Literature DB >> 8568860

Rules for coupled expression of regulator and effector genes in inducible circuits.

W S Hlavacek1, M A Savageau.   

Abstract

The induction of effector genes that encode enzymes is often controlled by the protein product of a regulator gene that is directly involved in the control of its own expression. This coupling of elementary gene circuits can lead to three patterns of regulator and effector gene expression. As effector gene expression increases, regulator gene expression can increase, remain the same, or decrease, and these are referred to as directly coupled, uncoupled, or inversely coupled patterns. To determine the relative merits of each pattern, we have constructed appropriate mathematical models for the alternative gene circuits and made well-controlled comparisons using a priori criteria to evaluate their functional effectiveness. We have considered both negatively and positively controlled systems that are induced by an intermediate of the regulated pathway. Different results are obtained in the two cases. Our results indicate that direct coupling is better than inverse coupling or uncoupling for negatively controlled systems, while inverse coupling is better than the other two patterns for positively controlled systems. These optimal forms of coupling promote a fast response to inducer. Our results also indicate that realization of the optimal forms of coupling is influenced by the subunit structure of regulator proteins and requires a low capacity for induction, i.e. the ratio of maximal to minimal level of effector gene expression is small. These results lead to testable predictions, which we have compared with experimental data from over 30 systems.

Mesh:

Year:  1996        PMID: 8568860     DOI: 10.1006/jmbi.1996.0011

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


  29 in total

1.  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

2.  Distinctive topologies of partner-switching signaling networks correlate with their physiological roles.

Authors:  Oleg A Igoshin; Margaret S Brody; Chester W Price; Michael A Savageau
Journal:  J Mol Biol       Date:  2007-04-14       Impact factor: 5.469

3.  Calibration of dynamic models of biological systems with KInfer.

Authors:  Paola Lecca; Alida Palmisano; Adaoha Ihekwaba; Corrado Priami
Journal:  Eur Biophys J       Date:  2009-08-11       Impact factor: 1.733

4.  Design principles of a conditional futile cycle exploited for regulation.

Authors:  Dean A Tolla; Patricia J Kiley; Jason G Lomnitz; Michael A Savageau
Journal:  Mol Biosyst       Date:  2015-07

Review 5.  Approach of the functional evolution of duplicated genes in Saccharomyces cerevisiae using a new classification method based on protein-protein interaction data.

Authors:  Christine Brun; Alain Guénoche; Bernard Jacq
Journal:  J Struct Funct Genomics       Date:  2003

6.  Comparative study of three commonly used continuous deterministic methods for modeling gene regulation networks.

Authors:  Martin T Swain; Johannes J Mandel; Werner Dubitzky
Journal:  BMC Bioinformatics       Date:  2010-09-14       Impact factor: 3.169

7.  Rational design of a bacterial transcriptional cascade for amplifying gene expression capacity.

Authors:  A Cebolla; C Sousa; V de Lorenzo
Journal:  Nucleic Acids Res       Date:  2001-02-01       Impact factor: 16.971

8.  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

9.  Grammatical Immune System Evolution for reverse engineering nonlinear dynamic Bayesian models.

Authors:  B A McKinney; D Tian
Journal:  Cancer Inform       Date:  2008-08-28

10.  Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses.

Authors:  Gonzalo Guillén-Gosálbez; Albert Sorribas
Journal:  BMC Bioinformatics       Date:  2009-11-24       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.