ArticleNature communications2023
Growth phase estimation for abundant bacterial populations sampled longitudinally from human stool metagenomes.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Article
- Article
- Linear scaling reveals low-dimensional structure in observable microbial dynamics.bioRxiv : the preprint server for biology · 2025Article
- Moving from genome-scale to community-scale metabolic models for the human gut microbiome.Nature microbiology · 2025Review
- Consideration of a Liquid Mutation-Accumulation Experiment to Measure Mutation Rates by Successive Serial Dilution.Genome biology and evolution · 2025Article
- Phage-mediated intercellular CRISPRi for biocomputation in bacterial consortia.Nucleic acids research · 2025Article
- The Potential of Co-Evolution and Interactions of Gut Bacteria-Phages in Bamboo-Eating Pandas: Insights from Dietary Preference-Based Metagenomic Analysis.Microorganisms · 2024Article
- Sparse species interactions reproduce abundance correlation patterns in microbial communities.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Article
- Boosting Fitness Costs Associated with Antibiotic Resistance in the Gut: On the Way to Biorestoration of Susceptible Populations.Biomolecules · 2024Review
- Island biogeography theory provides a plausible explanation for why larger vertebrates and taller humans have more diverse gut microbiomes.The ISME journal · 2024Article
- Growth phase estimation for abundant bacterial populations sampled longitudinally from human stool metagenomes.Nature communications · 2023Article
- Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
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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Registered trials
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