the structure and function of amphibian skin bacterial...

The Structure and Function of Amphibian Skin Bacterial Communities and Their Role in

Susceptibility to a Fungal Pathogen

Jenifer Banning Walke

Dissertation submitted to the faculty of the Virginia Polytechnic Institute and State University in

partial fulfillment of the requirements for the degree of

Doctor of Philosophy

In

Biological Sciences

Lisa K. Belden, Chair

Reid N. Harris

Dana M. Hawley

Ann M. Stevens

July 23, 2014

Blacksburg, Virginia

Keywords: amphibian, microbiota, transmission, symbiosis, structure-function, disease, fungus

ii

The Structure and Function of Amphibian Skin Bacterial Communities and Their Role in

Susceptibility to a Fungal Pathogen

Jenifer B. Walke

ABSTRACT

As part of the ongoing loss of global biodiversity, amphibian populations are experiencing

declines and extinctions. A primary factor in these declines is the skin disease chytridiomycosis,

which is caused by the fungus Batrachochytrium dendrobatidis (Bd). Recent research suggests

that the amphibian skin microbiota has anti-Bd activity and may be an important factor in host

disease resistance. However, little is known about the basic ecology of this host-microbe

symbiosis, such as how much variation there is in microbial symbionts among host species and

populations, and the nature of symbiont transmission, culturability, and function. My dissertation

research addressed these basic questions in microbial ecology, as well as used a novel system to

examine the long-standing ecological theory of community structure-function relationships.

First, host-specificity, population-level variation and potential environmental transmission of the

microbiota were examined by conducting a field survey of bacterial communities from bullfrogs,

newts, pond water, and pond substrate at a single pond, and newts from multiple ponds. There

was variation among amphibian host species and populations in their skin symbionts, and, in a

host species-specific manner, amphibian skin may select for microbes that are generally in low

abundance in the environment. Second, the culturability of amphibian skin bacteria was assessed

by directly comparing culture-dependent and -independent bacterial sequences from the same

individuals. Although less than 7% of the amphibian skin microbes were captured using R2A

medium, most of the dominant bacteria were represented in our cultures, and similar patterns of

diversity among four amphibian species were captured with both approaches. Third, the

relationship between microbial community structure and function and selective forces shaping

structure and function were examined in bullfrogs by tracking microbial community structure

and function following experimental manipulation of the skin microbiota and pathogen exposure.

Results of this study demonstrated that Bd is a selective force on cutaneous bacterial community

structure and function, and suggest that beneficial states of bacterial structure and function may

iii

serve to limit infection and negative fitness consequences of Bd exposure. Using a combination

of observational and experimental approaches, my dissertation contributes to understanding

structure-function relationships of these complex symbiotic communities of vertebrates.

iv

Acknowledgements

I am thankful for the support and mentorship of my advisor, Lisa Belden. In addition to

investing time and effort into my development as a scientist, Lisa has provided me with

wonderful life opportunities and guidance, and for that I am thankful. I value the opportunity to

have Lisa as a mentor and a friend. I would also like to thank my advisory committee, Reid

Harris, Dana Hawley, and Ann Stevens, for their invaluable guidance throughout my graduate

program. I would like to especially thank Reid, who sparked my interest in amphibian skin

bacteria a decade ago at James Madison University and opened my eyes to the amazing

microbial world.

I thank the members of the Belden Lab (Matthew Becker, Sally Zemmer, Daniel Medina,

Myra Hughey, and Skylar Hopkins) for their friendship, support, and valuable discussions about

science. I would especially like to thank Matt Becker for the numerous insightful conversations

we’ve had while travelling to field sites and conferences, swabbing in the field, or pipetting

endlessly in the lab. I am also thankful for Laila Kirkpatrick’s invaluable advice regarding

molecular laboratory procedures, as well as the numerous undergraduate researchers who have

helped with my dissertation research.

I am grateful to the agencies, awards, and programs that have made this work possible,

including the Cunningham Doctoral Scholar Award, Robert and Marion Patterson Scholarship,

Perry Holt Scholarship, Virginia Tech Graduate Research and Development Program, The Fralin

Life Sciences Institute at Virginia Tech, Morris Animal Foundation, and the National Science

Foundation. Also, thanks to Virginia Tech’s Department of Biological Sciences and the

University of Virginia’s Mountain Lake Biological Station, whose people and scenery made

working very pleasant.

Finally, I thank my family. The unconditional love and support provided by my parents in

so many ways made this possible. I also thank my husband, Kirby, for helping with field work,

providing constant and reassuring motivation, and always offering a fun and unique perspective

on life. I am forever thankful for my daughter, Claire, who motivates and inspires me every day.

v

Attributions

Chapter 2: Amphibian skin may select for rare environmental microbes

This chapter has been reproduced legally from The ISME Journal, 2014, online ahead of print,

doi:10.1038/ismej.2014.77

The published article included six additional authors:

Matthew H. Becker, Virginia Tech, Blacksburg, VA: contributed to the conceptual design of the

study, field and lab work, analysis, and manuscript development

Stephen C. Loftus, Virginia Tech, Blacksburg, VA: contributed to statistical analysis

Leanna L. House, Virginia Tech, Blacksburg, VA: contributed to statistical analysis

Guy Cormier, Virginia Tech, Blacksburg, VA: contributed to bioinformatics

Roderick V. Jensen, Virginia Tech, Blacksburg, VA: contributed to bioinformatics

Lisa K. Belden, Virginia Tech, Blacksburg, VA: contributed to the conceptual design of the

study, analysis, and manuscript development

Chapter 3: Linking culture-dependent and -independent characterizations of amphibian

skin microbial communities: Important insights into the use of probiotics in amphibian

conservation

The chapter included five additional authors:


study, field and lab work, analysis, and manuscript development

Myra C. Hughey, Virginia Tech, Blacksburg, VA: contributed to field and lab work, analysis,

and manuscript development

Meredith C. Swartwout, Virginia Tech, Blacksburg, VA: contributed to field and lab work

Roderick V. Jensen, Virginia Tech, Blacksburg, VA: contributed to bioinformatics



vi

Chapter 4: Community structure and function of amphibian skin microbes: an

experimental test with bullfrogs exposed to chytrid fungus

The chapter included six additional authors:


study, field and lab work, analysis

Thais L. Teotonio, Temple University, Philadelphia, PA: contributed to metabolite profile

generation and analysis

Stephen C. Loftus, Virginia Tech, Blacksburg, VA: contributed to statistical analysis of

metabolite profiles

Leanna L. House, Virginia Tech, Blacksburg, VA: contributed to statistical analysis of

metabolite profiles

Kevin P. C. Minbiole, Villanova University, Villanova, PA: contributed to metabolite profile

generation and analysis



vii

Table of Contents

Abstract .................................................................................................................................ii

Acknowledgements ..............................................................................................................iv

Attributions ..........................................................................................................................v

Table of Contents .................................................................................................................vii

List of Tables ........................................................................................................................viii

List of Figures .......................................................................................................................ix

Chapter 1: General Introduction ......................................................................................1

Dissertation Research Overview ................................................................................6

References ..................................................................................................................6

Chapter 2: Amphibian skin may select for rare environmental microbes ..................... 16

Abstract ......................................................................................................................16

Introduction ................................................................................................................16

Materials and Methods ...............................................................................................19

Results ........................................................................................................................22

Discussion ........................................................................................................................... 25

References ..................................................................................................................29



conservation ..........................................................................................................................44

Abstract ......................................................................................................................44

Introduction ................................................................................................................44


Results ........................................................................................................................53

Discussion ..................................................................................................................55

References ..................................................................................................................60


experimental test with bullfrogs exposed to chytrid fungus ............................................78

Abstract ......................................................................................................................78

Introduction ................................................................................................................79


Results ........................................................................................................................90

Discussion ..................................................................................................................94

References ..................................................................................................................98

Chapter 5: Synthesis ...........................................................................................................115

References ..................................................................................................................118

viii

List of Tables


Table 1. List of amphibian core OTUs at all three sites, and the mean relative abundances of

those OTUs on amphibian skin and in the environment at Mountain Lake .............37



conservation

Table 1. List of the most abundant OTUs on each amphibian species, with the mean relative

abundances, prevalence, and culturability of these OTUs .......................................69

Table 2. List of the most abundant bacterial families on each amphibian species based on the

culture-independent characterization and whether there were cultured representatives

within the families across any species ......................................................................71



Table 1. Experimental timeline showing field collection, bacterial treatment applications, Bd

exposures, and swabbing regime ..............................................................................109

Table 2. List of abundant OTUs across all samples and time points and whether they changed in

abundance significantly over time ............................................................................109

ix

List of Figures


Figure 1. Within-site variation in microbial communities .....................................................38

Figure 2. Venn diagram summarizing the overlap of environmental (pond water and substrate)

and amphibian (newts and bullfrog) OTUs at Mountain Lake ...............................39

Figure 3. Venn diagram showing overlap of newt OTUs across three sites ..........................40

Figure 4. Relative abundances of OTUs shared between amphibians and environmental samples

(pond water and pond substrate) .............................................................................41

Figure 5. Across-site variation in newt microbial communities ............................................42

Figure 6. Mean relative abundances of bacterial phyla across amphibian populations .........43



conservation

Figure 1. Phylogenetic tree of 259 culture-dependent OTUs (clustered at 97% sequence

similarity) ................................................................................................................72

Figure 2. Amphibian skin bacterial OTU richness (number of OTUs) and phylogenetic diversity

based on culture-independent and culture-dependent characterizations .................73

Figure 3. NMDS ordinations of Sorensen similarity and unweighted UniFrac distance matrices

for culture-independent and culture-dependent microbial communities associated with

four amphibian species ...........................................................................................74

Figure 4. Mean percentage of total OTUs “individually matched” and “species matched” to

cultured OTUs for each amphibian species ............................................................75

Figure 5. Phylogenetic tree of culture-independent OTUs, with culturability and mean relative

abundances of OTUs on each amphibian species shown ........................................76

Figure 6. Relative abundances of culture-independent bacterial phyla associated with bullfrogs,

newts, spring peepers, and toads .............................................................................77



Figure 1. Conceptual model representing potential responses and interpretations of microbial

community structure and function in the presence of a pathogen ..........................110

x

Figure 2. Effects of treatment on bullfrogs’ Bd infection intensity at day 7 and proportional

growth at day 42, and the relationship between individual bullfrogs’ Bd infection

intensity at day 7 and proportional growth at day 42..............................................111

Figure 3. NMDS ordinations based on weighted UniFrac distance matrices and Sorensen

dissimilarity matrices representing differences among bacterial treatments in microbial

community structure and metabolite profiles of frogs exposed and unexposed to Bd one

week after initial exposure to Bd ............................................................................112

Figure 4. Effects of Bd exposure and microbiota manipulation treatment (normal, antibiotics,

and augmented with J. lividum) on OTU richness, phylogenetic diversity, and relative

abundance of the probiotic J. lividum on bullfrog skin one week following exposure to

Bd ............................................................................................................................113

Figure 5. Effects of microbiota manipulation treatment (normal, antibiotics, and augmented with

J. lividum) on changes in OTU richness and phylogenetic diversity of bullfrogs’ skin

microbiota from the field to day 0 ..........................................................................114

1

Chapter 1: General Introduction

Global biodiversity is currently experiencing unprecedented losses (Woodruff 2001,

Avise et al. 2008, Pimm et al. 2014). This is especially true in human-dominated areas, where

exploitation, habitat destruction, and pollution directly impact diversity, and climate and

biogeochemical changes indirectly alter diversity (Avise et al. 2008, Ehrlich and Pringle 2008).

It is important to maintain biodiversity because species diversity is positively correlated with

measures of ecosystem function, such as productivity and stability (Hooper et al. 2005, Worm et

al. 2006, Pasari et al. 2013). Of all vertebrate taxa, amphibians are the most vulnerable as about

33% of the more than 6,300 known amphibian species are threatened and more than 43% are

experiencing population declines (Stuart et al. 2004). The number of declines and extinctions

that have occurred in the past several decades is alarming given the fact that amphibians have

persisted on Earth for more than 300 million years, a time period that includes several mass

extinction events (Avise et al. 2008, Wake and Vredenburg 2008).

Amphibian declines and disease

Collins and Storfer (2003) separate the various hypotheses for amphibian population

declines into two categories. The first category of hypotheses includes those in which the

mechanisms are clear and ecologically well-understood, such as habitat destruction (alteration

and fragmentation), introduced species, and over-exploitation (Fisher and Shaffer 1996, Kats and

Ferrer 2003, Vredenburg 2004). The other class of hypotheses are those for which little is

known about the mechanisms causing declines, which are likely complex and interact

synergistically to negatively affect amphibians (Kiesecker et al. 2001). These include climate

change, UV-B radiation, chemical contaminants, and emerging infectious diseases (Pounds et al.

1999, Kiesecker et al. 2001, Hayes et al. 2002, Blaustein et al. 2003, Carey and Alexander 2003,

Daszak et al. 2003). Of particular concern are the population declines and extinctions that occur

in “pristine” areas seemingly unaffected by anthropogenic factors such as agriculture, pollution,

and deforestation (Pounds and Crump 1994, Pounds et al. 2006, Lips et al. 2006, Skerratt et al.

2007). In these cases, mortality is usually associated with the lethal fungal pathogen,

Batrachochytrium dendrobatidis (Bd), which can cause the skin disease chytridiomycosis

(Berger et al. 1998, Longcore et al. 1999, Pounds et al. 2006, Lips et al. 2006, Skerratt et al.

2

2007). Chytridiomycosis has led to the decline and extinction of up to 200 species of frogs

(Skerratt et al. 2007) and appears to be rapidly increasing in incidence and geographic range

(Stuart et al. 2004, Skerratt et al. 2007, Woodhams et al. 2008, Savage et al. 2011, Kolby 2014,

Rebollar et al. 2014). The effects of chytridiomycosis on amphibians both locally and globally

are undoubtedly devastating. Further research is needed to better understand disease dynamics

and to offer potential disease amelioration efforts.

The amphibian chytrid fungus

Batrachochytrium dendrobatidis (Bd) was first described by Longcore et al. (1999) and

was placed into a new genus (Phylum Chytridiomycota, Class Chytridiomycetes, Order

Chytridiales). Until recently, Bd was considered the only member of its phylum to cause disease

in a vertebrate (Berger et al. 2005). However, a new species, Batrachochytrium

salamandrivorans (Bs), has been identified that infects and causes chytridiomycosis in fire

salamanders, which are experiencing massive population declines in parts of Europe (Martel et

al. 2013). The life cycle of Bd alternates between a motile zoospore stage for dispersal and a

zoosporangium, which resides and feeds on keratinized amphibian skin and releases zoospores

(Berger et al. 2005). The fungus causes hyperkeratosis and disrupts electrolyte and osmotic

balance across the skin (Voyles et al. 2009), which can be fatal.

There is variation in susceptibility to chytridiomycosis at the individual (Davidson et al.

2003), species (Daszak et al. 2004, Woodhams et al. 2007a, Searle et al. 2011), and population

levels (Briggs et al. 2005). For example, North American bullfrogs (Rana catesbeiana) and tiger

salamanders (Ambystoma tigrinum) appear to be carriers of Bd, but are not susceptible to

chytridiomycosis (Davidson et al. 2003, Daszak et al. 2004, Garner et al. 2006). On the other

hand, boreal toads (Bufo boreas) and poison dart frogs (Dendrobates tinctorius and D. auratus)

die within several weeks following exposure to Bd (Nichols et al. 2001, Carey et al. 2006). At

the population level, there are some populations of the mountain yellow-legged frog (Rana

muscosa) and its closely related sister species Rana sierrae (Vredenburg et al. 2007) in

California that are able to coexist with Bd, while other populations experience population

declines and extinctions (Briggs et al. 2005).

3

This variation in susceptibility could be explained by differences in host biogeography,

life history, behavior, or immune function (Woodhams et al. 2003, 2006a, Rowley and Alford

2007, Ramsey et al. 2010). The immune system of vertebrates includes adaptive and innate

defenses. Adaptive, or memory-based, immunity against Bd has recently been suggested in

amphibians (McMahon et al. 2014), and may play a role in variation in susceptibility to Bd.

Vertebrate adaptive immunity may have evolved, in part, to recognize and regulate beneficial

microbial communities that serve as a component of the innate, or non-specific, immune system

(McFall-Ngai 2007). In addition to skin microbiota, innate immune defenses of amphibians

include the epithelial barrier, mucus, and antimicrobial peptides. The epithelium and mucous

layer could explain species level differences in susceptibility, but most likely not population and

individual level differences. Many of the antimicrobial skin peptides that amphibians produce

are active against Bd (Rollins-Smith et al. 2002b, Rollins-Smith and Conlon 2005). Indeed,

Woodhams et al. (2006a, 2006b, 2007a) have demonstrated that amphibian skin peptides may

explain at least some variation in susceptibility at the population and species levels because the

effectiveness of the peptides against Bd in vitro is associated with survival of infected

individuals in nature. However, antimicrobial skin peptides are unlikely to be the sole factor in

determining disease susceptibility. For example, populations of the Tarahumara frog (Rana

tarahumarae) are experiencing declines due to Bd despite the fact that they produce

antimicrobial peptides capable of inhibiting Bd in vitro (Rollins-Smith et al. 2002c). This could

be a result of 1) environmental factors altering the synthesis, release, or effectiveness of

antimicrobial peptides (Rollins-Smith et al. 2002c), or 2) an additional immune defense, such as

antimicrobial cutaneous microbiota that complements the antimicrobial skin peptides.

Another example demonstrating that antimicrobial skin peptides are not the only defense

mechanism responsible for disease resistance is in bullfrogs. Bullfrogs are carriers of Bd, but do

not appear to be susceptible to chytridiomycosis (Daszak et al. 2004, Schloegel et al. 2010).

Their antimicrobial peptides, although somewhat active against Bd (Rollins-Smith et al. 2002a),

do not seem to explain their resistance to chytridiomycosis, because once the peptides are

reduced, bullfrogs remain unaffected by exposure to Bd (DC Woodhams, personal

communication). Therefore, the role of antimicrobial cutaneous microbiota in the innate

immunity of amphibians needs to be investigated further. Variation in skin microbial

4

communities that are effective against pathogens has the potential to explain differences in

susceptibility at the individual, population, and species levels.

Amphibian skin microbiota as an innate immune defense

For my doctoral dissertation work, I studied the microbial ecology of amphibian skin,

which is critical for understanding and ultimately controlling disease (Belden and Harris 2007,

Bletz et al. 2013). The skin of healthy amphibians is host to a diverse resident bacterial

community (Bettin and Greven 1986, Barra et al. 1998, Culp et al. 2007, Lauer et al. 2007, 2008,

Flechas et al. 2012, McKenzie et al. 2012, Roth et al. 2013), and a number of these bacteria can

inhibit Bd growth (Harris et al. 2006, Woodhams et al. 2007b, Flechas et al. 2012, Roth et al.

2013). Recent experimental evidence has demonstrated that a supplemented protective

microbiota can reduce morbidity and mortality in amphibians infected with Bd (Harris et al.

2009a, 2009b) and that the reduction of the cutaneous microbial community can alter disease

outcome (Becker and Harris 2010). In addition to experimental work, field surveys have shown

that amphibian populations coexisting with Bd had a higher proportion of individuals with anti-

Bd skin bacteria than populations experiencing declines (Woodhams et al. 2007b, Lam et al.

2010). Therefore, the resident cutaneous microbiota can be considered an important part of the

innate immune system of amphibians. This protective effect of the microbiota is likely due to

bacterial metabolites inhibiting zoospore colonization or development as amphibian skin

microbes produce metabolites that are inhibitory (Brucker et al. 2008a, 2008b) and exhibit

chemotaxis against Bd (Lam et al. 2011). In vitro assays, in vivo laboratory experiments, and

field surveys suggest that amphibians’ skin microbiota plays an important role in their innate

immune system.

Role of symbiotic microbiota in other taxa

Stable relationships have evolved between animals and symbiotic bacteria, many of

which are mutualistic (McFall-Ngai et al. 2013). Antifungal microbes and/or microbial

community structure on or within animal hosts play an important role in disease resistance in a

number of taxonomic groups, including insects, marine invertebrates, and potentially amphibians

(Rosenberg et al. 2007, Woodhams et al. 2007b, Harris et al. 2009a, Martín-Vivaldi et al. 2010,

Kaltenpoth and Engl 2013, Oliver et al. 2014, Clay 2014). The microbial communities of

5

humans are also important for maintaining health and play a role in disease outcome (Ordovas

and Mooser 2006, Ley 2010, Clemente et al. 2012). For instance, molecules secreted by

commensal gut bacteria inhibit the production of toxins by a pathogenic strain of Escherichia

coli, suggesting that some individuals may have greater susceptibility to infection due to an

imbalance in their intestinal microbiota (de Sablet et al. 2009). The protective effects of

beneficial microbes may be compromised if the microbial community is disrupted, and, as a

result, disease may occur (Dethlefsen et al. 2007, Belden and Harris 2007, Blaser and Falkow

2009, Abreu et al. 2012).

