OptEnvelope: A target point guided method for growth-coupled production using knockouts.

Area of Science:

• Biotechnology and metabolic engineering
• Computational systems biology
• Synthetic biology

Background:

• Optimizing metabolic pathways for simultaneous biomass growth and target metabolite production is crucial but challenging.
• Current methods for identifying gene knockout strategies often lack efficiency and comprehensive analysis of the solution space.

Purpose of the Study:

• To present OptEnvelope, a novel computational method for determining optimal gene knockout strategies.
• To identify minimal reaction sets that couple biomass growth with high metabolite production.
• To evaluate the production capabilities of E. coli and S. cerevisiae for specific metabolites.

Main Methods:

• Developed OptEnvelope, a three-step method using mixed-integer linear programming to define the feasible solution space (envelope).
• Identified minimal active reactions by removing inactive ones, then reduced knockouts while preserving the production envelope.
• Evaluated different target points to find envelopes with higher production rates or fewer knockouts, with an option to limit maximal knockouts.

Main Results:

• OptEnvelope successfully identified multiple strong coupled envelopes in the desired solution space for E. coli and S. cerevisiae.
• E. coli demonstrated higher suitability for acetate and succinate production, while S. cerevisiae was better for glycerol.
• Both microbes are suitable for ethanol production, with E. coli requiring more knockouts.

Conclusions:

• OptEnvelope is an effective tool for metabolic engineering, enabling the discovery of efficient gene knockout strategies.
• The method provides valuable insights into the metabolic capabilities of industrial microorganisms for targeted overproduction.
• Experimental validation supports some of the proposed gene deletions for enhanced metabolite yields.