Evidence map›Paper›PMID 32479612›Full record

ArticleNucleic acids research2020

Orthogonal tuning of gene expression noise using CRISPR-Cas.

Fan Wu, Jiyoung Shim, Ting Gong, Cheemeng Tan

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 36% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Fan WuDepartment of Biomedical Engineering, University of California Davis, Davis, CA 95616, USA.
Jiyoung ShimDepartment of Biomedical Engineering, University of California Davis, Davis, CA 95616, USA.
Ting GongDepartment of Biomedical Engineering, University of California Davis, Davis, CA 95616, USA.
Cheemeng TanDepartment of Biomedical Engineering, University of California Davis, Davis, CA 95616, USA.
University of California, Davis · US

Funding

Modeling heterogeneity of a cancer-signaling cascade using biomimetic cellsR21EB025938 · NIBIB · UNIVERSITY OF CALIFORNIA AT DAVIS · PI TAN, CHEEMENG · 2019 to 2021
$603k
NIBIB NIH HHS R21 EB025938
6 · The paper itself

Abstract

The control of gene expression noise is important for improving drug treatment and the performance of synthetic biological systems. Previous work has tuned gene expression noise by changing the rate of transcription initiation, mRNA degradation, and mRNA translation. However, these methods are invasive: they require changes to the target genetic components. Here, we create an orthogonal system based on CRISPR-dCas9 to tune gene expression noise. Specifically, we modulate the gene expression noise of a reporter gene in Escherichia coli by incorporating CRISPR activation and repression (CRISPRar) simultaneously in a single cell. The CRISPRar uses a single dCas9 that recognizes two different single guide RNAs (sgRNA). We build a library of sgRNA variants with different expression activation and repression strengths. We find that expression noise and mean of a reporter gene can be tuned independently by CRISPRar. Our results suggest that the expression noise is tuned by the competition between two sgRNAs that modulate the binding of RNA polymerase to promoters. The CRISPRar may change how we tune expression noise at the genomic level. Our work has broad impacts on the study of gene functions, phenotypical heterogeneity, and genetic circuit control.

Indexed as

Cloning, MolecularCRISPR-Cas SystemsEscherichia coliGene ExpressionGene Expression Regulation, BacterialGenes, ReporterRNA, Guide, CRISPR-Cas SystemsRNA, Guide, CRISPR-Cas Systems

Identifiers

PMID32479612
PMCPMC7367181
OpenAlexW4255111614

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.