• Medientyp: E-Artikel
  • Titel: Predicting fungal infection rate and severity with skin‐associated microbial communities on amphibians
  • Beteiligte: Chen, Melissa Y.; Kueneman, Jordan G.; González, Antonio; Humphrey, Greg; Knight, Rob; McKenzie, Valerie J.
  • Erschienen: Wiley, 2022
  • Erschienen in: Molecular Ecology
  • Sprache: Englisch
  • DOI: 10.1111/mec.16372
  • ISSN: 0962-1083; 1365-294X
  • Schlagwörter: Genetics ; Ecology, Evolution, Behavior and Systematics
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  • Beschreibung: <jats:title>Abstract</jats:title><jats:p>Pathogen success (risk and severity) is influenced by host‐associated microbiota, but the degree to which variation in microbial community traits predict future infection presence/absence (risk) and load (severity) for the host is unknown. We conducted a time‐series experiment by sampling the skin‐associated bacterial communities of five amphibian species before and after exposure to the fungal pathogen, <jats:italic>Batrachochytrium dendrobaditis</jats:italic> (<jats:italic>Bd</jats:italic>). We sought to determine whether microbial community traits are predictors of, or are affected by, <jats:italic>Bd</jats:italic> infection risk and intensity. Our results show that richness of putative <jats:italic>Bd</jats:italic>‐inhibitory bacteria strongly predicts infection risk, while the proportion of putative <jats:italic>Bd</jats:italic>‐inhibitory bacteria predicts future infection intensity. Variation in microbial community composition is high across time and individual, and bacterial prevalence is low. Our findings demonstrate how ecological community traits of host‐associated microbiota may be used to predict infection risk by pathogenic microbes.</jats:p>