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:
Matthew H. Becker, Virginia Tech, Blacksburg, VA: contributed to the conceptual design of the
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
Lisa K. Belden, Virginia Tech, Blacksburg, VA: contributed to the conceptual design of the
study, analysis, and manuscript development
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:
Matthew H. Becker, Virginia Tech, Blacksburg, VA: contributed to the conceptual design of the
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
Lisa K. Belden, Virginia Tech, Blacksburg, VA: contributed to the conceptual design of the
study, analysis, and manuscript development
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
Chapter 3: Linking culture-dependent and -independent characterizations of amphibian
skin microbial communities: Important insights into the use of probiotics in amphibian
conservation ..........................................................................................................................44
Abstract ......................................................................................................................44
Introduction ................................................................................................................44
Materials and Methods ...............................................................................................46
Results ........................................................................................................................53
Discussion ..................................................................................................................55
References ..................................................................................................................60
Chapter 4: Community structure and function of amphibian skin microbes: an
experimental test with bullfrogs exposed to chytrid fungus ............................................78
Abstract ......................................................................................................................78
Introduction ................................................................................................................79
Materials and Methods ...............................................................................................81
Results ........................................................................................................................90
Discussion ..................................................................................................................94
References ..................................................................................................................98
Chapter 5: Synthesis ...........................................................................................................115
References ..................................................................................................................118
viii
List of Tables
Chapter 2: Amphibian skin may select for rare environmental microbes
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
Chapter 3: Linking culture-dependent and -independent characterizations of amphibian
skin microbial communities: Important insights into the use of probiotics in amphibian
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
Chapter 4: Community structure and function of amphibian skin microbes: an
experimental test with bullfrogs exposed to chytrid fungus
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
Chapter 2: Amphibian skin may select for rare environmental microbes
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
Chapter 3: Linking culture-dependent and -independent characterizations of amphibian
skin microbial communities: Important insights into the use of probiotics in amphibian
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
Chapter 4: Community structure and function of amphibian skin microbes: an
experimental test with bullfrogs exposed to chytrid fungus
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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Chapter 2: Amphibian skin may select for rare environmental microbes
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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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
Chapter 3: Linking culture-dependent and -independent characterizations of amphibian
skin microbial communities: Important insights into the use of probiotics in amphibian
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
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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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)
Cellulomonadaceae1 Act culture4350881 7.9 (100)
Pseudomonas5 Pro culture564678 5.7 (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)
Comamonadaceae Pro culture4456068 1.9 (100)
Stenotrophomonas Pro denovo39301 1.7 (94)
Enterobacteriaceae Pro culture806686 1.7 (100)
Achromobacter Pro culturedenovo12 11.8 (100)
Cellulomonadaceae1 Act culture4350881 5.2 (100)
Sphingobacteriales Bac denovo1331 5.0 (92)
Comamonadaceae Pro culture823187 4.7 (100)
Pseudoalteromonas8 Pro denovo34355 3.6 (100)
Flavobacterium Bac culture737951 3.1 (100)
Pseudomonas5 Pro culture564678 2.8 (100)
Flavobacterium Bac culture960076 2.6 (92)
Pseudomonas Pro culturedenovo3 2.2 (100)
Oxalobacteraceae Pro culture582997 2.2 (100)
Neisseriaceae Pro culture560243 1.9 (100)
Comamonadaceae Pro culture110220 1.7 (100)
Comamonadaceae Pro culture834138 1.5 (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)
Pseudomonas5 Pro culture564678 6.4 (93)
Flectobacillus Bac denovo58139 5.4 (80)
70
Cellulomonadaceae1 Act culture4350881 3.3 (93)
Pseudomonas6 Pro culture926370 2.2 (80)
Oxalobacteraceae Pro culture620677 2.1 (100)
Pseudomonas Pro culture280459 2.0 (100)
Sphingomonas Pro culture4450360 2.0 (100)
Rhodococcus7 Act culture66626 1.8 (100)
Oxalobacteraceae Pro culture1008747 1.7 (93)
Oxalobacteraceae Pro culture539915 1.6 (100)
Pseudomonas Pro culture4353093 1.5 (93)
Xanthomonadaceae Pro culture111289 1.3 (93)
Enterobacteriaceae Pro culture194508 1.1 (40)
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
Resemblance: S8 Sorensen
SpeciesBullfrog
Newt
Peeper
Toad
2D Stress: 0.12
Resemblance: S8 Sorensen
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
Transform: Square root
Resemblance: S8 Sorensen
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
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Chapter 4: Community structure and function of amphibian skin microbes: an
experimental test with bullfrogs exposed to chytrid fungus
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.
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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
81
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
82
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
85
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
86
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
89
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.
90
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).
93
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
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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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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
Normal Antibiotics J. lividum
Bd
0
0.1
0.2
0.3
Pro
port
ion
al G
row
th a
t
Da
y 4
2
Normal Antibiotics J. lividum
No Bd
Normal Antibiotics J. lividum
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
Transform: Square root
Resemblance: S17 Bray Curtis similarity
BacteriaTrtNormal
Jlividum
Antibiotics
2D Stress: 0.09
Bd exposurea
No Bd exposure
b
Resemblance: S8 Sorensen
BacteriaTrtJlividum
Antibiotics
Normal
2D Stress: 0.13
Resemblance: S8 Sorensen
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
*
Normal Antibiotics J. lividum
Bd treatment
0
100
200
300
400
500
600
700O
TU
Ric
hn
ess
Normal Antibiotics J. lividum
*
0
10
20
30
40
50
60
Ph
ylo
gen
eti
c D
iversi
ty
Normal Antibiotics J. lividum
*
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
Normal Antibiotics J. lividum
-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
Normal Antibiotics J. lividum
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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