalence in these animals or other animals in PNG (Owen, 2005).

Infections in humans with G. duodenalis have been reported in several surveys in the

country (Owen, 2005). However, the importance of G. duodenalis as the causative

agent of diarrhoea in PNG has not been assessed. As little is known of the prevalence

of Giardia spp. in humans, domesticated animals or wildlife in PNG, the aim of the

present study was to screen sheep, goats and fish for G. duodenalis using molecular

tools.


147

5.2 Methods


results described in this chapter. A detailed description of all the methods is described

in Chapter 2 of this thesis.


Samples were collected from sheep, goats and fish in various locations in PNG

from February 2011 to August 2011. Further details of sampling are described in

Chapter 2, Sections 2.1 - 2.6.

5.2.2 DNA isolation and qPCR amplification

Genomic DNA were extracted from 250 mg of faecal sample and fish tissue

scrapings using a PowerSoil® DNA isolation kit (MO BIO laboratories, Carlsbad, CA,

USA) as described in Chapter 2, Sections 2.8.1 and 2.8.3.

All samples were screened for the presence of G. duodenalis at the glutamate

dehydrogenase (gdh) locus using a qPCR assay as previously described (Yang et al.,

2014b). The details of this assay are described in Chapter 2, Section 2.9.4.

5.2.3 Data analysis

Prevalences (samples which were positive for G. duodenalis at the gdh locus)

were expressed as a percentage of positive samples; with 95 % confidence intervals

calculated assuming a binomial distribution, using the software Quantitative

Parasitology 3.0 (Rozsa et al., 2000). Differences in prevalence among groups were

compared by Fisher’s exact test (FET) (for two groups) or chi-square analysis (for more

than two groups). Where multiple pairwise comparisons were made among groups, a

Bonferroni correction was applied to maintain an experiment-wide Type I error rate of

5 %.

5.3 Results

The overall prevalence of G. duodenalis was 9.1 % (25/256) in sheep, 12.3 %

(28/228) in goats and 7 % (19/272) in fish. For each farm type, the prevalence for

sheep ranged from 5 – 12.2 % and for goats from 8.6 – 66.7 % (Table 5-1). There was

no significant difference in prevalence between sheep and goats (FET: p = 0.2474).


148

There were no significant differences in prevalence of Giardia in sheep between farm

types (FET: p > 0.005) (Table 5-2). There were, however, differences in prevalence of

Giardia in goats between farms (Table 5-2). Specifically, the prevalence of

G. duodenalis in goats was higher in Menifo compared to Labu, Tambul and Baisu (p

values < 0.005).

In the three groups of fish, the prevalence was 4.1 % (5/121) in cultured

freshwater fish, 7.7 % (1/13) in wild freshwater fish and 9.4 % (13/138) in wild marine

fish (Table 5-3). There were no significant difference in the prevalences between the

fish groups (Chi-square: p values where larger than 0.05). Giardia duodenalis was

identified in eight fish species; Nile tilapia (n = 4), common carp (n = 1), Java carp

(n = 1), mackerel scad (n = 2), rainbow runner (n = 2), big eye scad (n = 4), reef

needlefish (n = 3) and oriental bonito (n = 4) (Table 5-4).

Table 5-1: Prevalence of G. duodenalis in sheep and goats in different farm types in the present study. N = the total number of faecal samples for sheep and goats. P = the number of animals, which were positive for Giardia. Given in parentheses are percent prevalence and 95 % confidence interval (CI).

Type of farm N P (%, 95 % CI)

Sheep

Lowland research institute (Labu) 40 2 (5, 0.9 - 18.2)

Highland research institute (Tambul) 115 14 (12.2, 7.1 - 19.9)

Public institute (Baisu) 27 2 (7.4, 1.3 - 25.8)

Government (Menifo) 40 2 (5, 0.9 - 18.2)

Smallholder 54 5 (9.3, 3.5 - 21.1)

Total 276 25 (9.1, 6.1 - 13.2)

Goats

Lowland research institute (Labu) 43 4 (9.3, 3.0 - 23.1)

Highland research institute (Tambul) 35 3 (8.6, 2.2 - 24.2)

Public institute (Baisu) 39 5 (12.8, 4.8 - 28.2)

Government (Menifo) 6 4 (66.7, 24.1 - 94.0)

Smallholder 105 12 (11.4, 6.3 - 19.5)

Total 228 28 (12.3, 8.5 - 17.4)


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Table 5-2: Comparisons of prevalences for G. duodenalis in sheep and goats between farm types. All pairs of farms were compared by FET. A Bonferroni correction was used to determine significance at p values < 0.005. * = values are significantly different between farm types by FET. RI = research institute, PI = public institute.

Data sets Sheep Goats

p values p values

Lowland RI (Labu) vs Highland RI (Tambul) 0.3619 1.0000

Lowland RI (Labu) vs PI (Baisu) 1.0000 0.7298

Lowland RI (Labu) vs Government (Menifo) 1.0000 0.0043*

Lowland RI (Labu) vs Smallholder 0.6947 1.0000

Highland RI (Tambul) vs PI (Baisu) 0.7385 0.7143

Highland RI (Tambul) vs Government (Menifo) 0.3619 0.0045*

Highland RI (Tambul) vs Smallholder 1.0000 0.7614

PI (Baisu) vs Government (Menifo) 1.0000 0.0103

PI (Baisu) vs Smallholder 1.0000 0.0103

Government (Menifo) vs Smallholder 0.6947 0.0038*

Table 5-3: Prevalence of G. duodenalis in fish from the three groups of aquatic environments in the present study.N = the total number of fish samples. P = the number of animals, which were positive for Giardia. Given in parentheses are percent prevalences and 95 % confidence intervals (CI).

Group N P (%, 95 % CI)

Cultured freshwater 121 5 (4.1, 1.5 - 9.6)

Wild freshwater 13 1 (7.7, 0.4 – 37.9)

Wild marine 138 13 (9.4, 5.3 – 15.9)

Total 272 19 (7.0, 4.4 – 10.9)

Table 5-4: Prevalence of G. duodenalis in different fish hosts in the present study. N = the total number of fish samples. P = the number of animals, which were positive for Giardia. Given in parentheses are percent prevalences and 95 % confidence intervals (CI). Cultured = fish from freshwater fish ponds/farms.

Fish group Scientific name Common name N P (%, 95 % CI)

Cultured Oreochromis niloticus Nile tilapia 80 4 (5, 1.3 - 13)

Cultured Cyprinus carpio Common carp 41 1 (2.4, 0.13 - 14.4)

Wild freshwater Puntius gonionotus Java carp 13 1 (7.7, 0.4 - 37.9)

Marine Decapterus macarellus Mackerel scad 27 2 (7.4, 1.3 - 25.8)

Marine Elagatis bipinnulatus Rainbow runner 5 2 (40, 7.3 - 83)

Marine Selar crumenophthalmus Bigeye scad 77 4 (5.2, 1.7 - 13.5)

Marine Strongylura incisa Reef needlefish 4 3 (75, 21.9 - 98.7)

Marine Sarda orientalis Oriental bonito 4 2 (50, 9.2 - 90.8)

Total 251 19 (7.6, 4.7 - 11.8)


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5.4 Discussion

This is the first study to identify Giardia spp. in sheep, goats and fish from PNG.

In the present study, G. duodenalis was found in adult sheep in all types of farming

environments, giving an overall prevalence of 9.1 % (25/276). This prevalence rate is

higher than a previous study in Italy, which detected a prevalence of 1.5 % (5/325) in

sheep using nested PCRs targeting the gdh and beta-giardin gene (Giangaspero et al.,

2005), but its lower than most other studies investigating G. duodenalis in post-

weaned/adult sheep. In those studies, the prevalences were 44 % (220/500) in

Australia (Ryan et al., 2005), 37.5 % (12/32) in the US (Santin et al., 2007) and 19.2 %

(86/446) in Spain (Castro-Hermida et al., 2007). The first two of these studies were

based on PCR analyses, while the latter study used immunofluorescent antibody tests.

The prevalence of G. duodenalis in adult goats in the present study was 12.3 %

(28/228) by qPCR analysis of the gdh gene. This rate falls in the range of reported

prevalences for G. duodenalis in adult goats in other countries. For example, in

Malaysia, a low prevalence (6.8 %, 21/310) of Giardia was found in goats (≥ 3 years of

age) using nested PCR of the 18S locus (Lim et al., 2013), while in Spain, it was 19.8 %

(23/116) in healthy adult goats using immunofluorescent antibody tests (Castro-

Hermida et al., 2007). However, a similar prevalence (14.3 % - 15/105) has also been

reported in goat kids (< 12 months old) in Brazil (Bomfim et al., 2005). Generally, high

prevalences of G. duodenalis have been reported in young goats (< 10 months old). For

example, in Spain, 42.6 % (133/315) were positive using molecular tools targeting the

beta-giardin and tpi genes (Ruiz et al., 2008) and in Belgium, 35.5 % (53/148) were

positive using immunofluorescent antibody tests (Geurden et al., 2008b).

Although the present finding showed that the prevalence of G. duodenalis in

goats was higher in Menifo as compared to the institutional farms, this may not be a

very accurate estimate as the total number of goats from Menifo, which were

screened for Giardia was small (n = 6).

The prevalence of G. duodenalis was low (7 %, 19/272) in fish in the present

study (Table 5-3). These results complement previous findings on overall low


151

prevalences of Giardia spp. in fish in Australia (3.8 %, 27/709) and Egypt (3.3 %, 3/92)

(Yang et al., 2010; Ghoneim et al., 2011). In Australia, G. duodenalis cysts and

trophozoites were detected in tissue sections of ten fish isolates including a marine

fish (sea mullet), cultured fingerlings (barramundi, black bream and mulloway) and a

freshwater fish (mulloway) (Yang et al., 2010). Whether the G. duodenalis identified in

the present study represents actual or mechanical infections remains to be

determined; the cysts may have been passing through rather than infecting these fish

and further research using histological analysis of rapidly preserved tissue specimens is

required to confirm this.

The present study identified G. duodenalis in seven new fish hosts including

common carp, Java carp, mackerel scad, rainbow runner, big eye scad, reef needlefish

and oriental bonito. The prevalence of G. duodenalis in Nile tilapia was 5 % (4/80),

which is similar to that reported in Egypt (4.2 %) (Ghoneim et al., 2011).

The low prevalence of Giardia detected in the present study could be due to

low levels of Giardia infections at the time of sampling. The sensitivity and specificity

of the qPCR assay used in this study have been evaluated by Yang et al. (2014b) and its

detection limit was 1 Giardia cyst per μL of faecal DNA extract. PCR is sometimes

hindered by inhibitors in stool specimens, including bile acids, bilirubins, haem and

complex carbohydrates (Wilson, 1997). However, in the present study, internal

amplification controls (IACs), as described previously (Yang et al., 2013), were included

in all the qPCR reactions to monitor faecal inhibition (see Chapter 2, Section 2.9.1).

5.5 Conclusions

Although the present study found low prevalences for G. duodenalis in adult

small ruminants and fish, these animals can be considered as sources of contamination

for susceptible hosts in PNG. Even low numbers (as low as ten) of Giardia cysts may

lead to an infection in humans (Rendtorff, 1979). Furthermore, Giardia cysts are

immediately infectious upon excretion and also are resistant and able to survive for

several weeks in the environment, resulting in a gradual increase in environmental

infection pressure (Geurden et al., 2010b). Previous studies have shown that


152

G. duodenalis assemblage E (livestock genotype) is more prevalent in sheep and goats

than the zoonotic assemblages A and B (Geurden et al., 2010b), whereas a high

prevalence of zoonotic assemblages (A and B) have been reported in fish (Yang et al.,

2010; Ghoneim et al., 2011). In the present study, despite numerous attempts, it was

not possible to genotype the Giardia positives identified. Future studies are required

to genotype Giardia species and assemblages (genotypes) in these hosts and other

hosts including humans to fully understand the transmission dynamics of Giardia in

PNG.

Chapter 6

6. Morphological and molecular

characterisation of Anisakis species in fish

from PNG


The contents of this chapter have been published in the journal of Veterinary

Parasitology. The article is listed below and it can be found in Appendix E.

Koinari, M., Karl, S., Elliot, A., Ryan, U., Lymbery, A.J., 2013. Identification of Anisakis

species (Nematoda: Anisakidae) in marine fish hosts from Papua New Guinea.

Veterinary Parasitology 193, 126-133.

The chapter describes morphological and molecular analyses of anisakid

nematodes from wild marine fish from PNG.


This study identified only one species from the genus Anisakis, Anisakis typica,

and the overall prevalence was 7.6 %.

Anisakis typica was found in seven species of fish including Decapterus

macarellus, Gerres oblongus, Pinjalo lewisi, Pinjalo pinjalo, Selar

crumenophthalmus, Scomberomorus maculatus and Thunnus albacares (these

are new hosts for A. typica).

6.1 Introduction

The family Anisakidae includes parasitic nematodes of marine fauna. They have

a worldwide distribution and a complex life cycle, which involves invertebrates, fish,

cephalopods and mammals (Chai et al., 2005). Further details on anisakids are

described in Chapter 1, Section 1-6. Anisakid nematodes can accidentally infect

humans who can suffer from several symptoms including sudden epigastric pain,

nausea, vomiting, diarrhoea and allergic reaction (Sakanari and McKerrow, 1989;

Audicana and Kennedy, 2008). Most cases of human infection involve anisakid species

belonging to the genus Anisakis. There are nine described species of Anisakis, which

are further subdivided into two types (Fig. 6-1) (Mattiucci and Nascetti, 2008;

Mattiucci et al., 2009). Of these, only A. simplex s.s, A. pegreffii and A. physeteris have

been shown to cause infection in humans (Mattiucci et al., 2011; Arizono et al., 2012).


155

Figure 6-1: Type 1 and Type II Anisakis species belonging to the genus Anisakis.

Anisakid nematodes can be differentiated based on their morphological

characteristics and molecular data (Fig. 6-2). Larval morphological features including

the absence or presence of a ventricular appendage and an intestinal caecum are

useful for distinction between several anisakid genera (Shamsi and Butcher, 2011).

Anisakis Type I or Type II larvae can be identified based on ventriculus length and the

presence of a tail spine (or mucron) (Berland, 1961; Cannon, 1977). More recently,

PCR-based tools have been widely used for characterisation of anisakid species at

multiple loci as discussed in Chapter 1, Section 1-6.

Anisakid nematodes are a major public health concern. In the last thirty years,

there has been a marked increase in the prevalence of anisakidosis throughout the

world, due in part to growing consumption of raw or lightly cooked seafood (Lymbery

and Cheah, 2007; Audicana and Kennedy, 2008) . The highest number of cases (> 90 %)

come from Japan (with up to 1, 000 cases per year) due to consumption of raw fish

dishes such as sushi and sashimi (Oshima, 1972; Sugimachi et al., 1985). Most of the

rest of the cases are from other countries with a tradition of eating raw or marinated

fish, which include the Netherlands, France, Spain, Chile and the Philippines (Chai et

al., 2005; Choi et al., 2009). Anisakidosis is caused most commonly by Anisakis simplex

and Pseudoterranova decipiens (Table 6-1) (Hochberg and Hamer, 2010).

Fish are important sources of food and income for the majority of people living

in the mainland coastal areas as well as islands in PNG. Little is known about the

prevalence of zoonotic animal parasites such as anisakids in fish or of anisakidosis in

humans in PNG. A review paper mentioned A. simplex in skipjack tuna (Katsuwonus

Anisakis Type II larvae

• A. paggiae • A. physeteris* • A. brevispiculata

Anisakis Type I larvae

• Anisakis simplex s.s* • A. pegriffi* • A. simplex C • A. typica • A. ziphidarum • A. nascettii

Genus: Anisakis

*Zoonotic species


156

pelamis) in waters on the south coast of PNG, but did not provide any supporting

information (Owen, 2005). The present study was aimed at investigating the

distribution of anisakid species and specifically to screen for zoonotic species of

anisakids obtained in fish from PNG, using both morphology and molecular analyses.

Figure 6-2: Schematic representation of diagnostic features for differentiating anisakids.Anisakis sp. Type I larvae: the posterior end with a micron (see arrow)

(Image from Cannon, 1977).

Table 6-1: Common zoonotic anisakids-geographic distribution, hosts, common food dishes and diseases. Host species 1 = primary host species. Host species 2 = predominant second intermediate host species.

Nematode Geographic distribution

Host species 1

Host species 2

Common food dishes

Form of anisakidosis

Anisakis simplex Japan, Northern Europe, US, Korea

Dolphins, porpoises, whales

Pacific salmon, herring, anchovies, scad, hake, mackerel

Sushi, sashimi, salted or smoked herring, gravlax, borquerones. Hawaiian lomi-lomi, ceviche

Gastrointestinal, ectopic, allergy

Pseudoterranova decipiens

US, Canada Seals, walruses, sea lions

cod Ceviche, cod Oropharyngeal


157

6.2 Methods


results described in this chapter. A detailed description of all the methods can be

found in Chapter 2 of this thesis. An overview schematic representation of methods

used for sample collection and screening of anisakid nematodes in this study is shown

in figure 6-3.

6.2.1 Parasite collection

A total of 276 whole fresh fish were collected from markets in the coastal

towns of Madang (specific study sites: Bilbil and Madang) and Rabaul (specific study

sites: Pilapila and Tavana) from March to August 2011 (see Chapter 2, Sections 2.3 and

2.5). The fish were necropsied and nematodes were collected from the body cavities.

The muscles of the fish were thinly sliced and investigated under white light to check

for nematode larvae. Nematodes were preserved in 70 % ethanol and transported to

Murdoch University, Australia, for analysis.

6.2.2 Morphological analysis

Whole nematodes were cleared in lactophenol for more than 48 h, individually

mounted onto microscope slides and viewed under an Olympus BX50 light microscope

equipped with Olympus DP70 Camera at 40/100x magnification. The following features

were measured: body width, oesophagus length, ventriculus length and mucron

length. Morphological identification was conducted according to keys previously

reported (Berland, 1961; Cannon, 1977; Shamsi et al., 2009a, b). Scanning electron

micrographs (SEMs) were taken for representative specimens to study further

morphological details using a Phillips XL30 scanning electron microscope. Specific

details of specimen preparations are described in Chapter 2, Section 2.7.2.


158

Figure 6-3: Overview of the methods for collection and screening of anisakid nematodes in the present study. Nematodes were obtained from within the body cavities or muscle of marine fish and identified by light microscopy based on published keys and confirmed using scanning electron microscopy. Nematodes were then screened by PCR analyses of the ITS and cox2 gene. PCR products were sequenced and phylogenetic analyses were conducted.

6.2.3 Genetic characterisation and phylogenetic analysis

DNA from individual nematodes was isolated using a Qiagen DNeasy® blood

and tissue kit (Qiagen, Hilden, Germany) as described in Chapter 2, Section 2.8.2.

The ITS rRNA region was amplified using primers NC5 and NC2 (Zhu et al.,

1998). The mitochondrial DNA cytochrome oxidase II (mt-DNA cox2) gene was


159

amplified using primers 210 and 211 (Nadler and Hudspeth, 2000). PCR assays were

performed as previously described (Kijewska et al., 2009a; Valentini et al., 2006). The

specific details of the PCR assays are described in Chapter 2, Section 2.9.5.

All PCR products were purified using an Ultra Clean® DNA purification kit

(MolBio, West Carlsbad, CA, USA). Sequencing was performed using the ABI Prism

BigDye® terminator cycle sequencing kit (Applied Biosystems, Foster City, CA, USA) on

an Applied Biosystems 3730 DNA Analyser instrument according to manufacturer’s

instructions except that the annealing temperature was lowered to 46 °C for the cox2

locus. Nucleotide sequences obtained were analysed using FinchTV 1.4.0 (Geospiza,

Inc.; Seattle, WA, USA; http://www.geospiza.com) and compared with published

sequences for identification in the GenBank database using BLAST

(http://blast.ncbi.nlm.nih.gov) for species identification. (Further details of the

molecular techniques used for DNA processing are described in Chapter 2, Sections

2.10 - 2.15).

Before phylogenetic analysis, sequences were aligned with 9 ITS and 9 cox2

reference sequences, representing selected Anisakis species obtained from GenBank.

The nucleotide sequences were aligned using MUSCLE (Edgar, 2004), edited manually

and tested with MEGA5 model test to find the best DNA model to infer the

phylogenetic trees using the MEGA5 software (Tamura et al., 2011). Phylogenetic

analyses with other known anisakid species were conducted using both neighbour-

joining (NJ) and maximum-likelihood (ML) analyses for both loci. Evolutionary

relationships were calculated using the Kimura two-parameter model for ITS

sequences and the Tamura-Nei model for cox2 sequences with Contracaecum

osculatum as an outgroup. Reliabilities for both NJ and ML trees were tested using

1000 bootstrap replications (Felsenstein, 1985) and bootstrap values exceeding 70

were considered well supported (Hills and Bull, 1993). The nucleotide sequences were

deposited in GenBank under the accession numbers: JX648312 - JX648326.



160

6.3 Results

6.3.1 Prevalence of Anisakis spp.

The overall prevalence of anisakids in fish from PNG (based on ITS PCR

positives) was 7.6 % (21/276, 95 % CI = 4.9 - 11.6). Anisakid larvae were found in 7 fish

species, at prevalences ranging from 2.9 - 100 % (Table 6-2). The larvae were observed

mostly within the body cavities of the fish and intensity ranged from 1 to 6 per

infected fish host with the exception of Pinjalo pinjalo, which had an intensity of 120

larvae per fish, with larvae being found in many other body parts including muscles,

pyloric region and liver.

Table 6-2: Prevalence of anisakid larvae in different fish hosts in the present study as determined by PCR. N = the number of fish sampled. P = the number of fish, which had anisakid nematodes. Given in parentheses are the percent prevalences and 95 % confidence intervals (CI). Mean intensity (MI) is the mean number of larvae in the infected fish hosts ± SD (range). Where no SD value was given, there were only one or few positive observations and SD could not be calculated.

Fish host N P (% P, 95 % CI) MI ± SD (min-max)

Specimen code

Decapterus macarellus (mackerel scad)

29 2 (6.9, 1.2 - 24.2) 1 DM23, DM24

Gerres oblongus (silver biddy) 54 2 (3.7, 0.6 - 13.8) 3 ± 0.4 (2 - 4) GO14, GO15

Pinjalo lewisi (slender pinjalo) 14 7 (50, 24 - 76) 5 ± 0.92 (1 - 6) PL1-PL5, PL8, PL9

Pinjalo pinjalo (pinjalo snapper)

1 1 (100, 5.5 - 100) 120 PP1

Scomberomorus maculatus (Spanish mackerel)

3 1 (33.3, 1.8 - 87.5) 1 SM3

Thunnus albacares (yellow-fin tuna)

34 1 (2.9, 0.2 - 17.1) 3 TA3

Selar crumenophthalmus (big eye scad)

106

7 (6.7, 2.9 - 13.6) 2.9 ± 0.95 (1 - 3) SC76 - SC78, SC88, SC97, SC100, SC102

6.3.2 Morphology of Anisakis Type I larvae

Morphological analysis showed that all anisakid nematodes examined were

Anisakis Type I larvae. The larvae were white and cylindrical in shape. They measured

between 20 - 36 mm in length and 0.4 - 0.45 mm in width. SEM revealed that the

cuticles were irregularly striated transversely at 5.5 µm intervals. The larvae had

inconspicuous lips with six papillae, a prominent boring tooth and excretory pore,


161

which opened ventrally at the cephalic end (Fig. 6-4, panels A and E). The mouth

opening led to a cylindrical striated oesophagus (length 1.6 - 2.1 mm), which was

followed by a slightly wider ventriculus (length 0.98 - 1.13 mm). The junction between

oesophagus and ventriculus was transverse (Fig. 6-4 panel B). The ventriculus

connected obliquely with the intestine, without a ventricular appendage and intestinal

caecum (Fig. 6-4 panel C). The intestine filled the remaining part of the body. The

mucron was distinct and was located at the caudal end (length 17.5 - 18.0 µm) (Fig. 6-4

panels D, F and G).

Figure 6-4: Anisakis Type I larvae from Selar crumenophthalmus. These images are exemplary for all larvae found in the present study. Light microscopy images: A. Cephalic end of larva showing the boring tooth and the excretory pore; B. ventriculus - oesophagus junction; C. ventriculus - intestine junction; D. caudal end showing the mucron, anal opening and anal glands. Scanning electron microscopy images: E. cephalic end; F. rounded tail with a mucron; G. mucron. ag = anal glands, ao = anal opening, bt = boring tooth, e = oesophagus, ep = excretory pore, int = intestine, l = lips, mu = mucron, ve = ventriculus.

6.3.3 Phylogenetic analysis of the ITS region

Amplification of the ITS rDNA generated an approximately 900 bp product.

Based on comparison with reference ITS rDNA nucleotide sequences from GenBank


162

database, all 21 specimens of Anisakis type I larvae from the present study were

identified as Anisakis typica. The nucleotide sequences from the present study

exhibited 99.1 - 100 % similarities to the published sequence of Anisakis typica

(AB432909) found in Indian mackerel (Rastrelliger kanagurta) in Thailand and 96.1 -

97.6 % similarities to the published sequence of Anisakis typica (JQ798962) found in

cutlassfish (Trichiurus lepturus) from Brazil. The sequences exhibited 82.7 - 88.7 %

similarities with other Anisakis species (Table 6-3). Both NJ and ML analyses produced

trees with similar topology. Neighbour-joining analysis of the ITS nucleotide sequences

from the present study with previously reported sequences from GenBank clustered all

the Anisakis Type I larvae examined with Anisakis typica (Fig. 6-5).

Table 6-3: Percentage similarity of the Anisakis species analysed in the present study and their closest relatives. At the ITS locus, comparison with A. typica, accession numbers AB432909 and JQ798962 were presented. Anisakis sp.* is conspecific with A. nascettii (Mattiucci et al., 2009).

% similarity at:

Species compared ITS rRNA locus Cox2 locus

A. typica 99.1 - 100 92.4 - 99.3

A. ziphidarum 87.5 - 88.7 82.1 – 84.3

A. pegreffii 85.4 - 86.2 84.7 - 87.2

A. simplex s. s 85.6 - 86.3 84.7 - 86.7

A. simplex C 85.8 - 86.6 84.2-85.8

Anisakis sp.* 86.5 - 87.8 not analysed

A. nascettii not analysed 83.9 - 86.7

A. physeteris 82.7 – 83.9 82.8 - 84.5

A. brevispiculata 78.6 - 80.1 77.0 – 79.1

A. paggiae 83.8 - 84.7 79.3 – 82.2


163

Figure 6-5: Phylogenetic relationships between Anisakis species from the present study (*) and other Anisakis species as inferred by neighbour-joining analysis of ITS rDNA. The evolutionary distances were computed using the Kimura-2 parameter method and the rate variation among sites was modelled with a gamma distribution with Contracaecum osculatum as an outgroup. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test (1, 000 replicates) are shown at the internal nodes (> 50 % only). Specimen codes are given in Table 6-2.


164

Figure 6-6: Phylogenetic relationships between Anisakis species from the present study (*) and other Anisakis species inferred using the neighbour-joining analysis of cox2 genes. The evolutionary distances were computed using Tamura-Nei model and the rate variation among sites was modelled with a gamma distribution with Contracaecum osculatum as an outgroup. The percentage of trees in which the associated taxa clustered together in a bootstrap test (1, 000 replicates) are shown next to the branches (> 50 % only). Specimen codes are given in Table 6-2.

Amplification of the cox2 gene generated an approximately 629 bp product. As

with the ITS locus, NJ and ML analyses produced trees with similar topology.

Neighbour-joining analysis of cox2 nucleotide sequences showed that all isolates

clustered broadly with A. typica (DQ116427) but revealed more variation. Two broad


165

groups were produced with subgroup I consisting of 5 isolates and A. typica reference

sequence (DQ116427), and subgroup II containing 16 isolates (Fig. 6-6). Based on

genetic distance analysis, subgroup I had 98.9 - 99.3 % similarity to A. typica

(DQ116427) while subgroup II had 92.4 - 94.6 % similarity to A. typica (DQ116427). The

cox2 nucleotide sequences from the present study shared 77.0 - 87.2 % similarity with

other known Anisakis species (Table 6-3).

6.4 Discussion

Anisakid larvae were found in 7.6 % (21/276) of the 7 fish species examined.

The intensity of infection was low (n ranged from 1 to 6) in all fish hosts except for

Pinjalo pinjalo (n = 120) (Table 6-2). Previous studies have reported wide variation in

prevalence and intensity of infection of anisakids in other fish hosts (Costa et al., 2003;

Farjallah et al., 2008a; Farjallah et al., 2008b; Setyobudi et al., 2011). The relatively low

infection level found in the present study could be due to the fact that most of the fish

hosts sampled were relatively small in size (ranged 16 - 49 cm, fork length) compared

to previous studies. In general, prevalence and parasite burden tend to increase with

the size and the age of the fish host (Setyobudi et al., 2011).

All nematodes in the present study were identified morphologically as Anisakis

Type I larvae, based on an oblique connection between the ventriculus and the

intestine, lack of a ventricular appendage and intestinal caecum, and the presence of a

mucron (Berland, 1961; Cannon, 1977). Larvae of A. typica found in cutlassfish

(Trichiurus lepturus) from Brazil shared similar morphological characteristics with the

A. typica larvae from the present study (Borges et al., 2012).

Phylogenetic analysis of DNA sequences indicated that all examined samples

were Anisakis typica. At the ITS locus, all isolates examined formed a single clade with

A. typica. The comparison of the ITS nucleotide sequences from this study with

sequences previously deposited in GenBank resulted in 96.1 - 97.6 % similarities to

A. typica found in cutlassfish (accession no. JQ798962) from Brazil and 99.1 - 100 %

similarities to A. typica (accession no. AB432909) from Indian mackerel in Thailand.


166

At the cox2 locus, whilst the isolates clustered broadly with the reference

A. typica genotype, two distinct subgroups (I: 98.9 - 99.3 % similarity and II: 92.4 -

94.6 % similarity) were identified. Previously reported cox2 trees by Valentini et al.

(2006) also showed similar genetic divergence within the Anisakis typica clade.

Furthermore, the sequence difference of 5.4 - 7.6 % between the subgroup II clade and

the reference A. typica sequence is still within the range found between conspecifics in

other nematode taxa (Blouin et al., 1998).

According to Mattiucci and Nascetti (2006), Anisakis species form two sister

clades and A. typica is grouped within clade I, based on phylogenetic relationships

inferred from allozyme and mitochondrial gene markers. In the present study, A. typica

clustered within clade I at the cox2 locus, consistent with previously reported

phylogenetic trees (Valentini et al., 2006; Mattiucci et al., 2009; Cavallero et al., 2011;

Setyobudi et al., 2011). However, at the ITS locus, A. typica did not cluster within clade

1 and formed a separate group to the two clades. Other studies have shown similar

tree topology at the ITS locus (Kijewska et al., 2009b; Cavallero et al., 2011). Anisakis

typica could form a distinct lineage (resulting in three clades, rather than two, for the

genus Anisakis). It should be noted, however, that the position of A. typica in both the

ITS tree and cox2 tree was not well supported (< 50 % bootstrap support) in our study

and therefore more sampling of the species from a wider range of hosts and

geographical areas is needed to resolve this discrepancy.

The present study identified seven new fish species (Decapterus macarellus,

Gerres oblongus, Pinjalo lewisi, Pinjalo pinjalo, Selar crumenophthalmus,

Scomberomorus maculatus and Thunnus albacares) as hosts for A. typica. Previous

studies have identified A. typica in more than 15 different fish hosts, which have an

epipelagic distribution in the Atlantic Ocean close to the coastlines of Brazil, Mauritius,

Morocco, Portugal and Madeira (Mattiucci et al., 2002; Pontes et al., 2005; Marques et

al., 2006; Farjallah et al., 2008a; Iniguez et al., 2009; Kijewska et al., 2009b). Anisakis

typica has also been found in the Mediterranean Sea close to Tunisia, Libya, Cyprus

and Crete, and in the Indian Ocean off Somalia (Mattiucci et al., 2002; Farjallah et al.,

2008b) and Australia (Yann, 2006). Furthermore A. typica has been found in Japan,


167

Taiwan, China, Thailand and Indonesia (Chen et al., 2008; Palm et al., 2008; Umehara

et al., 2010). Although it has been hypothesized that A. typica has a global distribution

that extends from a 30 °S to a 35 °N latitude (Mattiucci and Nascetti, 2006), a previous

distribution model for anisakid species has not included PNG (Kuhn et al., 2011).

6.5 Conclusions

In conclusion, all anisakids identified from PNG in the present study were

A. typica, which has not previously been associated with human infections. Further

studies are needed to extend the knowledge of anisakid species distribution in larger

fish hosts and other seafood hosts in Papua New Guinean waters, but the present

results suggest that the danger from zoonotic anisakid species in PNG is very low.

169

Chapter 7

7. Prevalence of Chlamydia in sheep and goats

from PNG by quantitative PCR


This chapter describes the screening for Chlamydia abortus and C. pecorum

using a species-specific multiplex qPCR assay in sheep and goats from PNG.


The overall prevalence of C. abortus was 12.2 % (27/221) in sheep and was 8.6

% (11/128) in goats in all farm types.

The overall prevalence of C. pecorum was 7.7 % (17/221) in sheep and was 8.6

% (11/128) in goats in all farm types.

7.1 Introduction

Chlamydiae are obligate intracellular bacteria, which cause a variety of diseases

in humans and animals, worldwide. The taxonomy of Chlamydia and infection with

Chlamydia abortus and C. pecorum are described in Chapter 1, Section 1.7.

Little is known about Chlamydia in sheep and goats in PNG. Therefore, the aim

of the present study was to use a species-specific multiplex qPCR assay for C. abortus

and C. pecorum to investigate the prevalence and species of Chlamydia found in sheep

and goats over a wide geographical area, representative for the major sheep and goat

farming regions of PNG.

7.2 Methods


results described in this chapter. A detailed description of all methods is described in

Chapter 2 of this thesis.


Faecal samples from 221 sheep and 128 goats collected in PNG from February

to April 2011 were screened for Chlamydia. The details of sample collection are

described in Chapter 2, Sections 2.3 - 2.6.

7.2.2 DNA isolation and qPCR amplification

Total DNA was extracted from 250 mg of faeces using a PowerSoil® DNA

isolation kit (MO BIO laboratories, Carlsbad, California, USA) (see Chapter 2, Section

2.8.1). All samples were screened for the presence of C. abortus and C. pecorum using

a multiplex qPCR assay, which targets the amplification of the outer membrane protein


171

cell surface antigen gene (ompA) as previously described (Yang et al., 2014c). The

details of this assay are described in Chapter 2, Section 2.9.6.

7.2.3 Data analysis

Prevalences (samples which were positive for C. abortus or C. pecorum) were

expressed as a percentage of positive samples, with 95 % confidence intervals

calculated assuming a binomial distribution, using the software Quantitative

Parasitology 3.0 (Rozsa et al., 2000). Differences in prevalence among groups were

compared by Fisher’s exact test (FET). Where multiple pairwise comparisons were

made among groups, a Bonferroni correction was applied to maintain an experiment-

wide Type I error rate of 5 %.

7.3 Results

The overall prevalence of C. abortus was 12.2 % (27/221) in sheep and 8.6 %

(11/128) in goats. There was no significant difference in the prevalence of C. abortus

between sheep and goats (FET: p = 0.3733). In each farm type, the prevalence of

C. abortus ranged from 6.0 % (smallholder farms) to 34.8 % (Baisu) for sheep and 4.6 %

(Labu) to 33.3 % (Menifo) for goats (Table 7-1). There were no differences in the

prevalences of C. abortus between farm types for sheep with one exception, that is the

prevalence observed in the public institution (Baisu) was higher than in the smallholder

farms (FET: p < 0.005) (Table 7-2). There were no differences in the prevalences of

C. abortus between farm types for goats (FET: p values > 0.005) (Table 7-2).

The overall prevalence of C. pecorum was 7.7 % (17/221) in sheep and 8.6 %

(11/128) in goat. There was no difference in the prevalence of C. pecorum between

sheep and goats (FET: p = 0.8386). ). In each farm type, the prevalence of C. pecorum

ranged from 6.5 % (Tambul) to 13 % (Baisu) for sheep and 1.9 % (smallholder) to 18.2

% (Labu) for goats (Table 7-1). There were no differences in the prevalences of

C. pecorum between farm types for both sheep and goats (FET: p values > 0.0083)

(Table 7-2).


Table 7-1: Prevalence of Chlamydia in sheep and goats in the present study. N = the total number of faecal samples for sheep and goats. P = the number of animals, which were positive for Chlamydia abortus or C. pecorum. Given in parentheses are percent prevalence and 95 % confidence interval (CI). RI = Research institute.

