Evidence map›Paper›PMID 31548547›Full record

ArticleNature communications2019

Massively parallel RNA device engineering in mammalian cells with RNA-Seq.

Joy S Xiang, Matias Kaplan, Peter Dykstra, Michaela Hinks, Maureen McKeague, Christina D Smolke

Abstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

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  15. Synthetic Gene Circuits for Regulation of Next-Generation Cell-Based Therapeutics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  16. Article
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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

6 authors.

Joy S XiangDepartment of Bioengineering, 443 Via Ortega, MC 4245, Stanford University, Stanford, CA, 94305, USA.
Matias KaplanDepartment of Bioengineering, 443 Via Ortega, MC 4245, Stanford University, Stanford, CA, 94305, USA.
Peter DykstraDepartment of Bioengineering, 443 Via Ortega, MC 4245, Stanford University, Stanford, CA, 94305, USA.ORCID http://orcid.org/0000-0002-2626-7104
Michaela HinksDepartment of Bioengineering, 443 Via Ortega, MC 4245, Stanford University, Stanford, CA, 94305, USA.
Maureen McKeagueDepartment of Pharmacology and Therapeutics, McGill University, 3655 Prom. Sir-William-Osler, Montreal, Quebec, H3G 1Y6, Canada.
Christina D SmolkeDepartment of Bioengineering, 443 Via Ortega, MC 4245, Stanford University, Stanford, CA, 94305, USA. csmolke@stanford.edu.

Funding

Frameworks for programming ligand-responsive RNA regulatory systemsR01GM086663 · NIGMS · STANFORD UNIVERSITY · PI ENDY, DREW · 2009 to 2024
$3.7M
NIGMS NIH HHS R01 GM086663
6 · The paper itself

Abstract

Synthetic RNA-based genetic devices dynamically control a wide range of gene-regulatory processes across diverse cell types. However, the limited throughput of quantitative assays in mammalian cells has hindered fast iteration and interrogation of sequence space needed to identify new RNA devices. Here we report developing a quantitative, rapid and high-throughput mammalian cell-based RNA-Seq assay to efficiently engineer RNA devices. We identify new ribozyme-based RNA devices that respond to theophylline, hypoxanthine, cyclic-di-GMP, and folinic acid from libraries of ~22,700 sequences in total. The small molecule responsive devices exhibit low basal expression and high activation ratios, significantly expanding our toolset of highly functional ribozyme switches. The large datasets obtained further provide conserved sequence and structure motifs that may be used for rationally guided design. The RNA-Seq approach offers a generally applicable strategy for developing broad classes of RNA devices, thereby advancing the engineering of genetic devices for mammalian systems.

Indexed as

AnimalsGene Regulatory NetworksGenetic EngineeringHEK293 CellsHumansMammalsNucleotide MotifsRNA, CatalyticRNA-SeqSynthetic BiologyRNA, Catalytic

Identifiers

PMID31548547
PMCPMC6757056

What OpenQuestion holds

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LicenceCC BY
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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.