Evidence map›Paper›PMID 34341535›Full record

ArticleNature biomedical engineering2022

Restoration of dystrophin expression in mice by suppressing a nonsense mutation through the incorporation of unnatural amino acids.

Ningning Shi, Qi Yang, Haoran Zhang, Jiaqi Lu, Haishuang Lin, Xu Yang, Aikedan Abulimiti, Jialu Cheng, Yu Wang, Le Tong and 4 more

Abstract read
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In one paragraph

Article in Nature biomedical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

33 citing papers in PubMed, 49 citations in OpenAlex.

  1. Review
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  17. Article
  18. Review
  19. Review
  20. Suppressor tRNA in gene therapy.Science China. Life sciences · 2024
    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

14 authors at 1 institution in 1 country.

Ningning Shi *State Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Qi Yang *State Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Haoran Zhang *State Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Jiaqi LuState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Haishuang LinState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Xu YangState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Aikedan AbulimitiState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Jialu ChengState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Yu WangState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Le TongState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0002-5298-8255
Tianchang WangState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Xiaodong ZhangState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Hongmin ChenState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Qing XiaState Key Laboratory of Natural and Biomimetic Drugs, Department of Chemical Biology, School of Pharmaceutical Sciences, Peking University, Beijing, China. xqing@hsc.pku.edu.cn.ORCID http://orcid.org/0000-0002-8191-7712
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Approximately 11% of monogenic diseases involve nonsense mutations that are caused by premature termination codons. These codons can in principle be read-through via the site-specific incorporation of unnatural amino acids to generate full-length proteins with minimal loss of function. Here we report that aminoacyl-tRNA-synthase-tRNA pairs specific for the desired unnatural amino acids can be used to read through a nonsense mutation in the dystrophin gene. We show partial restoration of dystrophin expression in differentiated primary myoblasts (from a mdx mouse model and a patient with Duchenne muscular dystrophy), and restoration of muscle function in two mouse models: mdx mice, via viral delivery of the engineered tRNA-synthase-tRNA pair intraperitoneally or intramuscularly and of the associated unnatural amino acid intraperitoneally; and mice produced by crossing mdx mice and transgenic mice with a chromosomally integrated pair, via intraperitoneal delivery of the unnatural amino acid. The incorporation of unnatural amino acids to restore endogenous protein expression could be explored for therapeutic use.

Indexed as

DystrophinMuscular Dystrophy, DuchenneAmino AcidsAnimalsCodon, NonsenseHumansMiceMice, Inbred mdxAmino AcidsCodon, NonsenseDystrophin

Identifiers

PMID34341535
OpenAlexW3192294857

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.