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

• Published in: eLife 2018-04, Vol.7
• Main Authors: Freddolino, Peter L, Yang, Jamie, Momen-Roknabadi, Amir, Tavazoie, Saeed
• Format: Article
• Language: English
• Subjects: Adaptation; Adaptation, Physiological; Algorithms; Cell division; Chromatin; Chromosomes and Gene Expression; Computational and Systems Biology; epigenetics; Gene expression; gene expression noise; Gene Expression Regulation, Fungal; Gene regulation; Gene Regulatory Networks; Genetic Variation; Genome, Fungal; Metabolism; Metabolites; Microscopy; Models, Genetic; Quantitative analysis; Reproductive fitness; Saccharomyces cerevisiae - genetics; Saccharomyces cerevisiae - growth & development; Saccharomyces cerevisiae - metabolism; Saccharomyces cerevisiae Proteins - genetics; Saccharomyces cerevisiae Proteins - metabolism; Stochastic Processes; stochastic tuning; Stochasticity; stress response; Transcription, Genetic; Whole Genome Sequencing
• ISSN: 2050-084X; 2050-084X
• DOI: 10.7554/eLife.31867

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 -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 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.