| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Biophysical Journal 68: 708-722 (1995)
© 1995 the Biophysical Society
Department of Chemistry, Stanford University, California 94305.
ABSTRACT
We present a model of the chemotactic mechanism of Escherichia coli that exhibits both initial excitation and eventual complete adaptation to any and all levels of stimulus ("exact" adaptation). In setting up the reaction network, we use only known interactions and experimentally determined cytosolic concentrations. Whenever possible, rate coefficients are first assigned experimentally measured values; second, we permit some variation in these rate coefficients by using a multiple-well optimization technique and incremental adjustment to obtain values that are sufficient to engender initial response to stimuli (excitation) and an eventual return of behavior to baseline (adaptation). The predictions of the model are similar to the observed behavior of wild-type bacteria in regard to the time scale of excitation in the presence of both attractant and repellent. The model predicts a weaker response to attractant than that observed experimentally, and the time scale of adaptation does not depend as strongly upon stimulant concentration as does that for wild-type bacteria. The mechanism responsible for long-term adaptation is local rather than global: on addition of a repellent or attractant, the receptor types not sensitive to that attractant or repellent do not change their average methylation level in the long term, although transient changes do occur. By carrying out a phenomenological simulation of bacterial chemotaxis, we find that the model is insufficiently sensitive to effect taxis in a gradient of attractant. However, by arbitrarily increasing the sensitivity of the motor to the tumble effector (phosphorylated CheY), we can obtain chemotactic behavior.
This article has been cited by other articles:
![]() |
B. A. Mello and Y. Tu Perfect and Near-Perfect Adaptation in a Model of Bacterial Chemotaxis Biophys. J., May 1, 2003; 84(5): 2943 - 2956. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. B. Bourret, N. W. Charon, A. M. Stock, and A. H. West Bright Lights, Abundant Operons--Fluorescence and Genomic Technologies Advance Studies of Bacterial Locomotion and Signal Transduction: Review of the BLAST Meeting, Cuernavaca, Mexico, 14 to 19 January 2001 J. Bacteriol., January 1, 2002; 184(1): 1 - 17. [Full Text] [PDF] |
||||
![]() |
J. VOHRADSKY Neural network model of gene expression FASEB J, March 1, 2001; 15(3): 846 - 854. [Abstract] [Full Text] [PDF] |
||||
![]() |
T.-M. Yi, Y. Huang, M. I. Simon, and J. Doyle Robust perfect adaptation in bacterial chemotaxis through integral feedback control PNAS, April 25, 2000; 97(9): 4649 - 4653. [Abstract] [Full Text] [PDF] |
||||
![]() |
B. E. Scharf, K. A. Fahrner, and H. C. Berg CheZ Has No Effect on Flagellar Motors Activated by CheY13DK106YW J. Bacteriol., October 1, 1998; 180(19): 5123 - 5128. [Abstract] [Full Text] |
||||
![]() |
P. J. E. Goss and J. Peccoud Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets PNAS, June 9, 1998; 95(12): 6750 - 6755. [Abstract] [Full Text] [PDF] |
||||
![]() |
H. McAdams and L Shapiro Circuit simulation of genetic networks Science, August 4, 1995; 269(5224): 650 - 656. [Abstract] [PDF] |
||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |