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Article overview
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Noise Filtering Strategies of Adaptive Signaling Networks: The Case of E. Coli Chemotaxis | | Pablo Sartori
; Yuhai Tu
; | | Date: |
20 Apr 2011 | | Abstract: | Two distinct mechanisms for filtering noise in an input signal are identi?ed
in a class of adaptive sensory networks. We find that the high frequency noise
is filtered by the output degradation process through time-averaging; while the
low frequency noise is damped by adaptation through negative feedback. Both
filtering processes themselves introduce intrinsic noises, which are found to
be un?ltered and can thus amount to a significant internal noise floor even
without signaling. These results are applied to E. coli chemotaxis. We show
unambiguously that the molecular mechanism for the Berg-Purcell time-averaging
scheme is the dephosphorylation of the response regulator CheY-P, not the
receptor adaptation process as previously suggested. The high frequency noise
due to the stochastic ligand binding-unbinding events and the random ligand
molecule diffusion is averaged by the CheY-P dephosphorylation process to a
negligible level in E.coli. We identify a previously unstudied noise source
caused by the random motion of the cell in a ligand gradient. We show that this
random walk induced signal noise has a divergent low frequency component, which
is only rendered finite by the receptor adaptation process. For gradients
within the E. coli sensing range, this dominant external noise can be
comparable to the significant intrinsic noise in the system. The dependence of
the response and its fluctuations on the key time scales of the system are
studied systematically. We show that the chemotaxis pathway may have evolved to
optimize gradient sensing, strong response, and noise control in di?erent time
scales | | Source: | arXiv, 1104.4092 | | Services: | Forum | Review | PDF | Favorites | |
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