ArticleACS synthetic biology2022
Individual-Based Modeling of Spatial Dynamics of Chemotactic Microbial Populations.
Article in ACS synthetic biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Study of wrap mode impact on Pseudomonas aeruginosa motion in the chemotactic field of fungi.NPJ systems biology and applications · 2026Article
- Agent-based model for simulating microbial movement with a preferred target for agricultural biologicals.PeerJ · 2026Article
- Article
- Digitize your Biology! Modeling multicellular systems through interpretable cell behavior.bioRxiv : the preprint server for biology · 2023Article
- Agent-Based Modeling of Microbial Communities.ACS synthetic biology · 2022Review
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Authors and funding
2 authors.
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Abstract
One important direction of synthetic biology is to establish desired spatial structures from microbial populations. Underlying this structural development process are different driving factors, among which bacterial motility and chemotaxis serve as a major force. Here, we present an individual-based, biophysical computational framework for mechanistic and multiscale simulation of the spatiotemporal dynamics of motile and chemotactic microbial populations. The framework integrates cellular movement with spatial population growth, mechanical and chemical cellular interactions, and intracellular molecular kinetics. It is validated by a statistical comparison of single-cell chemotaxis simulations with reported experiments. The framework successfully captures colony range expansion of growing isogenic populations and also reveals chemotaxis-modulated, spatial patterns of a two-species amensal community. Partial differential equation-based models subsequently validate these simulation findings. This study provides a versatile computational tool to uncover the fundamentals of microbial spatial ecology as well as to facilitate the design of synthetic consortia for desired spatial patterns.
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Registered trials
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