Literature DB >> 18600657

Measurement of bacterial random motility and chemotaxis coefficients: II. Application of single-cell-based mathematical model.

R M Ford1, D A Lauffenburger.   

Abstract

A quantitative description of bacterial chemotaxis is necessary for making predictions about the migratory behavior of bacterial populations in applications such as biofilm development, release of genetically engineered bacteria into the environment, and in situ bioremediation technologies. The bacterial chemotactic response is characterized by a mathematical model which relates individual cell properties such as swimming speed and tumbling frequency to population parameters, specifically the random motility coefficient and the chemotactic sensitivity coefficient. Our model includes a nonlinear dependence of the chemotactic velocity on the attractant gradient as well as a dependence of the random motility coefficient on the temporal and spatial attractant gradients, both of which previous analyses have neglected. As we will show, these aspects are critical for interpreting the results from experiments like those performed in the stopped-flow diffusion chamber (SFDC) because the initial temporal and spatial gradients are very steep. Our analysis demonstrates that values for the random motility coefficient and chemotactic sensitivity coefficient can be obtained from experimental plots of net cell redistribution from initial conditions versus the square root of time. Values for these parameters are determined from experimental measurements of bacterial population distributions in the SFDC as described in the companion article. Using parameter values determined from independent experiments, mu = 1.1 +/- 0.4 +/- 10(-5) cm(2)/s and chi(0) = 8 +/- 3 +/- 10(-5) cm(2)/s, excellent agreement is found between theoretically predicted bacterial density profiles and actual experimental profiles for Escherichia coli K12 responding to fucose over two orders of magnitude in initial attractant concentration. Thus, our model captures the concentration dependence of this behavioral response satisfactorily in terms of cell population parameters which are derived from individual cell properties and will therefore be useful for making predictions about the migratory behavior of bacterial populations in the environment.

Entities:  

Year:  1991        PMID: 18600657     DOI: 10.1002/bit.260370708

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  19 in total

1.  Quantification of chemotaxis to naphthalene by Pseudomonas putida G7.

Authors:  R B Marx; M D Aitken
Journal:  Appl Environ Microbiol       Date:  1999-07       Impact factor: 4.792

2.  Stochastic models for cell motion and taxis.

Authors:  Edward L Ionides; Kathy S Fang; R Rivkah Isseroff; George F Oster
Journal:  J Math Biol       Date:  2003-08-06       Impact factor: 2.259

3.  Cell balance equation for chemotactic bacteria with a biphasic tumbling frequency.

Authors:  Kevin C Chen; Roseanne M Ford; Peter T Cummings
Journal:  J Math Biol       Date:  2003-06-12       Impact factor: 2.259

4.  Calculating spatial statistics for velocity jump processes with experimentally observed reorientation parameters.

Authors:  E A Codling; N A Hill
Journal:  J Math Biol       Date:  2005-05-02       Impact factor: 2.259

5.  Collective bacterial dynamics revealed using a three-dimensional population-scale defocused particle tracking technique.

Authors:  Mingming Wu; John W Roberts; Sue Kim; Donald L Koch; Matthew P DeLisa
Journal:  Appl Environ Microbiol       Date:  2006-07       Impact factor: 4.792

Review 6.  A user's guide to PDE models for chemotaxis.

Authors:  T Hillen; K J Painter
Journal:  J Math Biol       Date:  2008-07-15       Impact factor: 2.259

7.  Experimental verification of the behavioral foundation of bacterial transport parameters using microfluidics.

Authors:  Tanvir Ahmed; Roman Stocker
Journal:  Biophys J       Date:  2008-07-25       Impact factor: 4.033

8.  Analysis of chemotactic bacterial distributions in population migration assays using a mathematical model applicable to steep or shallow attractant gradients.

Authors:  R M Ford; D A Lauffenburger
Journal:  Bull Math Biol       Date:  1991       Impact factor: 1.758

9.  Stopped-flow chamber and image analysis system for quantitative characterization of bacterial population migration: Motility and chemotaxis ofEscherichia coli K12 to fucose.

Authors:  R M Ford; B R Phillips; J A Quinn; D A Lauffenburger
Journal:  Microb Ecol       Date:  1991-12       Impact factor: 4.552

10.  The Intersection of Theory and Application in Elucidating Pattern Formation in Developmental Biology.

Authors:  Hans G Othmer; Kevin Painter; David Umulis; Chuan Xue
Journal:  Math Model Nat Phenom       Date:  2009-01-01       Impact factor: 4.157

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.