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

Genome-scale metabolic models (GEMs) guide strain engineering and process optimization, improving fermentation performance across microbial hosts and production contexts.

• Why it matters: Optimizing microbial fermentation is crucial for sustainable biomanufacturing, but current models vary in predictive accuracy and validation, limiting industrial application.
• What they did: The review discusses automated reconstruction tools, quality-control frameworks, and validation methods, highlighting recent advances like machine learning and community modeling involving multiple microbial species.
• The result: GEMs enable rational target identification and substrate utilization improvements, with ongoing challenges in model accuracy and validation, but continued progress promises to strengthen their industrial role.