Mathematical modeling and experimental validation of chemotaxis under controlled gradients of methyl-aspartate in Escherichia coli
- PMID: 20485750
- DOI: 10.1039/b924368b
Mathematical modeling and experimental validation of chemotaxis under controlled gradients of methyl-aspartate in Escherichia coli
Abstract
Escherichia coli has evolved an intracellular pathway to regulate its motion termed as chemotaxis so as to move towards a favorable environment such as regions with higher concentration of nutrients. Chemotaxis is a response to temporal and spatial variation of extracellular ligand concentration and randomness in motion induced by collisions with solvent molecules. Previous studies have reported average drift velocities for a given gradient and do not measure drift velocities as a function of time and space. To address this issue, a novel experimental technique was developed to quantify the motion of E. coli cells to varying concentrations and gradients of methyl-aspartate so as to capture the spatial and temporal variation of the drift velocity. A two-state receptor model accounting for the intracellular signaling pathway predicted the experimentally observed increase in drift velocity with gradient and the subsequent adaptation. Our study revealed that the rotational diffusivity induced by the extracellular environment is crucial in determining the drift velocity of E. coli. The model predictions matched with experimental observations only when the response of the intracellular pathway was highly ultra-sensitive to overcome the extracellular randomness. The parametric sensitivity of the pathway indicated that the dissociation constant for the binding of the ligand and the rate constants of the methylation/demethylation of the receptor are key to predict the performance of the chemotactic behavior. The study also indicates a possible role of oxygen in the chemotaxis response and that the response to a ligand may have to account for effects of oxygen.
Similar articles
-
Chemotaxis of Escherichia coli to L-serine.Phys Biol. 2010 May 26;7(2):026007. doi: 10.1088/1478-3975/7/2/026007. Phys Biol. 2010. PMID: 20505226
-
Theoretical results for chemotactic response and drift of E. coli in a weak attractant gradient.J Theor Biol. 2010 Sep 7;266(1):99-106. doi: 10.1016/j.jtbi.2010.06.012. Epub 2010 Jun 15. J Theor Biol. 2010. PMID: 20558183
-
Overview of mathematical approaches used to model bacterial chemotaxis I: the single cell.Bull Math Biol. 2008 Aug;70(6):1525-69. doi: 10.1007/s11538-008-9321-6. Epub 2008 Jul 19. Bull Math Biol. 2008. PMID: 18642048 Review.
-
Chemotaxis in Escherichia coli: a molecular model for robust precise adaptation.PLoS Comput Biol. 2008 Jan;4(1):e1. doi: 10.1371/journal.pcbi.0040001. Epub 2007 Nov 20. PLoS Comput Biol. 2008. PMID: 18179279 Free PMC article.
-
Chemotaxis: how bacteria use memory.Biol Chem. 2009 Nov;390(11):1097-104. doi: 10.1515/BC.2009.130. Biol Chem. 2009. PMID: 19747082 Review.
Cited by
-
How the motility pattern of bacteria affects their dispersal and chemotaxis.PLoS One. 2013 Dec 31;8(12):e81936. doi: 10.1371/journal.pone.0081936. eCollection 2013. PLoS One. 2013. PMID: 24391710 Free PMC article.
-
Enhancement of Swimming Speed Leads to a More-Efficient Chemotactic Response to Repellent.Appl Environ Microbiol. 2015 Dec 11;82(4):1205-1214. doi: 10.1128/AEM.03397-15. Print 2016 Feb 15. Appl Environ Microbiol. 2015. PMID: 26655753 Free PMC article.
-
Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.BMC Syst Biol. 2014 Jan 15;8:4. doi: 10.1186/1752-0509-8-4. BMC Syst Biol. 2014. PMID: 24428922 Free PMC article.
-
Variation of swimming speed enhances the chemotactic migration of Escherichia coli.Syst Synth Biol. 2015 Sep;9(3):85-95. doi: 10.1007/s11693-015-9174-x. Epub 2015 Jul 9. Syst Synth Biol. 2015. PMID: 26279703 Free PMC article.
MeSH terms
Substances
LinkOut - more resources
Full Text Sources