N P (% , 95 % CI) P (%, 95 % CI)

Type of farm Sheep C. abortus C. pecorum

Lowland RI (Labu) 35 4 (11.43, 3.7 - 27.7) 3 (8.6, 2.2 - 24.2)

Highland RI (Tambul) 93 10 (10.8, 5.6 – 19.3) 6 (6.5, 2.7 – 14.1)

Public Institute (Baisu) 23 8 (34.8, 17.2 – 57.2) 3 (13, 3.4 - 34.7)

Government 3 1 (33.3, 1.8 - 87.5) _

Smallholder 67 4 (6, 1.9 - 15.4) 5 (7.5, 2.8 – 17.3)

Total 221 27 (12.2, 8.4 – 17.5) 17 (7.7, 4.7 - 12.2)

Goat

Lowland RI (Labu) 22 1 (4.6, 0.24 – 24.9) 4 (18.2, 6.0 – 41.0)

Highland RI (Tambul) 21 3 (14.3, 3.8 – 37.4) 1 (4.8, 0.3 – 25.9)

Public Institute (Baisu) 29 2 (6.9, 1.2 – 24.2) 5 (17.2, 6.5 – 36.5)

Government 3 1 (33.3, 1.8 – 87.5) _

Smallholder 53 4 (7.6, 2.5 – 19.1) 1 (1.9, 0.1 – 11.4)

Total 128 11 (8.6, 4.6 – 15.2) 11 (8.6, 4.6 – 15.2)

Table 7-2: Comparisons of prevalences for Chlamydia in sheep and goats between farm types. All pairs of farms were compared by FET. A Bonferroni correction was used to determine significance at Bonferroni corrected significance levels of < 0.005 for C. abortus and < 0.008333 for C. pecorum. * = values are significantly different between farms types. RI = Research Institute.

p values p values

Data sets Sheep Goats

C. abortus


Lowland RI (Labu) vs Public Institute (Baisu) 0.0473 1.0000

Lowland RI (Labu) vs Menifo 0.3532 0.2300


Highland RI (Tambul) vs Public Institute (Baisu) 0.0087 0.6378

Highland RI (Tambul) vs Menifo 0.3087 0.4368


Public Institute (Baisu) vs Menifo 1.0000 0.2633

Public Institute (Baisu) vs Smallholder 0.0015* 1.0000

Menifo vs Smallholder 0.2020 0.2487

C. pecorum


Lowland RI (Labu) vs Public Institute (Baisu) 0.6727 1.0000


Highland RI (Tambul) vs Public Institute (Baisu) 0.3784 0.3803


Public Institute (Baisu) vs Smallholder 0.4162 0.0193


7.4 Discussion

This is the first study to detect C. abortus and C. pecorum in sheep and goats

(clinically healthy adult animals at the time of sampling) in PNG. The prevalence

observed for C. abortus was 12.2 % (27/221) in sheep in the present study. This rate is

within the range of reported prevalences of C. abortus in clinically healthy adult sheep

(free from diarrhoea, history of abortion or respiratory diseases), for example, 6.7 % in

Egypt (Osman et al., 2011) and 50 % in Germany (Lenzko et al., 2011). The prevalence

of C. abortus is usually higher in diseased sheep (presence of diarrhoea, history of

abortion or respiratory diseases). For example, in Egypt, the prevalence of C. abortus

was 25.7 % in diseased sheep (Osman et al., 2011).

In this study, the prevalence of C. abortus was low (8.6 %, 11/128) in clinically

healthy goats. A previous study in Egypt reported a higher prevalence of C. abortus in

in clinically healthy (free from diarrhoea, history of abortion or respiratory diseases)

(50 %) and diseased (presence of diarrhoea, history of abortion or respiratory diseases)

(16.2 %) goats (Osman et al., 2011). The higher prevalences in the previous study

compared to the present study could be due to the techniques used for screening, as

well as, the total number of animals sampled. In Egypt, molecular identification was

not performed directly on faecal samples collected from sheep and goats, but from

embryonated chicken eggs inoculated with cell cultures of faecal samples from sheep

and goats (Osman et al., 2011). Furthermore, fewer sheep and goats were screened

(sheep: asymptomatic n = 10 and diseased n = 59; goats: asymptomatic n = 12 and

diseased n = 24) (Osman et al., 2011), thereby, giving a higher prevalence than the

present study.

An obvious limitation of the present study is that vaginal swabs were not

screened and therefore the true prevalence of C. abortus in sheep and goats in PNG

may be higher. However, C. abortus is commonly found in faeces as well as the genital

tract (Herrmann et al., 2000; Tsakos et al., 2001; Longbottom et al., 2002; Longbottom

and Coulter, 2003; Jee et al., 2004; Lenzko et al., 2011; Talafha et al., 2012) and

previous studies have shown that C. abortus is frequently detected in faecal samples

by qPCR (Jee et al., 2004; Lenzko et al., 2011).


174

The prevalence of C. abortus in sheep was higher in public institutional farms

(Baisu) than in smallholder farms. The lower prevalence observed in smallholder farms

could be due to the fact that the stocking rates were much lower (each smallholder

farms owned 3 – 20 animals), thus resulting in little contamination and spread of

C. abortus.

The prevalence of C. pecorum was 7.7 % (17/221) in sheep and 8.6 % (11/128)

in goats in the present study. In contrast, other studies have detected a high

prevalence of C. pecorum in clinically healthy adult sheep in Germany (47 %) (Lenzko

et al., 2011) and Australia (30. 1 %, 1027/3412) (Yang et al., 2014c). The observed

differences in the prevalence could be due to stocking rates and faecal contamination

of pastures and resting places. The flock sizes ranged from 6 – 115 in the present

study, 250 – 1, 800 in Germany (Lenzko et al., 2011) and 300 – 5, 500 in Australia (Yang

et al., 2014c). Faecal shedding is an important mode of transmission for Chlamydia

spp. (Shewen, 1980; Brenner J., 2001). The high prevalences observed in Germany and

Australia may be due to high contamination of pasture or resting places, where animal

numbers are large.

There are very few studies which have screened goats’ faecal samples for

C. pecorum. For example, in Egypt, Osman et al. (2011) did not identify C. pecorum in

goats, although it was present in sheep (at low prevalence). Chlamydia pecorum is

commonly isolated from the digestive tract of ruminants, in which the infections are

clinically inconspicuous, but under circumstances of stress, host animals may shed the

organism in large numbers and may suffer from clinical disease (Shewen, 1980; Osman

et al., 2011).

In summary, low prevalences of C. abortus and C. pecorum in sheep and goats

in the present study could be due to low distribution of the bacteria in the biological

material. Also, the observed lower prevalence could be related to low contamination

of environment with these bacteria; however further epidemiological studies are

needed. The analytical sensitivity may be a contributing factor for the observed lower

prevalence. The multiplex qPCR assay used for screening the samples in the present

was previously validated by Yang et al. (2004c). The detection limit for C. abortus and


175

C. pecorum was 5 and 5 organisms respectively per 1 µL of faecal DNA extract (Yang et

al., 2004c). Therefore, the detection technique is unlikely be a contributing factor to

the observed low prevalences.

7.5 Conclusions

In conclusion, prevalences of C. abortus and C. pecorum in sheep and goats in

PNG were low in comparison to previous studies, which also used molecular methods

for detection. However, the results of the present study indicate that C. abortus occurs

in sheep and goats in PNG and could pose a risk of transmission to humans, especially

in villages in PNG, where the small ruminants are cared for by women on a daily basis.

Little is known about chlamydial abortions in women in PNG. Previous studies in PNG

have focused on C. trachomatis infections, for which the reported prevalences were

from 14 – 26.1 % in females (Theunissen et al., 1995; Vallely et al. 2010).

Future studies should include surveys on the history of abortion in sheep and

goats, and compare clinically healthy Chlamydia-positive flocks with diseased flocks

(those with clinical chlamydial infection) and flocks with reproductive disorders

without chlamydial infections to determine the clinical impact of Chlamydia in PNG.

Also, further isolation and characterisation of Chlamydia spp. are required to assess

their possible zoonotic potential.

Chapter 8

8. General discussion and concluding remarks


8.1 General discussion

The focus of the work conducted in this thesis was to investigate the

epidemiology of gastrointestinal pathogens in sheep and goats in PNG and to detect

potential zoonotic pathogens present in these animals in smallholder and institutional

flocks, as well as, government breeding sites. Also, fish were sampled in aquaculture

farms, rivers and marine systems to specifically identify potential zoonotic

gastrointestinal parasites (Cryptosporidium, Giardia and anisakids), which may

represent a source of illness for local populations. It should be noted that sample

collection in rural areas in PNG is logistically difficult, especially in the remote areas

where most of the sampling was done. The present study represents the most detailed

investigation of gastrointestinal parasites in sheep, goats and fish in PNG to date, using

molecular tools, and a variety of gastrointestinal pathogens were identified. This

provides an important update on internal pathogens of sheep and goats from previous

studies (Quartermain, 2004b).

A high prevalence of gastrointestinal nematodes, especially Haemonchus

contortus, and protozoa, particularly Eimeria spp., were detected in both sheep and

goats (Chapter 3). According to the survey questionnaire, most smallholder farmers did

not know about parasites and the diseases they can cause in their flocks, which may be

one reason for the high prevalence observed in the smallholder settings. In the

research institute farms, although anthelmintics were given to the flocks to control the

burden of gastrointestinal nematodes, the animals were kept at higher stocking rates

compared to smallholder farms, lambing pens were dirty and floors of the resting

houses were not swept. These factors may contribute to the spread of gastrointestinal

parasites (Van Metre, 2013).

The main goal of employing practises to control gastrointestinal parasites in

farm management is to break their life cycle, which can be done in a variety of ways

including the use of anthelmintics, pasture management and animal management.

Good pasture management as well as the use of anthelmintics, depends on the level of

anthelmintic resistance in a particular flock (Sani et al., 2004). Parasite control can be

exercised even without the use of anthelmintics through practises such as rotational


179

grazing and applying basic hygienic measures, but requires considerable efforts in

management and planning and the farmers continued commitment to these activities

(Sani et al., 2004). Committed farmers in turn need support and clear advice from

informed veterinary practitioners, animal scientists, and extension workers on

relevant, scientifically sound strategies for parasite control. In low-income countries

like PNG, this infrastructure is often not established.

PNG has a climate ideal for development of H. contortus, Teladorsagia

(Ostertagia), and Trichostrongylus spp., where the latter two genera occur especially in

the cool highlands areas. Rational grazing, where sheep and goats are allowed to graze

in a paddock for 3 - 4 days, after which they are moved to another paddock (Sani et al.,

2004) may be an appropriate strategy to reduce parasite burden in sheep and goats in

PNG. The potential success of such methods is due to the relatively short larval survival

times on open pasture. Previous studies of trichostrongylid nematodes on open

pasture in humid tropical climates in Southeast Asia found that eggs developed to

infective larvae in a minimum time of 3 – 4 days after faecal deposition and most

larvae developed within seven days. Infective larvae on open pasture survived for 5 - 6

weeks, and on vegetation under tree crops survived for 5 - 8 weeks (Cheah and

Rajamanickam, 1997; Sam-Mohan, 1995; Sani, 1994). The relatively short larval

survival times observed allows for the integration of grazing management with worm

control. Small ruminants can safely graze for 3 - 4 days in an area which is ‘rested’ for 5

- 6 weeks (Sani et al., 2004).

In addition, low-cost and simple diagnostic tools, such FAMACHA (described in

Chapter 1, Section 1.2.4) (van Wyk et al, 2002), could be used by farmers in PNG for

diagnosis of anaemia, so that the affected sheep and goats can be selectively treated

with anthelmintic drugs.

The protozoan parasites, Cryptosporidium and Giardia were also found in

sheep, goats and fish (Chapters 4 and 5) in the present study, however the pathogenic

effects of these parasites in PNG need to be further investigated. Sheep and goat

producers should be informed of the clinical signs (diarrhoea) caused by these

protozoa and measures should be taken if disease signs are observed in young animals


180

to prevent the spread of these parasites to other animals, or to humans. Such

measures include but are not limited to an improvement of hygiene (clean pens,

washing of hands).

In terms of molecular characterisation, the present study did not characterise

assemblages of G. duodenalis and future studies using techniques such as PCR and

sequencing are needed to genotype G. duodenalis isolates to assemblage level to

better understand the zoonotic potential of this parasite in these hosts. The present

study used a qPCR assay to determine the presence or absence of G. duodenalis.

The work described in Chapter 6 was aimed at identifying zoonotic anisakid

nematodes in fish, as fish are a major source of food for people living in coastal villages

and towns in PNG. Papua New Guineans prepare their fish by smoking, steaming and

deep-frying. More recently, raw seafood dishes, especially, sushi and sashimi, are

becoming popular in hotels and restaurants in towns and cities due to an increasing

international community. In addition to the consumption of raw fish dishes, the

presence of live third stage larvae of anisakid nematodes, in smoked fish or deep fried

fish, could cause health implications (Bier, 1976; Hauck, 1977; Gardiner, 1990; Kim et

al., 2006). The present study did not find zoonotic anisakid species in a variety of fish

hosts in PNG; however, further studies are necessary to confirm the absence of

zoonotic anisakid in PNG waters.

In Chapter 7, a species-specific multiplex qPCR assay was used to screen for

C. abortus and C. pecorum in sheep and goats from PNG. Both pathogens were

prevalent in sheep and goats in all the farms types. The presence of Chlamydia in small

ruminants in PNG has not been investigated before. A possible explanation for this is

that livestock officers, veterinarians and human health professionals are not

necessarily aware of the widespread occurrence and zoonotic nature of Chlamydia. As

both species could cause abortion in sheep and goats, this study provides valuable

information for researchers and veterinarians who are working to improve production

of sheep and goats throughout the country. Everyone in contact with sheep and goats

should be informed about the clinical signs of Chlamydia. It is particularly important


181

that pregnant women in rural areas should be made aware of the risks of C. abortus

and how to avoid infection.

8.2 Future directions

There are many open questions remaining, which require scientific work

beyond the scope of this thesis and research opportunities which have arisen due to

the performed work. Some of the most important questions originating from this

research are raised in the next few paragraphs.

(1) What diseases are prevalent in sheep and goats in PNG?

There is little current research documenting the consequences of internal

pathogens on sheep and goats in PNG. Documentation is limited because, in the past,

small ruminants in PNG have been perceived to be less important than pigs, poultry

and cattle (Quartermain, 2004b). Therefore, human and financial resources available

for research, directed at sheep and goats, have been limited. The farmers in the

present study said they have noticed foot-rot disease, diarrhoea and coughing in their

sheep and goats, yet, most were unaware of other diseases and the underlying

pathogens causing the diseases in their flocks.

Further studies into internal pathogen species/genotype epidemiology,

especially in the lowland smallholder farms in areas with different levels of rainfall, are

required. The present study provided insights into gastrointestinal nematodes

(including trichostrongylids, Strongyloides and Trichuris), liver fluke (Fasciola), cestode

(Moniezia), protozoa (Eimeria, Cryptosporidium and Giardia) and bacteria (C. abortus

and C. pecorum), in a warm lowland site (Labu) and the highland sites (smallholder

farms, Menifo, Baisu and Tambul). However, more information about other important

infectious agents of small ruminants is needed. Specifically, other important pathogens

known to cause diarrhoea (Escherichia coli, Salmonella sp., Clostridium perfringins, and

rotavirus) and abortion (Campylobacter fetus, Toxoplasma gondii, Brucella ovis) in

sheep and goats should be investigated.

Due to the scarcity of veterinary research in PNG and the associated severe

knowledge gaps, a large scale longitudinal research study is needed to:


182

(i) collect data on the epidemiology of a wide range of pathogens in different

geographical areas and farm types at different time points, in both warm and

cool agro-ecological zones, to determine the distribution of different

species/genotypes of internal pathogens (parasites, bacteria and viruses) across

different geographical areas, and;

(ii) to determine in detail, the impact on human and animal health as well as the

economic impact, caused by these pathogens in PNG.

However, it should be noted that such studies are logistically difficult and costly

to conduct in PNG for several reasons. The smallholder farms are remote and to

ensure the samples are kept viable, the sampling team has to stay in a nearby town or

village, where there is power for refrigeration. Roads are usually in very poor condition

and only 4WD vehicles may be used. Furthermore, farmers have to be notified a day in

advance, before sampling so that animals are kept in the night house on the day the

field team arrives. This is often very difficult due to the lack of telecommunication.

(2) What are the longitudinal prevalence rates of pathogens and transmission

dynamics of zoonotic pathogens?

This study was a cross-sectional study (faecal samples collected at one time

point) and the true prevalence, especially of Cryptosporidium spp., Giardia spp.,

Chlamydia abortus and Chlamydia pecorum may be underestimated due to factors

such as intermittent shedding, seasonal variation and imperfect detection. Therefore,

their true prevalence may be considerably higher in PNG and future longitudinal

studies, as described above, could give more accurate estimates. Also, as these

pathogens have zoonotic potential, further studies should include a wide range of

hosts such as humans, companion animals and cattle, to more fully understand their

transmission dynamics in PNG.

(3) Which fish species serve as hosts for Cryptosporidium and Giardia?

Further morphological and histological analyses of Cryptosporidium and Giardia

in fish hosts are required (in addition to genetic studies) to identify sites of infection


183

and confirm that fish hosts are actually infected and not just serving as mechanical

transmitters of Cryptosporidium and Giardia oo/cysts, as this information is currently

lacking. This is particularly important for zoonotic species of Cryptosporidium and

Giardia. Infection studies that inoculate fish with zoonotic species of Cryptosporidium

and Giardia and subsequent morphological/histological and genetic studies should be

conducted to better understand the transmission dynamics of zoonotic

Cryptosporidium and Giardia in fish hosts.

(4) What is the true burden of gastrointestinal nematodes in livestock?

A wider analysis of total worm counts and histopathological analysis of tissue

sections of sheep and goats in a flock are critical to determine the burden of nematode

infections in the gut to allow decisions about treatment of flocks with anthelmintics. In

addition, although this study used molecular tools to identify species of strongylid

nematodes, future studies should include larval culture (on individual faecal samples),

in addition to worm egg counts for species identification of internal helminths. In PNG,

where molecular tools are rare in veterinary (research) laboratories, larval cultures are

critical. However, for such studies to take place, a better veterinary science

infrastructure needs to be established in PNG. But the funds available to build state-of-

the-art facilities for molecular research in veterinary research are scarce. To date,

there are several PCR machines in all of PNG and these are located in PNG Institute of

Medical Research and the Port General Hospital for use with samples from humans.

8.3 Concluding remarks

The results generated in this study have been given to the livestock research

team at NARI in Labu, who can disseminate information to breeders and farmers in the

country. To reduce the burden caused by gastrointestinal parasites and improve

productivity of sheep and goats, veterinary scientists at NARI could assist farmers in

understanding the diseases and control measures that could be applied to prevent

contamination and illness in their animals.

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Appendices Gastrointestinal pathogens in sheep, goats and fish in PNG

Appendices

The following appendices include journal articles published by the candidate

over the course of the candidature. They are submitted as additional evidence for

candidature for the degree of Doctor of Philosophy.

Appendix A: The survey questionnaire described in Chapter 2.

Appendix B: Koinari, M., Karl, S., Ryan, U., Lymbery, A.J., 2013. Infection levels of

gastrointestinal parasites in sheep and goats in Papua New Guinea. Journal of

Helminthology. 87, 409-415.

Appendix C: Koinari, M., J., Lymbery, A.J., Ryan, U.M., 2014. Cryptosporidium species in

sheep and goats from Papua New Guinea. Experimental Parasitology. 141, 134-137.

Appendix D: Koinari, M., Karl, S., Ng-Hublin, J., Lymbery, A.J., Ryan, U.M., 2013.

Identification of novel and zoonotic Cryptosporidium species in fish from Papua New

Guinea. Veterinary Parasitology. 198, 1-9.

Appendix E: Koinari, M., Karl, S., Elliot, A., Ryan, U., Lymbery, A.J., 2013. Identification

of Anisakis species (Nematoda: Anisakidae) in marine fish hosts from Papua New

Guinea. Veterinary Parasitology. 193, 126-133.

Appendix A Gastrointestinal pathogens in sheep, goats and fish in PNG

A-1

Appendix A

Survey Questionnaire


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Prevalence and management factors related to the prevalence of gastrointestinal parasites in sheep and goat in wet mainland of Papua New Guinea.

Conducted by: Melanie Koinari, Murdoch University, in collaboration with National Agricultural Research Institute of Papua New Guinea, Bubia, Morobe Province.

