Evidence map›Paper›PMID 41974726›Full record

ArticleNature communications2026

Design of the biosensor-dependent coupling system stabilizes the high-synthesis phenotype of cell factory.

Lei Qin, Bo Yang, Rui Huang, Haocheng Zhang, Qiuyang Li, Xinyi Li, Yingqi Tan, Wentao Sun, Haiyang Jia, Bing Hu and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 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.

Lei Qin *Department of Chemical Engineering, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0002-9089-4348
Bo Yang *SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering, Key Laboratory of Systems Bioengineering, Ministry of Education, School of Chemical Engineering and Technology, Tianjin University, Tianjin, China.ORCID http://orcid.org/0000-0002-8875-3300
Rui Huang *Institute of Biochemical Engineering, School of Chemistry and Chemical Engineering, Key Laboratory of Medical Molecule Science and Pharmaceutical Engineering, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, China.ORCID http://orcid.org/0009-0003-0670-0278
Haocheng ZhangDepartment of Chemical Engineering, Tsinghua University, Beijing, China.
Qiuyang LiInstitute of Biochemical Engineering, School of Chemistry and Chemical Engineering, Key Laboratory of Medical Molecule Science and Pharmaceutical Engineering, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, China.
Xinyi LiInstitute of Biochemical Engineering, School of Chemistry and Chemical Engineering, Key Laboratory of Medical Molecule Science and Pharmaceutical Engineering, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, China.
Yingqi TanDepartment of Chemical Engineering, Tsinghua University, Beijing, China.
Wentao SunDepartment of Chemical Engineering, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0002-3467-501X
Haiyang JiaInstitute of Biochemical Engineering, School of Chemistry and Chemical Engineering, Key Laboratory of Medical Molecule Science and Pharmaceutical Engineering, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, China.ORCID http://orcid.org/0000-0002-8330-5031
Bing HuInstitute of Biochemical Engineering, School of Chemistry and Chemical Engineering, Key Laboratory of Medical Molecule Science and Pharmaceutical Engineering, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, China.ORCID http://orcid.org/0000-0002-9313-9428
Bo LvInstitute of Biochemical Engineering, School of Chemistry and Chemical Engineering, Key Laboratory of Medical Molecule Science and Pharmaceutical Engineering, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, China. lv-b@bit.edu.cn.ORCID http://orcid.org/0000-0001-7879-0741
Chun LiDepartment of Chemical Engineering, Tsinghua University, Beijing, China. lichun@tsinghua.edu.cn.ORCID http://orcid.org/0000-0003-4262-6848

Funding

National Natural Science Foundation of China (National Science Foundation of China) 22138006National Natural Science Foundation of China (National Science Foundation of China) 22178024National Natural Science Foundation of China (National Science Foundation of China) 22278240National Natural Science Foundation of China (National Science Foundation of China) 22478031National Natural Science Foundation of China (National Science Foundation of China) 22478032
6 · The paper itself

Abstract

Microbial cell factories offer a sustainable route to plant-derived natural products, but yield drift and strain degeneration persist. Growth-coupled biosynthesis can continuously enrich high producers, yet specific product-responsive biosensors remain scarce and their population-level effects are unclear. Here, we describe a rapid transcriptome-mining workflow that, as proof-of-concept, delivers yeast biosensors for glycyrrhetinic acid and medicarpin. By fine-tuning PDR5 promoter, we expand the dynamic range of the glycyrrhetinic acid sensor and wire it to an essential gene, establishing a growth-addiction circuit that increases titer by 46.8 % after subculture. Single-cell transcriptome reveals that the evolved strain population exhibits a completely different division of labor compared to the initial strain. Coupling does not eliminate phenotypic heterogeneity; instead, it amplifies a dedicated sub-population marked by discrete transcriptional signatures. Deletion of genes highly expressed in non-producing cells or enrichment of high-producing cell clusters can further boost population-level production. This study provides both a generalizable biosensor-discovery platform and single-cell-guided strategies for stabilizing and optimizing natural-product cell factories.

Indexed as

Biosensing TechniquesSaccharomyces cerevisiaeGene Expression ProfilingGene Expression Regulation, FungalPhenotypePromoter Regions, GeneticSaccharomyces cerevisiae ProteinsSingle-Cell Gene Expression AnalysisTranscriptomeSaccharomyces cerevisiae Proteins

Identifiers

PMID41974726
PMCPMC13247036

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.