Structure-function relationships

The debate over the relationship between community structure and function has a long

history in the ecological literature (MacArthur 1955, Cummins 1974, Hooper et al. 2005,

Hillebrand and Matthiessen 2009, Thompson et al. 2012). In general, species richness appears to

have a positive effect on most ecosystem services, such as stability and primary production

(Hooper et al. 2005, Balvanera et al. 2006, Worm et al. 2006, Pasari et al. 2013). However, a

majority of studies addressing this issue have been conducted in grassland systems, and have

examined few functional endpoints making it difficult to assume the generality of the

relationship (Balvanera et al. 2006, Pasari et al. 2013). This ecological theory has only begun to

be applied in complex microbial communities (Torsvik and Ovreas 2002, Bever et al. 2010,

Robinson et al. 2010, Gonzalez et al. 2011, Costello et al. 2012, Fierer et al. 2012), which was

the aim of my dissertation. It is important to examine structure-function relationships in

microbial communities because (1) microbes play critical roles in many ecosystem functions,

such as nitrogen and carbon cycling, and (2) all organisms have evolved in the presence of

microbes and serve as hosts to numerous symbiotic microorganisms that constitute their natural

microbiota.

Despite the fact that microorganisms represent a large portion of biodiversity and are

responsible for many important functions, the majority of these microbes have not been cultured

(Amann et al. 1995, Pace 1997, van der Heijden et al. 2008). Recent advances in culture-

independent molecular approaches have allowed for a greater assessment of microbial

community structure (Pace 1997, Hugenholtz et al. 1998, Shokralla et al. 2012), and to some

6

extent, function, through the use of metagenomics (Riesenfeld et al. 2004, Handelsman 2004,

Tringe and Rubin 2005, Kurokawa et al. 2007, Vega Thurber et al. 2009). Yet to fully

understand the physiology and metabolic capabilities of microbes and to use them in biological

applications such as probiotics, we have to be able to grow these organisms in culture. Therefore,

understanding the fraction, abundance, and identity of the cultured representatives in a variety of

systems is important.

Dissertation research overview

While Chapter 1 provides a general introduction to my study system, Chapters 2-4

provide observational and experimental evidence of a symbiosis between amphibians and their

skin microbes and address many ecological questions relating to this interaction. The study

reported in Chapter 2 examined the microbial community structure (using 454 pyrosequencing)

of amphibian skin across species and sites. In addition, this study was designed to provide an

initial investigation of the possible transmission dynamics of amphibian symbionts by comparing

the microbes on the skin with those in the environment. In many microbial systems, only a small

portion of the total microbial community can be cultured with standard media and techniques,

and in many cases, cultured isolates represent rare members of the community. Therefore, the

study reported in Chapter 3 addressed the culturability of amphibian skin microbiota. A direct

comparison of the culture-dependent and culture-independent microbial sequences allowed for

an estimation of the proportion of amphibian skin bacteria that are culturable across four

amphibian species. In addition, this chapter examined the abundance and taxonomic

representation of the cultured bacteria and placed the results in the context of probiotic

development. To link community structure and potential function, the study in Chapter 4

experimentally tested how microbial community structure drives community function following

exposure to Bd in bullfrogs. Bullfrogs have been introduced around the world and are carriers of

Bd. By experimentally manipulating microbiota and pathogen exposure, I tested whether a

reduced microbiota increased infection and an augmented microbiota decreased infection. Lastly,

Chapter 5 synthesizes my dissertation research results and provides recommendations for future

research on amphibian-associated microbiota and its role in disease.

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Walke JB, MH Becker, SC Loftus, LL House, G Cormier, RV Jensen, LK Belden. (2014)

Amphibian skin may select for rare environmental microbes. The ISME Journal.

doi:10.1038/ismej.2014.77

Reproduced from The ISME Journal, 2014.

Abstract

Host-microbe symbioses rely on the successful transmission or acquisition of symbionts in each

new generation. Amphibians host a diverse cutaneous microbiota, and many of these symbionts

appear to be mutualistic and may limit infection by the chytrid fungus, Batrachochytrium

dendrobatidis, which has caused global amphibian population declines and extinctions in recent

decades. Using bar-coded 454 pyrosequencing of the 16S rRNA gene, we addressed the question

of symbiont transmission by examining variation in amphibian skin microbiota across species

and sites and in direct relation to environmental microbes. While acquisition of environmental

microbes occurs in some host-symbiont systems, this has not been extensively examined in free-

living vertebrate-microbe symbioses. Juvenile bullfrogs (Rana catesbeiana), adult red-spotted

newts (Notophthalmus viridescens), pond water, and pond substrate were sampled at a single

pond to examine host-specificity and potential environmental transmission of microbiota. To

assess population-level variation in skin microbiota, adult newts from two additional sites were

also sampled. Co-habiting bullfrogs and newts had distinct microbial communities, as did newts

across the three sites. The microbial communities of amphibians and the environment were

distinct; there was very little overlap in the amphibians’ core microbes and the most abundant

environmental microbes, and the relative abundances of OTUs that were shared by amphibians

and the environment were inversely related. These results suggest that, in a host species-specific

manner, amphibian skin may select for microbes that are generally in low abundance in the

environment.

Introduction

All animals are host to symbiotic microorganisms that constitute their natural microbiota.

As a result of these ancient, intimate associations, animals may rely on microbes for many

critical life processes, such as digestion and energy acquisition (Wenzel et al. 2002, Turnbaugh

17

et al. 2006, Rosenberg et al. 2007), circadian rhythm control (Heath-Heckman et al. 2013), and

disease resistance (Dethlefsen et al. 2007, Rosenberg et al. 2007, Kaltenpoth and Engl 2013).

Advances in culture-independent molecular techniques, including next-generation sequencing of

the 16S rRNA gene, have greatly expanded our ability to characterize these often complex

microbial communities, and can provide key insights into the function of these symbiotic

microbes, as well as to their maintenance in populations across generations.

Long-term host-microbe symbioses rely on the successful transmission or acquisition of

symbionts in each new generation. In some systems, this may predominantly occur via vertical

transmission from parent to offspring. Many insect-microbe symbioses are maintained by

vertical transmission (Hosokawa et al. 2007, Damiani et al. 2008, Lauzon et al. 2009). However,

in other systems, symbionts may predominantly be obtained from the environment in each new

generation. This appears to be the case in the squid-Vibrio (Nyholm and McFall-Ngai 2004),

legume-Rhizobium (Jones et al. 2007), and stinkbug-Burkholderia (Kikuchi et al. 2007)

symbioses. There is great variation in symbiont transmission modes among plants and animals;

however, with some hosts using a combination of environmental acquisition and vertical

transmission of symbiotic microbes (Bright and Bulgheresi 2010). Understanding the route of

transmission is important, as it influences evolutionary dynamics in the system (Ewald 1987,

Bright and Bulgheresi 2010). For example, symbionts that are strictly transmitted vertically often

exhibit reduced genome size as a result of gene loss and lack of horizontal gene transfer (Moran

2003, Sachs et al. 2011b, 2011a). Genome reduction can affect the ability of these symbionts to

evolve or repair degraded genes, which can limit the functioning of the symbionts and thus the

evolution of the symbiosis (Sachs et al. 2011b). On the other hand, symbionts that are

transmitted via the environment often have large, expanded genomes (Sachs et al. 2011a).

Conflicts of fitness interests exist between hosts and symbionts, even in obligate mutualisms, and

transmission mode is thought to modulate these conflicts and thus influence evolutionary

patterns (Sachs et al. 2011a). In addition to evolutionary implications of transmission, systems

reliant on environmental transmission of symbionts may be more likely to be impacted by large-

scale environmental change.

Work on transmission in free-living vertebrate-microbe symbioses suggests that factors

such as habitat use and diet are likely important in determining the composition of the gut

18

microbiota (e.g. humans, non-human primates, other mammals, fish, iguanas; Ley et al. 2008a,

2008b, Nayak 2010, Hong et al. 2011, Muegge et al. 2011, Amato et al. 2013). Several recent

studies on fish suggest that the gut microbiota may not be a simple reflection of the microbes in

their environment, but that selection for specific environmental microbes may be occurring

(Roeselers et al. 2011, Sullam et al. 2012). Furthermore, by comparing the microbial

communities of different species of larval amphibians co-habiting in single ponds and thus

exposed to the same environmental inocula, the results of McKenzie et al. (2012) suggest that

host specificity, not pond environment, influences microbial community composition. However,

few studies on free-living vertebrates have been able to directly assess the composition of the

environmental microbes that individuals are exposed to in relation to their associated microbes

using culture-independent methods.

Amphibian skin microbes provide a good model system for examining this question of

transmission. In recent years, it has become clear that amphibians host a diverse array of

cutaneous microbes (Culp et al. 2007, Lauer et al. 2007, 2008, Walke et al. 2011, McKenzie et

al. 2012). Many of these microbial symbionts appear to be mutualistic and may play a role in

resistance to the chytrid fungus, Batrachochytrium dendrobatidis, which has caused global

amphibian population declines and extinctions in recent decades (Woodhams et al. 2007b, Harris

et al. 2009a, 2009b, Becker and Harris 2010, Lam et al. 2010), as well as to other potential

amphibian pathogens (e.g. Banning et al. 2008). In the first next-generation sequencing study of

these skin symbionts, McKenzie et al. (2012) demonstrated that these communities roughly

parallel the complexities of the human skin microbiota, and that there are likely amphibian

species-specific microbial assemblages, even across sites. There is also some evidence for

different potential routes of transmission in amphibian microbe systems. Banning et al. (2008)

and Walke et al. (2011) provide evidence that microbes may be vertically transmitted in two

amphibian species that exhibit nest attendance behavior, while Muletz et al. (2012)

experimentally demonstrated that it is possible to transfer probiotic bacteria from soil to

salamanders. Using bar-coded 454 pyrosequencing of the 16S rRNA gene, we examined the

bacterial community structure on the skin of two co-habiting amphibian species, and the

relationship of these bacterial communities to those of their pond environment. For one of these

species, we surveyed two additional locations to examine population-level variation in skin

microbiota. Lastly, we compared the bacteria associated with Virginia amphibians to those

19

associated with Colorado amphibians sampled in McKenzie et al. (2012) to begin to synthesize

our knowledge of amphibian skin microbiomes. The results we present have important

implications for understanding host-microbe interactions in wildlife, including transmission of

mutualistic symbionts.

Materials and methods

Sample collection

In a single pond at the University of Virginia's Mountain Lake Biological Station (Giles

County, VA, USA), we examined the bacterial community structure of juvenile bullfrogs, Rana

catesbeiana (N=12), and co-habiting adult red-spotted newts, Notophthalmus viridescens

(N=10), and how their communities relate to those of their pond environment (water, N=3;

substrate, N=3). While it is possible amphibians could acquire microbes from environmental

sources other than pond water and pond substrate (e.g. vegetation or forest surrounding the

pond), we focused on the environment with which these aquatic newts and juvenile bullfrogs

were currently and primarily in contact. In addition, to assess population-level variation in

microbiota, adult newts (N=10/site) from two additional sites were also sampled (Pandapas Pond

in Jefferson National Forest, Montgomery County, VA, USA, and Virginia Tech’s Kentland

Farm, Montgomery County, VA, USA). Amphibians were captured either by hand or dip-net. All

sampling occurred in summer 2010.

In the field, individual amphibians were rinsed with sterile water to remove transient

bacteria (Lauer et al. 2007), then swabbed using sterile, rayon-tipped swabs, which are non-

inhibitory to live microorganisms (Medical Wire & Equipment MW121). The swab was used to

examine whole bacterial community structure using bar-coded 454 pyrosequencing. Each

individual was swabbed ten strokes along the ventral side and five strokes along each

dorsal/lateral side to standardize the sample collection. A fresh pair of gloves was used when

handling each individual. Swabs were also used to collect the pond water and pond substrate

samples at three randomly selected locations around the ponds. For water sampling, a sterile

swab was moved around in the water for five seconds at a depth of ~10 cm. Substrate from the

pond bottom (including mud and decaying leaves) was collected with a dip-net then swabbed for

five seconds. We sampled the top ~15 cm of substrate, as this is the part of the substrate to which

20

the amphibians are likely exposed. Swabs were immediately placed on ice, and were then frozen

at -20C until DNA extraction.

DNA extraction, amplification, and pyrosequencing

Whole-community DNA was extracted from each of the 48 swabs using the Qiagen

DNeasy Blood & Tissue Kit. The V2 region of the 16S rRNA gene was amplified by PCR with

primers 27F-338R (Fierer et al. 2008). The reverse primers contained unique 12-bp error-

correcting Golay barcodes used to tag each PCR product (Fierer et al. 2008), which allowed us to

assign sequences to each sample based on the unique barcode. All samples were run in triplicate,

and no-template controls were run for each sample. After equimolar pooling of PCR amplicons,

12 samples were run on each of four regions using the Roche 454 FLX Titanium platform at the

University of South Carolina Environmental Genomics Core Facility.

Bioinformatics and statistical analysis

The total number of 454 sequences generated was 323,979, with an average number of

sequences per sample of 6,750 (range 86-31,153). Sequences were analyzed using the

Quantitative Insights Into Microbial Ecology (MacQIIME, v. 1.5.0) pipeline (Caporaso et al.

2010b). Sequences were de-multiplexed and filtered based on read length (minimum of 200bp),

quality score (minimum of 25), and number of errors in the barcode (maximum of 1.5). After

denoising with Denoiser (Reeder and Knight 2010), sequences were clustered into OTUs

(operational taxonomic units) at 97% sequence similarity using the uclust method (Edgar 2010).

The most abundant sequence in a cluster was assigned as the representative sequence for that

OTU. Sequences were aligned to the Greengenes 12_10 reference database (DeSantis et al.

2006) using PyNAST (Caporaso et al. 2010a) and assigned taxonomy using RDP classifier

(Wang et al. 2007). Only OTUs containing 0.001% of the total number of sequences were used

in analyses (Bokulich et al. 2013). To standardize sampling effort across samples, the samples

were rarefied at 1,000 sequences, resulting in final sample sizes of Mountain Lake bullfrogs,

N=11, Mountain Lake newts, N=7, Pandapas Pond newts, N=9, and Kentland Farm newts, N=8.

Final pond substrate and water samples remained unchanged, N=3 each.

21

The core microbiota was defined as the set of OTUs present on 80% or more of

individuals in a host population. To assess beta-diversity, we applied Nonmetric Multi-

Dimensional Scaling (NMDS; Kruskal 1964) based on the Bray-Curtis measure of dissimilarity

(Bray and Curtis 1957) in OTU relative abundances across samples. In addition, we used the

phylogenetic-based weighted UniFrac distance metric (Lozupone et al. 2011) to evaluate beta-

diversity. The results using Bray-Curtis and weighted UniFrac were the same, and only the

results for Bray-Curtis are presented. OTU relative abundances were computed for each sample

by dividing the number of reads assigned to the OTU by the total number of rarefied reads for

that sample.

Ordinations are useful in that the interpretation of pair-wise relative distances as a

reflection of observation similarities is clear; e.g., samples in an ordination that are close are

more similar to one another (across all dimensions) than those that are far apart. To decipher if

variation in the pair-wise distances can be explained by covariates, we applied Adonis [available

in the vegan package (Oksanen et al. 2013) in R (version 2.15.1; www.r-project.org); Anderson

2001]. Specifically, Adonis is an analytical method that is comparable to a non-parametric

version of multivariate analysis of variance (MANOVA) and was applied to test if microbial

communities were significantly different across sample source or site. Measures of significance

are interpreted like a P-value and, for this application, were based on 999 permutations. It has

been shown that Adonis may confound location and dispersion effects (Anderson 2001), but it is

less sensitive to dispersion than some of its alternatives, such as analysis of similarities, or

ANOSIM (Oksanen et al. 2013). Separate analyses were conducted for the within-site (Mountain

Lake bullfrogs, newts, pond water, and pond substrate) and across-site (Mountain Lake,

Pandapas Pond, and Kentland Farm newts) data sets.

Venn diagrams were created using the program Venny (Oliveros 2007) to visualize the

OTUs that were shared between bullfrogs, newts, pond substrate, and pond water at Mountain

Lake and between newts at the three sites. To examine the relationship between amphibian and

environmental microbes, we calculated the proportion of amphibian OTUs that were also found

in the environment and used a Fisher’s exact test to compare these proportions across the two

amphibian species. We then compared the mean relative abundances of OTUs that were shared

between newts or bullfrogs and pond water and pond substrate. Mean relative abundances of

22

OTUs were calculated by dividing the sum of relative abundances across all samples in a group

by the total number of samples in that group.

We compared the bacterial communities found on our Virginia amphibians to a prior

published dataset of skin microbes on Colorado amphibian species to begin to synthesize our

knowledge of the amphibian skin microbiome. Also using barcoded pyrosequencing, McKenzie

et al. (2012) sampled the skin microbial communities of three amphibian species (tiger

salamanders, Ambystoma tigrinum, N=12; Western chorus frogs, Pseudacris triseriata, N=13;

and Northern leopard frogs, Lithobates pipiens, N=7) across two to four sites each, for a total of

32 individuals. Using the representative sequences of our amphibian-associated OTUs as a

reference database, we clustered the sequences from McKenzie et al. (2012) at 97% similarity

using the closed-reference OTU picking method in QIIME. The sequences from McKenzie et al.

(2012) that we used for this analysis were quality-filtered, but not previously clustered into

OTUs. The resulting closed-reference dataset was then rarefied to an even sampling depth of 80

sequences/sample, which produced 180 OTUs.

Results

Within the Mountain Lake site, red-spotted newts, bullfrogs, pond water, and pond

substrate had distinct microbial communities based on NMDS ordination (Figure 1; NMDS

stress: 0.16; Adonis F=4.555, P=0.001, R2=0.41). Bullfrogs also had greater individual

variability in microbial communities than newts as indicated in the greater distances among

bullfrog samples on the NMDS ordination as compared to the newt samples (i.e. newts clustered

more tightly together than bullfrogs). A total of 595 and 117 OTUs were observed on bullfrogs

and newts at Mountain Lake, respectively, with 71 of these OTUs observed on both species

(Figure 2). Overall, most amphibian OTUs were not observed in the environmental samples

(84%, 538 of 641 total amphibian OTUs). However, newts shared more of their microbes with

the environment (38%, 44 of 117 OTUs) than bullfrogs shared with the environment (16%, 94 of

595 OTUs; Fisher’s exact test, P=0.0001; Figure 2). This was the case for both water (newts:

25%, 29 of 117 OTUs; bullfrogs: 11%, 65 of 595; Fisher’s exact test, P=0.0002) and substrate

(newts: 17%, 20 of 117 OTUs; bullfrogs: 8%, 49 of 595; Fisher’s exact test, P=0.0056). Lastly,

newts across the three sites shared 55 OTUs (Figure 3).

23

Most OTUs (80%, 82 of 103 OTUs) that were shared between any amphibian host and

the environment were at relative abundances in the pond water or substrate of 0.1% or less

(Figure 4, cluster of points near origin). The OTUs that were abundant on bullfrog or newt skin

were in relatively low abundance in the environment, and similarly, the more abundant

environmental OTUs were in relatively low abundance on bullfrog or newt skin (Figure 4). For

example, two OTUs, in the genus Bacillus and family Enterobacteriaceae, dominated the

Mountain Lake pond substrate samples, representing 36% and 30%, respectively, of all substrate

OTUs. These were present on bullfrogs at relative abundances of 0.05% and 0.08%, and on

newts at 0.03% and 2.2%. The most abundant pond water OTU belonged to the ACK-M1 family

of the Actinomycetales, representing 18% of pond water OTUs, yet only 0.02% and 0.01% of

bullfrog and newt OTUs, respectively.

The general pattern of inversely related relative abundance of the skin microbes and the

environmental samples is exemplified by examination of the core skin microbiota (Table 1),

which was defined as OTUs that were present on >80% of individual hosts at a site. Bullfrogs

and newts at Mountain Lake each had seven OTUs representing the core microbial community

(Table 1). Ten of the 11 Mountain Lake amphibian core OTUs were present in the environment

at relative abundances at or below 0.1%. The more abundant environmental OTU was a

Pseudomonas that was in the pond substrate with a relative abundance of 6.2%. Indeed, of the 29

most abundant substrate OTUs (>0.1% relative abundance), this Pseudomonas OTU was the

only one to overlap with the Mountain Lake amphibian core microbiota, and it was actually a

core member of all four amphibian populations sampled (Table 1). The distribution of pond

water OTUs was more dispersed than the substrate samples, with 70 pond water OTUs present in

relative abundances greater than 0.1%. But again, of that group, only a single Hydrogenophaga

OTU appeared as a core member of the newt skin microbiota at Mountain Lake. Furthermore,

most of the abundant environmental OTUs (66% of substrate OTUs and 66% of water OTUs)

were not observed on any amphibian host, suggesting that amphibian skin is not simply

colonized by the abundant environmental microbes.