Section 1: GENERAL MANAGEMENT 1. How many animals are there in your farm/herd? Sheep:____________________ Goats:____________________ 2 a) How many animals by age group? Sheep Number of animals

Male Adults

Female Breeder

Pre-weaned (0-2 months old lamb)

Post-weaned (2-6 months old lambs)

Goats Number of animals

Male Adults

Female Breeder

Pre-weaned (0-2 months old lamb)

Post-weaned (2-6 months old lambs)

2 b) Number of lambs in your herd/farm: __________________________ Number of kids in your herd/farm: __________________________ 3. How large is your farm? __________________________ 4. How are the animals fed? Feed Yes/No

Grazing: Cut and Carry: Feed: Mixed feeding (eg: grazing and cut and carry):

5. If the animals are let free to graze, what type of grazing system is adopted for the herd?

No restriction (free area) The animals are allowed to graze at particular areas restricted by non-electric fencing.

6. Are the animals separated according to gender? Yes/No __________ 7. Do the animals get any feed supplements? Yes/No __________ If no, go to Question number 10. If yes, what type of feed supplement is used? (Please specify)

8. If feed supplement is used, is it specially made or purchased?

Made Purchased Both


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9. If purchased, where do you buy the feed supplement from? Feed distributor

Others (Please specify): _____________________

10. What is the source of water for the herd?

Tap water River Groundwater Others (Please specify): ______________________

11. a) Approximately how far is your sheep herd from the nearest sheep herd? ___________________________ b) Approximately how far is your goat herd from the nearest goat herd? ___________________________ 12. a) Approximately how far is your sheep herd from other livestock such as goat, buffalo, cattle, and pigs? ___________________________ b) Approximately how far is your goat herd from other livestock such as sheep, buffalo, cattle, and pigs? ___________________________ 13. When was the last time you introduced new sheep/goat to your farm? Sheep: ___________________________ Goat: ___________________________ 14. How often do you introduce new animals to your farm? ___________________________ 15. Are there are any other animals on this farm? Yes/No __________ If yes, please specify: ____________________________________________________________________ 16. Do you have any specific management practices for handling animal waste? Yes/No __________ 17. If no, where do the faeces or effluent go? _____________________________________________________________________________ 20. If yes, how do you manage the animal waste? _____________________________________________________________________________ 22. If treated, what type of waste treatment system do you use? _____________________________________________________________________________


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Section 2: EWES - LAMB MANAGEMENT

Perinatal management

1a) Where are lambs born?

multi-ewes lambing area single-ewes lambing area born in the field

1b) Where are kids born? multi-does doeling area single -does doeling area born in the field

If the lambs/kids are born in pens, please answer Questions 2 to 4. If not proceed to Question 5. 2. Do you clean the lambing pens before young are born? Lamb Goat kid Yes Yes No No 3. What is the floor of the lambing pen made of?

Lamb (Yes/No) Kid (Yes/No)

Concrete __________ __________

Earth __________ __________

Gravel __________ __________

Others (Please specify) __________ __________

4. If earth flooring, do you sweep the floor? Yes/No __________ 5. Do you separate young animal from their mothers within 12 hours after birth? Lamb Kids Yes Yes No No

Section 3: HERD HEALTH PROGRAM

1. Is medication given to your herd? Yes/No __________If no, proceed to Section 4.

2. Is medication given to newborn animals?

Lamb Kids Yes Yes No No

3. If yes, what type of medication is given to the young animals?

Lamb: __________________________________

Kid: __________________________________

4. When was the most recent medication given?

Date: _____________ (dd/mm/yyyy)


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5. What type of medication is routinely used for the herd?

The brand name: __________________________________

6. Approximately how many times do you give treatments each year? _________

Section 4: HEALTH

1. Do you know any disease in your herd/flock? Yes/No _________________

If yes, please specify:_____________________________________________

If your heard has diarrhoea, please answer questions 2 to 4.

2. Do you know what caused this diarrhoea? Yes/No _________________

If yes, please outline: _____________________________________________

3. Do you know the clinical signs of diarrhoea? Yes/No _________________

If yes, please describe: _____________________________________________

4. Do you know how to control diarrhoea? Yes/No _________________

If yes, please describe: ____________________________________________

General comments:

Thank you for taking the time to complete this questionnaire. Melanie Koinari PhD student, Faculty of Veterinary Medicine and Biomedical Sciences, Murdoch University, Perth, Australia

Appendix B Gastrointestinal pathogens in sheep, goats and fish in PNG

B-1

Appendix B

Infection levels of gastrointestinal parasites in sheep and goats in

Papua New Guinea.

Infection levels of gastrointestinal parasitesin sheep and goats in Papua New Guinea

M. Koinari1*, S. Karl2, U. Ryan1 and A.J. Lymbery1

1School of Veterinary and Biomedical Sciences, Murdoch University,Murdoch, Western Australia 6150, Australia: 2School of Physics,The University of Western Australia, Crawley, Western Australia,

Australia

(Received 28 February 2012; Accepted 25 July 2012; First Published Online 11 October 2012)

Abstract

Gastrointestinal parasites of livestock cause diseases of important socio-economic concern worldwide. The present study investigated the prevalence ofgastrointestinal parasites in sheep and goats in lowland and highland regionsof Papua New Guinea (PNG). Faecal samples were collected from a total of165 small ruminants (110 sheep and 55 goats) from February to April 2011.Analysis by a modified McMaster technique revealed that 128 animals (72%of sheep and 89% of goats) were infected with one or more species ofgastrointestinal parasites. The gastrointestinal parasites found and theirprevalences in sheep (S) and in goats (G) were as follows: strongyle 67.3% (S),85.5% (G); Eimeria 17.3% (S), 16.4% (G); Strongyloides, 8.2% (S), 23.6% (G); Fasciola,5.5% (S), 18.2% (G); Trichuris, 1.8% (S), 3.6% (G); and Nematodirus, 1.8% (S), 3.6%(G). Two additional genera were found in goats: Moniezia (9.1%) and Dictocaulus(3.6%). This is the first study to quantitatively examine the prevalence ofgastrointestinal parasites in goats in PNG. The high rates of parasitism observedin the present study are likely to be associated with poor farming managementpractices, including lack of pasture recovery time, lack of parasite controlmeasures and poor-quality feed.

Introduction

Parasitism is recognized as a major threat to theproduction of small ruminants in both small-scale andlarge-scale farms. Gastrointestinal (GI) parasites causehigh mortality, reduce production and lead to asignificant overall economic loss (Al-Quaisy et al., 1987;McLeod, 1995; Simpson, 2000). GI parasites are highlyprevalent in sheep and goats in humid subtropical andtropical areas of the world (Yadav & Tandon, 1989; Bankset al., 1990; Barger et al., 1994; Dorny et al., 1995; Cheah &Rajamanickam, 1997; Regassa et al., 2006; Nwosu et al.,2007; Gadahi et al., 2009; Abebe et al., 2011; Dagnachewet al., 2011).

There are approximately 15,000 sheep and 20,000 goatsin Papua New Guinea (PNG) (Quartermain, 2002).Animals are raised by institutions for breeding or fornutritional research purposes and by smallholder farmersfor subsistence meat production. There are no sheep andgoats native to PNG. Tropical sheep from South-EastAsia were introduced by colonial administrators andmissionaries in the late 19th century and this sheeppopulation is known as PNG Priangan. In the 1980s,temperate Corriedale and Perendale sheep from NewZealand were brought to the cooler highlands of PNG.These temperate sheep breeds were crossed with thePNG Priangan sheep to produce crossbreds known asHighlands Halfbred (Quartermain, 2002). PNG Priangansheep are mainly raised in areas of lower altitude,whereas Highlands Halfbred sheep are raised at higheraltitudes. A variety of dairy goats, which are now referredto as PNG genotype, were introduced during the earlycolonial period (Quartermain, 2002).

*Fax: 61 89310 414E-mail: [email protected]

Journal of Helminthology (2013) 87, 409–415 doi:10.1017/S0022149X12000594q Cambridge University Press 2012


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Distribution and productivity of small ruminants inPNG are hindered mainly by poor health, nutritionand management (Quartermain, 2004). GI parasites areexpected to be widespread in PNG due to its humidtropical climate. In some parts of PNG, previoussurveys, which were conducted mostly in governmentstations, identified a diversity of internal parasitespecies in small ruminants (Varghese & Yayabu, 1985;Owen, 1988, 1989, 1998; also reviewed by Quartermain,2004). However, there is insufficient information onthe epidemiology of the GI parasites infecting sheepand goats in PNG. Such information is essential forunderstanding the economic impact these parasites canhave on farmers and to support decision-makingregarding the treatment and prevention of parasiticdiseases in these animals. The present study, therefore,was conducted to obtain data on the prevalence andinfection levels of gastrointestinal parasites in sheep andgoats on several farms in PNG.

Materials and methods

Study sites

The study was conducted from February to April 2011in two broad agro-climatic zones, the highlands (specificstudy sites: Tambul, Baisu, Menifo and Ungai-Bena) andlowlands (specific study site: Labu) in the central regionof mainland PNG (fig. 1).

The altitudes of the study sites are 0 m for Labu,1600–1608 m for Menifo and Ungai-Bena, 1730 m forBaisu and 2320 m for Tambul, with mean annualtemperatures of 268C, 20.18C, 20.18C, 18.38C and 14.78C,respectively (Bourke, 2010). The mean annual rainfall forLabu is above 4000 mm and between 2000 and 3500 mmfor Ungai-Bena, Baisu and Tambul (Quartermain, 2004).Menifo is drier than most of the PNG highlands andreceives a mean annual rainfall of 1000–1500 mm(Quartermain, 2004).

The study sites were further characterized by aquestionnaire survey, in which 20 farm managers andsmallholder farmers were interviewed. It consisted of

questions regarding general farm management practices,feeding systems and herd health programmes.

Farm managementThe flocks from the three institutional farms (Labu,

Baisu and Tambul) were kept together in fenced areas(approximately 20–60 ha), grazed pasture at a highstocking rate at daytime and were kept in houses withwooden, slatted floors at night. At the time of samplecollection, the total numbers of sheep and goats in Labu,Baisu and Tambul were 125, 70 and 143, respectively.The subsistence farmers kept few animals (usually fewerthan 15) which grazed free range or were tethered andhoused at night on slatted floors or on the groundunderneath the farmer’s house.

Feeding systemMost animals grazed on native grasses and shrubs.

Smallholder farmers also fed their animals with starchyvegetables (mostly sweet potatoes). The interviewedfarmers also indicated that there were shortages offeed. The animals drank from troughs (sourced fromwater supply or rainwater tanks), rainwater run-off wateror ponds.

Herd health programThe floors of the resting houses were not swept. The

animals were penned on dirty floor, ground or on bareconcrete floors. The smallholder farmers did not sheartheir sheep and explained that they did not have theresources for it. Most farm managers reported that themost common signs of illness in their animals werediarrhoea and coughing, followed by itching and hairloss. Most smallholder farmers did not know aboutcauses of diseases in their sheep and goats or the use ofanthelmintic drugs for treatment of nematode infec-tions. For instance, a man in Ungai-Bena reported thedeath of his entire flock (n ¼ 25) and noticed nematodeworms in the gut of a dead sheep. The three largeinstitutional flocks were drenched with benzimidazole(Panacur) nominally at bimonthly intervals. At the timeof sampling animals had been drenched 2 monthspreviously in Labu and 4 months previously in Baisuand Tambul.

Collection and examination of faecal samples

A total of 110 faecal samples from sheep and 55 faecalsamples from goats were obtained from the rectum ofrandomly selected animals between 07.30 and 09.00 h andkept at 48C until taken to the laboratory for analysis. Eachsample was examined visually for consistency, mucusand macroscopic parasites. Two grams of each faecalsample were examined using a modified McMastertechnique (Whitlock, 1948). Parasites were identifiedmorphologically to genus, or in the case of strongyles, togroup level (Soulsby, 1965). Parasite egg load wasexpressed as eggs per gram faeces (EPG). The volume ofthe flotation fluid used in the examinations was 50 ml andthe fluid volume examined in the counting chamber was0.3 ml. Since EPG is calculated using equation 1, the

Fig. 1. Topographical map of Papua New Guinea (PNG) showingthe study sites.

410 M. Koinari et al.


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minimum EPG count in our analyses was 83 eggs/gand occurred when only one egg was observed in thecounting chamber.

EPG ¼ eggscounted£total volume ðmlÞ

½examined volume ðmlÞ£weight of faeces ðgÞ�ð1Þ

Data analysis

Prevalence was calculated as the percentage of positivesamples in the total number of samples examined. Apartfrom the overall prevalence (i.e. the infection with any GIparasite) in each flock, prevalence was also calculated foreach parasite type, stratified by animal species and breed,study site, agro-ecological zone and farm managementtype. Differences in prevalence among groups werecompared by Fisher’s exact test (FET) (for two groups) orchi-squared analysis (for more than two groups).

EPG counts were transformed to their decadiclogarithms to obtain a normal distribution of valuesprior to statistical testing for significant differencesbetween animal species and breeds, study sites, agro-ecological zones and farm management systems. Differ-ences between/among groups were compared by t-testsor one-way analysis of variance (ANOVA); followed by apost hoc Tukey’s HSD test. Statistical analyses wereperformed using GraphPad Prism version 4 (GraphPadInc., California, USA).

Results

From the total of 165 small ruminants examined, 128(78%) were found to be infected with one or more types ofGI parasites. A mixed infection with two or more types ofGI parasites was found in 39% (50/128) of the infectedanimals: 33% (26/79) of sheep and 49% (24/49) of goats(not significantly different by FET, P ¼ 0.09).

Table 1 shows prevalence and mean EPG counts overall sampling sites, stratified by the type of host animal(sheep or goat) and the type of parasite. The overallprevalence of GI parasite infection was significantly

higher (FET; P ¼ 0.017) in goats (89%, 49/55) than insheep (72%, 79/110). Specifically, prevalence of strongyle(FET; P ¼ 0.0002), Strongyloides (FET; P ¼ 0.013) andFasciola (FET; P ¼ 0.013) were significantly higher ingoats than in sheep. In addition, the mean EPG counts forstrongyle were significantly higher in goats than in sheep(t ¼ 2.48, P ¼ 0.014).

Table 2 summarizes prevalence and mean EPG datagrouped by study site. There were no statisticallysignificant differences in the prevalence but there wereseveral significant differences in the EPG counts fordifferent GI parasite types across the study sites.

Strongyle and Strongyloides parasites were foundin both sheep and goats in all study sites. The meanEPG counts for goats infected with Strongyloides in Tambulwere significantly higher than the ones in Labu (ANOVA:F ¼ 3.91, P ¼ 0.05, Tukey’s test: P , 0.05). Eimeria wasfound in sheep from four study sites (Labu, Ungai-Bena,Tambul and Menifo) and in goats from three sites (Labu,Ungai-Bena and Baisu). In sheep, the mean EPG count forEimeria in Labu was significantly lower than in Menifo(ANOVA: F ¼ 3.41, P ¼ 0.045; Tukey’s test: P , 0.05).

No significant differences were observed for theother genera of GI parasites. Fasciola was found in sheepfrom three study sites (Labu, Ungai-Bena and Tambul)and in goats from three study sites (Labu, Ungai-Benaand Baisu). Trichuris occurred in sheep from two studysites (Ungai-Bena and Menifo) and in goats only fromLabu. Nematodirus was found in sheep from two sites(Baisu and Tambul) and in goats only from Baisu.Moniezia was only found in goats from three study sites(Labu, Ungai-Bena and Baisu). Dictyocaulus was onlyfound in goats from Labu.

There was also a trend for goats to be more heavilyinfected than sheep in all areas. In Labu, mean EPG forstrongyle (t ¼ 2.47, P ¼ 0.021) and Eimeria (t ¼ 3.95,P ¼ 0.004) were higher in goats than in sheep. In Ungai-Bena, the prevalence for Strongyloides was higher in goatsthan in sheep (FET: P ¼ 0.037) and mean EPG forstrongyle in goats was higher than in sheep (t ¼ 3.03;P ¼ 0.006).

Table 1. GI parasite prevalence and eggs/g (EPG) counts stratified by GI parasite type for thetotal number of faecal samples collected in the present study. N is the total number of faecalsamples. The total prevalence refers to the fraction of animals infected with one or more GIparasite types. EPG counts are given as means ^ SD. Where no SD value is given on themean EPG count, there was only a single or few positive observations with the same values,so that SD could not be calculated. Values with the superscript (*) are significantly differentbetween sheep and goats by either Fisher’s exact test (FET) or t-test.

Goat (N ¼ 55) Sheep (N ¼ 110)

ParasitePrevalence

(%) EPGPrevalence

(%) EPG

Strongyle 85.5* 745 ^ 622* 67.3* 762 ^ 1264*Strongyloides 23.6* 277 ^ 437 8.2* 323 ^ 377Eimeria 16.4 203 ^ 103 17.3 633 ^ 1467Fasciola 18.2* 257 ^ 275 5.5* 125 ^ 46Trichuris 3.6 125 ^ 59 1.8 111 ^ 48Moniezia 9.1 116 ^ 46 0 0Dictyocaulus 3.6 83 0 0Nematodirus 3.6 249 ^ 117 1.8 111 ^ 48Total 89* 927 ^ 821 72* 909 ^ 1795

Gastrointestinal parasites in sheep and goats in Papua New Guinea 411


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Table 3 shows the prevalence and mean EPG counts forGI parasites with respect to sheep breed, agro-ecologyand farm management systems. For comparisons ofagro-ecology and farm management systems, the data

for sheep and goats were combined. No statisticallysignificant differences were found in either prevalence ormean EPG counts for each parasite type between the twoagro-ecological zones, with the exception for Eimeria and

Table 2. GI parasite prevalence and eggs/g (EPG) counts for GI parasite type and study site. NG and NS are the total numbers of faecalsamples collected at each study site for goats and sheep, respectively. P (%) is the prevalence in per cent. EPG counts are given as means^SD. Where no SD value is given on the mean EPG count, there was only a single or few positive observations with the same EPG values,so that SD could not be calculated.

Labu Ungai-Bena Baisu Tambul Menifo(NG ¼ 14,NS ¼ 27)

(NG ¼ 15,NS ¼ 16)

(NG ¼ 22,NS ¼ 19)

(NG ¼ 4,NS ¼ 29)

(NG ¼ 0,NS ¼ 19)

P (%) EPG P (%) EPG P (%) EPG P (%) EPG P (%) EPG

GoatStrongyle 71.4 813 ^ 603 93.3 810 ^ 582 90.9 706 ^ 713 75 478 ^ 212 No dataStrongyloides 21.4 831 40 210 ^ 170 9.1 83 50 960 ^ 9961

Eimeria 21.4 221 ^ 95 20 249 ^ 143 13.6 138 ^ 48 0 0Fasciola 35.7 199 ^ 216 20 470 ^ 374 9.1 83 0 0Trichuris 14.3 125 ^ 59 0 0 0 0 0 0Moniezia 14.3 83 6.7 166 9.1 125 ^ 59 0 0Dictyocaulus 14.3 83 0 0 0 0 0 0Nematodirus 0 0 0 0 9.1 249 ^ 117 0 0

SheepStrongyle 66.7 406 ^ 570 68.8 445 ^ 677 78.9 603 ^ 389 69.0 1216 ^ 1585 52.6 1087 ^ 2303Strongyloides 3.7 1246 6.3 83 5.3 83 17.2 266 ^ 180 5.3 166Eimeria 25.9 95 ^ 311 25 374 ^ 220 0 0 6.9 125 ^ 59 31.6 1605 ^ 24531

Fasciola 11.1 166 6.25 83 0 0 6.9 83 0 0Trichuris 0 0 12.5 83 0 0 0 0 5.3 166Moniezia 0 0 0 0 0 0 0 0 0 0Dictyocaulus 0 0 0 0 0 0 0 0 0 0Nematodirus 0 0 0 0 5.3 83 6.9 125 ^ 59 0 0

1 Values are significantly different by ANOVA/Tukey’s HSD testing.

Table 3. GI parasite prevalence and mean eggs/g (EPG) counts stratified for sheep breed, agro-ecology and farmmanagement. N is the number of animals examined and prevalence (%) is the observed percentage of animals infested withone or more GI parasite types. EPG counts are given as mean ^ SD. Where no SD value is given for the mean EPG count,there was only a single or few positive observations with the same EPG values, so that SD could not be calculated.

