Stochastic fluctuations (noise) in gene expression can cause members of otherwise genetically identical populations to display drastically different phenotypes. An understanding of the sources of noise and the strategies cells employ to function reliably despite noise is proving to be increasingly important in describing the behavior of natural organisms and will be essential for the engineering of synthetic biological systems. Here we describe the design of synthetic constructs, termed ribosome competing RNAs (rcRNAs), as a means to rationally perturb noise in cellular gene expression. We find that noise in gene expression increases in a manner proportional to the ability of an rcRNA to compete for the cellular ribosome pool. We then demonstrate that operons significantly buffer noise between coexpressed genes in a natural cellular background and can even reduce the level of rcRNA enhanced noise. These results demonstrate that synthetic genetic constructs can significantly affect the noise profile of a living cell and, importantly, that operons are a facile genetic strategy for buffering against noise.
Center for Systems and Synthetic Biology and Institute for Cell and Molecular Biology, University of Texas at Austin, Austin. andy.ellington@mail.utexas.edu.
%0 Journal Article
%1 Tabor2008Engineering
%A Tabor, Jeffrey J.
%A Bayer, Travis S.
%A Simpson, Zachary B.
%A Levy, Matthew
%A Ellington, Andrew D.
%C Center for Systems and Synthetic Biology and Institute for Cell and Molecular Biology, University of Texas at Austin, Austin. andy.ellington@mail.utexas.edu.
%D 2008
%I The Royal Society of Chemistry
%J Mol. BioSyst.
%K gene-expression stochasticity synthetic-biology
%N 7
%P 754--761
%R 10.1039/b801245h
%T Engineering stochasticity in gene expression
%U http://dx.doi.org/10.1039/b801245h
%V 4
%X Stochastic fluctuations (noise) in gene expression can cause members of otherwise genetically identical populations to display drastically different phenotypes. An understanding of the sources of noise and the strategies cells employ to function reliably despite noise is proving to be increasingly important in describing the behavior of natural organisms and will be essential for the engineering of synthetic biological systems. Here we describe the design of synthetic constructs, termed ribosome competing RNAs (rcRNAs), as a means to rationally perturb noise in cellular gene expression. We find that noise in gene expression increases in a manner proportional to the ability of an rcRNA to compete for the cellular ribosome pool. We then demonstrate that operons significantly buffer noise between coexpressed genes in a natural cellular background and can even reduce the level of rcRNA enhanced noise. These results demonstrate that synthetic genetic constructs can significantly affect the noise profile of a living cell and, importantly, that operons are a facile genetic strategy for buffering against noise.
@article{Tabor2008Engineering,
abstract = {Stochastic fluctuations (noise) in gene expression can cause members of otherwise genetically identical populations to display drastically different phenotypes. An understanding of the sources of noise and the strategies cells employ to function reliably despite noise is proving to be increasingly important in describing the behavior of natural organisms and will be essential for the engineering of synthetic biological systems. Here we describe the design of synthetic constructs, termed ribosome competing {RNAs} ({rcRNAs}), as a means to rationally perturb noise in cellular gene expression. We find that noise in gene expression increases in a manner proportional to the ability of an {rcRNA} to compete for the cellular ribosome pool. We then demonstrate that operons significantly buffer noise between coexpressed genes in a natural cellular background and can even reduce the level of {rcRNA} enhanced noise. These results demonstrate that synthetic genetic constructs can significantly affect the noise profile of a living cell and, importantly, that operons are a facile genetic strategy for buffering against noise.},
added-at = {2018-12-02T16:09:07.000+0100},
address = {Center for Systems and Synthetic Biology and Institute for Cell and Molecular Biology, University of Texas at Austin, Austin. andy.ellington@mail.utexas.edu.},
author = {Tabor, Jeffrey J. and Bayer, Travis S. and Simpson, Zachary B. and Levy, Matthew and Ellington, Andrew D.},
biburl = {https://www.bibsonomy.org/bibtex/27ad9265f3c55d4cb475b1acdf81ef0c8/karthikraman},
citeulike-article-id = {2914484},
citeulike-linkout-0 = {http://dx.doi.org/10.1039/b801245h},
citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/18563250},
citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=18563250},
citeulike-linkout-3 = {http://www.rsc.org/Publishing/Journals/article.asp?doi=b801245h},
doi = {10.1039/b801245h},
interhash = {75dd1008ba2cf02ac6f2e8e940a4a740},
intrahash = {7ad9265f3c55d4cb475b1acdf81ef0c8},
issn = {1742-206X},
journal = {Mol. BioSyst.},
keywords = {gene-expression stochasticity synthetic-biology},
month = jul,
number = 7,
pages = {754--761},
pmid = {18563250},
posted-at = {2010-01-27 20:19:27},
priority = {2},
publisher = {The Royal Society of Chemistry},
timestamp = {2018-12-02T16:09:07.000+0100},
title = {Engineering stochasticity in gene expression},
url = {http://dx.doi.org/10.1039/b801245h},
volume = 4,
year = 2008
}