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Antimicrobial drug resistance at the human-animal interface in Vietnam

Nguyen, V.T.

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Download date: 15 Nov 2020

ANTIMICROBIAL DRUG RESISTANCE AT THE HUMAN – ANIMAL INTERFACE IN VIETNAM

Nguyen Vinh Trung

ANTIMICROBIAL DRUG RESISTANCE

AT THE HUMAN – ANIMAL INTERFACE IN VIETNAM

Nguyen Vinh Trung

ANTIMICROBIAL DRUG RESISTANCE

AT THE HUMAN - ANIMAL INTERFACE IN VIETNAM

Thesis, University of Amsterdam, the Netherlands

Copyright © 2017, Nguyen Vinh Trung, Ho Chi Minh City, Vietnam

No part of this thesis may be reproduced, stored or transmitted in any form or by any means,

without prior permission from the author.

Printing: Ipskamp Drukkers B.V., Enschede, the Netherlands

Cover design: A Vietnamese farmer and his chickens by Nguyen Ngoc Minh Thy and Nguyen Vinh Trung

The studies included in this thesis were initiated from the Oxford University Clinical Research Unit

in Ho Chi Minh City, Vietnam; the Department of Medical Microbiology; the Department of Global Health and

Amsterdam Institute for Global Health and Development, Academic Medical Center, University

of Amsterdam, the Netherlands.

Funding was from The Netherlands Organisation for Health Research and Development/

The Netherlands Organisation for Scientific Research (grant number 205100012)

and The Wellcome Trust, UK (grant number 089276/Z/09/Z)

ANTIMICROBIAL DRUG RESISTANCE

AT THE HUMAN - ANIMAL INTERFACE IN VIETNAM

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad van doctor

aan de Universiteit van Amsterdam

op gezag van de Rector Magnificus

prof. dr. ir. K.I.J Maex

ten overstaan van een door het College voor Promoties ingestelde commissie,

in het openbaar te verdedigen in de Aula

op 13 september 2017, te 13.00 uur

door Nguyễn Vĩnh Trung

geboren te Dong Thap, Vietnam

Promotiecommissie:

Promotor(es): prof. dr. C. Schultsz AMC – UvA

prof. dr. J.A. Wagenaar Universiteit Utrecht

Copromotor(es): dr. N.T. Hoa Oxford University

Overige leden: prof. dr. B.H. ter Kuile Universiteit van Amsterdam

prof. dr. C.M.J.E. Vandenbroucke-Grauls Vrije Universiteit Amsterdam

prof. dr. H.F.L. Wertheim Radboud Universiteit Nijmegen

prof. dr. D.J. Mevius Universiteit Utrecht

prof. dr. F.G.J. Cobelens AMC – UvA

prof. dr. J.M. Prins AMC – UvA

Faculteit der Geneeskunde

TABLE OF CONTENTS

CHAPTER 1: Introduction ............................................................................................ 1

CHAPTER 2: Antimicrobial usage in chicken production in the Mekong Delta of

Vietnam ...................................................................................................................... 13

CHAPTER 3: Non-typhoidal Salmonella colonization in chickens and humans in the

Mekong Delta of Vietnam ........................................................................................... 29

CHAPTER 4: Prevalence and risk factors for carriage of antimicrobial resistant

Escherichia coli on household and small-scale chicken farms in the Mekong Delta of

Vietnam ...................................................................................................................... 41

CHAPTER 5: Colonization of Enteroaggregative Escherichia coli and Shiga Toxin-

producing Escherichia coli in chickens and humans in southern Vietnam .................... 73

CHAPTER 6: Contribution of non-intensive chicken farming to extended-spectrum Beta-

lactamase producing Escherichia coli colonization in humans in southern Vietnam ..... 87

CHAPTER 7: Zoonotic transmission of the mcr-1 colistin resistance gene from non-

intensive poultry farms in Vietnam ............................................................................ 113

CHAPTER 8: Discussion .......................................................................................... 127

Thesis summary ........................................................................................................ 137

Appendix................................................................................................................... 145

CHAPTER 1 INTRODUCTION

CHAPTER 1

Chapter 1: Introduction

The world is facing a major threat from the development of antimicrobial-resistant Gram-

negative bacteria, including Enterobacteriaceae, that have become resistant to most available

antibiotics [1]. In addition, development of novel and effective antimicrobials is lagging behind

the increase in antimicrobial resistance [2].

It has been shown that antimicrobial use is one of the main drivers of antimicrobial resistance

[3]. Therefore, it is crucial to understand the antimicrobial use and the epidemiology of

antimicrobial resistance in both humans and animals to combat or delay resistant bacteria

spreading in the community.

The aims of this chapter are (a) to describe the situation of antimicrobial usage and antimicrobial

resistance in Vietnam, (b) to review current knowledge of transmission of antimicrobial resistant

micro-organisms or resistance encoding genes between chickens and humans worldwide, and (c)

to provide the outline of this thesis.

Antimicrobial Usage and Antimicrobial Resistance in Vietnam

Antimicrobial usage in Vietnam

According to the pharmaceutical law in Vietnam, antimicrobials are prescription-only drugs.

Unfortunately, these regulations are just not enforced. As a result, antimicrobial drugs can be

purchased without prescription from pharmacies. No official and detailed figures on

antimicrobial usage are available in the country. Despite the continuous increase of the literacy

rate in Vietnam, knowledge on antimicrobial usage is still poor. People have the tendency of

buying antimicrobials from private pharmacies since it is faster and cheaper than visiting a clinic

or hospital. Even if clinics and hospitals are visited, doctors do not always prescribe the correct

type or dosage of antimicrobial drugs.

Hospitals in Vietnam commonly lack adequate infection control and diagnostic microbiology

capacities. Therefore, broad-spectrum antimicrobials are commonly prescribed by many

clinicians. Multiple studies have been performed to investigate the usage of antimicrobials in the

2

CHAPTER 1 clinical setting in Vietnam. A study in 2008 indicated the widespread and often inappropriate use

of antimicrobials in Vietnamese hospitals [4]. In the clinical setting, antimicrobials are frequently

administered intravenously and as combination therapy, mostly with two antibiotics [5, 6]. While

national antimicrobial therapy guidelines are not available, local guidelines are frequently used.

Since infectious diseases are common in the country and infection control is not always efficient,

even in a clinical setting, antimicrobials for prophylactic purposes may account for up to 10 % of

the indications [5]. Interestingly, in intensive care units, the mean antimicrobial usage was 811

defined daily doses (DDD) in 1000 occupied bed days [7] which is similar to European data [8].

Cephalosporins, especially third-generation cephalosporins, are repeatedly reported as the most

common antimicrobial class used in hospitals in Vietnam [4-7, 9].

The main suppliers of antimicrobials in the community in Vietnam are private pharmacies, where

most antimicrobials are sold without a prescription. It is possible to rent a pharmacist license and

own a pharmacy with no or very limited medical background [10]. As a result, knowledge about

antimicrobials and antimicrobial resistance of those responsible for selling antimicrobials is

inadequate [11]. These drug sellers, however, are consulted by patients and decide which

antimicrobial drugs should be used for people in the community [12]. Therefore, antimicrobials

are frequently dispensed inappropriately from these private pharmacies. An intervention study

has shown that strengthening education and regulation of prescription effectively improved the

knowledge and reported practices of drug sellers [13]. Obviously, continuous training of drug

sellers on antimicrobial use and enforcement of regulations of antimicrobial distribution are

equally important.

Although antimicrobial usage is common practice in animal farming, data on antimicrobial usage

in animals in Vietnam are limited. The main purposes of using antimicrobials in animals are

growth promotion, and prophylaxis and treatment of infectious diseases. A study has shown that

antimicrobials were intensively used in chicken and pig farming in northern Vietnam [14]. Up to

10 different antimicrobial classes were used, of which colistin, chlortetracycline and

oxytetracycline were the most common antimicrobials used in animal husbandry, both for

prophylactic and therapeutic purposes [14]. However, quantitative data on antimicrobial usage

are not available. Although an effort has been made to create a centralized system for registration

and distribution of antimicrobials for animals in the country, it remains difficult to precisely

3

CHAPTER 1 quantify antimicrobial usage in animals since commercial feeds commonly contain antimicrobial

drugs [10]. Not only the quantity but also the quality of antimicrobial drugs for animals is a

concern in Vietnam. A study on antimicrobials in Vietnam found that in a considerably small

percentage of antimicrobials the concentrations of active ingredients were correctly declared

[15]. Strikingly, some mixed antimicrobial products did not even contain any of the labeled

ingredients [15]. Clearly, review of the approval procedures and monitoring of the quality of

antimicrobials in animal husbandry are urgently needed. In addition, it is notable that a

considerable amount of antimicrobials in agriculture is discharged and hence accumulating in the

environment [16], where they may accelerate antimicrobial resistance selection in bacteria [17].

In addition, farmers do not always respect the withdrawal period of antimicrobials when used for

their food animals [14]. As a consequence, concentrations of antimicrobial residues in food

sources may be high [18].

Antimicrobial resistance in Vietnam

Since no active national surveillance programs and systematic data collection on antimicrobial

resistance are conducted in the country, data on antimicrobial resistance are fragmented.

In recent years, bacterial antimicrobial resistance levels in Vietnam are on the rise. We observed

a substantial increase of antimicrobial resistance in various bacterial pathogens in the clinical

setting. Notably, amongst Gram-negative bacteria causing intra-abdominal and urinary tract

infections, particularly in E. coli and K. pneumoniae, high rates of extended-spectrum β-

lactamase (ESBL) producers up to 50% were reported between 2009 - 2011 [19, 20]. Among

diarrheal pathogens, resistance to at least two antimicrobials of different classes was detected in

78.6% of Shigella strains and 89.5% of E. coli strains [21]. The rate of multidrug resistance

(resistance to at least three antimicrobial agents of different classes) in Streptococcus

pneumoniae in 2008 - 2009 was 75.5% [22]. In addition, a study in 2004 – 2005 has found that

all Neisseria gonorrhoeae isolates were resistant to ciprofloxacin [23] whilst multidrug

resistance (resistance to erythromycin, tetracycline and chloramphenicol) in Streptococcus suis

has increased from 2.5% to 12.5% during the period of 1998 - 2008 [24]. Meanwhile, multidrug

resistance (resistance to chloramphenicol, ampicillin, and trimethoprim- sulfamethoxazole) in

Salmonella enterica Typhi has increased from 63.2% in 1993 to 80.4% in 2007 – 2008 [25].

4

CHAPTER 1 In a community-based study in 2007, more than 65% of fecal commensal E. coli was shown to

be resistant to tetracycline, co-trimoxazole and ampicillin. Multidrug resistance (resistance to 3

antimicrobials) among those isolates was 60% [26]. In another study performed in 2013 - 2014,

the carriage rate of ESBL-producing E. coli in healthy individuals in Vietnam was reported to be

around 50% [27].

Antimicrobial resistance in food-borne pathogens and in commensal bacteria of food animals is a

major threat to public health worldwide and certainly in Vietnam. Multidrug resistant was

observed in 41.1% Salmonella isolated from raw meats and seafood in 2012 - 2015 [28]. The rate

of multidrug resistance in E. coli isolates from pork was 75% in 2004 [29]. In another study in

2007, 86.5% of Enterococcus faecium isolated from chickens was resistant to enrofloxacin [30].

Transmission of Antimicrobial Resistance between Chickens and Humans

Many studies have examined the link between antimicrobial resistance indifferent bacterial

species isolated from chickens and humans, including commensal and pathogenic bacteria. There

are multiple routes of transmission of antimicrobial resistant bacteria or genomic antimicrobial

resistance determinants from chickens to humans and vice versa. Transmission from chickens to

humans can occur via direct contact with chickens or food of chicken origin as well as through

indirect routes such as by contaminated foods or through environmental contamination [31].

In 1976, one of the first studies demonstrating potential transmission of antimicrobial resistant

bacteria between chicken and humans in the United States was published [32]. The authors

showed that 2 weeks after the introduction of tetracycline–medicated feed, intestinal bacteria of

the chickens were almost all tetracycline resistant. Interestingly, the farmers on those farms also

showed an increase of fecal carriage of tetracycline resistant bacteria within 6 months. One year

later, in 1977, a study in the UK showed that antimicrobial resistant E. coli from chickens were

established and persisted for about 10 days as part of the flora in exposed humans [33]. A similar

trend of increasing quinolone-resistant Campylobacter was observed in poultry products and

humans in the Netherlands during the period between 1982 and 1989 [34]. During this time, the

prevalence of quinolone-resistant Campylobacter has grown from 0% to 14% in poultry products

5

CHAPTER 1 and from 0% to 11% in humans. This observation coincided with the increasing usage of

fluoroquinolones, especially enrofloxacin, in poultry farming in the Netherlands.

Chicken products were also demonstrated as a source of fluoroquinolone-resistant E. coli that

colonized and caused bacteremia in humans in Spain, since resistant isolates from humans were

phylogenetically indistinguishable from chicken isolates [35]. These findings were supported by

a study from Iceland showing quinolones in chicken feed driving resistance development of E.

coli in chickens, which could subsequently be a source of ciprofloxacin resistant E. coli in

humans [36].

Similar observations were shown for gentamicin-resistant bacteria. A study in the USA reported

evidence for transmission of gentamicin resistant Enterococci from chickens to humans via the

food supply [37]. In another study, the risk of colonization with gentamicin resistant E. coli was

significantly higher in chicken farmers than in non-exposed individuals in the USA [38].

In a study performed in the Netherlands, E. coli with an identical pulsed-field gel electrophoresis

pattern was isolated from a chicken and a chicken farmer [39]. In a population based study from

the US, the authors concluded that human antimicrobial resistant E. coli likely originated from

poultry since phylogenetic distribution and drug-resistance of isolates from poultry were similar

to isolates from humans [40]. Another study in Europe has also shown that antimicrobial

resistant E. coli isolated from chickens were genetically similar to resistant isolates in humans

[41].

Another study in Denmark also concluded that chickens and chicken meat probably were the

source of extraintestinal pathogenic E. coli (ExPEC) in community-based individuals and

patients with urinary tract infections (UTI) since cluster analysis showed strong similarities of

antimicrobial resistance profiles as well as virulence genes between UTI patients, community-

based individuals and chicken isolates [42]. The relationship of Klebsiella pneumoniae isolates

originating from chickens and those from humans in a clinical setting was investigated in the

USA. The authors observed a close relatedness of K. pneumoniae isolates from chicken meat and

clinical isolates. These findings suggested that retail meat could be a vehicle for spreading

antimicrobial resistant K. pneumoniae from chickens to humans [43].

6

CHAPTER 1 In a study from China, apramycin-resistant E. coli were isolated from poultry farm workers,

although apramycin is licensed for use in animals only and has never been used in humans. This

observation indicated the likely transfer of apramycin-resistance genes between E. coli isolates

from chickens and humans [44].

Most studies on the transmission of antimicrobial resistance bacteria or mobile genetic elements

between chickens and humans have focused on extended-spectrum cephalosporins, because these

are important and critical antimicrobials to treat infections in both animals and humans. The

increasing prevalence of extend-spectrum cephalosporin-resistant microorganisms is a great

concern worldwide [45].

A study in Canada in 2010 showed an association between the use of ceftiofur in chickens and

the occurrence of extended spectrum cephalosporin-resistant bacteria in chickens and humans.

Temporal changes in ceftiofur-resistant Salmonella and E. coli in chickens and humans was

observed and related to voluntary withdrawal or reintroduction of ceftiofur use in chickens [46].

Another study in Spain has detected two ESBL E. coli of two different clonal groups (A and D)

from poultry farms that were having similar backgrounds of virulence genes and PFGE profiles

to human clinical isolates suggesting potential zoonotic transmission of these E. coli isolates

[47].

Studies from the Netherlands also supported the possibility of transmission of antimicrobial

resistance between chickens and humans [48-50] since genetic analyses of Enterobacteriaceae,

mostly E. coli, from chicken meat and humans revealed similarities between ESBL genes,

plasmids and bacterial strains. These studies suggested the transmission of bacterial strains and

antimicrobial resistance determinants including ESBL genes or plasmids from chickens to

humans via the food chain.

Despite this growing evidence of zoonotic transmission of antimicrobial resistant bacteria or

resistance determinants between chickens and humans, there also were studies that did not

support such transmission. With the increased access to whole genome sequencing, more

accurate and detailed analysis and comparison of bacterial isolates from animals and humans

have become possible and the results of such analyses have changed earlier views.

7

CHAPTER 1 In a study from the USA, E. coli ST 131 pulsotype isolates from diverse sources and locales

collected during the period of 1967 -2009 did not show similarities between isolates from

humans, food-producing animals and foods [51]. Several other studies worldwide have

documented divergence in sequence types and resistance genes of E. coli isolates originating

from chickens and humans [52-55]. Even in the Netherlands, a country with strong evidence for

transmission of ESBL-producing bacteria or ESBL genes, whole genome sequence analyses

suggested that ESBL genes are disseminated in chickens and humans through transmission of

different plasmids [56]. In addition, another study from the Netherlands revealed that the risk of

carriage of ESBL-producing Enterobacteriaceae among individuals in high and low broiler

densities was the same [57], suggesting that chickens are not a major contributor to colonization

with ESBL-producing Enterobacteriaceae in humans. Similarly, a study from northern Vietnam

in 2015 also showed limited transmission of an ESBL gene (CTX-M-9 type) between human and

chicken E. coli isolates [58].

Although there have been an increasing number of studies on transmission of antimicrobial

resistance worldwide, there are still many knowledge gaps about antimicrobial use in chickens,

as well as the prevalence and transmission of AMR between chickens and humans in Vietnam.

This is especially true for backyard farms settings, which represent the majority of chicken

farming in Vietnam and South East Asia but which have rarely been studied.

Thesis Outline

The aims of this thesis are (1) to assess the prevalence of antimicrobial drug resistance among

non-typhoidal Salmonella and E. coli strains isolated from backyard farm chickens and humans

in Vietnam; (2) to relate these findings to antimicrobial usage; and (3) to estimate the risk of

human colonization with antimicrobial resistant bacteria and transmission of genomic resistance

determinants as a result of chicken farming in southern Vietnam.

Chapter 1 provides a review of the current situation of antimicrobial usage and antimicrobial

resistance in humans and chicken in Vietnam. In addition, current knowledge of the transmission

of antimicrobial resistant bacteria and genomic resistance determinants is reviewed.

8

CHAPTER 1 In Vietnam, although antimicrobials are used commonly in chicken production, quantitative data

are not available. Therefore, studies reported in chapter 2 investigated and quantified

antimicrobial usage in chicken farming in the Mekong Delta of Vietnam.

In Chapters 3 to 7 the prevalence of colonization with antimicrobial resistant E. coli and

Salmonella as well as transmission of antimicrobial resistance genes between these bacteria

isolated from chickens and humans in southern Vietnam were studied. Chapter 3 describes

studies investigating the prevalence of colonization with non-typhoidal Salmonella (NTS) in

chickens and humans in the southern of Vietnam as well as the risk of human NTS colonization

through direct chicken exposure. The prevalence of antimicrobial resistance among commensal

E. coli isolates on non-intensive chicken farms, common in southern Vietnam, and the

association between antimicrobial resistance and farming practices as well as antimicrobial usage

are described in Chapter 4. Chapter 5 assesses the potential presence of highly pathogenic

Enterohaemorrhagic E. coli (EHEC) O104:H4 strains in samples collected from Vietnamese

chicken farms, farmers and matched asymptomatic humans not exposed to chickens. Chapter 6

was conducted to study the potential contribution of transmission from poultry to colonization

with ESBL-producing E. coli in humans. This was done by determining the prevalence and

relatedness of resistance-encoding genes in ESBL-positive E. coli isolated from humans and

chickens and to relate these to antimicrobial drug usage. In Chapter 7, we investigated the

consequences of colistin usage in non-intensive poultry farms for the prevalence of colonization

with bacteria carrying the mcr-1 - a plasmid-mediated colistin resistance gene. In addition, the

risk of onward transmission to humans was studied by molecular epidemiological analyses of

isolates from chickens, their farmers and unexposed populations in a defined geographical area

of southern Vietnam. The main findings of this thesis and future perspectives are discussed in

Chapter 8.

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48. Leverstein-van Hall, M.A., et al., Dutch patients, retail chicken meat and poultry share the same ESBL genes, plasmids and strains. Clin Microbiol Infect, 2011. 17(6): p. 873-80.

49. Kluytmans, J.A., et al., Extended-spectrum beta-lactamase-producing Escherichia coli from retail chicken meat and humans: comparison of strains, plasmids, resistance genes, and virulence factors. Clin Infect Dis, 2013. 56(4): p. 478-87.

50. Overdevest, I., et al., Extended-spectrum beta-lactamase genes of Escherichia coli in chicken meat and humans, The Netherlands. Emerg Infect Dis, 2011. 17(7): p. 1216-22.

51. Johnson, J.R., et al., Comparison of Escherichia coli ST131 pulsotypes, by epidemiologic traits, 1967-2009. Emerg Infect Dis, 2012. 18(4): p. 598-607.

11

CHAPTER 1 52. Dhanji, H., et al., Cephalosporin resistance mechanisms in Escherichia coli isolated from raw chicken

imported into the UK. J Antimicrob Chemother, 2010. 65(12): p. 2534-7. 53. Kawamura, K., et al., Molecular epidemiology of extended-spectrum beta-lactamases and Escherichia coli

isolated from retail foods including chicken meat in Japan. Foodborne Pathog Dis, 2014. 11(2): p. 104-10. 54. Wu, G., et al., Comparative analysis of ESBL-positive Escherichia coli isolates from animals and humans

from the UK, The Netherlands and Germany. PLoS One, 2013. 8(9): p. e75392. 55. Belmar Campos, C., et al., Prevalence and genotypes of extended spectrum beta-lactamases in

Enterobacteriaceae isolated from human stool and chicken meat in Hamburg, Germany. Int J Med Microbiol, 2014. 304(5-6): p. 678-84.

56. de Been, M., et al., Dissemination of cephalosporin resistance genes between Escherichia coli strains from farm animals and humans by specific plasmid lineages. PLoS Genet, 2014. 10(12): p. e1004776.

57. Huijbers, P.M., et al., Prevalence of extended-spectrum beta-lactamase-producing Enterobacteriaceae in humans living in municipalities with high and low broiler density. Clin Microbiol Infect, 2013. 19(6): p. E256-9.

58. Ueda, S., et al., Limited transmission of bla(CTX-M-9)-type-positive Escherichia coli between humans and poultry in Vietnam. Antimicrob Agents Chemother, 2015. 59(6): p. 3574-7.

12

CHAPTER 2 ANTIMICROBIAL USAGE IN CHICKEN PRODUCTION IN THE

MEKONG DELTA OF VIETNAM

CHAPTER 2

Chapter 2: Antimicrobial usage in chicken production in the Mekong delta of Vietnam Juan J Carrique-Mas1, Nguyen V. Trung1,2, Ngo T. Hoa1, Ho Huynh Mai3, Tuyen H. Thanh1, James I. Campbell1, Jaap A. Wagenaar4, Anita Hardon5, Thai Quoc Hieu3 and Constance Schultsz1,6 1 Nuffield Department of Medicine, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam 2 Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, The Netherlands 3 Sub-Department of Animal Health Ly Thuong Kiet, Tien Giang, Vietnam 4 Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, The Netherlands 5 Center for Social Science and Global Health, University of Amsterdam, The Netherlands 6 Department of Global Health - Amsterdam Institute for Global Health and Development, University of Amsterdam, The Netherlands

Zoonoses and Public Health, 2015 (62) Suppl 1:70-8

14

CHAPTER 2

Abstract

Antimicrobials are used extensively in chicken production in Vietnam, but to date no quantitative

data are available. A 2012-2013 survey of 208 chicken farms in Tien Giang province, stratified

by size (10-200 chickens; >200-2,000) was carried out to describe and quantify use of

antibacterial antimicrobials (usage per week per chicken, and usage per 1,000 chickens

produced) in the Mekong delta, and to investigate factors associated with usage. Twenty-eight

types of antimicrobial belonging to 10 classes were reported. Sixty three per cent of all

commercial formulations contained at least two antimicrobials. On 84% occasions antimicrobials

were administered with a prophylactic purpose. The overall adjusted quantities of antimicrobials

used/week/chicken and per 1,000 chickens produced (g) were 26.36mg (SE ±3.54) and 690.4g

(SE ±203.6), respectively. Polypeptides, tetracyclines, penicillins and aminoglycosides were the

antimicrobials used by most farms (18.6% farms, 17.5%, 11.3% and 10.1% farms, respectively),

whereas penicillins, lincosamides, quinolones, and sulphonamides/trimethoprim, were

quantitatively the most used compounds (8.27mg, 5.2mg, 3.16mg and 2.78mg per week per

chicken, respectively). Factors statistically associated with higher levels of usage (per week per

chicken) were: meat farms (OR=1.40) and farms run by a male farmer (OR=2.0). All-in-all out

farming systems (correlated with medium farms) were associated with reduced levels of

antimicrobial usage (OR=0.68). Usage levels to produced meat chickens were considerably

higher than those reported in European countries. This should trigger the implementation of

surveillance programmes to monitor sales of antimicrobials that should contribute to the rational

administration of antimicrobials in order to preserve the efficacy of existing antimicrobials in

Vietnam.

Keywords: Antimicrobial use, antimicrobial resistance, antibiotics, poultry, Vietnam

15

CHAPTER 2

Introduction

Antimicrobial resistance (AMR) is currently one of the most serious threats to global health,

resulting in a decreasing repertoire of antimicrobials available to treat serious infections [1].

Almost all classes of antibiotics available to humans have also been used in animal production

[1, 2], and AMR has been increasingly identified in animal pathogens [3-5]. Over recent years

there has been mounting evidence that the use of antimicrobials in agriculture is a major factor

driving AMR globally [6]. Antimicrobials are extensively used in animal farming with the aim of

treating and prevent animal diseases, as well as improving growth performance [7].

Antimicrobial usage on farms selects for AMR bacteria and other genetic determinants that may

spread to humans either through direct contact, consumption of meat or indirectly through

environmental pathways [6, 8].

In Vietnam, high levels of resistance against a number of antimicrobials have been reported in

food-borne pathogens such as non-typhoid Salmonella serovars and Campylobacter spp. in

poultry, livestock and meat [9-14]. Compared with isolated from pigs and fish, E. coli from

Vietnamese chickens have higher levels of AMR [15]. In Vietnam antimicrobials are available to

farmers over the counter without prescription. Some reports have suggested high levels of usage

of a range of antimicrobials in pig and poultry farming, although the quantities used are unknown

[16, 17].

The aims of this study were: (1) to describe and quantify levels of antimicrobial usage, both in

terms of usage per unit time as well as per chicken produced, in chicken farms in the Mekong

delta; and (2) to identify factors associated with usage. Results from this study will serve to

increase awareness and identify required efforts to reduce usage of antimicrobials in animal

production in the region.

16

CHAPTER 2 Materials and methods

Survey design and data collection

Data on antimicrobial usage on chicken farms were obtained from a survey carried out on 208

chicken farms sampled from three districts containing 40% poultry population in Tien Giang

province, Mekong delta, Vietnam. The survey was carried out between March 2012 and April

2013. For logistic reasons, sampling was stratified by size (10-200, ‘household farms’; 201-2,000

chickens, ‘small to-medium farms’) and district (My Tho, Cho Gao and Chau Thanh) (total 6

strata), with ~34 farms sampled per stratum. Within each stratum, farms were randomly selected

from the census by staff from Tien Giang sub-Department of Animal Health. The sample size per

stratum (34) was determined based on requirements for determining the prevalence in each

district of E. coli resistance against a number of antimicrobials. Questionnaires with both open

and closed questions were used to obtain data on antimicrobial usage. Farm owners were asked

about details on administration of any bacterial antimicrobial formulations over a period of time,

including: (1) Method of administration (water, feed, injection, spray); (2) Type of use

(prophylactic/therapeutic/both); (3) Timing of application: (a) continuously; (b) on arrival; (c) in

response to disease; (c) periodic (i.e. change of season, changing feed, before selling).

Quantitative data on each formulation administered over a set period of time were gathered,

including the commercial name of the product, presentation and number of containers used.

From these data the total amount of active antimicrobial compound was calculated.

Questionnaires enquired about usage ‘from restocking until the visit date’ for small-to-medium

farms. A fixed period of observation (90 days) was determined for household farms since

household farms did not practice all-in-all-out production. In addition farmers were asked about

the source of advice for using the antimicrobial (veterinary pharmacist; district veterinarian;

chief animal health worker; drug company sales person; friend/neighbour; and ‘other’).

Calculation of antimicrobial usage

Two outcomes were of interest: (a) usage per chicken per time unit (or ‘intensity’ of usage); and

(b) usage related to production output (usage per 1,000 chickens produced).

Usage per week per chicken (Uwc milligrams) was calculated by dividing in each farm the

amount of each antimicrobial used (Ur milligrams) by the length of the reporting period for that

17

CHAPTER 2 farm (t weeks), and then by the number of chickens present in the farm (N chickens) on the visit

date. The ‘amount of each antimicrobial used to produce 1,000 chickens’ (in grams) (U1000c

grams) is dependent on the length of production cycle in each farm. Therefore chicken output

and antimicrobial usage were estimated in each study farm over one year.

Estimated annual antimicrobial usage (Uy grams) was calculated for each antimicrobial:

Uy grams= Ur milligrams * 0.001 grams/milligram * (52 weeks-[0.1*52 weeks]) /t weeks

From the above formula, U1000c grams was derived:

U1000c grams = Uy grams * 1000 chickens /(C * Nchickens).

C (number of cycles of production per year) was obtained from:

C = 1/(a years + [0.1 * a years]), where a is the expected age of depopulation of chickens. These

calculations assume a fixed downtime of 10% (i.e. time when the farm is not productive and

therefore neither chickens are produced nor antimicrobials are used). Estimates of usage (farm

prevalence of usage by farm and quantitative estimates) were calculated after adjusting for the

stratified study design by assigning a stratum-specific sampling weight to each observation unit

(farm). Standard errors were corrected to take into account potential similarities of usage

between farms in each stratum [18].

Risk factor analyses

Risk factor analyses for usage were carried out by fitting proportional odds model (ordinal

logistic model) [19] for the two outcomes describing total antimicrobial usage (i.e. usage in

relation to time, usage in relation to production), after adjusting for the stratified survey design.

Data on usage were categorised into three levels: no use; low level usage; high level usage. Low

and high level usage categories were determined from dividing the farms that had consumed

antimicrobials into two categories, based on the median quantity used. The following

explanatory variables were investigated: (1) farmer’s gender; (2) farmer’s age (years) (log); (3)

farmer’s highest educational attainment (four levels: ‘no formal education’, ‘primary school’,

‘secondary school’ and ‘higher’); (4) farmer’s experience in chicken farming (years) (log); (5)

number of chickens (log); (6) type of production (three levels: meat; layer; dual purpose); (7)

18

CHAPTER 2 density of chickens (chickens/sq. metre) in houses; (8) all-in-all-out production; (9) chickens lost

to disease over the previous 90 days; (10) presence of species other than chickens (pigs,

cattle/buffalo, or ducks) in the farm; and (11) district (Cho Gao, Chau Thanh, My Tho).

Candidate variables were those significant in the univariable models for any of the two outcomes

(p<0.05). Variables were ranked by their degree of significance and were included in the model

starting with the most significant ones using a step-wise forward approach [20]. In the final

multivariable model, variables were retained if their p-value was less than 0.05 for any of the two

outcome variables. All interactions between all significant variables in the model were assessed.

The suitability of each new variable included in the model was assessed using the AIC

information criterion [21]. All interactions between final significant variables were tested. All

statistical analyses were performed using R (packages ‘epicalc’, ‘epiR’, and ‘survey’)

(http://www.r-project.org).

Results

Antimicrobial usage in study farms

A total of 123 farms (59.1%) reported administration of at least one antimicrobial formulation. A

total of 168 administrations of an antimicrobial formulation were reported. A higher percentage

of owners of medium farms reported administering antimicrobials in their farms, compared with

owners of small farms (71.2% vs. 47.1%, respectively) (χ2= 11.5, p<0.001). Owners of small-to-

medium farms reported usage over a median of 140 days [56-224] (i.e. the median age of flocks

visited), whereas owners of household farms reported usage over a fixed period of 90 days

(Table 1). For 157/168 (95.7%) administrations the active ingredients (antimicrobial

compounds) could be accurately described, either by direct observation of the container, or by

farmer’s recollection. A total of 28 different antimicrobial compounds belonging to 10 classes

were identified (Table 2). A total of 100/157 administrations (63.7%) consisted of formulations

containing at least two antimicrobial classes (Table 3). After adjusting for the sampling frame,

polypeptides, tetracyclines, penicillins and aminoglycosides were the antimicrobials used by

most farms.

19

CHAPTER 2 Table 1. Number of antimicrobial formulations used by chicken farmers, stratified by farm size (Tien Giang province, Vietnam).

Household farms Small-to-medium farms

All farms (N=208) All

(N=104) Meat

(N=79) Mixed (N=25) All

(N=104) Meat

(N=40) Eggs

(N=63) No. of antimicrobial formulations

used 168 68 52 16 100 39 59

No. of farms that used antimicrobial formulations (%) 123

(59.1%) 49 (47.1%)

40 (50.6%)

9 (36.0%) 74

(71.2%) 30

(76.9%) 43

(68.2%) No. of different antimicrobial formulations used per farm

0 85 55 39 16 30 10 20 1 85 32 29 3 53 22 31 2 32 15 10 5 17 7 9 3 5 2 1 1 3 1 2 4 1 0 0 1 1

Median observation time per farm (days)[IQR] 90 [90-140] 90 [90-90] 90 [90-90] 90 [90-90] 140 [56-224] 49[28-70] 196 [157-280]

Table 2. Types of antimicrobials administered in 123 chicken farms, Tien Giang, Vietnam (2012-2013).

Class of antimicrobial Name of antimicrobial

No. (%) formulations administered

containing the antimicrobial (N=157)

(%)

Percent farms using antimicrobial (N=208) (%)

Adjusted % farms using antimicrobial (95% CI)

Tetracyclines Docycycline, 57 (36.3%) 52 (25.0%) 17.5 (16.9-18.1)

oxytetracycline,

tetracycline

Polypeptides Colistin 48 (30.6%) 39 (18.8%) 18.6 (9.9-27.3)

Macrolides Tylosin, tilmicosin, 40 (25.5%) 40 (19.2%) 9.7 (8.2-11.3)

erythromycin,

spiramycin

Penicillins Ampicillin, amoxicillin 41 (26.1%) 33 (15.9%) 11.3 (10.4-12.1)

Quinolones Flumequine, oxolinic 22 (14.0%) 19 (9.1%) 6.0 (0.1-12.1)

acid, norfloxacin,

enrofloxacin

Aminoglycosides Spectinomycin, 19 (12.1%) 19 (9.1%) 10.1 (8.0-12.1)

neomycine,

gentamicin,

apramycin,

streptomycin

Phenicols Florfenicol, 14 (8.9%) 13 (6.3%) 0.90 (0-2.5)

thiamphenicol

Sulphonamides/ Sulfamethoxazole, 12 (7.6%) 12 (5.8%) 6.1 (4.7-7.5)

trimethoprim sulphadimidine,

sulphadimetoxine,

sulphadimerazine,

trimethoprim

Lincosamides Lincomycin 4 (2.5%) 4 (1.9%) 4.3 (1.9-6.8)

Pleuromutilins Tiamulin 1 (0.6%) 1 (0.5%) 0.03 (0.01-0.05) CI=Confidence interval

20

CHAPTER 2 The most common antimicrobial formulations combining multiple antimicrobial classes included

penicillins and polypeptides (21% of all formulations) followed by macrolides plus tetracyclines

(15.9%). A total of 28/157 (17.8%) of products reported included a combination of an

antimicrobial considered to be bacteriostatic with another antimicrobial considered bactericidal

(Table 3). Formulations including bacteriostatic/bactericidal combinations included:

aminoglycosides combined with tetracyclines (i.e. gentamycin/doxcycyline,

neomycin/tetracycline) or polypeptides combined either with tetracyclines (i.e. colistin/

oxytetracyclin), sulphonamides (colistin/sulphadimethoxine); or macrolides (colistin/tylosin)

Antimicrobial formulations were administered in water on 137 (81.5%) occasions, followed by

both in feed and water (9.5%), and in feed only (4.2%). In 4.2% cases antimicrobial formulations

were injected. In 141 (84%) cases farmers reported that the antimicrobial formulation was

administered for prevention of disease (prophylaxis), and in 21 (12%) cases they were used

exclusively for therapeutic reasons (i.e. to treat disease). On 6 (3.8%) occasions farmers reported

using the antimicrobial formulation with a double purpose (both to prevent and treat). The most

commonly reported timing of use was: on arrival (34.4%) followed by periodic (28.7%) and

continuously (18.5%). The most common sources of advice with regards to antimicrobial

formulations used were: the drug seller (56%), the district veterinarian (18%), a friend/neighbour

(12%), a salesperson (12%), and ‘other’ (2%).

