Evidence map›Paper›PMID 42572581›Full record

ArticleSynthetic and systems biotechnology2027

An orthogonal transcription system enables high-efficiency rescue of measles virus-based vaccine vectors against multiple pathogens.

Zihan Ma, Weijun Wang, Qiuli Lou, Hai Jiang, Yanhui Xiang, Wenhui Zhang, Xue Tian, Yu Fan, Wen Yin, Chunbo Lou

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Synthetic and systems biotechnology, 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Zihan MaState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic, Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 510855, China.
Weijun WangState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic, Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 510855, China.
Qiuli LouState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic, Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 510855, China.
Hai JiangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Yanhui XiangState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic, Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 510855, China.
Wenhui ZhangState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic, Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 510855, China.
Xue TianState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic, Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 510855, China.
Yu FanNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Wen YinState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic, Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 510855, China.
Chunbo LouState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic, Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 510855, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recombinant measles virus (rMeV) vectors are promising platforms for vaccine development against emerging infectious diseases due to their safety, stability, and potent immunogenicity. However, conventional rMeV rescue systems frequently exhibit low efficiency, thereby constraining their scalability and throughput. In this study, we developed a modular, helper-virus-free and high-efficiency rescue platform based on an orthogonal transcription system utilizing orthogonal promoters and engineered RNA polymerases fused to an mRNA capping enzyme. This innovative system facilitated robust cytoplasmic manufacture of both genomic and auxiliary components, eliminating the need for helper virus co-infection (such as modified vaccinia virus) and enhancing rescue efficiency by more than 50-fold relative to traditional rescue approaches. Utilizing this technology, we demonstrated the versatility of the platform by successfully generating six rMeV-based vaccine antigen candidates from influenza virus,

Indexed as

Helper-virus-free rescueOrthogonal transcription systemRecombinant measles virusReverse geneticsVaccine vectors

Identifiers

PMID42572581
PMCPMC13453018

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Registered trials

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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.