For newts at Pandapas Pond and Kentland Farm respectively, 7 and 10 OTUs were

observed in >80% of individuals in a population and thus considered core microbes (Table 1).

Within newts, across the three sites, newt skin bacterial communities were significantly different

24

from each other (Figure 5; NMDS stress: 0.12; Adonis F=4.000, P=0.001, R2=0.28). Pair-wise

comparisons were made between the sites, and the microbial communities at each site were

significantly different from each other (KF vs. PP: F=4.500, P=0.002; KF vs. ML: F=6.926,

P=0.003; ML vs. PP: F=1.953, P=0.05) despite some overlap in the NMDS ordination (Figure 5).

The NMDS ordination demonstrates that the skin microbial communities on the Kentland Farm

newts are less variable among individuals than the skin microbial communities on Pandapas

Pond and Mountain Lake newts (Figure 5). It is important to note that the Adonis significance

test may confound location (across-group variation) and dispersion (within-group variation)

effects (Anderson 2001), such that significant differences may be caused by different within-

group variation or different means across groups. To explore the possibility that dispersion was

driving the between group differences, we removed the outliers and re-ran the analyses. With the

outliers removed and dispersion effects minimized, the Mountain Lake and Pandapas Pond newt

microbial communities become only weakly significantly different (Adonis, ML vs. PP:

F=2.090, P=0.06), suggesting that dispersion may have a stronger role in the identified

differences between those two forested sites. However, both forested sites (ML and PP)

remained significantly different from the agricultural Kentland Farm (KF) site following outlier

removal (Adonis, KF vs. PP: F=4.624, P=0.001; KF vs. ML: F=9.412, P=0.004), suggesting that

it is group location and not dispersion that drive this pattern.

Despite the distinct clustering of microbial communities across species and sites (Figures

1 and 5), there was some overlap in particular OTUs on the amphibians. Three amphibian core

OTUs (in the genera Pseudomonas, Sanguibacter and Varivorax) were present on both bullfrogs

and newts in the same pond. The Pseudomonas and Sanguibacter OTUs were also present on

newts at all three sites. There was one additional core OTU that was found on newts at all three

sites and was not found on the bullfrogs (in the genera Stenotrophomonas; Table 1). The mean

relative abundances of the amphibians’ core OTUs ranged from 0.3% to 34.4% (Table 1),

suggesting that the amphibians’ core microbiota also tends to contain the more dominant

members of their microbial communities. Indeed, with the exception of Pandapas Pond newts,

the most dominant OTU (in terms of relative abundance) in each amphibian population was also

part of the core microbiota (bolded OTUs in Table 1).

25

At the phylum level, newts’ and bullfrogs’ microbiota across all sites were dominated by

Proteobacteria, followed by Actinobacteria, Firmicutes, and Bacteroidetes (Figure 6), with mean

relative abundances across all samples of 71%, 16%, 7%, and 3%, respectively. When focusing

on the 12 bacterial phyla with mean relative abundances >0.1% across all samples, newts at

Mountain Lake were dominated by Proteobacteria (96%) with the remaining 11 phyla ranging

from 0 to 3.6% in relative abundance. Bullfrogs at Mountain Lake, on the other hand, had a more

even representation of these phyla, ranging from 0 to 45% in relative abundances. The newts at

Pandapas Pond also had a more even representation of the phyla than newts at Mountain Lake or

Kentland Farm (Figure 6).

Of the 875 amphibian OTUs observed in this study, 180 (20.6%) overlapped with those

associated with amphibians sampled from Colorado in McKenzie et al. (2011). Five of the 14

newt or bullfrog core OTUs were also detected on Colorado amphibians (underlined in Table 1).

A newt core OTU classified as Hydrogenophaga was found on all three amphibian species

sampled in Colorado. Newt core OTUs in the genera Stenotrophomonas and Microbacterium

were detected on Western chorus frogs and Northern leopard frogs, while a newt core OTU

classified as Methylotenera was only detected on the Western chorus frog. Lastly, a

Pseudomonas OTU that was a member of Virginia bullfrog and newt core microbiotas was also

detected on the two Colorado frog species sampled, but not on the tiger salamanders.

Discussion

Our results suggest that amphibian skin harbors microbes that are generally in low

abundance in the environment, as opposed to being colonized by microbes that are abundant in

the environment. The microbial communities of amphibians and the environment clustered

separately in the NMDS ordination, there was very little overlap in the amphibians’ core

microbes and the most abundant environmental microbes, and the relative abundances of OTUs

that were shared by amphibians and the environment were inversely related. This same pattern

has been seen in sponge and squid systems, such that symbionts that are in very low abundance

in the surrounding environment, are highly abundant in the hosts (Nyholm et al. 2000, Nyholm

and McFall-Ngai 2004, Webster et al. 2010). In these other systems, the mucous layer appears to

act as a filter, selecting for certain members of the free-living environmental microbial

26

community, and in some cases specific microbes in the environment may be attracted to host-

produced compounds (Bright and Bulgheresi 2010). Indeed, Lee & Qian (2004) identified

potential host chemically-mediated control of bacteria on the surface of sponges.

While both symbiont and host factors are important in determining the composition of the

microbiota, the amphibian host likely has a strong influence on the composition of microbes

inhabiting the skin. Amphibian skin is complex, involving mucous skin secretions, host-

produced anti-microbial peptides, microbes, and microbially-produced metabolites. The

components are likely to interact in a complex manner. For example, Myers et al. (2012) found a

synergistic interaction between bacterially-produced metabolites and host-produced peptides, in

terms of inhibition of a fungal pathogen of amphibians. Amphibians produce varying amounts of

mucus secretions (Lillywhite and Licht 1975), which, in addition to preventing desiccation and

aiding in skin-shedding and escape from predators, may act to regulate microbial growth.

Furthermore, each amphibian species has their own set of anti-microbial peptides (AMPs;

Woodhams et al. 2006a, 2006b, 2007a, Daum et al. 2012), with some host species not producing

any at all (Conlon 2011). Some amphibian populations can be differentiated based on their

AMPs (Tennessen et al. 2009, Woodhams et al. 2010). These peptides are likely playing a role in

regulating the growth of certain microbes, leading to amphibian species-specific and population-

specific microbiota.

An additional factor that may influence both transmission dynamics and the host-specific

nature of amphibian skin microbiota is skin sloughing. Amphibians shed their skin at different

intervals, and this interval can further be influenced by environmental factors, such as

temperature (Meyer et al. 2012). Meyer et al. (2012) also found that sloughing reduces the

abundance of symbiotic skin microbes substantially, although Harris et al. (2009a) found that in

a Rana muscosa bioaugmentation study at least some microbes can persist on the skin despite

shedding, even without an available environmental inoculum. In terms of transmission, important

questions arise, such as whether all symbionts persist on the skin or whether hosts re-acquire at

least some of their symbionts from the environment after each sloughing event (intragenerational

transmission; Bulgheresi 2011).

27

Interestingly, there were six amphibian core OTUs (two newt, three bullfrog, and one

shared) that were not detected in the environment at all. This could be because these microbes

are in such low abundance in the environment that they were simply not detected with our

methods, that they are present in a habitat other than the pond water or substrate, such as grass

along the edge of the pond, or that they are transmitted vertically or horizontally via

conspecifics. However, our results, in combination with other recent studies, suggest that the

amphibian skin microbiota is likely to be maintained by a mixture of transmission modes (e.g.

Banning et al. 2008, Walke et al. 2011, Muletz et al. 2012). This is not unusual in the animal

kingdom, as several sponge-symbiont associations are maintained via a combination of vertical

and environmental transmission (Schmitt et al. 2008, Webster et al. 2010), and therefore, the

relative importance of the environmental microbe pool varies across host taxa. A lot of progress

has been made in understanding the transmission dynamics of the bobtail squid-Vibrio fischeri

symbiosis (Nyholm and McFall-Ngai 2004), which consists of a single cultivable bacterium. In

the cases of sponge-associated and amphibian-associated microbiota, the complex and diverse

nature of the symbiont communities may make symbiont transmission dynamics more difficult to

elucidate (Webster et al. 2010).

We observed differences in microbial communities of juvenile bullfrogs and adult newts

at the same site. These species have different life histories, which may, in part, explain

differences in their microbial communities. Newts have aquatic embryos that hatch into an

aquatic larval stage. The aquatic larvae metamorphose into terrestrial juvenile ‘efts’ before

returning to the pond to breed as adults. The juvenile bullfrogs, on the other hand, had recently

metamorphosed and would never have left this site, as they would have developed there from

aquatic embryos and larvae.

We also observed differences in microbial communities of newts across three sites,

including greater individual variation at Pandapas Pond and Mountain Lake as compared to

Kentland Farm. The pond at Kentland Farm is surrounded by a large agricultural experimental

farm, whereas the ponds at Pandapas and Mountain Lake are surrounded by forest and fed by

creeks or springs. Pandapas Pond is also stocked with fish and is a popular recreation site for

humans and their pets, which are additional sources of new and diverse microbes. The isolation

of the pond at Kentland Farm and the characteristics of the surrounding habitat may limit the

28

dispersal opportunities for newts at this site, thus limiting microbial sources. Amphibians’ life

history and site characteristics appear to play a role in microbial community structure of

amphibian skin.

The four most abundant bacterial phyla identified in this study (Proteobacteria,

Actinobacteria, Firmicutes, and Bacteroidetes) are consistent with the dominant groups found on

amphibian skin in other studies, including those of other species and that employed different

microbial community characterization methods (Culp et al. 2007, Lauer et al. 2007, 2008, Lam et

al. 2010, McKenzie et al. 2012). Interestingly, these four dominant amphibian skin bacterial

phyla are also the most dominant phyla on human skin, although the order of relative abundance

varies (Grice et al. 2009, Costello et al. 2009). A further sequence comparison analysis between

this study and data from McKenzie et al. (2012) revealed that approximately 20% of Virginia

amphibian-associated bacteria were also associated with Colorado amphibians, so there may be

some broad-scale similarities in these communities. However, only three of the 12 newt core

bacteria in our study were considered core in all three newt populations, and this pattern of

intraspecific variation in core or dominant bacteria across populations also appears to be

consistent with the results of McKenzie et al. (2012) in Colorado. This suggests that only a

subset of the "core" for any given amphibian population might be considered a member of the

core microbiota of that species across its broader geographic range.

The devastating amphibian skin disease, chytridiomycosis, is caused by the fungus

Batrachochytrium dendrobatidis (Bd; Berger et al. 1998, Longcore et al. 1999, Lips et al. 2006,

Skerratt et al. 2007). Although research examining the role of cutaneous symbionts in preventing

chytridiomycosis and Bd infection is growing (Belden and Harris 2007, Bletz et al. 2013), key

questions remain about individual, population, and species variation in susceptibility to Bd

(Daszak et al. 2004, Retallick et al. 2004, Briggs et al. 2005, Searle et al. 2011). Our results

demonstrate that bullfrogs and newts have distinct microbial communities, despite co-habitation

in a single pond. This finding of host species-specific microbiota is consistent with another study

of amphibian skin microbiota (McKenzie et al. 2012), and could explain some variation in

disease susceptibility among species, as some members of amphibians’ natural microbiota can

inhibit growth of Bd (Harris et al. 2006, Walke et al. 2011) and appear to play a role in

preventing colonization by pathogenic microbes (Harris et al. 2009a, 2009b, Becker and Harris

29

2010). Within a species, population-specific microbiota, which we also observed with the newts

in our study, could explain variation in disease susceptibility among populations (Lam et al.

2010). Understanding variation in skin microbiota and how microbes are transmitted is a critical

step in the development of amphibian probiotics for conservation (Belden and Harris 2007, Bletz

et al. 2013).

By directly assessing the microbial community composition of free-living amphibian

hosts and the environmental microbes to which these individuals are exposed, we were able to

demonstrate that amphibian skin microbiota is not simply a reflection of the microbes in the

environment, but that host species-specific selection for rare environmental microbes is likely

occurring. This finding is consistent with other systems, such as squid (Nyholm and McFall-Ngai

2004), sponges (Webster et al. 2010), and some fishes (Roeselers et al. 2011, Sullam et al. 2012).

Amphibian skin microbiota appears to be maintained by a combination of transmission modes, as

occurs in other animal-microbe symbioses. Regardless of their transmission mode, endo- and

ecto-symbionts exploit a range of fascinating cellular mechanisms to ensure intra- and trans-

generational associations with their hosts (Bulgheresi 2011). Further research into the cellular

mechanisms of the complex interactions taking place on amphibian skin will provide insights

into the overall ecology and evolution of this symbiosis.

Acknowledgements

We thank the University of Virginia’s Mountain Lake Biological Station, Virginia Tech’s

Kentland Farm, and the Jefferson National Forest for allowing us to conduct research on their

lands. We also thank K. Walke for field assistance, and V. McKenzie for providing us with

access to the sequence files from her 2011 study. This research was funded by the Morris Animal

Foundation, the Fralin Life Science Institute at Virginia Tech, and the National Science

Foundation (DEB-1136640).

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37

Table 1. List of amphibian core OTUs (≥ 80% prevalence in amphibian populations) at all three

sites, and the mean relative abundances of those OTUs on amphibian skin and in the

environment at Mountain Lake. Because environmental samples were not collected at PP and KF

sites, dashes are present in environmental sample columns for newt core OTUs from PP and KF

sites. The lowest taxonomic resolution that could be defined for OTU identification is listed;

bacterial phylum for each core OTU is listed in parentheses (Pro=Proteobacteria,

Act=Actinobacteria). Core OTUs are sorted in descending order of the sum of mean relative

abundances across all populations. The most abundant OTU in each population is denoted in

bold (Note: For PP newts, the OTU with the highest mean relative abundance was not part of the

core). The Virginia amphibian core OTUs that were also detected on Colorado amphibians by

McKenzie et al. (2011) are underlined. ML = Mountain Lake, PP = Pandapas Pond, KF =

Kentland Farm.

ML Bullfrogs ML Newts PP Newts

KF

Newts

ML

substrate

ML

water

N = 11 7 9 8 3 3

# OTUs = 595 117 218 291 136 348

# core OTUs = 7 7 7 10 - -

OTU taxonomic

description

Mean Relative Abundances (%) of Amphibian Core OTUs

Pseudomonas (Pro)

1.5 15.8 17.5 21.7 6.2 0

Stenotrophomonas (Pro)

6.0 4.7 34.4 0 0

Hydrogenophaga (Pro)

33.5 8.3

0 0.1

Sanguibacter (Act)

14.2 2.1 2.5 11.8 0 0

Methylotenera (Pro)

14.4 3.8

0 0

Rhodococcus (Act)

15.4

0.9 <0.1 0

Varivorax (Pro)

0.9 0.8

4.5 0 <0.1

Pseudomonadaceae (Pro)

0.8

3.7 0 0

Pseudochrobactrum (Pro)

3.4

0 0

Enterobacteriaceae (Pro)

0.5 1.6 - -

Cellulomonas (Act)

2.1

0 0

Microbacterium (Act)

0.7 1.2 - -

Betaproteobacteria (Pro)

0.8

0.6 0 <0.1

Gammaproteobacteria (Pro)

0.3 - -

38

Figure 1. Within-site variation in microbial communities. Non-metric Multidimensional Scaling

(NMDS) ordination of Bray-Curtis distances between microbial communities of co-habiting

amphibians and their environment. Each point represents an individual amphibian or

environmental sample. 2D Stress = 0.16

39

Figure 2. Venn diagram summarizing the overlap of environmental (pond water and substrate)

and amphibian (newts and bullfrog) OTUs at Mountain Lake.

40

Figure 3. Venn diagram showing overlap of newt OTUs across three sites. ML = Mountain Lake,

KF = Kentland Farm, PP = Pandapas Pond.

41

Figure 4. Relative abundances of OTUs shared between amphibians and environmental samples

(pond water and pond substrate). Relative abundances were averaged across all

individuals/species or samples/environment. Each point represents an OTU that is shared

between the groups.

0

5

10

15

20

0 20 40

Bu

llfr

og

OT

U m

ea

n

rela

tive

ab

un

da

nc

e

0

2

4

6

8

10

0 10 20

0

5

10

15

20

0 20 40

Ne

wt

OT

U m

ea

n

rela

tive

ab

un

da

nc

e

Substrate OTU mean relative abundance

0

10

20

30

40

0 10 20Water OTU mean relative

abundance

42

Figure 5. Across-site variation in newt microbial communities. Non-metric Multidimensional

Scaling (NMDS) ordination of Bray-Curtis distances between microbial communities of newts at

three different sites. Each point represents an individual amphibian sample. 2D Stress = 0.12

43

Figure 6. Mean relative abundances of bacterial phyla across amphibian populations. The twelve

phyla with >0.1% mean relative abundance across all samples are shown. ML = Mountain Lake,

KF = Kentland Farm, PP = Pandapas Pond.

ML Bullfrogs ML Newts

ML Substrate KF Newts

ML Water PP Newts

ML Bullfrogs

Proteobacteria

Actinobacteria

Firmicutes

Bacteroidetes

Other

Cyanobacteria

Verrucomicrobia

Acidobacteria

Fusobacteria

Chloroflexi

Spirochaetes

Bacterial Phyla

44



conservation

Abstract

Some cutaneous microbial symbionts of amphibians can inhibit establishment and growth of the

fungal pathogen, Batrachochytrium dendrobatidis (Bd), and thus there is great interest in using

these symbiotic bacteria as probiotics for the conservation of amphibians threatened by Bd.

Currently, it is estimated that only 0.001-15% of microbes in other systems can be cultured with

commonly used techniques and media, yet culturing is critically important for investigations of

bacterial function and for probiotic selection. This study examined the portion of the culture-

independent microbial community (based on Illumina amplicon sequencing of the 16s rRNA

gene) that was culturable with R2A low nutrient agar, and whether the cultured bacteria

represented rare or dominant members of the community in four amphibian species: bullfrogs

(Rana catesbeiana, N=19), eastern newts (Notophthalmus viridescens, N=18), spring peepers

(Pseudacris crucifer, N=12), and American toads (Bufo americanus, N=15). To determine what

percentage of the community was cultured, we clustered the whole community Illumina

sequences at 97% similarity using the culture sequences as a reference database. For individual

amphibians within a species, we cultured on average 0.59-1.12% of their bacterial community.

However, the average percentage of bacteria that was culturable for an amphibian species was

higher, ranging from 2.81 to 7.47%. Furthermore, most of the dominant OTUs, families, and

phyla were represented in our cultures. The fact that many of the dominant bacterial groups are

represented by culturing is encouraging, as these dominant groups are likely to play an important

role in host defense against Bd, and might be successful probiotics.

Introduction

Microorganisms represent a large portion of global biodiversity and are responsible for

many important ecological functions, yet the majority of these microbes have not been cultured

(Amann et al. 1995, Pace 1997, van der Heijden et al. 2008). It is estimated that only 0.001-15%

of microbes can be cultured with commonly used techniques and media (Amann et al. 1995,

45

Schleifer 2004), and only a third of the known bacterial phyla have cultured representatives

(Achtman and Wagner 2008). Recent advances in culture-independent rRNA gene molecular

approaches have allowed for a greater understanding of bacterial diversity (Pace 1997,

Hugenholtz et al. 1998, Shokralla et al. 2012), but in most cases, the only information we have

about uncultured microbes are these DNA sequences obtained directly from the environment.

Next-generation sequencing has led in some cases to the discovery of entire groups, such

as the TM7 candidate division often found in terrestrial, aquatic, and clinical habitats

(Hugenholtz et al. 2001). This group is phylogenetically-distinct and geographically widespread,

yet has no cultured representatives (Hugenholtz et al. 2001, Marcy et al. 2007). There are also

consistently discovered bacteria seen in culture-independent data sets that are uncultured but

appear to be closely related to commonly cultured bacteria, such as Pseudomonas spp. (Binnerup

et al. 1993, Lloyd-Jones et al. 2005, Costa et al. 2006).

The advantages of next-generation molecular technologies for describing microbial

communities should complement, and not replace, an organismal approach to explaining the

functional role of microbes (Lazcano 2011), which includes growing and studying bacteria in

culture. Studying bacteria in culture has led to a greater understanding of their functions,

physiology and metabolic capabilities. For example, fermentation processes of mixed culture

bacterial consortia can be used to improve renewable energy production (Hallenbeck and Ghosh

2009), and knowledge of metabolic pathways and products of microbes in culture has accelerated

bioremediation efforts to decontaminate pollutants (Tyagi et al. 2011, Bachmann et al. 2014).