Household farms used 24.9 mg (SE ±7.91) of antimicrobial per chicken per week, compared

with 5.21 mg (SE ±0. 91) used by small-to-medium farms (Kruskal-Wallis test; p=0.014).

Likewise, household farms used greater amounts to produce 1,000 chickens, compared with

small-to-medium farms (543.4g, SE±223.4 vs. 172.8g, SE±25.2) (Kruskal-Wallis test; p=0.360).

After adjusting for the sampling frame, estimates of usage increased, since household farms in

the district of Chao Gao reported by far the highest levels of usage, and household farms in this

district had the greatest sampling weight (since they contained 46% of chickens of the study area

according to the census) (Table 4). The adjusted levels of usage of antimicrobial per week per

chicken and per 1,000 chickens (Uwc and U1000c) produced were, respectively 26.36 mg (SE

±3.54) and 690.4g (SE ±203.6). The model derived estimates of antimicrobial consumed per

1,000 meat and layer chickens produced were 470.4g (SE ±184.1) and 870.1g (SE ±263.9),

respectively (model derived p=0.325).

21

CHAPTER 2

Table 3. Combination of antimicrobials reported in 157 administrations of antimicrobial reported by 123 chicken farmers, Tien Giang province, Vietnam. The highlighted cells indicate a combination of a bacteriostatic and a bactericidal antimicrobial.

*One administration of a macrolide/tetracycline product included a polypeptide antimicrobial

Quantitative estimates of antimicrobial usage

Penicillins, lincosamides, quinolones, and sulphonamides/trimethoprim, were the four most

commonly antimicrobials consumed, with average Uwc values of 8.27mg, 5.20mg, 3.16mg and

2.78mg/week/chicken, and average U1000c values of 142.4g, 38.7g, 35.6g and 38.0g per 1,000

chickens produced (Figure 1).

Risk factors for antimicrobial usage

Results indicated a significantly higher prevalence of usage per unit time (Uwc) for farms

located in Cho Gao (OR=1.49) and Chau Thanh (OR=1.53) compared with My Tho (baseline,

Table 5). Male farmers used more antimicrobials per unit time (OR=2.02). Meat farms used

higher amounts of antimicrobial per unit time, compared with layer and dual purpose production

Peni

cilli

n

Poly

pept

ide

Mac

rolid

es

Tetra

cycl

ines

Qui

nolo

nes

Phen

icol

s

Am

inog

lyco

side

s

Sulp

hona

mid

es

Linc

osam

ides

Pleu

rom

utili

ns

Tota

l

No.

app

licat

ions

with

eac

h cl

ass o

f an

timic

robi

al

Penicillin 6 33

1 1

41 41

Polipeptides 2 2 5 1 1 3

14 48

Macrolides 3 25* 5 4

1 38 40

Tetracyclines 13 6 7

26 57

Quinolones 20 1

21 22

Phenicols 8

8 14

Aminoglycosides 1 1 3

5 19

Sulphonamides 3

3 12

Lincosamides 1

1 4

Pleuromutilin

0 1

Total

258

22

CHAPTER 2 (OR=1.40). All-in-all out systems (highly correlated with small-to-medium farms) had reduced

levels of usage per unit time compared with farms with continuous production (correlated with

household farms) (OR=0.68). No interactions were significant.

Table 4. Sampling weights and sampling fraction and administration of antimicrobials by in poultry farms belonging to each survey stratum, Tien Giang, Vietnam.

Stratum No. farms sampled

No. chickens sampled

No. chickens (census)

Fraction sampled (%)

Sampling weight

Milligrams of active compound

used per week per chicken (±SE)

Grams of active

compound per 1,000 chickens

produced

CG, hh 34 2,890 409,850 0.007 141.8 30.4 (±15.6) 901.2 (±622.8) CG, sm 34 47,970 128,250 0.374 2.7 5.3 (±1.5) 167.5 (±63.9) CT, hh 36 4,505 268,295 0.017 59.5 5.6 (±1.4) 327.8 (±122.4) CT, sm 36 50,230 56,700 0.886 1.1 18.6 (±7.2) 193.1 (±57.3) MT, hh 34 2,290 58,310 0.039 25.5 26.4 (±17.2) 413.8 (±256.4) MT, sm 34 52,500 73,300 0.716 1.4 4.7 (±1.9) 156.6 (±63.7)

All 208 160,385 994,705 0.161 15.1 (±4.0) 358.1 (±113.5)

CG=Cho Chao; CT=Chau Thanh; MT=My Tho; hh=household farms; sm=small-to-medium farms

Fig. 1A: Antimicrobial usage per week per chicken (milligrams of active compound) (both unadjusted and adjusted by the survey design), 208 chicken farms, Tien Giang, Vietnam

23

CHAPTER 2 Fig. 1B: Antimicrobial usage per 1000 chickens produced (grams of active compound) (unadjusted and adjusted by survey design), 208 chicken farms, Tien Giang, Vietnam

Key: PE, Penicillins; LI, Lincosamides; Q, Quinolones; S/T, Sulphonamides/trimethoprim; TE, Tetracyclines; PO, Polypeptides; AM, Aminoglycosides; MA, Macrolides; PH, Phenicols; PL, Pleuromutilins. Table 5. Results showing final multivariable proportional odds model (ordinal logistic model) investigating the outcomes: (i) antimicrobial usage per week per chicken (Uwc); and (ii) antimicrobial usage per 1000 chickens produced (U1000c). Only variables remaining significant in either model are kept. 208 chicken farms, Tien Giang, Vietnam

Usage per chicken per week (Uwc)

Usage per 1000 chickens produced (U1000c)

OR 95% CI P-value

OR 95% CI P-value

District (baseline=MyTho) 1.0

1.0 1.0

Cho Gao 1.49 1.42–1.55 <0.001

1.01 0.50–2.01 0.998

Chau Thanh 1.53 1.47–1.59 <0.001

1.22 0.61–2.45 0.575

Male farmer(baseline=Female) 2.02 1.53–2.61 <0.001

2.18 1.12–3.98 0.019

Meat production (baseline layer and ‘dual purpose’) 1.40 1.01–1.89 0.040

0.65 0.43–1.38 0.374

All-in-all-out 0.68 0.56–0.81 <0.001

0.76 0.39–1.23 0.211 OR, Odds ratio; CI, Confidence interval.

Discussion

To our knowledge this is the first study quantifying antimicrobial usage in chicken farms in

Vietnam. The key findings are: (1) An extensive range of antimicrobials compounds (28)

belonging to ten antimicrobial classes were used, including macrolides, quinolones, and

polypeptides; (2) A majority of antimicrobials (84%) were used to prevent, rather than to treat

clinical diseases of chickens; (3) Higher levels of usage (per unit time) were associated with

meat and household production systems.

24

CHAPTER 2 We estimated usage of antimicrobials for chicken production in the Mekong delta region from a

detailed survey of 208 farms in Tien Giang province. Although we believe that chicken

production systems are quite homogeneous across the Mekong delta, results must be interpreted

with caution given the limited geographical scope of our sample (i.e. three districts) and the

limited sample size. Even small recall errors on behalf of the farmers may have skewed the

results in unforeseen directions. In particular the reported higher usage (in quantitative terms) in

smaller farms may well reflect a recall bias of usage over an arbitrary period of 90 days. For

medium farms recall biases are likely to be less important, since the questionnaire gathered

information about ‘any antimicrobials used since restocking’, which is generally easier to

remember. Results reported here are likely to underestimate total antimicrobial usage, since

commercial feed commonly includes sub-therapeutic amounts of chlortetracycline and

bacitracin, among other antimicrobials. Unfortunately data on feed consumption were not

systematically collected.

Our results suggest that a total of 470.4mg of antimicrobials were used to produce one ‘meat’

chicken in the Mekong delta. These results contrast with data from other European countries

(2009), where sales ranged from 14mg/chicken produced (Norway) to 165 mg (Netherlands),

with an overall country average of 77.0 mg (SD=53.4) [2]. However it is important to highlight

that the average production cycles of meat chickens are longer in the Mekong Delta (20.2 weeks

SE±0.62 in our data set) compared with most developed countries (7-8 weeks). In addition, a

considerable proportion (24%) of farms in our dataset were ‘dual purpose’ systems, which (per

unit time) used less amount of antimicrobials compared with ‘specialised’ meat chicken farms.

Furthermore, after statistical adjustment quantitative estimates were much higher due to the

higher weight of observations from household farms in the district of Cho Gao. Household farms

(<200 chickens) represented 74% of the chicken census in our study population, a similar figure

for the whole of Vietnam (79% of chicken production). The observed higher levels of usage

among household farms may reflect either lack of technical ability to administer antimicrobials

correctly, or a higher perception of risk of disease by household farm owners. This suggests that

training of household farmers on the correct administration of antimicrobials would be an

effective strategy aiming at reducing overall antimicrobial usage on poultry farms.

25

CHAPTER 2 Results from the study have highlighted important discrepancies between qualitative and

quantitative estimates of usage. For example, polypeptides, tetracyclines, penicillins and

aminoglycosides were the most commonly used antimicrobials in terms of reported usage by

farms; however penicillins, lincolsamides, quinolones and sulphonamides/trimethoprim were

used more in quantitative terms. Differences in the doses and concentration of active principles

of the different antimicrobials used may explain these differences. There were also some

differences in the quantitative assessment of antimicrobial usage, depending on the chosen

estimate. For example, lincosamides ranked second to penicillins in terms of ‘usage per unit

time’ (Uwc) (19.7% of total usage), but third in terms of usage per chicken produced (U1000c)

(11.1% of total usage). The reason for these discrepancies lie in the variable levels of usage of

antimicrobials in different production systems. Antimicrobials used with similar intensity (per

unit time) in layer and meat flocks, will result in overall higher estimates of usage per 1,000

chickens, compared with antimicrobials used more commonly in meat flocks, since layer flocks

have a longer lifespan. In particular lincosamides were administered to relatively few layer

flocks (data not shown).

Most of the reported antimicrobial usage was ‘prophylactic’, that is in the absence of clinical

disease, to prevent infection. This explains why the variable ‘chickens lost to disease in the last

three months’ was not associated with higher usage in our risk analyses. Our results contrast

with studies in chicken farms in Europe and Africa where usage was largely explained by history

of disease in the flocks a response to disease [22, 23].

Quinolones and macrolides, both listed by the World Health Organization as antimicrobials

‘critically important for human medicine’ [24], represented 15.8% (per unit time) and 11.0%

(per chicken produced) of overall antimicrobial usage. Neither the use of glycopeptides nor

cephalosporins were reported in our study, although avoparcin (a glycopeptide) is sometimes

used in feed, and ceftiofur and cefquinome (third/fourth generation cephalosporins) are currently

licenced for animal production in Vietnam [25]. Polypeptides (colistin) were the second most

commonly used antimicrobials, and represented 4-7% of all usage in quantitative terms in our

study, compared with 1.6% reported from nine European countries [2]. This is a concern since

colistin is a very valuable to treat serious nosocomial infections caused by multidrug-resistant

26

CHAPTER 2 gram-negative bacteria such as Pseudomonas aeruginosa and Acinetobacter baumannii in

humans [26].

The finding that female farmers used less antimicrobials merits further investigation, and

suggests that cultural factors may also explain behaviour related to antimicrobial usage on

farms. In our study females accounted for 35% of all farmers.

In Vietnam chicken production represents only a small fraction of total animal production, fish

and pork being more common animal protein sources [27]. Usage of antimicrobials in

Vietnamese aquaculture has been reported to be high compared with most other countries (700 g

per tonne of production, compared to 1-200 g per tonne in three European countries, Canada and

Chile) [28]. In order to provide an accurate estimate of the selective pressure for antimicrobial

resistance in each species, it would be important to determine the comparative levels of usage in

all relevant types of animal production, as well as in humans, as has been recommended

internationally [29, 30]. Quantitative data on antimicrobial usage on chicken farms should ideally

be complemented with surveillance of antimicrobial resistance of selected bacterial species both

in main farmed species, food and humans. This should allow accurate monitoring of potential

reductions in use and resistance in animal production as well as in humans.

References

1. Anonymous. WHO Global Principles for the Containment of Antimicrobial Resistance in Animals Intended for Food. WHO, Geneva. 2000; Available from: http://www.who.int/foodsafety/publications/containment-amr/en/.

2. Anonymous. Trends in the sales of veterinary antimicrobial agents in nine European countries (2005-2009). European Medicines Agency. 2011; Available from: http://www.ema.europa.eu/docs/en_GB/document_library/Report/2011/09/WC500112309.pdf.

3. Katsuda, K., et al., Antimicrobial resistance and genetic characterization of fluoroquinolone-resistant Mannheimia haemolytica isolates from cattle with bovine pneumonia. Vet Microbiol, 2009. 139(1-2): p. 74-9.

4. Pitkala, A., et al., Bovine mastitis in Finland 2001-prevalence, distribution of bacteria, and antimicrobial resistance. J Dairy Sci, 2004. 87(8): p. 2433-41.

5. Wissing, A., J. Nicolet, and P. Boerlin, The current antimicrobial resistance situation in Swiss veterinary medicine. Schweiz Arch Tierheilkd, 2001. 143(10): p. 503-10.

6. Silbergeld, E.K., J. Graham, and L.B. Price, Industrial food animal production, antimicrobial resistance, and human health. Annu Rev Public Health, 2008. 29: p. 151-69.

7. Pagel, S.W. and P. Gautier, Use of antimicrobial agents in livestock. Rev Sci Tech, 2012. 31(1): p. 145-88. 8. Aarestrup, F.M. and H.C. Wegener, The effects of antibiotic usage in food animals on the development of

antimicrobial resistance of importance for humans in Campylobacter and Escherichia coli. Microbes Infect, 1999. 1(8): p. 639-44.

9. Carrique-Mas, J.J., et al., An epidemiological investigation of Campylobacter in pig and poultry farms in the Mekong delta of Vietnam. Epidemiol Infect, 2014. 142(7): p. 1425-36.

27

CHAPTER 2 10. Garin, B., et al., Prevalence, quantification and antimicrobial resistance of Campylobacter spp. on chicken

neck-skins at points of slaughter in 5 major cities located on 4 continents. Int J Food Microbiol, 2012. 157(1): p. 102-7.

11. Thai, T.H., et al., Antimicrobial resistance of Salmonella serovars isolated from beef at retail markets in the north Vietnam. J Vet Med Sci, 2012. 74(9): p. 1163-9.

12. Thai, T.H., et al., Antibiotic resistance profiles of Salmonella serovars isolated from retail pork and chicken meat in North Vietnam. Int J Food Microbiol, 2012. 156(2): p. 147-51.

13. Thai, T.H., et al., Antimicrobial resistance in Salmonella serovars isolated from meat shops at the markets in North Vietnam. Foodborne Pathog Dis, 2012. 9(11): p. 986-91.

14. Thai, T.H. and R. Yamaguchi, Molecular characterization of antibiotic-resistant Salmonella isolates from retail meat from markets in Northern Vietnam. J Food Prot, 2012. 75(9): p. 1709-14.

15. Van, T.T., et al., Safety of raw meat and shellfish in Vietnam: an analysis of Escherichia coli isolations for antibiotic resistance and virulence genes. Int J Food Microbiol, 2008. 124(3): p. 217-23.

16. Anonymous. Situation Analysis: Antibiotic use and resistance in Vietnam. In: E. a. P. Center for Disease Dynamics (ed.). Center for Disease Dynamics, Economics and Policy, Washington DC. 2010; Available from: http://www.cddep.org/publications/situation_analysis_antibiotic_use_and_resistance_vietnam#sthash.YWpTVblU.dpbs.

17. Dang, S.T., et al., Impact of medicated feed on the development of antimicrobial resistance in bacteria at integrated pig-fish farms in Vietnam. Appl Environ Microbiol, 2011. 77(13): p. 4494-8.

18. Dohoo, I., S. Martin, and H. Stryhn, Veterinary Epidemiologic Research. 1st edn ed. 2003, Charlottetown, Canada: AVC Inc.

19. McCullagh, P., Regression models for ordinal data. J. R. Stat. Soc., 1980(42): p. 109-142. 20. Hosmer, D. and S. Lemeshow, Applied logistic regression. 1st Edn ed. 1989: Jonh Wiley and Sons, New

York. 21. Thrusfield, M., Veterinary Epidemiology. 2007: Blackwell Publishing, Oxford. 22. Hughes, L., P. Hermans, and K. Morgan, Risk factors for the use of prescription antibiotics on UK broiler

farms. J Antimicrob Chemother, 2008. 61(4): p. 947-52. 23. Mitema, E.S., et al., An assessment of antimicrobial consumption in food producing animals in Kenya. J

Vet Pharmacol Ther, 2001. 24(6): p. 385-90. 24. Anonymous. Critically important antimicrobials for human medicine. 3rd revision (2011). World Health

Organization, Geneva. 2011; Available from: http://apps.who.int/iris/bitstream/10665/77376/1/9789241504485_eng.pdf.

25. Anonymous. List of antimicrobials authorized in agriculture. Ministry of Agriculture, Hanoi, Vietnam. 2013; Available from: http://vanban.chinhphu.vn/portal/page/portal/chinhphu/hethongvanban?class_id=1&mode=detail&document_id=168233.

26. Kadar, B., et al., The renaissance of polymyxins. Curr Med Chem, 2013. 20(30): p. 3759-73. 27. Anonymous. Review of the livestock sector in the Mekong countries. FAO, Rome. 2004; Available from:

http://www.fao.org/ag/againfo/resources/es/publications/sector_reports/lsr_mekong.pdf. 28. Smith, P., Antimicrobial resistance in aquaculture. Rev Sci Tech, 2008. 27(1): p. 243-64. 29. Anonymous. Second Joint FAO/OIE/WHO Expert Workshop on Non-Human Antimicrobial Usage and

Antimicrobial Resistance (AMR). Management options. Oslo, Norway. 2004; Available from: https://www.oie.int/doc/ged/D895.PDF.

30. Anonymous. Critically important antimicrobials for human medicine: categorization for the development of risk management strategies to contain antimicrobial resistance due to non-human antimicrobial use : report of the second WHO Expert Meeting, Copenhagen. 2007; Available from: http://apps.who.int/iris/bitstream/10665/43765/1/9789241595742_eng.pdf

28

CHAPTER 3 NON-TYPHOIDAL SALMONELLA COLONIZATION IN CHICKENS AND

HUMANS IN THE MEKONG DELTA OF VIETNAM

CHAPTER 3

Chapter 3: Non-typhoidal Salmonella colonization in chickens and humans in the Mekong delta of Vietnam

N. V. Trung1,2,3, J. J. Carrique-Mas3,4, N. H. Nghia3, L. T. P. Tu3, H. H. Mai5, H. T. Tuyen3, J. Campbell3,4, N. T. Nhung3, H. N. Nhung3, P. V. Minh3, T. T. B. Chieu3, T. Q. Hieu5, N. T. N. Mai6, S. Baker3,4, J. A. Wagenaar7,8, N. T. Hoa3,4 and C. Schultsz1,2,3

1 Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands

2 Department of Global Health-Amsterdam Institute for Global Health and Development, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands

3 Oxford University Clinical Research Unit, Centre for Tropical Medicine, Ho Chi Minh City, Vietnam

4 Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, UK

5 Sub-Department of Animal Health, My Tho, Tien Giang, Vietnam

6 Preventive Medicine Center, Tien Giang, Vietnam

7 Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands

8 Central Veterinary Institute of Wageningen UR, Lelystad, The Netherlands

Zoonoses and Public Health, 2017 (64) 94–99

30

CHAPTER 3

Abstract

Salmonellosis is a public health concern both in the developed and developing countries.

Although the majority of human non-typhoidal Salmonella enterica (NTS) cases are the result of

foodborne infections or person-to-person transmission, NTS infections may also be acquired by

environmental and occupational exposure to animals. While a considerable number of studies

have investigated the presence of NTS in farm animals and meat/carcasses, very few studies

have investigated the risk of NTS colonization in humans as a result of direct animal exposure.

We investigated asymptomatic NTS colonization in 204 backyard chicken farms, 204 farmers

and 306 matched individuals not exposed to chicken farming, in southern Vietnam. Pooled

chicken faeces, collected using boot- or handheld-swabs on backyard chicken farms, and rectal

swabs from human participants were tested. NTS colonization prevalence was 45.6%, 4.4% and

2.6% for chicken farms, farmers and unexposed individuals, respectively. Our study observed a

higher prevalence of NTS colonization among chicken farmers (4.4%) compared with age-, sex-

and location- matched rural and urban individuals not exposed to chickens (2.9% and 2.0%). A

total of 164 chicken NTS strains and 17 human NTS strains were isolated and 28 serovars were

identified. Salmonella Weltevreden was the predominant serovar in both chickens and humans.

NTS isolates showed resistance (20-40%) against tetracycline, chloramphenicol,

sulfamethoxazole-trimethoprim and ampicillin. Our study reflects the epidemiology of NTS

colonization in chickens and humans in the Mekong delta of Vietnam and emphasizes the need

of larger, preferably longitudinal studies to study the transmission dynamics of NTS between and

within animal and human host populations.

Keywords: Non-typhoidal Salmonella, colonization, antimicrobial resistance, chickens, humans,

Vietnam

31

CHAPTER 3

Introduction

Salmonellosis caused by non-typhoidal Salmonella enterica (NTS) is a potentially zoonotic

infection commonly associated with gastroenteritis and represents a significant public health

problem both in the developing and developed countries [1].

Although the majority of human NTS cases is the result of foodborne infection [2] or person-to-

person transmission [3], humans can also become infected with NTS as a result of environmental

and occupational exposure to animals, including farm animals [4-6]. This type of exposure is

particular prevalent in developing countries, where a large fraction of the population is involved

in raising livestock and/or poultry. Farms in these countries are typically backyard or small-scale

and farming procedures mostly involve low levels of biosecurity and personal protection. This

results in very close contact between animals and humans. To date, very few studies have

investigated the role of exposure to farm animals in asymptomatic NTS infection.

We hypothesized that exposure to chickens through farming results in increased risk of

asymptomatic colonisation with NTS in Vietnam, a country with a majority of rural population.

In this country, small and backyard chicken farming is very common, with most farms typically

having less than 50 chickens [7]. To investigate this hypothesis, we investigated chicken flocks

and farmers to study the prevalence and serovar distribution of NTS organisms. The prevalence

in farmers was compared with that among age- and gender-matched individuals living in the

same areas but not engaged in poultry farming. In addition, given the extensive antimicrobial

drug usage in these chicken farms [8], we analysed and compared the frequencies of resistance

against key antimicrobial drugs of the most relevant classes, used both in veterinary and human

medicine.

32

CHAPTER 3 Materials and Methods

Study population

The target population consisted of chicken farms, including chicken flocks and their farmers, as

well as individuals not involved in poultry farming from 2 rural districts and the capital of the

Mekong Delta province of Tien Giang (Vietnam).

Sampling of farms was conducted at random within two size strata: 10–200 chickens (‘household

farms’, N=102), and 201–2,000 chickens (‘small farms’, N=102). In selected farms, both flocks

and the person responsible for raising the chickens (‘farmer’, N=204) were recruited. In addition

to the 204 farmers, 306 participants not involved in chicken or livestock farming were randomly

selected (‘unexposed individuals’). A subgroup of unexposed individuals (‘rural subjects’) were

selected from the same commune as the farmer, and were matched to the farmer by age and

gender (N=204, one per farmer). Another subgroup of unexposed individuals (‘urban subjects’)

were selected from the provincial capital, and were matched to the farmers by age and gender

(N=102, one every two farmers).

Farm selection and chicken flock sampling was carried out by staff at the Sub-Department of

Animal Health (SDAH) in Tien Giang. Selection and sampling of human subjects was performed

from the population census provided by the Preventive Medicine Centre (PMC) of Tien Giang

[9].

Written informed consents were obtained from all participants prior to participation in the study.

Participants that refused to participate were replaced by the next available eligible participant.

The study was approved by the Peoples’ Committee of Tien Giang Province, the Department of

Health in Tien Giang and the Oxford University Tropical Research Ethics Committee (OxTREC,

No. 48/11).

Sample collection

Farm and human household visits were evenly distributed over a year period from March 2012 to

April 2013 in order to avoid seasonal effects. Pooled chicken faeces samples were collected from

chicken houses using boot swabs (flocks reared on barn systems) or handheld gauze swabs

33

CHAPTER 3 (caged layer flocks and flocks on stilted mesh houses) as described previously [10]. The sample

collection was conducted by a trained sampling team from Tien Giang SDAH.

Rectal swab samples were obtained from all human participants by trained staff from Tien Giang

PMC, using Fecalswab (Copan, Italy).

All samples were stored at 4oC, transported to the laboratory at the Oxford University Clinical

Research Unit in Ho Chi Minh City and cultured within 24 hours after sample collection.

Laboratory methods

Salmonella was isolated using the modification of the ISO 6579:2002 (Annex D) method for

chicken faecal samples, involving: (a) pre-enrichment in 225 ml of buffered peptone water

(BPW) (37°C, 18 hours); (b) plating 100 l of the pre-enriched culture onto modified semi-solid

Rappaport–Vassiliadis medium (Oxoid; UK) (41°C, 24 hours) and (c) plating onto Rambach

agar (37°C, 24 hours) [11]. For human samples, rectal swabs were cultured on MacConkey agar,

xylose-lysinedeoxycholate agar and selenite broth according to guidelines of World Health

Organization [12].

Suspected NTS colonies were selected for each sample and confirmed by slide agglutination

with relevant poly O antiserum [13]. All isolates confirmed as NTS were further tested for their

antimicrobial susceptibility.

Antimicrobial susceptibility testing was performed by disc diffusion method and breakpoints

were interpreted using the Clinical and Laboratory Standards Institute guidelines for

Enterobacteriaceae [14]. Eleven antimicrobials were tested including chloramphenicol (30 mg),

ceftazidime (30 mg), ceftriaxone (30 mg), amoxicillin/clavulanic acid (30 mg), meropenem (10

mg), ciprofloxacin (5 mg), tetracycline (30 mg), trimethoprim/sulfamethoxazole (1.25/23.75

mg), amikacin (30 mg), gentamicin (10 mg) and ampicillin (10 mg). Quality controls for

susceptibility testing and identification were performed every week according to the CLSI

guidelines. An MDR strain was defined as a strain resistant to at least three different

antimicrobial classes. Chicken farms and farmers were the study unit of analysis. A chicken farm

was defined as ‘positive’ for NTS if NTS was isolated from at least one of the boot- or handheld

gauze swabs.

34

CHAPTER 3 Confirmed NTS isolates were genotyped using multilocus sequence typing (MLST) as described

previously [15]. Briefly, pure colonies of overnight culture on nutrition agar were subjected to

DNA extraction using Wizard Genomic DNA extraction kit (Promega, USA). Seven MLST loci

(aroC, dnaN, hemD, hisD, purE, sucA and thrA) were amplified and sequenced in forward and

reverse directions using the Big Dye Cycle Sequencing kit (Applied Biosystems, USA) on an

ABI 3770 automatic sequencer according to the manufacturer’s instructions. Sequence data of

seven loci was trimmed and blasted to determine sequence type as well as serotype based on data

available on the MLST database ((http://mlst. warwick.ac.uk/mlst/dbs/Senterica/)

Differences in proportions were compared using the Chi-square test and the Fisher's Exact Test,

when the Chi-square test was not relevant. A p-value <0.05 was considered statistically

significant.

Results

Of 204 chicken farms, 93 (45.6%, 95% CI= 38.8–52.4%) tested positive for NTS. There was no

statistically significant difference in the NTS farm-level prevalence between household farms

(46/102, 45.1%) and small farms (47/102, 46.1%). NTS was recovered from 9 chicken farmers

(4.4%, 95% CI= 1.6–7.2%), 6 rural subjects (2.9%, 95% CI= 0.6–5.3%) and 2 urban subjects

(2.0%, 95% CI= 0.0–4.7%). The prevalence of NTS did not statistically differ between chicken

farmers and unexposed individuals. The prevalence of NTS among farmers of NTS-positive

chicken flocks (5/93, 5.4%; 95% CI= 0.8–10.0%) was similar to the prevalence of NTS among

farmers of NTS-negative chicken flocks (4/111, 3.6%; 95% CI= 0.1–7.1%).

Among 164 chicken NTS isolates, the highest observed levels of resistance were against

tetracycline (39.6%), chloramphenicol (28.0%), sulfamethoxazole-trimethoprim (26.8%),

ampicillin (26.2%) and amoxicillin plus clavulanic acid (12.8%). The proportion of strains

resistant against ciprofloxacin and gentamicin was 1.8%. No resistance against meropenem,

ceftazidime and ceftriaxone was observed. A total of 9 NTS isolates from farmers and 8 NTS

isolates from individuals unexposed to chicken farming were tested for antimicrobial resistance,

which indicated similar levels of resistance against all tested antimicrobials. 27.4% (45/164),

22.2% (2/9) and 12.5% (1/8) of NTS isolates from chickens, farmers and unexposed individuals

were multidrug resistant, respectively (Figure 1). Interestingly, one of the two multidrug resistant

35

CHAPTER 3 isolates from farmers was identical to the most common resistance pattern found in chicken

flocks (chloramphenicol – ampicillin – tetracycline – trimethoprim/sulfamethoxazole) (Data not

shown).

Figure 1: Percentage of NTS isolates resistant to a panel of 11 antimicrobials

C: chloramphenicol (30µg), CAZ: ceftazidime (30µg), CRO: ceftriaxone (30µg), AMC: amoxicilin/clavulanic acid (30 µg), MEM: meropenem (10µg), CIP: ciprofloxacin (5µg), TE: tetracycline (30µg), SXT: trimethoprim-sulphamethoxazole (10µg), AK: amikacin (30µg), CN: gentamicin (10µg), AMP: ampicillin (10µg), MDR: Multidrug resistance (resistant against at least three classes of antimicrobial).

MLST was performed on 163/164 chicken isolates from 93 chicken farms (one isolate could not

be recovered after storage) and on all 17 isolates from humans. Salmonella Weltevreden was the

most common serovar detected in chicken farms (10.3% of farms), farmers (2.0%), rural subjects

(1.0%) and urban subjects (2.0%). Besides Salmonella Weltevreden, the predominant serovars in

chickens were Salmonella Enteritidis, Salmonella Paratyphi B var Java monophasic, Salmonella

Albany, Salmonella Derby, Salmonella Give, Salmonella Newport and Salmonella

Typhimurium. Salmonella Enteritidis and Salmonella Typhimurium were only found in chickens

and were detected in 4.4% and 1.5% of the chicken farms, respectively (Table 1).

NTS were detected both in chickens and farmers on 5/204 farms (2.5%, 95% CI= 0.3-4.6%).

MLST revealed that the serovar of NTS isolates obtained from the farmer and their chicken on

the same farm were identical in one farm (Salmonella Weltevreden), but differed between farmer

and their chickens for the other 4 farms (Table 2).

36

CHAPTER 3 Table 1. Distribution of different serovars of NTS isolated from chickens and humans in southern Vietnam. No. culture positive (%) NTS serovar Chicken farmsa (n=204) Chicken farmers

(n=204) Rural subjects (n=204) Urban subjects (n=102)

Weltevreden 21 (10.3) 4 (2.0) 2 (1.0) 2 (2.0) Enteritidis 9 (4.4) 0 0 0 Paratyphi B var Java monophasic 9 (4.4) 0 0 0 Albany 7 (3.4) 0 0 0 Derby 6 (2.9) 0 1 (0.5) 0 Give 6 (2.9) 2 (1.0) 0 0 Newport 4 (2.0) 0 1 (0.5) 0 Typhimurium 3 (1.5) 0 0 0 Braenderup 1 (0.5) 1 (0.5) 0 0 Orientalis 0 1 (0.5) 0 0 Rubislaw 0 1 (0.5) 0 0 Ohio 0 0 1 (0.5) 0 Other serovarsb 28 (13.7) 0 0 0 Untypeable 19 (9.3) 0 0 0 Any serovar 93 (45.6) 9 (4.4) 6 (2.9) 2 (2.0)

aOn 19 farms, multiple serovars were present. bOther serovars: Anatum, Senftenberg, Stanley, Virchow (each serovar was present on 3 farms); Kentucky, London, Montevideo, Typhimurium monophasic (each serovar was present on 2 farms); Cerro, Indian, Litchfield, Mbandaka, Meleagridis, Oslo, Poona, Tennessee (each serovar was present on one farm).

Table 2. Serovar and antimicrobial resistance pattern of NTS isolated from chicken flocks and farmers from the same farm. Farm ID Source Isolate number Salmonella serovar Antimicrobial resistance patterna

CG 37 Farmer 1 Weltevreden Fully susceptible Chicken 1 Untypeable Fully susceptible

CT 67 Farmer 1 Rubislaw C-AMC-TE-AMP Chicken 1 Albany Fully susceptible

MT 26 Farmer 1 Weltevreden Fully susceptible Chicken 1 Weltevreden Fully susceptible Chicken 2 Weltevreden Fully susceptible

MT 28 Farmer 1 Give C-TE-SXT-AMP Chicken 2 Enteritidis TE

MT 53 Farmer 1 Weltevreden Fully susceptible Chicken 1 Senftenberg CIP-TE-SXT Chicken 2 Senftenberg Fully susceptible Chicken 3 Cerro Fully susceptible

a Isolates were tested for susceptibility to 11 antimicrobials using disk diffusion method and interpreted according to breakpoints as defined by Clinical and Laboratory Standard Institute (11). C: chloramphenicol (30µg), AMC: amoxicillin/clavulanic acid (30 µg), CIP: ciprofloxacin (5µg), TE: tetracycline (30µg), SXT: trimethoprim-sulphamethoxazole (10µg), AMP: ampicillin (10µg).

37

CHAPTER 3 Discussion

To our knowledge, this is the first field survey reporting on prevalence of asymptomatic NTS

colonization in humans occupationally exposed and unexposed to chickens in Vietnam. The

observed prevalence of asymptomatic NTS colonization in humans was 3.3%, a figure

considerably higher than the reported prevalence of asymptomatic NTS in developed countries

(0.3% – 0.4%) [16-18]. However, our results were similar to the results from a study performed

in 2004 in Hanoi, Vietnam (3.1%) [19] and from Thailand in 2003 (4.7%) [20].

We found a higher prevalence of NTS colonization among chicken farmers (4.4%) compared

with unexposed individuals (2.6%). The prevalence of NTS colonization in the rural subjects was

also higher (2.9%) than in the urban subjects (2.0%). Similarly, farmers of NTS-positive chicken

flocks had a higher prevalence of infection compared with farmers of NTS-negative chicken

flocks (5.4% versus 3.6%). However, none of these differences were statistically significant.

Our study demonstrated a high prevalence (45.6%) and high diversity of NTS serovars in both

household-size and small-size chicken farms in the Mekong Delta of Vietnam, similar to the

results from a recent survey (64.7%) carried out in Dong Thap, another Mekong Delta province

[21]. In unconfined flocks, swabs may potentially gathered faecal material from other animals in

the farm. However, in those cases, sampling was carried out near the perching and eating areas

where chicken droppings were visible, so it is expected that the overwhelming majority of faecal

material and Salmonella strains were of chicken origin. In terms of antimicrobial sensitivity,

multidrug resistance was commonly observed in the chicken NTS isolates. Of antimicrobials of

critical importance, the prevalence of resistance against ampicillin was particularly high among

tested isolates (26.2%). However, levels of resistance against aminoglycosides (gentamicin) and

fluoroquinolones (ciprofloxacin) were low (<2%).

We acknowledge several limitations in our study. Firstly, the number of NTS isolates from

humans was small, limiting the power to demonstrate any statistical difference between study

cohorts. Secondly, the cross-sectional study design may preclude the demonstration of

transmission of any particular serovar, which is highly depending on the dynamics of NTS

transmission between chickens and humans. It is therefore possible that the presence of NTS in

the farmer results from earlier infection and further clearance in the current chicken flock, or

38

CHAPTER 3 from transmission from a previous flock. In addition, differences in NTS isolation methods for

chicken and human samples may have had an impact on the sensitivity of detection. A higher

sensitivity of detection of the ISO 6572: 2002 (Annex D) method compared with the WHO

method for human samples is to be expected, since the former include a pre-enrichment,

selective enrichment phase, which allows the detection of low numbers of Salmonella such as

those likely to be found in asymptomatic chicken samples [22].

In spite of these limitations, we found that 1/21 (4.7%) of the farmers with Salmonella

Weltevreden infected chicken flocks was also Salmonella Weltevreden positive compared with

3/183 (1.6%) of the farmers without Salmonella Weltevreden infected chicken flocks.

Interestingly, the Salmonella Weltevreden isolated from the farmer had an identical antimicrobial

resistance pattern to the isolate from his/her chickens (fully susceptible). It has been suggested

that Salmonella Weltevreden may have acquired properties which facilitate adaptation to a

broader range of hosts [23], and Salmonella Weltevreden has been shown to be able to persist in

manure and soil for prolonged periods of time [24].

