Literature DB >> 15617166

Robustness, stability and efficiency of phage lambda genetic switch: dynamical structure analysis.

X-M Zhu1, L Yin, L Hood, P Ao.   

Abstract

Based on the dynamical structure theory for complex networks recently developed by one of us and on the physical-chemical models for gene regulation, developed by Shea and Ackers in the 1980's, we formulate a direct and concise mathematical framework for the genetic switch controlling phage lambda life cycles, which naturally includes the stochastic effect. The dynamical structure theory states that the dynamics of a complex network is determined by its four elementary components: The dissipation (analogous to degradation), the stochastic force, the driving force determined by a potential, and the transverse force. The potential may be interpreted as a landscape for the phage development in terms of attractive basins, saddle points, peaks and valleys. The dissipation gives rise to the adaptivity of the phage in the landscape defined by the potential: The phage always has the tendency to approach the bottom of the nearby attractive basin. The transverse force tends to keep the network on the equal-potential contour of the landscape. The stochastic fluctuation gives the phage the ability to search around the potential landscape by passing through saddle points. With molecular parameters in our model fixed primarily by the experimental data on wild-type phage and supplemented by data on one mutant, our calculated results on mutants agree quantitatively with the available experimental observations on other mutants for protein number, lysogenization frequency, and a lysis frequency in lysogen culture. The calculation reproduces the observed robustness of the phage lambda genetic switch. This is the first mathematical description that successfully represents such a wide variety of major experimental phenomena. Specifically, we find: (1) The explanation for both the stability and the efficiency of phage lambda genetic switch is the exponential dependence of saddle point crossing rate on potential barrier height, a result of the stochastic motion in a landscape; and (2) The positive feedback of cI repressor gene transcription, enhanced by the CI dimer cooperative binding, is the key to the robustness of the phage lambda genetic switch against mutations and fluctuations in kinetic parameter values.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15617166     DOI: 10.1142/s0219720004000946

Source DB:  PubMed          Journal:  J Bioinform Comput Biol        ISSN: 0219-7200            Impact factor:   1.122


  26 in total

1.  Probability landscape of heritable and robust epigenetic state of lysogeny in phage lambda.

Authors:  Youfang Cao; Hsiao-Mei Lu; Jie Liang
Journal:  Proc Natl Acad Sci U S A       Date:  2010-10-11       Impact factor: 11.205

2.  Nonlinear protein degradation and the function of genetic circuits.

Authors:  Nicolas E Buchler; Ulrich Gerland; Terence Hwa
Journal:  Proc Natl Acad Sci U S A       Date:  2005-06-22       Impact factor: 11.205

3.  Noise in a Small Genetic Circuit that Undergoes Bifurcation.

Authors:  Trent Toulouse; Ping Ao; Ilya Shmulevich; Stuart Kauffman
Journal:  Complexity       Date:  2005       Impact factor: 2.833

4.  Highly designable phenotypes and mutational buffers emerge from a systematic mapping between network topology and dynamic output.

Authors:  Yigal D Nochomovitz; Hao Li
Journal:  Proc Natl Acad Sci U S A       Date:  2006-03-03       Impact factor: 11.205

5.  Reaction coordinates for the flipping of genetic switches.

Authors:  Marco J Morelli; Sorin Tanase-Nicola; Rosalind J Allen; Pieter Rein ten Wolde
Journal:  Biophys J       Date:  2008-01-25       Impact factor: 4.033

6.  Stochastic probability landscape model for switching efficiency, robustness, and differential threshold for induction of genetic circuit in phage lambda.

Authors:  Youfang Cao; Hsiao-Mei Lu; Jie Liang
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2008

7.  State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation.

Authors:  Youfang Cao; Anna Terebus; Jie Liang
Journal:  Bull Math Biol       Date:  2016-04-22       Impact factor: 1.758

8.  Global view of bionetwork dynamics: adaptive landscape.

Authors:  Ping Ao
Journal:  J Genet Genomics       Date:  2009-02       Impact factor: 4.275

9.  Probabilistic control of HIV latency and transactivation by the Tat gene circuit.

Authors:  Youfang Cao; Xue Lei; Ruy M Ribeiro; Alan S Perelson; Jie Liang
Journal:  Proc Natl Acad Sci U S A       Date:  2018-11-19       Impact factor: 11.205

10.  Mathematical models of the transitions between endocrine therapy responsive and resistant states in breast cancer.

Authors:  Chun Chen; William T Baumann; Jianhua Xing; Lingling Xu; Robert Clarke; John J Tyson
Journal:  J R Soc Interface       Date:  2014-05-07       Impact factor: 4.118

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.