Additionally, research on spore formation by Bacillus anthracis has enhanced preparedness

against bio-warfare threats (Spencer 2003, Hermanson et al. 2004), and culture-based bioassays

have largely contributed to the successes of probiotic therapy and bioaugmentation in a number

of systems (Jacobsen et al. 1999, Verschuere et al. 2000, Harris et al. 2006, Jankovic et al. 2010).

Experiments with microbial cultures are also invaluable for studying the fundamental basis of

evolution (Elena and Lenski 2003, Barrick et al. 2009), community assembly (Jessup et al.

2004), and biodiversity-ecosystem function relationships (Krause et al. 2014). The evaluation

and optimization of current culturing techniques in diverse habitats is undoubtedly valuable to

understanding the basic and applied functions of microorganisms.

46

Microbial symbionts play important roles in life processes of plants and animals,

including humans, (Rosenberg and Gophna 2011), yet few studies have assessed the culturability

of these symbiotic microbial communities (Webster et al. 2001, Hayashi et al. 2002, Broderick et

al. 2004, Bougoure and Cairney 2005, Lindh et al. 2005, Rani et al. 2009). In amphibians, some

cutaneous microbial symbionts can inhibit growth of the fungal pathogen, Batrachochytrium

dendrobatidis (Bd), which is responsible for global amphibian population declines and

extinctions (Harris et al. 2006, 2009, Woodhams et al. 2007, Becker et al. 2009, Becker and

Harris 2010, Flechas et al. 2012, Myers et al. 2012). There is great interest in using these

cultured symbiotic bacteria as probiotics for the conservation of amphibians threatened by Bd

(Becker et al. 2012, Bletz et al. 2013). However, it is not known if these cultured symbionts

represent dominant members of the natural microbial community. Knowing this might allow us

to predict whether a potential probiotic isolate will successfully become established or restored

in a community and provide protective effects to the host (Becker et al. 2012, Bletz et al. 2013).

In this study, we characterized the cutaneous microbial communities of four species of

amphibians commonly found in eastern North America: bullfrogs (Rana catesbeiana), eastern

newts (Notophthalmus viridescens), spring peepers (Pseudacris crucifer), and American toads

(Bufo americanus). We used both culture-dependent and culture-independent approaches to

characterize diversity, and then we estimated the portion of the amphibian skin microbial

community that was culturable by directly comparing the sequences obtained from the culture-

independent method to the sequences of the cultured isolates. Additionally, we examined

whether the cultured isolates or culturable portion of the community represented rare or

dominant community members and taxonomic groups. Lastly, we tested whether patterns of

diversity among amphibian species using the two approaches (culture-dependent and -

independent) were comparable.

Materials and Methods

Field Sampling

We performed culture-dependent and culture-independent molecular characterizations of

the bacteria associated with 64 individuals of four amphibian species near Blacksburg, Virginia,

USA: bullfrogs (Rana catesbeiana, n=19), eastern newts (Notophthalmus viridescens, n=18),

47

spring peepers (Pseudacris crucifer, n=12), and American toads (Bufo americanus, n=15).

Bullfrogs and newts were sampled in 2010 from a single pond at Mountain Lake Biological

Station (Giles County, Virginia). Toads and spring peepers were sampled in 2012 from the

Jefferson National Forest (Montgomery County, Virginia) and the Town of Blacksburg’s

Heritage Community Park and Natural Area (Montgomery County, Virginia), respectively. All

sites were located within 33 km of each other. Amphibians were collected in the field by hand or

dipnet. Each individual was handled with fresh gloves, rinsed twice with sterile water to remove

environmental debris and transient microbes (Lauer et al. 2007), then swabbed twice using two

separate sterile rayon swabs (Medical Wire & Equipment, MW113). Each amphibian was

swabbed with twenty strokes along the ventral side and five strokes along each thigh and hind

foot to standardize sampling. Because of the different body shape, newts were swabbed with ten

strokes on the ventral side, ten strokes along the dorsal/lateral sides, and five strokes on the hind

feet. In each case, the first swab was used for the culture-independent microbial community

characterization using MiSeq Illumina sequencing, and the second swab was used for the culture-

dependent characterization by plating onto R2A media (Difco; Becton, Dickinson and Company)

prepared according to the manufacturer’s instructions.

Culture-independent microbial community characterization

The first swab taken from each individual was used for culture-independent analysis of

microbial communities. The swab was placed into an empty 1.5 ml microcentrifuge tube and

frozen until DNA extraction using the Qiagen DNeasy Blood & Tissue Kit (Valencia, CA) with

lysozyme pretreatment (Walke et al. 2014). The V4 region of the 16S rRNA gene was amplified

using the primers 515F and barcoded 806R (Caporaso et al. 2011, 2012). Triplicate reactions for

each sample were performed, and PCR conditions followed the procedure in Caporaso et al.

(Caporaso et al. 2011). Controls without template were run for each sample. Equimolar amplified

samples were pooled, cleaned using the Qiagen QIAquick PCR Clean Up Kit, and sequenced on

the MiSeq Illumina platform using a 250 bp paired-end approach (Caporaso et al. 2012) at the

Dana Farber Cancer Institute’s Molecular Biology Core Facilities (Boston, MA).

Paired reads were assembled with Fastq-join (https://code.google.com/p/ea-

utils/wiki/FastqJoin; 38, 39) and processed with the Quantitative Insights Into Microbial Ecology

https://code.google.com/p/ea-utils/wiki/FastqJoin

https://code.google.com/p/ea-utils/wiki/FastqJoin

48

pipeline (MacQIIME v. 1.8.0) (Caporaso et al. 2010b). Sequences were de-multiplexed and

quality-filtered following methods similar to Bokulich et al. (Bokulich et al. 2013). Specifically,

sequences were discarded if: (1) there were any ambiguous base calls, (2) there were errors in the

barcode, (3) less than 50% of the read length had consecutive base calls with a phred quality

score greater than 3, (4) there were more than 10 consecutive low-quality base calls, or (5) the

read length was not between 252 and 255 bp. After quality filtering, 6,206,929 reads were

retained (number of sequences per sample: 27,693-173,588). Quality-filtered sequences were

then clustered into operational taxonomic units (OTUs) at a sequence similarity threshold of 97%

with the UCLUST method (Edgar 2010) and a minimum cluster size of 0.001% of the total reads

(Bokulich et al. 2013). Sequences were clustered against the Greengenes database (May 2013

release; (DeSantis et al. 2006)), and those that did not match the database were clustered de novo

at 97% sequence similarity. The most abundant sequence for a given cluster was assigned as the

representative sequence for that OTU. Taxonomy was assigned with RDP classifier (Wang et al.

2007) and the Greengenes database (Claesson et al. 2009). Representative sequences were

aligned to the Greengenes database with PyNAST (Caporaso et al. 2010a) and a phylogenetic

tree was constructed with FastTree (Price et al. 2010). After the 0.001% OTU cluster size

threshold was implemented, the number of sequences per sample ranged from 23,482 to 169,562.

All samples were rarefied to 23,400 sequences to standardize sampling effort. The resulting

culture-independent data set was used to examine patterns of alpha and beta diversity across the

four amphibian species and to test for a correlation between the culture-dependent and –

independent methods.

Culture-dependent microbial community characterization

R2A is a low-nutrient medium originally designed for cultivation of bacteria from potable

water (Reasoner and Geldreich 1985). It was chosen because it is the most commonly used

medium for culturing amphibian-associated bacteria (Harris et al. 2006, Woodhams et al. 2007,

Lauer et al. 2007, 2008, Walke et al. 2011, Flechas et al. 2012, Roth et al. 2013, Antwis et al.

2014), it is a relatively low nutrient medium, which reflects nutrient conditions typically

encountered by microbes in the environment, and it supports slow-growing bacteria, which

would quickly be suppressed by faster-growing species on a high-nutrient medium. The culture-

dependent swabs obtained from bullfrogs and newts were plated directly onto R2A plates in the

49

field by streaking the swab in a “W” pattern while simultaneously rotating the swab. The swabs

from spring peepers and toads were placed in a 1.5 ml microcentrifuge tube containing 100 μl

TSYE-glycerol medium (2% trypticase soy broth, 1% yeast extract, 20% glycerol) and incubated

at room temperature for 45 minutes before storage at -80°C. These glycerol swabs were later

thawed, vortexed to homogenize bacterial cells in the solution, and a 30 μl sample was plated

onto R2A. For toads, because colony densities were too high, 1:10 dilutions of glycerol solution

were plated to enable colony growth and isolation.

Culture plates were incubated at room temperature for 14 days, and during that time,

morphologically-distinct colonies were isolated into pure culture based on whole colony color,

form, margin, elevation, and substance (Salle 1973). Reasoner and Geldreich (1985) found that

maximal bacterial counts were observed on R2A medium after 14 days of incubation at 20°C.

Pure cultures were frozen at −80°C in TSYE-glycerol medium until DNA extraction. DNA from

bacterial pure cultures was extracted using PrepMan® Ultra Sample Preparation Reagent

(Applied Biosystems, Foster City, CA), UltraClean® Microbial DNA Isolation Kit (MO BIO

Laboratories, Inc., Carlsbad, CA), or DNeasy Blood & Tissue Kit (QIAGEN, Inc., Valencia, CA)

and amplified with the universal eubacterial primers 8F and 1492R using the protocol described

in Lauer et al. (55). Two-directional sequencing of the 16S rRNA gene was performed using

Sanger DNA sequencing at either The University of Kentucky Advanced Genetic Technologies

Center (UK-AGTC; Lexington, KY, USA) or Beckman Coulter Genomics (Danvers, MA, USA).

A total of 719 bacterial isolates were obtained from the 64 amphibians sampled.

However, sequences could not be obtained from 41 of these isolates because they either did not

amplify or did not sequence well, despite multiple attempts at modifying PCR conditions with

varying cycle numbers, BSA addition, or diluted (1:10) DNA. Furthermore, 12 isolate sequences

were removed from the analysis because they were not long enough to overlap with the culture-

independent sequences of the V4 region of the 16S rRNA gene. Quality sequences for the

remaining 666 isolates were clustered into 259 OTUs at a sequence similarity threshold of 97%

using UCLUST (Edgar 2010) in QIIME (Caporaso et al. 2010b), and 237 of these OTUs

matched sequences in the Greengenes database. Consistent with the culture-independent

sequence analysis, the most abundant sequence for a given cluster was assigned as the

representative sequence for that OTU. Taxonomy was assigned with RDP classifier (Wang et al.

50

2007) and the Greengenes database (Claesson et al. 2009). Representative sequences were

aligned to the Greengenes database with PyNAST (Caporaso et al. 2010a) and a phylogenetic

tree was constructed with FastTree (Price et al. 2010). The resulting culture-dependent data set

was used to examine patterns of alpha and beta diversity across the four amphibian species and

to test for a correlation between the culture-dependent and –independent methods.

Analysis of patterns of alpha- and beta-diversity

Alpha diversity metrics (richness and phylogenetic diversity), assessing within species

diversity patterns, were computed with MacQIIME for each individual in both culture-

independent and culture-dependent data sets. OTU richness was defined as the number of OTUs

observed in a sample after rarefaction, and phylogenetic diversity was Faith’s phylogenetic

diversity metric, which sums the branch lengths in the phylogenetic tree of each sample and is a

way to quantify the phylogenetic scope of each individual’s microbial community (Faith 1992).

To compare OTU richness across amphibian species, we used a generalized linear model with a

Poisson error distribution and log link function. To compare phylogenetic diversity across

species, we used a linear model with a normal error distribution. For each of these analyses,

adjusted pair-wise comparisons were also conducted. To test for an overall correlation between

culture-independent and culture-dependent OTU richness, a generalized linear model with a

Poisson error distribution and a log link function was used. To test for a correlation between

culture-independent and culture-dependent phylogenetic diversity, a simple linear regression

model with a normal error distribution was used. The above analyses were all conducted using R,

version 2.15.2 (R Development Core Team 2012).

To compare patterns of diversity among amphibian host species, and to determine

whether both culture-dependent and -independent data sets led to similar conclusions about

potential among species differences, two indices of beta diversity were assessed using Primer 6

version 6.1.15 and PERMANOVA+ version 1.0.5 (Clarke and Gorley 2006). The incidence-

based Sorensen index and unweighted UniFrac distances were calculated for both the culture-

dependent and square-root transformed culture-independent data. The Sorensen index is a

measure of community similarity among samples, with an emphasis on the number of shared

OTUs, while UniFrac is a phylogenetically-based measure of community similarity (Lozupone et

51

al. 2011). For both distance matrices, differences in beta diversity across species were analyzed

with a permutational multivariate analysis of variance (PERMANOVA), and visualized with

non-metric multidimensional scaling (Kruskal 1964). Pair-wise tests between each pair of

species were performed on both Sorensen and UniFrac matrices of the culture-independent and

culture-dependent data.

Direct comparison of culture-independent and -dependent sequences

The above analyses examined patterns of diversity based on the culture-dependent and

culture-independent data sets separately. To calculate the percentage and abundance of culturable

bacteria, we then performed a direct comparison of the culture-dependent and -independent

sequences. To determine the fraction of the total community for each individual amphibian host

that we cultured with R2A medium, the 259 representative sequences from the culture-dependent

OTUs (Sanger sequences of isolates clustered at 97% similarity) were used as a reference

database to cluster the quality-filtered Illumina sequences at 97% sequence similarity using

UCLUST (Edgar 2010) in QIIME (Caporaso et al. 2010b). The Illumina sequences that did not

cluster to the Sanger OTU reference sequences were then clustered de novo, also at 97%

similarity. OTUs that did not contain at least 0.001% of the total reads were discarded (Bokulich

et al. 2013) and samples were rarified to an even sampling depth of 24,900 sequences per sample

(pre-rarefaction sequences/sample: 24,948-169,125).

When the culture-independent sequences were clustered against the representative

sequences of the 259 culture OTUs at 97% sequence similarity, 218 OTUs (or 84%) received hits

from the Illumina sequences. An OTU was considered “individually matched” if it was both

cultured and detected with the culture-independent approach on the same individual. An OTU

was considered “species matched” if it was detected on an individual with the culture-

independent approach, not cultured from that specific individual, but cultured on a different

individual from the same species. Additionally, a cultured OTU could be “individually

unmatched” if it was cultured from an individual, not detected in the Illumina sequences for that

individual, but found in the Illumina sequence data on a different individual of any of the four

amphibian species. Contamination was ruled out for these cases because these OTUs were

52

present on other individuals in both the culture-dependent and -independent data sets, although

often at very low relative abundances (all but one OTU <2% relative abundance).

Forty-one of the 259 culture OTUs did not receive hits from any Illumina sequences and

were considered “completely unmatched.” Over half of the “completely unmatched” culture

OTUs were isolated from a single individual (22 of 41 OTUs), and the remaining 19 OTUs were

cultured from less than 20% of amphibians. We further investigated whether the “completely

unmatched” culture OTUs belonged to a certain taxonomic group or were rare in the microbial

community or sampled amphibian population. First, we built a phylogenetic tree to visually

determine if “completely unmatched” cultured OTUs were related. The tree was constructed on

the PyNAST (Caporaso et al. 2010a) alignment of all cultured OTU sequences using FastTree

(Price et al. 2010) and visualized with the Interactive Tree of Life, or iTOL (Letunic and Bork

2007, 2011). There was no phylogenetic clustering of “completely unmatched” cultured OTUs

(Figure 1). Next, to estimate their rarity, we used the “species matched” OTU data set, which

was comparable in being absent from the culture-independent data of the individual from which

they were cultured. The only difference was that the “species matched” OTUs were in the

Illumina data set on another individual, while the “completely unmatched” OTUs were entirely

absent. The “species matched” OTUs that were not detected in Illumina sequencing from a given

individual tended to be low in relative abundance (<5%) and prevalence (<30%) on other

individuals of the same species. For example, in spring peepers, these OTUs were found on less

than 20% of the spring peepers, and, when present, were at relative abundances of <0.1% on the

frogs. This suggests that the “completely unmatched” OTUs might also be rare—so rare that

they were not picked up from multiple swabs with our sampling.

To establish the proportion of bacteria culturable from each individual amphibian, we

focused on the “individually matched” and “species matched” OTUs. For each individual, we

calculated percentages of the total number of OTUs that were “individually matched” and

“species matched” to cultured OTUs. We then averaged these percentages for each amphibian

species. Dominant bacterial phyla were identified as those with mean relative abundances greater

than 0.5% for each species. To evaluate the portion of the dominant bacterial phyla that was

culturable, relative abundances for OTUs that were culturable and uncultured from each

individual were calculated, summarized by phylum, and averaged across amphibian species.

53

Lastly, to visualize the distribution and abundance of culturable OTUs amongst all OTUs, a

phylogenetic tree of OTUs resulting from the direct comparison of culture-independent and

culture-dependent sequences of bullfrogs, newts, spring peepers, and toads was constructed using

PyNAST and iTOL as above, with OTUs that were cultured and “matched” on any species

indicated. OTUs with greater than or equal to 0.01% relative abundance across all amphibian

species were included in this analysis. This tree was designed as a visualization tool and is not

meant to portray specific evolutionary relationships among individual OTUs.

Results

OTU richness per individual ranged from 1-24 for culture-dependent methods and from

200-1525 for culture-independent methods. Phylogenetic diversity ranged from 0.15-1.7 for

culture-dependent methods and from 19.3-100.7 for culture-independent methods. While the

culture-independent method clearly detected OTU richness and phylogenetic diversity orders of

magnitude greater than the culture-dependent method, differences among host species were

observed using both methods of characterizing amphibians’ skin microbiota. Spring peepers and

toads had higher OTU richness than bullfrogs and newts in both the culture-independent (Figure

2a; overall Χ2=4612, df=3, P<0.001; bullfrog-newt P=0.19, spring peeper-toad P=0.99, all other

pair-wise comparisons P<0.001) and -dependent methods (Figure 2c; overall Χ2=149.5, df=3,

P<0.001; bullfrog-newt P=0.06, spring peeper-toad P=0.96, all other pair-wise comparisons

P<0.001). In addition, spring peepers and toads had greater phylogenetic diversity of skin

bacteria than bullfrogs and newts (Figure 2b, d). This pattern was observed for both methods

(culture-independent: overall F=16.5, P<0.001, spring peeper-toad P=0.69, all other pair-wise

comparisons P<0.04; culture-dependent: overall F=41.9, P<0.001, spring peeper-toad P=0.99, all

other pair-wise comparisons P<0.001). In addition, both methods suggested a difference between

bullfrogs and newts in phylogenetic diversity (culture-independent P=0.06; culture-dependent

P<0.001). Finally, there was a positive relationship between culture-dependent and -independent

measures of OTU richness (Figure 2e; Poisson GLM, P<0.001) and phylogenetic diversity

(Figure 2f; GLM, P<0.001), such that individuals with greater culture-dependent OTU richness

54

or phylogenetic diversity also had higher culture-independent OTU richness or phylogenetic

diversity.

Culture-independent microbial community composition (β-diversity), as measured by the

Sorensen index, differed among amphibian species (Figure 3a; PERMANOVA: overall Pseudo

F=16.14, P<0.001; all pair-wise comparisons, P<0.001). Although the host species do not cluster

as clearly in the culture-dependent ordination, microbial community composition based on

cultured isolates also differed significantly across species (Figure 3b; PERMANOVA: overall

Pseudo F=4.56, P<0.001; all pair-wise comparisons, P<0.005). The phylogenetic-based distance

metric, unweighted UniFrac, also revealed host species-specific microbiota with both the culture-

independent (Figure 3c; PERMANOVA: overall Pseudo F=10.45, P<0.001; all pair-wise

comparisons, P<0.001) and culture-dependent approaches (Figure 3d; PERMANOVA: overall

Pseudo F=9.75, P<0.001; all pair-wise comparisons, P<0.002).

For individual bullfrogs, newts, spring peepers, and toads, we cultured on average 0.59%,

0.60%, 1.12%, and 0.95% of bacterial OTUs, respectively (Figure 4; “individually matched”

analysis). However, the average percentage of bacteria that was culturable from a species (i.e.

“species matched”) was higher; 5.26%, 2.81%, 7.02%, and 7.47% of bacterial OTUs were

culturable on bullfrogs, newts, spring peepers, and toads, respectively (Figure 4). Across all

amphibian species, 179 of the 3779 culture-independent OTUs (4.7%) were culturable from at

least one of the four species.

