Literature DB >> 19932119

Response acceleration in post-translationally regulated genetic circuits.

Alexander Y Mitrophanov1, Eduardo A Groisman.   

Abstract

Transcription factors must often be chemically modified to perform their functions. Yet, it is not known whether the mechanisms that bring about such modifications impact the quantitative or kinetic properties of gene expression. Phosphorylation controls the activity of regulatory proteins of the two-component system family, which constitutes a prevalent form of bacterial signal transduction. These proteins are phosphorylated/dephosphorylated by cognate sensor proteins in response to specific signals. The phosphorylation level of the regulatory proteins is also modulated by small proteins-termed connectors-that are produced when a cell experiences signals other than those detected directly by the sensors. Here, we explore how differences in the targets (i.e., sensor or regulator) and the mechanisms used by connectors to generate phosphorylated regulatory proteins affect the output of two-component systems. Our mathematical modeling demonstrates that sensor-targeting mechanisms exhibit stronger response acceleration than those where the connector targets the regulator. These differences are robust to perturbations in kinetic parameters but dependent upon the specific sensor-to-regulator ratio and how the ratio is controlled in living cells. In contrast, the steady-state output levels of the circuits are determined primarily by the circuit parameters, and can be adjusted without affecting response acceleration. Likewise, the analyzed connector-mediated circuits exhibit similar noise generation properties. Our results highlight the relationship between the architecture of genetic regulatory circuits and their dynamic properties. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

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Year:  2009        PMID: 19932119      PMCID: PMC2861412          DOI: 10.1016/j.jmb.2009.11.043

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  46 in total

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Authors:  Guri Tzivion; Joseph Avruch
Journal:  J Biol Chem       Date:  2001-11-14       Impact factor: 5.157

Review 2.  Stochasticity in gene expression: from theories to phenotypes.

Authors:  Mads Kaern; Timothy C Elston; William J Blake; James J Collins
Journal:  Nat Rev Genet       Date:  2005-06       Impact factor: 53.242

3.  A positive feedback loop promotes transcription surge that jump-starts Salmonella virulence circuit.

Authors:  Dongwoo Shin; Eun-Jin Lee; Henry Huang; Eduardo A Groisman
Journal:  Science       Date:  2006-12-08       Impact factor: 47.728

4.  Control of Streptococcus pyogenes virulence: modeling of the CovR/S signal transduction system.

Authors:  Alexander Y Mitrophanov; Gordon Churchward; Mark Borodovsky
Journal:  J Theor Biol       Date:  2006-11-21       Impact factor: 2.691

Review 5.  The biology and future prospects of antivirulence therapies.

Authors:  Lynette Cegelski; Garland R Marshall; Gary R Eldridge; Scott J Hultgren
Journal:  Nat Rev Microbiol       Date:  2008-01       Impact factor: 60.633

6.  Predictive behavior within microbial genetic networks.

Authors:  Ilias Tagkopoulos; Yir-Chung Liu; Saeed Tavazoie
Journal:  Science       Date:  2008-05-08       Impact factor: 47.728

Review 7.  A methodology for performing global uncertainty and sensitivity analysis in systems biology.

Authors:  Simeone Marino; Ian B Hogue; Christian J Ray; Denise E Kirschner
Journal:  J Theor Biol       Date:  2008-04-20       Impact factor: 2.691

8.  The IkappaB-NF-kappaB signaling module: temporal control and selective gene activation.

Authors:  Alexander Hoffmann; Andre Levchenko; Martin L Scott; David Baltimore
Journal:  Science       Date:  2002-11-08       Impact factor: 47.728

9.  B1500, a small membrane protein, connects the two-component systems EvgS/EvgA and PhoQ/PhoP in Escherichia coli.

Authors:  Yoko Eguchi; Junji Itou; Masatake Yamane; Ryo Demizu; Fumiyuki Yamato; Ario Okada; Hirotada Mori; Akinori Kato; Ryutaro Utsumi
Journal:  Proc Natl Acad Sci U S A       Date:  2007-11-12       Impact factor: 11.205

Review 10.  Positive feedback in cellular control systems.

Authors:  Alexander Y Mitrophanov; Eduardo A Groisman
Journal:  Bioessays       Date:  2008-06       Impact factor: 4.345

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  4 in total

1.  Kinetic model facilitates analysis of fibrin generation and its modulation by clotting factors: implications for hemostasis-enhancing therapies.

Authors:  Alexander Y Mitrophanov; Alisa S Wolberg; Jaques Reifman
Journal:  Mol Biosyst       Date:  2014-07-29

2.  A critical quantity for noise attenuation in feedback systems.

Authors:  Liming Wang; Jack Xin; Qing Nie
Journal:  PLoS Comput Biol       Date:  2010-04-29       Impact factor: 4.475

3.  Positive autoregulation shapes response timing and intensity in two-component signal transduction systems.

Authors:  Alexander Y Mitrophanov; Tricia J Hadley; Eduardo A Groisman
Journal:  J Mol Biol       Date:  2010-06-30       Impact factor: 5.469

4.  Computational Identification of Mechanistic Factors That Determine the Timing and Intensity of the Inflammatory Response.

Authors:  Sridevi Nagaraja; Jaques Reifman; Alexander Y Mitrophanov
Journal:  PLoS Comput Biol       Date:  2015-12-03       Impact factor: 4.475

  4 in total

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