Abstract

Lacticaseibacillus rhamnosus GG (LGG) is an important gut commensal bacterial strain that has been extensively studied in both industrial and health settings. Despite its long history of study, a high-quality genome-scale metabolic network model (GEM) for LGG has yet to be reconstructed. Only automatically-generated draft models have been published, which have notoriously limited functional accuracy. Furthermore, comprehensive nutrient requirements have not been established for well-controlled in vitro study. Here we present the first curated GEM for LGG using a new approach for reconstruction and validation that leverages multiple automatically-generated draft models, applied study literature, and high-throughput defined media experiments. In addition, our results include a series of chemically defined media, extensive single-component nutrient dropout growth data, insights from in silico and in vitro experiments into major secretion products lactate and indole-3-carboxaldehyde, a minimal medium and in silico characterization of LGG's nutrient requirements. Our approach for developing interdisciplinary research tools for LGG metabolism comprises a new framework that could be applied to many understudied microorganisms, particularly useful in studying bacteria within the human microbiome.