Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae

Dar, R. D.; Karig, D. K.; Cooke, J. F.; Cox, C. D.; Simpson, M. L.

doi:10.1063/1.3486800

Title: Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae

Journal Article · Wed Sep 01 00:00:00 EDT 2010 · Chaos: An Interdisciplinary Journal of Nonlinear Science

DOI:https://doi.org/10.1063/1.3486800· OSTI ID:1076448

Dar, R. D. ^[1]; Karig, D. K. ^[1]; Cooke, J. F. ^[2]; Cox, C. D. ^[1]; Simpson, M. L. ^[1]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)
Univ. of Tennessee, Knoxville, TN (United States)

Stochasticity is an inherent feature of complex systems with nanoscale structure. In such systems information is represented by small collections of elements (e.g. a few electrons on a quantum dot), and small variations in the populations of these elements may lead to big uncertainties in the information. Unfortunately, little is known about how to work within this inherently noisy environment to design robust functionality into complex nanoscale systems. Here, we look to the biological cell as an intriguing model system where evolution has mediated the trade-offs between fluctuations and function, and in particular we look at the relationships and trade-offs between stochastic and deterministic responses in the gene expression of budding yeast (Saccharomyces cerevisiae). We find gene regulatory arrangements that control the stochastic and deterministic components of expression, and show that genes that have evolved to respond to stimuli (stress) in the most strongly deterministic way exhibit the most noise in the absence of the stimuli. We show that this relationship is consistent with a bursty 2-state model of gene expression, and demonstrate that this regulatory motif generates the most uncertainty in gene expression when there is the greatest uncertainty in the optimal level of gene expression.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1076448

Journal Information:: Chaos: An Interdisciplinary Journal of Nonlinear Science, Vol. 20, Issue 3; ISSN 1054-1500

Publisher:: American Institute of Physics (AIP)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 10 works

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Computational Investigation of Environment-Noise Interaction in Single-Cell Organisms: The Merit of Expression Stochasticity Depends on the Quality of Environmental Fluctuations Lück, Anja; Klimmasch, Lukas; Großmann, Peter Scientific Reports, Vol. 8, Issue 1 https://doi.org/10.1038/s41598-017-17441-8	journal	January 2018
High-Throughput Yeast Aging Analysis for Cryptococcus (HYAAC) microfluidic device streamlines aging studies in Cryptococcus neoformans Orner, Erika P.; Zhang, Pengchao; Jo, Myeong C. Communications Biology, Vol. 2, Issue 1 https://doi.org/10.1038/s42003-019-0504-5	journal	July 2019
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Screening for noise in gene expression identifies drug synergies Dar, R. D.; Hosmane, N. N.; Arkin, M. R. Science, Vol. 344, Issue 6190 https://doi.org/10.1126/science.1250220	journal	June 2014
The Low Noise Limit in Gene Expression Dar, Roy D.; Razooky, Brandon S.; Weinberger, Leor S. PLOS ONE, Vol. 10, Issue 10 https://doi.org/10.1371/journal.pone.0140969	journal	October 2015

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