ArticleCell systems2025
Biophysical metabolic modeling of complex bacterial colony morphology.
Article in Cell systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Comparative evaluation of deep learning architectures for microbial colony classification in microbiological imaging.BMC microbiology · 2026Article
- Genomic diversification, adaptive convergence, and regulatory rewiring in aging Escherichia coli colonies.BMC microbiology · 2026Article
- Transition from traveling fronts to diffusion-limited growth in expanding populations.Physical review. E · 2026Article
- Article
- Dynamic metabolic modelling of ATP allocation during viral infection.Journal of the Royal Society, Interface · 2026Article
- Spatial structure: shaping the ecology and evolution of microbial communities.FEMS microbiology reviews · 2026Review
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6 authors.
Funding
Abstract
Microbial colony growth is shaped by the physics of biomass propagation and nutrient diffusion and by the metabolic reactions that organisms activate as a function of the surrounding environment. While microbial colonies have been explored using minimal models of growth and motility, full integration of biomass propagation and metabolism is still lacking. Here, building upon our framework for computation of microbial ecosystems in time and space (COMETS), we combine dynamic flux balance modeling of metabolism with collective biomass propagation and demographic fluctuations to provide nuanced simulations of E. coli colonies. Simulations produced realistic colony morphology, consistent with our experiments. They characterize the transition between smooth and furcated colonies and the decay of genetic diversity. Furthermore, we demonstrate that under certain conditions, biomass can accumulate along "metabolic rings" that are reminiscent of coffee-stain rings but have a completely different origin. Our approach is a key step toward predictive microbial ecosystems modeling. A record of this paper's transparent peer review process is included in the supplemental information.
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Registered trials
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