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Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking

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  • Daniel P. G. H. Wong

    (Stanford University)

  • Benjamin H. Good

    (Stanford University
    Stanford University
    Chan Zuckerberg Biohub–San Francisco)

Abstract

Gut microbiota can adapt to their host environment by rapidly acquiring new mutations. However, the dynamics of this process are difficult to characterize in dominant gut species in their complex in vivo environment. Here we show that the fine-scale dynamics of genome-wide transposon libraries can enable quantitative inferences of these in vivo evolutionary forces. By analyzing >400,000 lineages across four human Bacteroides strains in gnotobiotic mice, we observed positive selection on thousands of cryptic variants — most of which were unrelated to their original gene knockouts. The spectrum of fitness benefits varied between species, and displayed diverse tradeoffs over time and in different dietary conditions, enabling inferences of their underlying function. These results suggest that within-host adaptations arise from an intense competition between numerous contending variants, which can strongly influence their emergent evolutionary tradeoffs.

Suggested Citation

  • Daniel P. G. H. Wong & Benjamin H. Good, 2024. "Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45792-0
    DOI: 10.1038/s41467-024-45792-0
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    Cited by:

    1. John McEnany & Benjamin H. Good, 2024. "Predicting the first steps of evolution in randomly assembled communities," Nature Communications, Nature, vol. 15(1), pages 1-10, December.

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