L-lactate production in engineered Saccharomyces cerevisiae using a multistage multiobjective automated design...

Area of Science:

• Biotechnology and Metabolic Engineering
• Synthetic Biology
• Polymer Science

Background:

• Petrochemical-based polymers contribute to environmental concerns.
• Renewable feedstocks and microbial conversions offer sustainable alternatives.
• Lactic acid (LA) is crucial for biodegradable plastics, driving research in microbial production.

Purpose of the Study:

• To computationally maximize lactic acid (LA) production yield in Saccharomyces cerevisiae.
• To investigate the impact of various metabolic engineering strategies on yeast LA production.
• To compare aerobic and anaerobic conditions for enhanced LA biosynthesis.

Main Methods:

• Utilized Flux Balance Analysis (FBA) on the S. cerevisiae 8.3 metabolic model.
• Employed evolutionary algorithms for automated metabolic engineering (gene knock-in/out, regulation, medium optimization).
• Developed a postprocessing methodology to analyze genetic manipulation outcomes.

Main Results:

• Identified promising genetic and metabolic manipulations for increased LA production.
• Demonstrated the effectiveness of in silico engineering strategies in selecting optimal modifications.
• Showcased the potential for developing competitive yeast strains for sustainable chemical production.

Conclusions:

• The developed computational approach successfully identifies key genetic targets for enhancing microbial LA production.
• This method facilitates the design of custom microorganisms for sustainable chemical synthesis.
• The study paves the way for more efficient and environmentally friendly bioprocesses.