ArticleJournal of mathematical biology2015
Macroscopic equations for bacterial chemotaxis: integration of detailed biochemistry of cell signaling.
Article in Journal of mathematical biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Identification of the governing equation of stimulus-response data for run-and-tumble dynamics.PLoS computational biology · 2025Article
- Mechanisms Underlying the Virulence Regulation ofMicroorganisms · 2022Article
- Individual based models exhibiting Lévy-flight type movement induced by intracellular noise.Journal of mathematical biology · 2021Article
- Migration and accumulation of bacteria with chemotaxis and chemokinesis.The European physical journal. E, Soft matter · 2021Article
- Spatial pattern formation in reaction-diffusion models: a computational approach.Journal of mathematical biology · 2020Article
- Article
- The role of intracellular signaling in the stripe formation in engineered Escherichia coli populations.PLoS computational biology · 2018Article
- Structured models of cell migration incorporating molecular binding processes.Journal of mathematical biology · 2017Article
- Derivation of the bacterial run-and-tumble kinetic equation from a model with biochemical pathway.Journal of mathematical biology · 2016Article
- Moment-flux models for bacterial chemotaxis in large signal gradients.Journal of mathematical biology · 2016Article
- A model for collective dynamics in ant raids.Journal of mathematical biology · 2016Article
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Abstract
Chemotaxis of single cells has been extensively studied and a great deal on intracellular signaling and cell movement is known. However, systematic methods to embed such information into continuum PDE models for cell population dynamics are still in their infancy. In this paper, we consider chemotaxis of run-and-tumble bacteria and derive continuum models that take into account of the detailed biochemistry of intracellular signaling. We analytically show that the macroscopic bacterial density can be approximated by the Patlak-Keller-Segel equation in response to signals that change slowly in space and time. We derive, for the first time, general formulas that represent the chemotactic sensitivity in terms of detailed descriptions of single-cell signaling dynamics in arbitrary space dimensions. These general formulas are useful in explaining relations of single cell behavior and population dynamics. As an example, we apply the theory to chemotaxis of bacterium Escherichia coli and show how the structure and kinetics of the intracellular signaling network determine the sensing properties of E. coli populations. Numerical comparison of the derived PDEs and the underlying cell-based models show quantitative agreements for signals that change slowly, and qualitative agreements for signals that change extremely fast. The general theory we develop here is readily applicable to chemotaxis of other run-and-tumble bacteria, or collective behavior of other individuals that move using a similar strategy.
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