Agro-ecology Farm management Sheep breed

Highlands Lowlands NARI Smallholder Priangan H/HalfbredN ¼ 124 N ¼ 41 N ¼ 115 N ¼ 50 N ¼ 27 N ¼ 83

Prevalence (%)Strongyle 75 68.3 74.8 70 66.7 67.5Strongyloides 14.5 9.8 12.2 16 3.7 9.6Eimeria 14.5 24.4 13.1 26 25.9 14.5Fasciola 6.5* 19.5* 10.4 8 11.1 3.6Trichuris 2.4 4.9 1.7 6 0 3.6Moniezia 2.4 4.9 3.5 2 0 0Dictyocaulus 0 4.9 1.7 0 0 0Nematodirus 4 0 4.3 0 0 3.6

EPGStrongyle 818 ^ 1156 551 ^ 605 748 ^ 942 775 ^ 1316 405 ^ 570 889 ^ 1412Strongyloides 278 ^ 375 374 ^ 582 357 ^ 491 189 ^ 151 1246 208 ^ 160Eimeria 696 ^ 1492* 133 ^ 80* 133 ^ 69* 913 ^ 1723* 95 ^ 32* 948 ^ 1796*Fasciola 228 ^ 283 187 ^ 165 152 ^ 141 374 ^ 362 166 83Trichuris 111 ^ 48 126 ^ 59 125 ^ 59 111 ^ 48 0 111 ^ 48Moniezia 138 ^ 48 83 104 ^ 42 166 0 0Dictyocaulus 0 83 83 0 0 0Nematodirus 166 ^ 102 0 166 0 0 111 ^ 48

NARI, National Agricultural Research Institute.H/Halfbred, Highlands Halfbred sheep.* Values are significantly different by either FET or t-test.



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Fasciola. The mean EPG for Eimeria was higher in thehighlands than in the lowlands (t ¼ 2.1, P ¼ 0.045) andthe prevalence of Fasciola was higher in the lowlands thanhighlands (FET, P ¼ 0.028). There were no significantdifferences in prevalence or mean EPG between theinstitutional and smallholder farm management systemswith the exception for Eimeria. The mean EPG for Eimeriawas higher in the smallholder farms than NationalAgricultural Research Institute (NARI) farms (t ¼ 3.0,P ¼ 0.004). Similarly, no significant differences werefound in both parasite prevalence and mean EPGbetween sheep breeds, with the exception of Eimeriawhere the mean EPG in the Highlands Halfbred sheepwas higher than in Priangan sheep (t ¼ 2.1, P ¼ 0.045).

Discussion

The present study observed 78% of the examined farmanimals in PNG being infected with one or more types ofGI parasites. Similar infection rates for both sheep andgoats have been reported in other developing countries,such as Ethiopia and Kenya (Maichomo et al., 2004;Regassa et al., 2006). This high parasite prevalence may beattributed to poor farm management, e.g. little pasturerest time, poor nutrition and lack of anthelmintictreatment. At all study sites, mixed-species flocks grazedor browsed on natural forage on the same land for most ofthe time or were moved to other areas with only shortpasture rest times. Studies in Fiji, Tonga and Malaysiafound that nematodes have short survival times onpasture and suggested rotational grazing as an effectivemeasure for parasite control (Banks et al., 1990; Bargeret al., 1994; Cheah & Rajamanickam, 1997).

Natural pasture and shrubs in PNG are often not verynutritious and may contain anti-nutritive factors such astannin types, which restrict rather than enhance proteinavailability to the ruminant (Macfarlane, 2000). Signalgrass, for example, may cause hepatic dysfunction infarm animals (Macfarlane, 2000). The low-quality feedmay result in subsequent malnutrition which maynegatively affect the development of acquired immunityagainst GI parasites (Kyriazakis & Houdijk, 2006). We didnot observe significantly lower GI parasite prevalence atstudy sites with more frequent anthelminthic treatment.

Strongyles were the most abundant parasites detectedin this study. Strongyles, especially Haemonchus species,are highly fecund, laying up to 5000 eggs/day whereenvironmental factors are favourable (Gupta et al., 1987).The pre-parasitic stages of Haemonchus contortus developand survive better at mean monthly maximum tempera-tures $18.38C (Gupta et al., 1987). Our study sites havemean maximum annual temperatures ranging from 18.9to 31.18C with only little variation throughout the year,due to their proximity to the equator. Additionally, moststudy sites were very humid, which is likely to sustain thesurvival of the free-living stages of H. contortus, leading tohigh pasture contamination.

A previous study reported high prevalence (89%)of Eimeria in sheep from three locations in PNG (Varghese& Yayabu, 1985) whereas the present study found alower prevalence (21–36%) in similar areas. This may bedue to the different methodologies used for parasite

identification. In the present study a simple flotationprocedure was used, while in the previous study acentrifugation/flotation method was used which hasbeen reported to be more sensitive for detection of oocytesin faecal samples (Dryden et al., 2005). Notwithstanding,this is the first study to report Eimeria in goats in PNG. Wefound Eimeria in goats in all study sites except Tambul,where only four goats were screened, and Menifo, whereno goats were screened.

The trematode Fasciola was present in sheep and/orgoats from Labu, Ungai-Bena, Baisu and Tambul.A previous study in PNG found Fasciola in the areaof Aiyura and showed that the sheep there are exposed tocontinual (low-level) pasture contamination leadingto chronic fasciolosis at all times (Owen, 1989). In PNG,in all areas where the intermediate snail host, Lymnaeaspecies, exists, acute fasciolosis can occur in the wetseason, especially in areas where the land is not welldrained and the grazing pressure is high (Owen, 1989).

This is the first study reporting the prevalence ofDictyocaulus in sheep and goats in PNG. Some studieshave found that goats are more susceptible to Dictyocaulusthan sheep (Sharma, 1994; Berrag & Urquhart, 1996;Alemu et al., 2006). We found Dictyocaulus in 14% of goatsexamined in Labu (lowland). A similar prevalence hasbeen reported in Ethiopia in areas with an altitude,1500 m (Alemu et al., 2006).

We found higher overall infection levels in goatscompared to sheep. Goats were also infected with a widerspectrum of GI parasites. This contradicts some previousstudies that found a lower prevalence in goats (Kanyariet al., 2009; Khan et al., 2010; Abebe et al., 2011), butis in agreement with a number of other studies, whichalso reported higher parasite prevalence in goats (Regassaet al., 2006; Nwosu et al., 2007; Gadahi et al., 2009;Dagnachew et al., 2011). Hoste et al. (2008) suggested thatgoats do not develop resistance as efficiently as sheep andthis may be an explanation for our findings.

The EPG counts for Eimeria in PNG Priangan sheep(N ¼ 27) were significantly lower than those in theHighlands Halfbred sheep (N ¼ 83). It is difficult toascertain the mechanisms behind this difference,especially as, coincidentally, most PNG Priangan sheepsamples were collected in Labu, where anthelminthicdrug treatment was conducted more regularly. Never-theless, previous studies have shown that some indigen-ous sheep breeds exhibit higher levels of resistanceagainst GI parasites and this might partially explain thepresent findings (Baker & Gray, 2004). PNG Priangansheep are native to tropical climates, as they originatedfrom South-East Asia and have been exposed to GIparasites in PNG for over a century. In contrast,Highlands Halfbred sheep, which are crossbreeds of thePNG Priangan sheep and the temperate Corriedale andPerendale breeds, have only a fraction of this resistanceand will therefore be more susceptible to infection. Moredetailed studies on immunology and feeding behaviourof the different sheep breeds are required to elucidatethis problem further.

The information collected in this study is an importantupdate on GI parasite presence in sheep and goats inPNG. Future investigations should include longitudinalstudies and larger cohorts to further assess parasite



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epidemiology in the diverse agro-climatic zones in thecountry. Molecular methods should be used to identifythe different species of GI parasites infecting sheep andgoats in PNG, thus extending previous studies (Varghese& Yayabu, 1985; Owen, 1988, 1989, 1998).

Acknowledgements

The authors would like to sincerely thank the ownersof the herds and logistic support by the NationalAgricultural Research Institute, Department of Agricul-ture and Livestock in Eastern Highlands Province, andDivine Word University in Papua New Guinea. Thisresearch received no specific grant from any fundingagency, commercial or not-for-profit sectors. This studywas approved by the Murdoch University Animal EthicsCommittee (Permit R2368/10).

References

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Baker, R.L. & Gray, G.D. (2004) Appropriate breeds andbreeding schemes for sheep and goats in the tropics.pp. 63–75 in Sani, R.A., Gray, G.D. & Baker, R.L. (Eds)Worm control for small ruminants in tropical Asia. ACIARMonograph No. 113. Canberra, Australian Centre forInternational Agricultural Research.

Banks, D.J., Singh, R., Barger, I.A., Pratap, B. &Le Jambre, L.F. (1990) Development and survivalof infective larvae of Haemonchus contortus andTrichostrongylus colubriformis on pasture in a tropicalenvironment. International Journal for Parasitology 20,155–160.

Barger, I.A., Siale, K., Banks, D.J. & Le Jambre, L.F.(1994) Rotational grazing for control of gastrointestinalnematodes of goats in a wet tropical environment.Veterinary Parasitology 53, 109–116.

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Dorny, P., Symoens, C., Jalila, A., Vercruysse, J. &Sani, R. (1995) Strongyle infections in sheep and goatsunder the traditional husbandry system in peninsularMalaysia. Veterinary Parasitology 56, 121–136.

Dryden, M.W., Payne, P.A., Ridley, R. & Smith, V. (2005)Comparison of common fecal flotation techniques forthe recovery of parasite eggs and oocysts. VeterinaryTherapeutics 6, 15–28.

Gadahi, J.A., Arshed, M.J., Ali, Q., Javaid, S.B. & Shah,S.I. (2009) Prevalence of gastrointestinal parasites ofsheep and goat in and around Rawallpindi andIslamabad, Pakistan. Veterinary World 2, 21–53.

Gupta, R.P., Yadav, C.L. & Chaudhri, S.S. (1987)Epidemiology of gastrointestinal nematodes of sheepand goats in Haryana, India. Veterinary Parasitology 24,117–127.

Hoste, H., Torres-Acosta, J.F. & Aguilar-Caballero, A.J.(2008) Nutrition–parasite interactions in goats:is immunoregulation involved in the control ofgastrointestinal nematodes? Parasite Immunology 30,79–88.

Kanyari, P.W.N., Kagira, J.M. & Mhoma, R.J.(2009) Prevalence and intensity of endoparasites insmall ruminants kept by farmers in Kisumu Munici-pality, Kenya. Livestock Research for Rural Development21(11). Available at http://www.lrrd.org/lrrd21/11/kany21202.htm (accessed 15 January 2012).

Khan, M.N., Sajid, M.S., Khan, M.K., Iqbal, Z. &Hussain, A. (2010) Gastrointestinal helminthiasis:prevalence and associated determinants in domesticruminants of district Toba Tek Singh, Punjab, Pakistan.Parasitology Research 107, 787–794.

Kyriazakis, I. & Houdijk, J. (2006) Immunonutrition:nutritional control of parasites. Small RuminantResearch 62, 79–82.

Macfarlane, D. (2000) Country pasture/forage resourceprofiles Papua New Guinea FAO database. Available atwww.fao.org/ag/AGP/AGPC/doc/Counprof/southpacific/png.htm (accessed January 2012).

Maichomo, M.W., Kagira, J.M. & Walker, T. (2004) Thepoint prevalence of gastro-intestinal parasites incalves, sheep and goats in Magadi division, south-western Kenya. Onderstepoort Journal of VeterinaryResearch 71, 257–261.

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Nwosu, C.O., Madu, P.P. & Richards, W.S. (2007)Prevalence and seasonal changes in the population ofgastrointestinal nematodes of small ruminants in thesemi-arid zone of north-eastern Nigeria. VeterinaryParasitology 144, 118–124.

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Owen, I.L. (1998) A study of the contamination of sheeppasture with nematode larvae in the highlands ofPapua New Guinea. Science in New Guinea 24, 3–9.

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Quartermain, A.R. (2004) Internal parasites of smallruminants in Papua New Guinea. pp. 241–248 in Sani,R.A., Gray, G.D. & Baker, R.L. (Eds) Worm control forsmall ruminants in tropical Asia. ACIAR MonographNo. 113. Canberra, Australian Centre for InternationalAgricultural Research.

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Appendix C Gastrointestinal pathogens in sheep, goats and fish in PNG

C-1

Appendix C

Cryptosporidium species in sheep and goats in Papua New Guinea.

Research Brief

Cryptosporidium species in sheep and goats from Papua New Guinea

M. Koinari a,⇑, A.J. Lymbery b, U.M. Ryan a

a School of Veterinary and Life Sciences, Murdoch University, Murdoch, Western Australia 6150, Australiab Fish Health Unit, School of Veterinary and Life Sciences, Murdoch University, Murdoch, Western Australia 6150, Australia

h i g h l i g h t s

� Detection of Cryptosporidium spp. inadult sheep and goats from PapuaNew Guinea using molecular tools.� In sheep, C. parvum, C. andersoni and

C. scrofarum were identified.� In goats, C. hominis, C. parvum, C. xiaoi

and rat genotype II were identified.� Subtypes detected were C. hominis

IdA15G1 and C. parvum IIaA15G2R1and IIaA19G4R1.

g r a p h i c a l a b s t r a c t

a r t i c l e i n f o

Article history:Received 9 December 2013Received in revised form 20 March 2014Accepted 24 March 2014Available online 3 April 2014

Keywords:CryptosporidiumSheepGoat18S rRNA60 kDa glycoproteinZoonoticPapua New Guinea

a b s t r a c t

Species of Cryptosporidium are extensively recognised as pathogens of domesticated livestock and poul-try, companion animals, wildlife, and are a threat to public health. Little is known of the prevalence ofCryptosporidium spp. in humans, domesticated animals or wildlife in Papua New Guinea (PNG). Theaim of the present study was to screen sheep and goats for Cryptosporidium using molecular tools. A totalof 504 faecal samples were collected from sheep (n = 276) and goats (n = 228) in village, government andinstitutional farms in PNG. Samples were screened by nested PCR and genotyped at the 18S rRNA and atthe 60 kDa glycoprotein (gp60) loci. The overall prevalences were 2.2% for sheep (6/278) and 4.4% (10/228) for goats. The species/genotypes identified were Cryptosporidium hominis (subtype IdA15G1) ingoats (n = 6), Cryptosporidium parvum (subtypes IIaA15G2R1and IIaA19G4R1) in sheep (n = 4) and ingoats (n = 2), Cryptosporidium andersoni (n = 1) and Cryptosporidium scrofarum (n = 1) in sheep, Cryptospo-ridium xiao (n = 1) and Cryptosporidium rat genotype II (n = 1) in goats. This is the first report of Cryptos-poridium spp. identified in sheep and goats in PNG. Identification of Cryptosporidium in livestock warrantsbetter care of farm animals to avoid contamination and illness in vulnerable population. The detection ofzoonotic Cryptosporidium in livestock suggests these animals may serve as reservoirs for human infection.

� 2014 Elsevier Inc. All rights reserved.

1. Introduction

Species of Cryptosporidium are globally distributed, zoonoticintestinal protozoan parasites that cause diarrheal disease in ani-mals and are one of the main causes of serious diarrhoea in chil-dren (Kotloff et al., 2013). Clinical effects of Cryptosporidium

infection, which include diarrhoea, weight loss and often deathin lambs and goat kids, severely impact the economy of sheepand goat farming (de Graaf et al., 1999).

Globally, the prevalence of Cryptosporidium spp. in sheep canvary drastically from <5% to >70% (Robertson, 2009). Although few-er epidemiological studies have examined Cryptosporidium spp. ingoats, it appears that prevalence is similarly variable, with valuesof <10% to >40% reported (Robertson, 2009). At least eight Cryptos-poridium species have been identified in sheep faeces including

http://dx.doi.org/10.1016/j.exppara.2014.03.0210014-4894/� 2014 Elsevier Inc. All rights reserved.

⇑ Corresponding author. Fax: +61 89310 414.E-mail address: [email protected] (M. Koinari).

Experimental Parasitology 141 (2014) 134–137

Contents lists available at ScienceDirect

Experimental Parasitology

journal homepage: www.elsevier .com/locate /yexpr


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Cryptosporidium parvum, Cryptosporidium hominis, Cryptosporidiumandersoni, Cryptosporidium suis, Cryptosporidium xiaoi, Cryptospori-dium fayeri, Cryptosporidium ubiquitum and Cryptosporidium scrofa-rum, with C. xiaoi, C. ubiquitum and C. parvum most prevalent (Ryanet al., 2005; Santin et al., 2007; Fayer and Santin, 2009; Giles et al.,2009; Yang et al., 2009; Robertson, 2009; Diaz et al., 2010a; Wanget al., 2010; Sweeny et al., 2011; Cacciò et al., 2013; Connelly et al.,2013). Three of these species; C. parvum, C. hominis and C. xiaoihave also been identified in goats (Giles et al., 2009; Robertson,2009; Diaz et al., 2010b).

Sheep and dairy goats were introduced to Papua New Guinea(PNG) in the early 19th century by colonial administrators andmissionaries (Quartermain, 2004). There are two predominantbreeds of sheep (PNG Priangan sheep and the Highlands Halfbred)and one breed of goat (PNG goat genotype) in PNG (Quartermain,2004). Currently, sheep and goats are raised in government sta-tions for breeding and distribution to smallholder farms and in re-search institutional farms. Little is known about Cryptosporidium insheep and goats in PNG and therefore the aim of the present studywas to determine the prevalence and genotypes of Cryptosporidiumin these two hosts in PNG.

2. Materials and methods

2.1. Sample collection

Faecal samples from a total of 228 goats and 276 sheep werecollected from February 2011 to April 2011 from government,institutional and smallholder farms in a variety of agro-economiczones in PNG.

2.1.1. Farm managementThe flocks from the government (Menifo) and institutional

(Labu, Baisu and Tambul) farms grazed pasture in fenced areas(20–60 ha) at daytime. At night time, the flocks were kept inhouses with wooden, slatted floors in institutional farms and onthe ground in the government farm. At the time of sample collec-tion, the combined numbers of sheep and goats in Menifo, Labu,Baisu, and Tambul were 55, 125, 70 and 143, respectively. The sub-sistence farmers kept few animals, usually less than 20, whichgrazed free range or were tethered and housed at night on slattedfloors or on the ground underneath the farmer’s house. Most ani-mals grazed on native grasses and shrubs. Smallholder farmers alsofed their animals with starchy vegetables (mostly sweet potatoes).The animals drank from troughs (sourced from water supply orrainwater tanks), rainwater run-off water or ponds.

