Nutrient control enables metabolic reconstruction of Lacticaseibacillus rhamnosus GG and analysis of secretions.

A first manually curated genome-scale metabolic model for Lacticaseibacillus rhamnosus GG (LGG) was reconstructed and validated, enabling accurate simulation of its nutrient use and secretions.

• Why it matters: Reliable tools to simulate LGG metabolism and define its nutrient requirements are lacking, limiting interpretation of how this widely used gut commensal grows and produces bioactive compounds in controlled studies.
• What they did: The authors built a curated GEM by integrating multiple draft models, study literature, and high-throughput defined-media experiments, then validated it with chemically defined media and extensive single-component nutrient dropout growth data.
• The result: In silico and in vitro analyses linked LGG growth and secretion products to nutrient availability, including lactate and indole-3-carboxaldehyde, and provided a minimal medium and in silico nutrient requirement characterization.