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Science 339 (6119): 584-587

Copyright © 2013 by the American Association for the Advancement of Science

Systematic Identification of Signal-Activated Stochastic Gene Regulation

Gregor Neuert,1,2,* Brian Munsky,3,* Rui Zhen Tan,1,5,6 Leonid Teytelman,1 Mustafa Khammash,4,7,{dagger} Alexander van Oudenaarden1,8,{dagger},{ddagger}

Abstract: Although much has been done to elucidate the biochemistry of signal transduction and gene regulatory pathways, it remains difficult to understand or predict quantitative responses. We integrate single-cell experiments with stochastic analyses, to identify predictive models of transcriptional dynamics for the osmotic stress response pathway in Saccharomyces cerevisiae. We generate models with varying complexity and use parameter estimation and cross-validation analyses to select the most predictive model. This model yields insight into several dynamical features, including multistep regulation and switchlike activation for several osmosensitive genes. Furthermore, the model correctly predicts the transcriptional dynamics of cells in response to different environmental and genetic perturbations. Because our approach is general, it should facilitate a predictive understanding for signal-activated transcription of other genes in other pathways or organisms.

1 Departments of Physics and Biology and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
2 Department of Molecular Physiology and Biophysics, School of Medicine, Vanderbilt University, Nashville, TN 37232, USA.
3 Center for Nonlinear Studies and the Information Sciences Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
4 Department of Biosystems Science and Engineering, ETH-Zuerich, 4058 Basel, Switzerland.
5 Bioinformatics Institute, A*STAR, Singapore 138671, Singapore.
6 Harvard University Graduate Biophysics Program, Harvard Medical School, Boston, MA 02115, USA.
7 Center for Control, Dynamical Systems and Computation and Department of Mechanical Engineering, University of California, Santa Barbara, CA 93106, USA.
8 Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT, Utrecht, Netherlands.

* These authors contributed equally to this work.

{dagger} Co-senior authors.

{ddagger} To whom correspondence should be addressed. E-mail: a.vanoudenaarden{at}

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