Stochastic tuning: a novel regulatory mechanism for cellular adaptation

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Abstract Regulation of gene expression is the fundamental mechanism by which cells adapt to changes in the external environment. As such, dedicated pathways have evolved to sense environmental signals and to convey this information to specific signaling and regulatory circuits in order to execute pre-programmed changes in gene expression. This has been our conventional understanding of gene regulation and cellular adaptation for over sixty years. We have recently discovered that eukaryotic cells employ an entirely distinct strategy to achieve adaptive gene expression states independent of these conventional hard-wired pathways. In this process that we call stochastic tuning, cells utilize the inherent noise in mRNA transcription to randomly increase or decrease expression of genes and to actively reinforce only those changes that improve the overall health of the cell. This real-time empirical optimization strategy enables cells to adapt to extreme/unfamiliar environments by establishing arbitrary patterns of gene expression that are beyond the capacity of their hard- wired regulatory programs. We have extensive published and preliminary data that stochastic tuning operates in both budding yeast S. cerevisiae and human cell-lines. We are compelled by the possibility that stochastic tuning may be a widespread mechanism of adaptation in eukaryotes. In particular, it may be the basis for ‘non- genetic’ phenomena of disease relevance including epigenetic chemotherapeutic resistance. We have recently identified candidate genetic loci and chemical perturbations that substantially affect stochastic tuning behavior in yeast. We propose to substantially scale these efforts to comprehensively identify the underlying cis and trans molecular effectors using unbiased systems biological approaches. These include: (1) utilization of our recently developed full yeast CRISPR-interference library to quantitatively determine the role of all essential and non-essential genes in stochastic tuning; (2) Comprehensive profiling of all core yeast promoters for tuning efficacy using FACS-sorting of fluorescent reporter libraries and high-throughput sequencing; (3) de novo computational inference and experimental validation of critical DNA sequence features; (4) high-resolution profiling of mRNA and chromatin dynamics along a tuning trajectory; (5) precise induction and monitoring of tuning events using optogenetic perturbations and high-temporal resolution monitoring of gene expression in single cells; and (6) determining the functional roles of discovered effectors in the distinct phases of tuning using a closed-loop system that enables precise control and monitoring of tuning trajectories. These efforts represent the very first systematic genetic interrogation of stochastic tuning. We expect these studies to generate a parts-list of key effectors in stochastic tuning and to delineate their roles in the various phases of the process, monitored and perturbed in single cells. This is a critical first step in the determining the detailed molecular mechanism of stochastic tuning and in revealing the full implications of this gene-regulatory phenomenon in physiology, development, and disease.