ArticleProceedings of the National Academy of Sciences of the United States of America2010
Probability landscape of heritable and robust epigenetic state of lysogeny in phage lambda.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Truncating the time-evolving discrete chemical master equation for stochastic biological networks.Biophysical journal · 2026Article
- Neuro-Dynamic Quantitative Systems Pharmacology (QSP) model describing Alzheimer's disease pathophysiology and treatment effects.NPJ systems biology and applications · 2026Article
- Progenitor neighborhoods function as transient niches to sustain olfactory neurogenesis.Stem cell reports · 2025Article
- Understanding the role of toggle genes in chronic lymphocytic leukemia proliferation.NPJ systems biology and applications · 2025Article
- Quantifying nonequilibrium dynamics and thermodynamics of cell fate decision making in yeast under pheromone induction.Biophysics reviews · 2023Article
- Network design principle for robust oscillatory behaviors with respect to biological noise.eLife · 2022Article
- Inferring initial state of the ancestral network of cellular fate decision: a case study of phage lambda.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021Article
- Exact Probability Landscapes of Stochastic Phenotype Switching in Feed-Forward Loops: Phase Diagrams of Multimodality.Frontiers in genetics · 2021Article
- Automatic error control during forward flux sampling of rare events in master equation models.The Journal of chemical physics · 2020Article
- Quantifying the Stability of Coupled Genetic and Epigenetic Switches With Variational Methods.Frontiers in genetics · 2020Article
- Discrete and continuous models of probability flux of switching dynamics: Uncovering stochastic oscillations in a toggle-switch system.The Journal of chemical physics · 2019Article
- Data-Driven Method for Efficient Characterization of Rare Event Probabilities in Biochemical Systems.Bulletin of mathematical biology · 2019Article
- Forecasting cell fate during antibiotic exposure using stochastic gene expression.Communications biology · 2019Article
- Probabilistic control of HIV latency and transactivation by the Tat gene circuit.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Discrete flux and velocity fields of probability and their global maps in reaction systems.The Journal of chemical physics · 2018Article
- PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space.BMC bioinformatics · 2017Article
- Markov State Models of gene regulatory networks.BMC systems biology · 2017Article
- Mechanisms of stochastic focusing and defocusing in biological reaction networks: insight from accurate chemical master equation (ACME) solutions.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2016Article
- Challenges in structural approaches to cell modeling.Journal of molecular biology · 2016Review
- A moment-convergence method for stochastic analysis of biochemical reaction networks.The Journal of chemical physics · 2016Article
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3 authors.
Funding
Abstract
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 Schrödinger'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 discrete 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 O(R)1 and O(R)2 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.
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Registered trials
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