Model‐Guided Systematic Metabolic Engineering for Enhanced Spinosad Biosynthesis in <i>Saccharopolyspora spinosa</i> NHF132

Spinosad (a mixture of spinosyns A and D) is a macrocyclic lactone green bioinsecticide produced by Saccharopolyspora spinosa. It is known for its high efficiency, low toxicity, and broad-spectrum activity. Although numerous strategies have been employed to enhance spinosad production, intricate regulation of secondary metabolism and inefficient genetic manipulation impede systematic and comprehensive metabolic engineering in this spinosad-producing strain. In this study, a genome-scale metabolic model (GEM) for Sa. spinosa NHF132 is developed to dissect the intricate secondary metabolic pathways of spinosad biosynthesis, analyzing interactions among precursors, key enzymes, and competing or bypass pathways. Guided by the model, the impact of rhamnose precursor overexpression, gene cluster amplification, short-chain acyl-CoA enhancement, and chassis optimization on spinosad production is systematically evaluated. By integrating these metabolic engineering strategies, engineered strain NHF132-BAC-SP43-NCM achieved a spinosad titer of 1816.8 mg L<sup>-1</sup>, a 553.3% increase over the starting strain, with substantial improvements in yield and product proportion. The model-driven framework for metabolic engineering of complex secondary metabolites in actinomycetes substantially increased spinosad production and offered valuable insights for other complex natural products.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2025-09-26
DOI
https://doi.org/10.1002/advs.202511411
Primary Topic
Microbial Metabolic Engineering and Bioproduction
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Model‐Guided Systematic Metabolic Engineering for Enhanced Spinosad Biosynthesis in Saccharopolyspora spinosa NHF132

Jiagao Cheng, Xiaoqian Zeng, Yuxin Liu, Gao‐Yi Tan et al.
Advanced Science
Microbial Metabolic Engineering and Bioproduction
article

Model‐Guided Systematic Metabolic Engineering for Enhanced Spinosad Biosynthesis in Saccharopolyspora spinosa NHF132

Jiagao Cheng, Xiaoqian Zeng, Yuxin Liu, Gao‐Yi Tan, Shuliu Wang, Qian Zhang, Lixin Zhang, Chengyu Zhang, Yue Jiang, Weishan Wang
article en

Abstract

Spinosad (a mixture of spinosyns A and D) is a macrocyclic lactone green bioinsecticide produced by Saccharopolyspora spinosa. It is known for its high efficiency, low toxicity, and broad-spectrum activity. Although numerous strategies have been employed to enhance spinosad production, intricate regulation of secondary metabolism and inefficient genetic manipulation impede systematic and comprehensive metabolic engineering in this spinosad-producing strain. In this study, a genome-scale metabolic model (GEM) for Sa. spinosa NHF132 is developed to dissect the intricate secondary metabolic pathways of spinosad biosynthesis, analyzing interactions among precursors, key enzymes, and competing or bypass pathways. Guided by the model, the impact of rhamnose precursor overexpression, gene cluster amplification, short-chain acyl-CoA enhancement, and chassis optimization on spinosad production is systematically evaluated. By integrating these metabolic engineering strategies, engineered strain NHF132-BAC-SP43-NCM achieved a spinosad titer of 1816.8 mg L<sup>-1</sup>, a 553.3% increase over the starting strain, with substantial improvements in yield and product proportion. The model-driven framework for metabolic engineering of complex secondary metabolites in actinomycetes substantially increased spinosad production and offered valuable insights for other complex natural products.

Advanced ScienceVol. 12(47)
East China University of Science and Technology (CN), Institute of Mechanics (CN)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, Shanghai Normal University, Shanghai Jiao Tong University, Bundesanstalt für Arbeitsschutz und Arbeitsmedizin, Higher Education Discipline Innovation Project
Openalex Percentile: Top 77%
Microbial Metabolic Engineering and Bioproduction
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.