2.1.2. Herd health programsThe floors of the resting houses were not swept. The animals

were penned on dirty floor, ground or on bare concrete floors.The farmers at the institutions and government farms shearedtheir sheep, whereas, the smallholder farmers did not and ex-plained that they did not have the resources for it. Most farm man-agers reported that the most common signs of illness in theiranimals were diarrhoea and coughing, followed by itching and hairloss. The three large institutional flocks were drenched with benz-imidazole (Panacur) nominally at bimonthly intervals. At the timeof sampling, animals had been drenched 2 months previously inLabu, four months previously in Baisu and Tambul and 6 monthspreviously in Menifo. Most smallholder farmers did not knowabout causes of diseases in their sheep and goats or the use ofanthelmintic drugs for parasite control. For instance, a smallholderfarmer reported the death of his entire flock (n = 25) and noticednematode worms in the gut of a dead sheep.

All animals sampled were adults. Faecal samples were obtainedfrom the rectum of randomly selected animals and examined visu-ally for consistency, mucus and macroscopic parasites. All samplecollection methods used were approved by the Murdoch UniversityAnimal Ethics Committee (approval number R2368/10). The faecalsamples were preserved in 70% ethanol and transported to Mur-doch University, Australia, for further analysis.

2.2. DNA isolation and genotyping of Cryptosporidium sp

Total DNA was extracted from 250 mg of faeces using a Power-Soil� DNA Isolation Kit (MO BIO laboratories, Carlsbad, California,USA). All samples were screened for the presence of Cryptosporidi-um spp. at the 18S rRNA locus using a nested PCR as previously de-scribed (Morgan et al., 1997). C. parvum and C. hominis-positiveisolates were subtyped at the 60 kDa glycoprotein locus (gp60) asdescribed by Sulaiman et al. (2005). All positive isolates were se-quenced as previously described (Koinari et al., 2013).

3. Results

Cryptosporidium was detected in 2.2% (6/276; 95% CI 2.8–6.2) ofsheep and 4.4% (10/228; 95% CI 2.8–6.2) of goats at the 18S rRNAlocus. Three species of Cryptosporidium were detected in sheep,namely C. parvum (n = 4), C. andersoni (n = 1) and C. scrofarum(n = 1). Four species/genotypes were detected in goats; C. hominis(n = 6), C. parvum (n = 2), C. xiaoi (n = 1) and rat genotype II(n = 1) (Table 1). Rat genotype II, C. xiaoi, C. scrofarum and C. ander-soni isolates were detected in animals from smallholder farms. TheC. hominis isolates were from smallholder (n = 4) and institutional(n = 2) farms, while C. parvum was identified in animals from allthree types of farms; government (n = 1), institutional (n = 3) andsmallholder (n = 1). Analysis of the gp60 gene identified the pres-ence of two C. parvum subtypes; IIaA15G2R1 (n = 3) andIIaA19G4R1 (n = 2) in sheep and goats and a C. hominis subtype(IdA15G1) (n = 1) in a goat (Table 1). The partial 18S and gp60nucleotide sequences were deposited in the GenBank database un-der the accession numbers KJ584567–KJ584584.

4. Discussion

This is first study to identify and molecularly characterise Cryp-tosporidium in sheep and goats in PNG and analysis revealed a highdiversity of Cryptosporidium parasites within these animal popula-tions. The results of the present study complement recent findingsof C. parvum in fish from freshwater aquaculture, wild freshwaterand wild saltwater, and C. hominis in a wild marine fish in PNG(Koinari et al., 2013). The only other previous study of Cryptospori-dium in PNG identified Cryptosporidium antibodies in 24% of youngchildren from Goroka (Groves et al., 1994).

Although point prevalences were low for Cryptosporidium in thepresent study, the true prevalence may be underestimated as onlysingle faecal samples were screened at one time point and inter-mittent shedding and seasonal variation are common (O’Handleyet al., 1999). In addition, only adult animals were screened andprevalences are known to be much higher in younger animals(Santin et al., 2007). Most importantly, the identification of Cryp-tosporidium in livestock warrants better care of farm animals toavoid contamination and illness in vulnerable populations, as Cryp-tosporidium spp. are known for causing diarrhoea and mortality inyoung animals in both natural and artificial infections (de Graafet al., 1999; Quilez et al., 2008; Giles et al., 2009).

The three species (C. parvum, C. andersoni and C. scrofarum)identified in sheep from the present study have also been reportedin sheep in previous studies (Ryan et al., 2005; Santin et al., 2007;

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Quilez et al., 2008; Giles et al., 2009). In addition, C. andersoni is fre-quently reported in cattle and occasionally in humans, while C.scrofarum is commonly identified in pigs (Xiao, 2010). C. ubiquitumis a common species found in sheep in other countries (Ryan et al.,2005; Santin et al., 2007; Wang et al., 2010; Yang et al., 2009);however, it was not identified in the present study.

Three species, C. hominis, C. parvum and C. xiaoi, detected ingoats in the present study have also been reported in goats in otherstudies (Goma et al., 2007; Geurden et al., 2008; Quilez et al., 2008;Giles et al., 2009; Diaz et al., 2010b). For example, molecular anal-yses confirmed infections with C. hominis and C. parvum in diar-rheic goat kids in the UK (Giles et al., 2009) and C. parvum ingoats in Spain (Quilez et al., 2008). C. xiaoi is commonly reportedin sheep (Fayer and Santin, 2009) and occasionally in goats (Diazet al., 2010b). This is the first report of rat genotype II in goats.Rat genotype II has been reported in house rats in China (Lvet al., 2009), and in the Philippines (Ng-Hublin et al., 2013), brownrats in the Philippines (Ng-Hublin et al., 2013) and in wild blackrats in Northern Australia (Paparini et al., 2012). The goat in whichrat genotype II was identified was from a smallholder farm inBena–Bena, PNG. Smallholders usually keep their goats in nighthouses, which are built very close to their own homes in order toavoid theft. The goat could have acquired this genotype from thehouse rats; however, further studies are required to confirm thisand to determine if the goat was actually infected or just passingoocysts from ingestion of rat faeces. Identification of species suchas C. andersoni, C. scrofarum and C. xiaoi in smallholder flocks prob-ably reflects the management system. Typically, these small rumi-nants are tethered and/or allowed to graze freely on shrubs andgrasses along road sides, near homes and gardens, where theyshare the feeding grounds with other livestock, especially cattleand pigs.

C. hominis and C. parvum are the most common causes of cryp-tosporidiosis in humans worldwide (Xiao, 2010). In the presentstudy, C. hominis (subtype IdA15G1) was found in goats and C. par-vum (subtypes IIaA15G2R1 and IIaA19G4R1) was found in bothsheep and goats. Both the C. parvum IIa subtypes and C. hominisId subtype identified in the present study were previously identi-fied in fish in PNG (Koinari et al., 2013). The C. parvum subtypeIIaA15G2R1, has been reported in sheep and goats in previousstudies in Belgium, Spain, Brazil, China and Australia (Diaz et al.,2010a; Geurden et al., 2008; Paz et al., 2014; Yang et al., 2014;Ye et al., 2014). C. parvum subtype IIaA15G2R1 is a common sub-type in cattle and humans (Feng et al., 2013; Xiao, 2010) in theAmericas, Europe, Northern Africa and Asia (Alyousefi et al.,2013; Amer et al., 2010; Brook et al., 2009; Diaz et al., 2010a; Geur-den et al., 2009; Helmy et al., 2013; Iqbal et al., 2012; Meireles

et al., 2011; Quilez et al., 2008; Rahmouni et al., 2014; Rieuxet al., 2013; Santin et al., 2008; Soba and Logar, 2008). It has alsobeen found in yak in China (Mi et al., 2013) and in buffalo in Egypt(Helmy et al., 2013). The C. parvum subtype IIaA19G4R1 was iden-tified in both a goat and a sheep in the present study. Previously, C.parvum subtype IIaA19G4R1 was identified in cattle in NorthernIreland (Thompson et al., 2007) and Australia (Ng et al., 2008)and freshwater fish (tilapia and silver barb) from PNG (Koinariet al., 2013).

These findings suggest that sheep and goats may be importantreservoirs of C. hominis and zoonotic C. parvum subtypes in PNG.The detection of C. hominis in goats presumably reflects the veryclose association between humans and goats. Further research isnecessary to characterise the prevalence of various Cryptosporidi-um species and genotypes in young lambs, goats and cattle andother hosts such as humans to more fully understand the transmis-sion dynamics of Cryptosporidium in PNG.

Acknowledgments

We acknowledge the staff of National Agriculture ResearchInstitute (NARI), especially Dr. Workneh Ayalew for logistical sup-port and advice, Atmaleo Aguyanto and Martin Lobao for assistancewith sampling of animals and the staff of Department of Agricul-ture and Livestock for their assistance during sampling in PapuaNew Guinea. Also, we would like to thank Josephine Ng-Hublinand Dr. Rongchang Yang at Murdoch University, Australia, for theiradvice with the molecular work.

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Appendix D Gastrointestinal pathogens in sheep, goats and fish in PNG

D-1

Appendix D Identification of novel and zoonotic Cryptosporidium species in fish

from Papua New Guinea.

Veterinary Parasitology 198 (2013) 1– 9

Contents lists available at ScienceDirect

Veterinary Parasitology

jo u r nal homep age: www.elsev ier .com/ locate /vetpar

Identification of novel and zoonotic Cryptosporidium speciesin fish from Papua New Guinea

M. Koinari a,∗, S. Karlb, J. Ng-Hublina, A.J. Lymberyc, U.M. Ryana

a School of Veterinary and Life Sciences, Murdoch University, Murdoch, Western Australia 6150, Australiab School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australiac Fish Health Unit, School of Veterinary and Life Sciences, Murdoch University, Murdoch, Western Australia 6150, Australia


Article history:Received 26 March 2013Received in revised form 28 August 2013Accepted 30 August 2013

Keywords:CryptosporidiumFish18S rRNAgp60Novel genotypeZoonotic

a b s t r a c t

There is still limited information on the distribution of Cryptosporidium species and geno-types in fish. The present study investigated the prevalence of Cryptosporidium species incultured freshwater (n = 132), wild freshwater (n = 206) and wild marine (n = 276) fish inPapua New Guinea (PNG) by PCR screening at the 18S rRNA locus. A total of seven fish (2cultured freshwater, 1 wild freshwater and 4 wild marine fish) were identified as positive forCryptosporidium. Specifically, Cryptosporidium was found in four different host species (Niletilapia, Oreochromis niloticus; silver barb, Puntius gonionotus; mackerel scad, Decapterusmaracellus and oblong silver biddy, Gerres oblongus), giving an overall prevalence of 1.14%(95% CI: 0.3–2%, n = 7/614). Of the seven positive isolates, five were identified as C. parvumand two were a novel piscine genotype, which we have named piscine genotype 8. Piscinegenotype 8 was identified in two marine oblong silver biddies and exhibited 4.3% geneticdistance from piscine genotype 3 at the 18S locus. Further subtyping of C. parvum iso-lates at the 60 kDa glycoprotein (gp60) locus identified 3 C. parvum subtypes (IIaA14G2R1,IIaA15G2R1 and IIaA19G4R1) all of which are zoonotic and a C. hominis subtype (IdA15G1).The zoonotic Cryptosporidium were identified in fish samples from all three groups; culturedand wild freshwater and wild marine fish. Detection of Cryptosporidium among aquaculturefingerlings warrants further research to gain a better understanding of the epidemiologyof Cryptosporidium infection in cultured fish. The identification of zoonotic Cryptosporid-ium genotypes in fish from PNG has important public health implications and should beinvestigated further.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

The apicomplexan protozoan parasite Cryptosporidiuminfects a wide range of mammals, birds, reptiles andfish, primarily causing diarrhoea in mammals, diarrhoeaand/or catarrhal respiratory signs in birds and gastritis

∗ Corresponding author at: Division of Health Sciences, School ofVeterinary and Life Sciences, Murdoch University, Murdoch, WesternAustralia 6150, Australia. Tel.: +61 89360 6379; fax: +61 89310 414.

E-mail addresses: [email protected], [email protected](M. Koinari).

in reptiles and possibly fish (O’Donoghue, 1995; Ryan,2010). Cryptosporidium has been described in more than17 species of both fresh and salt water fish with parasiticstages located deep within and on the surface of thestomach or intestinal epithelium (Alvarez-Pellitero andSitja-Bobadilla, 2002; Alvarez-Pellitero et al., 2004; Ryanet al., 2004; Murphy et al., 2009; Reid et al., 2010; Zangueeet al., 2010; Morine et al., 2012). In fish, Cryptosporidiumcan cause high morbidity with clinical signs includingvariable levels of emaciation, poor growth rates, swollencoelomic cavities, anorexia, listlessness and increasedmortality (Murphy et al., 2009).

0304-4017/$ – see front matter © 2013 Elsevier B.V. All rights reserved.http://dx.doi.org/10.1016/j.vetpar.2013.08.031


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Table 1Species/genotypes of Cryptosporidium reported in fish in previous studies (N = the number of specimens in which each species/genotype of Cryptosporidiumwas identified).

Species/genotype N Fish host References

C. molnari >100 Gilthead sea bream and European seabass Alvarez-Pellitero and Sitja-Bobadilla(2002), Palenzuela et al. (2010)

C. scophthalmi 49 Turbot Alvarez-Pellitero and Sitja-Bobadilla(2002), Alvarez-Pellitero et al. (2004)

C. molnari-like 7 Butter bream, madder seaperch, bristle tooth tang,upsidedown catfish, wedgetailed blue tang and greenchromas, golden algae eater

Zanguee et al. (2010)

Piscine genotype 1 2 Guppy and neon tetra Ryan et al. (2004), Zanguee et al. (2010)Piscine genotype 2 >5 Angelfish, neon tetra and Oscar fish Murphy et al. (2009), Zanguee et al. (2010)Piscine genotype 3 2 Sea mullet Reid et al. (2010)Piscine genotype 4 4 Golden algae eater, kupang damsel, Oscar fish and

neon tetraZanguee et al. (2010), Morine et al. (2012)

Piscine genotype 5 3 Angelfish, butter bream and golden algae eater Zanguee et al. (2010)Piscine genotype 6 1 Guppy Zanguee et al. (2010)Piscine genotype 6-like 1 Gold gourami Morine et al. (2012)Piscine genotype 7 3 Red-eye tetra Morine et al. (2012)Rat genotype 3-like Goldfish Morine et al. (2012)C. scrofarum 2 School whiting Reid et al. (2010)C. parvum 1 School whiting Reid et al. (2010)C. xiaoi 1 School whiting Reid et al. (2010)

Currently the only recognised species infecting fishis Cryptosporidium molnari, which was identified ingilthead sea bream (Sparus aurata) and European seabass (Dicentrarchus labarx) (Alvarez-Pellitero and Sitja-Bobadilla, 2002) and was characterised genetically in2010 (Palenzuela et al., 2010). C. molnari primarily infectsthe epithelium of the stomach and seldom the intes-tine (Alvarez-Pellitero and Sitja-Bobadilla, 2002). In 2004,C. scophthalmi was described in turbot (Psetta maxima.syn. Scopthalmus maximus) (Alvarez-Pellitero and Sitja-Bobadilla, 2002; Alvarez-Pellitero et al., 2004). However,no genetic sequences are available for C. scophthalmi and itcan thus not be considered a valid species due to the highgenetic heterogeneity and morphological similarity amongCryptosporidium species in fish. In addition to C. molnari, atotal of 3 species and 10 genotypes have been characterisedgenetically in fish (Table 1).

Fish are an important part of the diet and a sourceof income especially for people living on the coast andalong the rivers in Papua New Guinea (PNG). Freshwaterfish farming began in the 1960s with the introduction ofcarp and trout species; however, difficulties due to lackof knowledge among farmers impeded farming progressand the spread of its nutritional and financial benefits torural communities (Smith, 2007). Since 1995, the num-ber of inland aquaculture operations has increased in PNGdue to international programmes that involve the expan-sion of hatcheries, training of farmers and the introductionof new fish species (Smith, 2007). To date, very littleis known about the prevalence and genotypes of Cryp-tosporidium in fish or other animals in PNG (Owen, 2005;Koinari et al., 2012, 2013). The present study represents adetailed investigation of the prevalence and genetic charac-terisation of Cryptosporidium in cultured freshwater, wildfreshwater and wild marine fish sampled from a numberof different locations throughout PNG. It is therefore thefirst comprehensive study describing the distribution ofCryptosporidium species in PNG.


2.1. Sample collection

A total of 614 fish from cultured freshwater, wild fresh-water and wild marine environments were collected inPNG between February and August 2011 (Fig. 1). Cul-tured fish (n = 133) included three species, which werecollected from four smallholder fish ponds in Kundiawa,Asaro, Mumeng and Bathem (Table 2). Wild freshwaterfish (n = 205) included six species and were collected fromthe Ramu and Sepik Rivers, while 276 wild marine fishconsisting of 16 species were bought from local fisher-men in Bilbil, Madang, Tavana and Pilapila (Table 2). Onaverage, time lag between collection or purchasing andprocessing of the fish was up to 4 h. All sampling was con-ducted under Murdoch University Animal Ethics permitR2369/10.

The fish were weighed, measured (length and weight)and dissected. Sections of intestine and stomach were cutusing a sterile scalpel blade for each fish, placed in 2 mLEppendorf tubes and preserved in 70% ethanol for molec-ular screening. The remaining stomach and intestine werefixed in 10% buffered formalin for histological analysis. Allsamples were stored at 4 ◦C in PNG until sample collec-tion was completed. The samples were then transportedto Murdoch University, Perth, Australia and stored at 4 ◦Cuntil analysis.

2.2. DNA isolation

The preserved intestines and stomachs were washed5 times with water to remove ethanol and the epithe-lial layers were scraped using a sterile scalpel blade foreach fish. DNA was extracted from 25 mg of intestinal andstomach scrapings using a PowerSoil® DNA Isolation Kit(MO BIO laboratories, Carlsbad, California, USA) accordingto the manufacturer’s instructions and incorporating five


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M. Koinari et al. / Veterinary Parasitology 198 (2013) 1– 9 3

Fig. 1. Map of the study sites in Papua New Guinea. Cultured freshwater fish were obtained from Bathem, Kundiawa, Asaro and Mumeng; wild freshwaterfish were collected in the Ramu River near Sausi and the Sepik River near Pagwi and marine fish were collected from Bilbil, Madang, Pilapila and Tavana.


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Table 2Cultured freshwater, wild freshwater and marine fish species collected in the present study.

