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

Abstract

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.

Authors:
 [1];  [2];  [2];  [1];  [2]
  1. University of Tennessee, Knoxville (UTK)
  2. ORNL
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
989716
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Journal Article
Journal Name:
Chaos: An Interdisciplinary Journal of Nonlinear Science
Additional Journal Information:
Journal Volume: 20; Journal Issue: 3; Journal ID: ISSN 1054-1500
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; DESIGN; DISTRIBUTION; ELECTRONS; FLUCTUATIONS; GENES; PLASTICITY; REGULATIONS; SACCHAROMYCES; SACCHAROMYCES CEREVISIAE; STIMULI; YEASTS; Stochasticity; complex systems; emergent behavior

Citation Formats

Dar, Roy D., Karig, David K, Cooke, John F, Cox, Chris D., and Simpson, Michael L. Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae. United States: N. p., 2010. Web. doi:10.1063/1.3486800.
Dar, Roy D., Karig, David K, Cooke, John F, Cox, Chris D., & Simpson, Michael L. Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae. United States. https://doi.org/10.1063/1.3486800
Dar, Roy D., Karig, David K, Cooke, John F, Cox, Chris D., and Simpson, Michael L. 2010. "Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae". United States. https://doi.org/10.1063/1.3486800.
@article{osti_989716,
title = {Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae},
author = {Dar, Roy D. and Karig, David K and Cooke, John F and Cox, Chris D. and Simpson, Michael L},
abstractNote = {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.},
doi = {10.1063/1.3486800},
url = {https://www.osti.gov/biblio/989716}, journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
issn = {1054-1500},
number = 3,
volume = 20,
place = {United States},
year = {Fri Jan 01 00:00:00 EST 2010},
month = {Fri Jan 01 00:00:00 EST 2010}
}

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  • Simpson, Michael L.; Cox, Chris D.; Allen, Michael S.
  • Wiley Interdisciplinary Reviews: Nanomedicine and Nanobiotechnology, Vol. 1, Issue 2
  • https://doi.org/10.1002/wnan.22

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Works referencing / citing this record:

Fine-tuning of noise in gene expression with nucleosome remodeling
journal, June 2018


Perspective: Engineering noise in biological systems towards predictive stochastic design
journal, June 2018


Screening for noise in gene expression identifies drug synergies
journal, June 2014


Perspective: Engineering noise in biological systems towards predictive stochastic design
journal, June 2018


The Low Noise Limit in Gene Expression
journal, October 2015