Genome-scale metabolic models enable predictive strain and process design for sustainable biomanufacturing.

Genome-scale metabolic models (GEMs) improve microbial strain and process design, achieving up to 50% better fermentation performance across diverse biomanufacturing contexts.

• Why it matters: Optimizing microbial fermentation is crucial for sustainable biomanufacturing, but current models often lack predictive accuracy and scalability, limiting industrial application.
• What they did: The review covers automated reconstruction tools, validation methods, and how GEMs guide strain engineering and process optimization through computational and experimental validation, including recent machine learning advances.
• The result: Enhanced GEMs enable more precise target identification and process improvements, paving the way for more efficient, scalable, and sustainable bioproduction systems.