Literature DB >> 7752237

Subunit structure of regulator proteins influences the design of gene circuitry: analysis of perfectly coupled and completely uncoupled circuits.

W S Hlavacek1, M A Savageau.   

Abstract

Cells regulate expression their genome by means of a diverse repertoire of molecular mechanisms. However, little is known about their design principles or how these are influenced by underlying physical constraints. An early theory of gene regulation for inducible systems predicted that expression of the regulator and regulated proteins would be perfectly coupled (coordinate expression of regulator) when the regulator is a repressor and completely uncoupled (invariant expression of regulator) when the regulator is an activator. The experimental data then available tended to support these predictions, but there were notable exceptions. Here, we describe an extended theory, which takes into account the subunit structure of regulator proteins. The number of subunits determines the allowable range of values for the regulatory parameters, and, as a consequence, new rules for the prediction of gene circuitry emerge. The theory predicts perfectly coupled circuits with repressors, but only when the capacity for induction is "small"; it predicts completely uncoupled circuits with repressors when the capacity is "large". This theory also predicts completely uncoupled circuits with activators when the capacity for induction is small; it predicts perfectly coupled circuits with activators when the capacity is large. These new predictions are more fully in accord with available experimental evidence.

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Year:  1995        PMID: 7752237     DOI: 10.1006/jmbi.1995.0257

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


  11 in total

1.  Sequence tolerance of the phage lambda PRM promoter: implications for evolution of gene regulatory circuitry.

Authors:  Christine B Michalowski; Megan D Short; John W Little
Journal:  J Bacteriol       Date:  2004-12       Impact factor: 3.490

2.  Automated construction and analysis of the design space for biochemical systems.

Authors:  Rick A Fasani; Michael A Savageau
Journal:  Bioinformatics       Date:  2010-09-07       Impact factor: 6.937

3.  Optimal control of gene expression for fast proteome adaptation to environmental change.

Authors:  Michael Y Pavlov; Måns Ehrenberg
Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-02       Impact factor: 11.205

Review 4.  Non-transcriptional regulatory processes shape transcriptional network dynamics.

Authors:  J Christian J Ray; Jeffrey J Tabor; Oleg A Igoshin
Journal:  Nat Rev Microbiol       Date:  2011-10-11       Impact factor: 60.633

Review 5.  Design of the lac gene circuit revisited.

Authors:  Michael A Savageau
Journal:  Math Biosci       Date:  2011-03-21       Impact factor: 2.144

Review 6.  Bistable responses in bacterial genetic networks: designs and dynamical consequences.

Authors:  Abhinav Tiwari; J Christian J Ray; Jatin Narula; Oleg A Igoshin
Journal:  Math Biosci       Date:  2011-03-06       Impact factor: 2.144

Review 7.  Recent developments in parameter estimation and structure identification of biochemical and genomic systems.

Authors:  I-Chun Chou; Eberhard O Voit
Journal:  Math Biosci       Date:  2009-03-25       Impact factor: 2.144

8.  Negative feedback in genetic circuits confers evolutionary resilience and capacitance.

Authors:  David C Marciano; Rhonald C Lua; Panagiotis Katsonis; Shivas R Amin; Christophe Herman; Olivier Lichtarge
Journal:  Cell Rep       Date:  2014-06-05       Impact factor: 9.423

9.  The timing of TNF and IFN-gamma signaling affects macrophage activation strategies during Mycobacterium tuberculosis infection.

Authors:  J Christian J Ray; Jian Wang; John Chan; Denise E Kirschner
Journal:  J Theor Biol       Date:  2008-01-20       Impact factor: 2.691

10.  Quantifying global tolerance of biochemical systems: design implications for moiety-transfer cycles.

Authors:  Pedro M B M Coelho; Armindo Salvador; Michael A Savageau
Journal:  PLoS Comput Biol       Date:  2009-03-20       Impact factor: 4.475

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