Many of the abundant (>1% mean relative abundance) culture-independent OTUs were

culturable (Figure 5, Table 1). For example, 10 of the 14 most abundant culture-independent

OTUs on toads were cultured from toads (Table 1). In bullfrogs, 7 of the 13 most abundant

OTUs were culturable, and in spring peepers, 8 of the 17 most abundant OTUs were culturable

(Table 1). In contrast, for newts, only 2 of the top 16 OTUs were culturable (Table 1). However,

if the OTUs that were cultured from other amphibian species are included, 11 of the top 16 newt

OTUs were culturable. Eight OTUs were abundant (>1%) on more than one amphibian species

(superscript numbers, Table 1), and six of these were culturable. The two that were not

culturable were a Proteobacteria in the family Comamonadaceae and a Proteobacteria in the

55

genus Pseudoalteromonas. One OTU in the family Cellulomonadaceae (Phylum: Actinobacteria)

was abundant (>1%) on all four species sampled and was also culturable.

Four phyla were dominant across all four amphibian species (Proteobacteria,

Actinobacteria, Bacteroidetes, and Firmicutes), and all of the 179 culture OTUs belonged to

these phyla (Figure 6). Proteobacteria was the most abundant phylum across all the amphibian

species, representing on average 54% of all bacteria on bullfrogs, 80% on newts, 64% on

peepers, and 60% on toads (Figure 6). Proteobacteria was also the phylum with the largest

portion of cultured bacteria based on relative abundance (black portion of bars, Figure 6). For

example, in bullfrogs, 59% of the relative abundance of Proteobacteria was represented in the

cultures. However, only 41 of the 1016 Proteobacteria OTUs (4%) on bullfrogs contributed to

this abundance (Figure 6a). The portion of each phylum that was cultured varied, however,

depending on amphibian host species. In newts, only 12% of Proteobacteria relative abundance

was represented in the cultures, and 16 of the 764 Proteobacteria OTUs (2%) contributed to the

abundance (Figure 6b). Actinobacteria was another abundant phylum that varied in its

culturability across amphibian hosts; 57% of this phylum’s relative abundance was represented

by cultures from toads, while less than 3.5% was represented by cultures from bullfrogs, newts,

and spring peepers (Figure 6).

Of the 32 most abundant bacterial families across bullfrogs, newts, spring peepers, and

toads, 20, or 63%, contained culturable OTUs (Table 2). There were five bacterial families that

were highly abundant (>1%) on all four amphibian species sampled (Table 2). Three of these

abundant bacterial families (Comamonadaceae, Oxalobacteraceae, and Pseudomonadaceae; all

Proteobacteria phylum) were culturable on all four amphibian species, while two

(Cellulomonadaceae, Phylum: Actinobacteria; and Xanthomonadaceae, Phylum: Proteobacteria)

were only culturable on two of the four species (Table 2).

Discussion

Our culturing approach captured between 0.59-1.1% of skin bacteria associated with

individual bullfrogs, newts, spring peepers, and toads, which falls within the range observed in

other environments (Amann et al. 1995). However, when bacteria that were cultured from other

individuals of the same species were included, a greater portion of the community (2.81-7.47%)

56

was culturable with our methods. For any given individual, all of the culturable bacteria were not

cultured consistently when they were present in the culture-independent data. This suggests that

we are missing some culturable bacteria with our present sampling methods. To capture more

diversity in our culture collections, the plating methodology needs to be refined. For example,

serial dilution techniques (Garland and Lehman 1999, Connon and Giovannoni 2002) could be

used to more consistently recover all of the culturable bacteria from an individual. But in

general, to obtain a more complete profile of isolates for a species, it appears that sampling

multiple individuals in a population will greatly increase the chances for culturing the most

dominant, core community members.

There are many factors that could impact the low culturability of amphibian skin bacteria.

First, bacteria need specific nutrients, pH, temperature, and oxygen conditions to grow

(Vartoukian et al. 2010), and laboratory and amphibian skin conditions are not identical. Second,

cross-feeding and metabolic cooperation between bacterial species is common, and many

bacteria require helper bacterial strains or their by-products for growth in vitro (Vartoukian et al.

2010). For example, it has been found that a previously uncultured isolate related to

Verrucomicrobia only grows in the presence of a siderophore growth factor produced by a

particular neighbor (D’Onofrio et al. 2010). This group was among the dominant phyla

associated with amphibians in this study; however, it was not culturable with our methods. Third,

culture-independent methods capture the DNA from both active and inactive organisms, while

culture-dependent methods only capture the viable and metabolically active cells. Approximately

20-80% of bacterial cells in various natural environments are dormant, with environmental

samples tending to have a higher inactive portion than host-associated samples, such as the

human gut microbiota (Lennon and Jones 2011). There are likely numerous dormant, viable but

non-culturable (VBNC) microbes (Oliver 2010) in our samples that further contribute to the

small culturable portion of the community. In fact, uncultured microbes in our samples are

related to those that are known to enter this dormant state, such as Burkholderia, Enterobacter,

Erwinia, Klebsiella, Legionella, Mycobacterium, Pseudomonas, Streptococcus, and Vibrio

(Oliver 2010). Microbes could be dormant either on the amphibian skin or become VBNC once

transferred to media, which is an environment that may not match their growth requirements.

Lastly, the growth of some potentially culturable bacteria may have been inhibited by excess

antimicrobial peptides produced by the amphibians (Rollins-Smith 2009). The bacteria that

57

reside on amphibian skin must be able to withstand these antimicrobial peptides (Woodhams et

al. 2014). However, amphibians secrete these peptides in excess when stressed (Rollins-Smith et

al. 2005), such as during swabbing, and thus microbial growth could be inhibited (Myers et al.

2012).

Culture collections are critical for advancing basic and applied microbial ecology, even in

the age of sequencing. Cultures are necessary for experimental work to understand functions of

microbiomes, for identifying members of a community who produce key metabolites, and for

applied purposes such as probiotic therapy. In addition, microorganisms serve as useful models

for testing basic ecological and evolutionary theories (Jessup et al. 2004, Krause et al. 2014).

Given their importance, efforts should be made to expand culture collections, including those for

the amphibian microbiome. While it may be challenging to recreate the complex conditions of

amphibian skin, certain aspects of this habitat, such as pH and mineral components, can be

simulated in vitro to attempt to culture previously uncultured amphibian skin microbes. Indeed,

the addition of specific minerals (e.g., CaCl2), sonication of the samples prior to plating, and an

extended incubation time (e.g., 12 weeks) can enhance culturability of bacteria, including groups

also identified in our samples such as Actinobacteria, Acidobacteria, Proteobacteria, and

Verrucomicrobia (Taylor 1951, Janssen et al. 2002). Additionally, it may be possible to

supplement media with amphibian skin washes, containing bacteria, their by-products, and

amphibian-produced compounds, which may facilitate the growth of previously uncultured

amphibian skin bacteria. Another method for increasing the culturability of microbial

communities is to culture in the actual habitat, as opposed to in a laboratory setting (Kaeberlein

et al. 2002, Vartoukian et al. 2010). This method has been used successfully in aquatic habitats

(Kaeberlein et al. 2002, Bollmann et al. 2007, Nichols et al. 2008), but may not be realistic, or at

least would be extremely challenging logistically, for living vertebrates, such as amphibians.

Nonetheless, by incubating diffusion chambers in pond sediment, Bollmann et al. (Bollmann et

al. 2007) were successfully able to culture rarely cultivated bacterial groups, such as

Deltaproteobacteria, Verrucomicrobia, and Acidobacteria. These groups were among the more

dominant phyla associated with amphibians in this study; however, only one OTU from these

three groups was culturable with our methods (Figures 5 and 6). A similar approach may prove

useful to explore in the amphibian skin system to target these groups. Lastly, rRNA-rDNA

combined approaches can be used to establish the active and inactive (dormant or dead) portions

58

of the community, which would inform the regulatory factors influencing the structure and

function of these microbial communities (Jones and Lennon 2010, Lennon and Jones 2011).

It is traditionally thought that culturable microorganisms are not necessarily the

numerically dominant members in microbial communities, but that they are isolated simply

because they grow easily or rapidly in culture (Hugenholtz 2002). In our study, however, most of

the dominant bacterial phyla, families, and OTUs were cultured. Microbes that are abundant in

skin microbial communities could be competitively dominant, which could contribute to the

successful establishment when introduced or restored in a community, such as occurs during

bioaugmentation. Bacteria have evolved a wide range of competitive strategies (Hibbing et al.

2010), including specialized nutrient acquisition (Zubkov et al. 2003) and microbial defense

systems (Riley and Wertz 2002). Indeed, amphibian-associated bacteria produce metabolites that

inhibit the growth of Bd and other amphibian pathogens (Harris et al. 2006, Lauer et al. 2007,

2008, Banning et al. 2008, Brucker et al. 2008a, 2008b), and several of these antifungal

compounds induce chemotaxis of Bd zoospores away from the compounds (Lam et al. 2011).

Therefore, we hypothesize that these abundant bacteria will also be inhibitory against Bd due to

the same competitive qualities that contribute to their abundance in the community. Costa et al.

(Costa et al. 2007) demonstrated that the most dominant members of the plant rhizosphere

microbial community exhibited antagonistic properties against a plant fungal pathogen. Further

studies that directly correlate microbial abundance and inhibitory capabilities against Bd are

needed to fully test this hypothesis in the amphibian skin system.

Despite the fact that only a small portion of the amphibian-associated microbiota was

culturable, overall patterns of alpha and beta diversity were similar with the culture-independent

and -dependent approaches. Spring peepers and toads had more diverse microbial communities

(in terms of OTU richness and phylogenetic diversity) than bullfrogs and newts, and the

microbial communities associated with bullfrogs, newts, spring peepers, and toads were

different. This result of host species specific microbiota is consistent with other studies of

amphibian skin microbiota (McKenzie et al. 2012, Kueneman et al. 2014, Walke et al. 2014).

Furthermore, culture-dependent OTU richness and phylogenetic diversity predicted culture-

independent OTU richness and phylogenetic diversity. Individuals with higher OTU richness or

phylogenetic diversity based on culturing had higher overall OTU richness and phylogenetic

59

diversity. This is encouraging for being able to make at least some basic comparisons among

culture-dependent and -independent data sets.

A subset of our culture collection was not detectable in the Illumina data set. This was

also seen in a study of mosquito midgut bacteria where they found that cultured bacteria were not

represented in the culture-independent characterization (Lindh et al. 2005). Based on our results,

this appears to be a result of the difficulty of recovering rare bacteria consistently. Additionally,

taxon-specific DNA extraction, PCR and sequencing biases are inherent with next-generation

sequencing approaches, including Illumina (Pinto and Raskin 2012, Shokralla et al. 2012), and

could also explain why some of our culture sequences were not detected in our Illumina data set.

We investigated whether certain taxonomic groups of cultured OTUs consistently failed to match

Illumina sequences. However, this does not appear to be the case as unmatched OTUs are evenly

distributed across the phylogeny. Furthermore, the culture-dependent and -independent

characterizations were performed on two separate, sequential swabs from each individual. The

first swab likely removes part of the whole microbial community, thus exposing microbes that

are present in a deeper layer that are then picked up by the second, culturing swab. Therefore, it

is possible that different bacterial species may be detected on each sequential swab. Taken

together, rare microbes appear to be difficult to detect consistently with both culture-dependent

and -independent methods, and are also unlikely to be successful candidates for amphibian

probiotics.

Our direct comparison of culture-dependent and -independent sequences identified

recommendations to improve our culturing conditions to increase the diversity of culturable

amphibian skin bacteria and thus enhance our understanding of the functional role of these

microbes in the community, including the applied use as probiotics for amphibian conservation

(Bletz et al. 2013). However, most of the abundant, and likely functionally important, bacteria on

amphibian skin were cultured with current methods. While it is clear that culture-independent

approaches provide a more complete assessment of the microbial community composition,

culture-dependent approaches may be adequate, and in some cases more valuable (Ellis et al.

2003), for capturing patterns of community structural and functional diversity.

Acknowledgements

60

This work was supported by the Morris Animal Foundation, The Fralin Life Sciences Institute at

Virginia Tech, and the National Science Foundation (DEB-1136640). We thank Mountain Lake

Biological Station, the Jefferson National Forest, and the Town of Blacksburg for allowing us to

perform our research on their lands. We also appreciate the Illumina sequencing provided by

Zach Herbert and the Molecular Biology Core Facilities at Dana-Farber Cancer Institute and the

statistical assistance provided by S. Hopkins. This research was conducted with approval from

Virginia Tech’s Institutional Animal Care and Use Committee (protocols 08-042-BIOL, 10-029-

BIOL, and 12-040-BIOL) and permission from the Virginia Department of Game and Inland

Fisheries (permits 38862 and 44303).

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69

Table 1. List of the most abundant OTUs on each amphibian species (>1% relative abundance),

and the mean relative abundances and prevalences of these OTUs. Cultured OTUs for each

amphibian species are indicated in bold. OTUs that were identified on more than one amphibian

species are denoted with superscript numbers. The lowest taxonomic resolution that could be

defined for OTU identification and the bacterial phylum for each OTU is listed

(Act=Actinobacteria, Bac=Bacteroidetes, Fir=Firmicutes, Pro=Proteobacteria,

Ver=Verrucomicrobia).

Mean Relative Abundances, % (Prevalence, %)

OTU taxonomic description Phylum OTU ID no. Bullfrogs Newts Spring Peepers Toads

Cellulomonadaceae1 Act culture4350881 14.3 (100)

Methylibium3 Pro culturedenovo8 12.2 (100)

Rhodococcus7 Act culture66626 9.6 (100)

Comamonadaceae Pro culture610486 5.6 (95)

Acinetobacter Pro culture710275 4.6 (95)

Brucellaceae Pro denovo27416 3.1 (100)

Cellulomonas Act culture3053045 2.4 (100)

Spirobacillales Pro denovo32120 2.3 (63)

Pseudomonadaceae Pro culture271891 2.1 (100)

Xanthomonadaceae2 Pro culture160115 1.4 (100)

Oxalobacteraceae Pro culture821956 1.4 (95)

Roseateles depolymerans Pro culture803885 1.2 (89)

Neisseriaceae Pro culture2912622 1.1 (95)

Comamonadaceae4 Pro denovo68717 13.2 (100)

Pseudomonas6 Pro culture926370 12.1 (100)

Methylophilaceae Pro denovo83301 10.6 (100)



Enterobacteriaceae Pro culture548293 5.3 (78)

Serratia Pro culture564290 4.9 (56)

Xanthomonadaceae2 Pro culture160115 4.8 (100)

Candidatus Xiphinematobacter Ver denovo33126 4.6 (100)

Methylibium3 Pro culturedenovo8 3.7 (100)

Xanthomonadaceae Pro denovo100077 3.5 (100)

Pseudomonas Pro culture170405 3.4 (100)

Bacillaceae Fir culture4444460 2.8 (94)


Stenotrophomonas Pro denovo39301 1.7 (94)


Achromobacter Pro culturedenovo12 11.8 (100)


Sphingobacteriales Bac denovo1331 5.0 (92)


Pseudoalteromonas8 Pro denovo34355 3.6 (100)

Flavobacterium Bac culture737951 3.1 (100)


Flavobacterium Bac culture960076 2.6 (92)

Pseudomonas Pro culturedenovo3 2.2 (100)


Neisseriaceae Pro culture560243 1.9 (100)



Rheinheimera Pro denovo15848 1.3 (100)

Comamonadaceae4 Pro denovo68717 1.3 (100)

Flavobacterium Bac denovo79205 1.2 (92)

Rhodobacter Pro denovo72960 1.0 (100)


Flectobacillus Bac denovo58139 5.4 (80)

70





Sphingomonas Pro culture4450360 2.0 (100)

Rhodococcus7 Act culture66626 1.8 (100)




Xanthomonadaceae Pro culture111289 1.3 (93)


Pseudoalteromonas8 Pro denovo34355 1.0 (100)

71

Table 2. List of the most abundant bacterial families (>1% relative abundance) on each

amphibian species based on the culture-independent characterization and whether there were

cultured representatives within the families across any species (marked with X). The relative

abundances of the bacterial families on each amphibian species are listed. Bolded relative

abundances indicate that the bacterial family was cultured from that particular amphibian

species.

Mean Relative Abundances, %

Phylum Family Culturable Bullfrogs Newts Spring Peepers Toads

Actinobacteria Cellulomonadaceae X 18.7 9.0 6.6 3.7

Microbacteriaceae X <1 <1 <1 1.2

Nocardiaceae X 10.2 <1 1.1 1.8

Bacteroidetes unclassified Bacteroidales 1.1 <1 <1 <1

Chitinophagaceae <1 <1 <1 2.4

Cytophagaceae X <1 <1 1.8 7.4

Flavobacteriaceae X <1 <1 10.9 <1

Porphyromonadaceae 1.1 <1 <1 <1

Rikenellaceae 2.5 <1 <1 <1

Sphingobacteriaceae X <1 <1 <1 2.0

unclassified Sphingobacteriales <1 <1 5.5 <1

Firmicutes Bacillaceae X <1 2.9 <1 <1

Ruminococcaceae 2.2 <1 <1 <1

Proteobacteria [Chromatiaceae] <1 <1 1.4 <1

Alcaligenaceae X <1 <1 11.9 <1

Brucellaceae 3.4 <1 <1 <1

Caulobacteraceae X <1 <1 1.1 1.8

Comamonadaceae X 25.1 20.1 15.5 5.5

Desulfovibrionaceae 1.5 <1 <1 <1

Enterobacteriaceae X <1 12.6 <1 2.1

Hyphomicrobiaceae X <1 <1 <1 1.4

Methylophilaceae <1 10.9 <1 <1

Moraxellaceae X 5.3 <1 <1 <1

Neisseriaceae X 1.8 <1 2.1 <1

Oxalobacteraceae X 2.0 1.3 4.4 7.1

Pseudoalteromonadaceae <1 <1 3.6 1.0

Pseudomonadaceae X 5.3 23.2 7.6 14.2

Rhodobacteraceae X <1 <1 2.0 1.1

Sphingomonadaceae X 1.0 <1 3.0 7.2

unclassified Spirobacillales X 2.5 <1 <1 <1

Xanthomonadaceae X 1.7 11.0 2.2 3.5

Verrucomicrobia [Chthoniobacteraceae] <1 4.7 <1 <1

72

Figure 1. Phylogenetic tree of 259 culture-dependent OTUs (clustered at 97% sequence

similarity). The 218 culture OTUs that matched Illumina sequences from the full dataset at 97%

similarity are indicated with a black bar, while “completely unmatched” culture OTUs do not

have a black bar. Bacterial orders are indicated with colored branches.

Actinomycetales

Burkholderiales

Pseudomonadales

Enterobacteriales

Flavobacteriales

Rhizobiales

Sphingobacteriales

Neisseriales

Bacillales

Xanthomonadales

Aeromonadales

Other

“Matched” culture OTUs

73

Figure 2. Amphibian skin bacterial OTU richness (number of OTUs) and phylogenetic diversity

based on culture-independent (a,b) and culture-dependent (c,d) characterizations. Correlations

between culture-dependent and -independent measures of OTU richness (e) and phylogenetic

diversity (f) are shown for all amphibians combined.

OTU Richness Phylogenetic Diversitya b

c d

e f

74

Figure 3. NMDS ordinations of Sorensen similarity (a,b) and unweighted UniFrac distance (c,d)

matrices for culture-independent (a,c) and culture-dependent (b,d) microbial communities

associated with four amphibian species.

Transform: Square root

Resemblance: S8 Sorensen

SpeciesBullfrog

Newt

Peeper

Toad

2D Stress: 0.12Transform: Square root


SpeciesBullfrog

Newt

Peeper

Toad

2D Stress: 0.12


SpeciesToad

Bullfrog

Newt

Peeper

2D Stress: 0.09

SpeciesBullfrog

Newt

Peeper

Toad

2D Stress: 0.14Species

Bullfrog

Newt

Peeper

Toad

2D Stress: 0.14SpeciesToad

Bullfrog

Newt

Peeper

2D Stress: 0.12



SpeciesBullfrog

Newt

Peeper

Toad

2D Stress: 0.12

Culture-independent Culture-dependentS

oren

sen

Un

iFra

c

a b

c d

75

Figure 4. Mean percentage of total OTUs “individually matched” and “species matched” to

cultured OTUs for each amphibian species. An OTU was considered “individually matched” if it

was present in the Illumina data for the same individual from which it was cultured, and was

considered “species matched” if it was cultured from a different individual of the same

amphibian species.

