Evidence map›Paper›PMID 33436562›Full record

ArticleNature communications2021

Multiplexed characterization of rationally designed promoter architectures deconstructs combinatorial logic for IPTG-inducible systems.

Timothy C Yu, Winnie L Liu, Marcia S Brinck, Jessica E Davis, Jeremy Shek, Grace Bower, Tal Einav, Kimberly D Insigne, Rob Phillips, Sriram Kosuri and 1 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
9.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 52 citations in OpenAlex.

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  11. Targeted mutagenesis of specific genomic DNA sequences in animals for thebioRxiv : the preprint server for biology · 2024
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  14. Flexibility and sensitivity in gene regulation out of equilibrium.Proceedings of the National Academy of Sciences of the United States of America · 2024
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  15. Review
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  17. Scalable design of orthogonal DNA barcode libraries.Nature computational science · 2024
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  20. Fine-Tuning Gene Expression in Bacteria by Synthetic Promoters.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 1 country.

Timothy C YuDepartment of Bioengineering, University of California, Los Angeles, CA, 90095, USA.
Winnie L LiuDepartment of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA, 90095, USA.
Marcia S BrinckDepartment of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, CA, 90095, USA.ORCID 0000-0001-8149-0555
Jessica E DavisDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA, 90095, USA.
Jeremy ShekDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA, 90095, USA.ORCID 0000-0002-5419-060X
Grace BowerDepartment of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA, 90095, USA.
Tal EinavDepartment of Physics, California Institute of Technology, Pasadena, CA, 91125, USA.ORCID 0000-0003-0777-1193
Kimberly D InsigneBioinformatics Interdepartmental Graduate Program, University of California, Los Angeles, CA, 90095, USA.
Rob PhillipsDepartment of Physics, California Institute of Technology, Pasadena, CA, 91125, USA.
Sriram KosuriDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA, 90095, USA. sri@ucla.edu.ORCID 0000-0002-4661-0600
Guillaume UrtechoMolecular Biology Interdepartmental Doctoral Program, University of California, Los Angeles, CA, 90095, USA. gurtecho@ucla.edu.ORCID 0000-0003-1045-1721
University of California, Los Angeles · USCalifornia Institute of Technology · USQB3 · US

Funding

UCLA NIGMS T32 Program AssessmentT32GM007185 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI TORRES, JORGE · 1985 to 2020
$21.7M
REVERSE GENOMICS OF REGULATORY ELEMENTS GOVERNING SPLICINGDP2GM114829 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KOSURI, SRIRAM · 2014 to 2014
$2.3M
NIGMS NIH HHS DP2 GM114829NIGMS NIH HHS T32 GM007185
6 · The paper itself

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.

Indexed as

LogicPromoter Regions, GeneticBinding SitesBiophysical PhenomenaDNA-Directed RNA PolymerasesEscherichia coliFluorescenceGenes, ReporterIsopropyl ThiogalactosideMutationOperator Regions, GeneticProtein BindingReproducibility of ResultsThermodynamicsTranscription FactorsDNA-Directed RNA PolymerasesIsopropyl ThiogalactosideTranscription Factors

Identifiers

PMID33436562
PMCPMC7804116
OpenAlexW3118661275

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.