Multiplexed characterization of rationally designed promoter architectures deconstructs combinatorial logic for IPTG-inducible systems
Abstract
A crucial step towards engineering biological systems is the ability to precisely tune the genetic response to environmental stimuli. In the case of Escherichia coli inducible promoters, our incomplete understanding of the relationship between sequence composition and gene expression hinders our ability to predictably control transcriptional responses. Here, we profile the expression dynamics of 8269 rationally designed, IPTG-inducible promoters that collectively explore the individual and combinatorial effects of RNA polymerase and LacI repressor binding site strengths. We then fit a statistical mechanics model to measured expression that accurately models gene expression and reveals properties of theoretically optimal inducible promoters. Furthermore, we characterize three alternative promoter architectures and show that repositioning binding sites within promoters influences the types of combinatorial effects observed between promoter elements. In total, this approach enables us to deconstruct relationships between inducible promoter elements and discover practical insights for engineering inducible promoters with desirable characteristics.
Additional Information
© The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Received 14 February 2020; Accepted 04 November 2020; Published 12 January 2021. This work was supported by the National Science Foundation Graduate Research Fellowship 2015210106 to G.U., National Institutes of Health New Innovator Award DP2GM114829 to S.K., Searle Scholars Program to S.K., U.S. Department of Energy (DE-FC02-02ER63421 to S.K.), UCLA, and Linda and Fred Wudl. We thank the UCLA BSCRC high-throughput sequencing core and Technology Center for Genomics and Bioinformatics for technical assistance; All past and present members of the Kosuri lab for technical feedback; Suzannah Beeler for thoughtful discussions; and Reid C. Johnson for the paper feedback. Lastly, we thank the UCLA Molecular Biology Interdepartmental Graduate Program and UCLA Bioinformatics Interdepartmental Graduate Program. Data availability: Raw data and promoter expression datasets are available without restrictions through NCBI Gene Expression Omnibus (Accession no. GSE145630). All other relevant data are available from the authors upon reasonable request. Source data are provided with this paper. Code availability: The Mathematica notebook used for the thermodynamic model, as well as all code for recreating plots, are available at https://github.com/timcyu/inducible_architecture. Statistical significance is reported to a lower limit of P < 2.2 × 10⁻¹⁶, the lowest reportable value by R. These authors contributed equally: Timothy C. Yu, Winnie L. Liu. These authors jointly supervised this work: Sriram Kosuri, Guillaume Urtecho. Author Contributions: T.C.Y., G.U., W.L.L., J.E.D., J.S., G.B., T.E., and S.K. designed the study. T.C.Y. and K.D.I. generated the sequence libraries. T.C.Y., M.S.B., W.L.L., J.S., and G.B. performed the experiments. T.C.Y., G.U., J.E.D., and T.E. analyzed the data. W.L.L. designed the figures. T.E. and R.P. developed the statistical mechanics model. T.C.Y., G.U., W.L.L., J.E.D., J.S., G.B., and T.E. wrote the paper. All authors edited and approved the paper. The authors declare no competing interests. Peer review information: Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.Attached Files
Published - s41467-020-20094-3.pdf
Submitted - 2020.01.31.928689v1.full.pdf
Supplemental Material - 41467_2020_20094_MOESM1_ESM.pdf
Supplemental Material - 41467_2020_20094_MOESM2_ESM.pdf
Supplemental Material - 41467_2020_20094_MOESM3_ESM.pdf
Supplemental Material - 41467_2020_20094_MOESM4_ESM.zip
Files
| Name | Size | Download all |
|---|---|---|
|
md5:cc0801cb12b288bb5de9a7f73bd76378
|
2.2 MB | Preview Download |
|
md5:5325c06286539f6881d651ac2444e49f
|
2.0 MB | Preview Download |
|
md5:332566147e62fc93922fb5e5ab67ffef
|
2.0 MB | Preview Download |
|
md5:cefce2630bcbb7b66152f50fb54e472f
|
3.3 MB | Preview Download |
|
md5:6576b666a3c81ef20bb8066362f7685b
|
5.2 MB | Preview Download |
|
md5:047ad0ca08e84cc175c6417205817d83
|
9.9 MB | Preview Download |
Additional details
- PMCID
- PMC7804116
- Eprint ID
- 101053
- Resolver ID
- CaltechAUTHORS:20200203-092359628
- NSF Graduate Research Fellowship
- 2015210106
- NIH
- DP2GM114829
- Searle Scholars Program
- Department of Energy (DOE)
- DE-FC02-02ER63421
- UCLA
- Linda and Fred Wudl
- Created
-
2020-02-03Created from EPrint's datestamp field
- Updated
-
2023-06-01Created from EPrint's last_modified field
- Caltech groups
- Division of Biology and Biological Engineering (BBE)