Evidence map›Paper›PMID 41333073›Full record

ArticleSynthetic and systems biotechnology2026

Engineering ω-transaminase for efficient dihydroxyacetone transamination in serinol biosynthesis starting from methanol.

Ya Wu, Chonghao Guo, Lizhen Deng, Derui Zhang, Yutong Bie, Yuxin He, Gen Lu, Shewei Hu, Ruiqi Zeng, Zeyang Li and 2 more

Abstract read
In one paragraph

Article in Synthetic and systems biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Ya WuKey Laboratory of Pesticide & Chemical Biology of Ministry of Education, Hubei Key Laboratory of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, 152 Luoyu Road, Wuhan, 430079, China.
Chonghao GuoInstitute of Resource Biology and Biotechnology, Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, China.
Lizhen DengInstitute of Resource Biology and Biotechnology, Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, China.
Derui ZhangInstitute of Resource Biology and Biotechnology, Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, China.
Yutong BieInstitute of Resource Biology and Biotechnology, Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, China.
Yuxin HeInstitute of Resource Biology and Biotechnology, Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, China.
Gen LuInstitute of Resource Biology and Biotechnology, Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, China.
Shewei HuDepartment of Biology and Food Engineering, Bozhou University, Bozhou, 236800, China.
Ruiqi ZengInstitute of Resource Biology and Biotechnology, Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, China.
Zeyang LiInstitute of Resource Biology and Biotechnology, Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, China.
Xudong XuKey Laboratory of Pesticide & Chemical Biology of Ministry of Education, Hubei Key Laboratory of Genetic Regulation and Integrative Biology, School of Life Sciences, Central China Normal University, 152 Luoyu Road, Wuhan, 430079, China.
Longjiang YuInstitute of Resource Biology and Biotechnology, Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Serinol (2-amino-1,3-propanediol) is an important pharmaceutical intermediate, but conventional chemical or microbial routes are hampered by high energy demand, product toxicity, or complex regulation. Here, we report a modular cell-free enzyme cascade, termed the methanol-to-serinol pathway (MSP), that efficiently converts methanol-a low-cost C1 feedstock-into serinol with high carbon yield. The cascade comprises two modules: Module 1 employs an alcohol oxidase and an engineered formolase to generate dihydroxyacetone (DHA), while Module 2 uses a tailored ω-transaminase for direct one-step amination. To overcome the rate-limiting DHA amination, we applied an "ALF" scanning strategy and identified a triple-mutant Cv-ωTA (Y153F/Y168F/C418F) with 6.3-fold higher specific activity than the wild type. Fitness landscape analysis revealed strong non-additive interactions, highlighting the synergistic effect of these three mutations. Molecular dynamics simulations revealed structural changes underlying the activity boost. By incorporating a pyruvate-removal system to drive the equilibrium toward product formation, the integrated cascade achieved 43.86 mM (4 g/L) serinol from 150 mM methanol in 7 h, corresponding to 87.7 % carbon yield and a productivity of 0.57 g/L/h. This work establishes a carbon-efficient route for serinol biosynthesis and provides a generalizable strategy for sustainable C1 biomanufacturing.

Indexed as

C1 biomanufacturingEpistasis analysisMolecular simulationMultienzyme cascade catalysisSerinolTransaminase engineering

Identifiers

PMID41333073
PMCPMC12666128

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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.