0

1

2

3

4

5

6

7

8

9

Bullfrogs Newts Spring

Peepers

Toads

Per

cen

t o

f O

TU

s

"Individually matched"

"Species matched"

76

Figure 5. Phylogenetic tree of culture-independent OTUs. Mean relative abundances of OTUs on

each amphibian species are shown (blue=bullfrogs, teal=newts, red=spring peepers,

green=toads). OTUs with mean relative abundances greater than or equal to 0.01% across all

amphibian species were included in this analysis. Cultured OTUs are indicated with black bars,

and bacterial phyla are indicated with colored branches. The Proteobacteria phylum was divided

into classes (Alpha-, Beta-, Delta-, and Gammaproteobacteria).

Alphaproteobacteria

Betaproteobacteria

Deltaproteobacteria

Gammaproteobacteria

Actinobacteria

Bacteroidetes

Firmicutes

Verrucomicrobia

Cyanobacteria

Acidobacteria

Fusobacteria

Other

Bullfrog relative abundance

Newt relative abundance

Spring peeper relative abundance

Toad relative abundance

“Matched” culture OTUs

77

Figure 6. Relative abundances of culture-independent bacterial phyla associated with bullfrogs

(a), newts (b), spring peepers (c), and toads (d). The complete bar represents the total mean

relative abundance of each phylum, while the black portion of the bar represents the cultured

portion of each phylum. In parentheses is the number of “species matched” cultured OTUs

(bolded) out of the total number of OTUs in the phylum for each amphibian species. Phyla with

mean relative abundances greater than 0.5% for each species are shown. Error bars represent

standard error.

0 0.2 0.4 0.6 0.8 1

Proteobacteria

Actinobacteria

Bacteroidetes

Firmicutes

Deferribacteres

Mean relative abundance

a

Uncultured

Culturable

(41/1016)

(5/397)

(2/322)

(3/274)

0 0.2 0.4 0.6 0.8 1

Proteobacteria

Actinobacteria

Verrucomicrobia

Firmicutes

b(16/764)

(1/335)

0 0.2 0.4 0.6 0.8 1

Proteobacteria

Bacteroidetes

Actinobacteria

Cyanobacteria

Verrucomicrobia

Firmicutes

c(33/986)

(9/431)

(1/33)

(12/316)

0 0.2 0.4 0.6 0.8 1

Proteobacteria

Bacteroidetes

Actinobacteria

Cyanobacteria

Acidobacteria

Firmicutes

Verrucomicrobia

Planctomycetes

d(50/1153)

(10/392)

(25/437)

(1/93)

Cultured

Uncultured

78



Abstract

The ecological relationships between community structure and function have only recently been

investigated in complex microbial communities, which often play critical roles in a variety of

contexts, including host health and disease resistance. The protective effects of beneficial

microbial community structure or function may be compromised if the community is disrupted,

and as a result disease may occur. This study evaluated the implications of bacterial community

structure on disease outcome, as well as the relationships between community structure and

function in the face of disturbance and disease. Chytridiomycosis is a skin disease of amphibians

that is caused by the fungus, Batrachochytrium dendrobatidis (Bd), and is a major factor in the

global decline and extinction of amphibian populations. Although generally not considered

susceptible to this disease, bullfrogs have been introduced all over the world and are implicated

in the spread of chytridiomycosis. Therefore, understanding factors that contribute to their

tolerance and ways to potentially control the global transmission of this pathogen is an important

endeavor. In a factorial experiment, bullfrogs’ skin microbiota was either greatly reduced with

antibiotics, augmented with an anti-Bd bacterial isolate (Janthinobacterium lividum), or

unmanipulated, and individuals were then either exposed or not exposed to Bd. The microbial

community structure associated with individual frogs prior to Bd exposure influenced Bd

infection intensity one week following exposure. Furthermore, Bd infection intensity of

individual frogs was negatively correlated with their proportional growth over the course of the

experiment. Microbial community structure and function (as measured by metabolite profiles)

were directly related to each other, and differed among unmanipulated, antibiotic-treated, and J.

lividum-treated frogs only when frogs were exposed to Bd. This may explain the reduced growth

of antibiotic-treated frogs that were exposed to Bd relative to those whose normal microbiota

was unmanipulated. We have demonstrated that Bd is a selective force on microbial community

structure and function, and that beneficial states of microbial community structure may serve to

limit infection.

79

Introduction

The debate over the relationship between community structure and function has a long

history in the ecological literature (MacArthur 1955, Cummins 1974, Hooper et al. 2005,

Hillebrand and Matthiessen 2009, Thompson et al. 2012, Pimm et al. 2014). In general, species

richness appears to have a positive effect on ecosystem stability and services, such as primary

production (Hooper et al. 2005, Balvanera et al. 2006, Worm et al. 2006, Pasari et al. 2013).

However, a majority of studies addressing this issue have been conducted in grassland systems,

and have examined few functional endpoints making it difficult to assume the generality of the

relationship (Balvanera et al. 2006, Pasari et al. 2013). This ecological theory has only begun to

be applied in complex microbial communities (Torsvik and Ovreas 2002, Bever et al. 2010,

Robinson et al. 2010, Gonzalez et al. 2011, Costello et al. 2012, Fierer et al. 2012). In particular,

microbial experimental manipulation studies with the aim of further understanding structure-

function relationships are limited, yet given the short generation times, relative ease of

manipulations, and advanced molecular tools, have the promise to reveal patterns and

mechanisms underlying structure-function relationships in general (Krause et al. 2014).

Stable relationships have evolved between multi-cellular organisms and symbiotic

bacteria, many of which are mutualistic (Rosenberg and Gophna 2011, McFall-Ngai et al. 2013).

Antifungal microbes and/or microbial community structure on or within hosts play an important

role in disease resistance in a range of taxonomic groups (Martín-Vivaldi et al. 2010, Rosenberg

and Gophna 2011, Clemente et al. 2012, Daskin and Alford 2012, Kaltenpoth and Engl 2013,

Oliver et al. 2014, Clay 2014). However, even highly stable relationships are prone to

disturbance, and the protective effects of beneficial microbes may be compromised, resulting in

disease (Dethlefsen et al. 2007, Belden and Harris 2007, Blaser and Falkow 2009, Abreu et al.

2012). For instance, in humans, molecules secreted by commensal gut bacteria inhibit the

production of toxins by pathogenic bacteria (de Sablet et al. 2009), and an imbalance in intestinal

microbiota is often linked to disease (Clemente et al. 2012). Additionally, coral-associating

bacterial communities are severely altered during thermal and nutrient stress, and these

disruptions are correlated with coral disease (Vega Thurber et al. 2009, Ainsworth et al. 2010,

Mao-Jones et al. 2010, Oksanen et al. 2013). These relationships support the coral holobiont

hypothesis, which posits that the coral host and its symbiotic microbial community act as one

80

unit, the holobiont, on which selection occurs for the most advantageous holobiont in different

environmental conditions (Rosenberg et al. 2007). This hypothesis further suggests that the

holobiont can adapt much faster (weeks to years) to changing environmental conditions by

altering the microbial communities than it can by mutation and selection of the coral host alone

(Rosenberg et al. 2007). Rapid adaptation of the holobiont can occur in several ways. The

abundance of microorganisms can change, microbes can be added or removed, or the current

microbial community can experience genetic mutation or horizontal gene transfer (Rosenberg et

al. 2007). Zilber-Rosenberg and Rosenberg (2008) extrapolate from this hypothesis to propose

the hologenome theory of evolution, which may be relevant in a great number of systems. This

hypothesis suggests that the holobiont can alter its microbial community to be better adapted for

changing environmental conditions, including pathogen exposure.

The expected links between microbial community structure and function in complex

symbiont consortia are not entirely clear. For instance, different community structures, with

varying relative abundances of individual microbes, could provide similar functions for the host

(especially given the potential for horizontal gene transfer), or there could be groups of critical

taxa that must be present for a function to be performed. These differences in the potential

relationship between microbial community structure and function can be conceptualized based

on the expected changes incurred in community structure and the functional response. Here, we

focus on understanding these relationships in the context of pathogen exposure, as potentially

lethal pathogens should be strong selective forces on the defensive microbial symbiont

communities (Figure 1). One prediction is that with pathogen presence, community structure will

change as the pathogen competes with other microbes in the community. In this case, the

function of the community may or may not change depending on whether bacterial symbionts are

functionally redundant or whether keystone species are affected. If species are redundant, the

loss of one species can be offset by another, and we predict that the structure of the community

can change when the pathogen is introduced while the function of the community remains the

same. If, however, each species makes a unique contribution to the function of the community,

the loss or gain of a keystone species will impact the community function. In this case, we

predict that if a keystone species is lost or gained when a pathogen is introduced, then the

function of the community will also change. Alternatively, community structure could remain

unchanged, but community function could exhibit a shift towards disease resistance. This would

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imply that community members exhibit plasticity in their functional response. Lastly, both

community structure and function could remain unchanged with pathogen presence, suggesting

that the pathogen is not a strong selective force on community function. We tested this

conceptual model by experimentally examining changes in microbial community structure and

function of microbial communities on bullfrog skin in response to pathogen exposure.

Chytridiomycosis is a skin disease of amphibians that is caused by the fungus,

Batrachochytrium dendrobatidis (Bd) (Longcore et al. 1999). This emerging infectious disease is

a major factor in the decline and extinction of amphibian populations globally (Berger et al.

1998, Pounds et al. 2006, Lips et al. 2006, Skerratt et al. 2007). The skin of healthy amphibians

is host to a diverse resident bacterial community (Bettin and Greven 1986, Barra et al. 1998,

Culp et al. 2007, Lauer et al. 2007, 2008, Flechas et al. 2012, McKenzie et al. 2012, Roth et al.

2013), and a number of these bacteria can inhibit Bd growth (Harris et al. 2006, Woodhams et al.

2007b, Flechas et al. 2012, Roth et al. 2013). A supplemented, protective cutaneous microbiota

can reduce morbidity and mortality in amphibians infected with Bd (Harris et al. 2009a, 2009b),

and reduction of the cutaneous microbial community can alter disease outcome (Becker and

Harris 2010). In addition to experimental work, field surveys have shown that amphibian

populations coexisting with Bd had a higher proportion of individuals with anti-Bd skin bacteria

than populations experiencing declines (Woodhams et al. 2007b, Lam et al. 2010). Therefore,

the resident cutaneous microbiota can be considered an important part of the innate immune

system of amphibians.

By experimentally forcing changes in microbial community structure of bullfrogs’ skin,

we were able to assess the role of bacterial community structure on Bd infection intensity and

host response (growth), as well as the effects of Bd on community structure and disease

resistance function and the links between structure and function. In addition, we tested whether a

microbiota reduced with antibiotics increased Bd susceptibility and infection intensity, and a

microbiota augmented with the anti-Bd bacterium J. lividum decreased Bd susceptibility and

infection intensity.

Materials and Methods

Study species

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Bullfrogs were chosen as the study species for this experiment because they are

introduced all over the world and are implicated in the spread of chytridiomycosis (Hanselmann

et al. 2004, Garner et al. 2006, Ficetola et al. 2006, Bai et al. 2010, Schloegel et al. 2010), but are

generally not considered susceptible to chytridiomycosis (Daszak et al. 2004, but see Gervasi et

al. 2013). Bullfrogs secrete antimicrobial peptides (Goraya et al. 1998, Konishi et al. 2013),

including peptides active against Bd (Rollins-Smith and Conlon 2005), which have been

correlated with disease resistance in other species (Woodhams et al. 2006, 2007a). While skin

peptides may contribute to immune defense, they also help regulate the microbiota of bullfrogs

(D.C. Woodhams, personal communication). Thus, the role of the skin microbiota should be

investigated further as a contributing innate immune defense in bullfrogs. Additionally, the

normal and anti-Bd skin microbiota of bullfrogs has been characterized in various life stages and

in various locations (Culp et al. 2007, Mendoza et al. 2012, Walke et al. 2014), although not in

the context of Bd infection.

Sample collection and experimental treatments

Sixty juvenile bullfrogs (Rana catesbeiana) were collected in August 2010 from

Mountain Lake Biological Station, Giles County, Virginia, swabbed in the field initially,

returned to the laboratory and randomly assigned to one of six experimental treatment groups.

Frogs had their skin microbiota unmanipulated, reduced with antibiotics, or augmented with

Janthinobacterium lividum (used in prior probiotic studies to limit Bd impacts on amphibians,

e.g. Becker et al. 2009, Harris et al. 2009a, 2009b), and were then either exposed or unexposed to

Bd. We used an unbalanced design, with higher sample sizes in the Bd exposure treatments (N =

13) than in the unexposed treatments (N = 7), because we were mainly interested in assessing the

effect of bacterial treatment on the structure and function of the microbiota in the presence of Bd.

In the laboratory, frogs were kept at 17C on a 12 hour light cycle in autoclaved 15 x 33 x 23 cm

containers that were slanted and contained 500 ml sterile water and two sterile moist paper

towels. Cages were changed and frogs were fed crickets ad lib twice per week throughout the

experiment.

To produce amphibians with a greatly reduced skin microbiota, individuals in the

antibiotic treatment were housed in fresh containers with 500 ml broad-spectrum antibiotic

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solution everyday for 2 weeks (Table 1b), alternating among Maracyn (5 ml/L), Enrofloxacin (30

mg/L), and Cephalexin (12 mg/L). A similar cocktail has been shown to be a safe and effective

technique to reduce skin microbiota (Becker and Harris 2010). We were able to use our 16S

rRNA molecular analyses to assess our treatment success (see methods below). In our

experiment, at day 0 following the two weeks of antibiotic treatment, treatment with antibiotics

effectively reduced bacterial diversity, both in terms of the number of unique bacteria and

phylogenetic diversity (mean+/-SE number of unique bacteria: Antibiotics=303+/-8,

Unmanipulated=425+/-20, J. lividum=451+/-19, ANOVA overall F=22.50, P<0.0001; mean+/-

SE phylogenetic diversity: Antibiotics=28.4+/-0.6, Unmanipulated=33.1+/-1, J. lividum=34.3+/-

1.1, ANOVA overall F=11.73, P<0.0001).

The frogs in the augmented microbiota treatment were supplemented with the anti-Bd

bacterial species, Janthinobacterium lividum, which is effective in reducing morbidity and

mortality due to Bd in some amphibians (Becker et al. 2009, Harris et al. 2009a, 2009b). To

produce individuals augmented with anti-Bd bacteria (J. lividum treatment), frogs were placed in

sterilized 400 ml Ziploc containers with 100 ml of J. lividum cells in sterile water for six hours

(as in Harris et al. 2009a). Two inoculations were performed, at 11 (1.8x108 cells/ml) and 4

(3.8x107 cells/ml) days before exposure to Bd (considered experiment day 0; Table 1b).

Although J. lividum was present on 55% (28 of 51) of bullfrogs in the field at our initial

swabbing time point, with a mean relative abundance of 0.02% (SE=0.005%, range=0.008-

0.1%), our experimental inoculation was successful. By day 0, J. lividum successfully became

established onto J. lividum-treated frogs at a mean relative abundance of 2.7% by day 0 and

7.8% by day 7. Individuals inoculated with J. lividum had a higher mean relative abundance than

control and antibiotic-treated individuals at day 0 (Steel-Dwass—Jliv-Unmanipulated: Z=-4.90,

P<0.001; Jliv-AB: Z=4.93, P<0.001). Individuals in the unmanipulated microbiota treatment

were placed in 100 ml of sterile water for the same time period to control for handling effects.

To maximize the potential impact of Bd on the bullfrogs, a strain of Bd isolated from a

Panamanian amphibian species (Bd310) was used in this experiment. This strain was previously

demonstrated to be lethal in another North American amphibian species, Plethodon cinereus,

(Becker et al. 2009) that did not experience mortality from a North American Bd isolate (Becker

and Harris 2010). Frogs (N=13/pre-treatment) were exposed to Bd at day 0 by placing them in

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100 ml solutions containing 7x106 zoospores for 24 hours in sterilized 400 ml Ziploc containers

(Table 1b). Unexposed frogs (N=7/pre-treatment) were placed in sterile water. To ensure

successful infection, a second Bd exposure (4.8x107 zoospores) was performed at day 4 (Table

1b).

Frogs were swabbed for microbial community analysis and Bd infection intensity initially

in the field (day –21), after bacterial treatment and prior to Bd exposure (day 0), and one week

after exposure to Bd (day 7; Table 1). Frogs were also swabbed on days 14, 28, and 42, but these

samples were not used for microbial community analysis. DNA from day 42 was used to

quantify final Bd infection intensity. A second swab for metabolite profiling was also taken in

the same manner at days 0 and 7 (Table 1). Metabolite analysis was performed on day 7 data.

Sterile rayon swabs (Medical Wire & Equipment, MW113) were used for DNA and metabolite

collection. Each individual was handled with fresh gloves. Frogs were rinsed twice with sterile

water to remove transient microbes (Lauer et al. 2007), and swabbed ten strokes along the

ventral side and five strokes along each thigh and rear foot. We focused on these regions for

swabbing because Bd infection is generally concentrated in the thighs, hands, feet, and ventral

surface of the abdomen (Berger et al. 2005; Puschendorf and Bolaños 2006). Swabs were placed

in empty, sterile 1.5 ml microcentrifuge tubes and frozen at -20°C. Frog mass was also recorded

at each sampling time point (day 0, 7, 14, 28, and 42), as mass loss is a common sublethal effect

of Bd exposure (Davidson et al. 2007, Retallick and Miera 2007, Harris et al. 2009a, 2009b,

Cheatsazan et al. 2013). No frogs died during the experiment, which lasted 42 days. At the end

of the experiment, frogs were euthanized in 0.1% MS-222.

Microbial community analysis

DNA from bacterial swabs was extracted using the Qiagen DNeasy Blood & Tissue Kit

(Valencia, CA) with lysozyme pretreatment. For 10 of the 13 frogs in each of the 3 Bd exposed

treatments, and all 7 individuals in each no Bd exposure treatment, the V4 region of the 16S

rRNA gene was amplified using the primers 515F and barcoded 806R (Caporaso et al. 2011,

2012). For each sample, triplicate reactions and a control without template were run. PCR

conditions followed the procedure in Caporaso et al. (2011). Equimolar amplified samples were

pooled, cleaned using Qiagen QIAquick PCR Clean Up Kit (Valencia, CA), and sequenced on

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the MiSeq Illumina platform with a 250 bp paired-end approach (Caporaso et al. 2012) at the

Dana Farber Cancer Institute’s Molecular Biology Core Facilities (Boston, MA).

Paired reads were assembled with Fastq-join (Aronesty 2011, 2013) and processed with

Quantitative Insights Into Microbial Ecology (MacQIIME v. 1.7.0) (Caporaso et al. 2010b).

Sequences were de-multiplexed and quality-filtered (Bokulich et al. 2013) based on if there were

any ambiguous base calls, errors in the barcode, less than 50% of read length had consecutive

base calls with a phred quality score greater than 4, more than 10 consecutive low-quality base

calls, or the read length was not between 252 and 255 bp. After quality filtering, the number of

reads was 18,299,242 (number of sequences per sample: 27,693-176,285). Quality-filtered

sequences were clustered into operational taxonomic units (OTUs) at a sequence similarity

threshold of 97% with the UCLUST method (Edgar 2010) and a minimum cluster size of 0.001%

of the total reads (Bokulich et al. 2013). Sequences were clustered against the 12_10 Greengenes

database (October 2012 release; DeSantis et al. 2006), and those that did not match the database

were clustered de novo at 97% sequence similarity. The most abundant sequence for a given

cluster was assigned as the representative sequence for that OTU. Taxonomy was assigned with

RDP classifier (Wang et al. 2007) using the Greengenes database (Claesson et al. 2009).

Representative sequences were aligned to the Greengenes database with PyNAST (Caporaso et

al. 2010a) and a phylogenetic tree was constructed with FastTree (Price et al. 2010). After the

0.001% OTU threshold was implemented, 2023 OTUs remained and the number of sequences

per sample ranged from 25,669 to 161,652. All samples were rarefied to 25,000 sequences to

standardize sampling effort prior to subsequent analyses.

Metabolite analysis

To examine skin community function, we characterized the metabolite profiles of

individual skin swabs using high performance liquid chromatography/mass spectroscopy

(LC/MS) with quadrupole, time-of-flight (qTOF) mass detection and Agilent MassProfiler

software. To extract the metabolites, 125 µL of HPLC grade methanol was added to each tube,

which was vortexed for approximately 3 sec and left to sit for 10 min. The swab was

subsequently removed from the centrifuge tube using tweezers that were washed with acetone.

During removal, the swab was squeezed along the side of the centrifuge tube to help remove any

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absorbed methanol extract and thus maximally recover sample. Methanolic extracts were

evaporated to dryness in vacuo. Crude, recovered material was reconstituted in 50 µL of 30%

LC/MS grade acetonitrile and 70% LC/MS grade water. The tube was then vortexed for 3 sec

and left to sit for 5 min.

A 6530 Accurate-Mass Q-TOF mass spectrometer coupled to a 1290 Infinity UHPLC

(Agilent Technologies, Santa Clara, CA) was used for sample analysis. Each sample was run in

triplicate with blank runs in between samples. Five µL of the sample was injected into the U-

HPLC equipped with an Eclipse Plus C18 column (2.1 x 100 mm) that was held at 50°C.

Compounds were eluted at a flow rate of 0.3 mL/min. with mobile phases of water with 0.1%

formic acid (A) and acetonitrile with 0.1% formic acid (B). Mobile phase A decreased from 95%

to 5% in 4.5 min, after which the mobile phase composition returned to the initial conditions and

held until 5 min. A 1.5 min post-run (95% A) ensured the column was flushed and equilibrated

for the next injection. After separation, compounds were ionized for mass spectrometric

detection by negative ion ESI at -3000 V. Agilent MassProfiler software was used to compare

the samples to a blank. Compounds found in the blank were subtracted from the bullfrog samples

so only metabolites of interest were analyzed.

The initial dataset contained 18,603 distinct compounds identified by the LC-MS

technology. To focus on the most dominant and likely important metabolites, and to reduce the

high dimensionality of the dataset for analysis, several filtering steps were performed. A

metabolite was deemed present if it appeared in all three replicates of a sample. Metabolites were

included in analyses if present on at least five samples across all samples and time points. In

addition, as our antibiotic treatment was effective at significantly decreasing bacterial diversity,

we also used that as a set point for the metabolite analysis, and only analyzed the metabolites that

were absent on all three replicates of antibiotic-treated frogs immediately following antibiotic

treatment (day 0). These filtering steps resulted in a final day 7 dataset that consisted of 176

metabolites.

Bd infection analysis

To quantify Bd infection, we used a quantitative, real-time PCR (qPCR) assay developed

by Boyle et al. (2004). Each run included a series of five dilution standards ranging in

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concentration by an order of magnitude from 0.1 to 1000 zoospore equivalents as well as a

negative control. The Bd strain used in the experimental exposures (Bd310) was used to create

the standards, which were run in triplicate. Samples were initially run in singlicate (Kriger et al.

2006); however, positive samples were rerun 1–2 more times to confirm the consistency of

results and more accurately estimate infection intensity. Samples with <0.1 zoospore estimates

were considered negative for the presence of Bd because the quantification accuracy outside the

range of the standards is unknown and low intensities are especially susceptible to indeterminate

results (Skerratt et al. 2011). To confirm that inhibition was not affecting amplification, an

internal positive control (Taqman Exogenous Internal Positive Control reagents, Applied

Biosystems, Foster City, CA, USA; Hyatt et al. 2007) was added to several randomly selected

samples. The positive control was added to one of the three triplicate reactions for each of these

samples.

Statistics

We examined the effects of the microbiota manipulations and Bd treatments on Bd

infection intensity, frog growth, microbial community structure (beta and alpha diversity, J.

lividum abundance), and function (metabolite profiles). Using individual-based models, we

tested for relationships between microbial community structure and Bd infection intensity, Bd

infection intensity and frog growth, and microbial community structure and function. Lastly, we

evaluated the effects of captivity and laboratory housing on the amphibian skin microbiota and

Bd infection. Below are the specific statistical methods we used to address each of these

questions.

Bd infection was characterized by prevalence (proportion of individuals infected) and

intensity (number of Bd zoospore equivalents). In the field, bullfrogs had low levels of Bd

infection, both in terms of prevalence (50%, 30 of the 60 frogs were infected) and intensity

(mean+/-SE = 0.61+/-0.25 zoospore equivalents, range = 0-14 zoospore equivalents). Our post-

experiment qPCR revealed that initial field levels of Bd infection did not differ across treatments

following our random assignment of individuals to treatment (Χ2=6.75, df=5, P=0.2); therefore,

initial infection intensity was not likely a factor in treatment effects on day 7 Bd infection

intensity or day 42 proportional growth. Treatment effects on Bd infection intensity at day 7

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were analyzed with a generalized linear model using a normal distribution. Bd infection intensity

at day 7 was log transformed to obtain a normal distribution. Transformation of Bd infection

intensity at day 42 did not result in a normal distribution; therefore, treatment effects on Bd

infection intensity at day 42 were analyzed with a Wilcoxon nonparametric ANOVA. The effects

of captivity on Bd infection intensity were analyzed by calculating the percent change in

zoospore intensity from the field to day 0 (prior to experimental Bd exposure) and performing a

Wilcoxon nonparametric ANOVA.

To examine treatment effects on frog growth, proportional growth between the beginning

(Day 0) and end (Day 42) of the experiment was calculated and used as the response variable in a

mixed model ANOVA with frog as a random effect. Day 0 was used as a baseline in this analysis

because there was no difference in mass among the six treatment groups at the start of the

experiment (ANOVA: df=5, F=0.797, P=0.557). Contrasts were used to compare growth

between unmanipulated and antibiotic- or J. lividum-treated frogs in different Bd environments.

To determine if individuals’ Bd infection intensity predicted frog growth at the end of the

experiment, linear regression was used to investigate proportional growth at Day 42 in response

to day 7 log-transformed Bd infection intensity.

Differences in microbial community structure (beta diversity) across time points and

treatments were examined statistically by PERMANOVA, which is a permutational multivariate

analysis of variance, on the relative abundance- and phylogenetic-based weighted UniFrac

distance matrices. Differences in microbial community function were also analyzed by

PERMANOVA on the incidence-based Sorensen dissimilarity matrix generated from day 7

metabolite profiles. Pair-wise tests between treatments were performed on the matrices. For both

structure and function matrices, non-metric multidimensional scaling (Kruskal 1964) was used to

visualize differences among individual frogs. The programs Primer 6 version 6.1.15 and

Permanova+ version 1.0.5 (Clarke and Gorley 2006) were used for these analyses. To test for a

relationship between individuals’ microbial community structure prior to Bd exposure (day 0)

and Bd infection intensity one week following exposure (day 7), a Mantel test was performed

using the day 0 weighted UniFrac distance matrix and the day 7 Bd infection intensity Euclidean

distance matrix. To test for a relationship between individuals’ microbial community structure

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and function at day 7, one week following Bd exposure, a Mantel test was performed using the

day 7 weighted UniFrac distance matrix and the day 7 metabolite Sorensen matrix.

We could not account for Bd-produced metabolites in the metabolite profiles. However,

we don't think this impacted our results for several reasons. First, there was an effect of Bd on

microbial community structure, therefore, it is reasonable to expect that there could also be an

effect on metabolite profiles. Also, within a bacterial treatment, the effect of Bd on metabolites

varied (J. lividum-yes, antibiotics and unmanipulated-no). This suggests that the observed

patterns in metabolite profiles are not likely an artifact of Bd produced metabolites, but rather an

accurate representation of bacterially-produced metabolites and thus function.

To test for treatment effects (microbiota manipulation, Bd exposure, and their interaction)

on alpha diversity (OTU richness and phylogenetic diversity) one week after exposure to Bd,

generalized linear models using a normal error distribution were used. Pair-wise contrasts were

conducted for each analysis. The alpha diversity metrics of OTU richness and phylogenetic

diversity were computed on rarefied data with MacQIIME.

The relative abundance of J. lividum OTUs were compared across bacterial treatments

using a nonparametric Wilcoxon ANOVA followed by Steel-Dwass multiple comparisons. This

was done using the Illumina dataset, with the relative abundances combined for two J. lividum

OTUs that had 99.6% or greater sequence similarity to the isolate used in the experiment.

Additionally, to test for a relationship between J. lividum relative abundance and Bd infection

intensity of individuals within the J. lividum treatment at day 7, linear regression was used.

The effects of bringing frogs into captivity on microbial diversity were analyzed by

calculating percent change in OTU richness and phylogenetic diversity from the initial sample to

day 0 (3 weeks in the lab and immediately post-microbiota manipulation treatments). To

compare changes in diversity across microbiota manipulation treatments, Wilcoxon

nonparametric ANOVA was used with Steel-Dwass nonparametric adjusted pair-wise

comparisons among treatments. To identify OTUs driving differences in microbial communities

over time and across treatments, the relative abundances of each OTU were compared across

time points with Kruskal-Wallis tests with Bonferroni corrected p-values using MacQIIME.

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Results

Bd infection intensity

Bd-exposed frogs had significantly higher infection intensity at day 7 than unexposed

frogs (Figure 2a; Bd exposure: Χ2=37.64, P<0.001), demonstrating successful laboratory

infection with Bd. However, there was no effect on Bd infection intensity of microbiota

treatment or the interaction between Bd exposure and microbiota treatment at day 7 (Figure 2a;

Microbiota manipulation: Χ2=1.48, P=0.5; Microbiota manipulation*Bd exposure: Χ

2=0.57,

P=0.8). Within the J. lividum treatment, in fact, there was a significant positive relationship

between relative abundance of J. lividum at day 7 and Bd infection intensity at day 7 (F=6.74,

P=0.02, R2=0.31), with individuals harboring higher levels of J. lividum also having higher

levels of Bd.

Frog Growth

All frogs survived and gained weight over time, but those exposed to Bd tended to grow

less over the course of the experiment than those not exposed to Bd (Figure 2b; F=3.63, P=0.06).

Microbiota manipulation did not affect growth (F=2.15, P=0.1), and there was no interaction

between bacteria and Bd (F=0.09, P=0.9). However, in a Bd environment, antibiotic-treated

frogs grew significantly less than frogs with their microbiota unmanipulated (Figure 2b;

AntibioticBd-UnmanipBd: t=-1.98, P=0.05). Without exposure to Bd, there was no difference in

growth between unmanipulated and antibiotic-treated frogs (t=-1.05, P=0.3). Augmentation with

J. lividum did not significantly affect growth, with (J. lividumBd-UnmanipBd: t=-1.14, P=0.26)

or without exposure to Bd (J. lividumNoBd-UnmanipNoBd: t=0.13, P=0.89). There was a

significant relationship between individual frogs’ Bd infection intensity at day 7 and their growth

at day 42 (F=8.27, P=0.006, R2=0.12), such that frogs with higher infection tended to grow less

(Figure 2c).

Microbial Community Structure – Beta diversity

Microbiota manipulation resulted in differences in microbial community structure at day

0 (PERMANOVA: Pseudo-F=15.21, P<0.001). Antibiotic treatment (Unmanip-Antibiotic:

t=4.30, P<0.001) and addition of J. lividum (Unmanip-J. lividum: t=1.62, P=0.01) altered the

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normal microbial community. Different microbial community structures before Bd exposure

(weighted UniFrac) were significantly associated with variation in Bd infection intensity one

week post-Bd exposure on day 7 (Bd-exposed frogs only, Mantel r statistic=0.15, P=0.03).

Exposure to Bd significantly affected microbial community structure one week post-

exposure (day 7; PERMANOVA: Pseudo-F=3.34, P=0.008). Interestingly, there was an

interaction between microbiota manipulation and Bd exposure treatments, such that J. lividum

and antibiotic treatment altered the normal microbiota only when individuals were also exposed

to Bd (Figure 3a,b; Bd exposed: Pseudo-F=9.66, P<0.001; Not Bd exposed: Pseudo-F=1.58,

P=0.06). To determine if particular OTUs were driving these differences in community structure

among Bd exposed individuals, we compared relative abundances of each OTU across

microbiota manipulation treatments and identified 37 OTUs that differed significantly across

microbiota manipulation treatments at day 7, including J. lividum OTUs. Among these 37

significant OTUs, a Comamonadaceae OTU exhibited the highest overall relative abundance,

and was highest in the unmanipulated treatment (20.7% mean relative abundance +/- 3.2%

standard error), medium in the J. lividum treatment (5.9% mean relative abundance +/- 2.0%

standard error), and very low in the antibiotic treatment (0.06% mean relative abundance +/-

0.008% standard error). Although there were other significantly different OTUs, they were

typically in low mean relative abundance (<0.6%).

Microbial Community Structure – Alpha Diversity

One week after exposure to Bd (day 7), there was a significant effect of microbiota

manipulation treatment and a significant interaction between microbiota manipulation and Bd

exposure treatments on OTU richness; however, exposure to Bd overall did not significantly

affect OTU richness (Figure 4a; GLM—overall: Χ2=26.83, df=5, P<0.0001; Microbiota

manipulation: Χ2=18.52, df=2, P<0.0001; Bd exposure: Χ

2=2.76, df=1, P=0.1; Microbiota

manipulation*Bd exposure: Χ2=6.33, df=2, P=0.04). Frogs treated with antibiotics continued to

harbor fewer OTUs than unmanipulated frogs (Χ2=18.25, P<0.0001). Interestingly, J. lividum-

treated frogs that were also exposed to Bd had greater OTU richness than J. lividum-treated frogs

that were not exposed to Bd (Figure 4a; Χ2=7.65, P=0.006). However, within the unmanipulated

or antibiotic treatments, there was no effect of Bd on OTU richness (UnmanipBd-

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UnmanipNoBd: Χ2=0.69, P=0.4; AntibioticBd-AntibioticNoBd: Χ

2=0.62, P=0.4). Microbiota

manipulation treatment, but not Bd treatment or their interaction, significantly affected

phylogenetic diversity of the bacterial skin communities on day 7 (Figure 4b; GLM—Bd

exposure: Χ2=1.23, P=0.3; Microbiota manipulation: Χ

2=18.5, P<0.001; Microbiota

manipulation*Bd exposure: Χ2=4.02, P=0.1). Frogs treated with antibiotics had lower

phylogenetic diversity than unmanipulated frogs (Χ2=18.29, P<0.0001), and J. lividum-treated

frogs that were also exposed to Bd had greater phylogenetic diversity than those that were not

exposed to Bd (Figure 4b; Χ2=4.18, P=0.04).

Microbial Community Structure – J. lividum relative abundance

J. lividum-treated frogs exposed to Bd had higher levels of J. lividum than unexposed

frogs (Steel-Dwass— J. lividumBd- J. lividumNoBd: Z=-3.37, P=0.01), while Bd exposure did

not significantly affect J. lividum abundance within the antibiotic or unmanipulated treatments

(Steel-Dwass—AntibioticsBd-AntibioticsNoBd: Z=-0.82, P=0.96; UnmanipBd-UnmanipNoBd:

Z=0.59, P=0.99). Providing further support for an interaction between Bd and J. lividum, within

the Bd exposed group, J. lividum-treated individuals had significantly higher levels of J. lividum

than individuals with an unmanipulated microbiota (Steel-Dwass— J. lividumBd-UnmanipBd:

Z=-3.76, P=0.002); however, without exposure to Bd, J. lividum and control treatments did not

have different levels of J. lividum (Steel-Dwass— J. lividumNoBd-UnmanipNoBd: Z=-2.63,

P=0.09).

Microbial Community Function – Metabolite Profiles

Similar to the effects of Bd on microbial community structure, exposure to Bd

significantly affected metabolite profiles one week after Bd exposure (day 7; PERMANOVA:

Pseudo-F=2.78, P=0.006). Also consistent with the community structure data, there was an

interaction between microbiota manipulation and Bd exposure treatments, such that microbiota

manipulation affected metabolite profiles only on individuals also exposed to Bd (Figure 3c,d;

Bd exposure: Pseudo-F=1.72, P=0.01; No Bd exposure: Pseudo-F=1.16, P=0.3). Furthermore,

individuals’ microbial community structure at day 7 directly related to metabolite profiles at day

7 (Mantel r statistic=0.15, P=0.02).

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Laboratory housing effects on Bd infection and bacterial skin microbiota

In the field, bullfrogs had low levels of Bd infection, both in terms of prevalence and

intensity. After bringing the frogs into the lab and subsequent microbiota manipulation

treatments, Bd infection increased substantially at day 0 prior to Bd exposure (Prevalence: 93%;

Intensity: mean+/-SE = 78.8+/-16.5 zoospore equivalents, range = 0-577 zoospore equivalents),

but percent increase did not differ by microbiota manipulation treatment (Wilcoxon Χ2=2.77,

P=0.25). By the end of the experiment on day 42, levels of infection decreased again, were more

similar to initial field levels (Prevalence: 63%; Intensity: mean+/-SE = 2.84+/-1.23 zoospore

equivalents, range = 0-70 zoospore equivalents) and did not differ by any treatment (Wilcoxon

Χ2=5.91, P=0.3).

Bullfrogs experienced a reduction in bacterial diversity (OTU richness and phylogenetic

diversity) following laboratory housing. The change in OTU richness from the field to day 0 (3

weeks) differed based on microbiota manipulation treatment (Figure 5a; Wilcoxon, Χ2=9.94,

P=0.007), such that frogs treated with antibiotics lost significantly more OTUs than those in the

unmanipulated or J. lividum treatments (Figure 5a; Steel-Dwass—Antibiotic-Unmanip: Z=2.45,

P=0.04; Antibiotic- J. lividum: Z=2.93, P=0.02). However, phylogenetic diversity was reduced

equally among all three treatment groups over the same time frame (Figure 5b; Wilcoxon,

Χ2=3.88, P=0.14).

Regardless of treatment, microbial communities of bullfrogs changed over time

(PERMANOVA: Pseudo-F=12.78, P<0.001). Bringing bullfrogs into the lab changed their

microbial communities (initial-day0: t=3.34, P<0.001), and they continued to change in the lab

over time (day0-day7: t=2.43, P=0.002). To identify the particular OTUs that contributed to

these differences, we focused on OTUs that were present at a mean relative abundance of 0.5%

or greater across all treatments and time points. Of these 23 OTUs, nearly half (11 of 23 OTUs)

did not change significantly from field levels, including the three most abundant OTUs in the

field related to Sanguibacter sp., Comamonadaceae, and Rhodococcus sp. (Table 2; mean

relative abundances in the field: 16.4, 14.7, and 9.4%, respectively). Nine OTUs significantly

increased in abundance, including the Janthinobacterium lividum OTU that was used in the

probiotic treatments (Table 2). In most cases, the abundance of these OTUs increased

94

continuously at each time point with the exception of an OTU related to Comamonas sp., which

increased dramatically in abundance at Day 0, followed by a marked decrease by day 7. Two

OTUs in the genus Acinetobacter also increased dramatically on day 0 and were maintained at

high levels through day 7. There were three OTUs that decreased significantly over time,

including an OTU related to Comamonadaceae that was highly abundant on frogs in the field

(Table 2; mean relative abundance in the field: 9%)

Discussion

We have experimentally demonstrated that Bd is a selective force on amphibian skin

bacterial community structure and function. There were differences in community structure and

function between unmanipulated, antibiotic-treated, and J. lividum-treated frogs only when

individuals were exposed to chytrid fungus. Without the pressure of the pathogen, there were no

differences in microbial community structure or function between microbiota manipulation

treatments. These differences in microbial community structure and function provide an

explanation for the reduced growth of antibiotic-treated frogs only when they were exposed to

Bd. Furthermore, individuals’ microbial community structure prior to Bd exposure significantly

influenced Bd infection intensity one week post Bd exposure. This suggests that these bacterial

symbiont communities can limit infection, but that the extent of that defense is likely dependent

on community structure, and subsequent function. Another recent study has also found that the

initial microbial community structure associated with amphibians, in that case the Bd-susceptible

Panamanian golden frog, predicted survival following Bd exposure (M.H. Becker et al.,

unpublished data). This relationship between host-associated microbiota and disease outcomes

has been observed in many other systems as well (Costa et al. 2007, Ley 2010, Mao-Jones et al.

2010, Rosenthal et al. 2011, Morrow et al. 2013). In humans, early microbial imbalance of

preterm infants’ intestinal microbiota is predictive of the devastating intestinal disease,

necrotizing enterocolitis (Morrow et al. 2013). Knowing whether a disease-limiting microbial

community structure exists can inform efforts to manipulate the microbiome to increase host

defenses to disease. For instance, root exudates of plants can be used to modify the rhizosphere

microbiome to promote disease suppression (Chaparro et al. 2012), and in humans, entire fecal

microbiota can be transplanted to eliminate recurrent Clostridium difficile infections with a 90%

success rate (Gough et al. 2011). Overall, our results, which are based on a novel system and

95

functional endpoint, highlight the general importance of understanding the impacts of

community structure on “ecosystem” function (Balvanera et al. 2006, Pasari et al. 2013).