Cultured freshwater fish Locations

Kundiawa Asaro Mumeng Bathem Total

Nile tilapia (Oreochromis niloticus) 36 20 27 – 83Common carp (Cyprinus carpia) – 11 32 – 43Mozambique tilapia (Oreochromis massambic) – – – 7 7

Total 36 31 59 7 133

Wild freshwater fish Ramu River Sepik River Total

Silver barb (Puntius gonionotus) 13 39 52Highfin catfish (Neoarius berneyi) – 20 20Mozambique tilapia (Oreochromis massambic) – 15 15Pacu (Colossoma bidens) – 34 34Indo-Pacific trapon (Megalops cyprinoides) – 70 70Redtail catfish (Phractocephalus hemioliopterus) – 14 14

Total 13 192 205

Wild marine fish Bilbil Madang Pilapila Tavana Total

Bigeye scad (Selar crumenopthalmus) 46 – 60 – 106Bigeye trevally (Caranx sexfasciatus) 4 – – – 4Blackfin barracuda (Sphyraena qenie) 9 – – – 9Coachwhip trevally (Carangoides oblongus) – – – 1 1Indo-Pacific trapon (Megalops cyprinoides) 4 – – – 4Mackerel scad (Decapterus macarellus) 5 – 24 – 29Oblong silver biddy (Gerres oblongus) 1 – – 54 55Oriental bonito (Sarda orientalis) – 4 – – 4Pinjalo snapper (Pinjalo pinjalo) – – 1 – 1Rainbow runner (Elagatis bipinnulatus) – 5 – – 5Reef needlefish (Strongylura incisa) – 4 – – 4Slender pinjalo (Pinjalo lewisi) – – – 14 14Spanish mackerel (Scomberomous maculatus) – 3 – – 3Talang queenfish (Scomberoides commersonnianus) – – 2 – 2Wahoo (Acanthocybium solandri) – 1 – – 1Yellow fin tuna (Thunnus albacares) – 34 – – 34

Total 69 51 87 69 276

freeze–thaw cycles as described previously (Ng et al., 2006)to break open the Cryptosporidium oocysts. DNA was elutedin 50 �L of elution buffer. All extracted samples were storedat −20 ◦C until required for screening.

2.3. Cryptosporidium genotyping and subtyping

All 614 samples from fish were screened for thepresence of Cryptosporidium at the 18S rRNA locus as pre-viously described (Morgan et al., 1999). Prevalences wereexpressed as a percentage of positive samples; with 95%confidence intervals calculated assuming a binomial dis-tribution, using the software Quantitative Parasitology 3.0(Rozsa et al., 2000). Isolates that were positive at the 18Slocus were subtyped at the 60 kDa glycoprotein (gp60)locus using primers which produce an 850 bp product(Alves et al., 2003); however, amplification was unsuc-cessful and a shorter (400 bp) product was amplified asdescribed by Sulaiman et al. (2005).

Positive isolates were also amplified at the actin locus.New primers were designed specifically based on actingene sequences of piscine-derived Cryptosporidium anda semi-nested PCR protocol was used. For the primaryPCR, a PCR product of ∼392 bp was amplified using theforward primer ActinallF1 (5′-GTAAATATACAGGCAGTT-3′)

and reverse primer ActinallR1 (5′-GGTTGGAACAATGCTTC-3′). Each PCR was performed in a reaction volume of 25 �Lusing 1 �L of DNA, 1× PCR buffer (Kapa Biosystems, CapeTown, South Africa), 2.0 mM MgCl2, 200 �M (each) dNTP(Fisher Biotech, Perth, Australia), 12.5 pmol of forward andreverse primers and 0.5 U of kapa Taq DNA polymerase(Kapa Biosystems, Cape Town, South Africa). Forty-fivePCR cycles (95 ◦C for 30 s, 46 ◦C for 30 s, 72 ◦C for 30 s)were performed using a Perkin Elmer Gene Amp PCR 2400thermocycler with an initial hot start (95 ◦C for 4 min)and a final extension (72 ◦C for 7 min). For the secondaryPCR, a fragment of ∼278 bp was amplified using 1 �L ofprimary PCR product with forward primer ActinallF2 (5′-CCTCATGCTATAATGAG-3′) and reverse primer ActinallR1.The conditions used for the secondary PCR were identicalto those for the primary PCR.

Secondary PCR products were separated by gel elec-trophoresis and purified using a simple tip elution method.Briefly, the PCR product was excised from the gel usinga scalpel blade and purified using an in house filter tipmethod and used for sequencing without any furtherpurification as previously described (Yang et al., 2013). DNAsequencing was performed using the ABI Prism BigDye®

terminator cycle sequencing kit (Applied Biosystems, Fos-ter City, CA, USA) on an Applied Biosystems 3730 DNA


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Analyser instrument. Nucleotide sequences were ana-lysed using FinchTV 1.4.0 (Geospiza, Inc., Seattle, WA,USA; http://www.geospiza.com) and aligned with refer-ence genotypes retrieved from GenBank using ClustalOmega (http://www.ebi.ac.uk/Tools/msa/clustalo/).

Phylogenetic trees were constructed using additionalsequences retrieved from GenBank. Distance estimationwas conducted using MEGA5 (Tamura et al., 2011) basedon evolutionary distances calculated using the p distancemodel (Nei and Zhang, 2006) and grouped using neighbour-joining. Parsimony and maximum likelihood analyses werealso conducted using the MEGA5 software. Reliabilities forthe trees were tested using 1000 bootstrap replications(Felsenstein, 1985) and bootstrap values exceeding 70 wereconsidered well supported (Hills and Bull, 1993).

2.4. Microscopy

Sections of intestinal and stomach tissues fixed in 10%formalin were embedded in paraffin. Histological sectionswere cut at 5 �m thicknesses, stained with haematoxylinand eosin and examined with an Olympus BX50 lightmicroscope at 400 and 1000 fold magnification.

3. Results

3.1. Prevalence of Cryptosporidium in fish hosts

Of the 614 fish sampled, seven (1.14%, 95% CI 0.3–2%)were positive by PCR, of which, two (0.33%, 95% CI0.09–1.2%) were cultured fingerlings, one (0.16%, 95% CI0.03–0.9%) was a wild freshwater species and four (0.65%,95% CI 0.25–1.66%) were wild marine species. Among thefish hosts infected were: two Nile tilapias (Oreochromisniloticus) with a prevalence of 2.4% (95% CI = 0–5.7%; 2/83)from fish ponds in Kundiawa and Mumeng; one silver barb(Puntius gonionotus) from Sepik River with a prevalenceof 1.9% (95% CI = 0–5.7%; 1/52); two oblong silver biddies(Gerres oblongus) from Bilbil and Tavana with a prevalenceof 3.6% (95% CI = 0–8.5%; 2/55) and two mackerel scads(Decapterus macarellus) from Pilapila with a prevalence of6.9% (95% CI = 0–16.1%; 2/29) (Fig. 1).

3.2. Sequence and phylogenetic analysis of the 18S rDNA,gp60 and actin genes

Sequence analysis identified C. parvum (5 isolates: Niletilapia ON36 and ON68, mackerel scad DM17 and DM18,and silver barb PG37) and a novel piscine genotype (2

Table 4Percentage of genetic differences between piscine genotype 8 and otherCryptosporidium species/genotypes at the 18S rRNA and actin loci.

18S locus Actin locus

Piscine genotype 1 13.0 17.4Piscine genotype 2 5.1 Not analyseda

Piscine genotype 3 4.3 Not analyseda





C. molnari 10.8 7.3–8.5C. parvum 15.4 21.4C. hominis 15.4 21.4C. bovis 17.7 19.0C. baileyi 14.7 19.4C. muris 15.0 19.4C. andersoni 13.8 20.1

a Actin sequences were not available for these genotypes.

isolates: silver biddy GO18 and GO55), hereafter referredto as piscine genotype 8 at the 18S rRNA locus (Table 3).The two piscine genotype 8 isolates from silver biddieswere genetically identical to each other, but distinct fromall isolates previously characterised at the 18S rRNA locus(Table 4). Neighbour-joining, parsimony and maximumlikelihood analysis produced similar results and indicatedthat piscine 8 genotype clustered most closely with thepiscine 3 genotype from a sea mullet, while the other fiveisolates regularly clustered with C. parvum (85% bootstrapsupport) (Fig. 2). Sequences were also obtained for the twopiscine genotype 8 isolates at the actin locus. At this locus,sequence information was only available for C. molnariand piscine genotype 1 and piscine genotype 8 groupedmore closely with C. molnari genotypes (7.3–8.5% geneticdifferences) (Fig. 3 and Table 4).

At the gp60 locus, three subtypes belonging to C. parvum(family IIa: IIaA14G2R1, IIaA15G2R1, IIaA19G4R1) and aC. hominis subtype (family Id: IdA15G1) were identified(Table 3).

3.3. Microscopy

No parasites were observed during microscopic exam-ination of the intestinal or stomach tissues due tosubstantial autolysis of tissues.

3.4. Nucleotide sequence accession numbers

The unique partial 18S rRNA and actin sequences ofpiscine genotype 8 from silver biddies were deposited

Table 3Species, genotypes and subtypes of Cryptosporidium identified in fish in the present study. Sample DM18 was typed as C. parvum at the 18S locus but atgp60 locus it was typed as C. hominis (IdA15G1) indicating the presence of mixed C. parvum/C. hominis in this sample.

Sample Host species Group 18S gp60 Actin

ON36 Nile tilapia Cultured C. parvum IIaA19G4R1 –ON68 Nile tilapia Cultured C. parvum IIaA14G2R1 –PG37 Silver barb Wild freshwater C. parvum IIaA19G4R1 –DM17 Mackerel scad Wild marine C. parvum IIaA15G2R1 –DM18 Mackerel scad Wild marine C. parvum, IdA15G1 –GO18 Silver biddy Wild marine Piscine genotype 8 – Piscine genotype 8GO55 Silver biddy Wild marine Piscine genotype 8 – Piscine genotype 8


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Fig. 2. Evolutionary relationships of Cryptosporidium piscine-derived isolates inferred by neighbour-joining analysis of p distances calculated from pairwisecomparison of 18S rRNA sequences. The percentage of replicate trees in which associated taxa clustered together in the bootstrap test (1000 replicates),are shown at the internal nodes (>50% only) for distance, ML and parsimony (n.s. = not supported). Accession numbers are given in parentheses. Isolatesfrom the present study are marked with asterisk (*).


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Fig. 3. Phylogenetic relationships of Cryptosporidium isolates inferred by neighbour-joining analysis of the actin gene based on genetic distances calculatedby the p distance model. The percentage of replicate trees in which associated taxa clustered together in the bootstrap test (1000 replicates), are shown atthe internal nodes (>50% only) for distance, ML and parsimony (n.s. = not supported). Accession numbers are given in parentheses. Isolates from the presentstudy are marked with asterisk (*).

in the GenBank database under the accession numbersKC807985–KC807988.

4. Discussion

In the present study, the overall prevalence of Cryp-tosporidium sp. was low (1.14%, 7/614). Previous studieshave also reported low prevalences in similar groups of fish(0.8%, 6/709) (Reid et al., 2010) and in ornamental fish (3.5%,6/171) (Morine et al., 2012) while others have reportedhigher prevalences (10–100%) mostly among juvenile fish(Alvarez-Pellitero et al., 2004; Sitja-Bobadilla et al., 2005;Murphy et al., 2009; Zanguee et al., 2010).

This study identified three new fish hosts for Cryp-tosporidium; silver barb (P. gonionotus), mackerel scad (D.maracellus) and oblong silver biddy (G. oblongus). Thefourth host Nile tilapia (O. niloticus) could also be a new hostsince previous studies have detected Cryptosporidium in thesame genus but did not identified the species (Landsbergand Paperna, 1986; Paperna and Vilenkin, 1996).

No oocysts or life cycle stages were observed in theinfected fish hosts in the present study due to substantialautolysis of tissues, which has been reported as an issue forCryptosporidium detection in piscine hosts (Zanguee et al.,2010). Fish are known to have a very rapid rate of tissueautolysis compared to homeotherms (Roberts, 2012) andmany of the fish were dead for up to 4 h prior to beingprocessed which contributed to the problem. Previousstudies have provided histological and electron micro-scopic evidence of considerable cellular damage associatedwith several Cryptosporidium species/genotypes that infectfish; C. molnari in the stomach of fingerlings and juveniles ofgilt-head sea bream (Alvarez-Pellitero and Sitja-Bobadilla,2002), piscine genotype 1 in the stomach of a guppy(Ryan et al., 2004) and piscine genotype 3 in the intes-tine of a mullet (Reid et al., 2010). Piscine genotype 2 wasassociated with gastric infections in angelfish, with thegreatest morbidity and mortality seen in larval and juve-nile fish (Murphy et al., 2009). Whether the C. parvumand C. hominis identified in the present study represents


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actual or mechanical infections remains to be determinedas the oocysts may have been passing through rather thaninfecting these fish and further research using histologicalanalysis of rapidly preserved tissue specimen is required toconfirm this.

The zoonotic Cryptosporidium genotypes identified inthis study are of significance to public health. Cryp-tosporidium parvum subtypes IIaA14G2R1, IIaA15G2R1and IIaA19G4R1 were found in cultured freshwater (Niletilapia), wild freshwater (silver barb) and a marine (mack-erel scad) fish. The zoonotic C. parvum IIa subtype familyhas predominantly been found in calves and in humans inNorth America, Europe and Australia (Xiao, 2010). Only onestudy has previously detected zoonotic C. parvum (subtypeIIaA18G3R1) in a marine fish (Reid et al., 2010). The pres-ence of IIa subtypes in the fish samples from the presentstudy could be due to waterborne contamination withhuman and animal waste. Human sewage managementsystems in PNG villages typically involve dugout toiletsnear the homes and toilets built over the rivers or seas. Nocattle farms were seen in close vicinity to where the sam-ples were collected, whereas dugout toilets, companionanimals and/or domesticated poultry and pigs were seen inthe environment. Fish ponds, rivers and seas could be con-taminated from rainwater runoff and from humans and/oranimals bathing in them. A previous study has detectedantibodies against Cryptosporidium among children fromPNG (Groves et al., 1994), however, no molecular work hasbeen done to confirm the species or genotypes present.

One marine fish (mackerel scad DM18) was identifiedas C. parvum at the 18S locus while at the gp60 locus itwas subtyped as C. hominis IdA15G1R1, indicating that amixed C. parvum/C. hominis infection was present. This isthe first report of C. hominis in fish. The only other marineorganism in which C. hominis has been reported was adugong (Dugong dugon) (Morgan et al., 2000), and its pres-ence probably reflects human sewage contamination of thewater.

The novel piscine genotype 8 was identified in twomarine silver biddies. At the 18S locus, piscine genotype 8exhibited 4.3% genetic difference with piscine genotype 3and 13.8–17.7% genetic difference with other Cryptosporid-ium spp. (Table 4). At the actin locus, piscine genotype8 exhibited 7.3% genetic difference with C. molnari 2and 19.0–21.4% with other Cryptosporidium spp. (Table 4).Based on the differences in the genetic sequences, piscinegenotype 8 is unique and may represent a new species;however, further research is required to confirm this.

The present study identified zoonotic C. parvum sub-types in fish species, which are frequently eaten in PNG.Previous studies have not identified conclusive evidencefor transmission of Cryptosporidium from fish to humansbut one study reported that urban anglers are at a riskfor contracting cryptosporidiosis from exposures receivedwhile fishing and consuming caught fish (mean probabil-ity of infection was nearly one) (Roberts et al., 2007). It istherefore essential that fish for human consumption arehandled appropriately to avoid contamination. In addition,a novel Cryptosporidium sp. (piscine genotype 8) was iden-tified based on molecular data but lacks histological detailsof infection or morphological features of the oocysts, thus

future work is required to establish this genotype as aspecies.

Acknowledgements

We are grateful to the staff of PNG’s National AgricultureResearch Institute (NARI), especially Dr. Workneh Ayalewfor logistical support and advice, Ms Atmaleo Aguyanto andMr Densley Tapat for assistance with sampling of culturedfish and staff at the PNG Department of Agriculture andLivestock for their assistance during sampling. We wouldlike to thank Dr. Andrea Paparini for helping with PCR at theactin locus and Dr. Rongchang Yang for helpful discussions.

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Appendix E Gastrointestinal pathogens in sheep, goats and fish in PNG

E-1

Appendix E Identification of Anisakis species (Nematoda: Anisakidae) in marine

fish hosts from Papua New Guinea

Veterinary Parasitology 193 (2013) 126– 133

Contents lists available at SciVerse ScienceDirect

Veterinary Parasitology

jou rn al h om epa ge: www.elsev ier .com/ locate /vetpar

Identification of Anisakis species (Nematoda: Anisakidae) in marinefish hosts from Papua New Guinea

M. Koinari a,∗, S. Karlb, A. Elliota, U. Ryana, A.J. Lymberyc

a School of Veterinary and Biomedical Sciences, Murdoch University, Murdoch, Western Australia 6150, Australiab School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australiac Fish Health Unit, School of Veterinary and Biomedical Sciences, Murdoch University, Murdoch, Western Australia 6150, Australia


Article history:Received 18 October 2012Received in revised form 5 December 2012Accepted 10 December 2012

Keywords:Anisakid nematodesAnisakis typicaMarine fishITSMt-DNA cox2ZoonoticPapua New Guinea

a b s t r a c t

The third-stage larvae of several genera of anisakid nematodes are important etiologicalagents for zoonotic human anisakiasis. The present study investigated the prevalence ofpotentially zoonotic anisakid larvae in fish collected on the coastal shelves off Madangand Rabaul in Papua New Guinea (PNG) where fish represents a major component of thediet. Nematodes were found in seven fish species including Decapterus macarellus, Gerresoblongus, Pinjalo lewisi, Pinjalo pinjalo, Selar crumenophthalmus, Scomberomorus maculatusand Thunnus albacares. They were identified by both light and scanning electron microscopyas Anisakis Type I larvae. Sequencing and phylogenetic analysis of the ribosomal inter-nal transcribed spacer (ITS) and the mitochondrial cytochrome C oxidase subunit II (cox2)gene identified all nematodes as Anisakis typica. This study represents the first in-depthcharacterisation of Anisakis larvae from seven new fish hosts in PNG. The overall preva-lence of larvae was low (7.6%) and no recognised zoonotic Anisakis species were identified,suggesting a very low threat of anisakiasis in PNG.

© 2012 Elsevier B.V. All rights reserved.

1. Introduction

The family Anisakidae includes parasitic nematodes ofmarine fauna. They have a worldwide distribution anda complex life-cycle which involves invertebrates, fish,cephalopods and mammals (Chai et al., 2005). Anisakidnematodes can accidentally infect humans who can sufferfrom several symptoms including sudden epigastric pain,nausea, vomiting, diarrhoea and allergic reaction (Sakanariand McKerrow, 1989; Audicana and Kennedy, 2008). Mostcases of human infection involve anisakid species belong-ing to the genus Anisakis Dujardin, 1845. There are nine

∗ Corresponding author at: School of Veterinary and Biomedical Sci-ences, Murdoch University, 90 South Street, Murdoch, Western Australia6150, Australia. Tel.: +61 89360 6379; fax: +61 89310 414.

E-mail addresses: [email protected], [email protected](M. Koinari).

described species of Anisakis, which are further subdividedinto two types. Type I consists of Anisakis simplex sensustricto (s.s), A. pegreffii, A. simplex C, A. typica, A. ziphidarumand A. nascettii while Type II consists of A. paggiae, A. phy-seteris and A. brevispiculata (Mattiucci and Nascetti, 2008;Mattiucci et al., 2009). Of these, only A. simplex s.s, A. pegr-effii and A. physeteris have been shown to cause infection inhumans (Mattiucci et al., 2011; Arizono et al., 2012).