We believe that our study reflects the epidemiological situation of NTS in the Mekong delta of

Vietnam, characterized by a high prevalence of infection in chicken flocks and a relatively high

prevalence of colonization of human adults. Our study also underscores the need for additional

larger and preferably longitudinal studies to investigate transmission dynamics of NTS between

and within animal and human host populations.

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18. Nataro, J.P., et al., Diarrheagenic Escherichia coli infection in Baltimore, Maryland, and New Haven, Connecticut. Clin Infect Dis, 2006. 43(4): p. 402-7.

19. Do, T.T., et al., Epidemiology and aetiology of diarrhoeal diseases in adults engaged in wastewater-fed agriculture and aquaculture in Hanoi, Vietnam. Trop Med Int Health, 2007. 12 Suppl 2: p. 23-33.

20. Sirinavin, S., L. Pokawattana, and A. Bangtrakulnondh, Duration of nontyphoidal Salmonella carriage in asymptomatic adults. Clin Infect Dis, 2004. 38(11): p. 1644-5.

21. Tu, L.T., et al., High levels of contamination and antimicrobial-resistant non-typhoidal Salmonella serovars on pig and poultry farms in the Mekong Delta of Vietnam. Epidemiol Infect, 2015: p. 1-13.

22. Carrique-Mas, J.J. and R.H. Davies, Sampling and bacteriological detection of Salmonella in poultry and poultry premises: a review. Rev Sci Tech, 2008. 27(3): p. 665-77.

23. Brankatschk, K., et al., Comparative genomic analysis of Salmonella enterica subsp. enterica serovar Weltevreden foodborne strains with other serovars. Int J Food Microbiol, 2012. 155(3): p. 247-56.

24. Arthurson, V., A. Sessitsch, and L. Jaderlund, Persistence and spread of Salmonella enterica serovar Weltevreden in soil and on spinach plants. FEMS Microbiol Lett, 2011. 314(1): p. 67-74.

40

CHAPTER 4 PREVALENCE AND RISK FACTORS FOR CARRIAGE OF

ANTIMICROBIAL RESISTANT ESCHERICHIA COLI ON HOUSEHOLD AND SMALL-SCALE CHICKEN FARMS IN THE MEKONG DELTA OF

VIETNAM

CHAPTER 4

Chapter 4: Prevalence and risk factors for carriage of antimicrobial-resistant Escherichia coli on household and small-scale chicken farms in the Mekong delta of Vietnam Nguyen Vinh Trung1–3*, Juan J. Carrique-Mas3,4, Ngo Thi Hoa3,4, Ho Huynh Mai5, Ha Thanh Tuyen3, James I. Campbell3,4, Nguyen Thi Nhung3, Hoang Ngoc Nhung3, Pham Van Minh3, Jaap A. Wagenaar6,7, Anita Hardon8, Thai Quoc Hieu5 and Constance Schultsz1–3 1 Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. 2 Department of Global Health-Amsterdam Institute for Global Health and Development, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. 3 Oxford University Clinical Research Unit, Centre for Tropical Medicine, Ho Chi Minh City, Vietnam. 4 Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, UK. 5 Sub-Department of Animal Health, My Tho, Tien Giang, Vietnam. 6 Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands. 7 Central Veterinary Institute of Wageningen UR, Lelystad, The Netherlands. 8 Center for Social Science and Global Health, University of Amsterdam, Amsterdam, The Netherlands

J. Antimicrob. Chemother. 2015 (70) 2144-2152

42

CHAPTER 4 Abstract

Objectives

To describe the prevalence of antimicrobial resistance (AMR) among commensal Escherichia

coli isolates in household and small-scale chicken farms common in southern Vietnam and to

investigate the association of AMR with farming practices and antimicrobial usage.

Methods

We collected data on farming and antimicrobial usage from 208 chicken farms. E. coli was

isolated from boot swab samples using MacConkey agar (MA) and MA with ceftazidime,

nalidixic acid or gentamicin. Isolates were tested for their susceptibility against 11 antimicrobials

and for extended spectrum β-lactamase production. Risk factor analyses were carried out using

logistic regression, at both bacterial population and farm level.

Results

E. coli resistant against gentamicin, ciprofloxacin, and 3rd-generation cephalosporins was

detected in 201 (96.6%), 191 (91.8%) and 77 (37.0%) of the farms, respectively. Of 895 E. coli

isolates, resistance against gentamicin, ciprofloxacin, and 3rd-generation cephalosporins was

detected in 178 (19.9%), 291 (32.5%) and 29 (3.2%) of the isolates, respectively. Ciprofloxacin

resistance was significantly associated with quinolone (OR=2.26) and tetracycline usage

(OR=1.70). ESBL-producing E. coli were associated with farms containing fish ponds

(OR=4.82).

Conclusions

Household and small farms showed frequent antimicrobial usage associated with high prevalence

of resistance against the most commonly used antimicrobials. Given the weak bio-containment,

the high prevalence of resistant E. coli could represent a risk to the environment and humans.

Keywords: antimicrobial use, antimicrobial resistance, poultry, treatment incidence

43

CHAPTER 4 Introduction

Antimicrobials are extensively used in animal farming with the aim to treat and prevent animal

diseases, as well as to improve growth performance [1]. The overuse of antimicrobials in food

animal farming is an important factor contributing to the emergence and dissemination of

antimicrobial-resistant organisms in animal production systems, and contributes at an unknown

level to the overall problem of antimicrobial resistance (AMR) in human medicine [2]. The use

of fluoroquinolones, aminoglycosides and 3rd-generation cephalosporins in animal farming is of

particular concern, since these are among the most important antimicrobials currently available

to treat serious human infections [3].

Commensal Escherichia coli organisms are commonly used to monitor AMR prevalence in

livestock and poultry, since they reflect well the selective pressure on Gram-negative enteric

bacteria [4, 5] AMR determinants present in E. coli that are selected or amplified in farms may

spread to humans either through direct contact, consumption of meat, or indirectly through

environmental pathways [6]. Furthermore, some animal-derived E. coli strains can also be

pathogenic to humans, or may act as a donor of AMR genes to other pathogenic

Enterobacteriaceae [7, 8].

A number of studies has demonstrated an overall higher prevalence of AMR among chicken E.

coli compared to human isolates [7, 9] and have incriminated chickens as a source of

fluoroquinolone-resistant, extra-intestinal pathogenic E. coli infections in humans [7, 10].

Because of this, the recently observed increase in plasmid-mediated resistance against

fluoroquinolones among E. coli of chicken origin is of concern [5, 11]. Human infections with

micro-organism resistant against 3rd and 4th-generation cephalosporins due to the acquisition of

extended spectrum β-lactamase genes have increased rapidly worldwide since they were first

described in 1989. Recent reports have shown the presence of ESBL-producing E. coli in poultry

[12-14] and a great level of molecular similarity between ESBL-producing E. coli from chicken

meat and humans, suggesting that chickens are a major source [15-17]. A rise in aminoglycoside

resistance in Gram-negative micro-organism has been described in European and Asian countries

[18]. In Vietnam antimicrobials including fluoroquinolones and aminoglycosides are extensively

used in large scale pig and poultry farming [19-21] and a high prevalence of AMR against both

classes of antimicrobials has been observed both in commensal and zoonotic bacteria from farms

and meat [22, 23].

44

CHAPTER 4 Vietnam is an agricultural country with around 70% of the population living in rural areas.

Around 40% of households engage in poultry raising [24], and 94% of these 8 million

households, has a flock size of less than 50 chickens [25]. Little is known about the prevalence

of AMR in E. coli in such relatively small production systems, and its potential association with

antimicrobial use and other farming practices. It is often assumed that, compared with larger

farms, backyard farms use less antimicrobial drugs and feed their chicken more often with by-

products instead of (often medicated) commercial feed. We therefore carried out a survey to

investigate the prevalence of AMR in E. coli indicator bacteria in Vietnamese household and

small chicken farms, with the aims of: (1) estimating the prevalence of resistant E. coli against

key antimicrobials, with a focus on fluoroquinolones, aminoglycosides and 3rd -generation

cephalosporins; and (2) identifying risk factors for faecal carriage of AMR E. coli in chickens,

including demographics, management practices, as well as antimicrobial usage.

Materials and methods

Study population

With an extension of 2,481 km2, the province of Tien Giang (Vietnam) is home to approximately

1.67 million people and 5.96 million chickens. For logistic reasons the study was conducted in 3

districts (My Tho, Cho Gao and Chau Thanh) out of the 10 in the province, as they contain

44.5% of the total chicken population of the province. The study population consisted of 208

chicken farms, equally divided into two strata according to the number of chickens per farm:

≥10-200 (‘household’ farms) and >200-2,000 (‘small’ farms, in contrast to large scale farms with

>2,000 chickens). To avoid regional biases in the sampling, 34 farms from each of the 4 strata

(district-farm size combinations) in Cho Gao and My Tho and 36 farms from each of the 2 strata

in Chau Thanh were selected.

The number of farms to be sampled from each commune (the lower administrative unit within a

district) was calculated with a probability directly proportional to the number of farms in that

commune according to the Vietnamese rural, agricultural and fishery census in 2006 [26]. Farms

were randomly sampled from each chosen commune. Farmers refusing to participate were

replaced by the next eligible farm.

Written informed consent was obtained from all farmers prior to participation in the study. The

study was approved by the Sub-Department of Animal Health (SDAH) and the Peoples’

Committee of Tien Giang Province.

45

CHAPTER 4 Data collection

Farm visits were evenly distributed over the period March 2012 - April 2013 to avoid seasonal

effects. Data on antimicrobial usage and farm management practices were collected using a

structured questionnaire, which was conceived in a workshop including local facilitators, and

was tested in the field prior to sampling (Supplemental Material 1). The questionnaire was aimed

at the person with primary responsibility for chicken husbandry and contained both open and

closed questions. This person was asked about details on administration of any antibacterial

formulation from restocking until the visit date for farms applying all-in-all-out (AIAO) systems,

and for a fixed period of 90 days for the remaining farms not practicing AIAO.

Data on each antibacterial formulation administered (excluding coccidiostats, antiparasitic and

antifungal drugs), were gathered by SDAH staff, including the commercial name of the product,

presentation and number of containers used. To facilitate farmers’ recall, open discussions were

initiated after inspecting the medicine cabinet for all products present containing antibacterial

formulations. This approach is analogous to the medicine cabinet survey used in human

medicine, which has been shown to be highly effective in obtaining information on community

usage of antimicrobial drugs [27].

Sample collection

From each flock, naturally pooled chicken faeces was collected from representative sections of

the chicken pens/houses using 2 (household farms) or 3 pairs (small farms) of boot swabs. For

unconfined flocks, boot swab samples were collected from the areas where the chickens roosted

at night. Boot swabs were used to walk at least 30 steps on areas where fresh droppings were

visible. For flocks on stilts or caged flocks where it was not possible to use boot swabs, visible

faecal material was collected using 2-3 hand-held gauze swabs, which were similar in size to the

boot swabs, each collecting material from at least 10 different locations.

Swab samples were immediately stored at 4°C, transferred to the laboratory in Ho Chi Minh

City, and cultured within 24 hours after sample collection. Both interviews and faecal sample

collection were conducted by trained veterinarians from Tien Giang SDAH.

E. coli isolation

A fixed volume (225 mL) of Buffered Peptone Water was added to each gauze or boot swab in a

separate container and was then manually shaken. One mL from each container was pipetted and

pooled into a sample. From this pooled sample, 1 mL was further diluted 1:1000 in saline

46

CHAPTER 4 solution, and 50 µL of this suspension was plated onto MacConkey agar without supplement and

MacConkey agar supplemented with ceftazidime (2 mg/L) to select for isolates with reduced

susceptibility against 3rd-generation cephalosporins , nalidixic acid (16 mg/L) to select for

isolates with reduced susceptibility against quinolones, or gentamicin (8 mg/L) to select for

isolates with reduced susceptibility against gentamicin, and incubated at 37°C overnight. From

each plate the total number of suspect E. coli colonies was counted. A random selection of five

(MacConkey agar unsupplemented) and two (MacConkey agar supplemented with antimicrobial

drugs) presumptive E. coli colonies of different morphologies were subcultured, and identified as

E. coli using standard biochemical tests (hydrogen sulfide production, carbohydrate

fermentation, urease test, nitrate reductase test, methyl red test, motility test, indole test) and/or

API 20E (BioMérieux, France). Isolates confirmed as E. coli were tested for their antimicrobial

susceptibility.

Antimicrobial susceptibility testing

For the determination of antimicrobial susceptibility, the disk diffusion method was performed

and interpreted according to breakpoints as defined by Clinical and Laboratory Standard Institute

(CLSI) [28]. The following antimicrobials were tested at the given disk content: ampicillin (10

µg), ceftriaxone (30 µg), ceftazidime (30 µg), amoxicillin/clavulanic acid (30 µg),

chloramphenicol (30 µg), ciprofloxacin (5 µg), trimethoprim-sulphamethoxazole (1.25/23.75

µg), gentamicin (10 µg), amikacin (30 µg), tetracycline (30 µg), meropenem (10 µg). Potential

production of ESBLs, as indicated by resistance to ceftriaxone and/or ceftazidime and by an

inhibitory effect of clavulanic acid was confirmed using a double disk diffusion test according to

CLSI guidelines. Strains with an intermediate sensitive result were considered resistant. A MDR

strain was defined as a strain resistant to at least three different classes of antimicrobials. A farm

was defined as ‘positive’ for a resistant E. coli if at least one E. coli isolate resistant against the

antimicrobial drug under study was cultured from MacConkey agar either with or without

supplementation with antimicrobial drugs. Quality controls for identification and sensitivity

testing were performed on a weekly basis according to CLSI guidelines.

Since all MacConkey agar plates (i.e. with or without supplementation with antimicrobial drugs)

were streaked using an identical inoculum, counts of E. coli-like colonies on each plate were

used to determine the proportion of colonies resistant against ceftazidime, gentamicin and

nalidixic acid in relation to the total E. coli population for each farm.

47

CHAPTER 4 Data analyses

Since the study was designed as a stratified survey with fixed number of farms in each stratum,

not all study units (farms) had the same probability of being selected. The prevalence of

resistance against each antimicrobial of a randomly selected isolate cultured from non-selective

plates, as well as the prevalence of resistance by farm was adjusted for the stratified survey

design by assigning a stratum-specific sampling weight (Wi) to each observation unit (either

isolate or farm) using the following equation: Wi = NT/Ni, where NT is the total number of farms

in the three study districts (29,106) and Ni is the number of farms in each stratum sampled (i

=1…6). Standard errors were corrected to take into account potential similarities of prevalence

between farms in each stratum [29].

The frequency of antimicrobial treatment was quantified by calculating treatment incidence as

described by Persoons et al. [30]. Treatment incidence (TI) is defined as the number of chickens

per 1000 that is treated daily with one defined daily dose (DDD) for each antimicrobial

administered in each farm using the following formula:

TI =

Total amount of an antimicrobial administered was calculated using (1) the total consumption as

reported by the farmer (i.e. number of containers of antimicrobial-containing products used), (2)

the concentration of the product, and (3) the reporting usage period.

Defined animal daily dose was estimated based on the dosage mentioned in the drug’s instruction

leaflet. In case medication was dissolved in drinking water or feed, the dosage as indicated by the

manufacturer was standardised to mg/kg chicken body weight, given that an average chicken

consumes 190 mL of water and 80 g of feed per day. The average weight of one chicken was

considered 1kg [31]. The Anatomical Therapeutic Chemical classification system for veterinary

medicinal product (ATCvet) [32] was used for antimicrobial drug identification.

To determine risk factors associated with resistance considered of clinical importance for human

medicine, we modelled the probability of a randomly selected E. coli isolate from any given farm

for the following three outcomes: (1) resistance against ciprofloxacin; (2) resistance against

gentamicin; and (3) MDR. This was carried out by building hierarchical generalized linear mixed

regression models with the term ‘farm’ modelled as a random effect.

(kg) farm on chicken of weight Totalx risk at days ofNumber x (mg/kg) DDD(mg) edadminister ialantimicrob ofamount Total

48

CHAPTER 4 For the outcome ‘resistance against 3rd-generation cephalosporins’, where we observed a very

low probability of resistance amongst individual randomly selected E. coli isolates (3.2%),

culture results from supplemented and un-supplemented plates were combined and standard

logistic regression models were built to model the probability of presence of resistant strains at

the farm.

To build each model, a total of 42 variables were first tested in univariable analyses including

factors describing the farms (production type, size, presence of other animals), farmer

demographic factors, husbandry factors and antimicrobial usage (see Supplemental Material 2

for all variables included). Variables were considered as candidate for multivariable analysis

based on their biological plausibility and p-value <0.15 in the univariable analyses. Candidate

variables were ranked by their degree of significance and were included in the models starting

with the most significant ones using a step-wise forward approach [33]. In the final multivariable

models, variables were retained if their p-value was < 0.05. All interactions between all

significant variables in the model were assessed.

All statistical analyses were performed using the packages epicalc and survey with R statistical

software (http://www.r-project.org).

Results

Description of farm demographic and management factors

Of 104 household farms, 76.0% raised chickens for meat, whereas 23.1% raised chickens with a

mixed-purpose (meat and eggs). In contrast, 60.6% of 104 small farms raised egg laying flocks,

and most of the remainder 38.5% raised meat chickens (Table 1). Confinement of chickens in

pens or houses for 24 hours per day was more common in small farms compared with household

farms (89.4% versus 2.0%, respectively) (p<0.001). The percentage of small farms that used

commercial feed (99.0%) was greater than the percentage of household farms that followed this

practice (70.2%) (p<0.001).

49

CHAPTER 4 Table 1. Characteristics of 208 chicken farms in Tien Giang province, Vietnam studied between March 2012 and May 2013.

IQR: Interquartile range

Prevalence of antimicrobial resistance in E. coli isolates

A total of 895 E. coli isolates were recovered from un-supplemented MacConkey agar. The

crude (unadjusted) and adjusted prevalence of resistance in E. coli isolates are presented in Table

2. Among these randomly selected E. coli isolates, the adjusted prevalence of resistance against

ciprofloxacin was 24.2% (Table 2). The adjusted prevalence of resistance against gentamicin was

15.0% and against ‘any 3rd-generation cephalosporin’ (ceftazidime and/or ceftriaxone) was 3.1%

(Table 2). A total of 81.3% of isolates were multidrug resistant (Table 2).

Variable Household farms Small farms (N=104) (N=104)

Age of farm manager (years) (median) (IQR) 46 (40-55) 43 (37-52) Male farm manager (No. farms) (%) 59 (56.7%) 77 (74.0%) Level of education attained (No. farms) (%) Up to primary school 38 (36.5%) 18 (17.3%) Secondary school 40 (38.5%) 54 (51.9%) Higher 26 (25.0%) 32 (30.8%) No. chickens (median) (IQR) 75 (63-120) 1,500 (1,000-1,900) Production type Meat 79 (76.0%) 40 (38.5%) Eggs 1 (1.0%) 63 (60.6%) Mixed purpose 24 (23.1%) 1 (1.0%) Age of chickens (weeks) (median) (IQR) 15 (8 - 20) 20 (8-32) All-in-all-out system (No. farms) (%) 32 (30.8%) 68 (65.4%) Chickens confined in pen/house 24h per day (No. farms) (%) 2 (2.0%) 93 (89.4%) Source of day-old chickens (No. farms) (%) Hatched on farm 59 (58.4%) 10 (11.2%) Local hatchery 23 (22.8%) 19 (21.3%) Company hatchery 8 (7.9%) 59 (66.3%) Other 11 (10.9%) 1 (1.1%) Presence of animals other than chickens (No. farms) (%) 103 (99.0%) 97 (93.3%) Duck(s) 47 (45.2%) 27 (26.0%) Pig(s) 54 (51.9%) 42 (40.4%) Cattle/buffalo(s) 22 (21.2%) 15 (14.4%) Dog(s) 97 (93.3%) 83 (79.8%) Cat(s) 58 (55.8%) 54 (51.9%) Fish /fish pond(s) 65 (62.5%) 54 (51.9%) Change shoes/boot before entering pen/house (No. farms) (%) 53 (51.0%) 90 (86.5%) Foot bath/foot dip at entrance (No. farms) (%) 43 (41.3%) 82 (78.8%) Used commercial feed (No. farms) (%) 73 (70.2%) 103 (99.0%) Used of antimicrobials (No. farms) (%) 49 (47.1%) 72 (69.2%)

50

CHAPTER 4 Table 2. Prevalence of antimicrobial resistance in E. coli isolates and in chicken farms without and with sampling adjustment in Tien Giang province, Vietnam.

Antimicrobial E. coli isolatesa (N=895) Farmsb (N=208) Prevalence of resistance (%)

Adjusted Prevalence (%) [95% CI]

Prevalence of resistance (%)

Adjusted Prevalence (%) [95% CI]

Tetracycline 93.4 91.1 (88.4 - 93.7) 100 100 (100 - 100) Trimethoprim-sulphamethoxazole 69.7 67.0 (62.7 - 71.3) 100 100 (100 - 100) Chloramphenicol 68.1 61.2 (57.1 - 65.4) 99.0 100 (99.9 - 100) Gentamicin 19.9 15.0 (11.8 - 18.1) 96.6 98.2 (95.0 - 100) Amikacin 5.4 5.4 (3.5 - 7.4) 22.1 22.3 (13.1 - 31.5) Ciprofloxacin 32.5 24.2 (20.3 - 28.1) 91.8 92.8 (87.2 - 98.4) Ampicillin 86.0 83.2 (79.5 - 87.0) 100 100 (100 - 100) Amoxicilin/clavulanic acid 47.9 44.2 (39.6 - 48.9) 95.7 95.0 (89.7 - 100) Ceftazidime 2.0 1.9 (0.4 - 3.5) 31.2 44.2 (33.1 - 55.3) Ceftriaxone 2.5 2.2 (0.7 - 3.7) 35.1 44.6 (33.5 - 55.7) 3rd-generation cephalosporinsc 3.2 3.1 (1.3 - 4.9) 37.0 45.9 (34.8 - 57.0) ESBL- confirmed 0.2 0.4 (0 - 1.1) 14.9 20.6 (11.5 - 29.7) Meropenem 0 0 0 0 Multidrug resistantd 85.3 81.3 (77.8 - 84.8) 100 100 (100 - 100)

CI: Confidence interval a Prevalence of resistance among E. coli isolates randomly picked from un-supplemented MacConkey agar plates representing an unbiased snap shot of the E. coli population. b Prevalence of resistance among chicken farms based on the isolation of resistant E. coli using selective MacConkey agar containing ceftazidim, gentamicin and nalidixic acid. c 3rd-generation cephalosporins: ceftazidime and/or ceftriaxone. ESBL: extended spectrum beta-lactamase d Multidrug resistant: resistant against at least three different classes of antimicrobial drugs

Prevalence of antimicrobial resistant E. coli in chicken farms

E. coli isolates resistant against tetracyclin, co-trimoxazole, chloramphenicol and ampicillin were

detected in 100% of farms. Isolates resistant against gentamicin (98.2%), amoxicillin-clavulanic

acid (95.0%), and ciprofloxacin (92.8%) were also prevalent at most farms whereas isolates

resistant against ceftriaxone (44.6%), ceftazidime (44.2%), and amikacin (22.3%) were less

common. From 20.6% of farms at least one ESBL-producing E. coli isolate was recovered. MDR

E. coli isolates were identified in all farms (Table 2)

Proportion of E. coli isolates showing resistance by farms

The proportion of E. coli isolates resistant against ceftazidime, gentamicin and nalidixic acid in

relation to the total E. coli population in each farm was estimated and was depicted in Figure 1.

Gentamicin and nalidixic acid resistant colonies accounted for 100% of E. coli like colonies in 9

(4.3%) and 32 (15.4%) farms, respectively.

51

CHAPTER 4 Figure 1. Distribution of the percentage of E. coli isolates resistant against ceftazidime, gentamicin and nalidixic acid, across all farms (N=208)

Antimicrobial usage

Treatment incidences of different classes of antimicrobial drugs are shown in Table 3. The mean

treatment incidence was highest for tetracyclines (90.8) followed by macrolides (73.3),

penicillins (52.1) and polymyxins (51.3) (Table 3). The treatment incidence for overall

antimicrobial drug consumption was 370.6, meaning that on average per day 371 chickens out of

1000 were treated with one defined daily dose of an antimicrobial drug.

Risk factors analyses

The use of quinolones (OR=2.26) and tetracyclines (OR=1.70) was significantly associated with

ciprofloxacin resistance in E. coli isolates (Table 4). Small farm size and farming strategies

including the use of commercial feed, AIAO system and change of shoes/boots practice, were all

associated with ciprofloxacin resistance but these associations were not independent (Table 4).

We observed significant interactions between the size of the farm and change shoes/boot practice

(OR=0.22) as well as between the usage of commercial feed and AIAO practice (OR=10.99).

52

CHAPTER 4 Table 3. Treatment incidence of different classes of antimicrobial drugs in household and small-scale chicken farms in Tien Giang province, Vietnam (N=208) Class of antimicrobial druga Name of antimicrobial drug No. of farms using

antimicrobial Mean treatment incidence Standard deviation

Tetracyclines Docycycline, oxytetracycline, tetracycline

52 90.8 608.9

Macrolides Tylosin, tilmicosin, erythromycin, spiramycin

40 73.3 582.0

Polymyxins Colistin 39 51.3 234.2 Penicillins Ampicillin, amoxicillin 33 52.1 383.1 Quinolones Flumequine, oxolinic acid, norfloxacin,

enrofloxacin 19 44.3 304.9

Aminoglycosides Neomycine, gentamicin, apramycin, streptomycin

15 8.0 40.7

Amphenicols Florfenicol, thiamphenicol 13 6.4 54.2 Sulfonamides Sulfamethoxazole, sulphadimidine,

sulphadimetoxine, sulphadimerazine 10 15.5 140.6

Lincosamides Lincomycin 4 8.5 81.9 Spectinomycin Spectinomycin 4 10.0 85.0 Trimethoprim Trimethoprim 2 0.3 2.9 Pleuromutilins Tiamulin 1 0.1 1.0 All classes All antimicrobials 121 370.6 1447.4

a Classes were based on ATCvet classification

Lincosamides (OR=4.47) and tetracyclines (OR=1.99) usage were associated with resistance

against gentamicin in E. coli isolates. In addition, farming strategies, including change of

shoes/boot practice (OR=2.41), the purchase of day-old chicken from other sources than

industrial hatchery companies (local hatcheries, markets, neighbor etc.) (OR=4.93), and raising

chickens for meat or mixed (meat and egg) but not for egg laying only purpose (OR=9.88 and

OR=5.03, respectively) were associated with isolation of gentamicin resistant E. coli. A high

density of chicken (number of chickens per square meter) was associated with both gentamicin

resistance and MDR. We observed a 32% and 28% increase in the odds of isolating gentamicin

resistant or MDR E. coli respectively, for one unit increase in chicken density (chickens per

square metre). The use of commercial feed was also associated with isolation of MDR E. coli

(OR=2.49). The risk of carriage multi-drug resistance E. coli was decreased 4.0% for one-unit

increase in the number of years of experience in chicken farming of the farmer.

The presence of fish pond(s) (OR=2.93 [95% CI, 1.11 to 7.76]) and usage of any antimicrobial

drug (OR=2.80; [95% CI, 1.08 to 7.28) were associated with resistance against 3rd-generation

cephalosporins in E. coli. The presence of fish pond(s) (OR=4.82; [95% CI, 1.27 to 18.27]),

purchase of day-old chicken from other sources (i.e., local hatcheries) compared to day-old

chicken from industrial hatchery companies (OR=13.02; [95% CI, 1.89 to 89.61]), and having a

53

CHAPTER 4 change of shoes/boots practice on the farm (OR=3.4; [95% CI, 0.98 to 11.81]) were associated

with the presence of ESBL-producing E. coli on the farm.

Table 4. Risk factors for resistance against ciprofloxacin, gentamicin, and multidrug resistance in 895 randomly selected E. coli isolates recovered from 208 chicken farms (Tien Giang province, Vietnam). Outcome Variables OR 95% CI p-value Ciprofloxacin resistance a Small farm (baseline=household farm) 6.42 2.74 - 15.03 <0.001 Use of commercial feed 1.87 1.06 - 3.30 0.032 Change shoes/boots practice 2.43 1.44 - 4.09 <0.001 AIAO system 0.17 0.02 - 1.28 0.086 Use of quinolones 2.26 1.20 - 4.25 0.011 Use of tetracyclines 1.70 1.05 - 2.76 0.031 Interaction ‘Small farm’ and ‘Change shoes/boots’ 0.22 0.09 - 0.55 0.001 Interaction ‘Use of commercial feed’ and ‘AIAO ‘ 10.99 1.38 - 87.7 0.024 Gentamicin resistance b Use of tetracyclines 1.99 1.17 - 3.36 0.011 Presence of cat(s) 0.44 0.24 - 0.82 0.010 Change shoes/boots practice 2.41 1.27 - 4.59 0.007 Day-old chickens from other sourcese 4.93 1.22 - 19.97 0.026 Use of lincosamides 4.74 1.18 - 18.97 0.028 log(Density)f 1.32 1.02 - 1.69 0.034 Chicken purpose (baseline= Egg laying chicken) Meat chicken 9.88 5.32 - 18.33 <0.001 Mixed chicken 5.03 1.81 - 14.01 0.002 Multidrug resistance c,d Use of commercial feed 2.49 1.14 - 4.14 0.001 log(Density) 1.28 1.06 - 1.54 0.008 Year of experience in chicken farming 0.96 0.93 - 0.99 0.004

OR= Odds ratio; CI= Confidence interval; AIAO=All-in-all-out; a Intercept: -2.60(SE±0.28), b Intercept: -5.79(SE±0.74), c Intercept: 1.41(SE±0.28) d Resistant to at least three different classes of antimicrobial drugs; e Baseline = day-old chicken from industrial hatchery companies, other sources include local hatcheries, the farm and other sources. f No. of chickens per square metre

Discussion

This study demonstrated a very high (81.3%) prevalence of multi-drug resistant E. coli isolated

from household and small-scale chicken farms in an unbiased study population in the Mekong

Delta of Vietnam., The prevalence of resistance against both ciprofloxacin (24.2%) and

gentamicin (15.0%), was substantial whilst resistance against 3rd-generation cephalosporins

(3.1%) was at a much lower level. The prevalence of resistance among chicken farms based on

the isolation of resistant E. coli using selective culture media, was very high (Table 2). Our

results indicate a generally higher or similar prevalence of AMR among chicken E. coli isolates

from Vietnam against commonly used antimicrobials (tetracycline, chloramphenicol, ampicillin,

gentamicin) compared with results from industrialized countries [34-36]. Data from 7 European

54

CHAPTER 4 countries suggest a higher prevalence of ciprofloxacin resistance (57.6%), whilst data from 5

European countries indicate a higher prevalence of ceftazidime resistance (11.1%) in chickens in

these countries [37]. Whilst such comparisons should be interpreted with caution because of

differences in sampling methods as well as differences in breakpoints used for interpretation of

susceptibility test results between studies from different regions, the high AMR prevalence

observed in these backyard farms in Vietnam is striking and unexpected.

The observed high prevalence of AMR reflects the common use of antimicrobial products for

therapeutic and prophylactic purpose as found in our survey on antimicrobial drug usage. Even

though there was a large variation in treatment incidence between farms and between

antimicrobial drugs, the treatment incidence of any antimicrobial drug usage calculated in our

study (370.6) was much higher than the treatment incidence calculated for countries with

industrial broiler production such as Belgium (131.8), the Netherlands (82.2) and Denmark (8.2)

[30, 38] although such comparisons should be interpreted with caution given the differences in

study design. In addition, most of these products were available without prescription in a pilot

survey across 20 veterinary drug stores in the area (data not shown).

We found statistical associations between usage of quinolones and tetracyclines and

ciprofloxacin resistance, as well as between usage of tetracyclines and lincosamides and

resistance against gentamicin. Other field studies have also demonstrated that usage of

quinolones selects for carriage of quinolone-resistant E. coli in poultry [4, 39]. The association

between usage of tetracyclines and quinolone resistance may be explained by an effect of

tetracycline induced mutations in the Mar operon resulting in over-expression of marA, which

increases resistance against multiple drugs including quinolones [40]. Finally, co-selection of

resistance determinants, encoded by genes located on mobile elements such as integrons, could

explain the observed association between usage of tetracyclines and lincomycin, which is often

formulated in combination with spectinomycin, and gentamicin resistance [41]. We acknowledge

the limitations in obtaining accurate usage data derived from a cross-sectional study design.

Recall biases with regards to data on usage may have introduced error with unknown impact on

the observed associations. In addition, we have tried to use the treatment incidence of different

antimicrobials as continuous variables in the risk factor analyses. However, we did not succeed

in getting a stable model with these continuous variables and as a result we had to consider them

as binary variables for the analyses. Despite these limitations, our study provides a unique view

55

CHAPTER 4 on antimicrobial drug usage and associated antimicrobial resistance in backyard chicken farms in

Vietnam.

The use of commercial feed was associated with an increased risk of fluoroquinolone resistance

and MDR, in agreement with a study on turkey farms in Europe [39] and reflects the fact that in

Vietnam commercial poultry feed is commonly medicated with antimicrobials [42]. In this study

we randomly collected 25 feed samples from 25 different chicken farms and tested these for the

presence of antimicrobial agents (Premi-test, R-Biopharm AG). Antimicrobial compound(s)

were detected in all feed samples (data not shown). The test, however, does not allow further

identification of the antimicrobial compounds present or their concentration in the feed.

Independent of antimicrobial drug or medicated feed usage, there was mixed evidence of an

association between intensification of chicken production and AMR. For example, E. coli

isolates from household farms had clearly lower levels of ciprofloxacin resistance than isolates

from small farms and an increase in density of chickens was associated with gentamicin

resistance and MDR. In contrast, AIAO systems, which were more commonly observed in the

larger farms, decreased risks of ciprofloxacin resistance whilst purchase of day-olds chickens

from company hatcheries and the production of layer flocks were associated with lower levels of

gentamicin resistance, in line with studies in Europe that reported much lower level of

gentamicin resistance in layer chicken compared with broiler chickens [37].

We did not find evidence of any usage of 3rd-generation cephalosporins on any chicken farm

surveyed. However, in Vietnam, cephalosporins are among the most common antimicrobial

classes used in human medicine [43, 44]. It is therefore possible that transmission of resistance

determinants from humans or other species (e.g. pigs) to chickens may have occurred which

would explain the observed, albeit at low prevalence, ceftazidime and ceftriaxone resistance. We

found that the presence of an integrated fish pond at the farm was associated with isolation of

3rd-generation cephalosporin resistant and ESBL-producing E. coli. We speculate that this

association was related to the contact of chicken with fish pond water which would underscore

the relevance of human activities for antimicrobial resistance in poultry, since a relatively high

proportion of households in the rural areas of the Mekong delta do not have latrines that meet

established hygienic standards in terms of construction, operation and maintenance [45]. A

recent study in China suggested that the presence of ESBL-positive Enterobacteriaceae in fish

farms was likely to have originated from human sewage contamination [46]. Further

56

CHAPTER 4 comparisons of isolates from humans, chickens, and fish ponds should help elucidate this

relationship.

We have identified several potential risk factors for antimicrobial resistance in household and

small-scale farms in southern Vietnam, which include antimicrobial usage, farm management

practices, and environmental risks. Given the existing low levels of ‘bio-containment’ in these

farms, the rare use of personal protective equipment of farming personnel when dealing with the

animals, as well as the fact that there is a great degree of overlap between the farming and the

household environment, the risks of transmission of AMR E. coli posed to both farmers and the

communities living in the proximity of chicken farms are likely to be high, and need to be

properly assessed in order to formulate effective strategies to limit further development of

resistance to safeguard human health.

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Rev, 2011. 24(4): p. 718-33. 3. WHO. Critically important antimicrobials for human medicine 2011; Available from:

http://www.who.int/foodsafety/publications/antimicrobials-third/en/. 4. da Costa, P.M., et al., Field trial evaluating changes in prevalence and patterns of antimicrobial resistance

among Escherichia coli and Enterococcus spp. isolated from growing broilers medicated with enrofloxacin, apramycin and amoxicillin. Vet Microbiol, 2009. 139(3-4): p. 284-92.

5. de Jong, A., B. Stephan, and P. Silley, Fluoroquinolone resistance of Escherichia coli and Salmonella from healthy livestock and poultry in the EU. J Appl Microbiol, 2011. 112(2): p. 239-45.

6. Aarestrup, F.M., H.C. Wegener, and P. Collignon, Resistance in bacteria of the food chain: epidemiology and control strategies. Expert Rev Anti Infect Ther, 2008. 6(5): p. 733-50.

7. Johnson, J.R., et al., Similarity between human and chicken Escherichia coli isolates in relation to ciprofloxacin resistance status. J Infect Dis, 2006. 194(1): p. 71-8.

8. Hammerum, A.M. and O.E. Heuer, Human health hazards from antimicrobial-resistant Escherichia coli of animal origin. Clin Infect Dis, 2009. 48(7): p. 916-21.

