How are genome-scale metabolic models used for strain engineering?

Genome-scale metabolic models (GEMs) are comprehensive representations of organism metabolism derived from genome annotation. Model construction: automated reconstruction from genome, gap-filling for growth, and manual curation. Applications: flux balance analysis (FBA) predicts flux distributions under constraints, gene essentiality prediction guides knockout targets, strain design algorithms (OptKnock, OptForce) identify engineering strategies, and medium optimization predicts beneficial supplements. Model-guided engineering workflow: identify limiting steps through flux analysis, predict beneficial modifications, implement changes, measure impact, and refine model. Challenges: missing or incorrect annotations, parameter uncertainty, regulatory constraints not captured, and incomplete metabolite data. Integration with omics data improves predictions. GEMs are standard tools for metabolic engineering, enabling systematic rather than trial-and-error approaches.