Growth phase estimation for abundant bacterial populations sampled longitudinally from human stool metagenomes

Lim, Joe J.; Diener, Christian; Wilson, James; Valenzuela, Jacob J.; Baliga, Nitin S.; Gibbons, Sean M.

doi:10.1038/s41467-023-41424-1

Title: Growth phase estimation for abundant bacterial populations sampled longitudinally from human stool metagenomes

Journal Article · 14 September 2023 · Nature Communications

DOI: https://doi.org/10.1038/s41467-023-41424-1 · OSTI ID:2281214

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^[2]; Valenzuela, Jacob J. ^[2]; Baliga, Nitin S. ^[3];

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Univ. of Washington, Seattle, WA (United States)
Institute for Systems Biology, Seattle, WA (United States)
Institute for Systems Biology, Seattle, WA (United States); Univ. of Washington, Seattle, WA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Institute for Systems Biology, Seattle, WA (United States); Univ. of Washington, Seattle, WA (United States)

Longitudinal sampling of the stool has yielded important insights into the ecological dynamics of the human gut microbiome. However, human stool samples are available approximately once per day, while commensal population doubling times are likely on the order of minutes-to-hours. Despite this mismatch in timescales, much of the prior work on human gut microbiome time series modeling has assumed that day-to-day fluctuations in taxon abundances are related to population growth or death rates, which is likely not the case. Here, we propose an alternative model of the human gut as a stationary system, where population dynamics occur internally and the bacterial population sizes measured in a bolus of stool represent a steady-state endpoint of these dynamics. We formalize this idea as stochastic logistic growth. We show how this model provides a path toward estimating the growth phases of gut bacterial populations in situ. We validate our model predictions using an in vitro Escherichia coli growth experiment. Finally, we show how this method can be applied to densely-sampled human stool metagenomic time series data. We discuss how these growth phase estimates may be used to better inform metabolic modeling in flow-through ecosystems, like animal guts or industrial bioreactors.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Institutes of Health (NIH)

Grant/Contract Number:: AC02-05CH11231; R01DK133468

OSTI ID:: 2281214

Journal Information:: Nature Communications, Vol. 14, Issue 1; ISSN 2041-1723

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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