9. Miles, T.D., W. McLaughlin, and P.D. Brown, Antimicrobial resistance of Escherichia coli isolates from broiler chickens and humans. BMC Vet Res, 2006. 2: p. 7.

10. Literak, I., et al., Broilers as a source of quinolone-resistant and extraintestinal pathogenic Escherichia coli in the Czech Republic. Microb Drug Resist, 2013. 19(1): p. 57-63.

11. Huang, S.Y., et al., Increased prevalence of plasmid-mediated quinolone resistance determinants in chicken Escherichia coli isolates from 2001 to 2007. Foodborne Pathog Dis, 2009. 6(10): p. 1203-9.

12. Yuan, L., et al., Molecular characterization of extended-spectrum beta-lactamase-producing Escherichia coli isolates from chickens in Henan Province, China. J Med Microbiol, 2009. 58(Pt 11): p. 1449-53.

13. Randall, L.P., et al., Characteristics of ciprofloxacin and cephalosporin resistant Escherichia coli isolated from turkeys in Great Britain. Br Poult Sci, 2013. 54(1): p. 96-105.

14. Kola, A., et al., High prevalence of extended-spectrum-beta-lactamase-producing Enterobacteriaceae in organic and conventional retail chicken meat, Germany. J Antimicrob Chemother, 2012. 67(11): p. 2631-4.

15. Overdevest, I., et al., Extended-spectrum beta-lactamase genes of Escherichia coli in chicken meat and humans, The Netherlands. Emerg Infect Dis, 2011. 17(7): p. 1216-22.

16. Leverstein-van Hall, M.A., et al., Dutch patients, retail chicken meat and poultry share the same ESBL genes, plasmids and strains. Clin Microbio Infect, 2011. 17(6): p. 873-880.

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CHAPTER 4 17. Depoorter, P., et al., Assessment of human exposure to 3rd generation cephalosporin resistant E. coli

(CREC) through consumption of broiler meat in Belgium. Int J Food Microbiol, 2012. 159(1): p. 30-8. 18. Yamane, K., et al., Global spread of multiple aminoglycoside resistance genes. Emerg Infect Dis, 2005.

11(6): p. 951-3. 19. Dang, P.K., et al., First Survey on the Use of Antibiotics in Pig and Poultry Production in the Red River

Delta Region of Vietnam. Food and Public Health 2013. 3(5): p. 247-256. 20. CDDEP. Situation Analysis: Antibiotic use and resistance in Vietnam. 2010; Available from:

http://www.cddep.org/sites/default/files/vn_report_web_1_8.pdf. 21. Carrique-Mas, J.J., et al., Antimicrobial Usage in Chicken Production in the Mekong Delta of Vietnam.

Zoonoses Public Hlth, 2014. 61(Suppl 2): p. 1-9. 22. Van, T.T., et al., Antibiotic resistance in food-borne bacterial contaminants in Vietnam. Appl Environ

Microbiol, 2007. 73(24): p. 7906-11. 23. Carrique-Mas, J.J., et al., An epidemiological investigation of Campylobacter in pig and poultry farms in

the Mekong delta of Vietnam. Epidemiol Infect, 2013: p. 1-12. 24. PRISE. A general review and a description of the poultry production in Vietnam. 2008; Available from:

http://orbi.ulg.ac.be/bitstream/2268/157619/1/2008_Review_Poultry_Prod_Vietnam.PDF. 25. Burgos S, et al., Characterization of poultry production systems in Vietnam. Int J of Poult Sci, 2007. 6(10):

p. 709-712. 26. General Statistics Office of Vietnam. Results of the 2006 Rural, Agricultural and Fishery Census.

Statistical Publishing House, Hanoi, Vietnam, 2007. 27. WHO. How to investigate the use of medicines by consumers. 2004; Available from:

http://www.who.int/drugresistance/Manual1_HowtoInvestigate.pdf. 28. Clinical and Laboratory Standards Institute. Performance standards for antimicrobial susceptibility

testing; twenty-first international supplement M100-S21. CLSI, Wayne, PA, USA, 2011. 2011, Clinical and Laboratory Standards Institute.

29. Dohoo, I., W. Martyn, and H. Stryhn, Veterinary Epidemiologic Research. 2nd Edition ed. 2010, 2nd Edition: AVC Inc, Charlottetown, Canada.

30. Persoons, D., et al., Antimicrobial use in Belgian broiler production. Pre Vet Med, 2012. 105(4): p. 320-5. 31. MARAN 2009. Monitoring of Antimicrobial Resistance and Antibiotic Usage in Animals in the Netherlands

in 2009. Available from: http://edepot.wur.nl/165958 32. WHO Collaborating Centre for Drug Statistics Methodology. Guidelines for ATCvet classification 2014.

Available from: http://www.whocc.no/filearchive/publications/2014_atcvet_guidelines.pdf. 33. Hosmer, D., S. Lemeshow, and R. Sturdivant, Applied Logistic Regression. Third ed. 2004: Wiley. 34. Tadesse, D.A., et al., Antimicrobial drug resistance in Escherichia coli from humans and food animals,

United States, 1950-2002. Emerg Infect Dis, 2012. 18(5): p. 741-9. 35. Persoons, D., et al., Prevalence and persistence of antimicrobial resistance in broiler indicator bacteria.

Microb Drug Resist, 2010. 16(1): p. 67-74. 36. Ozaki, H., et al., Antimicrobial resistance in fecal Escherichia coli isolated from growing chickens on

commercial broiler farms. Vet Microbiol, 2012. 150(1-2): p. 132-9. 37. EFSA and ECDC. European Union Summary Report on antimicrobial resistance in zoonotic and indicator

bacteria from humans, animals and food 2012. [News] 2014; 2014/04/05:[20748]. Available from: http://ecdc.europa.eu/en/publications/Publications/antimicrobial-resistance-in-zoonotic-and-indicator-bacteria-summary-report-2012.pdf.

38. Bondt, N., et al., Comparing antimicrobial exposure based on sales data. Pre Vet Med, 2013. 108(1): p. 10-20.

39. Jones, E.M., et al., Risk factors for antimicrobial resistance in Escherichia coli found in GB turkey flocks. Vet Rec, 2013. 173(17): p. 422.

40. Ruiz, C. and S.B. Levy, Many chromosomal genes modulate MarA-mediated multidrug resistance in Escherichia coli. Antimicrob Agents Chemother, 2010. 54(5): p. 2125-34.

41. Toleman, M.A., P.M. Bennett, and T.R. Walsh, ISCR elements: novel gene-capturing systems of the 21st century? Microbio Mol Biol Rev, 2006. 70(2): p. 296-316.

42. Dang, S.T., et al., Impact of medicated feed on the development of antimicrobial resistance in bacteria at integrated pig-fish farms in Vietnam. Appl Environ Microbiol, 2011. 77(13): p. 4494-8.

43. Nguyen, K.V., et al., Antibiotic use and resistance in emerging economies: a situation analysis for Viet Nam. BMC Public Health, 2013. 13: p. 1158.

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study. BMC Pharmaco Toxicol, 2014. 15(1): p. 6. 45. Van Minh, H., et al., Assessing willingness to pay for improved sanitation in rural Vietnam. Environ Health

Prev Med, 2013. 18(4): p. 275-84. 46. Jiang, H.X., et al., Prevalence and characteristics of beta-lactamase and plasmid-mediated quinolone

resistance genes in Escherichia coli isolated from farmed fish in China. J Antimicrob Chemother, 2012. 67(10): p. 2350-3.

59

CHAPTER 4

Supplementary Material 1: Questionnaire to study antimicrobial use in chicken farms in Tien Giang province, Vietnam

Name of interviewer: [_________________________________]

Interview date (dd/mm/yy) : [__|__]/[__|__]/[__|__]

We are conducting a study to investigate medicines used by Tien Giang farmers for their chickens. You have received information about our study and you have agreed to participate. We would like to ask you some questions about your farm and your experience in the use of medicines for your chicken. For example, which medicines do you use and when and why. Do you agree to do the interview now?

A. GENERAL INFORMATION

1. Age of farm owner/manager (years): [__|__] years

2. Gender: Male Female

3. Highest educational attainment: No schooling Primary school Secondary school High school Post-high school degree

4. Years of experience in poultry farming: [__|__] years

B. PROFILE OF CHICKEN FLOCK(S):

5. Please provide details on chicken flock(s) present on your farm now

Use a different flock number for each poultry keeping area

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CHAPTER 4

Flock number

Chicken purpose

Total number

Age Are your birds

confined 24

hours/day in a

house/pen?

If confined, are they

kept inside

24h/day

If unconfined

or partly confined, do they

have access to

outside the farm?

All-in/all-

out

No of crop/s

per year

Expected age of

depopulation or sale. If

chicken are sold at

different ages, indicate range

Chicken procured as

Day-olds At age other than day-olds, specify age at purchase

1 - Yes

2 - No

1-Hatched in farm

2-Purchased from local hatchery

3-From company hatchery

4-Purchased from Market/ Dealer/ neighbor

9-Unknown

1 - Yes 2 - No

(in weeks)

(99 if unknown)

1-Meat chicken

2-Layer chicken

3-Mixed purpose chickens

(in week/s)

0 - Unconfined

1 - Pen

2 - House

1 - Yes

2 - No

1 - Yes

2 - No

1 - Yes

2 - No

(in weeks)

[__|__] [__] [__|__|__|__] [__|__] [__] [__] [__] [__] [__] [__|__] [__] [__] [__] [__|__]

[__|__] [__] [__|__|__|__] [__|__] [__] [__] [__] [__] [__] [__|__] [__] [__] [__] [__|__]

[__|__] [__] [__|__|__|__] [__|__] [__] [__] [__] [__] [__] [__|__] [__] [__] [__] [__|__]

[__|__] [__] [__|__|__|__] [__|__] [__] [__] [__] [__] [__] [__|__] [__] [__] [__] [__|__]

[__|__] [__] [__|__|__|__] [__|__] [__] [__] [__] [__] [__] [__|__] [__] [__] [__] [__|__]

[__|__] [__] [__|__|__|__] [__|__] [__] [__] [__] [__] [__] [__|__] [__] [__] [__] [__|__]

[__|__] [__] [__|__|__|__] [__|__] [__] [__] [__] [__] [__] [__|__] [__] [__] [__] [__|__]

61

CHAPTER 4

6. Have any of the chickens currently present in your farm been vaccinated? 7. Yes No

If Yes, tick all that apply

HPAI Newcastle Gumboro Infectious bronchitis

Infectious encephalomyelitis Fowl Cholera Marek Other

8. Please provide details on previous chicken crop(s) – the one(s) occupying chicken pens/houses immediately before the current one(s)

Pen/House

Number (use same number as in q. 5)

No of chickens

Age of chickens at depopulation or

sale (in weeks)

How many were lost due to diseases?

How many were lost due to other

causes?

[__|__] [__|__|__|__] [__|__] [__|__|__] [__|__|__]

[__|__] [__|__|__|__] [__|__] [__|__|__] [__|__|__]

[__|__] [__|__|__|__] [__|__] [__|__|__] [__|__|__]

[__|__] [__|__|__|__] [__|__] [__|__|__] [__|__|__]

[__|__] [__|__|__|__] [__|__] [__|__|__] [__|__|__]

9. Any there other animal species on the farm now? Yes No

If Yes, tick all that apply

Fighting cock Duck Muscovy duck Other poultry species

Pigs Cattle/buffalo Dog Cat Fish

C. ANTIBIOTIC USE

10. What do you do to keep your chickens healthy? Probe, anything else? [____________________________________________________________________] [____________________________________________________________________]

11. What products have you used to keep your chickens healthy? Do you keep them in the farm? Can we see them? Which have you used in the current flock(s)? For continuously occupied houses or farms, describe use over the last 3 months. If no antibiotic is used, tick this box

62

CHAPTER 4

Flock number

Commercial Name

Manufacturer

Contents

Supplier (1)

Com

plet

e o

nly

for

the

curr

ent (

crop

)

Presentation (2)

Content per unit (eg. Grams of active

compound)

Administration (3)

Total number of units used on the flock

(probe, if don’t remember write dk)

How long ago was the last administration?

(days) (probe, if don’t remember write dk)

Purpose of use (4)

Diseases/Problems (5)

Advice from (6)

Timing of application (7)

Coding for products: see product list and pictures

(1) Supplier 1- Drug/feed shop; 2- Drug company/salesman; 3-Friend/neighbor; 9-Other, if applicable, specify

(2) Formulation 1- Powder; 2- Liquid

(3) Administration 1-Dissolve in drinking water; 2-Mix with feed; 3- Both dissolve in drinking water and mix with feed; 4- Injection; 5-Nose drops

(4) Purpose of use 1-Prevention; 2- Treatment; 3- Both prevention and treatment; 9- Other, specify

(5) Symptom 1-Respiratory problems; 2-Digestive problems; 3-Poor performance/Malaise; 4-High mortality; 9-Other, if applicable, write down symptoms:……………………..

(6) Advice from 1-Drug seller; 2-District veterinarian; 3-Chief of animal health worker; 4-Salesperson; 6-Friend/neighbor; 9-Other, if applicable, write down advisor ………………

(7) Timing of application

1-On arrival; 2-Before/after vaccination; 3-Changing of feed; 4-Changing of season; 5-Before selling; 6-Other, if applicable, write down timing……………………

63

CHAPTER 4

12. Do you read the administration guidelines of the antibiotics before use?

Always Sometimes Never

D. BIO-SECURITY AND CLEANING & DISINFECTION (C&D) OF CHICKEN HOUSES:

13. Ask only for enclosed chicken house/pen. Tick those that apply to your chicken flock(s): If no chicken house/pen tick box

14. Ask only for enclosed chicken house/pen. Please describe the procedure of cleaning and disinfection in the chicken house/pen(s). Tick those that apply to your chicken flock(s): If no chicken house/pen tick box

15. Ask only for enclosed chicken house/pen. What disinfectants do you use for cleaning and disinfection of your chicken house? If no chicken house/pen tick box If no disinfectant is used, tick this box.

Flock number Commercial name of disinfectants Dilution rate

Method /Application 1-Pressure washer 2- Sprayer 4-Backpack 5-Hose 6-Others

[__|__] [__]

[__|__]

[__]

[__|__]

[__]

[__|__]

[__]

Flock number

Ante-room

Change of boot/shoes Foot bath/boot dip Are outsiders allowed?

[__|__] Yes No Yes No Yes No Yes No

[__|__] Yes No Yes No Yes No Yes No

[__|__] Yes No Yes No Yes No Yes No

[__|__] Yes No Yes No Yes No Yes No

[__|__] Yes No Yes No Yes No Yes No

Flock number

Type of C&D Mucking out

Washing

Disinfec-tion

What do you do with the used

muck/litter/bedding?

If Dispose

1 - During production 2 – Terminal 3- Both 1 and 2 4-None

1- Yes 2-No

1- Yes 2-No

1- Yes 2-No

1-Fertilize your field 2-Dispose 3-Sell it

1-Water way 2-Burn 3-Others

[__|__] [__] [__] [__] [__] [__] [__]

[__|__] [__] [__] [__] [__] [__] [__]

[__|__] [__] [__] [__] [__] [__] [__]

[__|__] [__] [__] [__] [__] [__] [__]

[__|__] [__] [__] [__] [__] [__] [__]

[__|__] [__] [__] [__] [__] [__] [__]

64

CHAPTER 4

[__|__]

[__]

16. Wild birds seen in the farm

Never Sometimes (1-4 times per month) Often (>4 times per month)

17. Rodents seen in the farm

Never Sometimes (1-4 times per month) Often (>4 times per month)

18. Do you use any other product for disinfection? Yes No a. If yes, specify: [________________________________________________________]

E. CHICKEN FEED 19. Please describe the types of feed you give to your chickens. Include feed you have given in your farm to previous flock(s) or the current

chicken flock(s) only. Do not include any feed you intend to give in the future.

Flock number

Household left-overs

Uncooked rice/rice by products

Locally mixed chicken feed

Commercial feed Others, specify

[__|__]

[__|__]

[__|__]

[__|__]

[__|__]

20. Please provide details on commercial feed given to the current crop(s) until present.

If no commercial feed is given, tick this box .

Flock number

Commercial name Manufacturer

Presentation

1-Crumbs

2-Pellet

3-Mash

Quantity

(in kg)

Given to previous crop(s)

1-Yes

2-No

[__|__] [__] [__]

[__|__] [__] [__]

[__|__] [__] [__]

[__|__] [__] [__]

[__|__] [__] [__]

21. Do you use other products for your chicken, for example additives to feed or drinking water?

Yes No

If yes, list: [_________________________________________________________]

22. Source of water for chickens (tick all that apply)

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CHAPTER 4

Municipal supply Borehole/well Rain water

Pond River/stream/canal other, specify________________

23. Distance from the farm to the closest running water sources (in meter) [__|__|__|__|__]

F. QUESTION

24. Do you have any questions or comments? Yes No [_____________________________________________________________________] [_____________________________________________________________________]

Thank you, this is the end of the interview.

66

CHAPTER 4 Supplementary Material 2.1: Univariate analyses of risk factors associated with ciprofloxacin resistant E. coli detected among chicken E. coli isolated from farms.

No Name of variable OR Lower 95% CI Upper 95% CI p-value 1 Age of farmer 0.98 0.96 1.00 0.036 2 Gender of farmer 0.60 0.39 0.92 0.018 3 No of Year Experience in chicken farming 0.96 0.93 0.99 0.003 4 Highest education of farmer No schooling or primary school 1.01 0.57 1.80 0.737

Secondary school 1.20 0.69 2.07 0.737

Higher than secondary school ref ref ref ref 5 Small farm (baseline=household farm) 3.24 2.43 4.34 0.000 6 Chicken production type Egg laying chicken ref ref ref ref

Meat chicken 3.31 2.46 4.47 0.227

Mixed chicken 2.92 1.79 4.75 0.227 7 Chicken confined 24h inside 3.35 1.79 6.28 0.000 8 Farm followed All-in-all-out practice 2.23 1.44 3.47 0.000 9 Location of farm My Tho ref ref ref ref

Cho Gao 1.99 1.20 3.29 0.137

Chau Thanh 2.20 1.30 3.72 0.137 10 Chicken visited at later stage of production (baseline=early stage) 0.59 0.39 0.90 0.016 11 Farm used commercial feed 2.83 1.81 4.41 0.000 12 Farm used disinfectants 0.91 0.32 2.54 0.850 13 Farm with the presence of ante-room 0.39 0.05 3.35 0.395 14 Farm followed changing shoes/boot practice 3.17 1.94 5.20 0.000 15 Farm with the presence of footbath 2.35 1.51 3.64 0.000 16 Farm with access of outsider 1.06 0.55 2.06 0.862 17 log(Density of chicken - per square meter) 1.10 0.95 1.28 0.196 18 Rodents seen in farm Never ref ref ref ref

Sometimes 0.82 0.53 1.25 0.702

Often 0.82 0.18 3.72 0.702 19 Wildbird seen in farm Never ref ref ref ref

Sometimes 1.13 0.73 1.76 0.647

Often 0.67 0.16 2.75 0.647 20 Chicken procured as day-olds 0.61 0.20 1.90 0.395 21 Day-old chicken from other sources than industrial hatchery company 0.86 0.39 1.92 0.718 22 Presence of dog 1.69 0.80 3.55 0.169 23 Presence of duck 0.92 0.59 1.42 0.698 24 Presence of fighting cock 1.03 0.64 1.65 0.899 25 Presence of fish pond 0.69 0.45 1.06 0.090 26 Presence of cat 0.53 0.34 0.81 0.004 27 Presence of Cattle/Buffalo 1.19 0.67 2.14 0.550 28 Presence of Pigs 1.06 0.69 1.62 0.792 29 Read guideline before usage antimicrobials Always ref ref ref ref

Sometimes 1.07 0.60 1.90 0.962

Never 1.11 0.38 3.20 0.962 30 Farm use antimicrobials (any) 2.61 1.64 4.14 0.000 31 Used aminoglycosides 0.52 0.19 1.45 0.212 32 Used amphenicols 0.83 0.16 4.41 0.830 33 Used lincosamides 2.60 1.12 6.04 0.026 34 Used macrolides 2.55 1.47 4.45 0.001 35 Used penicillins 0.53 0.23 1.25 0.147 36 Used pleuromutilins NC NC NC NC 37 Used polymyxins 0.53 0.25 1.15 0.111 38 Used quinolones 2.83 1.55 5.16 0.001 39 Used spectinomycin 2.04 0.79 5.22 0.139 40 Used sulfonamides 0.28 0.06 1.24 0.094 41 Used tetracyclines 2.25 1.43 3.56 0.001 42 Used trimethoprim 0.09 0.06 0.14 0.000

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Supplementary Material 2.2: Univariate analyses of risk factors associated with ciprofloxacin resistant E. coli detected among chicken E. coli isolated from farms.

No Name of variable OR Lower 95% CI Upper 95% CI p-value 1 Age of farmer 0.99 0.97 1.02 0.546 2 Gender of farmer 0.47 0.29 0.79 0.004 3 No of Year Experience in chicken farming 0.96 0.92 0.99 0.010 4 Highest education of farmer No schooling or primary school 1.41 0.66 3.03 0.388 Secondary school 1.62 0.74 3.56 0.388 Higher than secondary school ref ref ref ref 5 Small farm (baseline=household farm) 2.30 1.64 3.22 0.000 6 Chicken production type Egg laying chicken ref ref ref ref Meat chicken 4.68 3.28 6.68 0.138 Mixed chicken 3.07 1.50 6.30 0.138 7 Chicken confined 24h inside 3.64 2.05 6.45 0.000 8 Farm followed All-in-all-out practice 1.02 0.61 1.69 0.946 9 Location of farm My Tho ref ref ref ref Cho Gao 1.19 0.73 1.95 0.012 Chau Thanh 0.55 0.29 1.05 0.012

10 Chicken visited at later stage of production (baseline=early stage) 0.55 0.33 0.92 0.022 11 Farm used commercial feed 1.26 0.80 1.99 0.320 12 Farm used disinfectants 0.52 0.18 1.57 0.250 13 Farm with the presence of ante-room 0.71 0.08 6.32 0.758 14 Farm followed changing shoes/boot practice 3.22 1.77 5.87 0.000 15 Farm with the presence of footbath 1.49 0.90 2.46 0.118 16 Farm with access of outsider 0.52 0.19 1.42 0.205 17 log(Density of chicken - per square meter) 1.18 1.02 1.37 0.026 18 Rodents seen in farm Never ref ref ref ref Sometimes 0.55 0.32 0.93 0.101 Often 1.32 0.29 5.88 0.101

19 Wildbird seen in farm Never ref ref ref ref Sometimes 0.79 0.48 1.31 0.705 Often 0.74 0.16 3.48 0.705

20 Chicken procured as day-olds 0.50 0.13 1.92 0.315 21 Day-old chicken from other sources than industrial hatchery company 3.96 1.08 14.52 0.038 22 Presence of dog 12.63 4.36 36.58 0.000 23 Presence of duck 0.85 0.51 1.40 0.517 24 Presence of fighting cock 0.80 0.42 1.53 0.496 25 Presence of fish pond 0.53 0.32 0.90 0.018 26 Presence of cat 0.33 0.19 0.58 0.000 27 Presence of Cattle/Buffalo 1.53 0.81 2.92 0.193 28 Presence of Pigs 1.31 0.78 2.20 0.307 29 Read guideline before usage antimicrobials Always ref ref ref ref Sometimes 0.56 0.22 1.38 0.253 Never 0.52 0.14 2.01 0.253

30 Farm use antimicrobials (any) 3.09 1.72 5.55 0.000 31 Used aminoglycosides 0.91 0.30 2.74 0.868 32 Used amphenicols 0.05 0.03 0.08 0.000 33 Used lincosamides 4.23 1.54 11.67 0.005 34 Used macrolides 2.66 1.49 4.74 0.001 35 Used penicillins 0.97 0.42 2.21 0.941 36 Used pleuromutilins 3.79 0.51 28.48 0.195 37 Used polymyxins 0.54 0.22 1.31 0.172 38 Used quinolones 1.62 0.69 3.78 0.269 39 Used spectinomycin 2.90 1.04 8.12 0.043 40 Used sulfonamides 0.01 0.01 0.02 0.000 41 Used tetracyclines 2.48 1.56 3.93 0.000 42 Used trimethoprim 0.05 0.01 0.20 0.000

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Supplementary Material 2.3: Univariate analyses of risk factors associated with multidrug resistant E. coli detected among chicken E. coli isolated from farms.

No Name of variable OR Lower 95% CI Upper 95% CI p-value 1 Age of farmer 1.00 0.98 1.02 0.915 2 Gender of farmer 0.61 0.37 1.00 0.049 3 No of Year Experience in chicken farming 0.95 0.92 0.97 0.000 4 Highest education of farmer No schooling or primary school 0.75 0.39 1.42 0.650

Secondary school 0.87 0.45 1.66 0.650

Higher than secondary school ref ref ref ref 5 Small farm (baseline=household farm) 2.99 1.90 4.71 0.000 6 Chicken production type Egg laying chicken ref ref ref ref

Meat chicken 8.58 1.60 46.07 0.010

Mixed chicken 5.02 0.90 28.05 0.010 7 Chicken confined 24h inside 2.67 0.82 8.67 0.102 8 Farm followed All-in-all-out practice 2.78 1.47 5.23 0.002 9 Location of farm My Tho ref ref ref ref

Cho Gao 1.15 0.75 1.77 0.022

Chau Thanh 2.08 1.24 3.50 0.022 10 Chicken visited at later stage of production (baseline=early stage) 0.63 0.38 1.04 0.071 11 Farm used commercial feed 3.12 1.89 5.16 0.000 12 Farm used disinfectants 0.50 0.28 0.90 0.021 13 Farm with the presence of ante-room 1.89 0.21 17.22 0.573 14 Farm followed changing shoes/boot practice 1.11 0.70 1.76 0.671 15 Farm with the presence of footbath 1.62 0.99 2.67 0.056 16 Farm with access of outsider 1.23 0.58 2.58 0.589 17 log(Density of chicken - per square meter) 1.45 1.23 1.72 0.000 18 Rodents seen in farm Never ref ref ref ref

Sometimes 1.84 1.12 3.00 0.014

Often 1.96 1.26 3.05 0.014 19 Wildbird seen in farm Never ref ref ref ref

Sometimes 1.06 0.66 1.70 0.642

Often 1.83 0.45 7.39 0.642 20 Chicken procured as day-olds 0.39 0.05 3.07 0.371 21 Day-old chicken from other sources than industrial hatchery company 0.14 0.03 0.73 0.020 22 Presence of dog 5.62 2.35 13.43 0.000 23 Presence of duck 1.82 1.11 2.97 0.017 24 Presence of fighting cock 0.67 0.39 1.12 0.127 25 Presence of fish pond 0.65 0.40 1.05 0.076 26 Presence of cat 0.85 0.53 1.35 0.481 27 Presence of Cattle/Buffalo 0.68 0.41 1.13 0.141 28 Presence of Pigs 1.07 0.66 1.72 0.785 29 Read guideline before usage antimicrobials Always ref ref ref ref

Sometimes 0.51 0.28 0.91 0.002

Never 0.25 0.11 0.60 0.002 30 Farm use antimicrobials (any) 1.28 0.80 2.04 0.297 31 Used aminoglycosides 4.05 0.64 25.59 0.137 32 Used amphenicols 0.25 0.09 0.64 0.004 33 Used lincosamides 5.61 0.72 43.94 0.101 34 Used macrolides 1.79 0.75 4.28 0.191 35 Used penicillins 1.67 0.83 3.35 0.149 36 Used pleuromutilins NC NC NC NC 37 Used polymyxins 0.68 0.39 1.18 0.167 38 Used quinolones 0.85 0.37 1.93 0.695 39 Used spectinomycin NC NC NC NC 40 Used sulfonamides 0.40 0.18 0.88 0.023 41 Used tetracyclines 1.48 0.76 2.90 0.250 42 Used trimethoprim NC NC NC NC

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Supplementary Material 2.4: Univariate analyses of risk factors associated with 3rd generation cephalosporin resistant E. coli detected on farms.

No Name of variable OR Lower 95% CI Upper 95% CI p-value 1 Age of farmer 0.99 0.96 1.03 0.652 2 Gender of farmer 1.01 0.40 2.54 0.978 3 No of Year Experience in chicken farming 0.97 0.91 1.02 0.228 4 Highest education of farmer No schooling or primary school 1.31 0.42 4.09 0.543 Secondary school 0.74 0.23 2.32 0.543 Higher than secondary school ref ref ref ref 5 Small farm (baseline=household farm) 0.61 0.31 1.21 0.157 6 Chicken production type Egg laying chicken ref ref ref ref Meat chicken 15.04 2.34 96.72 0.277 Mixed chicken 16.11 2.14 121.38 0.277 7 Chicken confined 24h inside 0.70 0.19 2.55 0.591 8 Farm followed All-in-all-out practice 0.55 0.21 1.42 0.216 9 Location of farm My Tho ref ref ref ref Cho Gao 1.29 0.49 3.37 0.659 Chau Thanh 1.64 0.64 4.21 0.659

10 Chicken visited at later stage of production (baseline=early stage) 1.46 0.58 3.69 0.424 11 Farm used commercial feed 1.22 0.42 3.55 0.711 12 Farm used disinfectants 2.17 0.29 16.07 0.450 13 Farm with the presence of ante-room NC NC NC NC 14 Farm followed changing shoes/boot practice 1.57 0.64 3.85 0.325 15 Farm with the presence of footbath 1.35 0.54 3.34 0.520 16 Farm with access of outsider 0.76 0.20 2.86 0.691 17 log(Density of chicken - per square meter) 1.17 0.86 1.58 0.330 18 Rodents seen in farm

Never ref ref ref ref Sometimes 1.41 0.56 3.56 0.722 Often 1.57 0.17 15.00 0.722

19 Wildbird seen in farm Never ref ref ref ref Sometimes 0.62 0.24 1.58 0.399 Often 1.87 0.24 14.53 0.399

20 Chicken procured as day-olds 0.45 0.04 4.57 0.498 21 Day-old chicken from other sources than industrial hatchery company 1.75 0.35 8.67 0.493 22 Presence of dog 0.22 0.03 1.56 0.133 23 Presence of duck 1.05 0.43 2.59 0.914 24 Presence of fighting cock 1.16 0.43 3.11 0.763 25 Presence of fish pond 2.49 0.99 6.28 0.055 26 Presence of cat 0.71 0.29 1.76 0.462 27 Presence of Cattle/Buffalo 1.96 0.63 6.15 0.247 28 Presence of Pigs 0.41 0.16 1.03 0.059 29 Read guideline before usage antimicrobials Always ref ref ref ref Sometimes 1.18 0.37 3.81 0.820 Never 0.55 0.06 5.44 0.820

30 Farm use antimicrobials (any) 2.37 0.95 5.88 0.066 31 Used aminoglycosides 0.76 0.15 3.71 0.731 32 Used amphenicols 1.72 0.11 26.39 0.698 33 Used lincosamides 1.19 0.15 9.29 0.867 34 Used macrolides 0.65 0.16 2.69 0.550 35 Used penicillins 1.24 0.36 4.28 0.737 36 Used pleuromutilins NC NC NC NC 37 Used polymyxins 2.76 0.84 9.08 0.097 38 Used quinolones 3.14 0.68 14.58 0.146 39 Used spectinomycin 3.37 0.33 34.36 0.307 40 Used sulfonamides 2.48 0.39 15.79 0.338 41 Used tetracyclines 1.17 0.39 3.56 0.778 42 Used trimethoprim NC NC NC NC

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Supplementary Material 2.5: Univariate analyses of risk factors associated with ESBL-producing E. coli detected on farms.

No Name of variable OR Lower 95% CI Upper 95% CI p-value 1 Age of farmer 0.97 0.92 1.02 0.210 2 Gender of farmer 0.81 0.26 2.50 0.709 3 No of Year Experience in chicken farming 0.93 0.86 1.01 0.101 4 Highest education of farmer No schooling or primary school 2.03 0.49 8.33 0.571

Secondary school 1.23 0.28 5.42 0.571

Higher than secondary school ref ref ref ref 5 Small farm (baseline=household farm) 0.39 0.15 1.05 0.064 6 Chicken production type Egg laying chicken ref ref ref ref

Meat chicken 23.51 2.56 215.76 0.468

Mixed chicken 25.76 2.28 291.54 0.468 7 Chicken confined 24h inside 1.18 0.20 7.02 0.852 8 Farm followed All-in-all-out practice 0.83 0.26 2.70 0.760 9 Location of farm My Tho ref ref ref ref

Cho Gao 1.20 0.38 3.77 0.597

Chau Thanh 0.79 0.24 2.62 0.597 10 Chicken visited at later stage of production (baseline=early stage) 1.58 0.48 5.20 0.457 11 Farm used commercial feed 0.87 0.23 3.27 0.832 12 Farm used disinfectants 5.68 0.61 52.75 0.128 13 Farm with the presence of ante-room NC NC NC NC 14 Farm followed changing shoes/boot practice 2.52 0.79 8.06 0.120 15 Farm with the presence of footbath 1.79 0.58 5.48 0.309 16 Farm with access of outsider 0.45 0.08 2.55 0.371 17 log(Density of chicken - per square meter) 0.91 0.66 1.26 0.578 18 Rodents seen in farm Never ref ref ref ref

Sometimes 0.81 0.26 2.51 0.531

Often 0.20 0.02 2.25 0.531 19 Wildbird seen in farm Never ref ref ref ref

Sometimes 0.95 0.30 2.97 0.323

Often 0.12 0.01 1.26 0.323 20 Chicken procured as day-olds NC NC NC NC 21 Day-old chicken from other sources than industrial hatchery company 11.40 1.65 78.95 0.015 22 Presence of dog 0.26 0.04 1.71 0.163 23 Presence of duck 0.77 0.25 2.39 0.652 24 Presence of fighting cock 1.86 0.57 6.04 0.301 25 Presence of fish pond 3.32 0.95 11.61 0.061 26 Presence of cat 0.76 0.25 2.34 0.636 27 Presence of Cattle/Buffalo 1.75 0.50 6.15 0.385 28 Presence of Pigs 0.54 0.18 1.67 0.288 29 Read guideline before usage antimicrobials Always ref ref ref ref

Sometimes 1.83 0.48 7.01 0.612

Never 2.12 0.21 21.84 0.612 30 Farm use antimicrobials (any) 2.08 0.67 6.47 0.205 31 Used aminoglycosides 1.04 0.17 6.43 0.965 32 Used amphenicols 5.79 0.37 90.63 0.212 33 Used lincosamides NC NC NC NC 34 Used macrolides 1.33 0.26 6.85 0.732 35 Used penicillins 2.46 0.62 9.67 0.200 36 Used pleuromutilins NC NC NC NC 37 Used polymyxins 1.91 0.51 7.17 0.337 38 Used quinolones 1.33 0.24 7.44 0.742 39 Used spectinomycin NC NC NC NC 40 Used sulfonamides 4.34 0.66 28.48 0.127 41 Used tetracyclines 1.20 0.31 4.64 0.792 42 Used trimethoprim NC NC NC NC

71

CHAPTER 5 COLONIZATION OF ENTEROAGGREGATIVE ESCHERICHIA COLI

AND SHIGA TOXIN-PRODUCING ESCHERICHIA COLI IN CHICKENS AND HUMANS IN SOUTHERN VIETNAM

CHAPTER 5

Chapter 5: Colonization of Enteroaggregative Escherichia coli and Shiga toxin-producing Escherichia coli in chickens and humans in southern Vietnam

Nguyen Vinh Trung1,2,3, Hoang Ngoc Nhung3, Juan J. Carrique-Mas3,4, Ho Huynh Mai5, Ha Thanh Tuyen3, James Campbell3,4, Nguyen Thi Nhung3, Pham Van Minh3, Jaap A.Wagenaar6,7, Nguyen Thi Nhu Mai8, Thai Quoc Hieu5, Constance Schultsz1,2,3, Ngo Thi Hoa3,4

1Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. 2 Department of Global Health-Amsterdam Institute for Global Health and Development, The Netherlands. 3 Oxford University Clinical Research Unit, Centre for Tropical Medicine, Ho Chi Minh City, Vietnam. 4 Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford, United Kingdom. 5 Sub-Department of Animal Health, My Tho, Tien Giang, Vietnam. 6 Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, The Netherlands. 7 Central Veterinary Institute of Wageningen UR, Lelystad, The Netherlands.8 Preventive Medicine Center, My Tho, Tien Giang, Vietnam

BMC Microbiol. 2016, 16 (1): 208

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Abstract

Background: Enteroaggregative (EAEC) and Shiga-toxin producing Escherichia coli (STEC) are

a major cause of diarrhea worldwide. E. coli carrying both virulence factors characteristic for

EAEC and STEC and producing extended-spectrum beta-lactamase caused severe and protracted

disease during an outbreak of E. coli O104:H4 in Europe in 2011. We assessed the opportunities

for E. coli carrying the aggR and stx genes to emerge in ‘backyard’ farms in south-east Asia.

