Evidence map›Paper›PMID 35272699›Full record

ArticleMicrobiome2022

Microbiome function predicts amphibian chytridiomycosis disease dynamics.

Kieran A Bates, Ulf Sommer, Kevin P Hopkins, Jennifer M G Shelton, Claudia Wierzbicki, Christopher Sergeant, Benjamin Tapley, Christopher J Michaels, Dirk S Schmeller, Adeline Loyau and 5 more

Abstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

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  9. Advancing the study of microbial symbionts of amphibians and reptiles.Frontiers in amphibian and reptile science · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Kieran A BatesDepartment of Zoology, University of Oxford, 11a Mansfield Road, Oxford, OX1 3SZ, UK. kieran.bates@zoo.ox.ac.uk.ORCID 0000-0003-1559-6014
Ulf SommerNERC Biomolecular Analysis Facility - Metabolomics Node (NBAF-B), School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK.
Kevin P HopkinsInstitute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
Jennifer M G SheltonMRC Centre for GlobaI Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, W2 1PG, UK.
Claudia WierzbickiMRC Centre for GlobaI Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, W2 1PG, UK.
Christopher SergeantInstitute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
Benjamin TapleyZSL London Zoo, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
Christopher J MichaelsZSL London Zoo, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
Dirk S SchmellerLaboratoire Écologie Fonctionnelle et Environnement, Université de Toulouse, CNRS, Toulouse INP, Université Toulouse 3 - Paul Sabatier (UPS), Toulouse, France.
Adeline LoyauDepartment of Experimental Limnology, Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Alte Fischerhütte 2, 16775, Stechlin, Germany.
Jaime BoschIMIB Biodiversity Research Institute (CSIC-University of Oviedo), 33600, Mieres, Spain.
Mark R ViantNERC Biomolecular Analysis Facility - Metabolomics Node (NBAF-B), School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK.
Xavier A HarrisonInstitute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
Trenton W J GarnerInstitute of Zoology, Zoological Society of London, Regent's Park, London, NW1 4RY, UK.
Matthew C FisherMRC Centre for GlobaI Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, W2 1PG, UK.

Funding

Medical Research Council MR/R015600/1
6 · The paper itself

Abstract

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.

Indexed as

ChytridiomycotaMicrobiotaMycosesAnimalsAnuraRNA, Ribosomal, 16SRNA, Ribosomal, 16SAmphibianBatrachochytrium dendrobatidisChytridiomycosisMetabolomeMicrobiomeMulti-omics

Identifiers

PMID35272699
PMCPMC8908643

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.