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Related Experiment Videos

Noise-induced Min phenotypes in E. coli.

David Fange1, Johan Elf

  • 1Department of Cell and Molecular Biology, Biomedical Centre, Uppsala University, Uppsala, Sweden.

Plos Computational Biology
|July 19, 2006
PubMed
Summary
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Stochastic modeling reveals how random fluctuations in Escherichia coli Min proteins (MinD and MinE) explain cell division patterns in mutants, overcoming limitations of deterministic models for diverse phenotypes.

Area of Science:

  • Cell Biology
  • Biophysics
  • Systems Biology

Background:

  • The Min system (MinD and MinE proteins) in Escherichia coli regulates cell division placement through spatiotemporal oscillations.
  • Existing quantitative models fail to fully explain all observed mutant phenotypes of the Min system.
  • Understanding Min system dynamics is crucial for comprehending bacterial cell division mechanisms.

Purpose of the Study:

  • To analyze the stochastic reaction-diffusion kinetics of Min proteins in various Escherichia coli mutants.
  • To compare stochastic and deterministic (mean-field) models in explaining Min system behavior.
  • To develop a comprehensive model that accounts for all documented Min phenotypes.

Main Methods:

  • Analysis of stochastic reaction-diffusion kinetics for Min proteins in wild-type and mutant Escherichia coli.

Related Experiment Videos

  • Comparison of stochastic model results with deterministic mean-field descriptions.
  • Investigated phenotypes included wild-type, filamentous (ftsZ-), spherical (rodA-), and phosphatidylethanolamine-deficient (PE-) mutants.

    • Main Results:

    • Deterministic models adequately describe wild-type and filamentous cells, but stochastic models are essential for spherical and PE- mutants.
    • Stochastic modeling explains the oscillatory behavior in spherical mutants, preventing trapping in non-oscillatory states predicted by mean-field models.
    • The stochastic model accurately reproduces MinD cluster formation in PE- mutants as a nucleation phenomenon driven by low copy number fluctuations.

    Conclusions:

    • A simple five-reaction model incorporating stochastic kinetics and 3D diffusion can explain all documented Min system phenotypes.
    • Local copy number fluctuations, or intrinsic noise, are critical for generating phenotypic diversity, even with high total molecule counts.
    • Stochastic effects are fundamental to understanding the complex behaviors observed in the Min system and bacterial cell division.