Literature DB >> 19162730

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

Youfang Cao1, Hsiao-Mei Lu, Jie Liang.   

Abstract

The genetic switch of phage lambda provides a paradigm for studying developmental biology and cell fate. Although there have been numerous experimental and theoretical studies, the mechanisms for switching efficiency, stability and robustness, maintenance of lysogenic state, and the induction lytic state are not fully understood. In this paper, a new method is adopted to account for the full stochasticity typical in small copy events and the exact steady state probability landscape of the genetic circuit of the switch network is computed. The stability and sensitivity of phage lambda switch and its robustness against perturbations derived from our model for wild type and mutants are consistent with experimental data. Our study has revealed likely mechanism of the phage switch network that was previously unknown.

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Year:  2008        PMID: 19162730      PMCID: PMC2630505          DOI: 10.1109/IEMBS.2008.4649227

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  19 in total

1.  Epigenetics as a first exit problem.

Authors:  E Aurell; K Sneppen
Journal:  Phys Rev Lett       Date:  2002-01-08       Impact factor: 9.161

2.  Stability puzzles in phage lambda.

Authors:  Erik Aurell; Stanley Brown; Johan Johanson; Kim Sneppen
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2002-05-16

3.  Cellular levels of the prophage lambda and 434 repressors.

Authors:  A Levine; A Bailone; R Devoret
Journal:  J Mol Biol       Date:  1979-07-05       Impact factor: 5.469

4.  A quantitative study of lambda-phage SWITCH and its components.

Authors:  Chunbo Lou; Xiaojing Yang; Xili Liu; Bin He; Qi Ouyang
Journal:  Biophys J       Date:  2007-01-26       Impact factor: 4.033

5.  Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells.

Authors:  A Arkin; J Ross; H H McAdams
Journal:  Genetics       Date:  1998-08       Impact factor: 4.562

6.  Protein mobility in the cytoplasm of Escherichia coli.

Authors:  M B Elowitz; M G Surette; P E Wolf; J B Stock; S Leibler
Journal:  J Bacteriol       Date:  1999-01       Impact factor: 3.490

7.  The OR control system of bacteriophage lambda. A physical-chemical model for gene regulation.

Authors:  M A Shea; G K Ackers
Journal:  J Mol Biol       Date:  1985-01-20       Impact factor: 5.469

8.  Rate-limiting steps in RNA chain initiation.

Authors:  W R McClure
Journal:  Proc Natl Acad Sci U S A       Date:  1980-10       Impact factor: 11.205

9.  Control of lambda repressor synthesis.

Authors:  L Reichardt; A D Kaiser
Journal:  Proc Natl Acad Sci U S A       Date:  1971-09       Impact factor: 11.205

10.  Coupled energetics of lambda cro repressor self-assembly and site-specific DNA operator binding II: cooperative interactions of cro dimers.

Authors:  P J Darling; J M Holt; G K Ackers
Journal:  J Mol Biol       Date:  2000-09-22       Impact factor: 5.469

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  4 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 LANGEVIN MODEL WITH PRODUCT STOCHASTICITY FOR BIOLOGICAL NETWORKS: THE CASE OF THE SCHNAKENBERG MODEL.

Authors:  Youfang Cao; Jie Liang
Journal:  J Syst Sci Complex       Date:  2010-11-09       Impact factor: 1.260

3.  Computational Cellular Dynamics Based on the Chemical Master Equation: A Challenge for Understanding Complexity.

Authors:  Jie Liang; Hong Qian
Journal:  J Comput Sci Technol       Date:  2010-01       Impact factor: 1.571

Review 4.  Challenges in structural approaches to cell modeling.

Authors:  Wonpil Im; Jie Liang; Arthur Olson; Huan-Xiang Zhou; Sandor Vajda; Ilya A Vakser
Journal:  J Mol Biol       Date:  2016-05-30       Impact factor: 5.469

  4 in total

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