Quantitative dissection of the simple repression input–output function
- Creators
- Garcia, Hernan G.
-
Phillips, Rob
Abstract
We present a quantitative case study of transcriptional regulation in which we carry out a systematic dialogue between theory and measurement for an important and ubiquitous regulatory motif in bacteria, namely, that of simple repression. This architecture is realized by a single repressor binding site overlapping the promoter. From the theory point of view, this motif is described by a single gene regulation function based upon only a few parameters that are convenient theoretically and accessible experimentally. The usual approach is turned on its side by using the mathematical description of these regulatory motifs as a predictive tool to determine the number of repressors in a collection of strains with a large variation in repressor copy number. The predictions and corresponding measurements are carried out over a large dynamic range in both expression fold change (spanning nearly four orders of magnitude) and repressor copy number (spanning about two orders of magnitude). The predictions are tested by measuring the resulting level of gene expression and are then validated by using quantitative immunoblots. The key outcomes of this study include a systematic quantitative analysis of the limits and validity of the input–output relation for simple repression, a precise determination of the in vivo binding energies for DNA–repressor interactions for several distinct repressor binding sites, and a repressor census for Lac repressor in Escherichia coli.
Additional Information
© 2011 National Academy of Sciences. Edited by Curtis G. Callan, Princeton University, Princeton, NJ, and approved May 26, 2011 (received for review October 18, 2010). Published online before print July 5, 2011. We thank Rob Brewster, Stephanie Johnson, Jane Kondev, Tom Kuhlman, Kathy Matthews, Ron Milo, Alvaro Sanchez, Paul Wiggins, and Bob Schleif for enlightening discussions over the course of many years and comments on the manuscript, and to Thomas Gregor and Ted Cox for lending their respective laboratory spaces for further experiments. We thank Franz Weinert, James Boedicker, Heun Jin Lee, and Maja Bialecka for help with the cell counts calibration. We thank the National Institutes of Health for support through Grant DP1 OD000217 (Director's Pioneer Award) and Grant R01 GM085286, and La Fondation Pierre Gilles de Gennes (R.P.). Author contributions: H.G.G. and R.P. designed research; H.G.G. performed research; H.G.G. and R.P. analyzed data; and H.G.G. and R.P. wrote the paper.Attached Files
Published - Garcia2011p15340P_Natl_Acad_Sci_Usa.pdf
Supplemental Material - pnas.201015616SI.pdf
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Additional details
- PMCID
- PMC3141941
- Eprint ID
- 24609
- Resolver ID
- CaltechAUTHORS:20110801-102535300
- NIH
- DP1 OD000217
- NIH
- R01 GM085286
- La Fondation Pierre Gilles de Gennes
- Created
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2011-09-26Created from EPrint's datestamp field
- Updated
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2021-11-09Created from EPrint's last_modified field