Anisakid nematodes can be differentiated based ontheir morphological characteristics and molecular data.According to Berland (1961), larval morphological featuresincluding the absence of a ventricular appendage and anintestinal caecum are useful for distinction between sev-eral anisakid genera. Anisakis Type I or Type II larvae can beidentified based on ventriculus length and the presence of atail spine (or mucron) (Berland, 1961). More recently, poly-merase chain reaction (PCR) based tools have been widelyused for characterisation of anisakid species at multipleloci, including ribosomal internal transcribed spacer (ITS)

0304-4017/$ – see front matter © 2012 Elsevier B.V. All rights reserved.http://dx.doi.org/10.1016/j.vetpar.2012.12.008


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Fig. 1. Map of the study sites. Samples were collected on the coastalshelves off Madang and Rabaul in Papua New Guinea.

regions (Zhu et al., 1998; D’Amelio et al., 2000; Nadler et al.,2005; Pontes et al., 2005; Abe et al., 2006; Umehara et al.,2006, 2008; Zhu et al., 2007; Kijewska et al., 2009) andthe mitochondrial cytochrome C oxidase subunit II (cox2)gene (Valentini et al., 2006; Mattiucci et al., 2009; Murphyet al., 2010; Cavallero et al., 2011; D’Amelio et al., 2011;Setyobudi et al., 2011).

Anisakid nematodes are a major public health con-cern. In the last thirty years, there has been a markedincrease in the prevalence of anisakiasis throughout theworld, due in part to growing consumption of raw or lightlycooked seafood (Lymbery and Cheah, 2007; Audicana andKennedy, 2008). Over 90% of cases of anisakiasis are fromJapan where consumption of raw fish is popular, with mostof the rest from other countries with a tradition of eat-ing raw or marinated fish, such as the Netherlands, France,Spain, Chile and the Philippines (Chai et al., 2005; Choi et al.,2009).

Fish are one of the most important food sources in thecoastal areas of Papua New Guinea (PNG). A wide varietyof fish species are caught and sold at local markets. Littleis known about the prevalence of zoonotic animal para-sites including anisakids in fish or of anisakiasis in humansin PNG (Koinari et al., 2012). A review paper mentionedA. simplex in skipjack tuna (Katsuwonus pelamis) in waterson the south coast of PNG, but did not provide any sup-porting information (Owen, 2005). The present study wasaimed at investigating the distribution of anisakid speciesin the archipelago off the New Guinean northern coast andspecifically to screen for zoonotic species in fish using bothmorphology and PCR analysis of the ITS region and themitochondrial cox2 gene.


2.1. Parasite collection

A total of 276 whole fresh fish were collected frommarkets in the coastal towns of Madang and Rabaul fromMarch to August 2011 (Fig. 1). The fish were necropsied andnematodes were collected from the body cavities. The mus-cles of the fish were thinly sliced and investigated under

white light to check for nematode larvae. Nematodes werepreserved in 70% ethanol and transported to Murdoch Uni-versity, Australia, for analysis. The prevalence of anisakidsin each fish host was expressed as the percentage of pos-itive samples; with 95% confidence intervals calculatedassuming a binomial distribution (Rozsa et al., 2000).

2.2. Morphological analysis

Whole nematodes were cleared in lactophenol formore than 48 h and individually mounted onto microscopeslides. The body lengths of the nematodes were directlymeasured. Images were taken with an Olympus BX50light microscope equipped with Olympus DP70 Camera at40/100× magnification. The following features were mea-sured: body width, oesophagus length, ventriculus lengthand mucron length. Morphological identification was con-ducted according to keys previously reported (Berland,1961; Cannon, 1977; Shamsi et al.,2009a,b).

Scanning electron micrographs (SEMs) were taken forrepresentative specimens to study further morphologicaldetails. SEMs were obtained on a Phillips XL30 scanningelectron microscope at the Centre for Microscopy Char-acterisation and Analysis at the University of WesternAustralia. Parasite samples were fixed in 2% glutaralde-hyde and 1% paraformaldehyde in PBS for 60 min at 4 ◦Cand washed twice with PBS (pH = 7.4) in 1.5 mL eppendorftubes. Samples were dehydrated using a PELCO Biowavemicrowave processor (TedPella Inc., Redding, CA, USA)by passage through increasing ethanol concentrations inwater (33%, 50%, 66% and 100%) followed by two washesin dry acetone. Samples were then dried in a critical pointdryer (Emitech 850, Quorum Technologies, Ashford, UK),attached to aluminium sample holders and coated witha 5 nm thick platinum coating to enable surface electricalconduction.

2.3. Genetic characterisation and phylogenetic analysis

DNA from individual nematodes was isolated usinga DNeasy® Tissue Kit (Cat. No. 69504, Qiagen, Hilden,Germany). The ITS rDNA region was amplified usingprimers NC5 5′-GTAGGTGAACCTGCGGAAGGATCAT-3′

and NC2 5′-TTAGTTTCTTTTCCCTCCGCT-3′ (Zhu et al.,1998) and the mt-DNA cox2 gene was amplified usingprimers 210 5′-CACCAACTCTTAAAATTATC-3′ and 2115′-TTTTCTAGTTATATAGATTGRTTYAT-3′ (Nadler andHudspeth, 2000).

Each PCR was performed in a reaction volume of 25 �Lusing 1 �L of DNA, 1× PCR buffer (Kapa Biosystems, CapeTown, South Africa), 1.5 mM MgCl2, 200 �M (each) dNTP(Fisher Biotech, Australia), 12.5 pmol of each primer and0.5 U of kapa Taq DNA polymerase (Kapa Biosystems, CapeTown, South Africa). Negative (no DNA template) and pos-itive (genomic DNA from L3 Anisakis typica larvae) controlswere included in all PCRs. Thermal cycling was performedin a Perkin Elmer Gene Amp PCR 2400 thermal cycler atconditions as previously described (Valentini et al., 2006;Kijewska et al., 2009).

All amplicons were purified using an Ultra Clean®

DNA purification kit (MolBio, West Carlsbad, CA, USA).


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Table 1Fish species from which anisakid larvae were collected in the present study.

Fish species N Prevalence (CI) MI ± SD (min–max) Specimen code

Decapterus macarellus (Mackerel Scad) 29 6.9 (−0.03 to 0.17) 1 DM23, DM24Gerres oblongus (Slender Silver-biddy) 54 3.7 (−0.02 to 0.09) 3 ± 0.4 (2–4) GO14, GO15Pinjalo lewisi (White-spot Pinjalo Snapper) 14 50 (0.2–0.8) 5 ± 0.92 (1–6) PL1, PL5, PL8, PL9Pinjalo pinjalo (Pinjalo) 1 100 (0.2–0.8) 120 PP1Scomberomous maculatus (Spanish Mackerel) 3 33.3 (−1.1 to 1.8) 1 SM3Thunnus albacares (Yellowfin Tuna) 34 2.9 (−0.3 to 0.09) 3 TA3Selar crumenophthalmus (Bigeye Scad) 106 6.6 (0.02–0.11) 2.9 ± 0.95 (1–3) SC76, SC77, SC78, SC88, SC97, SC100, SC102

N is the number of fish sampled, prevalence is the % of infected fish (95% CI in parentheses) and mean intensity (MI) is the mean number of larvae in theinfected fish hosts ± SD (range). Where no SD value was given, there was only one observation or all observations were similar so that SD could not becalculated.

Sequencing was performed using the ABI Prism BigDye®

terminator cycle sequencing kit (Applied Biosystems,Foster City, CA, USA) on an Applied Biosystems 3730DNA Analyser instrument according to manufacturer’sinstructions except that the annealing temperature waslowered to 46 ◦C for the cox2 locus. Sequences were ana-lysed using FinchTV 1.4.0 (Geospiza, Inc.; Seattle, WA,USA; http://www.geospiza.com) and compared with pub-lished sequences for identification using the NationalInstitute of Health’s National Centre for Biotechnol-ogy Information Basic Local Alignment Search Tool(http://blast.ncbi.nlm.nih.gov). Additional known ITS andcox2 nucleotide sequences were obtained from GenBank(http://www.ncbi.nlm.nih.gov/genbank) for phylogeneticanalysis.

MEGA5 (http://www.megasoftware.net/) was used forall phylogenetic analyses (Tamura et al., 2011). Thenucleotide sequences were aligned using MUSCLE (Edgar,2004), edited manually and tested with MEGA5 modeltest to find the best DNA model to infer the phylo-genetic trees. Phylogenetic analysis with other knownanisakid species was conducted using both neighbour-joining (NJ) and maximum-likelihood (ML) analysis forboth loci. Evolutionary relationships were calculated usingthe Kimura two-parameter model for ITS sequences andthe Tamura–Nei model for cox2 sequences with Contra-caecum osculatum as an outgroup. Reliabilities for both NJand ML trees were tested using 1000 bootstrap replica-tions (Felsenstein, 1985) and bootstrap values exceeding 70were considered well supported (Hills and Bull, 1993). Thenucleotide sequences were deposited in GenBank underthe accession numbers: JX648312–JX648326.

3. Results

3.1. Anisakid prevalence

The overall prevalence of anisakids in fish from PNGwas 7.6% (21/276, 95% CI = 0.05–0.11). Anisakid larvae werefound in 7 fish species, at prevalences ranging from 2.9% to100% (Table 1). The larvae were observed mostly within thebody cavities of the fish and their intensity ranged from 1 to6 per infected fish host with the exception of Pinjalo pinjalo,which had an intensity of 120 larvae per fish, with larvaebeing found in many other body parts including muscles,pyloric region and liver.

3.2. Morphology of Anisakis Type I larvae

Morphological analysis showed that all anisakid nema-todes examined were Anisakis Type I larvae. The larvaewere white and cylindrical in shape. They measuredbetween 20–36 mm in length and 0.4–0.45 mm in width.SEM revealed that the cuticles were irregularly striatedtransversely at 5.5 �m intervals. The larvae had incon-spicuous lips with six papillae, a prominent boring toothand excretory pore which opened ventrally at the cephalicend (Fig. 2, panels A and E). The mouth opening ledto a cylindrical striated oesophagus (length 1.6–2.1 mm),which was followed by a slightly wider ventriculus (length0.98–1.13 mm). The junction between oesophagus andventriculus was transverse (Fig. 2, panel B). The ventriculusconnected obliquely with the intestine, without a ventric-ular appendage and intestinal caecum (Fig. 2, panel C). Theintestine filled the remaining part of the body. The mucronwas distinct and was located at the caudal end (length17.5–18.0 �m) (Fig. 2, panels D, F and G).

3.3. Sequence and phylogenetic analysis of the ITS region

Amplification of the ITS rDNA generated an approx-imately 900 bp product. Both neighbour-joining andmaximum-likelihood analyses produced trees with similartopology. Neighbour-joining analysis of the ITS nucleotidesequences from the present study with previously reportedsequences from GenBank clustered all the Anisakis TypeI larvae examined with Anisakis typica (Fig. 3). The ITSnucleotide sequences of all the Anisakis Type I larvae fromthe present study exhibited 99.1–100% similarities to thepublished sequence of Anisakis typica (AB432909) foundin Indian mackerel (Rastrelliger kanagurta) in Thailandand 96.1–97.6% similarities to the published sequence ofAnisakis typica (JQ798962) found in cutlassfish (Trichiu-rus lepturus) from Brazil. The sequences exhibited 82.7% to88.7% similarities with other Anisakis species (Table 2).

Amplification of the cox2 gene generated an approxi-mately 629 bp product. As with the ITS locus, neighbour-joining and maximum-likelihood analyses produced treeswith similar topology. Neighbour-joining analysis of cox2nucleotide sequences showed that all isolates clusteredbroadly with A. typica (DQ116427) but revealed morevariation. Two broad groups were produced with sub-group I consisting of 5 isolates and A. typica reference


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Fig. 2. Anisakis Type I larvae from S. crumenophthalmus. These images are exemplary for all larvae found in the present study. Light microscopy imagesshow: (A) cephalic end of larva showing the boring tooth and the excretory pore; (B) ventriculus – oesophagus junction; (C) ventriculus – intestine junction;(D) claudal end showing the mucron, anal opening and anal glands. Scanning electron microscopy images show: (E) cephalic end; (F) rounded tail with amucron; (G) mucron. ag, anal glands; ao, anal opening; bt, boring tooth; e, oesophagus; ep, excretory pore; int, intestine; l, lips; mu, mucron; ve, ventriculus.

sequence (DQ116427), and subgroup II containing 16isolates (Fig. 4). Based on genetic distance analysis, sub-group I had 98.9–99.3% similarity to A. typica (DQ116427)while subgroup II had 92.4–94.6% similarity to A. typ-ica (DQ116427). The cox2 nucleotide sequences from thepresent study shared 77.0–87.2% similarity with otherknown Anisakis species (Table 2).

4. Discussion

Anisakid larvae were found in 7.6% (21/276) of the 7 fishspecies examined. The intensity of infection was low (1–6)

Table 2Percentage similarity of the Anisakis species analysed in the present studyand their closest relatives.

Species compared % similarity at

ITS rRNA locus Cox2 locus

A. typica 96.1–100 92.4–99.3A. ziphidarum 87.5–88.7 82.1–84.3A. pegreffii 85.4–86.2 84.7–87.2A. simplex s.s 85.6–86.3 84.7–86.7A. simplex C 85.8–86.6 84.2–85.8Anisakis sp.* 86.5–87.8 Not analysedA. nascettii Not analysed 83.9–86.7A. physeteris 82.7–83.9 82.8–84.5A. brevispiculata 78.6–80.1 77.0–79.1A. paggiae 83.8–84.7 79.3–82.2

At the ITS locus, comparison with A. typica, accession numbers AB432909and JQ798962 were presented. Anisakis sp.* is conspecific with A. nascettii(Mattiucci et al., 2009).

in all fish hosts except for Pinjalo pinjalo (120) (Table 1).Previous studies have reported wide variation in preva-lence and intensity of infection of anisakids in other fishhosts (Costa et al., 2003; Farjallah et al., 2008a,b; Setyobudiet al., 2011). The relatively low infection level found inthe present study could be due to the fact that most ofthe fish hosts sampled were relatively small in size (range16–49 cm fork length) compared to previous studies. Ingeneral, prevalence and parasite burden tends to increasewith the size and the age of the fish host (Setyobudi et al.,2011).

All nematodes in the present study were identified mor-phologically as Anisakis Type I larvae, based on an obliqueconnection between the ventriculus and the intestine, lackof a ventricular appendage and intestinal caecum, and thepresence of a mucron (Berland, 1961; Cannon, 1977). Lar-vae of A. typica found in cutlassfish (Trichiurus lepturus)from Brazil shared similar morphological characteristicswith the A. typica larvae from the present study (Borgeset al., 2012).

Phylogenetic analysis of DNA sequences indicatedthat all examined samples were Anisakis typica. At theITS locus, all isolates examined formed a single cladewith A. typica. The comparison of the ITS nucleotidesequences from this study with sequences previouslydeposited in Genbank resulted in 96.1–97.6% similar-ities to A. typica found in cutlassfish (accession no.JQ798962) from Brazil and 99.1–100% similarities to A.typica (accession no. AB432909) from Indian mackerel inThailand.


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Fig. 3. Phylogenetic relationships between Anisakis species from the present study (*) and other Anisakis species as inferred by neighbour-joining analysisof ITS rDNA. The evolutionary distances were computed using the Kimura-2 parameter method and the rate variation among sites was modelled with agamma distribution with Contracaecum osculatum as an outgroup. The percentage of replicate trees in which the associated taxa clustered together in thebootstrap test (1000 replicates) are shown at the internal nodes (>50% only). Specimen codes are given in Table 1.

At the cox2 locus, whilst the isolates clustered broadlywith the reference A. typica genotype, two distinctsubgroups (I: 98.9–99.3% similarity and II: 92.4–94.6% sim-ilarity) were identified. Previously reported cox2 trees byValentini et al. (2006) also showed similar genetic diver-gence within the Anisakis typica clade. Furthermore, thesequence difference of 5.4–7.6% between the subgroup IIclade and the reference A. typica sequence is still withinthe range found between conspecifics in other nematodetaxa (Blouin et al., 1998).

According to Mattiucci and Nascetti (2006), Anisakisspecies form two sister clades and A. typica is groupedwithin clade I, based on phylogenetic relationships inferredfrom allozyme and mitochondrial gene markers. In the

present study, A. typica clustered within clade I at thecox2 locus, consistent with previously reported phyloge-netic trees (Valentini et al., 2006; Mattiucci et al., 2009;Cavallero et al., 2011; Setyobudi et al., 2011). However, atthe ITS locus, A. typica did not cluster within clade 1 andformed a separate group to the two clades. Other stud-ies have shown similar tree topologies at the ITS locus(Kijewska et al., 2009; Cavallero et al., 2011) and accord-ing to Cavallero et al. (2011), A. typica could form a distinctlineage (resulting in three clades, rather than two, for thegenus Anisakis). It should be noted, however, that the posi-tion of A. typica in both the ITS tree and cox2 tree was notwell supported (<50% bootstrap support) in our study andtherefore more sampling of the species from a wider range


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Fig. 4. Phylogenetic relationships between Anisakis species from the present study (*) and other Anisakis species inferred using the neighbour-joininganalysis of cox2 genes. The evolutionary distances were computed using Tamura–Nei model and the rate variation among sites was modelled with agamma distribution with Contracaecum osculatum as an outgroup. The percentage of trees in which the associated taxa clustered together in a bootstraptest (1000 replicates) are shown next to the branches (>50% only). Specimen codes are given in Table 1.

of hosts and geographical areas is needed to resolve thisdiscrepancy.

The present study identified seven new fish species ashosts for A. typica; Decapterus macarellus, Gerres oblongus,Pinjalo lewisi, Pinjalo pinjalo, Selar crumenophthalmus,Scomberomous maculatus and Thunnus albacares. Previousstudies have identified A. typica in more than 15 dif-ferent fish hosts, which have an epipelagic distributionin the Atlantic Ocean close to the coast lines of Brazil,Mauritius, Morocco, Portugal and Madeira (Mattiucci et al.,2002; Pontes et al., 2005; Marques et al., 2006; Farjallahet al., 2008a; Iniguez et al., 2009; Kijewska et al., 2009;Borges et al., 2012). Anisakis typica has also been foundin the Mediterranean Sea close to Tunisia, Libya, Cyprusand Crete, and in the Indian ocean off Somalia (Mattiucciet al., 2002; Farjallah et al., 2008b) and Australia (Yann,2006). Furthermore A. typica has been found in Japan,Taiwan, China, Thailand and Indonesia (Chen et al., 2008;

Palm et al., 2008; Umehara et al., 2010). Although ithas been hypothesised that A. typica has a global dis-tribution that extends from a 30◦S to a 35◦N latitude(Mattiucci and Nascetti, 2006), a previous distributionmodel for anisakid species has not included PNG (Kuhnet al., 2011).

In conclusion, all anisakids identified from PNG in thepresent study were A. typica, which has not previouslybeen associated with human infections. Further studies areneeded to extend the knowledge of anisakid species dis-tribution in larger fish hosts and other seafood hosts inPNG waters, but the present study results suggest that thedanger from zoonotic anisakid species in PNG is very low.

Acknowledgements

We are grateful to Dr. Rongchang Yang and JosephineNg for helpful discussions.


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This research received no specific grant from any fund-ing agency, commercial or not-for-profit sectors. This studywas approved by the Murdoch University Animal EthicsCommittee (Permit R2368/10).

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