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Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
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Moran Model of Spatial Alignment in Microbial Colonies.

B R Karamched1, W Ott1, I Timofeyev1

  • 1Department of Mathematics, University of Houston, Houston, Texas 77004, USA.

Physica D. Nonlinear Phenomena
|January 1, 2020
PubMed
Summary
This summary is machine-generated.

We developed a spatial model to study how mechanical interactions and growth influence population patterns. This model shows how E. coli cells can align parallel or orthogonally to boundaries based on interaction strength.

Keywords:
Moran modelcell alignmentmean fieldphase transition

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Area of Science:

  • Mathematical Biology
  • Population Dynamics
  • Biophysics

Background:

  • Understanding collective behavior in populations requires models that account for spatial interactions and growth dynamics.
  • Cellular alignment and pattern formation are crucial phenomena in microbiology and developmental biology.

Purpose of the Study:

  • To introduce a solvable spatial Moran model incorporating mechanical interactions and directional growth.
  • To investigate the mechanisms driving population-level pattern formation, using E. coli as an example.

Main Methods:

  • Developed an analytically tractable spatial Moran model.
  • Applied a mean-field approximation for complete solvability.
  • Simulated E. coli growth in a microfluidic trap to observe pattern emergence.

Main Results:

  • The model elucidates pattern formation driven by a balance between boundary effects and cell-cell interactions.
  • E. coli cells exhibit parallel alignment to trap boundaries when boundary effects dominate.
  • Orthogonal alignment occurs when cell-cell interactions surpass a critical threshold.

Conclusions:

  • The spatial Moran model provides insights into collective behavior driven by local and global interactions.
  • This approach can be extended to various directionally growing cells and systems.
  • The study highlights how mechanical forces and growth dynamics shape population-level spatial organization.