ArticlePLoS computational biology2020
Modeling microbial cross-feeding at intermediate scale portrays community dynamics and species coexistence.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Challenges and Future Directives of Synthetic Biology in Engineering Plant-Microbe Partnerships for Sustainable Agriculture.Biotechnology and bioengineering · 2026Review
- Machine Learning-Guided Synthetic Microbial Communities Enable Functional and Sustainable Degradation of Persistent Environmental Pollutants.Environmental science & technology · 2026Article
- The network structure of cross-feeding impacts microbial community diversity under growth-inhibiting stresses.Nature communications · 2026Article
- Seed endophytic bacteria from invasive Lactuca serriola increase soil available phosphorus under phosphorus deficiency.Scientific reports · 2026Article
- When is microbial cross-feeding evolutionarily stable?bioRxiv : the preprint server for biology · 2025Article
- A data-driven modeling framework for mapping genotypes to synthetic microbial community functions.bioRxiv : the preprint server for biology · 2025Article
- Metabolic modeling of host-microbe interactions.Computational and structural biotechnology journal · 2025Review
- Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary dynamics.bioRxiv : the preprint server for biology · 2024Article
- Using metabolic networks to predict cross-feeding and competition interactions between microorganisms.Microbiology spectrum · 2024Article
- A molecular toolkit of cross-feeding strains for engineering synthetic yeast communities.Nature microbiology · 2024Article
- Oxidative stress changes interactions between 2 bacterial species from competitive to facilitative.PLoS biology · 2024Article
- Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary dynamics.Virus evolution · 2024Article
- Article
- A Roadmap for the Human Gut Cell Atlas.Nature reviews. Gastroenterology & hepatology · 2023Review
- Regulated bacterial interaction networks: A mathematical framework to describe competitive growth under inclusion of metabolite cross-feeding.PLoS computational biology · 2023Article
- Prolonging genetic circuit stability through adaptive evolution of overlapping genes.Nucleic acids research · 2023Article
- Spatial structure favors microbial coexistence except when slower mediator diffusion weakens interactions.eLife · 2023Article
- Classifying Interactions in a Synthetic Bacterial Community Is Hindered by Inhibitory Growth Medium.mSystems · 2022Article
- Article
- Ocular Microbiome in a Group of Clinically Healthy Horses.Animals : an open access journal from MDPI · 2022Article
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4 authors.
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Abstract
Social interaction between microbes can be described at many levels of details: from the biochemistry of cell-cell interactions to the ecological dynamics of populations. Choosing an appropriate level to model microbial communities without losing generality remains a challenge. Here we show that modeling cross-feeding interactions at an intermediate level between genome-scale metabolic models of individual species and consumer-resource models of ecosystems is suitable to experimental data. We applied our modeling framework to three published examples of multi-strain Escherichia coli communities with increasing complexity: uni-, bi-, and multi-directional cross-feeding of either substitutable metabolic byproducts or essential nutrients. The intermediate-scale model accurately fit empirical data and quantified metabolic exchange rates that are hard to measure experimentally, even for a complex community of 14 amino acid auxotrophies. By studying the conditions of species coexistence, the ecological outcomes of cross-feeding interactions, and each community's robustness to perturbations, we extracted new quantitative insights from these three published experimental datasets. Our analysis provides a foundation to quantify cross-feeding interactions from experimental data, and highlights the importance of metabolic exchanges in the dynamics and stability of microbial communities.
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