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Low-load pathogen spillover predicts shifts in skin microbiome and survival of a terrestrial-breeding amphibian.

ABSTRACT: Wildlife disease dynamics are strongly influenced by the structure of host communities and their symbiotic microbiota. Conspicuous amphibian declines associated with the waterborne fungal pathogen Batrachochytrium dendrobatidis (Bd) have been observed in aquatic-breeding frogs globally. However, less attention has been given to cryptic terrestrial-breeding amphibians that have also been declining in tropical regions. By experimentally manipulating multiple tropical amphibian assemblages harbouring natural microbial communities, we tested whether Bd spillover from naturally infected aquatic-breeding frogs could lead to Bd amplification and mortality in our focal terrestrial-breeding host: the pumpkin toadlet Brachycephalus pitanga. We also tested whether the strength of spillover could vary depending on skin bacterial transmission within host assemblages. Terrestrial-breeding toadlets acquired lethal spillover infections from neighbouring aquatic hosts and experienced dramatic but generally non-protective shifts in skin bacterial composition primarily attributable to their Bd infections. By contrast, aquatic-breeding amphibians maintained mild Bd infections and higher survival, with shifts in bacterial microbiomes that were unrelated to Bd infections. Our results indicate that Bd spillover from even mildly infected aquatic-breeding hosts may lead to dysbiosis and mortality in terrestrial-breeding species, underscoring the need to further investigate recent population declines of terrestrial-breeding amphibians in the tropics.

SUBMITTER: Becker CG

PROVIDER: S-EPMC6710587 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Low-load pathogen spillover predicts shifts in skin microbiome and survival of a terrestrial-breeding amphibian.

Becker C Guilherme CG Bletz Molly C MC Greenspan Sasha E SE Rodriguez David D Lambertini Carolina C Jenkinson Thomas S TS Guimarães Paulo R PR Assis Ana Paula A APA Geffers Robert R Jarek Michael M Toledo Luís Felipe LF Vences Miguel M Haddad Célio F B CFB

Proceedings. Biological sciences 20190814 1908

Wildlife disease dynamics are strongly influenced by the structure of host communities and their symbiotic microbiota. Conspicuous amphibian declines associated with the waterborne fungal pathogen Batrachochytrium dendrobatidis (Bd) have been observed in aquatic-breeding frogs globally. However, less attention has been given to cryptic terrestrial-breeding amphibians that have also been declining in tropical regions. By experimentally manipulating multiple tropical amphibian assemblages harbouri ...[more]

PMID: 31409249

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Project description:BackgroundThe fungal pathogen Batrachochytrium dendrobatidis (Bd) threatens amphibian biodiversity and ecosystem stability worldwide. Amphibian skin microbial community structure has been linked to the clinical outcome of Bd infections, yet its overall functional importance is poorly understood.MethodsMicrobiome taxonomic and functional profiles were assessed using high-throughput bacterial 16S rRNA and fungal ITS2 gene sequencing, bacterial shotgun metagenomics and skin mucosal metabolomics. We sampled 56 wild midwife toads (Alytes obstetricans) from montane populations exhibiting Bd epizootic or enzootic disease dynamics. In addition, to assess whether disease-specific microbiome profiles were linked to microbe-mediated protection or Bd-induced perturbation, we performed a laboratory Bd challenge experiment whereby 40 young adult A. obstetricans were exposed to Bd or a control sham infection. We measured temporal changes in the microbiome as well as functional profiles of Bd-exposed and control animals at peak infection.ResultsMicrobiome community structure and function differed in wild populations based on infection history and in experimental control versus Bd-exposed animals. Bd exposure in the laboratory resulted in dynamic changes in microbiome community structure and functional differences, with infection clearance in all but one infected animal. Sphingobacterium, Stenotrophomonas and an unclassified Commamonadaceae were associated with wild epizootic dynamics and also had reduced abundance in laboratory Bd-exposed animals that cleared infection, indicating a negative association with Bd resistance. This was further supported by microbe-metabolite integration which identified functionally relevant taxa driving disease outcome, of which Sphingobacterium and Bd were most influential in wild epizootic dynamics. The strong correlation between microbial taxonomic community composition and skin metabolome in the laboratory and field is inconsistent with microbial functional redundancy, indicating that differences in microbial taxonomy drive functional variation. Shotgun metagenomic analyses support these findings, with similar disease-associated patterns in beta diversity. Analysis of differentially abundant bacterial genes and pathways indicated that bacterial environmental sensing and Bd resource competition are likely to be important in driving infection outcomes.ConclusionsBd infection drives altered microbiome taxonomic and functional profiles across laboratory and field environments. Our application of multi-omics analyses in experimental and field settings robustly predicts Bd disease dynamics and identifies novel candidate biomarkers of infection. Video Abstract.

