Search from over 60,000 research works

Advanced Search

Understanding the link between single cell and population scale responses of Escherichia coli in differing ligand gradients

[thumbnail of Open Access]
Preview
1-s2.0-S2001037015000446-main.pdf - Published Version (1MB) | Preview
Available under license: Creative Commons Attribution
[thumbnail of Open Access]
Preview
ABM Paper Unmarked.pdf - Accepted Version (2MB) | Preview
Available under license: Creative Commons Attribution
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Edgington, M. P. and Tindall, M. J. (2015) Understanding the link between single cell and population scale responses of Escherichia coli in differing ligand gradients. Computational and Structural Biotechnology Journal, 13. pp. 528-538. ISSN 2001-0370 doi: 10.1016/j.csbj.2015.09.003

Abstract/Summary

We formulate an agent-based population model of Escherichia coli cells which incorporates a description of the chemotaxis signalling cascade at the single cell scale. The model is used to gain insight into the link between the signalling cascade dynamics and the overall population response to differing chemoattractant gradients. Firstly, we consider how the observed variation in total (phosphorylated and unphosphorylated) signalling protein concentration affects the ability of cells to accumulate in differing chemoattractant gradients. Results reveal that a variation in total cell protein concentration between cells may be a mechanism for the survival of cell colonies across a wide range of differing environments. We then study the response of cells in the presence of two different chemoattractants.In doing so we demonstrate that the population scale response depends not on the absolute concentration of each chemoattractant but on the sensitivity of the chemoreceptors to their respective concentrations. Our results show the clear link between single cell features and the overall environment in which cells reside.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/44878
Item Type Article
Refereed Yes
Divisions Interdisciplinary centres and themes > Institute for Cardiovascular and Metabolic Research (ICMR)
Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Publisher Elsevier
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar