ArticlePLoS computational biology2011
Noise contributions in an inducible genetic switch: a whole-cell simulation study.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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43 citing papers in PubMed, 95 citations in OpenAlex.
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- Switching off: The phenotypic transition to the uninduced state of the lactose uptake pathway.Biophysical journal · 2022Article
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- Generating Chromosome Geometries in a Minimal Cell From Cryo-Electron Tomograms and Chromosome Conformation Capture Maps.Frontiers in molecular biosciences · 2021Article
- Simultaneous cross-evaluation of heterogeneousScience (New York, N.Y.) · 2020Article
- An in-silico human cell model reveals the influence of spatial organization on RNA splicing.PLoS computational biology · 2020Article
- Automatic error control during forward flux sampling of rare events in master equation models.The Journal of chemical physics · 2020Article
- ReaDDy 2: Fast and flexible software framework for interacting-particle reaction dynamics.PLoS computational biology · 2019Article
- Emerging whole-cell modeling principles and methods.Current opinion in biotechnology · 2018Review
- A Digitally Programmable Cytomorphic Chip for Simulation of Arbitrary Biochemical Reaction Networks.IEEE transactions on biomedical circuits and systems · 2018Article
- Challenges of Integrating Stochastic Dynamics and Cryo-Electron Tomograms in Whole-Cell Simulations.The journal of physical chemistry. B · 2017Article
- Effects of cell cycle noise on excitable gene circuits.Physical biology · 2016Article
- Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution.Nucleic acids research · 2016Article
- Article
- Bursting noise in gene expression dynamics: linking microscopic and mesoscopic models.Journal of the Royal Society, Interface · 2016Article
- Effects of DNA replication on mRNA noise.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Sources of Variability in a Synthetic Gene Oscillator.PLoS computational biology · 2015Article
- Why Build Whole-Cell Models?Trends in cell biology · 2015Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stochastic expression of genes produces heterogeneity in clonal populations of bacteria under identical conditions. We analyze and compare the behavior of the inducible lac genetic switch using well-stirred and spatially resolved simulations for Escherichia coli cells modeled under fast and slow-growth conditions. Our new kinetic model describing the switching of the lac operon from one phenotype to the other incorporates parameters obtained from recently published in vivo single-molecule fluorescence experiments along with in vitro rate constants. For the well-stirred system, investigation of the intrinsic noise in the circuit as a function of the inducer concentration and in the presence/absence of the feedback mechanism reveals that the noise peaks near the switching threshold. Applying maximum likelihood estimation, we show that the analytic two-state model of gene expression can be used to extract stochastic rates from the simulation data. The simulations also provide mRNA-protein probability landscapes, which demonstrate that switching is the result of crossing both mRNA and protein thresholds. Using cryoelectron tomography of an E. coli cell and data from proteomics studies, we construct spatial in vivo models of cells and quantify the noise contributions and effects on repressor rebinding due to cell structure and crowding in the cytoplasm. Compared to systems without spatial heterogeneity, the model for the fast-growth cells predicts a slight decrease in the overall noise and an increase in the repressors rebinding rate due to anomalous subdiffusion. The tomograms for E. coli grown under slow-growth conditions identify the positions of the ribosomes and the condensed nucleoid. The smaller slow-growth cells have increased mRNA localization and a larger internal inducer concentration, leading to a significant decrease in the lifetime of the repressor-operator complex and an increase in the frequency of transcriptional bursts.
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