Literature DB >> 12779449

Design principles for elementary gene circuits: Elements, methods, and examples.

Michael A. Savageau1.   

Abstract

The control of gene expression involves complex circuits that exhibit enormous variation in design. For years the most convenient explanation for these variations was historical accident. According to this view, evolution is a haphazard process in which many different designs are generated by chance; there are many ways to accomplish the same thing, and so no further meaning can be attached to such different but equivalent designs. In recent years a more satisfying explanation based on design principles has been found for at least certain aspects of gene circuitry. By design principle we mean a rule that characterizes some biological feature exhibited by a class of systems such that discovery of the rule allows one not only to understand known instances but also to predict new instances within the class. The central importance of gene regulation in modern molecular biology provides strong motivation to search for more of these underlying design principles. The search is in its infancy and there are undoubtedly many design principles that remain to be discovered. The focus of this three-part review will be the class of elementary gene circuits in bacteria. The first part reviews several elements of design that enter into the characterization of elementary gene circuits in prokaryotic organisms. Each of these elements exhibits a variety of realizations whose meaning is generally unclear. The second part reviews mathematical methods used to represent, analyze, and compare alternative designs. Emphasis is placed on particular methods that have been used successfully to identify design principles for elementary gene circuits. The third part reviews four design principles that make specific predictions regarding (1) two alternative modes of gene control, (2) three patterns of coupling gene expression in elementary circuits, (3) two types of switches in inducible gene circuits, and (4) the realizability of alternative gene circuits and their response to phased environmental cues. In each case, the predictions are supported by experimental evidence. These results are important for understanding the function, design, and evolution of elementary gene circuits. (c) 2001 American Institute of Physics.

Year:  2001        PMID: 12779449     DOI: 10.1063/1.1349892

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  61 in total

1.  Assigning numbers to the arrows: parameterizing a gene regulation network by using accurate expression kinetics.

Authors:  Michal Ronen; Revital Rosenberg; Boris I Shraiman; Uri Alon
Journal:  Proc Natl Acad Sci U S A       Date:  2002-07-26       Impact factor: 11.205

2.  A nonlinear discrete dynamical model for transcriptional regulation: construction and properties.

Authors:  John Goutsias; Seungchan Kim
Journal:  Biophys J       Date:  2004-04       Impact factor: 4.033

3.  Bridging the gap between stochastic and deterministic regimes in the kinetic simulations of the biochemical reaction networks.

Authors:  Jacek Puchałka; Andrzej M Kierzek
Journal:  Biophys J       Date:  2004-03       Impact factor: 4.033

4.  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

5.  Architecture-dependent robustness and bistability in a class of genetic circuits.

Authors:  Jiajun Zhang; Zhanjiang Yuan; Han-Xiong Li; Tianshou Zhou
Journal:  Biophys J       Date:  2010-08-09       Impact factor: 4.033

6.  Biological role of noise encoded in a genetic network motif.

Authors:  Mark Kittisopikul; Gürol M Süel
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-28       Impact factor: 11.205

7.  Mathematical description of gene regulatory units.

Authors:  Reiko J Tanaka; Hiroyuki Okano; Hidenori Kimura
Journal:  Biophys J       Date:  2006-05-19       Impact factor: 4.033

Review 8.  Synthetic protocell biology: from reproduction to computation.

Authors:  Ricard V Solé; Andreea Munteanu; Carlos Rodriguez-Caso; Javier Macía
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2007-10-29       Impact factor: 6.237

9.  A top-down approach to mechanistic biological modeling: application to the single-chain antibody folding pathway.

Authors:  Scott Hildebrandt; David Raden; Linda Petzold; Anne Skaja Robinson; Francis J Doyle
Journal:  Biophys J       Date:  2008-07-18       Impact factor: 4.033

10.  Phenotypes and tolerances in the design space of biochemical systems.

Authors:  Michael A Savageau; Pedro M B M Coelho; Rick A Fasani; Dean A Tolla; Armindo Salvador
Journal:  Proc Natl Acad Sci U S A       Date:  2009-03-11       Impact factor: 11.205

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