Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria
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Abstract
Developing predictive models of multi-protein genetic systems to understand and optimize their behavior remains a combinatorial challenge, particularly when measurement throughput is limited. We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi-protein expression space across a > 10,000-fold range with tailored search parameters and well-predicted translation rates. We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram-positive and gram-negative bacterial hosts. We then combined the search algorithm with system-level kinetic modeling, requiring the construction and characterization of 73 variants to build a sequence-expression-activity map (SEAMAP) for a biosynthesis pathway. Using model predictions, we designed and characterized 47 additional pathway variants to navigate its activity space, find optimal expression regions with desired activity response curves, and relieve rate-limiting steps in metabolism. Creating sequence-expression-activity maps accelerates the optimization of many protein systems and allows previous measurements to quantitatively inform future designs.
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Large libraries of promoters, terminators, and RBS calculators have been developed and characterized for model organisms like E. coli, dramatically increasing the control of metabolic pathways and allowing efficient pathway refactoring and design of genetic circuits.
“Large libraries of promoters (Temme et al., 2012a), terminators (Chen et al., 2013b), and RBS calculators (Farasat et al., 2014) have been developed and characterized for model organisms like E. coli, dramatically increasing the control of metabolic pathways and allow efficient pathway refactoring and design of genetic circuits (Temme et al., 2012a,b).”
From Gas Fermentation—A Flexible Platform for Commercial Scale Production of Low-Carbon-Fuels and Chemicals from Waste and Renewable Feedstocks (2016) · cites this paper as Farasat et al., 2014
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- Authors
- Farasat, I., Kushwaha, M., Collens, J., Easterbrook, M., Guido, M., & Salis, H. M.
- Affiliations
- Pennsylvania State University (US)
- Corresponding author
- Salis, Howard M
- Venue
- Molecular Systems Biology
- Published
- 2014-06-01
- Volume
- 10
- Issue
- 6
- Pages
- 731-731
- ISSN
- 1744-4292 (ISSN-L)
- PMC
- PMC4265053
- OpenAlex
- W2164028644
- Cited by
- 235
- References
- 89
- Citations by year
- 2026: 16 · 2025: 13 · 2024: 10 · 2023: 14 · 2022: 11 · 2021: 16 · 2020: 19 · 2019: 29 · 2018: 19 · 2017: 25 · 2016: 29 · 2015: 29 · 2014: 4
- FWCI
- 11.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Molecular Systems Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Warwick Research Archive Portal (University of Warwick) (acceptedVersion)
- HAL (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Office of Naval Research (N00014‐13‐1‐0074)
- NSF Career Award (CBET‐1253641)
- DARPA Young Faculty
- Penn State Institute
- NSF Research
- Amazon AWS Research Grant
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Keywords
- synthetic biology, kinetic modeling, metabolic pathway optimization, plasmid expression, bacterial hosts, biosynthetic pathway, combinatorial designs
- MeSH terms
- Algorithms, Bacteria, Bacterial Proteins, Biophysics, Models, Theoretical, Plasmids, Genome, Bacterial, Computational Biology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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