Evidence map›Paper›PMID 22125482›Full record

ArticlePLoS computational biology2011

Speed, sensitivity, and bistability in auto-activating signaling circuits.

Rutger Hermsen, David W Erickson, Terence Hwa

Abstract read
In one paragraph

Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed.

  1. Article
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  7. Theoretical and computational tools to model multistable gene regulatory networks.Reports on progress in physics. Physical Society (Great Britain) · 2023
    Review
  8. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Rutger HermsenCenter for Theoretical Biological Physics and Department of Physics, University of California at San Diego, La Jolla, California, USA. hermsen@ctbp.ucsd.edu
David W Erickson
Terence Hwa

Funding

MOLECULAR BIOPHYSICS TRAINING PROGRAMT32GM008326 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIVES, ELIZABETH A. · 1989 to 2020
$7.5M
Quantitative Studies of Bacterial Growth PhysiologyR01GM095903 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HWA, TERENCE · 2011 to 2023
$3.8M
Quantitative Characterization & Modeling of sRNA-Mediated Gene RegulationR01GM077298 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HWA, TERENCE · 2007 to 2010
$1.3M
CGH CDC HHS T32GH08326NIGMS NIH HHS R01 GM077298NIGMS NIH HHS R01GM-077298NIGMS NIH HHS R01 GM095903NIGMS NIH HHS T32 GM008326
6 · The paper itself

Abstract

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.

Indexed as

Models, BiologicalComputational BiologyEscherichia coliEscherichia coli ProteinsGene Expression RegulationHomeostasisSignal TransductionTranscription FactorsEscherichia coli ProteinsTranscription Factors

Identifiers

PMID22125482
PMCPMC3219618

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.