Results: Faecal samples collected from 204 chicken farms; 204 farmers and 306 age- and gender-

matched individuals not exposed to poultry farming were plated on MacConkey agar plates with

and without antimicrobials being supplemented. Sweep samples obtained from MacConkey agar

plates without supplemented antimicrobials were screened by multiplex PCR for the detection of

the stx1, stx2 and aggR genes. One chicken farm sample each (0.5%) contained the stx1 and the

aggR gene. Eleven (2.4%) human faecal samples contained the stx1 gene, 2 samples (0.4%)

contained stx2 gene, and 31 (6.8%) contained the aggR gene. From 46 PCR-positive samples,

205 E. coli isolates were tested for the presence of stx1, stx2, aggR, wzxO104 and fliCH4 genes.

None of the isolates simultaneously contained the four genetic markers associated with E. coli

O104:H4 epidemic strain (aggR, stx2, wzxO104 and fliCH4). Of 34 EAEC, 64.7% were resistant to

3rd-generation cephalosporins.

Conclusion: These results indicate that in southern Vietnam, the human population is a more

likely reservoir of aggR and stx gene carrying E. coli than the chicken population. However,

conditions for transmission of isolates and/or genes between human and animal reservoirs

resulting in the emergence of highly virulent E. coli strains are still favorable, given the nature of

‘backyard’ farms in Vietnam.

Keywords: EAEC, STEC, E. coli, chicken, humans, Vietnam.

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Introduction

Escherichia coli is one of the most widely distributed bacteria in the environment, and therefore

humans and animals are exposed to saprophytic E. coli strains throughout their lives. Some E.

coli strains may become capable of causing disease in humans and some animal species by

expression of one or multiple virulence factors, such as adhesins and toxins [1]. These virulence

factors are encoded by genes which are typically located on mobile genetic elements such as

plasmids or phages. Horizontal gene transfer between E. coli strains carrying different virulence

determinants may result in novel virulence gene combinations leading to highly virulent

phenotypes.

An example of the emergence of highly virulent pathogenic E. coli strains is the

Enterohaemorrhagic E. coli (EHEC) O104:H4, responsible for the large and devastating outbreak

of hemorrhagic colitis in Europe in 2011 [2]. This outbreak strain was found to carry an unusual

combination of the pathogenic features of enteroaggregative E. coli (EAEC) and Shiga toxin

(Stx)-producing E. coli (STEC). Among the 6 pathotypes of E. coli capable of causing enteric

diseases, EAEC has emerged as a cause of acute and persistent diarrhea in children, as well as

adults, in both developed and developing countries [3, 4]. EAEC has rarely been isolated from

animal sources such as dogs and cats [5], but whether animals are reservoirs of EAEC or are

accidental hosts of EAEC due to close contact with humans [6] remains to be determined. In

contrast, it has been shown that cattle are the major reservoir species of STEC. However, other

livestock species, including sheep, goats, horses, pigs, and water buffalo, are also capable of

harboring these organisms [7]. In fact, STEC has been found in contaminated food, water [8] and

the farm environment [9-11]. Given these differences between reservoirs, it is striking that Stx-

producing EAEC has emerged to cause outbreaks in humans [12]. Therefore, further

investigation of the distribution of genes encoding for virulence factors aggR, stx1 and stx2 in

environmental, animal and human reservoirs is required to better understand the potential for the

emergence of E. coli carrying this unusual combination of virulence genes.

Although the prevalence of STEC in chicken is considered minimal, a previous study has shown

that chickens are readily and persistently infected by STEC [13]. Small-scale and backyard

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chicken farming are very common in southeast Asia, including the Mekong Delta in southern

Vietnam [14, 15]. In such farms, there is typically a great degree of overlap between the farming

and household environments, providing ample opportunity for horizontal gene transfer between

human and poultry E. coli. We aimed to assess the potential of such an occurance, by

investigating the prevalence of the highly conserved aggR and the stx1, stx2 genes in samples

collected from chicken farms, farmers and in matched asymptomatic humans not exposed to

chickens, as well as in E. coli isolates from these samples. In addition, with the hypothesis that E.

coli O104:H4 epidemic strains may be present in Vietnam, we also screened for the presence of

the combination of aggR, stx2, wzxO104 and fliCH4 genes in E. coli isolates.

Methods

Sample collection

This study was carried out as a part of a larger study on antimicrobial drug usage and

antimicrobial resistant E. coli colonization in backyard chicken farms and humans. We collected

faecal swabs from 204 randomly selected chicken farms; 204 healthy farmers in those farms, and

306 age- and sex-matched individuals in Tien Giang province, Vietnam. The matched

individuals not involved in poultry farming were randomly selected from the same district as the

farmers (rural individual, N=204,), as well as from the provincial capital (urban individual,

N=102), using the population census of Tien Giang [16]. Farms and household visits were

evenly distributed over a 13-month-period from March 2012 to April 2013 in order to avoid

seasonal effects. Faecal samples from chickens were collected using boot-swabs or hand-held

gauze swabs, as described previously [17]. The chicken sample collection was conducted by a

trained sampling team from the Tien Giang Sub-Department of Animal Health. Rectal swab

samples were obtained from all human participants by trained staff from Tien Giang Preventive

Medicine Center, using Fecalswab (Copan, Italy). All samples were stored and transported at

4oC to the laboratory at the Oxford University Clinical Research Unit in Ho Chi Minh City and

cultured within 24 hours after sample collection.

E. coli isolation and antimicrobial susceptibility testing

Buffered Peptone Water (225 mL) was added to each chicken faecal sample in a separate

container and was manually shaken. A volume of 1 mL from each container was diluted 1:1000

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in saline solution. Human rectal swabs were vortexed to release and suspend the sample in the

liquid transport medium and then 100 µL was diluted 1:100 in saline solution. A volume of 50

µL of each saline diluted sample was plated onto MacConkey agar (Oxoid, UK) with or without

antimicrobials supplemented. This procedure yielded on average 100 single colonies on each

plate, which allowed for unbiased detection of E. coli-like colonies of multiple morphologies in

all samples. A random selection of 5 (from MacConkey agar plate without antimicrobial

supplemented) and 2 (from each of MacConkey agar plates supplemented with either nalidixic

acid [16 mg/L], ceftazidime [2 mg/L], or gentamicin [8 mg/L]) presumptive E. coli-like colonies

were sub-cultured, identified and tested for their susceptibility using disc diffusion method in

accordance with the Clinical and Laboratory Standards Institute guidelines [18]. Eleven

antimicrobials (all Oxoid, UK) were tested including tetracycline (30 mg),

trimethoprim/sulfamethoxazole (1.25/23.75 mg), chloramphenicol (30 mg), gentamicin (10 mg),

amikacin (30 mg), ciprofloxacin (5 mg), ampicillin (10 mg), amoxicillin/clavulanic acid (30 mg),

ceftazidime (30 mg), ceftriaxone (30 mg) and meropenem (10 mg). Quality controls for

susceptibility testing and identification were performed every week according to the CLSI

guidelines. Strains with an intermediate susceptible result were considered resistant. An MDR

strain was defined as a strain resistant to at least three different antimicrobial classes.

Only E. coli strains with a unique morphology and/or phenotypic antimicrobial susceptibility

pattern isolated from each sample were saved for further analyses. In addition, a sweep from the

full remaining growth on the MacConkey plate without antimicrobial supplement was collected,

suspended in glycerol and stored in screw-cap tubes at - 20oC for further analyses.

Screening for the presence of E. coli virulence factors

As using sweep samples for PCR screening has been shown to be efficient and sensitive [19],

multiplex PCR was first performed on the glycerol stored sweeps to screen for the presence of

aggR, stx1 and stx2 genes. In brief, one loop full (1 µl) of the -20oC stored sweep was collected

and cultured on the MacConkey agar, then incubated for 16 hours at 37oC. A sweep of the

bacterial growth was then collected and suspended in 1 ml of water. Suspensions were heated at

95°C for 3 minutes and immediately placed on ice then centrifuged at 9000rpm/ 3 minutes to

collect DNA in the supernatant. Primers used for the multiplex PCR are listed in Table 1.

Primers were designed by using Nucleotide Blast, Align X and OligoAnalyzer 3.1 with the

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published sequences on NCBI database (Genbank accession numbers are M19473, X07865,

Z18751 for stx1, stx2 and aggR, respectively). The detection limit of the assay was determined

by cloning the target sequences into a pCR2.1 plasmid (TA Cloning kit, Invitrogen, USA). The

PCR had a detection limit of 10 copies per ml for each of the target gene as determined by serial

dilution from 10 ng/µl to 10-6 ng/µl. Each reaction mixture contained 2 mM MgCl2, 0.1 mM

deoxyribonucleotides, 0.2 uM each of the oligonucleotides and 0.5 U of Taq polymerase

(Bioline, UK), to which 50 – 100 ng of the DNA suspension was added. The mixtures were

processed in a GeneAmp PCR system 9700 (Applied Biosystems, USA). The PCR program was

96oC for 4 min, 30 cycles of 94oC for 20 s, annealing at 55oC for 20 s, and 72oC for 10 s. The

final extension step was 72oC for 7 min. DNA extracted from E. coli E3787 (stx1), E. coli

E32511 (stx2), E. coli E69187 (aggR) was used as a positive control in PCR reactions. A

negative control, containing water instead of template DNA was included in each run of PCR

reactions.

Table 1. List of primers used in this study

Target genes Primer name Primer sequences (5’-3’) Fragment size Reference

aggR aggR_F AAGCAGCGATACATTAAGACG

424 This study aggR_R TGCTTTGCTCATTCTTGATTGC

stx1 stx1_F TGATGATTGATAGTGGCACAGG

299 This study stx1_R AGAAGTAGTCAACGAATGGCG

stx2 stx2_F ACATCGGTGTCTGTTATTAACC

666 This study stx2_R TTGACTCTCTTCATTCACGGC

wzxO104 wzxO104_F GGTTTTATTGTCGCGCAAAG

337 [20] wzxO104_R TATGCTCTTTTTCCCCATCG

fliCH4 fliCH4_F ACGGCTGCTGATGGTACAG

244 [20] fliCH4_R CGGCATCCAGTGCTTTTAAC

From any sweep sample which produced positive PCR result for any of the target genes in

multiplex PCR, DNA extracted from all stored E. coli isolates obtained after culture of the

corresponding faecal sample on MacConkey agar plates with and without antimicrobials

supplemented, was subsequently tested for the presence of 3 genes (aggR, stx1 and stx2) using

multiplex PCR. The presence of 2 genes (wzxO104 and fliCH4) was also investigated using

monoplex PCR [20].

Results

Sweep samples were available for 188 of 204 chicken farms, 186 of 204 farmers, 182 of 204

rural individuals and 90 of 102 urban individuals. The remaining sweep samples were either

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missing (16 chicken samples and 45 human samples) or were not available because the primary

faecal culture on MacConkey agar did not show any growth (7 human samples). The aggR gene

was detected in 31 (6.8%) human samples but in only 1 (0.5%) of the chicken farm samples (p <

0.001). Gene stx1 was detected in 11 human samples (2.4%) and in one chicken farm sample

(0.5%) whereas gene stx2 was detected in one farmer (0.5%) and in one rural individual (0.5%).

In 46 samples, at least one of three tested genes (aggR, stx1 and stx2) was detected in the

multiplex PCR. None of the samples was positive with multiple genes (Table 2).

Table 2. Prevalence of aggR, stx1 and stx2 genes in sweep samples and prevalence of aggR, stx1, stx2, wzxO104 and fliCH4 genes in E. coli isolated from chicken faecal samples and human rectal swabs

Subject No. of positive samples (%) No. of positive E. coli / No. of E. coli investigated (%) aggR stx1 stx2 aggR stx1 stx2 wzxO104 fliCH4

Chicken farm (N=188) 1 (0.5) 1 (0.5) 0 0/4 0/5 ND 0/9 1/9 (11.1) Farmer (N=186) 12 (6.5) 7 (3.8) 1 (0.5) 16a/55 (29.1) 1/29 (3.4) 0/4 1/88 (1.1) 12/88 (13.6) Rural individual (N=182) 13 (7.1) 3 (1.6) 1 (0.5) 16b/58 (27.6) 0/13 0/4 0/75 5/75 (6.7) Urban individual (N=90) 6 (6.7) 1 (1.1) 0 2c/27 (7.4) 0/6 ND 0/33 1/33 (3.0)

aaggR-positive E. coli were isolated from samples of 7 farmers. baggR-positive E. coli were isolated from samples of 7 rural individuals. caggR-positive E. coli were isolated from sample of 1 urban individual. ND: Not done

DNA samples of 205 E. coli isolated from those 46 MacConkey sweep samples were tested for

the presence of aggR, stx1, stx2 and then further screened for the presence of wzxO104 and fliCH4

gene. The aggR gene was detected in 29.1%, 27.6% and 7.4% of E. coli strains isolated from

aggR positive samples in farmers, rural individuals and urban individuals, respectively (Table 2).

EAEC could be isolated from faecal samples of 3.8% (7/186) of farmers, 3.8% (7/182) rural

individuals and 1.1% (1/90) urban individuals. The EAEC isolates exhibited resistance against

ampicillin (100%), co-trimoxazole (85.3%), tetracycline (70.6%), gentamicin (70.6%),

ceftriaxone (64.7%), ceftazidime (50.0%), chloramphenicol (38.2%), ciprofloxacin (26.5%) and

amikacin (2.9%). 88.2% and 50.0% of EAEC isolates were multi-drug resistant and extended-

spectrum beta-lactamase positive, respectively (Table 3).

From the 12 stx1 positive sweep samples, only one E. coli (3.4%) from a farmer, among 53 E.

coli isolates investigated, was stx1 positive (Table 2). This E. coli isolate was also multi-drug

resistant against chloramphenicol, sulfamethoxazole-trimethoprim, ampicillin, tetracycline and

ciprofloxacin). Eight E. coli isolates from the two stx2 PCR positive samples were tested and

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none showed a positive result for stx2 gene. As a result, STEC was isolated in 0.5% (1/186) of

farmers or 0.2% (1/458) of studied humans.

Table 3. Antimicrobial susceptibility of EAEC isolates from asymptomatic humans in southern Vietnam

Antimicrobial No. of antimicrobial resistant EAEC (%)

Chicken farmer Rural individual Urban individual Total (N=16) (N=16) (N=2) (N=34)

Tetracycline 8 (50.0) 14 (87.5) 2 (100) 24 (70.6) Trimethoprim/sulfamethoxazole 13 (81.2) 14 (87.5) 2 (100) 29 (85.3) Chloramphenicol 11 (68.8) 2 (12.5) 0 13 (38.2) Gentamicin 13 (81.2) 11 (68.8) 0 24 (70.6) Amikacin 0 1 (6.2) 0 1 (2.9) Ciprofloxacin 0 9 (56.2) 0 9 (26.5) Ampicillin 16 (100) 16 (100) 2 (100) 34 (100) Amoxicillin/clavulanic acid 8 (50.0) 7 (43.8) 2 (100) 17 (50.0) Ceftazidime 6 (37.5) 11 (68.8) 0 17 (50.0) Ceftriaxone 8 (50.0) 14 (87.5) 0 22 (64.7) Third-generation cephalosporins 8 (50.0) 14 (87.5) 0 22 (64.7) ESBL-producing 6 (37.5) 11 (68.8) 0 17 (50.0) Meropenem 0 0 0 0 MDR 13 (81.2) 15 (93.8) 2 (100) 30 (88.2)

MDR: Multi-drug resistant

Among 196 E. coli isolates from 44 human individuals that were positive for any of the genes

screened for using the multiplex PCR, fliCH4 gene was detected in 13.6%, 6.7% and 3.0% of E.

coli isolates from farmers, rural individuals and urban individuals, respectively (Table 2). One

out of 9 isolates from two farm samples (11.1%) was positive with fliCH4 gene. Gene wzxO104 was

observed in one isolate from a farmer (1.1%). The only gene combination that we observed in

this study was aggR and fliCH4, which was detected in two isolates from one rural individual.

None of the isolates analyzed in our study simultaneously contained the four genetic markers

associated with the O104:H4 epidemic strain (aggR, stx2, wzxO104 and fliCH4).

Discussion

The differences in detection of the aggR gene in chicken faecal samples (1; 0.5%) and samples

from asymptomatic humans (31; 6.8%) suggest that humans are likely the main reservoir of

EAEC in the setting studied. The isolation rate of EAEC from humans in our study (3.3%,

15/458) was similar to previous studies including asymptomatic adults and children performed in

northern Vietnam [21, 22]. To our knowledge, this is the first study describing the presence of

the aggR gene in chicken faecal samples in Vietnam. We, however, speculate that this gene may

have a human origin since a relatively high proportion of households in the rural areas of the

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Mekong Delta do not have latrines that meet established hygiene standards with respect to their

construction, operation and maintenance [23].

Gene stx1 was also detected more frequently in samples from humans compared with those from

chickens (2.4% versus 0.5%) and the more toxic gene – stx2 – was only detected in two samples

from humans (0.4%). The nondetection of STEC in chicken farms is in agreement with previous

studies in chickens in the United States and United Kingdom in which the prevalence of STEC

colonization ranged between 0 and 1.5% [24]. Although we did not find the presence of STEC in

chicken samples in this study, STEC is still an important cause of diarrhea in farm animals in

Vietnam as has been shown in previous studies [25, 26]. The isolation rate of STEC (0.2%,

1/458) and EAEC (3.3%, 15/458) in asymptomatic humans in Vietnam is also similar to the

reported prevalence in both developed and developing countries [27-29]. Our results indicate a

generally high level of antimicrobial resistance among EAEC isolates from Vietnam compared

with results from other countries [30] and overuse of antimicrobials in the community could be

one of the possible explanations [31].

A total of 150 (73.2%) out of 205 E. coli isolates, which were isolated from positive sweep

samples, were negative in the colony PCR for detection of the five genes of interest. The lower

isolation rate of EAEC and STEC in comparison to the stx and aggR gene detection rate on

sweep samples may be due to the presence of the stx or aggR genes in E. coli strains other than

those selected or in bacterial species other than E. coli but capable of growing on MacConkey

agar [32]. In addition, the bacterial sweep was used as it was previously shown to better detect E.

coli in stool samples than testing up to 5 E. coli isolates because of its enrichment [19]. Hence

differences in sensitivity can also explain lower detection rates when testing single colonies and

the absence of stx-positive E. coli amongst the limited number of isolates tested, does not

completely rule out the presence of STEC in the sample.

The full combination of the four typical markers of the 2011 German E. coli O104:H4 outbreak

strain stx2, wzxO104, fliCH4 and aggR was not detected in any E. coli isolated from human faecal

and chicken farm samples in the current study, despite the great degree of overlap between the

farming and living environment in the study setting in Vietnam. We found one combination of

EAEC and STEC O104:H4 associated aggR and fliCH4 genes in two E. coli isolates from one

rural individual not exposed to poultry farming.

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Conclusions

Our results indicate that in southern Vietnam, the human population is a more likely reservoir of

aggR and stx gene carrying E. coli than the chicken population. However, it is important to note

that all four typical markers of the outbreak strain (stx2, wzxO104, fliCH4 and aggR) were detected,

albeit at low numbers, in samples (stx2 and aggR) and E. coli isolates (wzxO104, fliCH4) in

different host populations. Given the nature of ‘backyard’ farms in Vietnam, conditions for

transmission of isolates and/or genes between human and animal reservoirs are still favorable.

Therefore, strict personal hygiene practices as well as applying biosecurity in animal farming are

essential to avoid the emergence of highly virulent strains.

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12. !!! INVALID CITATION !!!13. La Ragione, R.M., et al., Variable and strain dependent colonisation of chickens by Escherichia coli O157.

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p. 709-712.15. Desvaux, S. and V.D. Ton, A general review and description of the poultry production in Vietnam, in

Research consortium on risks associated with livestock intensification. 2008, CIRAD: Hanoi, Vietnam.16. Statistical Office of Tien Giang Province. Statistical YearBook Tien Giang Province 2011. Statistical

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17. Nguyen, V.T., et al., Prevalence and risk factors for carriage of antimicrobial-resistant Escherichia coli onhousehold and small-scale chicken farms in the Mekong Delta of Vietnam. J Antimicrob Chemother, 2015.70(7): p. 2144-52.

18. CLSI, 2011. Performance standards for antimicrobial susceptibility testing; twenty-first internationalsupplement M100-S21. Clinical and Laboratory Standards Institute, Wayne, PA, USA.

19. Schultsz, C., et al., Detection of enterotoxigenic Escherichia coli in stool samples by usingnonradioactively labeled oligonucleotide DNA probes and PCR. J Clin Microbiol, 1994. 32(10): p. 2393-7.

20. Paddock, Z.D., et al., Detection of Escherichia coli O104 in the feces of feedlot cattle by a multiplex PCRassay designed to target major genetic traits of the virulent hybrid strain responsible for the 2011 Germanoutbreak. Appl Environ Microbiol, 2013. 79(11): p. 3522-5.

21. Do, T.T., et al., Epidemiology and aetiology of diarrhoeal diseases in adults engaged in wastewater-fedagriculture and aquaculture in Hanoi, Vietnam. Trop Med Int Health, 2007. 12 Suppl 2: p. 23-33.

22. Hien, B.T., et al., Diarrheagenic Escherichia coli and Shigella strains isolated from children in a hospitalcase-control study in Hanoi, Vietnam. J Clin Microbiol, 2008. 46(3): p. 996-1004.

23. Van Minh, H., et al., Assessing willingness to pay for improved sanitation in rural Vietnam. Environ HealthPrev Med, 2013. 18(4): p. 275-84.

24. Persad, A.K. and J.T. LeJeune, Animal Reservoirs of Shiga Toxin-Producing Escherichia coli. MicrobiolSpectr, 2014. 2(4): p. EHEC-0027-2014.

25. Nguyen, T.D., T.T. Vo, and H. Vu-Khac, Virulence factors in Escherichia coli isolated from calves withdiarrhea in Vietnam. J Vet Sci, 2011. 12(2): p. 159-64.

26. Vu-Khac, H. and N.A. Cornick, Prevalence and genetic profiles of Shiga toxin-producing Escherichia colistrains isolated from buffaloes, cattle, and goats in central Vietnam. Vet Microbiol, 2008. 126(4): p. 356-63.

27. Nataro, J.P., et al., Diarrheagenic Escherichia coli infection in Baltimore, Maryland, and New Haven,Connecticut. Clin Infect Dis, 2006. 43(4): p. 402-7.

28. Keskimaki, M., et al., EPEC, EAEC and STEC in stool specimens: prevalence and molecular epidemiologyof isolates. Diagn Microbiol Infect Dis, 2001. 40(4): p. 151-6.

29. Opintan, J.A., et al., Carriage of diarrhoeagenic Escherichia coli by older children and adults in Accra,Ghana. Trans R Soc Trop Med Hyg, 2010. 104(7): p. 504-6.

30. Kong, H., X. Hong, and X. Li, Current perspectivesin pathogenesis and antimicrobial resistance ofenteroaggregative Escherichia coli. Microb Pathog, 2015. 85: p. 44-9.

31. Nga do, T.T., et al., Antibiotic sales in rural and urban pharmacies in northern Vietnam: an observationalstudy. BMC Pharmacol Toxicol, 2014. 15: p. 6.

32. Mauro, S.A. and G.B. Koudelka, Shiga toxin: expression, distribution, and its role in the environment.Toxins (Basel), 2011. 3(6): p. 608-25.

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Supplementary Material: Patterns of antimicrobial resistance in EAEC and STEC isolated from humans

in southern Vietnam.

Isolate Code Study Code Subject Colony Number Plate Detected Gene(s) Resistance pattern CG15F.A1 CG15F F A1 A aggR C--AMC----SXT--CN--AMP CG15F.G1 CG15F F G1 G aggR C--AMC----SXT--CN--AMP CG15F.G2 CG15F F G2 G aggR C------SXT--CN--AMP CG37R.G1 CG37R R G1 G aggR/ fliCH4 C-CAZ-AMC-CRO--TE---CN-CIP-AMP CG37R.N1 CG37R R N1 N aggR/ fliCH4 -CAZ--CRO---SXT---CIP-AMP CG41F.A1 CG41F F A1 A aggR -----TE-----AMP CG41F.G1 CG41F F G1 G aggR C--AMC---TE-SXT--CN--AMP CG62R.C2 CG62R R C2 C aggR -CAZ-AMC-CRO--TE-SXT--CN-CIP-AMP CG62R.A2 CG62R R A2 A aggR -CAZ-AMC-CRO--TE-SXT--CN-CIP-AMP CG62R.N2 CG62R R N2 N aggR -CAZ--CRO--TE-SXT--CN-CIP-AMP CG62R.N1 CG62R R N1 N aggR -CAZ-AMC-CRO--TE-SXT--CN-CIP-AMP CG62R.G2 CG62R R G2 G aggR -CAZ--CRO--TE-SXT--CN-CIP-AMP CG62R.G1 CG62R R G1 G aggR -CAZ--CRO--TE-SXT--CN-CIP-AMP CG67R.G2 CG67R R G2 G aggR --AMC-CRO---SXT--CN--AMP CG67R.G1 CG67R R G1 G aggR ---CRO--TE-SXT--CN--AMP CG67R.C2 CG67R R C2 C aggR ---CRO--TE-SXT--CN--AMP CG67R.C1 CG67R R C1 C aggR -CAZ--CRO--TE-SXT--CN--AMP CT20F.A1 CT20F F A1 A Wzxo104 C-CAZ-AMC-CRO--TE-----AMP CT37R.A3 CT37R R A3 A aggR -----TE-----AMP CT55F.G1 CT55F F G1 G aggR C-CAZ--CRO--TE-SXT--CN--AMP CT55F.C2 CT55F F C2 C aggR C-CAZ-AMC-CRO--TE-SXT--CN--AMP CT55F.C1 CT55F F C1 C aggR C---CRO--TE-SXT--CN--AMP CT55F.A2 CT55F F A2 A aggR C---CRO--TE-SXT--CN--AMP CT58F.N2 CT58F F N2 N aggR C--AMC----SXT--CN--AMP CT61F.G2 CT61F F G2 G aggR C--AMC---TE-SXT--CN--AMP CT61F.G1 CT61F F G1 G aggR C--AMC---TE-SXT--CN--AMP MT12R.A2 MT12R R A2 A aggR -----TE-SXT----AMP MT13R.N2 MT13R R N2 N aggR -CAZ-AMC-CRO--TE-SXT-AK--CIP-AMP MT15F.N2 MT15F F N2 N stx1 C-----TE-SXT---CIP-AMP MT43R.C2 MT43R R C2 C aggR C-CAZ-AMC-CRO--TE-SXT---CIP-AMP MT51U.N1 MT51U U N1 N aggR --AMC---TE-SXT----AMP MT51U.A3 MT51U U A3 A aggR --AMC---TE-SXT----AMP MT65F.C1 MT65F F C1 C aggR C-CAZ--CRO-------AMP MT65F.A2 MT65F F A2 A aggR -CAZ-AMC-CRO-------AMP MT68F.G1 MT68F F G1 G aggR -CAZ-AMC-CRO---SXT--CN--AMP MT68F.C1 MT68F F C1 C aggR -CAZ-AMC-CRO---SXT--CN--AMP

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CHAPTER 6 CONTRIBUTION OF NON-INTENSIVE CHICKEN FARMING TO

EXTENDED-SPECTRUM BETA-LACTAMASE PRODUCING ESCHERICHIA COLI COLONIZATION IN HUMANS IN SOUTHERN

VIETNAM

CHAPTER 6

Chapter 6: Contribution of non-intensive chicken farming to extended-spectrum beta-lactamase producing Escherichia coli colonization in humans in southern Vietnam

Nguyen Vinh Trung1,2,3, Juan J Carrique-Mas3,4, Willemien van Rooijen1, Nguyen Thi Nhung3, Hoang Ngoc Nhung3, Ha Thanh Tuyen3, Pham Van Minh3, James Campbell3,4, Ho Huynh Mai5, Thai Quoc Hieu5, Nguyen Thi Nhu Mai6, Anita Hardon7, Roderick Card8, Muna Anjum8, Jaap A.Wagenaar9,10, Ngo Thi Hoa3,4, Constance Schultsz1,2,3

1 Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands 2 Department of Global Health-Amsterdam Institute for Global Health and Development, The Netherlands 3 Oxford University Clinical Research Unit, Centre for Tropical Medicine, Ho Chi Minh City, Vietnam 4 Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford, United Kingdom 5 Sub-Department of Animal Health, My Tho, Tien Giang, Vietnam 6 Preventive Medicine Center, My Tho, Tien Giang, Vietnam 7 Center for Social Science and Global Health, University of Amsterdam, The Netherlands 8 Animal and Plant Health Agency, United Kingdom 9 Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, The Netherlands 10 Central Veterinary Institute of Wageningen UR, Lelystad, The Netherlands

(Manuscript submitted)

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Abstract

Overuse of antimicrobial substances in agriculture in Asia has been reported, but the risk of

acquisition of extended spectrum beta-lactamase (ESBLs) in humans through non-intensive

chicken farming still remains unclear. To study the potential contribution of chicken farming to

colonization with ESBL-producing Escherichia coli (ESBL-Ec) in humans, we collected faecal

samples from 204 randomly selected farmers and their chickens, and from 306 community-based

individuals who did not raise poultry. ESBL-Ec was isolated from MacConkey agar with and

without antimicrobials supplemented. ESBL genes were characterized using microarray, PCR,

and sequencing. The prevalence of ESBL-Ec colonization was 20.0% in chicken farms, 31.1% in

chicken farmers, 49.5% in rural individuals and 38.3% in urban individuals. Multivariable

analysis showed that colonization with ESBL-Ec in humans was associated with the human

usage of antimicrobial drugs (OR=2.10, 95% CI= 0.97 – 4.55) but not with involvement in

chicken farming (OR= 0.46, 95% CI=0.30 – 0.70). CTX-M-55 was identified as the most

common ESBL encoding gene in chicken (12/20, 60.0% versus 8/60, 13.3% in human isolates,

p<0.05), whilst CTX-M-27 was the most prevalent in human isolates

(33/60, 55.0% versus 2/20, 10.0%; p<0.05). In 3/204 (1.5%) of the farms, identical ESBL genes

were detected in ESBL-Ec isolated from farmers and their chickens. These findings suggest that

non-intensive chicken farming is not a major source of ESBL-Ec colonization in humans and that

human antimicrobial drug usage appears as a more important driver of ESBL-Ec colonization in

community-based individuals in southern Vietnam.

Keywords: ESBL-producing, Escherichia coli, antimicrobial use, antimicrobial resistance,

farmer, poultry

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Introduction

The spread of extended-spectrum beta-lactamases (ESBLs) in nosocomial and community-

acquired Enterobacteriaceae is a challenge since therapeutic options for infections with these

organisms are limited [1]. Colonization with ESBL-producing Escherichia coli (ESBL-Ec) has

been documented in healthy humans as well as in food-producing animals, including chickens

[2], and the prevalence has increased significantly during the last decades [3, 4]. High and

inappropriate antimicrobial drug usage in humans and in food animals is an important driving

force for this increased prevalence [5].

It has been suggested that transmission of bacteria and/or mobile genetic elements carrying

ESBL encoding genes from food-producing animals to humans may contribute to human

infection with ESBL-Ec. Recent studies comparing ESBL genes and resistance

plasmids in isolates of poultry and human origin suggest that a significant proportion of human

extra-intestinal ESBL-Ec infections may originate from poultry because poultry and human

isolates appeared genetically related or carried similar resistance genes ESBL-Ec [6]. However,

in the majority of these studies human E. coli isolates came from invasive infections and were

compared with isolates from commercially purchased chicken meat samples. Bacterial

contamination of such samples may not represent the situation on the farm of origin and can

therefore not be directly attributed to chicken farming practices. In addition, human and chicken

samples were collected in different time frames whilst accompanying data on relevant

antimicrobial drug usage, which may explain observed resistance characteristics better than

transmission between host populations, were lacking. All of these comparative studies were

carried out in developed countries where industrial farming systems are predominant. The risk of

human colonization with ESBL-Ec resulting from farming practices in developing countries,

where poultry farms are often small and farming is practiced with low-levels of biosecurity and

high usage of antimicrobial drug [7] has not been addressed.

The Mekong Delta is a region in Vietnam where, as in large parts of Asia, a significant

proportion of the population raises poultry at home, typically in small numbers [8]. In addition,

available data indicate high rates of carriage of antimicrobial drug resistant E. coli in this region

[9, 10], where antimicrobial drugs for use in both animals and humans are available over the

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counter [11]. We, therefore, aimed to study the potential contribution of transmission of ESBL-

Ec from poultry to ESBL-Ec colonization in humans by determining the prevalence and

similarities in resistance encoding gene content of ESBL-Ec colonizing chickens and humans

and to relate these to antimicrobial drug usage.

Methods

Study population

A total of 204 chicken farms and 204 chicken farmers, defined as an adult person (≥ 18 years

old) responsible for raising the chickens, who were not hospitalized in the previous 4 weeks,

were randomly selected as described previously [9, 12]. In brief, sampling was stratified by farm

size (10 – 200 chickens, ‘household farms’; 201 – 2000 chickens, ‘small size farms’) and by

district (My Tho city, Cho Gao district and Chau Thanh district) (total 6 strata).

Age- and sex-matched individuals who were not involved in poultry farming were randomly

selected from the same district as the farmers (N=204), as well as from the provincial capital

(N=102) using the population census provided by the Preventive Medicine Centre (PMC) in Tien

Giang [13].

Written informed consent was obtained from all participants prior to recruitment. The study was

approved by the Peoples’ Committee of Tien Giang Province, the Department of Health in Tien

Giang and the Oxford University Tropical Research Ethics Committee (OxTREC, No. 48/11).

Data and sample collection

Data and samples were collected from March 2012 to April 2013. Data on antimicrobial drug

usage in both chickens and humans was collected using structured questionnaires

(Supplementary Materials 1 and 2).

Faecal samples from chickens were collected using boot-swabs or hand-held gauze swabs, as

described previously [9]. Rectal swab samples from human participants were obtained using

Faecalswab (Copan, Italy).

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Data and sample collection were conducted by combined sampling teams from Tien Giang

SDAH and PMC. Samples were stored and transported at 4oC to the laboratory at the Oxford

University Clinical Research Unit in Ho Chi Minh City and cultured within 24 hours after

collection

ESBL-producing E. coli isolation

E. coli isolation and identification were performed using MacConkey agar with and without

antimicrobials (ceftazidime, nalidixic acid and gentamicin) supplemented as described

previously [9]. Susceptibility testing and potential production of ESBL was confirmed using a

double disk diffusion test in accordance with CLSI guidelines [14]. Quality controls for

identification and sensitivity testing were performed on a weekly basis.

All isolates with a unique phenotypic antimicrobial susceptibility pattern in each subject were

stored for further analyses. Strains with an intermediate sensitive result were considered

resistant. A chicken farm or participant was defined as ‘positive’ for ESBL-Ec if at least one

ESBL-Ec isolate was cultured from any of the MacConkey plates used.

Identification of antimicrobial resistance genes and sequence types

To characterize beta-lactamase gene families in the ESBL-Ec isolates and other antimicrobial

resistance genes, a miniaturized micro-array (AMR-08, Alere, Jena, Germany) was used as

described previously [15]. The list of genes included in the AMR-08 microarray is shown in the

Supplementary Material 3. ESBL gene families detected from the array were further

characterized using PCR amplification and sequencing (Supplementary Material 2).

Multilocus sequence typing was performed on 43 E. coli isolates using the scheme described

previously [16].

Sample size and data analyses

The chosen sample size of 204 chicken farmers and 306 unexposed individuals is sufficient to

detect a difference in prevalence of colonization with ESBL-Ec, from 50.5% (unexposed

individuals) to 65.0% (exposed individuals) with 80% power and 95% confidence interval.

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As there is no method for determining sample size for genomic microarray analyses of bacterial

isolates, we randomly selected 80 ESBL-Ec isolates (20 isolates each study group from the total

of 40, 101, 173 and 57 ESBL-Ec isolates in chicken flocks, farmers, rural and urban individuals,

respectively) to study the distribution of ESBL encoding genes across groups. In addition, to

assess the similarity of ESBL encoding genes between chicken and farmer isolates of the same

farm, we analyzed all pairs of ESBL-Ec from the 16 farms where both chicken and farmer were

phenotypically ESBL-positive (‘matched isolates’). We used discriminant analysis of principal

components (DAPC) to compare overall antimicrobial resistance gene profiles distribution, not

limited to ESBL genes, between the different study groups [17].

The prevalence of colonization with ESBL-Ec was adjusted for the stratified survey design by

assigning a stratum-specific sampling weight (Supplementary Material 2).

We built a logistic regression model to investigate risk factors associated with the outcome

presence of phenotypically positive ESBL-Ec among all human participants (Supplementary

Material 4). Based on their biological plausibility and a p-value < 0.15 in the univariable

analyses, variables were considered for multivariable analysis and were included using a step-

wise forward approach [18]. Variables were retained in the final models if their p-value was <

0.05. All interactions between final significant variables were tested. All statistical analyses were

performed using R packages ‘epicalc’, ‘survey’ and ‘adegenet’ (http://www. r-project.org).

Results

Prevalence of colonization with ESBL-Ec in chickens and humans

Among 510 enrolled human participants, the median age was 46 [interquartile range 39 – 54

years] and 63.9% were male. The adjusted prevalence of ESBL-Ec colonization was 20.0% in

chicken farms, 31.1% in chicken farmers, 49.5% in rural individuals and 38.3% in urban

individuals (Table 1)

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Table 1. Prevalence of colonization with ESBL-producing Escherichia coli in chickens and humans in southern Vietnam

Subject Number of ESBL-Ec positive subjects (Prevalence; %)

Adjusted Prevalence (95% CI)

Chicken (N=204) 30 (14.7) 20.0 (10.8 – 29.1) Farmer (N=204) 65 (31.9) 31.1 (24.3 – 37.8) Rural (N=204) 101 (49.5) 49.5 (42.6 – 56.4) Urban (N=102) 39 (38.2) 38.3 (28.8 – 47.7)

Risk factors associated with ESBL-Ec colonization in humans

Chicken farmers were at lower risk of colonization with ESBL-Ec than rural individuals not

involved in poultry farming (OR= 0.46; 95% CI= 0.30 – 0.70) (Table 2). However, human usage

of any antimicrobial drug during the month prior to the study visit was associated with ESBL-Ec

colonization in humans (OR= 2.1; 95% CI= 0.97 – 4.55).

Table 2. Risk factor analyses for colonization with ESBL-producing Escherichia coli in human individuals (N=510) in southern Vietnam

aIntercept: - 0.068 (SEM±0.14) bnot involved in chicken farming cduring the month prior to the study visit

Distribution of ESBL genes and other antimicrobial resistance genes among ESBL-Ec

Microarray analysis of 80 randomly selected ESBL-Ec isolates demonstrated that CTX-M,

including CTX-M-1 group and CTX-M-9 group, was the predominant gene, found in 16/20

(80.0%) of chicken- and 60/60 (100%) of human isolates (Table 3). In 4 chicken ESBL-Ec

isolates, no ESBL gene could be detected by our microarray. Distribution of CTX-M genes

across isolates from farmers and unexposed individuals was similar. However, distribution of

CTX-M genes across chicken and human isolates was different. CTX-M-1 group genes were

commonly prevalent in both chicken (12/20, 60.0%) and human isolates (24/60, 40.0%), whilst

Variable Total number of participants

No. of ESBL-Ec positive participants

ORa 95% CI p-value

Participant group Rural individualb 204 101 ref ref ref Urban individualb 102 39 0.64 0.39 – 1.04 0.07 Chicken farmer 204 65 0.46 0.30 – 0.70 <0.001 Use of any antimicrobial drugsc 34 18 2.1 0.97 – 4.55 0.061

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CTX-M-9 group genes were more prevalent in isolates from humans (37/60, 61.7% versus 4/20,

20.0%) (p<0.05). One isolate from a chicken farmer was positive with both CTX-M-1 group and

CTX-M-9 group ESBL genes.

Table 3. Distribution of CTX-M genes in ESBL-producing Escherichia coli from chickens, farmers and individuals not involved in poultry farming in southern Vietnam

CTX-M group/gene

No. of chicken isolates (%)

No. of farmer isolates (%)

No. of rural individuals isolates (%)

No. of urban individual isolates (%)

No. of humana isolates (%)

(N=20) (N=20) (N=20) (N=20) (N=60) CTX-M-1 group 12 (60.0) 6 (30.0) 10 (50.0) 8 (40.0) 24 (40.0) CTX-M-15 0 2 (10.0) 8 (40.0) 6 (30.0) 16 (26.7) CTX-M-55 12 (60.0) 4 (20.0) 2 (10.0) 2 (10.0) 8 (13.3) CTX-M-9 group 4 (20.0) 15 (75.0) 10 (50.0) 12 (60.0) 37 (61.7) CTX-M-14 1 (5.0) 1 (5.0) 2 (10.0) 0 0 CTX-M-27 2 (10.0) 13 (65.0) 8 (40.0) 12 (60.0) 33 (55.0) CTX-M-65 1 (5.0) 0 0 0 0 Novel CTX-Mb 0 1 (5.0) 0 0 0

a Humans including farmers, rural and urban individuals b The DNA sequence of this novel gene differed from CTX-M-27 by one amino acid (Q7L).

A total of 76 PCR amplicons were DNA-sequenced to identify the specific CTX-M variants and

the results are shown in Table 3. Among CTX-M-1 group isolates, CTX-M-55 was the only

variant found in chicken isolates whereas two variants of the CTX-M-1 group, both CTX-M-55

and CTX-M-15, were detected in 24 human isolates. Among CTX-M-9 group isolates, CTX-M-

27 was the most prevalent variant detected in human isolates, followed by CTX-M-14 and CTX-

M-65. One novel variant within the CTX-M-9 group was identified from a farmer.

The distribution of other antimicrobial resistance genes in ESBL-Ec isolated from farmers, rural

individuals and urban individuals, as detected by microarray, is shown in the Supplementary

Material 5. The DAPC of antimicrobial resistance gene profiles, including all antimicrobial

resistance genes detected by microarray, indicated similarity between isolates from human

sources (Figure 1). Isolates from chickens exhibited profiles that were overall distinct from those

from the human groups. However, ESBL-Ec in urban population was most distinct and the

genotypes of the chicken isolates were closer to the rural and farmer isolates than to isolates from

the urban population.

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Figure 1. Discriminant analysis of principle components of genotypic antimicrobial resistance profiles applied to 80 randomly selected ESBL-producing Escherichia coli isolates from chicken and humans in southern Vietnam

Characteristics of ESBL-Ec isolated from chicken and farmer on the same farm

On 16/204 farms (6.9%; 95% CI= 3.4 – 10.3%) ESBL-Ec were detected phenotypically in both

the farmers and their chickens. Microarray, PCR and sequencing results revealed that in 10

farms, isolates from chickens and farmers showed different ESBL genes. On three other farms,

ESBL genes could not be detected by microarray or by PCR for detection of any CTX-M gene,

in three isolates from chickens (farm 10, farm 12 and farm 13). Hence a comparison of ESBL

genes between the farmers and their chickens on these 3 farms was impossible. In the remaining

three farms (1.5%; 95% CI= 0 – 3.1%), ESBL genes of ESBL-Ec isolated from three farmers and

their chickens were identical (farm 3, farm 11 and farm 16, Table 4). However, analysis of genes

encoding for resistance against other classes of antimicrobial drugs showed differences between

chicken and farmer isolates in all three farms (Supplementary Material 5). In addition, multi-

locus sequence typing of these isolates showed identical sequence types for chicken and farmer

isolates in one of these three farms only (farm 11, Table 4)

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Table 4. Comparison of ESBL-producing Escherichia coli isolated from farmer and chicken on the same farm

a These isolates showed different antimicrobial resistance phenotype NT: Non-typeable NI: Non-identified Underlining depicts identical ESBL genes and sequence type of ESBL-Ec isolated from chicken and farmer on the same farm

Farm Subject Isolate Number Sequence Type

ESBL gene Other resistance genes

1 Chicken 1 156 CTX-M-55 TEM, aadA1, strB, mrx, tetA, dfrA12, dfrA14, sul2, sul3 Farmer 1a 38 CTX-M-27 strB, mrx, tetA, dfrA17, sul1, sul2 Farmer 2a 38 CTX-M-27 strA, strB, mrx, tetA, dfrA17, sul1, sul2

2 Chicken 1 206 CTX-M-55 TEM, aadA1, aadA2, aadA4, qnrS, tetA, cmlA1, floR, dfrA12, sul1, sul3 Farmer 1 131 CTX-M-14 blaACC, TEM, strA, strB, mphA, mrx, tetA, dfrA17, sul1, sul2

3 Chicken 1 NT CTX-M-55 qnrS, tetA, floR Farmer 1a 155 CTX-M-55 TEM, aadA1, strB, qnrS, tetA, floR, dfrA14, dfrA17, sul2, sul3 Farmer 2a 155 CTX-M-55 TEM, aphA, aadA1, strA, strB, qnrS, tetA, floR, dfrA14, sul2, sul3

4 Chicken 1a 617 CTX-M-55 TEM, aphA, aadA1, aadA2, aadA4, tetM, cmlA1, floR, dfrA12, sul2, sul3 Chicken 2a 156 CTX-M-55 TEM, aac6-Ib, aadA1, strA, strB, tetA, tetB, catA, floR, catB3, sul1, sul2 Chicken 3a 1114 CTX-M-105 TEM, aphA, aadA1, strA, strB, tetA, floR, sul2, sul3 Farmer 1 38 CTX-M-27 TEM, strA, strB, ermB, mrx, tetA, dfrA17, sul1, sul2 Farmer 2 38 CTX-M-27 TEM, strA, strB, ermB, mrx, tetA, dfrA17, sul1, sul2

5 Chicken 1 349 CTX-M-55 aadA1, tetA, dfrA14, sul3 Farmer 1a 1163 CTX-M-27 TEM, ermB, mrx, tetB, dfrA17 Farmer 2a 1193 CTX-M-15 TEM, strB, mrx, tetA, dfrA17, sul2 Farmer 3a 1163 CTX-M-27 TEM, ermB, mrx, tetB, dfrA17, sul1

6 Chicken 1 448 CTX-M-55 aadA1, tetA, floR, dfrA14, sul3 Farmer 1 131 CTX-M-24 TEM, strB, mrx, tetA, dfrA17, sul1, sul2

7 Chicken 1 457 CTX-M-27 TEM, aphA, aadA1, strA, strB, ermB, catIII, cmlA1, dfrA14, sul2, sul3 Farmer 1 394 CTX-M-15 TEM

8 Chicken 1 NT CTX-M-14 TEM, aphA , tetA, floR, dfrA14, sul2, sul3 Farmer 1a 31 CTX-M-27 TEM, aadA1, ermB, mrx, tetA, catA, dfrA17, sul1 Farmer 2a 31 CTX-M-27 TEM, aadA1, mrx, tetA, catA, dfrA17 Farmer 3a 31 CTX-M-27 TEM, aadA1, ermB, mrx, tetA, catA, dfrA17, sul1

9 Chicken 1a 101 CTX-M-14 TEM, aphA, tetA, floR, dfrA14, sul2, sul3 Chicken 2a 101 CTX-M-55 TEM, aphA, aadA1, qnrS, tetA, tetM, floR, dfrA14, sul2, sul3 Farmer 1 NT CTX-M-27 strA, strB, ermB, mrx, tetA, dfrA12, sul1, sul2

10 Chicken 1 NT NI blaCMY, TEM, strA, strB, ermB, mrx, tetA, floR, dfrA17, sul1, sul2 Farmer 1 131 CTX-M-15 TEM, strA, strB, mrx, tetA, dfrA17, sul1, sul2

11 Chicken 1 226 CTX-M-65 TEM, aadA1, strB, mrx, tetA, cmlA1, floR, dfrA12, sul2, sul3 Farmer 1 226 CTX-M-65 aadA1, strA, strB, tetA, cmlA1, floR, dfrA12, sul2, sul3

12 Chicken 1 746 NI blaCMY, aadA1, aadA2, aadA4, tetA, catIII, cmlA1, floR, dfrA12, sul2, sul3 Farmer 1 69 CTX-M-27 mrx, tetA, dfrA17, sul2

13 Chicken 1 10 NI blaCMY, OXA-1, TEM, aadA1, aadB, strA, strB, tetA, floR, catB3, dfrA1, sul2 Farmer 1 131 CTX-M-15 OXA-1, aac6-Ib, mrx, tetA, dfrA17, sul1

14 Chicken 1 156 CTX-M-55 TEM, aphA, aadA1, tetA, floR, dfrA14, sul3 Farmer 1a 10 CTX-M-15 blaACC, TEM, aadA1, mphA, mrx, tetA, dfrA14, dfrA1, sul1, sul2 Farmer 2a 10 CTX-M-15 TEM, aadA1, mrx, tetA, dfrA14, sul2

15 Chicken 1 NT CTX-M-55 TEM, aphA, aadA1, strA, strB, qnrS, mrx, tetA, floR, dfrA14, sul2, sul3 Farmer 1 226 CTX-M-27 ermB, mrx

16 Chicken 1 162 CTX-M-55 TEM, strB, mrx, tetA, floR, dfrA17, sul2, sul3 Farmer 1 410 CTX-M-55 TEM, aphA, aadA1, strA, strB, tetA, floR, dfrA14, sul2, sul3

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Discussion

The prevalence of colonization with ESBL-Ec in chicken farms in Vietnam was almost 20%.

This prevalence is relatively low compared to the prevalence of colonization with ESBL-Ec in

chicken farms in other countries in Europe which range from about 40% to 100% [19-21]. Third-

generation cephalosporins usage in chickens was common in Europe [22]. The fact that we did

not find any cephalosporins usage in 204 chicken farms in our study (Supplementary Material 6)

is probably one of the explanations for the lower prevalence of colonization with ESBL-Ec in

chicken farms in our study. However, such comparisons should be interpreted with some caution

because the data were obtained in intensive farming settings in Europe as opposed to the

household and small-scale farm settings in Vietnam, and have used different sampling methods.

In contrast, the prevalence of colonization with ESBL-Ec in rural and urban individuals in this

study was much higher than reported for European countries [23] but was similar to the

prevalence of colonization with ESBL-Ec in the community in other Asian countries [24, 25].

This high prevalence of colonization with ESBL-Ec is in agreement with the high and

uncontrolled use of antimicrobial drugs in the community [11]. It probably have contributed to

ESBL-Ec colonization in chickens, for example through environmental contamination [26].

We did not find an apparent association between non-intensive chicken farming and ESBL-Ec

colonization in humans indicating that non-intensive chicken farming is not a major source of

ESBL-Ec colonization in humans in this setting. However, we observed an association between

antimicrobial use during the previous month and ESBL-Ec colonization; the risk of colonization

with ESBL-Ec was doubled among individuals who reported recent antimicrobial use. These

findings are in line with a recent publication where risk factors associated with faecal

colonization with ESBL-producing Enterobacteriaceae in healthy individuals were reviewed

[27].

Although cephalosporin usage was not reported in chicken farms, the prevalence of ESBL-Ec in

chickens was 20.0% (95% CI= 10.8 – 29.1). Therefore, we speculate that some human activities

or unknown practices, for example poor biosecurity or environmental contamination due to poor

sewage control [28], may contribute to ESBL-Ec colonization in chickens. However, it is not

necessarily through direct transmission of ESBL-Ec from humans to chickens or vice-versa, 98

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given the differences in sequence types and in resistance gene content between ESBL-Ec isolates

from the farmers and their chickens. Although we did not perform plasmid characterization, the

differences in antimicrobial resistance gene content also suggest that different plasmids are

potentially circulating in different host populations, concordant with the findings from a recent

study in northern Vietnam [29].

We are aware of the limitations of a cross-sectional study design, which precludes any inferences

on the dynamics of ESBL-Ec transmission between chickens and humans in Vietnam. In

addition, the number of isolates from chicken available for genotypic analyses was smaller than

expected due to the relatively low prevalence of colonization with ESBL-Ec in the chicken

farms. Despite these limitations, this study provides a comprehensive view on the prevalence of

colonization with ESBL-Ec in household-scale and small-scale chicken farms in the Mekong

Delta of Vietnam, and simultaneously sampled humans with and without direct chicken exposure

from the same geographic region. We found differences in prevalence of colonization with

ESBL-Ec in chickens and humans and this difference correlated with differences in usage of

cephalosporins. Antimicrobial usage thus emerged as the key factor that drives ESBL-Ec

colonization rather than direct transmission of ESBL-Ec from chicken to humans or vice versa.

Genotyping studies from the Netherlands support this notion, as whole genome sequencing from

chicken and human isolates with identical ESBL-genes showed clear differences between ESBL-

Ec from these different hosts supporting the hypothesis that ESBL-Ec selection is host specific

whilst horizontal gene transfer may contribute to the spread of resistance determinants [30].

Therefore, further studies are needed to compare E. coli populations in humans and chickens at

the whole genome level to better elucidate host specificity of ESBL-Ec colonization and the

drivers of horizontal gene transfer.

References

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2. Carattoli, A., Animal reservoirs for extended spectrum beta-lactamase producers. Clin Microbiol Infect,2008. 14 Suppl 1: p. 117-23.

3. Canton, R., et al., Prevalence and spread of extended-spectrum beta-lactamase-producingEnterobacteriaceae in Europe. Clin Microbiol Infect, 2008. 14 Suppl 1: p. 144-53.

4. Hawkey, P.M., Prevalence and clonality of extended-spectrum beta-lactamases in Asia. Clin MicrobiolInfect, 2008. 14 Suppl 1: p. 159-65.

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5. Levy, S.B., The 2000 Garrod lecture. Factors impacting on the problem of antibiotic resistance. JAntimicrob Chemother, 2002. 49(1): p. 25-30.

6. Lazarus, B., et al., Do human extraintestinal Escherichia coli infections resistant to expanded-spectrumcephalosporins originate from food-producing animals? A systematic review. Clin Infect Dis, 2015. 60(3):p. 439-52.

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8. Burgos S, et al., Characterization of poultry production systems in Vietnam. Int J of Poult Sci, 2007. 6(10):p. 709-712.

9. Nguyen, V.T., et al., Prevalence and risk factors for carriage of antimicrobial-resistant Escherichia coli onhousehold and small-scale chicken farms in the Mekong Delta of Vietnam. J Antimicrob Chemother, 2015.70(7): p. 2144-52.

10. Dyar, O.J., et al., High prevalence of antibiotic resistance in commensal Escherichia coli among childrenin rural Vietnam. BMC Infect Dis, 2012. 12: p. 92.

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12. Trung, N.V., et al., Non-Typhoidal Salmonella Colonization in Chickens and Humans in the Mekong Deltaof Vietnam. Zoonoses Public Health, 2016.

13. Anonymous. WHO Global Principles for the Containment of Antimicrobial Resistance in Animals Intendedfor Food. WHO, Geneva. 2000; Available from: http://www.who.int/foodsafety/publications/containment-amr/en/.

14. Dang, S.T., et al., Impact of medicated feed on the development of antimicrobial resistance in bacteria atintegrated pig-fish farms in Vietnam. Appl Environ Microbiol, 2011. 77(13): p. 4494-8.

15. Card, R., et al., Evaluation of an expanded microarray for detecting antibiotic resistance genes in a broadrange of gram-negative bacterial pathogens. Antimicrob Agents Chemother, 2013. 57(1): p. 458-65.

16. Hirai, I., et al., Characterization of Escherichia coli producing CTX-M-type extended-spectrum beta-lactamase carriage in healthy Vietnamese individuals. Antimicrob Agents Chemother, 2015.

17. Jombart, T., S. Devillard, and F. Balloux, Discriminant analysis of principal components: a new method forthe analysis of genetically structured populations. BMC Genet, 2010. 11: p. 94.

18. Hosmer, D., S. Lemeshow, and R. Sturdivant, Applied Logistic Regression. Third ed. 2004: Wiley.19. Smet, A., et al., Diversity of extended-spectrum beta-lactamases and class C beta-lactamases among

cloacal Escherichia coli Isolates in Belgian broiler farms. Antimicrob Agents Chemother, 2008. 52(4): p.1238-43.

20. Dierikx, C., et al., Extended-spectrum-beta-lactamase- and AmpC-beta-lactamase-producing Escherichiacoli in Dutch broilers and broiler farmers. J Antimicrob Chemother, 2013. 68(1): p. 60-7.

21. Costa, D., et al., Prevalence of extended-spectrum beta-lactamase-producing Escherichia coli isolates infaecal samples of broilers. Vet Microbiol, 2009. 138(3-4): p. 339-44.

22. Collignon, P., et al., Human deaths and third-generation cephalosporin use in poultry, Europe. EmergInfect Dis, 2013. 19(8): p. 1339-40.

23. Woerther, P.L., et al., Trends in human fecal carriage of extended-spectrum beta-lactamases in thecommunity: toward the globalization of CTX-M. Clin Microbio Rev, 2013. 26(4): p. 744-58.

24. Li, B., et al., High prevalence of CTX-M beta-lactamases in faecal Escherichia coli strains from healthyhumans in Fuzhou, China. Scand J Infect Dis, 2011. 43(3): p. 170-4.

25. Sasaki, T., et al., High prevalence of CTX-M beta-lactamase-producing Enterobacteriaceae in stoolspecimens obtained from healthy individuals in Thailand. J Antimicrob Chemother, 2010. 65(4): p. 666-8.

26. Guenther, S., C. Ewers, and L.H. Wieler, Extended-Spectrum Beta-Lactamases Producing E. coli inWildlife, yet Another Form of Environmental Pollution? Front Microbiol, 2011. 2: p. 246.

27. Karanika, S., et al., Fecal Colonization With Extended-spectrum Beta-lactamase-ProducingEnterobacteriaceae and Risk Factors Among Healthy Individuals: A Systematic Review and Metaanalysis.Clin Infect Dis, 2016. 63(3): p. 310-8.

28. Van Minh, H., et al., Assessing willingness to pay for improved sanitation in rural Vietnam. Environ HealthPrev Med, 2013. 18(4): p. 275-84.

29. Ueda, S., et al., Limited transmission of bla(CTX-M-9)-type-positive Escherichia coli between humans andpoultry in Vietnam. Antimicrob Agents Chemother, 2015. 59(6): p. 3574-7.

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30. de Been, M., et al., Dissemination of cephalosporin resistance genes between Escherichia coli strains fromfarm animals and humans by specific plasmid lineages. PLoS Genet, 2014. 10(12): p. e1004776.

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Supplementary Material 1: Questionnaire to study antimicrobial use in humans in Tien Giang province, Vietnam

Name of interviewer: [_________________________________]

Interview date (dd/mm/yy) : [__|__]/[__|__]/[__|__]

We are conducting a study to investigate medicines used by Tien Giang farmers for their chickens and for their own health. You have received information about our study and you have agreed to participate. You gave us information on your medicine use for your chicken. We would now like to ask you some questions about your experience in the use of medicines for your own health and the health of your family members. For example, which medicines do you use, when and why.

Do you agree to do the interview now?

A. GENERAL INFORMATION 1. Age of respondent: [__|__] 2. Gender: Male Female 3. This question NOT APPLICABLE for chicken farmers.

Are there any animal species (not poultry) in your household now? Yes No If Yes, tick all that apply Pig Cattle/buffalo Dog Cat Fish Other

4. Who live in your household?No Relationship of family/household member with the

respondent 1. The respondent 2. Respondent’s partner3. Child (3A for child 1, 3B for child 2 and so on –from oldest to youngest) 4. Mother/Father5. Grandparents 6. Others (6A. Son/daughter-in-law, 6B. Grandchildren, 6C. other )

Age (in years, if less than 1 year

old, write 01)

Gender 1 - Male 2 - Female

Tick if the person was sampled

1 [_0|1_] [__|__] [__|__] [__]

2 [__|__] [__|__] [__|__] [__]

3 [__|__] [__|__] [__|__] [__]

4 [__|__] [__|__] [__|__] [__]

5 [__|__] [__|__] [__|__] [__]

6 [__|__] [__|__] [__|__] [__]

7 [__|__] [__|__] [__|__] [__]

8 [__|__] [__|__] [__|__] [__]

9 [__|__] [__|__] [__|__] [__]

10 [__|__] [__|__] [__|__] [__]

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B. MEDICINE REVIEW (ANTIBIOTIC USAGE ONLY) 5. What medicines does your family use to treat illnesses or to stay healthy? Do you keep them in a medicine cabinet? Can we see them?

a. Medicines seen: Yes No b. Antibiotics present: Yes No Don’t know c. Please fill in the following table starting with the antibiotics present in the cabinet, describe them in detail as well as the member in

your family treated with those. Then continue listing any other antibiotic not present in the cabinet used by your family member over the last month

Antibiotic

(commercial name) Present

in the cabinet

1.Yes

2.No

Commercial presentation

(Use code *)

Active ingredient per unit

(g or mg)

Who used the

antibiotic

(Use code**)

Illness

(Use code +)

How long ago was the last usage?

(Use code#)

How many units

per day?

Duration

(How many days)

Whose advice

(Use code ++)

1. [____] [__|__] [__|__] [____] [____] [__] [__|__] [__]

2. [____] [__|__] [__|__] [____] [____] [__] [__|__] [__]

3. [____] [__|__] [__|__] [____] [____] [__] [__|__] [__]

4. [____] [__|__] [__|__] [____] [____] [__] [__|__] [__]

5. [____] [__|__] [__|__] [____] [____] [__] [__|__] [__]

6. [____] [__|__] [__|__] [____] [____] [__] [__|__] [__]

7. [____] [__|__] [__|__] [____] [____] [__] [__|__] [__]

8. [____] [__|__] [__|__] [____] [____] [__] [__|__] [__]

9. [____] [__|__] [__|__] [____] [____] [__] [__|__] [__]

10. [____] [__|__] [__|__] [____] [____] [__] [__|__] [__]

Codes Lists: *: T: Tablet; C: capsules; SY: syrup; D: drops; I: injection; SA: sachets; SU: suppositorium; P: pomade (cream) **: 1.Respondent, 2. Respondent’s partner, 3. Child (3A for child 1, 3B for child 2 and so on – from oldest to youngest), 4.

Parents or Grandparents, 5. Others +: R: Respiratory symptoms/infections; G: Gastrointestinal symptoms/infections; M: Mouth and teeth symptoms/infections; S: wound/skin symptoms/infections; G: General malaise symptoms/infections; O: other symptoms/infections specify.#: 1. still used, 2. 1-7 days ago, 3. 1-4 weeks ago, 4. More than 1 month ago 5. Not use this antibiotic yet

++: 1. Drug sellers; 2. Doctor/Health professionals; 3. Friend/neighbor 4. Others

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C. EATING HABITS

6. How often do you eat chicken meat (include any dish with chicken)? (tick 1 only) Everyday or almost every day

3-4 times per week

1-2 times per week

2-3 times per month

Less than 2 times per month

Never

7. This question ONLY APPLICABLE for chicken farmersOf all chicken meat you eat (include eating out), please choose the statement that better reflects your situation (tick 1 only).

All of the chicken meat I eat is not reared in my farm Most of the chicken meat I eat comes from outside and some of it is reared in my farm Some of the chicken meat I eat comes from outside and some of them is reared in my farm Most of the chicken meat I eat comes from my farm and a some of it comes from outside All of the chicken meat I eat comes from my farm

8. How often do you eat chicken eggs (include any dish with eggs)? (tick 1 only) Everyday or almost every day 3-4 times per week 1-2 times per week 2-3 times per month Less than 2 times per month Never

9. This question ONLY APPLICABLE for chicken farmersOf all chicken eggs you eat (include eating out), please choose the statement that better reflects your situation (tick 1 only)

All of the chicken eggs I eat come from outside Most of the chicken eggs I eat come from outside and some of them are produced in my farm Some of the chicken eggs I eat come from outside and some of them are produced in my farm Most of the chicken eggs I eat come from my farm and some of them come from outside All of the chicken eggs I eat come from my farm

10. Source of water (tick all that apply)

Municipal supply Borehole/well Rain water

Pond River/stream/canal other, specify________________

11. Distance to the closest running water sources (in meter) [__|__|__|__|__]

D. QUESTION

12. Do you have any questions or comments? Yes No[_____________________________________________________________________] [_____________________________________________________________________]

Thank you, this is the end of the interview.

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Supplemental Material 2

Materials and Methods

Collection of antimicrobial usage data Data on human antimicrobial drug usage during the month prior to the study visit, including the product’s commercial name, packaging format, dosage, and duration of usage, was collected for all participants as well as for all household members by medicine cabinet surveys, using a structured questionnaire containing both open and closed questions (supplementary material 1). Data on antimicrobial usage for chickens was similarly collected during interviews with the farmers, using a questionnaire as published previously (1). The medicine cabinet survey has been shown to be efficient in getting data on antimicrobial drugs usage in the community (2). Usage of an antimicrobial drug was defined as the reported usage in the previous month and/or the presence of the antimicrobial drug in the medicine cabinet. All questionnaires were administered by staff from Sub-Department of Animal Health and Preventive Medicine Center in Tien Giang for chicken and human antimicrobial usage, respectively. PCR and sequencing of ESBL genes

Table 1: PCR and sequencing primers for detection of ESBL genes

Gene Name Sequence

CTX-M-1 CTX-M-1_seq_F1 5'-TCGTCTCTTCCAGAATAAGGA-3'

CTX-M-1_seq_F2 5'-GACGATGTCACTGGCTGAGC-3'

CTX-M-1_seq_R1 5'-GTTTCGTCTCCCAGCTGTC-3'

CTX-M-1_seq_R2 5'-AAACGGAATGAGTTTCCCCAT-3'

CTX-M-9 CTX-M-9_seq_F1 5'-CTGATGTAACACGGATTGACC-3'

CTX-M-9_seq_F2 5'-TGCAGTACAGCGACAATACC-3'

CTX-M-9_seq_R1 5'-AAAAGCCGTCACGCCTCC-3'

CTX-M-9_seq_R2 5'-CGTGATCTGATCCTTCAACTC-3'

TEM TEM_seq_F1 5'-CAATAACCCTGRTAAATGCTTCAA-3'

TEM_seq_F2 5'-TGGCATGACAGTAAGAGAATTAT-3'

TEM_seq_R1 5'-TCCTCCGATCGTTGTCAGAA-3'

TEM_seq_R2 5'-CAATCTAAAGTATATATGAGTAAACT-3'

ESBL gene families detected from the array were further characterized using PCR amplification and sequencing (see Table 1 for primers used). Sequences were obtained using the BigDye Terminator V.1.1 Cycle Sequencing Kit (Applied Biosystems, USA). Sequence data were analysed using Codoncode Aligner 1.3.4 (CodonCode Corporation, Dedham, MA). The sequences obtained were compared to those registered in GenBank and present in the ESBL database at http://www.lahey.org/studies/.

Adjustment of prevalence estimates for stratified study design

Since the study was designed as a stratified survey with a fixed number of farms and participants in each stratum, not all the study units (farms and participants in the 3 districts) had the same probability of being selected. The prevalence of fecal colonization with mcr-1–carrying bacteria in chickens and humans was adjusted for the stratified survey design by assigning a stratum-specific sampling weight (Wi) to each observation unit (farm or subject) and then by using the following equation: Wi = NT/Ni, where NT = the

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total number of chicken farms or humans in that study district and Ni = the number of farms or participants in each stratum sampled (i = 1. . .7) (Technical Appendix Tables 1 and 2). Standard errors were corrected to calculate the prevalence in each stratum. Sampling weight and sampling fraction of participants belonging to each study stratum were calculated under the assumption that chicken farmers accounted for 80% of the rural population.

Table 2. Sampling weight and sampling fraction of chicken farms, Tien Giang province, Vietnam, 2012–2013*

Stratum NT† Ni Fraction that should be sampled Fraction sampled Wi Chau Thanh household farm 10,762 34 0.3697 0.00117 317 Cho Gao household farm 16,101 34 0.5532 0.00117 474 My Tho household farm 2,026 34 0.0696 0.00117 60 Chau Thanh small farm 36 34 0.0012 0.00117 1 Cho Gao small farm 147 34 0.0051 0.00117 4 My Tho small farm 34 34 0.0012 0.00117 1 *Ni, no. of farms sampled per stratum; NT, no. of farms per stratum; Wi, sampling weight. † Tien Giang statistical office (3)

Table 3. Sampling weight and sampling fraction of participants, Tien Giang province, Vietnam, 2012–2013*

Stratum NT† Ni Fraction that should be sampled Fraction sampled Wi My Tho, rural 16,621 68 0.027 0.000111 244 My Tho, farmer 66,486 68 0.108 0.000111 978 Chau Thanh, rural 46,067 68 0.075 0.000111 677 Chau Thanh, farmer 184,266 68 0.301 0.000111 2,710 Cho Gao, rural 33,594 68 0.055 0.000111 494 Cho Gao, farmer 134,375 68 0.219 0.000111 1,976 My Tho, urban 131,650 102 0.215 0.000166 1,291 *Ni, no. of farms sampled per stratum; NT, no. of farms per stratum; Wi, sampling weight. † Tien Giang statistical office (3)

References

1. Nguyen VT, Carrique-Mas JJ, Ngo TH, Ho HM, Ha TT, Campbell JI, Nguyen TN, Hoang NN,Pham VM, Wagenaar JA, Hardon A, Thai QH, Schultsz C. 2015. Prevalence and risk factors forcarriage of antimicrobial-resistant Escherichia coli on household and small-scale chicken farms inthe Mekong Delta of Vietnam. J Antimicrob Chemother 70:2144-2152.

2. WHO. 2004. How to investigate the use of medicines by consumers.http://www.who.int/drugresistance/Manual1_HowtoInvestigate.pdf. Accessed

3. Anonymous. Statistical Office of Tien Giang Province. Statistical YearBook Tien Giang Province2011. Statistical Printing Factory, Ho Chi Minh city, Vietnam, 2012.

