Speed, Sensitivity, and Bistability in Auto-activating Signaling Circuits

Hermsen, Rutger; Erickson, David W.; Hwa, Terence

doi:10.1371/journal.pcbi.1002265

i

Speed, Sensitivity, and Bistability in Auto-activating Signaling Circuits

Supporting Files

Nov 17 2011
By Hermsen, Rutger ; Erickson, David W. ; Hwa, Terence

File Language:

English

Details

Alternative Title:

PLoS Comput Biol
Personal Author:

Hermsen, Rutger ; Erickson, David W. ; Hwa, Terence
Description:

Cells employ a myriad of signaling circuits to detect environmental signals and drive specific gene expression responses. A common motif in these circuits is inducible auto-activation: a transcription factor that activates its own transcription upon activation by a ligand or by post-transcriptional modification. Examples range from the two-component signaling systems in bacteria and plants to the genetic circuits of animal viruses such as HIV. We here present a theoretical study of such circuits, based on analytical calculations, numerical computations, and simulation. Our results reveal several surprising characteristics. They show that auto-activation can drastically enhance the sensitivity of the circuit's response to input signals: even without molecular cooperativity, an ultra-sensitive threshold response can be obtained. However, the increased sensitivity comes at a cost: auto-activation tends to severely slow down the speed of induction, a stochastic effect that was strongly underestimated by earlier deterministic models. This slow-induction effect again requires no molecular cooperativity and is intimately related to the bimodality recently observed in non-cooperative auto-activation circuits. These phenomena pose strong constraints on the use of auto-activation in signaling networks. To achieve both a high sensitivity and a rapid induction, an inducible auto-activation circuit is predicted to acquire low cooperativity and low fold-induction. Examples from Escherichia coli's two-component signaling systems support these predictions.
Subjects:

Computational Biology Escherichia Coli Escherichia Coli Proteins Gene Expression Regulation Homeostasis Models, Biological Signal Transduction Transcription Factors
Source:

PLoS Comput Biol. 2011; 7(11).
Pubmed ID:

22125482
Pubmed Central ID:

PMC3219618
Document Type:

Journal Article
Funding:

R01 GM095903/GM/NIGMS NIH HHS/United States ; R01GM-077298/GM/NIGMS NIH HHS/United States ; T32 GM008326/GM/NIGMS NIH HHS/United States ; T32GH08326/GH/CGH CDC HHS/United States
Volume:

7
Issue:

11
Collection(s):

CDC Public Access
Main Document Checksum:

urn:sha256:17a579b3f4ccd28e2ebf02fcc73e9e3a70dcba5f6fb5cad8efa0bcb006ba23fb
Download URL:

https://stacks.cdc.gov/view/cdc/22791/cdc_22791_DS1.pdf
File Type:

[PDF - 572.06 KB ]

File Language:

English

ON THIS PAGE

Details Supporting Files

CDC STACKS serves as an archival repository of CDC-published products including scientific findings, journal articles, guidelines, recommendations, or other public health information authored or co-authored by CDC or funded partners.

As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.