We identified a direct link between community structure and function, and both were

altered by pathogen exposure. Therefore, according to our conceptual model (Figure 1), we can

hypothesize that one or more keystone bacterial species may be playing a major role in driving

these patterns. In aquatic microbial communities, certain metabolic functions are in fact mediated

by individual phylotypes, as opposed to being related to diversity of the whole community (Peter

et al. 2011). Within Bd exposed frogs, we identified 37 OTUs that differed significantly in mean

relative abundance across bacterial treatments. One of these OTUs, in the family

Comamonadaceae, may potentially serve as a keystone species in these microbial communities,

as it was the most dominant member in the unmanipulated communities, moderately dominant in

the probiotic treatment, and very rare in the antibiotic treatment. Members of the

Comamonadaceae family are culturable and abundant on wild bullfrogs and other amphibian

species, and some of them can inhibit Bd growth in vitro (Flechas et al. 2012, Roth et al. 2013,

Michaels et al. 2014, J.B. Walke et al., unpublished data). Furthermore, in another amphibian

study, OTUs belonging to this family were significantly positively associated with susceptible

amphibians that cleared experimental Bd infection (M.H. Becker et al., unpublished data). It is

therefore plausible that this bacterial group may play a key role in limiting Bd infection for

amphibian hosts.

Further supporting the relationship between pathogen exposure and the response of the

microbiota are the findings that, within the J. lividum treatment, Bd exposed frogs had higher

OTU richness, phylogenetic diversity, and J. lividum relative abundance. This suggests an

interaction between Bd and J. lividum, such that high J. lividum abundance and overall diversity

is maintained by pathogen exposure. Interestingly, metabolites produced by Bd can enhance the

growth of J. lividum in vitro (Woodhams et al. 2014). The maintenance and effectiveness of J.

lividum against Bd in many cases may in fact be facilitated by Bd. Microbial community

structure appears to be responding to pathogen exposure in a context-specific manner. This also

occurs in coral systems, where temperature changes cause shifts in the microbiota towards a

disease-associated state (Teplitski and Ritchie 2009, Vega Thurber et al. 2009, Mao-Jones et al.

2010).

96

We hypothesized that a reduced microbiota would increase susceptibility of bullfrogs to

the effects of Bd. While antibiotic-treated frogs did not have significantly lower Bd infection

intensities, they grew less than frogs with unmanipulated microbiota following Bd exposure. At

the individual level, the initial microbial community structure of bullfrogs predicted Bd infection

intensity, which then predicted host fitness in terms of growth. These results demonstrate that the

normal microbiota of bullfrogs is important for disease outcome and host fitness, and are

consistent with other amphibian studies that suggest that the skin microbiota is an important

factor for host response to Bd infection (Becker and Harris 2010, Woodhams et al. 2012).

Therefore, factors that determine microbiota community assembly on amphibian skin, including

environmental conditions, host factors, and the available microbial species pool, are important to

consider (Kueneman et al. 2014, Antwis et al. 2014, Michaels et al. 2014, Loudon et al. 2014,

Walke et al. 2014), as this has the potential to influence disease dynamics in natural amphibian

communities. For example, changes in temperature can alter the functional, anti-Bd capabilities

of amphibian skin symbionts (Daskin et al. 2014, Woodhams et al. 2014), which could directly

influence Bd susceptibility.

Bioaugmentation with probiotic bacteria is a promising tool in amphibian conservation

(Woodhams et al. 2011, Bletz et al. 2013). The probiotic used in this study, Janthinobacterium

lividum, has been successfully used to prevent morbidity and mortality in other amphibian

species that naturally harbor this bacterium on their skin (Becker et al. 2009, Harris et al. 2009a,

2009b). However, J. lividum was not effective as a probiotic in a tropical frog species, on which

it does not occur naturally, and is not maintained on the skin following experimental inoculation

(Becker et al. 2012). While this bacterium is a member of bullfrogs’ normal microbiota and it did

successfully colonize bullfrogs’ skin, it did not reduce Bd infection intensity in this study. In

fact, at the individual level, J. lividum relative abundance was positively correlated with levels of

Bd. This suggests that, in bullfrogs, this bacterium is unlikely to be useful for controlling Bd

infection. Bullfrogs are important for global transmission of Bd (Hanselmann et al. 2004, Garner

et al. 2006, Ficetola et al. 2006, Bai et al. 2010, Schloegel et al. 2010); therefore, controlling Bd

on bullfrogs has the potential to control global transmission of Bd.

This study also addressed the effects of laboratory housing on Bd infection and skin

bacterial communities. We found that bringing frogs into the lab caused a spike in Bd infection

97

intensity and prevalence, prior to Bd being introduced to the lab facility. We hypothesize that the

stress of collection and laboratory housing contributed to this spike. Prevalence presumably

increased because individuals that were considered negative for Bd by qPCR likely had very low

levels of Bd. We also observed changes in microbiota from field to lab settings and also over

time in the lab. Differences in wild and captive amphibian skin bacterial community structure,

specifically differences in relative abundances of community members, have been seen in other

amphibian species as well (Loudon et al. 2014, Becker et al. 2014). These observed changes in

microbiota, in combination with stress, could have contributed to the increase in Bd infection

upon bringing the frogs into the lab, as we have demonstrated that bacterial skin community

structure is related to Bd infection intensity. We also found that Bd infection eventually declined

over time in the lab, resulting in levels comparable to field levels by the end of the experiment.

This implies that bullfrogs may not be efficient long-term carriers of Bd, as suggested by another

bullfrog Bd infection experiment (Gervasi et al. 2013). However, this could vary by Bd strain

and could be dependent upon whether the frog and strain co-occur in nature. In this experiment,

we used a strain not found in the native habitat of bullfrogs.

In addition to microbial community structure changing over time in the lab, we also

observed a reduction in diversity (richness and phylogenetic diversity) upon bringing frogs into

the lab. However, half of the abundant field OTUs did not change in relative abundance from

field levels, including the three most abundant OTUs (Sanguibacter sp., Comamonadaceae, and

Rhodococcus sp.). Another highly abundant Comamonadaceae OTU, however, did decrease

significantly over time. Antibiotic treatment also altered the microbial community structure of

bullfrog skin, and this effect continued for at least one week. Long-lasting effects of antibiotics

on microbial community structure have also been seen in humans (Lozupone et al. 2012), and in

fact, even short-term antibiotic treatments can leave lasting impacts on microbial community

structure (Jernberg et al. 2007, Jakobsson et al. 2010).

In conclusion, our results show that microbial community structure, and not treatment

with the probiotic J. lividum, was related to reduced pathogen load on bullfrogs. The

investigation into the use of other probiotics is still a worthwhile effort to control bullfrog-

transmitted Bd, and our results draw attention to the potential key role that Comamonadaceae

may play. Our results also highlight the importance of a pathogen-limiting structure of the

98

community, as opposed to the addition of a single probiotic bacterium to limit infection. The

addition of a single probiotic bacterium can serve to manipulate microbial community structure

and function; however, in our study this only occurred in the face of pathogen exposure. This has

important implications for captive amphibian populations with goals of reintroduction.

Abundance of the probiotic itself as well as probiotic-mediated shifts in microbial community

structure and function may only be maintained with pathogen exposure. Taken together, we

found that microbial community structure influenced disease-limiting function in amphibians.

Studies such as this, that experimentally manipulate complex host-associated microbial

communities and potential selective forces, are valuable towards elucidating generalizations in

structure-function patterns and regulating mechanisms (Krause et al. 2014).

Acknowledgements

We thank R.N. Harris for thoughtful discussions, R.J. Domangue for statistical assistance, C.

Hughey for metabolite profile analysis assistance, and J. Linkous for field and laboratory

assistance. We are also grateful to Zach Herbert at the Molecular Biology Core Facilities at

Dana-Farber Cancer Institute for Illumina sequencing, as well as University of Virginia’s

Mountain Lake Biological Station for allowing us to work on their land. This work was

supported by the Virginia Tech Fralin Life Sciences Institute and the National Science

Foundation (DEB-113640), and all procedures were approved by Virginia Tech’s Institutional

Animal Care and Use Committee (Protocol number: 08-042-BIOL).

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109

Table 1. Experimental timeline showing field collection, bacterial treatment applications, Bd

exposures, and swabbing regime. Analyses focused on initial, day 0, day 7, and day 42 time

points.

Day -21 -14 -11 -4 0 4 7 42

Event Collected

from field

Antibiotic

treatment

started

J. lividum

inoculation 1

J. lividum

inoculation 2

Antibiotics

ended; Bd

exposure 1

Bd

exposure

2

Experiment

ended

Swab Initial DNA

swabs (field)

Day 0 DNA and

metabolite swabs (pre-Bd

exposure)

Day 7 DNA and

metabolite swabs (post-Bd

exposure)

Day 42 DNA

swabs - used for Bd only

Table 2. List of 23 OTUs with total mean relative abundance >0.5% across all samples and time

points and whether they changed in abundance significantly over time, based on a Kruskal-

Wallis test with Bonferroni corrected p values. OTUs are ranked in order of relative abundance

in the initial field samples, and the probiotic J. lividum OTU is bolded.

OTU ID Taxonomy Change over time Initial Day 0 Day 7 Test-Statistic Bonferroni_P

4378239 Sanguibacter No change 16.40 13.43 10.28 7.21 1.000

denovo138967 Comamonadaceae No change 14.73 13.59 12.65 1.95 1.000

4468125 Rhodococcus No change 9.41 7.36 3.56 17.63 0.301

315609 Comamonadaceae Decrease 8.95 0.01 0.01 89.65 <0.0001

817507 Brucellaceae No change 3.46 0.83 1.52 15.62 0.821

4473756 Cellulomonadaceae No change 3.39 3.92 1.86 12.88 1.000

269930 Pseudomonas veronii Decrease 2.50 1.01 0.76 21.99 <0.05

denovo117108 Spirobacillales Decrease 2.28 0.12 <0.01 42.62 <0.0001

4323897 Oxalobacteraceae No change 1.77 0.88 0.97 17.40 0.337

710275 Acinetobacter No change 1.61 0.02 0.01 1.88 1.000

1139932 Xanthomonadaceae No change 1.46 1.20 0.44 19.25 0.134

109263 Pseudomonadaceae No change 1.08 2.37 1.82 10.84 1.000

4469492 Comamonadaceae Increase 0.26 1.10 0.93 36.56 <0.0001

589010 Vogesella No change 0.18 0.61 1.12 1.05 1.000

4449458 Acinetobacter Increase 0.07 8.42 8.20 62.57 <0.0001

103411 Acinetobacter johnsonii Increase 0.02 5.47 6.69 69.37 <0.0001

71872 Comamonas Increase 0.02 11.50 0.36 72.89 <0.0001

677049 Chryseobacterium joostei Increase 0.02 1.70 2.74 74.59 <0.0001

4323076 Janthinobacterium lividum Increase 0.01 0.94 2.94 42.62 <0.0001

325027 Comamonas Increase 0.01 2.35 3.96 59.99 <0.0001

3330580 Stenotrophomonas Increase 0.01 0.23 1.98 26.15 <0.05

635524 Stenotrophomonas No change 0.01 0.46 1.04 7.91 1.000

64653 Acinetobacter Increase 0.01 <0.01 1.89 100.68 <0.0001

110

Figure 1. Conceptual model representing potential responses and interpretations of microbial

community structure and function in the presence of a pathogen.

Microbial community

function

Microbial community structure

Pathogen presence

Change

ChangePossible keystone

species

No changeFunctional

Redundancy

No change

ChangePathogen a selective force; Shift towards disease resistance

No changePathogen not a selective force

111

Figure 2. Effects of treatment on bullfrogs’ Bd infection intensity at day 7 (a) and proportional

growth at day 42 (b). Error bars represent standard error. The significant relationship between

individual bullfrogs’ Bd infection intensity at day 7 and proportional growth at day 42, the end of

the experiment, is shown (c).

0

0.5

1

1.5

2

Bd

infe

ctio

n i

nte

nsi

ty a

t

Day 7

(lo

g-t

ran

sform

ed)

Normal Antibiotics J. lividum

No Bd


Bd

0

0.1

0.2

0.3

Pro

port

ion

al G

row

th a

t

Da

y 4

2


No Bd


Bd

a

b

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.0 1.0 2.0 3.0

Pro

po

rtio

na

l G

row

th a

t D

ay

42

Bd infection intensity at Day 7 (log-transformed)

c

112

Figure 3. NMDS ordinations based on weighted UniFrac distance matrices (a,b) and Sorensen

dissimilarity matrices (c,d) representing differences among microbiota manipulations in

microbial community structure and metabolite profiles, respectively, of frogs exposed (a,c) and

unexposed (b,d) to Bd one week after initial exposure to Bd. There were differences in microbial

community structure and metabolite profiles among microbiota manipulation only with Bd

exposure.

BacteriaTrtJlividum

Antibiotics

Normal

2D Stress: 0.11 BacteriaTrtNormal

Jlividum

Antibiotics

2D Stress: 0.14


Resemblance: S17 Bray Curtis similarity

BacteriaTrtNormal

Jlividum

Antibiotics

2D Stress: 0.09

Bd exposurea

No Bd exposure

b


BacteriaTrtJlividum

Antibiotics

Normal

2D Stress: 0.13


BacteriaTrtJlividum

Antibiotics

Normal

2D Stress: 0.12

c d

Mic

rob

iota

Met

ab

oli

tes

113

Figure 4. Effects of Bd exposure (white bars=No exposure to Bd; black bars=Exposure to Bd)

and bacterial treatment (normal, antibiotics, and augmented with J. lividum) on OTU richness

(a), phylogenetic diversity (b), and relative abundance of the probiotic J. lividum (c) on bullfrog

skin one week following exposure to Bd (day 7). Error bars represent standard error. * represent

significant within bacterial treatment differences between Bd treatments.

0

5

10

15

J. l

ivid

um

Rela

tiv

e A

bu

nd

an

ce

*


Bd treatment

0

100

200

300

400

500

600

700O

TU

Ric

hn

ess


*

0

10

20

30

40

50

60

Ph

ylo

gen

eti

c D

iversi

ty


*

a

b

c

Bacterial treatment *

Bd treatment

Bacterial treatment *

Bd treatment

114

Figure 5. Effects of bacterial treatment (normal, antibiotics, and augmented with J. lividum) on

changes in OTU richness (a) and phylogenetic diversity (b) of bullfrogs’ skin microbiota from

the field to day 0 (three weeks after collection and immediately following bacterial treatment).

Error bars represent standard error.

-50

-40

-30

-20

-10

0

10

20P

ercen

t C

ha

ng

e i

n O

TU

Ric

hn

ess


-40

-35

-30

-25

-20

-15

-10

-5

0

Percen

t C

ha

ng

e i

n P

hy

log

en

eti

c

Div

ersi

ty


a

b

115

Chapter 5. Synthesis

All animals, including humans, host diverse microbial communities and are exposed to

pathogens, and therefore, while my dissertation focused on amphibians, understanding the

ecology of host-microbe-pathogen interactions is broadly relevant. Consistent with what has

been seen with sponge, squid, and fish symbionts, results presented in Chapter 2 suggest that

amphibian skin harbors microbes that are generally in low abundance in the environment, as

opposed to being colonized by microbes that are abundant in the environment (Walke et al.

2014). These results, in combination with other recent studies, suggest that the amphibian skin

microbiota is likely to be maintained by a mixture of transmission modes (e.g. Banning et al.

2008, Walke et al. 2011, 2014, Muletz et al. 2012) and is likely to vary depending on species’

life histories. Future research should focus on factors regulating the colonization of these

symbionts, including interactions with amphibian-produced antimicrobial peptides, as this will

provide further insight into the ecology and evolution of this symbiosis. Elucidating the

transmission dynamics of amphibian skin symbionts in a variety of host species will inform

probiotic efforts, specifically whether environmental inoculation, as opposed to individual

inoculations, will be an effective way to deliver probiotics to amphibians. The study reported in

Chapter 3 demonstrated that, although only a small portion of amphibian skin microbial

communities are being cultured with current methods, the cultures represent dominant members

of the community. This is encouraging for environmental probiotic delivery because even if an

environment is supplemented with probiotic cultures and these cultures are at relatively low

abundances in the environment, they should be able to colonize amphibian skin and become

dominant community members.

Efforts should be made to expand collections of amphibian skin bacterial cultures, as

cultures are critical to fully understand the function and potential applications of these microbes.

Based on results from Chapter 3, several specific suggestions were identified that may

potentially increase the diversity of isolated bacteria, including performing serial dilutions,

simulating the conditions of amphibian skin in vitro (e.g. pH), using different media types

including those supplemented with amphibian skin washes, as well as attempting the diffusion

chamber method of culturing on the actual skin. Even with the current culturing method,

however, most of the dominant bacteria were cultured, at the phylum, family, and OTU or

116

“species” levels. I hypothesize that these abundant, cultured bacteria are also functionally

important in terms of their activity against Bd because of their demonstrated competitive

advantage, likely mediated by dominance in resource acquisition (Zubkov et al. 2003) and

microbial defense mechanisms (Riley and Wertz 2002). Further studies that directly correlate

microbial abundance and inhibitory capabilities against Bd are needed to fully test this

hypothesis.

The results reported in Chapter 2 contribute to the mounting evidence that different

amphibian species and populations harbor distinct microbial communities (McKenzie et al. 2012,

Kueneman et al. 2014, Walke et al. 2014), and that this may explain why some amphibian

species and populations are more susceptible to Bd than others (Daszak et al. 2004, Briggs et al.

2005, Searle et al. 2011). Indeed, the study reported in Chapter 4 identified a link between the

microbial communities associated with individuals and Bd infection intensity, further supporting

the role microbial communities play in explaining individual, species, and population variation in

disease susceptibility in amphibians. Surveys of microbial communities associated with

susceptible amphibian species in comparison with those that are resistant will be key to exploring

this hypothesis. Approaches to this comparison should include analyzing beta diversity as well as

differences in relative abundances of potentially important bacterial groups, such as the

Comamonadaceae group identified in Chapter 4. Amphibians are just one example

demonstrating a relationship between host-associated microbiota and disease outcome, as this

pattern is observed in many other systems, including humans, plants, and corals (Costa et al.

2007, Ley 2010, Mao-Jones et al. 2010, Rosenthal et al. 2011).

Results presented in Chapter 4 demonstrate that an altered microbiota can increase

susceptibility to disease. Further research on factors that alter amphibian skin microbiota is

needed, including temperature, contaminants, and habitat alteration, so that we may predict and

potentially prevent disease outbreaks. Furthermore, if altered, microbial community structure and

function that are associated with certain species or populations may alter susceptibility, which

has the potential to impact disease dynamics at a broader scale.

Microbial experimental manipulation studies with the aim of further understanding

structure-function relationships are limited, yet given the advancement in molecular tools for

117

assessing communities, have great potential to elucidate general patterns and mechanisms

underlying structure-function relationships (Krause et al. 2014). The study presented in Chapter

4 provides an experimental examination of the relationship between microbial community

structure and disease-limiting function in amphibians. The expected links between microbial

community structure and function in complex symbiont consortia are not entirely clear. For

instance, different community structures, with varying relative abundances of individual

microbes, could provide similar functions for the host (especially given the potential for

horizontal gene transfer), or there could be groups of critical taxa that must be present for a

function to be performed. These differences in the potential relationship between microbial

community structure and function can be conceptualized based on the expected changes incurred

in community structure and the functional response. In Chapter 4, I focused on understanding

these relationships in the context of pathogen exposure, as potentially lethal pathogens should be

strong selective forces on the defensive microbial symbiont communities. I found that there may

actually be keystone bacterial species within these complex skin communities that could be

significant contributors to disease resistance, although more work will need to be done to

confirm that finding. For example, a probiotic experiment using the potentially key

Comamonadaceae OTU identified in Chapter 4 could be conducted to test if treatment with this

bacterium can reduce Bd infection in bullfrogs, which would have great potential for probiotic

therapy to reduce the global transmission of Bd. Indeed, this OTU was 97.2% related to a

cultured OTU from Chapter 3, which contained isolates >90% inhibitory against Bd. This study

would complement the survey mentioned above comparing the relative abundance and

prevalence of this bacterial group between susceptible and resistant amphibian species. On the

other hand, the probiotic strategy of using a single bacterial isolate may not be the best approach,

as results from probiotic-Bd infection experiments using a variety of amphibian and single

bacterial species have had mixed results. It may not be realistic to conduct multiple laboratory

trials with different bacterial isolates for each amphibian species until a successful isolate is

identified. Instead, a whole bacterial community probiotic approach may be necessary, and more

efficient and effective, to provide protection to a variety of amphibian hosts.

In conclusion, by combining experimental and observational approaches, my dissertation

research characterized the microbial community structure and function associated with

amphibian skin and identified both as being important factors influencing susceptibility to

118

disease. In addition to informing conservation efforts, my dissertation research contributes to the

field of microbial ecology by addressing ecological questions in a novel habitat, thus advancing

the understanding of the interactions among microbes, their hosts, and their environments.

Finally, my results extend to the general ecological debate regarding the importance of

community structure on ecosystem function (Balvanera et al. 2006, Pasari et al. 2013) by

focusing on a unique host-microbe system and functional endpoint.

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