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Supplemental Material 3: Full list of genes included in the AMR-08 microarray No Probe Antibiotic Gene 1 hp_aac6_611 Aminoglycoside aac6'-Ib 2 hp_aac6_612 Aminoglycoside aac6'-Ib 3 hp_aac6_613 Aminoglycoside aac6'-Ib 4 hp_aac6_615 Aminoglycoside aac6'-Ib 5 hp_aac6_617 Aminoglycoside aac6'-IIc 6 hp_aadB-2_611 Aminoglycoside aadB 7 hp_aadB_611 Aminoglycoside aadB 8 hp_aphA_611 Aminoglycoside aac6'-aph2' 9 hp_armA_611 Aminoglycoside armA 10 hp_npmA_611 Aminoglycoside npmA 11 hp_rmtC_611 Aminoglycoside rmtC 12 prob_aac3IVa_1 Aminoglycoside aac3-IVa 13 prob_aac3Ia_1 Aminoglycoside aac3-Ia 14 prob_aac6Ib_1 Aminoglycoside aac6'-Ib 15 prob_aadA1_1 Aminoglycoside aadA1-like 16 prob_aadA2_1 Aminoglycoside aadA2-like 17 prob_aadA4_1 Aminoglycoside aadA4-like 18 prob_ant2Ia_1 Aminoglycoside aadB 19 prob_strA_611 Aminoglycoside strA 20 prob_strB_611 Aminoglycoside strB 21 hp_blaCMY_611 Beta-lactam blaCMY 22 hp_blaCMY_612 Beta-lactam blaCMY 23 hp_blaKHM-1_611 Beta-lactam blaKHM 24 hp_blaMOX-CMY9_613 Beta-lactam blaMOX, blaCMY 25 hp_ges-1_611 Beta-lactam blaGES 26 hp_gim1_611 Beta-lactam blaGIM-1 27 hp_imi3_611 Beta-lactam blaIMI3 28 hp_imp_611 Beta-lactam blaIMP 29 hp_imp_612 Beta-lactam blaIMP 30 hp_imp_613 Beta-lactam blaIMP 31 hp_imp_614 Beta-lactam blaIMP 32 hp_imp_615 Beta-lactam blaIMP 33 hp_imp_616 Beta-lactam blaIMP 34 hp_imp_617 Beta-lactam blaIMP 35 hp_kpc4_611 Beta-lactam blaKPC-4 36 hp_oxa_611 Beta-lactam blaOXA-23 37 hp_oxa_612 Beta-lactam blaOXA-40 38 hp_oxa_613 Beta-lactam blaOXA-48 39 hp_oxa_614 Beta-lactam blaOXA-51 40 hp_oxa_617 Beta-lactam blaOXA-58 41 hp_per1_611 Beta-lactam blaPER-1 42 hp_spm1_611 Beta-lactam blaSPM-1 43 hp_veb1_611 Beta-lactam blaVEB-1 44 prob_acc1_11 Beta-lactam blaACC-1 45 prob_acc2_11 Beta-lactam blaACC-1 46 prob_cmy_11 Beta-lactam blaCMY 47 prob_ctxM26_11 Beta-lactam blaCTX-M-26 48 prob_ctxM8_11 Beta-lactam blaCTX-M-8 49 prob_ctxM9_11 Beta-lactam blaCTX-M-9 50 prob_dha1_1 Beta-lactam blaDHA-1 51 prob_fox_11 Beta-lactam blaFOX 52 prob_mox_1pm Beta-lactam blaMOX 53 prob_oxa1_21 Beta-lactam blaOXA-1 54 prob_oxa2_11 Beta-lactam blaOXA-2 55 prob_oxa7_11 Beta-lactam blaOXA-7 56 prob_oxa9_11 Beta-lactam blaOXA-9 57 prob_pse1_1mm Beta-lactam blaPSE-1-like 58 prob_pse1_1pm Beta-lactam blaPSE-1-like 59 prob_shv1_11 Beta-lactam blaSHV 60 prob_tem1_1 Beta-lactam blaTEM 61 hpn_ampC_Eaer_611 Beta-lactam ampC (E. aerogenes) 62 hpn_blaCTXM1_611 Beta-lactam blaCTX-M-1 63 hpn_blaCTXM1_612 Beta-lactam blaCTX-M-1 64 hpn_blaCTXM1_613 Beta-lactam blaCTX-M-1 65 hpn_blaCTXM2_611 Beta-lactam blaCTX-M-2 66 hpn_blaMAL_611 Beta-lactam blaMAL

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67 hpn_blaOKP_A_611 Beta-lactam blaOKP 68 hpn_blaOKP_B_611 Beta-lactam blaOKP 69 hpn_cblA_611 Beta-lactam cblA 70 hpn_cepA_611 Beta-lactam cepA 71 hpn_blaNDM_612 Beta-lactam blaNDM 72 hpn_blaNDM_613 Beta-lactam blaNDM 73 hpn_cfxA_612 Beta-lactam cfxA 74 hpn_blaVIM_617 Beta-lactam blaVIM 75 hpn_blaVIM_618 Beta-lactam blaVIM 76 hpn_blaVIM_619 Beta-lactam blaVIM 77 hpn_blaVIM_620 Beta-lactam blaVIM 78 hpn_blaVIM_621 Beta-lactam blaVIM 79 hpn_blaVIM_622 Beta-lactam blaVIM 80 hpn_blaVIM_623 Beta-lactam blaVIM 81 hpn_blaVIM_624 Beta-lactam blaVIM 82 hpn_blaVIM_625 Beta-lactam blaVIM 83 hpn_blaVIM_626 Beta-lactam blaVIM 84 hpn_blaOXY_614 Beta-lactam blaOXY 85 hpn_blaOXY_615 Beta-lactam blaOXY 86 hpn_blaOXY_616 Beta-lactam blaOXY 87 prob_catA1_11 Chloramphenicol catA1 88 prob_catB8_12 Chloramphenicol catB8 89 prob_catIII_1 Chloramphenicol catA3 90 prob_cmlA1_11 Chloramphenicol cmlA1-like 91 prob_floR_11 Chloramphenicol floR-1 92 hpn_catB3_611 Chloramphenicol catB3-like 93 hp_ereA_611 Erythromycin ereA 94 hp_ereA_612 Erythromycin ereA 95 hp_ermB_611 Erythromycin ermB 96 hp_ermB_612 Erythromycin ermB 97 prob_intI1_1 Intergrase intl1 98 prob_intI2_11 Intergrase intl2 99 hp_mphA_611 Macrolide mphA

100 prob_qnr_11 Quinolone qnrA 101 hpn_qepA_612 Quinolone qepA 102 hpn_qepA_613 Quinolone qepA 103 hpn_qnrB_611 Quinolone qnrB 104 hpn_qnrB_612 Quinolone qnrB 105 hpn_qnrB_613 Quinolone qnrB 106 hpn_qnrB_614 Quinolone qnrB 107 hpn_qnrC_611 Quinolone qnrC 108 hpn_qnrS_611 Quinolone qnrS 109 hp_arr-1_611 Rifampin arr-1 110 hp_vatE_611 Streptogramin vatE 111 hp_vatE_612 Streptogramin vatE 112 prob_sul1_11 Sulfonamide sul1 113 prob_sul2_11 Sulfonamide sul2 114 prob_sul3_11 Sulfonamide sul3 115 hp_tetX_611 Tetracycline tetX 116 prob_tetA_11 Tetracycline tetA 117 prob_tetB_11 Tetracycline tetB 118 prob_tetC_11 Tetracycline tetC 119 prob_tetD_1 Tetracycline tetD 120 prob_tetE_11 Tetracycline tetE 121 prob_tetG_11 Tetracycline tetG 122 prob_tetG_12 Tetracycline tetG 123 hpn_tetM_Ecoli_611 Tetracycline tetM 124 hpn_tetQ_611 Tetracycline tetQ 125 prob_dfr12_11 Trimethoprim dfrA12 126 prob_dfr13_11 Trimethoprim dfrA13 127 prob_dfrA14_21 Trimethoprim dfrA14 128 prob_dfrA15_1 Trimethoprim dfrA15 129 prob_dfrA17_11 Trimethoprim dfrA17 130 prob_dfrA19_1 Trimethoprim dfrA19 131 prob_dfrA1_21 Trimethoprim dfrA01 132 prob_dfrA1_22 Trimethoprim dfrA01 133 prob_dfrA7_11 Trimethoprim dfrA07 134 prob_dfrA7_12 Trimethoprim dfrA07

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Supplementary Material 4: Univariable analyses for risk factors associated with ESBL-Ec colonization in humans (N=510)

Lower Upper No No. of ESBL (+) subject Total % OR 95%CI 95%CI P-value 1 Participant group

Chicken farmers 65 204 31.9% ref ref ref ref Rural individual not involved in chicken farming 101 204 49.5% 2.2 1.43 3.3 <0.001

Urban individual not involved in chicken farming 39 102 38.2% 1.4 0.83 2.28 0.22 2 Household location

Cho Gao district 71 170 41.8% 1.4 0.89 2.22 0.147 Chau Thanh district 61 170 35.9% ref ref ref ref

My Tho city 73 170 42.9% 1.6 1.02 2.52 0.043

3 Age of participant (median age was used asbreakpoint)

< 46 years old 100 248 40.3% 1 1 1 0.81

≥ 46 years old 105 262 40.1% ref ref ref ref 4 Male participant 140 326 42.9% 1.5 1 2.2 0.048 5 Presence of other animals 122 341 35.8% 0.6 0.39 0.83 0.004 6 Presence of pig(s) 32 104 30.8% 0.6 0.38 1 0.05

7 Participants that used cephalosporins in the past month 11 20 55.0% 2.1 0.79 5.41 0.14

8 Participants that used antimicrobials in the pastmonth 18 34 52.9% 2.1 0.98 4.31 0.056

9 Chicken meat consumption Often (at least twice/week) 35 91 38.5% 1.1 0.44 2.75 0.84

Sometimes (at least twice/month) 158 392 40.3% 0.9 0.39 2.07 0.81

Never 12 27 44.4% ref ref ref ref 10 Egg consumption

Often (at least twice/week) 86 222 38.7% 0.9 0.44 1.82 0.76 Sometimes (at least twice/month) 101 247 40.9% 0.9 0.46 1.83 0.79

Never 18 41 43.9% ref ref ref ref

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Supplemental Material 5: Distribution of some common resistance genes (including ESBL genes) in ESBL-Ec isolated from chickens and humans

Gene Antimicrobial No. of isolates (%) Chicken Farmer Rural individual Urban Humana (N=20) (N=20) (N=20) (N=20) (N=60)

blaCTX-M-1-group Beta-lactam 12 (60.0) 6 (30.0) 10 (50.0) 8 (40.0) 24 (40.0) blaCTX-M-9-group Beta-lactam 4 (20.0) 15 (75.0) 10 (50.0) 12 (60.0) 37 (61.7)

blaTEMb Beta-lactam 16 (80.0) 12 (60.0) 10 (50.0) 7 (35.0) 29 (48.3) blaOXA-1 Beta-lactam 0 (0) 1 (5.0) 4 (20) 1 (5.0) 6 (10.0) blaOXA-7 Beta-lactam 1 (5.0) 0 (0) 0 (0) 1 (5.0) 1 (1.7) blaCMY Beta-lactam 4 (20.0) 0 (0) 0 (0) 0 (0) 0 (0)

blaACC-1 Beta-lactam 0 (0) 6 (30.0) 4 (20.0) 4 (20.0) 14 (23.3) catA1 Chloramphenicol 2 (10.0) 0 (0) 7 (35.0) 1 (5.0) 8 (13.3)

cmlA1-like Chloramphenicol 4 (20.0) 1 (5.0) 2 (10.0) 1 (5.0) 4 (6.7) floR-1 Chloramphenicol 13 (65.0) 3 (15.0) 1 (5.0) 2 (10.0) 6 (10.0)

catB3-like Chloramphenicol 1 (5.0) 1 (5.0) 0 (0) 0 (0) 1 (1.7) tetA Tetracycline 17 (85.0) 13 (65.0) 12 (60.0) 11 (55.0) 36 (60.0) tetB Tetracycline 3 (15.0) 4 (20.0) 6 (30.0) 7 (35.0) 17 (28.3)

dfrA12 Trimethoprim 3 (15.0) 0 (0) 1 (5.0) 0 (0) 1 (1.7) dfrA14 Trimethoprim 14 (70.0) 3 (15.0) 2 (10.0) 2 (10.0) 7 (11.7) dfrA17 Trimethoprim 5 (25.0) 14 (70.0) 11 (55.0) 13 (65.0) 38 (63.3) dfrA19 Trimethoprim 0 (0) 1 (5.0) 1 (5.0) 1 (5.0) 3 (5.0) dfrA1 Trimethoprim 0 (0) 1 (5.0) 0 (0) 0 (0) 1 (1.7) sul1 Sulfonamide 3 (15.0) 10 (50.0) 6 (30.0) 9 (45.0) 25 (41.7) sul2 Sulfonamide 15 (75.0) 13 (65.0) 11 (55.0) 12 (60.0) 36 (60.0) sul3 Sulfonamide 13 (65.0) 2 (10.0) 2 (10.0) 0 (0) 4 (6.7)

ermB Erythromycin 3 (15.0) 9 (45.0) 7 (35.0) 12 (60.0) 28 (46.7) mphA Macrolide 0 (0) 8 (40.0) 4 (20.0) 5 (25.0) 17 (28.3) mrx Macrolide 8 (40.0) 15 (75.0) 14 (70.0) 16 (80.0) 45 (75.0) qnrS Quinolone 5 (25.0) 2 (10.0) 0 (0) 1 (5.0) 3 (5.0) aphA Aminoglycoside 5 (25.0) 3 (15.0) 3 (15.0) 1 (5.0) 7 (11.7) aac6 Aminoglycoside 0 (0) 0 (0) 1 (5.0) 0 (0) 1 (1.7)

aac6'-Ib Aminoglycoside 1 (5.0) 1 (5.0) 5 (25.0) 1 (5.0) 7 (11.7) aadA1-like Aminoglycoside 15 (75.0) 3 (15.0) 3 (15.0) 2 (10.0) 8 (13.3) aadA2-like Aminoglycoside 1 (5.0) 0 (0) 1 (5.0) 0 (0) 1 (1.7) aadA4-like Aminoglycoside 1 (5.0) 0 (0) 1 (5.0) 0 (0) 1 (1.7)

aadB Aminoglycoside 0 (0) 1 (5.0) 1 (5.0) 0 (0) 2 (3.3) strA Aminoglycoside 6 (30.0) 9 (45.0) 5 (25.0) 6 (30.0) 20 (33.3) strB Aminoglycoside 11 (55.0) 12 (60.0) 11 (55.0) 10 (50.0) 33 (55.0) arr-1 Rifampin 5 (25.0) 1 (5.0) 0 (0) 1 (5.0) 2 (3.3)

a: humans including farmers, rural and urban individuals

b: any blaTEM. Sequencing of a random selection of 24 microarray blaTEM-positive isolates, including 4 ESBL-Ec isolates from chickens which were negative for any of the ESBL genes present on the microarray, showed that 100% of blaTEM genes were encoding narrow-spectrum beta-lactamase (TEM-1). Further sequencing of blaTEM genes was then abandoned.

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Supplemental Material 6: Usage of antimicrobial drugs in chickens and humans in southern Vietnam

Class of antimicrobial Chickens,* no. (%), N = 204 Humans,† no. (%)

Farmer, N = 204 Rural, N = 204 Urban, N = 102 Any antimicrobial drug 118 (57.8) 33 (16.2) 32 (15.7) 17 (16.7) 1st generation cephalosporin 0 (0) 12 (5.9) 17 (8.3) 7 (6.9) 2nd generation cephalosporin 0 (0) 1 (0.5) 2 (1.0) 1 (1.0) 3rd generation cephalosporin 0 (0) 5 (2.5) 6 (2.9) 1 (1.0) Penicillins 32 (15.7) 11 (5.4) 6 (2.9) 5 (4.9) Polymyxins 39 (19.1) 0 (0) 0 (0) 0 (0) Macrolides 38 (18.6) 3 (1.5) 4 (2) 4 (3.9) Quinolones 19 (9.3) 2 (1.0) 2 (1.0) 1 (1.0) Lincosamides 4 (2.0) 1 (0.5) 0 (0) 1 (1.0) Aminoglycosides 18 (8.8) 1 (0.5) 0 (0) 0 (0) Chloramphenicol 0 (0) 1 (0.5) 0 (0) 0 (0) Phenicols 12 (5.9) 0 (0) 0 (0) 0 (0) Sulfonamides/trimethoprim 12 (5.9) 0 (0) 0 (0) 1 (1.0) Tetracyclines 51 (25.0) 0 (0) 0 (0) 1 (1.0) Pleuromutilins 1 (0.5) 0 (0) 0 (0) 0 (0)

*Use during the previous 3 months for household-scale farms (≥10–200 chickens) or for the current flock for small-scale farms (>200–2000 chickens).†Use during the month before the survey visit.

111

CHAPTER 7 ZOONOTIC TRANSMISSION OF THE MCR-1 COLISTIN RESISTANCE

GENE FROM NON-INTENSIVE POULTRY FARMS IN VIETNAM

CHAPTER 7

Chapter 7: Zoonotic transmission of the mcr-1 colistin resistance gene from non-intensive

poultry farms in Vietnam

Nguyen Vinh Trung 1,2,3, Sébastien Matamoros 1,2, Juan J Carrique-Mas 3,4, Nguyen Huu Nghia 3, Nguyen Thi Nhung 3, Tran Thi Bich Chieu 3, Ho Huynh Mai 5, Willemien van Rooijen 1, James Campbell 3,4, Jaap A.Wagenaar 6,7, Anita Hardon 8, Nguyen Thi Nhu Mai, 9 Thai Quoc Hieu 5, Guy Thwaites 3,4, Menno D de Jong 1, Constance Schultsz 1,2,3, Ngo Thi Hoa 2,3

1 Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands

2 Department of Global Health-Amsterdam Institute for Global Health and Development, The Netherlands (N V Trung MS, S Matamoros PhD, C Schultsz PhD)

3 Oxford University Clinical Research Unit, Centre for Tropical Medicine, Ho Chi Minh City, Vietnam

4 Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford, United Kingdom

5 Sub-Department of Animal Health, My Tho, Tien Giang, Vietnam

6 Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, The Netherlands

7 Central Veterinary Institute of Wageningen UR, Lelystad, The Netherlands

8 Center for Social Science and Global Health, University of Amsterdam, The Netherlands

9 Preventive Medicine Center, My Tho, Tien Giang, Vietnam

Emerg Infect Dis. 2017, 23(3):529-532

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Abstract

We investigated the consequences of colistin use in backyard chicken farms in Vietnam, for the

presence of mcr-1 in fecal samples from chickens and humans. Detection of mcr-1 in chicken

samples was associated with colistin use, whereas mcr-1-carrying bacteria in humans was

associated with exposure to mcr-1-positive chickens.

Keywords: colistin resistance, chicken, farmer, mcr-1, plasmid

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Introduction

Colistin resistance has emerged and has been increasing gradually [1]. In addition to the known

chromosomally mediated resistance mechanisms, a plasmid-mediated colistin resistance gene

named mcr-1 was discovered in China and subsequently elsewhere around the world [2, 3]. The

mcr-1 gene was first detected in Escherichia coli and Klebsiella pneumoniae isolated from pigs,

chicken, retail meat, pork and hospitalized patients, with the prevalence of 28% in chickens, in

China. The discovery of the mcr-1 gene was followed by a wealth of reports indicating its global

geographic spread; its presence on various plasmids in multiple bacterial species originating

from a variety of environmental and animal sources; and its likely circulation for at least several

decades [3].

Usage of colistin in animal production has been suggested as the most likely contributing factor

to the emergence of the mcr-1 gene [2]. However, unbiased studies that demonstrate an

epidemiological link between the use of colistin in agriculture and the prevalence of mcr-1

carrying bacteria in the community are lacking. Such studies require an integrated one-health

approach and are crucial for the design of interventions to control the spread of the mcr-1 gene

[4].

Whereas its use in humans is negligible [5], colistin is one of the most commonly used

antimicrobial drugs in animal production in Vietnam, including household farms [6] which are

common in developing countries worldwide and are characterized by low levels of investment

and bio-containment [7]. We investigated the consequences of colistin usage in such non-

intensive poultry farms for the prevalence of colonization with mcr-1 carrying bacteria and the

risk of onward transmission to humans by molecular epidemiological analyses in chickens, their

farmers and unexposed populations in a defined geographical area of southern Vietnam.

Methods

Study population

This study was performed as a part of a cross-sectional observational study of antimicrobial drug

usage and antimicrobial resistant E. coli colonization in household farms and the community [8].

The target population included non-intensive chicken farms and their farmers in three districts in 116

CHAPTER 7

Tien Giang province, representing approximately 45% of the total chicken population in the

Mekong Delta, southern Vietnam. A total of 204 chicken farms and 204 chicken farmers, defined

as an adult person (≥ 18 years old) responsible for raising the chickens, who were not

hospitalized in the previous 4 weeks, were randomly selected as described previously [8, 9]. In

brief, sampling was stratified by farm size (10 – 200 chickens, ‘household farms’; 201 – 2000

chickens, ‘small size farms’) and by district (My Tho city, Cho Gao district and Chau Thanh

district) (total 6 strata). The sample size was calculated based on requirements for determining

the prevalence of E. coli resistance against a number of different antimicrobials in each district.

Age- and sex-matched individuals who are not involved in poultry farming were randomly

selected from the same district as the farmers (N=204), as well as from the provincial capital

(N=102) using the population census provided by the Preventive Medicine Centre (PMC) in Tien

Giang [10].

Written informed consent was obtained from all participants prior to recruitment. The study was

approved by the Department of Health in Tien Giang, the Peoples’ Committee of Tien Giang

Province, and the Oxford University Tropical Research Ethics Committee (OxTREC, No.

48/11).

Data collection

Data on human antimicrobial drug usage during the month prior to the study visit, including the

product’s commercial name, packaging format, dosage, and duration of usage, was collected for

all participants as well as for all household members by medicine cabinet surveys, using a

structured questionnaire containing both open and closed questions (supplementary material 1).

Data on antimicrobial usage for chickens was similarly collected during interviews with the

farmers, using a questionnaire as published previously [8]. The medicine cabinet survey has been

shown to be efficient in getting data on antimicrobial drugs usage in the community [11]. Usage

of an antimicrobial drug was defined as the reported usage in the previous month and/or the

presence of the antimicrobial drug in the medicine cabinet. All questionnaires were administered

by staff from Sub-Department of Animal Health (SDAH) and PMC for chicken and human

antimicrobial usage, respectively.

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Sample collection

To avoid seasonal effects, farm and household visits were evenly distributed over the period of

March 2012 and April 2013. Faecal samples from chickens were collected using boot-swabs or

hand-held gauze swabs, as described previously [8]. These sampling methods yield a faecal

sample representative of the entire chicken population for each farm and thus do not provide

information on individual chickens. Such a sampling approach is adequate given the limited

confinement of the chicken in the farms [8]. Rectal swab samples from human participants were

obtained using Faecalswab (Copan, Italy).

The sample collection was conducted by combined sampling teams from Tien Giang SDAH and

PMC. Samples were stored and transported at 4oC to the laboratory at the Oxford University

Clinical Research Unit in Ho Chi Minh City and cultured within 24 hours after collection.

Sample analysis

Buffered peptone water (225 mL) was added to each chicken faecal sample in different container

and was manually shaken. A volume of 1 mL from each container was diluted 1:1000 in saline

solution. Human rectal swabs were vortexed to release and suspend the sample in the liquid

transport medium and then 100 µL was diluted 1:100 in saline solution. This dilution resulted in

growth of >100 separate colonies after a volume of 50 µL of each diluted sample was plated onto

MacConkey agar without and supplemented with nalidixic acid [16 mg/L], ceftazidime [2 mg/L],

and gentamicin [8 mg/L], and incubated overnight at 370C. A sweep from the full growth was

collected and stored in glycerol at - 20oC, after, five randomly selected E. coli-like colonies from

MacConkey agar without antimicrobials and two from each of three antimicrobial-supplemented

agars, were picked and sub-cultured for identification and antimicrobial susceptibility testing

(AST). AST was performed using disc diffusion method in accordance with the Clinical and

Laboratory Standards Institute guidelines and breakpoints (supplementary material 2) [12]. From

each subject, all isolates with a unique phenotypic antimicrobial susceptibility pattern were

stored for further analyses.

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Detection of the mcr-1 gene

To assess the prevalence of the mcr-1 gene in faecal samples, all MacConkey sweep samples

were screened by conventional PCR as described previously [2]. The PCR-based mcr-1 gene

detection in a sweep sample is a targeted metagenomic approach to detect the gene within a

sample enriched for viable Gram-negative microorganisms. Positive control E. coli DNA and

negative controls were included in each run.

To subsequently confirm the presence of the mcr-1 gene in E. coli, we determined the presence

of the mcr-1 gene in 200 E. coli isolated from chickens and humans, which were randomly

selected from the total collection of 3160 stored E. coli isolates using PCR (supplementary

material 2). To detect a potential association of the mcr-1 gene with the presence of other

emerging resistance mechanisms, in particular the production of extended spectrum beta-

lactamases (ESBL), we additionally included 122 ESBL-producing E. coli isolates. These

included 38 ESBL-producing E. coli isolated from chickens, which is the total number of ESBL-

producing E. coli isolates found in chicken faecal samples in the study; and 84 ESBL-producing

E. coli isolated from human samples, randomly collected and stratified by human sampling

group. All mcr-1 positive E. coli isolates were tested for colistin susceptibility using E-test and

interpreted according to EUCAST breakpoints [13].

Characterization of mcr-1-positive E. coli isolates

Whole-genome sequencing was performed for all mcr-1 positive E. coli isolates. Bacterial DNA

was extracted from fresh pure cultures using either the Wizard Genomic DNA purification kit

(Promega, Madison, WI, USA) or the Qiagen DNeasy Blood and Tissue kit (Qiagen, Hilden,

Germany). Library preparation was done in accordance with the manufacturer’s instructions

(Illumina, San Diego, CA, USA) and sequenced using Illumina MiSeq technology with 150

paired-end settings. Data was cleaned and analysed using an analysis pipeline as described in the

Supplementary Material 2.

Data analyses

The prevalence of faecal colonization with mcr-1 carrying bacteria was adjusted for the stratified

survey design by assigning a stratum-specific sampling weight (supplementary material 2). 119

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We built logistic regression models to investigate risk factors associated with faecal colonization

with mcr-1 carrying bacteria in chicken farms and human participants. The list of variables that

were tested in the univariable analyses is shown in the Supplementary Material 3. Based on their

biological plausibility and a p value <0.15 in the univariable analyses, variables were considered

for multivariable analysis and were included using a step-wise forward approach [14]. Variables

were retained in the final models if the p-value was <0.05. All interactions between final

significant variables were tested. All statistical analyses were performed using R packages

‘epicalc’, ‘survey’ and ‘adegenet’ (http://www. r-project.org).

Results

Prevalence of faecal colonization with mcr-1 carrying bacteria

Of a total of 204 chicken faecal samples, collected from 204 farms, and of 510 human faecal

specimens, 188 and 440 MacConkey sweeps were available for mcr-1 screening by PCR,

respectively. The remaining sweep samples were either missing (16 chicken and 45 human

samples), were not available because the primary faecal culture on MacConkey agar did not

show any growth (7 human samples), or could not be tested because the culture after storage did

not show any growth (18 human samples). Characteristics of farms and human participants for

which a sweep sample was available were similar when compared to characteristics for farms

and participants without sweep sample (supplementary material 4).

The adjusted prevalence of faecal colonization with mcr-1 carrying bacteria was 59.4% (95% CI

47.9 – 71.0) in chicken faecal samples and 20.6% (95% CI 15.9 – 25.2) in human samples (Table

1), with much higher prevalence in farmers and rural individuals (25.2 and 17.6%, respectively)

than in individuals living in the city (9.1%). The adjusted prevalence for small scale and

household size farms was similar (Table 1).

Among 200 randomly selected E. coli isolates, mcr-1 was detected in 10/78 (12.8%) chicken E.

coli isolates, in 2/50 (4.0%) E. coli isolates from faecal samples of farmers and in none of 72 E.

coli isolates from non-farming individuals. Similarly, mcr-1 was detected in 9/38 (23.7%) and

1/44 (2.3%) of ESBL-producing E. coli isolated from chickens and farmers respectively.

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Table 1. Prevalence of faecal colonization with mcr-1-carrying bacteria in chicken and humans

in Tien Giang Province,Vietnam (2012 – 2013)

The usage of colistin

Colistin was used in 39/204 (19.1%) of the chicken farms. mcr-1 carrying bacteria were detected

in 23/39 (59.0%) chicken samples obtained from farms that used colistin compared with 70/149

(47.0%) of chicken samples from farms where colistin was not used (p=0.25). None of the

human participants reported the use of colistin (supplementary material 5)

Characterization of mcr-1 carrying isolates

The 22 mcr-1-carrying E. coli isolates all showed reduced susceptibility to colistin (MIC 3-4

mg/L) and belonged to 13 different sequence types (STs) as determined by MLST (Table 2). The

most frequent sequence type was ST156 including 5 isolates from chicken samples of 4 different

farms. SNPs-based phylogeny of the core genomes showed little genomic similarity between

isolates except for isolates belonging to the same MLST sequence type (Figure 1). Analysis of

the acquired resistance genes, reflecting the accessory genome, showed a large variation in

resistance gene content, with only the tet(A) gene, coding for tetracycline resistance, present in

all genomes (supplementary material 6). Carbapenemase-encoding genes were not detected.

The mcr-1 gene was located in genomic contigs (partially assembled plasmid sequences) which

sizes ranged from 2761 to 120156 bp (average: 31018 bp). No other antibiotic resistance genes

could be identified on the mcr-1 carrying contigs. A replication origin could be located for 5

Source Prevalence of faecal colonization with mcr-1-carrying bacteria

No of positive sweeps/ Total (%) Adjusted prevalence (95% CI)

All chicken farms 93/188 (49.5) 59.4 (47.9 – 71.0)

Household chicken farms 53/94 (56.4) 59.5 (47.9 – 71.1)

Small scale chicken farms 40/94 (42.6) 47.9 (35.4 – 60.3)

All human participants 84/440 (19.1) 20.6 (15.9 – 25.2)

All farmers 45/179 (25.1) 25.2 (18.3 – 32.0)

Farmer exposed to mcr-1-negative chicken 16/91 (17.6) 15.5 (7.7 – 23.3)

Farmer exposed to mcr-1-positive chicken 29/88 (33.0) 34.7 (23.9 – 45.5)

Rural persons 31/173 (17.9) 17.6 (11.6 – 23.7)

Urban persons 8/88 (9.1) 9.1 (3.1 – 15.1)

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contigs, allowing identification of the plasmid incompatibility groups IncHI2 (1 isolate), IncI2 (2

isolates), and combined IncHI2 and IncHI2A (2 isolates).

The sequence of the transposon ISAplI, initially described as carrying the mcr-1 gene, was

identified in 18 out of 22 contigs carrying the mcr-1 gene, with 100% similarity to the published

sequence [2].

Risk factors associated with faecal colonization with mcr-1 carrying bacteria

We investigated risk factors for faecal colonization with mcr-1 carrying bacteria separately for

small-scale and household farms since a joint model resulted in convergence. This convergence

was mainly due to the inflated sampling weight that was assigned to the household chicken

farms. Results of univariable analysis of risk factors are shown in supplementary material 3.

Multivariable analysis identified the presence of chicken less than 20.5 weeks old and the usage

of colistin as independent risk factors for faecal colonization with mcr-1-carrying bacteria in

chickens (OR=21.3 and OR=5.8, respectively) in small-scale farms (Table 2). We were unable to

identify the potential risk factor associated with faecal colonization with mcr-1 carrying bacteria

in household farms.

Among human participants, farmers who were exposed to mcr-1 positive chicken showed a

significantly increased risk of colonization with mcr-1-carrying bacteria (OR=5.3, Table 3)

compared to urban individuals not involved in chicken farming, in contrast to rural individuals

not exposed to chicken or farmers with mcr-1 negative chickens.

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Figure 1: Phylogenetic analyses of mcr-1-positive E. coli isolated from chicken farms and

farmers in Vietnam (2012 – 2013)

Maximum likelihood tree for 22 mcr-1-carrying E. coli isolated from 15 chicken faecal samples and 3 human faecal swab samples based on a

whole genome SNPs comparison using CSI Phylogeny 1.2, with E. coli SE15 as the reference strain. Red color indicates isolate from farmer; blue

color indicates isolates from chicken. A total of 74585 SNPs were concatenated for pairwise comparison (difference between pairs: 0 to 32267).

Branch length corresponds to the number of nucleotide substitutions per site. Corresponding multi-locus sequence types (ST) are indicated next to

the isolates’ names. Circles indicate isolates sharing the same ST. Isolates pairs CG05C.C1/CG05C.C2 (1 SNP difference),

CG48C.A2/CG48C.G2 (1 SNP and 1 antimicrobial resistance gene difference), CT48C.C1/CT48C.C2 (4 SNPs and 3 antimicrobial resistance

genes difference) and CT67C.C1/CT67C.C2 (0 SNPs difference) are phenotypically different but originate from the same sample and are

therefore likely to be highly related or identical.

Table 2. Risk factors associated with faecal colonization with mcr-1-carrying bacteria in small-

scale chicken farms (N = 94) and in humans (N = 440) in Vietnam (2012 – 2013)

*Intercept: - 2.15(SEM±0.57)

†Intercept: - 2.3(SEM±0.37)

‡ Not involved in poultry farming

Variables Number of subjects Number of mcr-1 positive subjects OR 95% CI p-value Small scale chicken farms (N = 94)* Age of the chickens

< 20.5 weeks old 47 32 21.3 5.8-78.5 <0.001 ≥ 20.5 weeks old 47 8 ref ref ref

Usage of colistin 21 14 5.1 1.4-18.8 0.017 Humans (N = 440)† Participant group

Urban persons‡ 88 8 ref ref ref Rural persons‡ 173 31 2.1 0.9-5.0 0.075

Farmers exposed to mcr-1 negative chicken 91 16 1.8 0.7-4.7 0.205 Farmers exposed to mcr-1 positive chicken 88 29 5.3 2.2 – 12.7 <0.001

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Discussion

We show that colonization with mcr1 carrying bacteria of chickens is associated with colistin

usage while colonization of humans is associated with exposure to mcr-1 positive chickens.

These findings suggest that the usage of colistin is the main driver for the observed very high

mcr-1 prevalence (59.4%) in faecal samples from chickens, with onward zoonotic transmission

explaining the high prevalence (25.2%) in farmers. While our cross-sectional study design may

preclude the demonstration of direct transmission of the mcr-1 gene between chickens and

humans, such transmission was reported for colistin resistant E. coli from a domesticated pig to

humans [15, 16] as well as between companion animals and humans [17].

We found that younger chickens were more likely to be colonized with mcr-1 carrying bacteria.

This observation may be explained by the more intensive usage of antimicrobial drugs in

younger chicken as indicated by the higher median of treatment incidence in young chickens

(74.0; IQR [0 - 278]) compared to older chickens (46.3; IQR [0 - 124]). However, our study was

insufficiently powered to detect such association in multivariable analysis. In addition, the

gastrointestinal tract of younger chickens may be colonized by antimicrobial resistant bacteria

more readily compared to older chickens [18]. Data from a previous study showed that the mcr-1

gene could be detected even in one-day-old chicks which suggests a possibility of vertical

transmission from chicken parent flocks [19].

The prevalence of mcr-1-carrying E. coli isolates ranged from 12.8% to 23.7% in chicken faecal

samples and from 2.3% to 4.0% in human samples. The lower detection rate of the mcr-1 gene in

E. coli isolates compared to sweep samples may indicate the presence of this gene in E. coli

strains other than those selected or bacterial species other than E. coli capable of growing on

MacConkey agar. The percentage of mcr-1-carrying E. coli isolates in chickens in our study was

similar to recently published data from Vietnam and China, but much higher than data from other

countries such as Japan (0%), France (1.8%) and Brazil (3.0%) [2, 20-22]. However, such

comparisons should be interpreted with caution because of differences in sample size and the

number of E. coli isolates selected per sample, as well as sampling methods.

Mcr-1-positive isolates in our study also carried multiple other resistance genes, including genes

encoding for extended-spectrum beta-lactamases (supplementary material 6). The proportion of 124

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isolates carrying mcr-1 gene among ESBL-producing E. coli was similar to a random selection

of E. coli (p=0.22), indicating that the mcr-1 gene is widespread among E. coli isolated from

chickens independent of the presence of ESBL genes.

We found that the mcr-1 gene was associated with at least three plasmid backbones belonging to

the incompatibility groups IncI2, IncHI2 and IncHI2A which were also discovered in previous

studies [2, 20, 23, 24]. The spread of the mcr-1 gene on different plasmid types might explain its

successful spread in different E. coli clones. Additionally, we identified the presence of the

ISApl1 transposon in 81.8% (18/22) of our isolates. As this genetic element is involved in

horizontal gene transfer [25] it is likely to be a key factor in explaining the presence of the mcr-1

gene in different plasmid types identified within a limited time frame in a restricted geographic

area.

Given the potentially serious consequences of the spread of the mcr-1 gene from food-producing

animals to humans and the association between usage of colistin in animals and the presence of

mcr-1, prudent usage of antimicrobial drugs in animal production should be enforced globally,

including in non-intensive farming settings such as ‘backyard’ farms, the most common farming

setting worldwide.

References

1. Olaitan, A.O., et al., Worldwide emergence of colistin resistance in Klebsiella pneumoniae from healthyhumans and patients in Lao PDR, Thailand, Israel, Nigeria and France owing to inactivation of thePhoP/PhoQ regulator mgrB: an epidemiological and molecular study. Int J Antimicrob Agents, 2014.44(6): p. 500-7.

2. Liu, Y.Y., et al., Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals andhuman beings in China: a microbiological and molecular biological study. Lancet Infect Dis, 2016. 16(2):p. 161-8.

3. Skov, R.L. and D.L. Monnet, Plasmid-mediated colistin resistance (mcr-1 gene): three months later, thestory unfolds. Euro Surveill, 2016. 21(9).

4. Schwarz, S. and A.P. Johnson, Transferable resistance to colistin: a new but old threat. J AntimicrobChemother, 2016. 71(8): p. 2066-2070.

5. The Center for Disease Dynamics, Economics and Policy (CDDEP). Available from:http://www.cddep.org/sites/default/files/vn_report_web_1_8.pdf.

6. Carrique-Mas, J.J., et al., Antimicrobial usage in chicken production in the Mekong Delta of Vietnam.Zoonoses Public Health, 2015. 62 Suppl 1: p. 70-8.

7. Conan, A., et al., Biosecurity measures for backyard poultry in developing countries: a systematic review.BMC Vet Res, 2012. 8: p. 240.

8. Nguyen, V.T., et al., Prevalence and risk factors for carriage of antimicrobial-resistant Escherichia coli onhousehold and small-scale chicken farms in the Mekong Delta of Vietnam. J Antimicrob Chemother, 2015.70(7): p. 2144-52.

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9. Trung, N.V., et al., Non-Typhoidal Salmonella Colonization in Chickens and Humans in the Mekong Deltaof Vietnam. Zoonoses Public Health, 2016.

10. Johnson, T.J., et al., Sequence analysis and characterization of a transferable hybrid plasmid encodingmultidrug resistance and enabling zoonotic potential for extraintestinal Escherichia coli. Infect Immun,2010. 78(5): p. 1931-42.

11. WHO. How to investigate the use of medicines by consumers. 2004; Available from:http://www.who.int/drugresistance/Manual1_HowtoInvestigate.pdf.

12. Dang, S.T., et al., Impact of medicated feed on the development of antimicrobial resistance in bacteria atintegrated pig-fish farms in Vietnam. Appl Environ Microbiol, 2011. 77(13): p. 4494-8.

13. Young, I., et al., Comparison of the prevalence of bacterial enteropathogens, potentially zoonotic bacteriaand bacterial resistance to antimicrobials in organic and conventional poultry, swine and beef production:a systematic review and meta-analysis. Epidemiol Infect, 2009. 137(9): p. 1217-32.

14. Hosmer, D., S. Lemeshow, and R. Sturdivant, Applied Logistic Regression. Third ed. 2004: Wiley.15. Olaitan, A.O., et al., Dissemination of the mcr-1 colistin resistance gene. Lancet Infect Dis, 2016. 16(2): p.

