Evidence map›Paper›PMID 39384754›Full record

ArticleNature communications2024

High-resolution and programmable RNA-IN and RNA-OUT genetic circuit in living mammalian cells.

Min Zhang, Xue Zhang, Yongyue Xu, Yanhui Xiang, Bo Zhang, Zhen Xie, Qiong Wu, Chunbo Lou

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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Programming Next-Generation Synthetic Biosensors by Genetic Circuit Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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

8 authors.

Min Zhang *MOE Key Laboratory of Bioinformatics, Center for Synthetic and System Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Xue Zhang *MOE Key Laboratory of Bioinformatics, Center for Synthetic and System Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.ORCID 0009-0009-8575-4189
Yongyue XuMOE Key Laboratory of Bioinformatics, Center for Synthetic and System Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Yanhui XiangCenter for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Bo ZhangMOE Key Laboratory of Bioinformatics, Center for Synthetic and System Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Zhen XieMOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and Systems Biology, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, 100084, China.ORCID 0000-0001-8798-9592
Qiong WuMOE Key Laboratory of Bioinformatics, Center for Synthetic and System Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China. wuqiong@mail.tsinghua.edu.cn.
Chunbo LouCenter for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China. cb.lou@siat.ac.cn.ORCID 0000-0002-7941-6038

Funding

Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2018YFA0900100
6 · The paper itself

Abstract

RNAs and their encoded proteins intricately regulate diverse cell types and states within the human body. Dysregulated RNA expressions or mutations can lead to various diseased cell states, including tumorigenesis. Detecting and manipulating these endogenous RNAs offers significant promise for restoring healthy cell states and targeting tumors both in research and clinical contexts. This study presents an RNA-IN and RNA-OUT genetic circuit capable dynamically sensing and manipulating any RNA target in a programmable manner. The RNA-IN module employes a programmable CRISPR-associated protease (CASP) complex for RNA detection, while the RNA-OUT module utilizes an engineered protease-responsive dCas9-VPR activator. Additionally, the CASP module can detect point mutations by harnessing an uncovered dual-nucleotide synergistic switching effect within the CASP complex, resulting in the amplification of point-mutation signals from initially undetectable levels (1.5-fold) to a remarkable 94-fold. We successfully showcase the circuit's ability to rewire endogenous RNA-IN signals to activate endogenous progesterone biosynthesis pathway, dynamically monitor adipogenic differentiation of mesenchymal stem cells (MSCs) and the epithelial-to-mesenchmal trans-differentiation, as well as selective killing of tumor cells. The programmable RNA-IN and RNA-OUT circuit exhibits tremendous potential for applications in gene therapy, biosensing and design of synthetic regulatory networks.

Indexed as

CRISPR-Cas SystemsGene Regulatory NetworksMesenchymal Stem CellsRNAAnimalsCell DifferentiationHEK293 CellsHumansPoint MutationRNA

Identifiers

PMID39384754
PMCPMC11464720

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.