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Published December 2008 | Presentation + Accepted Version + Supplemental Material
Journal Article Open

Regulatory activity revealed by dynamic correlations in gene expression noise

Abstract

Gene regulatory interactions are context dependent, active in some cellular states but not in others. Stochastic fluctuations, or 'noise', in gene expression propagate through active, but not inactive, regulatory links^(1,2). Thus, correlations in gene expression noise could provide a noninvasive means to probe the activity states of regulatory links. However, global, 'extrinsic', noise sources generate correlations even without direct regulatory links. Here we show that single-cell time-lapse microscopy, by revealing time lags due to regulation, can discriminate between active regulatory connections and extrinsic noise. We demonstrate this principle mathematically, using stochastic modeling, and experimentally, using simple synthetic gene circuits. We then use this approach to analyze dynamic noise correlations in the galactose metabolism genes of Escherichia coli. We find that the CRP-GalS-GalE feed-forward loop is inactive in standard conditions but can become active in a GalR mutant. These results show how noise can help analyze the context dependence of regulatory interactions in endogenous gene circuits.

Additional Information

© 2008 Nature Publishing Group. Received 9 June; accepted 23 September; published online 23 November 2008. We thank M. Fontes, F. Tan, L. Cai, E. Franco, and all members of the Elowitz and Murray groups for their feedback and suggestions. H. Garcia provided advice on the chromosomal integration and gene knockout experiments. We thank J. Garcia-Ojalvo, U. Alon, R. Kishony, N. Rosenfeld and B. Shraiman for discussions. M.J.D. and R.M.M. are supported by the Institute for Collaborative Biotechnologies through grant DAAD19-03-D-0004 from the US Army Research Office. M.J.D. was additionally supported by a Department of Energy Computational Science Graduate Fellowship. This research was supported by US National Institutes of Health grants R01GM079771, P50 GM068763, National Science Foundation CAREER Award 0644463 and the Packard Foundation.

Attached Files

Accepted Version - nihms166225.pdf

Supplemental Material - DUNng08supp.pdf

Presentation - DUNng08movie1.avi

Presentation - DUNng08movie2.avi

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August 22, 2023
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