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

journal contribution
posted on 2011-05-25, 00:00 authored by Youfang Cao, Hsiao-Mei Lu, Jie Liang
Computational studies of biological networks can help to identify components and wirings responsible for observed phenotypes. However, studying stochastic networks controlling many biological processes is challenging. Similar to Schr ¨odinger’s equation in quantum mechanics, the chemical master equation (CME) provides a basic framework for understanding stochastic networks. However, except for simple problems, the CME cannot be solved analytically. Here we use a method called direct chemical master equation (dCME) to compute directly the full steady-state probability landscape of the lysogeny maintenance network in phage lambda from its CME. Results show that wild type phage lambda can maintain a constant level of repressor over a wide range of repressor degradation rate, and is stable against UV irradiation, ensuring heritability of the lysogenic state. Furthermore, it can switch efficiently to the lytic state once repressor degradation increases past a high threshold by a small amount. We find that beyond bistability and nonlinear dimerization,cooperativity between repressors bound to OR1 and OR2 is required for stable and heritable epigenetic state of lysogeny that can switch efficiently. Mutants of phage lambda lack stability and do not possess a high threshold. Instead, they are leaky and respond to gradual changes in degradation rate. Our computation faithfully reproduces the hair triggers for UV-induced lysis observed in mutants and the limitation in robustness against mutations. The landscape approach computed from dCME is general and can be applied to study broad issues in systems biology.

Funding

This work was supported by a phase II 985 Project, 973 grant 2007CB914703, NIH grants GM079804-01A1, GM081682, NSF grant DMS-0800257, and a grant from the Chicago Biomedical Consortium.

History

Publisher Statement

Post print version of article may differ from published version. The definitive version is available through National Academy of Sciences at DOI: 10.1073/pnas.1001455107. This is a copy of an article published in the Proceedings- National Academy of Sciences USA © 2010- National Academy of Sciences USA

Publisher

National Academy of Sciences

Language

  • en_US

issn

0027-8424

Issue date

2010-10-26

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