Evidence map›Paper›PMID 31552424›Full record

ArticleNucleic acids research2019

De novo design of programmable inducible promoters.

Xiangyang Liu, Sanjan T P Gupta, Devesh Bhimsaria, Jennifer L Reed, José A Rodríguez-Martínez, Aseem Z Ansari, Srivatsan Raman

Abstract read
In one paragraph

Article in Nucleic acids research, 2019. 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
–field-weighted citation impact
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.

  1. Review
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  11. Deep Learning-Assisted Design of Novel Promoters inAdvanced genetics (Hoboken, N.J.) · 2023
    Article
  12. Review
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  14. Review
  15. Article
  16. Engineering activatable promoters for scalable and multi-input CRISPRa/i circuits.Proceedings of the National Academy of Sciences of the United States of America · 2023
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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

7 authors.

Xiangyang LiuDepartment of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
Sanjan T P GuptaThe Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI 53706, USA.
Devesh BhimsariaDepartment of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
Jennifer L ReedThe Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI 53706, USA.
José A Rodríguez-MartínezDepartment of Biology, University of Puerto Rico-Rio Piedras, San Juan, PR 00925, USA.
Aseem Z AnsariDepartment of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
Srivatsan RamanDepartment of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.

Funding

Understanding molecular rules governing protein allostery by deep mutational scanningDP2GM132682 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI RAMAN, SRIVATSAN · 2018 to 2018
$2.1M
Revealing Masked Specificities of Human Nuclear ReceptorsR01GM120625 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI ANSARI, ASEEM Z · 2016 to 2019
$1.7M
NIGMS NIH HHS DP2 GM132682NIGMS NIH HHS R01 GM120625
6 · The paper itself

Abstract

Ligand-responsive allosteric transcription factors (aTF) play a vital role in genetic circuits and high-throughput screening because they transduce biochemical signals into gene expression changes. Programmable control of gene expression from aTF-regulated promoter is important because different downstream effector genes function optimally at different expression levels. However, tuning gene expression of native promoters is difficult due to complex layers of homeostatic regulation encoded within them. We engineered synthetic promoters de novo by embedding operator sites with varying affinities and radically reshaped binding preferences within a minimal, constitutive Escherichia coli promoter. Multiplexed cell-based screening of promoters for three TetR-like aTFs generated with this approach gave rich diversity of gene expression levels, dynamic ranges and ligand sensitivities and were 50- to 100-fold more active over their respective native promoters. Machine learning on our dataset revealed that relative position of the core motif and bases flanking the core motif play an important role in modulating induction response. Our generalized approach yields customizable and programmable aTF-regulated promoters for engineering cellular pathways and enables the discovery of new small molecule biosensors.

Indexed as

Transcription, GeneticAllosteric RegulationEscherichia coliGene Expression RegulationLigandsMetabolic EngineeringPromoter Regions, GeneticSynthetic BiologyTranscription FactorsLigandsTranscription Factors

Identifiers

PMID31552424
PMCPMC6821364

What OpenQuestion holds

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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.