147. 16. Olaitan, A.O., et al., Clonal transmission of a colistin-resistant Escherichia coli from a domesticated pig to

a human in Laos. J Antimicrob Chemother, 2015. 70(12): p. 3402-4.17. Zhang, X.F., et al., Possible Transmission of mcr-1-Harboring Escherichia coli between Companion

Animals and Human. Emerg Infect Dis, 2016. 22(9).18. Smith, J.L., et al., Impact of antimicrobial usage on antimicrobial resistance in commensal Escherichia

coli strains colonizing broiler chickens. Appl Environ Microbiol, 2007. 73(5): p. 1404-14.19. Nguyen, N.T., et al., The use of colistin and other critical antimicrobials on pig and chicken farms in

southern Vietnam and their association with resistance in commensal Escherichia coli. Appl EnvironMicrobiol, 2016. 82(13): p. 3727-3735.

20. Suzuki, S., et al., Investigation of a plasmid genome database for colistin-resistance gene mcr-1. LancetInfect Dis, 2016. 16(3): p. 284-285.

21. Lentz, S.A., et al., Letter to the editor: Escherichia coli harbouring mcr-1 gene isolated from poultry notexposed to polymyxins in Brazil. Euro Surveill, 2016. 21(26).

22. Perrin-Guyomard, A., et al., Prevalence of mcr-1 in commensal Escherichia coli from French livestock,2007 to 2014. Euro Surveill, 2016. 21(6).

23. Falgenhauer, L., et al., Colistin resistance gene mcr-1 in extended-spectrum beta-lactamase-producing andcarbapenemase-producing Gram-negative bacteria in Germany. Lancet Infect Dis, 2016. 16(3): p. 282-283.

24. Tse, H. and K.Y. Yuen, Dissemination of the mcr-1 colistin resistance gene. Lancet Infect Dis, 2016. 16(2):p. 145-6.

25. Tegetmeyer, H.E., et al., ISApl1, a novel insertion element of Actinobacillus pleuropneumoniae, preventsApxIV-based serological detection of serotype 7 strain AP76. Vet Microbiol, 2008. 128(3-4): p. 342-53.

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CHAPTER 8 DISCUSSION

CHAPTER 8

Chapter 8: Discussion

Antimicrobial resistance (AMR) is increasing worldwide. The global trade and mobility of

persons facilitate the spread of resistant microorganisms and/or AMR determinants. There is a

longstanding debate on the attribution of the usage of antimicrobials in animals and the

subsequent increase of resistance determinants in the animal reservoir, to AMR in humans.

Given the increasing AMR burden in humans and the above debate, the project was initiated.

The majority of Vietnam’s population is living in the rural areas and around 40% of the

households engage in poultry raising. An approximately 94% of these households has a flock

size of 50 chickens or less [1, 2]. However, limited data on AMR in the chicken microbiome and

the association with AMR in the microbiome of the humans exposed to these animals are

available.

Non-typhoidal Salmonella (NTS) and E. coli were the bacteria of interest in this study. We have

chosen Salmonella because salmonellosis is a public health concern worldwide with poultry as a

major source for humans [3]. In addition, we also included E. coli since commensal E. coli are

considered as a reservoir for resistance genes and an indicator species for AMR surveillance [4,

5].

This is one of the first projects in Vietnam that used the One Health approach, with the

simultaneous collection of samples from chickens and farmers, as well as from location-, age-

and gender-matched humans without direct exposure to chickens.

High level of antimicrobial usage in both chicken farming and in the community

Data from Chapter 2 show that a wide range of antimicrobials from at least ten different

antimicrobial classes was used in poultry, with many of them also used in human medicine such

as quinolones and macrolides. In addition, antimicrobials were mainly used for prophylaxis

(84%) rather than therapeutic purposes.

Our results also show that the amount of antimicrobials used to produce one ‘meat’ chicken in

the Mekong delta was more than 6 times higher than in Europe [6]. Antimicrobial drug usage is

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unacceptably high in small-scale farms in southern Vietnam. In contrast to what was

hypothesized, back yard farming showed systematic usage of antimicrobial drugs and medicated

feed, probably similar to intensive farming practices.

Data obtained from human study participants, presented in Chapter 6, show that amongst 510

households, 82 households (16.1%) reported the use of antimicrobials by at least one member

during the month prior to the study visit. Antimicrobials were used in 33 (16.2%) of farmer

households, 32 (15.7%) of rural households and 17 (16.7%) of urban households. The three most

commonly used antimicrobials were cephalosporins (10.2%), penicillins (4.3%) and macrolides

(2.1%). The data in our study are consistent with other studies that have published about the use

of antimicrobials in humans in the community [7]. This is an obvious consequence of the lack of

an effective enforcement of the antimicrobial prescribing and dispensing laws which regulated

that antimicrobials should be prescribed by only clinicians or veterinarians.

High prevalence of colonization with antimicrobial resistant bacteria and antimicrobial

resistance determinants

Almost half of chicken farms in our study tested positive for non-typhoid Salmonella (NTS).

There was no statistically significant difference in the NTS farm-level prevalence between

household farms (46/102, 45.1%) and small farms (47/102, 46.1%). The prevalence of

asymptomatic NTS colonization in humans in our study is higher than the reported prevalence of

asymptomatic NTS in developed countries (0.3% – 0.4%) [8-10]. However, our findings were

comparable to other studies in the northern Vietnam (3.1%) [11] and Thailand (4.7%) [12].

Salmonella isolates in our study were commonly resistant to tetracycline, chloramphenicol,

trimethoprim-sulfamethoxazole and ampicillin. The results were similar to the results of another

survey also carried out in the Mekong Delta [13].

In general, the level of resistance was higher in E. coli compared to non-typhoidal Salmonella in

our study. MDR E. coli isolates (resistant to at least 3 different classes of antimicrobials) were

detected in 100% of the farms. The prevalence of antimicrobial resistant E. coli in these

backyard chicken farms was higher than expected since we did not expect so much of

antimicrobial use in backyard farms.

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Enteroaggregative E. coli (EAEC), an important cause of diarrhea, was studied in Chapter 5.

EAEC was only isolated from human faecal samples (3.3%, 15/458). These EAEC isolates

exhibited a high level of resistance in which 88.2% and 50.0% of the isolates were multi-drug

resistant and extended-spectrum beta-lactamase positive, respectively. The level of antimicrobial

resistance among EAEC isolates was also higher compared with results from other countries

[14].

As shown in Chapter 6, the prevalence of ESBL-Ec colonization was 20.0% in chicken farms,

31.1% in chicken farmers, 49.5% in rural individuals and 38.3% in urban individuals. This high

prevalence of human colonization with ESBL-Ec is in agreement with the high and uncontrolled

use of broad spectrum cephalosporins in the community [15]. However, the large difference in

prevalence between chicken and humans was unexpected and was related to the comparatively

low usage of cephalosporins in chicken.

In Chapter 7, we observed an extremely high prevalence of faecal colonization with mcr-1

carrying bacteria in chicken faecal samples (59.4%) as well as in human samples (20.6%). We

also noticed that the prevalence of faecal colonization with mcr-1 carrying bacteria in urban

individuals (9.1%) was much lower than in farmers and rural individuals (25.2 and 17.6%,

respectively). Our isolation rate of mcr-1-positive E. coli in chickens (approximately 20.0%) was

similar to previous published data from Vietnam and China [16, 17], but much higher than data

from other countries such as Japan (0%), France (1.8%) and Brazil (3.0%) [18-20].

Association of antimicrobial usage and colonization with antimicrobial resistant bacteria

and carriage of genomic antimicrobial resistance determinants

Data presented in Chapter 2 revealed the association of quinolones use and ciprofloxacin

resistant E. coli in chicken farms. Our findings are in line with other field studies that

demonstrated that the usage of quinolones selects for carriage of quinolone-resistant E. coli in

poultry [4, 21]. In addition, data from chapter 7 showed that the detection of a plasmid-mediated

colistin resistance encoding gene was associated with colistin use in chickens.

Results described in chapter 6 indicated that ESBL-Ec colonization was associated with the

recent usage of antimicrobial drug in humans. The findings are in line with a previous study

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where risk factors associated with faecal colonization with ESBL-producing Enterobacteriaceae

in healthy individuals were reviewed [22].

The risk of human colonization with antimicrobial resistant bacteria and carriage of

antimicrobial resistance determinants resulting from chicken farming

We initially hypothesized that exposure to chickens through farming results in higher risk of

asymptomatic colonization with antimicrobial resistant bacteria. However, although having

direct contact with chickens, farmers are not very likely to become a carrier of non-typhoidal

Salmonella (Chapter 2). There is a difference between the prevalence of NTS colonization in

farmers (4.4%) and general, unexposed individuals (2.6%), but the difference was not

statistically significant. In addition, among 204 studied farms, there is only 1 farm in which the

Weltevreden serovar is shared between chicken and farmer. Although in this study transmission

was not specifically investigated for resistant Salmonella, it seems unlikely that transmission of

resistant Salmonella would be different from susceptible Salmonella.

With regards to Enteroaggregative E. coli, our data in Chapter 5 suggest that there is little

transmission of EAEC from humans to chickens or that transmission does not lead to subsequent

colonization, since EAEC was detected only in human samples and not in chicken samples.

We did not find an association between non-intensive chicken farming and ESBL-Ec

colonization in humans in Vietnam (chapter 6) indicating that non-intensive chicken farming is

not a major source of ESBL-Ec colonization for humans in this setting. Data from chapters 4 and

6 suggest that resistance in E. coli in animals and humans is determined by the use of

antimicrobials in each of the specific domains: a relatively high prevalence of resistance to

fluoroquinolones in poultry due to the use of fluoroquinolones, and a higher resistance to 3rd

generation cephalosporines in humans compared to poultry due to use of this type of

antimicrobial in humans and hardly any use in poultry. Overall data suggest that the transfer

between animals and humans has restrictions resulting in different reservoirs in poultry and

humans.

However, in Chapter 7, we found that the risk of colonization with mcr-1-carrying bacteria was

significantly higher in farmers who were exposed to mcr-1 positive chickens than farmers with

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mcr-1 negative chickens or individuals not involved in chicken farming. The lack of human

colistin usage in the community and the association of mcr-1 presence with exposure to mcr-1

positive chicken suggest that mcr-1 transmission is predominantly zoonotic. This is, however, in

contrast to the conclusions from the other chapters. An additional factor that may play a role is

the exposure of farmers to colistin on farms when it is used for the animals. In that case, there is

not transfer of bacteria but a common exposure to colistin.

In summary, in our study, we found that bacterial transfer (e.g. NTS, EAEC) maybe limited

between humans and chickens. This observation could be the consequences of host adaptation. In

contrast, transmission of AMR determinants is extremely complex. It is likely to occur in

multiple directions, and may be restricted to certain AMR genes, AMR carrying mobile

elements, or bacterial clones, a.o. depending on the selective pressure exerted through

antimicrobial drug usage.

Limitations of the study

Our study is subject to several limitations. Firstly, the cross-sectional study design may preclude

the demonstration of direct transmission of the antimicrobial resistant bacteria and/or resistance

determinants between chickens and humans. Secondly, the number of non-typhoidal Salmonella

isolates from humans and the number of ESBL E. coli isolates from chickens was relatively

small, limiting the power to demonstrate any statistical difference between study cohorts. In

addition, results of antimicrobial usage reported in our study are likely to underestimate total

antimicrobial usage, since commercial feed commonly includes sub-therapeutic amounts of

antimicrobials (chlortetracycline, bacitracin and colistin). However, data on antimicrobials

added into animal feed were not precisely available.

The recommendations arising from the project

It is important to highlight that the epidemiological findings in this study might not applicable in

countries with different healthcare/farming settings, different access to antimicrobial drugs for

both humans and animals, as well as different level of antimicrobial resistance in the community.

Although there are large differences in antimicrobial drug legislation and regulation, policies for

antimicrobial usage among countries, the usage of antimicrobials in small-scale farming and in 132

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the community are unacceptable high in Vietnam. Given the potentially serious consequences of

the spread of antimicrobial resistance determinants (e.g. ESBL genes and plasmid-mediated

colistin resistance gene) between food-producing animals and humans as well as the association

between usage of antimicrobials and the prevalence of antimicrobial resistance, prudent usage of

antimicrobial drugs in the community and in agriculture should be enforced globally, especially

in a developing country such as Vietnam. Clearly, antimicrobial prescribing and dispending

practices need to be changed in both human and veterinary medicine in the country. In order to

implement that, enforcement needs to be improved for stricter regulation of over-the-counter

sales of antimicrobial drugs.

Given the low levels of investment and ‘bio-security’ in backyard chicken farms in Vietnam and

the fact that chickens and humans are living in almost the same environment, sharing of AMR

bacteria and/or resistance determinants between different hosts are possible (e.g. mcr-1 gene). As

a result, the first priority is that the level of ‘bio-containment’ on farms should be improved to

limit the conditions that release viable resistant bacteria and resistant determinants into the

surrounding farming and living environments.

The complexity of antimicrobial resistance deserves joint focus of multiple disciplines. While

collaboration between human and veterinary professions might be more common in other

countries, it is certainly not the case in Vietnam. Strengthening the collaboration between human

and animal health practitioners in southern Vietnam should be implemented in order to have

overall and thoughtful action plans to combat AMR in Vietnam. This project illustrated a typical

collaboration of the integrated “One-health” approach which involved both veterinarians as well

as medical healthcare workers in the province, encouraged knowledge exchanges and

understanding between different sectors.

Future research

This project assists us to identify important research aspects for the future. It is essential to

investigate (1) the relatedness of E. coli and Salmonella isolates that share the same sequence

types and the same phenotypic resistance patterns by using whole genome sequencing. This

high-resolution analysis is essential to understand the phylogenetic relationship between chicken

and human isolates; (2) the dynamics of antimicrobial resistance in chickens and humans based

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CHAPTER 8

on a longitudinal study. Since resistance development is a constant process a follow-up study

should be performed in such a way that we could contemporaneously capture as much as

possible the event (3) the role of farming environments in spreading antimicrobial resistant

bacteria and/or antimicrobial resistance determinants in chickens and humans. This is necessary

because antimicrobial resistant bacteria contamination and occurrence in the environment

contribute to the spread of resistant bacteria and/or resistance determinants.

References

1. PRISE. A general review and a description of the poultry production in Vietnam. 2008; Available from:http://orbi.ulg.ac.be/bitstream/2268/157619/1/2008_Review_Poultry_Prod_Vietnam.PDF.

2. Burgos S, et al., Characterization of poultry production systems in Vietnam. Int J of Poult Sci, 2007. 6(10):p. 709-712.

3. Majowicz, S.E., et al., The global burden of nontyphoidal Salmonella gastroenteritis. Clin Infect Dis, 2010.50(6): p. 882-9.

4. da Costa, P.M., et al., Field trial evaluating changes in prevalence and patterns of antimicrobial resistanceamong Escherichia coli and Enterococcus spp. isolated from growing broilers medicated withenrofloxacin, apramycin and amoxicillin. Vet Microbiol, 2009. 139(3-4): p. 284-92.

5. de Jong, A., B. Stephan, and P. Silley, Fluoroquinolone resistance of Escherichia coli and Salmonella fromhealthy livestock and poultry in the EU. J Appl Microbiol, 2011. 112(2): p. 239-45.

6. European Medicines Agency: Trends in the sales of veterinary antimicrobial agents in nine Europeancountries (2005-2009). 2011.

7. Nga do, T.T., et al., Antibiotic sales in rural and urban pharmacies in northern Vietnam: an observationalstudy. BMC Pharmacol Toxicol, 2014. 15(1): p. 6.

8. de Wit, M.A., et al., Sensor, a population-based cohort study on gastroenteritis in the Netherlands:incidence and etiology. Am J Epidemiol, 2001. 154(7): p. 666-74.

9. Hellard, M.E., et al., Prevalence of enteric pathogens among community based asymptomatic individuals. JGastroenterol Hepatol, 2000. 15(3): p. 290-3.

10. Nataro, J.P., et al., Diarrheagenic Escherichia coli infection in Baltimore, Maryland, and New Haven,Connecticut. Clin Infect Dis, 2006. 43(4): p. 402-7.

11. Do, T.T., et al., Epidemiology and aetiology of diarrhoeal diseases in adults engaged in wastewater-fedagriculture and aquaculture in Hanoi, Vietnam. Trop Med Int Health, 2007. 12 Suppl 2: p. 23-33.

12. Sirinavin, S., L. Pokawattana, and A. Bangtrakulnondh, Duration of nontyphoidal Salmonella carriage inasymptomatic adults. Clin Infect Dis, 2004. 38(11): p. 1644-5.

13. Tu, L.T., et al., High levels of contamination and antimicrobial-resistant non-typhoidal Salmonellaserovars on pig and poultry farms in the Mekong Delta of Vietnam. Epidemiol Infect, 2015: p. 1-13.

14. Kong, H., X. Hong, and X. Li, Current perspectivesin pathogenesis and antimicrobial resistance ofenteroaggregative Escherichia coli. Microb Pathog, 2015. 85: p. 44-9.

15. CDDEP. Situation Analysis: Antibiotic Use and Resistance in Vietnam. 2010; Available from:http://www.cddep.org/sites/default/files/vn_report_web_1_8.pdf.

16. Malhotra-Kumar, S., et al., Colistin-resistant Escherichia coli harbouring mcr-1 isolated from food animalsin Hanoi, Vietnam. Lancet Infect Dis, 2016.

17. Liu, Y.Y., et al., Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals andhuman beings in China: a microbiological and molecular biological study. Lancet Infect Dis, 2016. 16(2):p. 161-8.

18. Lentz, S.A., et al., Letter to the editor: Escherichia coli harbouring mcr-1 gene isolated from poultry notexposed to polymyxins in Brazil. Euro Surveill, 2016. 21(26).

19. Perrin-Guyomard, A., et al., Prevalence of mcr-1 in commensal Escherichia coli from French livestock,2007 to 2014. Euro Surveill, 2016. 21(6).

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20. Suzuki, S., et al., Investigation of a plasmid genome database for colistin-resistance gene mcr-1. LancetInfect Dis, 2016. 16(3): p. 284-285.

21. Jones, E.M., et al., Risk factors for antimicrobial resistance in Escherichia coli found in GB turkey flocks.Vet Rec, 2013. 173(17): p. 422.

22. Karanika, S., et al., Fecal Colonization With Extended-spectrum Beta-lactamase-ProducingEnterobacteriaceae and Risk Factors Among Healthy Individuals: A Systematic Review and Metaanalysis.Clin Infect Dis, 2016. 63(3): p. 310-8.

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THESIS SUMMARY

THESIS SUMMARY

Thesis Summary

This research was conducted to (1) assess the prevalence of antimicrobial drug resistance among

non-typhoidal Salmonella and E. coli strains isolated from backyard farm chickens and humans

in Vietnam; (2) relate these findings to antimicrobial usage; and (3) estimate the risk of human

colonization with antimicrobial resistant bacteria or resistance determinants as a result of chicken

farming in southern Vietnam.

The current situation of antimicrobial usage and antimicrobial resistance in Vietnam is reviewed

in Chapter 1. In addition, current knowledge on the transmission of antimicrobial resistant

bacteria or resistance determinants is also reviewed in this chapter.

Although antimicrobials are used commonly in chicken production in Vietnam, quantitative data

are not available. The results in Chapter 2 show that antimicrobials were systematically used in

chicken farming in the Mekong delta of Vietnam, even in backyard chickens. In addition, the

majority of antimicrobials were mainly used for prophylaxis rather than therapeutic purposes.

In Chapters 3, the risk of non-typhoidal Salmonella (NTS) colonization in farmers as a result of

direct chicken exposure was investigated. Although having direct contact with chickens, farmers

are not more likely to become a carrier of NTS than individuals who are not exposed to chicken

on a daily basis.

The high prevalence of antimicrobial resistance among commensal E. coli isolates in backyard

chicken farms, is described in Chapter 4. In addition, the association of fluoroquinolones use

with ciprofloxacin resistant E. coli in chicken is revealed in this chapter.

Chapter 5 shows that Enteroaggregative Escherichia coli (EAEC) strains are associated with

humans and not with chickens since EAEC isolates were only detected in humans. Similarly, in

Chapter 6, the prevalence of extended-spectrum beta-lactamases (ESBL) E. coli colonization

and ESBL genes are distinguishable between chickens and humans. ESBL-Ec colonization is

associated with human use of antimicrobials. Whereas, as shown in Chapter 7, the presence of

bacteria carrying the colistin resistance encoding mcr-1 gene is associated with colistin use in

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THESIS SUMMARY

chickens. Farmers working with mcr-1 positive chickens are also more likely to carry mcr-1

positive bacteria.

Chapter 8 discussed the findings of this thesis and highlighted that colonization with

antimicrobial resistant bacteria and transmission of genomic antimicrobial resistance

determinants in both humans and chickens are primarily driven by antimicrobial usage in each

sector.

139

THESIS SUMMARY

Tóm tắt luận án

Luận án này được thực hiện nhằm (1) đánh giá tỷ lệ kháng kháng sinh của vi khuẩn non-

typhoidal Salmonella và E. coli được phân lập từ các trại chăn nuôi gà nhỏ và từ người ở Việt

Nam (2) liên hệ các tỷ lệ này với tình hình sử dụng kháng sinh (3) đánh giá nguy cơ mang trùng

các vi khuẩn đề kháng kháng sinh cũng như các yếu tố qui định tính kháng của việc tham gia

hoạt động chăn nuôi ở Việt Nam.

Chương 1 của luận án trình bày tổng quan về tình hình sử dụng kháng sinh và kháng kháng sinh

tại Việt Nam. Bên cạnh đó, chương này cũng tóm lượt các nghiên cứu gần đây về sự lan truyền

của vi khuẩn đề kháng kháng sinh cũng như các yếu tố qui định tính kháng kháng sinh giữa

người và động vật trên thế giới.

Mặc dù kháng sinh được sử dụng phổ biến trong chăn nuôi ở Việt Nam, thông tin về lượng

kháng sinh sử dụng gần như không được thống kê. Vì vậy, chương 2 của luận án đã nghiên cứu

và ước lượng kháng sinh sử dụng trong chăn nuôi gà ở vùng Đồng bằng sông Cửu Long của Việt

Nam.

Tỷ lệ mang vi khuẩn E. coli và Salmonella đề kháng kháng sinh cũng như việc lây truyền gen

kháng kháng sinh của những vi khuẩn này giữa người và động vật ở Việt Nam được nghiên cứu

từ chương 3 đến chương 7 của luận án.

Chương 3 nghiên cứu tỷ lệ mang trùng vi khuẩn non-typhoidal Salmonella trên gà và người

cũng như nguy cơ mang trùng vi khuẩn này khi chăn nuôi gà ở Đồng bằng sông Cửu Long.

Tỷ lệ kháng kháng sinh trên vi khuẩn E. coli ở các trại chăn nuôi nhỏ và mối liên hệ giữa đề

kháng kháng sinh và việc thực hành chăn nuôi, cũng như sử dụng kháng sinh được trình bày

trong chương 4. Chương 5 tìm hiểu sự hiện diện của vi khuẩn E. coli độc lực EHEC O104:H4

trên các trại gà, người chăn nuôi và không tham gia chăn nuôi ở Việt Nam. Chương 6 được tiến

hành nhằm nghiên cứu nguy cơ lan truyền của vi khuẩn E. coli có khả năng tiết men beta-

lactamase phổ rộng (ESBL) giữa người và động vật thông qua việc xác định tỷ lệ và mối liên hệ

của các gen qui định tính kháng kháng sinh ở các chủng ESBL E. coli, đồng thời cũng liên hệ

tính kháng với việc sử dụng kháng sinh. Chương 7 điều tra ảnh hưởng của việc sử dụng colistin

trong chăn nuôi gà đến việc mang trùng vi khuẩn mang gen kháng colistin mcr-1. Ngoài ra , 140

THESIS SUMMARY

nguy cơ của việc lây truyền gen này sang người cũng được nghiên cứu bằng cách kết hợp phân

tích các yếu tố sinh học phân tử và dịch tể học liên quan ở gà, người chăn nuôi và không tham

gia chăn nuôi trong cùng một khu vực ở Việt Nam. Các kết quả nghiên cứu chính của luận án và

các đề xuất trong tương lai được thảo luận trong chương 8 của luận án.

141

THESIS SUMMARY

Nederlandse samenvatting

Dit proefschrift beschrijft de resultaten van het onderzoek dat de volgende vragen tracht te

beantwoorden. 1. Wat is de prevalentie van antimicrobiële resistentie onder Salmonella enterica

en Escherichia coli isolaten die gekweekt zijn uit de ontlasting van kippen en boeren op kleine

kippenhouderijen in de Mekongdelta in Vietnam; 2. Wat is de relatie met antibioticagebruik en 3.

Hoe groot is het geschatte risico op aanwezigheid van resistente bacteriën of resistentiegenen ten

gevolge van het houden van kippen in de bevolking van zuidelijk Vietnam.

Hoofdstuk 1 geeft een overzicht van het gebruik van antibiotica en het vóórkomen van

antibioticaresistentie in Vietnam. Daarnaast wordt de huidige kennis over transmissie van

bacteriën die resistent zijn voor antibiotica en van overdraagbare genen die coderen voor

antibioticaresistentie samengevat.

Hoewel het bekend is dat antibiotic veel gebruikt worden in de kippenhouderij in Vietnam, zijn

er geen kwantitatieve gegevens beschikbaar. De resultaten die beschreven worden in hoofdstuk

2 laten zien dat antibiotica systematisch gebruikt worden in kippenhouderijen in de Mekongdelta

in Vietnam, zelfs in heel kleine kippenhouderijen met minder dan 200 kippen. Bovendien werd

het grootste deel van deze antibiotica gebruikt om als profylaxe in plaats van als therapie.

Hoofdstuk 3 beschrijft het risico op kolonisatie met Salmonella enterica (NTS) ten gevolge van

directe blootstelling aan kippen. Hoewel kippenhouders dagelijks zijn blootgesteld aan kippen,

lijken zij geen groter risico op kolonisatie te lopen dan personen die niet dagelijks aan kippen

zijn blootgesteld.

In hoofdstuk 4 wordt de hoge prevalentie van antibioticaresistentie bij commensale E.coli

isolaten op kleine kippenhouderijen beschreven. Eveneens wordt een associatie van het gebruik

van fluoroquinolonen in kippen met resistentie tegen ciprofloxacin bij deze isolaten aangetoond.

In hoofdstuk 5 wordt beschreven dat Enteroaggregerende E. coli (EAEC) isolaten geassocieerd

zijn met een humane gastheer en niet met kippen. EAEC werden alleen gevonden bij mensen en

niet bij kippen.

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THESIS SUMMARY

In hoofdstuk 6 werd de prevalentie van E. coli die z.g. extended-spectrum beta-lactamasen

(ESBL) produceren en van de genen die coderen voor deze ESBLs onderzocht bij kippen,

kippenhouders en personen die niet zijn blootgesteld aan kippen. Er werd een verschil in

prevalentie gevonden en kolonisatie met ESBL producerende E. coli was geassocieerd met

humaan gebruik van antibiotica. Dit was in tegenstelling met de resultaten die beschreven zijn in

hoofdstuk 7, waarin werd aangetoond dat de aanwezigheid van het mcr-1 gen, dat codeert voor

resistentie tegen colistine, is geassocieerd met colistine gebruik in kippen. Kippenhouders met

kippen die bacteriën met het mcr-1 gen bij zich droegen hadden een significant grotere kans op

kolonisatie met deze bacteriën dan kippenhouders en anderen die niet dagelijks aan deze kippen

waren blootgesteld.

In Hoofdstuk 8 tenslotte, worden de resultaten bediscussieerd. Hierin wordt uitgelicht dat

kolonisatie met resistente bacteriën en transmissie van genen die coderen van

antibioticaresistentie zowel in mensen en in kippen vooral gedreven wordt door antibiotica

gebruik binnen elk van deze gastheren.

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APPENDIX

APPENDIX

Acknowledgments

Firstly, I would like to thank my promoters Prof. Constance Schultsz, Prof. Jaap Wagenaar

who have put a lot of effort into supervising me and patiently reviewed my thesis. Dear

Constance and Jaap, thank you for accepting me as your PhD student. I’m particularly fascinated

by your profound knowledge, intellectual scientific intuition as well as your connections with

other scientists worldwide. Secondly, I am enormously grateful to my co-promoter, Dr. Ngo Thi

Hoa who gave me the opportunity to conduct my PhD at the Oxford University Clinical

Research Unit (OUCRU) in Vietnam. Dear Hoa, thank you for your motivation and guidance

during my PhD journey. I am very thankful for having you as my mentor. You have provided me

endless scientific support and precious daily supervision. Thank you for taking care of my PhD

project and offering me your warm help that has secured me and motivated me to move on with

my PhD. I also would like to thank Prof. Menno de Jong for reviewing this thesis as well as for

his support and advice in my PhD project.

Many thanks to Dr. Juan Carrique-Mas, who has patiently coached me with the

epidemiological data analyses. Dear Juan, thank you for your patience, motivation and most

importantly friendship. I have learnt from you not only scientific knowledge but also dealing

with difficulties and having confidence in science.

I also would like to thank Prof. Anita Hardon for her technical supports and useful advices in

preparing the questionnaires that used in the study.

I very much appreciated the help of Mr. James Campbell, Mr. Nguyen Van Minh, Mrs. Ha

Thanh Tuyen, Ms. Nguyen Thi Nhung, Ms. Hoang Ngoc Nhung, Mrs. Tran Thi Bich Chieu

and Ms. Huynh Ngan Ha at OUCRU, Vietnam. My PhD could not have been completed

without a lot of technical support from all of you.

I would like to say thank you to Dr. Thai Quoc Hieu, Dr. Ho Huynh Mai at the Sub-

Department of Animal Health in Tien Giang as well as Dr. Nguyen Thi Nhu Mai and Dr.

Nguyen Duc Duy at the Preventive Medicine Center in Tien Giang for providing essential and

technical support during the sample collection of my PhD project.

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APPENDIX

I am extremely grateful to get intensive support from Dr. Arie van der Ende and my colleagues

at the Academic Medical Center: Laura, Payal, Niels, Jarne, Willemine, Kim, Leonie,

Xiaolin, and Martijn. I also thank colleagues, friends and students whose names I did not

mention but have helped me in different ways. It was great fun and pleasure to work, lunch and

coffee together with you all. Thank you for providing me many informative and practical

supports for my living in the Netherlands. Thank you for listening to my complaints, sharing

jokes and helping me with my Dutch questions. Every time I recall, I am delighted and grateful

for the friendship I made with you all. I will never forget these beautiful and precious memories.

I would like to give my cordial thanks to Friso, Julien and Carmen at The Amsterdam Institute

for Global Health and Development. Thank you for your substantial support and warm help

before and during my stay in Amsterdam. My travel and my stay in Amsterdam will not be easier

without you.

I also would like to thank my colleagues at the Veterinary Department, Can Tho University,

especially Dr. Luu Huu Manh and Dr. Nguyen Huu Hung who supported and encouraged me

greatly throughout my PhD. Many thanks to Mrs. Bui Thi Le Minh, Ms. Huynh Ngoc Trang,

Ms. Nguyen Ho Bao Tran and Mrs. Nguyen Thu Tam for the support and help during my

study.

Life will not be colorful without my lovely Vietnamese friends in Amsterdam: Duy, Cong

Nguyen, Triet, Truc Anh, Ngoc Anh, Nguyen, Chi, Thanh, Chung, Cuong, Hien, Thao,

Uyen...Thank you for sharing Vietnamese foods and cheerful game time with me and bringing

me the joyful time after research.

The biggest thank you goes to my family: my Dad, my Mum, my brother, my sister-in-law,

my niece and nephew. Con cảm ơn Ba Mẹ vì đã sinh ra con, thương yêu con, sẵn sàng hi sinh tất

cả để con có được cơ hội học tập tốt nhất. Ba Mẹ luôn ở bên con trong những lúc khó khăn nhất.

Dù Ba đã đi xa và không được chứng kiến ngày con thật sự trưởng thành; nhưng con biết ở nơi

nào đó, Ba vẫn dõi theo từng bước đi của con. Con yêu Ba Mẹ nhiều.

Nguyen Vinh Trung

147

APPENDIX

PORTFOLIO

Name PhD student: Nguyen Vinh Trung PhD period: 2011-2017 Name PhD supervisors: Constance Schultsz, Jaap Wagenaar, Ngo Thi Hoa 1. PhD training

Year General courses - Systematic Reviews (Graduate School, AMC, UvA) - Basic Safety Laboratory (Graduate School, AMC, UvA) - Oral presentation in English (Graduate School, AMC, UvA) - Reference Manager (Graduate School, AMC, UvA) - Computing in R (Graduate School, AMC, UvA) - Scientific writing in English for publication (Graduate School, AMC,

UvA)

2012 2013 2013 2013 2013 2014

Specific courses - Intensive course in epidemiology and medical statistics (the London

School of Hygiene and Tropical Medicine, London, UK) - One Health course (Erasmus University Medical Center, Rotterdam,

the Netherlands) - DNA technology (Graduate School, AMC, UvA) - Bioinformatics (Graduate School, AMC, UvA)

2012

2012

2013 2013

Seminars, workshops and master classes - Author and Reviewer workshop - Symposium Epidemiology of ESBLs in animals, humans and

healthcare (UMC Utrecht)

2013 2013

Presentations - International workshop on the use of antimicrobials in livestock

production and antimicrobial resistance in the Asia-Pacific region; Negombo, Sri Lanka – oral presentation

- 23rd European Congress of Clinical Microbiology and Infectious Diseases; Berlin, Germany – oral presentation

- 54th Inter-science Conference on Antimicrobial Agents and Chemotherapy; Washington D.C, United States – poster presentation

- 3rd International One Health Congress; Amsterdam, the Netherlands – oral presentation

- 26th European Congress of Clinical Microbiology and Infectious Diseases; Amsterdam, the Netherlands – oral presentation

2012

2013

2014

2015

2016

148

APPENDIX

(Inter)national conferences - Scientific Spring Meeting KNVM &NVMM - Scientific Spring Meeting KNVM &NVMM

2013 2014

2. Parameters of Esteem

Year Grants - Public Engagement Seed Awards for the project “Community

engagement activities to reduce the risk of zoonotic infections and antimicrobial resistance in Vietnam”, funded by Public Engagement Department, the Oxford University Clinical Research Unit

2016

Awards and Prizes - ASM Student and Post-Doctoral Fellows Travel Grant 2014

3. Publications

Year

Peer reviewed

1. Carrique-Mas JJ, Trung NV, Hoa NT, Mai HH, Thanh TH,

Campbell JI, et al. Antimicrobial usage in chicken production in the

Mekong Delta of Vietnam. Zoonoses and public health. 2015 Apr;62

Suppl 1:70-8.

2. Nguyen VT, Carrique-Mas JJ, Ngo TH, Ho HM, Ha TT,

Campbell JI, et al. Prevalence and risk factors for carriage of

antimicrobial-resistant Escherichia coli on household and small-scale

chicken farms in the Mekong Delta of Vietnam. The Journal of

antimicrobial chemotherapy. 2015 Jul;70(7):2144-52.

3. Nhung NT, Cuong NV, Campbell J, Hoa NT, Bryant JE, Truc

VN, et al. High levels of antimicrobial resistance among escherichia coli

isolates from livestock farms and synanthropic rats and shrews in the

Mekong Delta of Vietnam. Applied and environmental microbiology.

2015 Feb;81(3):812-20.

4. Nhung NT, Thuy CT, Trung NV, Campbell J, Baker S, Thwaites

G, et al. Induction of Antimicrobial Resistance in Escherichia coli and

2015

2015

2015

2015

149

APPENDIX

Non-Typhoidal Salmonella Strains after Adaptation to Disinfectant

Commonly Used on Farms in Vietnam. Antibiotics. 2015;4(4):480-94.

5. Nguyen NT, Nguyen HM, Nguyen CV, Nguyen TV, Nguyen MT,

Thai HQ, et al. The use of colistin and other critical antimicrobials on pig

and chicken farms in southern Vietnam and their association with

resistance in commensal Escherichia coli. Applied and environmental

microbiology. 2016 Apr 15.

6. Trung NV, Carrique-Mas JJ, Nghia NH, Tu LT, Mai HH, Tuyen

HT, et al. Non-Typhoidal Salmonella Colonization in Chickens and

Humans in the Mekong Delta of Vietnam. Zoonoses and public health.

2016 May 6.

7. Van Cuong N, Nhung NT, Nghia NH, Mai Hoa NT, Trung NV,

Thwaites G, et al. Antimicrobial Consumption in Medicated Feeds in

Vietnamese Pig and Poultry Production. EcoHealth. 2016 May 19.

8. Trung NV, Nhung HN, Carrique-Mas JJ, Mai HH, Tuyen HT,

Campbell J, et al. Colonization of Enteroaggregative Escherichia coli and

Shiga toxin-producing Escherichia coli in chickens and humans in

southern Vietnam. BMC microbiology. 2016;16:208.

9. Trung NV, Matamoros S, Carrique-Mas JJ, Nghia NH, Nhung

NT, Chieu TTB. Zoonotic transmission of mcr-1 colistin resistance gene

from small-scale poultry farms, Vietnam. Emerg Infect Dis. 2017 Mar

2016

2016

2016

2016

2017

150