Evidence map›Paper›PMID 39068154›Full record

ArticleNature communications2024

Guide RNA structure design enables combinatorial CRISPRa programs for biosynthetic profiling.

Jason Fontana, David Sparkman-Yager, Ian Faulkner, Ryan Cardiff, Cholpisit Kiattisewee, Aria Walls, Tommy G Primo, Patrick C Kinnunen, Hector Garcia Martin, Jesse G Zalatan and 1 more

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

11 authors.

Jason Fontana *Molecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA.ORCID 0000-0003-4758-6494
David Sparkman-Yager *Molecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA.
Ian Faulkner *Molecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA.ORCID 0009-0009-7715-0908
Ryan CardiffMolecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA.ORCID 0009-0001-0530-9010
Cholpisit KiattiseweeMolecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA.ORCID 0000-0002-6351-7352
Aria WallsMolecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA.ORCID 0000-0002-7530-8478
Tommy G PrimoMolecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA.ORCID 0009-0002-4489-4168
Patrick C KinnunenBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID 0000-0002-1741-2867
Hector Garcia MartinBiological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID 0000-0002-4556-9685
Jesse G ZalatanMolecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA. zalatan@uw.edu.ORCID 0000-0002-1458-0654
James M CarothersMolecular Engineering & Sciences Institute and Center for Synthetic Biology, University of Washington, Seattle, WA, USA. jcaroth@uw.edu.ORCID 0000-0001-6728-7833

Funding

National Science Foundation (NSF) MCB 1817623, MCB 2032794, CBET 1844152U.S. Department of Energy (DOE) DE-EE0008927, DE-SC0023091
6 · The paper itself

Abstract

Engineering metabolism to efficiently produce chemicals from multi-step pathways requires optimizing multi-gene expression programs to achieve enzyme balance. CRISPR-Cas transcriptional control systems are emerging as important tools for programming multi-gene expression, but poor predictability of guide RNA folding can disrupt expression control. Here, we correlate efficacy of modified guide RNAs (scRNAs) for CRISPR activation (CRISPRa) in E. coli with a computational kinetic parameter describing scRNA folding rate into the active structure (r

Indexed as

CRISPR-Cas SystemsEscherichia coliRNA, Guide, CRISPR-Cas SystemsBiosynthetic PathwaysGene Expression Regulation, BacterialHumansMetabolic EngineeringPromoter Regions, GeneticRNA FoldingRNA, Guide, CRISPR-Cas Systems

Identifiers

PMID39068154
PMCPMC11283517

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.