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

Area of Science:

• Microbial Biotechnology
• Metabolic Engineering
• Synthetic Biology

Background:

• Spinosad is a potent bioinsecticide derived from Saccharopolyspora spinosa.
• Enhancing spinosad production is challenging due to complex metabolic regulation and genetic manipulation difficulties.
• Existing strategies for improving spinosad yield are often insufficient for comprehensive metabolic engineering.

Purpose of the Study:

• To develop a genome-scale metabolic model (GEM) for Sa. spinosa NHF132.
• To dissect spinosad biosynthesis pathways and identify targets for metabolic engineering.
• To systematically evaluate and integrate strategies for significantly increasing spinosad production.

Main Methods:

• Construction and analysis of a genome-scale metabolic model for Sa. spinosa.
• Identification of key precursors, enzymes, and competing pathways in spinosad biosynthesis.
• Integration of metabolic engineering strategies including precursor overexpression, gene cluster amplification, and chassis optimization.

Main Results:

• A GEM for Sa. spinosa NHF132 was successfully developed.
• Model-guided engineering led to a 553.3% increase in spinosad titer (1816.8 mg L⁻¹).
• Significant improvements in spinosad yield and product proportion were achieved in the engineered strain.

Conclusions:

• A model-driven framework effectively enhances the production of complex secondary metabolites in actinomycetes.
• This approach provides a powerful tool for optimizing spinosad biosynthesis.
• The findings offer valuable insights for engineering other complex natural product pathways.