Tuning Promoter Strength through RNA Polymerase Binding Site Design in Escherichia coli
Abstract
One of the paramount goals of synthetic biology is to have the ability to tune transcriptional networks to targeted levels of expression at will. As a step in that direction, we have constructed a set of 18 unique binding sites for E. coli RNA Polymerase (RNAP) σ^(70) holoenzyme, designed using a model of sequence-dependent binding energy combined with a thermodynamic model of transcription to produce a targeted level of gene expression. This promoter set allows us to determine the correspondence between the absolute numbers of mRNA molecules or protein products and the predicted promoter binding energies measured in K_(B)T energy units. These binding sites adhere on average to the predicted level of gene expression over orders of magnitude in constitutive gene expression, to within a factor of in both protein and mRNA copy number. With these promoters in hand, we then place them under the regulatory control of a bacterial repressor and show that again there is a strict correspondence between the measured and predicted levels of expression, demonstrating the transferability of the promoters to an alternate regulatory context. In particular, our thermodynamic model predicts the expression from our promoters under a range of repressor concentrations between several per cell up to over 100 per cell. After correcting the predicted polymerase binding strength using the data from the unregulated promoter, the thermodynamic model accurately predicts the expression for the simple repression strains to within 30%. Demonstration of modular promoter design, where parts of the circuit (such as RNAP/TF binding strength and transcription factor copy number) can be independently chosen from a stock list and combined to give a predictable result, has important implications as an engineering tool for use in synthetic biology.
Additional Information
© 2012 Brewster et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received: April 10, 2012; Accepted: October 18, 2012; Published: December 13, 2012. This work was supported by the National Institutes of Health, grant numbers DP1 OD000217A (Directors Pioneer Award) and R01 GM085286 (www.nih.gov). This work was also supported by the Donna and Benjamin M. Rosen Center for Bioengineering at Caltech. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors wish to thank Justin Kinney, Hernan Garcia, James Boedicker, Heun Jin Lee, Franz Weinert, Stephanie Johnson, Mattias Rydenfelt, Ron Milo, Niv Antonovsky, Terry Hwa and Uli Gerland for useful discussions. Author Contributions: Conceived and designed the experiments: RCB DLJ RP. Performed the experiments: RCB DLJ. Analyzed the data: RCB DLJ. Contributed reagents/materials/analysis tools: RCB DLJ. Wrote the paper: RCB DLJ RP.Attached Files
Published - journal.pcbi.1002811.pdf
Supplemental Material - journal.pcbi.1002811.s001.eps
Supplemental Material - journal.pcbi.1002811.s002.txt
Supplemental Material - journal.pcbi.1002811.s003.txt
Supplemental Material - journal.pcbi.1002811.s004.txt
Supplemental Material - journal.pcbi.1002811.s005.txt
Supplemental Material - journal.pcbi.1002811.s006.txt
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Additional details
- PMCID
- PMC3521663
- Eprint ID
- 36848
- Resolver ID
- CaltechAUTHORS:20130211-115816554
- NIH Directors Pioneer Award
- DP1 OD000217A
- NIH
- R01 GM085286
- Caltech Donna and Benjamin M. Rosen Center for Bioengineering
- Created
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2013-02-11Created from EPrint's datestamp field
- Updated
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2021-11-09Created from EPrint's last_modified field