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Stochastic tuning of gene expression enables cellular adaptation in the absence of pre-existing regulatory circuitry

Peter L. Freddolino; Jamie Siyu Yang; Amir Momen-Roknabadi; Saeed Tavazoie

Title:
Stochastic tuning of gene expression enables cellular adaptation in the absence of pre-existing regulatory circuitry
Author(s):
Freddolino, Peter L.
Yang, Jamie Siyu
Momen-Roknabadi, Amir
Tavazoie, Saeed
Date:
Type:
Articles
Department(s):
Biochemistry and Molecular Biophysics
Systems Biology
Volume:
7
Persistent URL:
Book/Journal Title:
eLife
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.
Subject(s):
Gene regulatory networks
Systems biology
Gene expression
Stochastic processes
Epigenetics
Publisher DOI:
https://doi.org/10.7554/eLife.31867
Item views
20
Metadata:
text | xml
Suggested Citation:
Peter L. Freddolino, Jamie Siyu Yang, Amir Momen-Roknabadi, Saeed Tavazoie, , Stochastic tuning of gene expression enables cellular adaptation in the absence of pre-existing regulatory circuitry, Columbia University Academic Commons, .

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