1. Computational and Systems Biology
  2. Chromosomes and Gene Expression
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Stochastic tuning of gene expression enables cellular adaptation in the absence of pre-existing regulatory circuitry

  1. Peter L Freddolino
  2. Jamie Yang
  3. Amir Momen-Roknabadi
  4. Saeed Tavazoie  Is a corresponding author
  1. Columbia University, United States
Research Article
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Cite as: eLife 2018;7:e31867 doi: 10.7554/eLife.31867

Abstract

Cells adapt to familiar changes in their environment by activating predefined regulatory programs that establish adaptive gene expression states. These hard-wired pathways, however, may be inadequate for adaptation to environments never encountered before. Here, we reveal evidence for an alternative mode of gene regulation that enables adaptation to adverse conditions without relying on external sensory information or genetically predetermined cis-regulation. Instead, individual genes achieve optimal expression levels through a stochastic search for improved fitness. By focusing on improving the overall health of the cell, the proposed stochastic tuning mechanism discovers global gene expression states that are fundamentally new and yet optimized for novel environments. We provide experimental evidence for stochastic tuning in the adaptation of Saccharomyces cerevisiae to laboratory-engineered environments that are foreign to its native gene-regulatory network. Stochastic tuning operates locally at individual gene promoters, and its efficacy is modulated by perturbations to chromatin modification machinery.

Article and author information

Author details

  1. Peter L Freddolino

    Department of Systems Biology, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon 0000-0002-5821-4226
  2. Jamie Yang

    Department of Systems Biology, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Amir Momen-Roknabadi

    Department of Systems Biology, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Saeed Tavazoie

    Department of Systems Biology, Columbia University, New York, United States
    For correspondence
    st2744@columbia.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon 0000-0003-2183-4162

Funding

NIH Office of the Director (8DP1ES022578)

  • Saeed Tavazoie

National Institutes of Health (K99 (GM097033-01A1))

  • Peter L Freddolino

National Institutes of Health (MSTP)

  • Jamie Yang

National Institutes of Health (R01-AI077562)

  • Saeed Tavazoie

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Naama Barkai, Reviewing Editor, Weizmann Institute of Science, Israel

Publication history

  1. Received: September 9, 2017
  2. Accepted: April 4, 2018
  3. Accepted Manuscript published: April 5, 2018 (version 1)

Copyright

© 2018, Freddolino et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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