Evidence map›Paper›PMID 40593783›Full record

ArticleNature communications2025

An orthogonal transcription mutation system generating all transition mutations for accelerated protein evolution in vivo.

Mingwei Shao, Zhongnan Zhang, Xiaofan Jin, Jun Ding, Guo-Qiang Chen

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Combining Electrochemical Reduction with Biosynthesis for Directed Conversion of COAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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

5 authors.

Mingwei ShaoSchool of Life Sciences, Tsinghua University, Beijing, China.ORCID http://orcid.org/0009-0000-7923-8166
Zhongnan ZhangSchool of Life Sciences, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0003-2452-4901
Xiaofan JinSchool of Life Sciences, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0002-5950-5658
Jun DingSchool of Life Sciences, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0002-9448-7408
Guo-Qiang ChenSchool of Life Sciences, Tsinghua University, Beijing, China. chengq@mail.tsinghua.edu.cn.ORCID http://orcid.org/0000-0002-7226-1782

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32130001
6 · The paper itself

Abstract

Targeted mutagenesis systems are critical for protein evolution. Current deaminase-T7 RNA polymerase fusion systems enable gene-specific mutagenesis but remain limited to certain model organisms. Here, we develop an orthogonal transcription mutation system for in vivo hypermutation in both non-model organism Halomonas bluephagenesis and E. coli, achieving >1,500,000-fold increased mutation rates. By fusing deaminases with three phage RNA polymerases, this system uniformly introduces C:G to T:A and A:T to G:C mutations across target genes. The system demonstrates high specificity, minimal off-target effects, and high orthogonality between phage polymerases. We apply this system to rapidly evolve fluorescent proteins, chromoproteins, cytoskeletal proteins, cell division-related proteins, global sigma factor, and the LysE exporter within a single day of the mutagenesis process. Overall, the orthogonal transcription mutation system is a modular and versatile platform that accelerates protein evolution in the shortest period reported so far.

Indexed as

Directed Molecular EvolutionMutationTranscription, GeneticDNA-Directed RNA PolymerasesEscherichia coliEvolution, MolecularMutagenesisViral Proteinsbacteriophage T7 RNA polymeraseDNA-Directed RNA PolymerasesViral Proteins

Identifiers

PMID40593783
PMCPMC12218169

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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.