Evidence map›Paper›PMID 36017994›Full record

ArticleACS synthetic biology2022

Overcoming Leak Sensitivity in CRISPRi Circuits Using Antisense RNA Sequestration and Regulatory Feedback.

David A Specht, Louis B Cortes, Guillaume Lambert

Open access · hybridAbstract read
In one paragraph

Article in ACS synthetic biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 29% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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  7. 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
    Article
  8. 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

3 authors at 1 institution in 1 country.

David A SpechtApplied Physics, Cornell University, Ithaca, New York 14853, United States.ORCID 0000-0001-6094-5629
Louis B CortesApplied Physics, Cornell University, Ithaca, New York 14853, United States.ORCID 0000-0003-3447-8769
Guillaume LambertApplied Physics, Cornell University, Ithaca, New York 14853, United States.ORCID 0000-0003-4779-287X
Cornell University · US

Funding

Metabolic Control of Persistence in Individual BacteriaR35GM133759 · NIGMS · CORNELL UNIVERSITY · PI LAMBERT, GUILLAUME · 2019 to 2022
$1.6M
NIGMS NIH HHS R35 GM133759
6 · The paper itself

Abstract

The controlled binding of the catalytically dead CRISPR nuclease (dCas) to DNA can be used to create complex, programmable transcriptional genetic circuits, a fundamental goal of synthetic biology. This approach, called CRISPR interference (CRISPRi), is advantageous over existing methods because the programmable nature of CRISPR proteins in principle enables the simultaneous regulation of many different targets without crosstalk. However, the performance of dCas-based genetic circuits is limited by both the sensitivity to leaky repression within CRISPRi logic gates and retroactive effects due to a shared pool of dCas proteins. By utilizing antisense RNAs (asRNAs) to sequester gRNA transcripts as well as CRISPRi feedback to self-regulate asRNA production, we demonstrate a mechanism that suppresses unwanted repression by CRISPRi and improves logical gene circuit function in

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsRNA, Guide, CRISPR-Cas SystemsCRISPR-Cas SystemsDNAEscherichia coliFeedbackRNA, AntisenseDNARNA, AntisenseRNA, Guide, CRISPR-Cas SystemsantisensecircuitCRISPRiinvertersequestrationsingle-cell

Identifiers

PMID36017994
PMCPMC9486968
OpenAlexW4293115787

What OpenQuestion holds

Textmetadata
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.