A Refined Adaptive Laboratory Evolution Strategy With Biosensor‐Assisted Selection Resolves the Tolerance–Efficiency Trade‐Off in Toxic Chemical Biosynthesis

Enhancing microbial tolerance to target chemicals through conventional adaptive laboratory evolution (ALE) is time-consuming, labor-intensive, and further constrained by the challenge of balancing improved tolerance with maintaining optimal biosynthetic efficiency. Here, this work proposes a refined ALE strategy that combines initial mutagenesis with an automated microdroplet cultivation (MMC) system, thereby expediting the acquisition of tolerance phenotypes. Integrating a biosensor-assisted high-throughput screening platform enables identification of strains exhibiting advantageous "win-win" phenotypes, characterized by simultaneous improvements in both tolerance and biosynthetic capacity. Using E. coli for the biosynthesis of 3-hydroxypropionic acid (3-HP) as a model system, this work rapidly evolves strains capable of tolerating 720 mM 3-HP within 12 days. Leveraging a newly developed and validated 3-HP-responsive biosensor, this work efficiently screens and isolates superior strains. The top-performing strain produced 86.3 g L<sup>-1</sup> 3-HP with a yield of 0.82 mol mol<sup>-1</sup> glycerol. Transcriptomic analysis provide insights into mechanisms underlying this "win-win" phenotype. Collectively, this study establishes an effective ALE framework for accelerating the development of microbial chassis tailored for high-efficiency biochemical production.

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Publication Details

Journal
Advanced Science
Published
2025-08-12
DOI
https://doi.org/10.1002/advs.202507740
Citations
3
Primary Topic
Microbial Metabolic Engineering and Bioproduction
Type
article
Field-Weighted Citation Impact
2.42

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article

A Refined Adaptive Laboratory Evolution Strategy With Biosensor‐Assisted Selection Resolves the Tolerance–Efficiency Trade‐Off in Toxic Chemical Biosynthesis

Hossain M. Zabed, Guoyan Zhang, Xinrui Tang, Xianghui Qi et al.
3 citations
Advanced Science
Microbial Metabolic Engineering and Bioproduction
2.42
article

A Refined Adaptive Laboratory Evolution Strategy With Biosensor‐Assisted Selection Resolves the Tolerance–Efficiency Trade‐Off in Toxic Chemical Biosynthesis

Hossain M. Zabed, Guoyan Zhang, Xinrui Tang, Xianghui Qi, Yufei Zhang, Jia Li, Junhua Yun, Yuehui Tian
article en
3 citations

Abstract

Enhancing microbial tolerance to target chemicals through conventional adaptive laboratory evolution (ALE) is time-consuming, labor-intensive, and further constrained by the challenge of balancing improved tolerance with maintaining optimal biosynthetic efficiency. Here, this work proposes a refined ALE strategy that combines initial mutagenesis with an automated microdroplet cultivation (MMC) system, thereby expediting the acquisition of tolerance phenotypes. Integrating a biosensor-assisted high-throughput screening platform enables identification of strains exhibiting advantageous "win-win" phenotypes, characterized by simultaneous improvements in both tolerance and biosynthetic capacity. Using E. coli for the biosynthesis of 3-hydroxypropionic acid (3-HP) as a model system, this work rapidly evolves strains capable of tolerating 720 mM 3-HP within 12 days. Leveraging a newly developed and validated 3-HP-responsive biosensor, this work efficiently screens and isolates superior strains. The top-performing strain produced 86.3 g L<sup>-1</sup> 3-HP with a yield of 0.82 mol mol<sup>-1</sup> glycerol. Transcriptomic analysis provide insights into mechanisms underlying this "win-win" phenotype. Collectively, this study establishes an effective ALE framework for accelerating the development of microbial chassis tailored for high-efficiency biochemical production.

Advanced ScienceVol. 12(41)
Jiangsu University (CN), Key Laboratory of Guangdong Province (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 11%
Microbial Metabolic Engineering and Bioproduction
2.42
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