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A macroecological perspective on genetic diversity in the human gut microbiome

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  • William R Shoemaker

Abstract

While the human gut microbiome has been intensely studied, we have yet to obtain a sufficient understanding of the genetic diversity that it harbors. Research efforts have demonstrated that a considerable fraction of within-host genetic variation in the human gut is driven by the ecological dynamics of co-occurring strains belonging to the same species, suggesting that an ecological lens may provide insight into empirical patterns of genetic diversity. Indeed, an ecological model of self-limiting growth and environmental noise known as the Stochastic Logistic Model (SLM) was recently shown to successfully predict the temporal dynamics of strains within a single human host. However, its ability to predict patterns of genetic diversity across human hosts has yet to be tested. In this manuscript I determine whether the predictions of the SLM explain patterns of genetic diversity across unrelated human hosts for 22 common microbial species. Specifically, the stationary distribution of the SLM explains the distribution of allele frequencies across hosts and predicts the fraction of hosts harboring a given allele (i.e., prevalence) for a considerable fraction of sites. The accuracy of the SLM was correlated with independent estimates of strain structure, suggesting that patterns of genetic diversity in the gut microbiome follow statistically similar forms across human hosts due to the existence of strain-level ecology.

Suggested Citation

  • William R Shoemaker, 2023. "A macroecological perspective on genetic diversity in the human gut microbiome," PLOS ONE, Public Library of Science, vol. 18(7), pages 1-28, July.
  • Handle: RePEc:plo:pone00:0288926
    DOI: 10.1371/journal.pone.0288926
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    1. repec:plo:pgen00:1007855 is not listed on IDEAS
    2. Yulia Fridman & Zihan Wang & Sergei Maslov & Akshit Goyal, 2022. "Fine-scale diversity of microbial communities due to satellite niches in boom and bust environments," PLOS Computational Biology, Public Library of Science, vol. 18(12), pages 1-15, December.
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