ArticlePLoS computational biology2021
Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 27 citations in OpenAlex.
- Spatial structure: shaping the ecology and evolution of microbial communities.FEMS microbiology reviews · 2026Review
- Disentangling the feedback loops driving spatial patterning in microbial communities.NPJ biofilms and microbiomes · 2025Review
- In silico encounters: harnessing metabolic modelling to understand plant-microbe interactions.FEMS microbiology reviews · 2025Review
- Deciphering microbial spatial organization: insights from synthetic and engineered communities.ISME communications · 2025Review
- DyMMM-LEAPS: An ML-based framework for modulating evenness and stability in synthetic microbial communities.Biophysical journal · 2024Article
- Size Sensitivity of Metabolite Diffusion in Macromolecular Crowds.Nano letters · 2024Article
- MIGRENE: The Toolbox for Microbial and Individualized GEMs, Reactobiome and Community Network Modelling.Metabolites · 2024Article
- Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing.Microbial biotechnology · 2024Review
- Article
- From microbiome composition to functional engineering, one step at a time.Microbiology and molecular biology reviews : MMBR · 2023Review
- Pharmacodynamic Model of the Dynamic Response ofBiomedicines · 2023Article
- Regulated bacterial interaction networks: A mathematical framework to describe competitive growth under inclusion of metabolite cross-feeding.PLoS computational biology · 2023Article
- A structured evaluation of genome-scale constraint-based modeling tools for microbial consortia.PLoS computational biology · 2023Article
- Ecological modelling approaches for predicting emergent properties in microbial communities.Nature ecology & evolution · 2022Review
- The influence of the crowding assumptions in biofilm simulations.PLoS computational biology · 2021Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The metabolic capabilities of the species and the local environment shape the microbial interactions in a community either through the exchange of metabolic products or the competition for the resources. Cells are often arranged in close proximity to each other, creating a crowded environment that unevenly reduce the diffusion of nutrients. Herein, we investigated how the crowding conditions and metabolic variability among cells shape the dynamics of microbial communities. For this, we developed CROMICS, a spatio-temporal framework that combines techniques such as individual-based modeling, scaled particle theory, and thermodynamic flux analysis to explicitly incorporate the cell metabolism and the impact of the presence of macromolecular components on the nutrients diffusion. This framework was used to study two archetypical microbial communities (i) Escherichia coli and Salmonella enterica that cooperate with each other by exchanging metabolites, and (ii) two E. coli with different production level of extracellular polymeric substances (EPS) that compete for the same nutrients. In the mutualistic community, our results demonstrate that crowding enhanced the fitness of cooperative mutants by reducing the leakage of metabolites from the region where they are produced, avoiding the resource competition with non-cooperative cells. Moreover, we also show that E. coli EPS-secreting mutants won the competition against the non-secreting cells by creating less dense structures (i.e. increasing the spacing among the cells) that allow mutants to expand and reach regions closer to the nutrient supply point. A modest enhancement of the relative fitness of EPS-secreting cells over the non-secreting ones were found when the crowding effect was taken into account in the simulations. The emergence of cell-cell interactions and the intracellular conflicts arising from the trade-off between growth and the secretion of metabolites or EPS could provide a local competitive advantage to one species, either by supplying more cross-feeding metabolites or by creating a less dense neighborhood.
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