Project description:BackgroundPlants can recruit beneficial microbes to enhance their ability to defend against pathogens. However, in contrast to the intensively studied roles of the rhizosphere microbiome in suppressing plant pathogens, the collective community-level change and effect of the phyllosphere microbiome in response to pathogen invasion remains largely elusive.ResultsHere, we integrated 16S metabarcoding, shotgun metagenomics and culture-dependent methods to systematically investigate the changes in phyllosphere microbiome between infected and uninfected citrus leaves by Diaporthe citri, a fungal pathogen causing melanose disease worldwide. Multiple microbiome features suggested a shift in phyllosphere microbiome upon D. citri infection, highlighted by the marked reduction of community evenness, the emergence of large numbers of new microbes, and the intense microbial network. We also identified the microbiome features from functional perspectives in infected leaves, such as enriched microbial functions for iron competition and potential antifungal traits, and enriched microbes with beneficial genomic characteristics. Glasshouse experiments demonstrated that several bacteria associated with the microbiome shift could positively affect plant performance under D. citri challenge, with reductions in disease index ranging from 65.7 to 88.4%. Among them, Pantoea asv90 and Methylobacterium asv41 identified as "recruited new microbes" in the infected leaves, exhibited antagonistic activities to D. citri both in vitro and in vivo, including inhibition of spore germination and/or mycelium growth. Sphingomonas spp. presented beneficial genomic characteristics and were found to be the main contributor for the functional enrichment of iron complex outer membrane receptor protein in the infected leaves. Moreover, Sphingomonas asv20 showed a stronger suppression ability against D. citri in iron-deficient conditions than iron-sufficient conditions, suggesting a role of iron competition during their antagonistic action.ConclusionsOverall, our study revealed how phyllosphere microbiomes differed between infected and uninfected citrus leaves by melanose pathogen, and identified potential mechanisms for how the observed microbiome shift might have helped plants cope with pathogen pressure. Our findings provide novel insights into understanding the roles of phyllosphere microbiome responses during pathogen challenge. Video abstract.

Project description:Symbiotic microbial communities play key roles in the health and development of their multicellular hosts. Understanding why microbial communities vary among different host species or individuals is an important step toward understanding the diversity and function of the microbiome. The amphibian skin microbiome may affect resistance to the fungal pathogen Batrachochytrium dendrobatidis (Bd). Still, the factors that determine the diversity and composition of the amphibian skin microbiome, and therefore may ultimately contribute to disease resistance, are not well understood. We conducted a two-phase experiment to first test how host and environment shape the amphibian skin microbiome, and then test if the microbiome affects or is affected by Bd infection. Most lab experiments testing assembly of the amphibian skin microbiome so far have compared sterile to non-sterile environments or heavily augmented to non-augmented frogs. A goal of this study was to evaluate, in an experimental setting, realistic potential drivers of microbiome assembly that would be relevant to patterns observed in nature. We tested effects of frog genetic background (2 source populations) and 6 natural lake water sources in shaping the microbiome of the frog Rana sierrae. Water in which frogs were housed affected the microbiome in a manner that partially mimicked patterns observed in natural populations. In particular, frogs housed in water from disease-resistant populations had greater bacterial richness than frogs housed in water from populations that died out due to Bd. However, in the experiment this difference in microbiomes did not lead to differences in host mortality or rates of pathogen load increase. Frog source population also affected the microbiome and, although none of the frogs in this study showed true resistance to infection, host source population had a small effect on the rate of pathogen load increase. This difference in infection trajectories could be due to the observed differences in the microbiome, but could also be due to other traits that differ between frogs from the two populations. In addition to examining effects of the microbiome on Bd, we tested the effect of Bd infection severity on the microbiome. Specifically, we studied a time series of the microbiome over the course of infection to test if the effects of Bd on the microbiome are dependent on Bd infection severity. Although limited to a small subset of frogs, time series analysis suggested that relative abundances of several bacterial phylotypes changed as Bd loads increased through time, indicating that Bd-induced disturbance of the R. sierrae microbiome is not a binary effect but instead is dependent on infection severity. We conclude that both host and aquatic environment help shape the R. sierrae skin microbiome, with links to small changes in disease resistance in some cases, but in this study the effect of Bd on the microbiome was greater than the effect of the microbiome on Bd. Assessment of the microbiome differences between more distantly related populations than those studied here is needed to fully understand the role of the microbiome in resistance to Bd.

Project description:Predicting pathogen spillover requires counting spillover events and aligning such counts with process-related covariates for each spillover event. How can we connect our analysis of spillover counts to simple, mechanistic models of pathogens jumping from reservoir hosts to recipient hosts? We illustrate how the pathways to pathogen spillover can be represented as a directed graph connecting reservoir hosts and recipient hosts and the number of spillover events modelled as a percolation of infectious units along that graph. Percolation models of pathogen spillover formalize popular intuition and management concepts for pathogen spillover, such as the inextricably multilevel nature of cross-species transmission, the impact of covariance between processes such as pathogen shedding and human susceptibility on spillover risk, and the assumptions under which the effect of a management intervention targeting one process, such as persistence of vectors, will translate to an equal effect on the overall spillover risk. Percolation models also link statistical analysis of spillover event datasets with a mechanistic model of spillover. Linear models, one might construct for process-specific parameters, such as the log-rate of shedding from one of several alternative reservoirs, yield a nonlinear model of the log-rate of spillover. The resulting nonlinearity is approximately piecewise linear with major impacts on statistical inferences of the importance of process-specific covariates such as vector density. We recommend that statistical analysis of spillover datasets use piecewise linear models, such as generalized additive models, regression clustering or ensembles of linear models, to capture the piecewise linearity expected from percolation models. We discuss the implications of our findings for predictions of spillover risk beyond the range of observed covariates, a major challenge of forecasting spillover risk in the Anthropocene. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.

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Low-load pathogen spillover predicts shifts in skin microbiome and survival of a terrestrial-breeding amphibian.

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Low-load pathogen spillover predicts shifts in skin microbiome and survival of a terrestrial-breeding amphibian.

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