Genome-Scale Metabolic Modelling of Indigenous Lactic Acid Bacteria from Nigerian Fermented Foods for Starter Culture Design

Lactic acid bacteria indigenous to Nigerian fermented foods possess metabolic properties adapted to local substrate composition and processing conditions, making them potentially superior starter cultures for the standardisation of traditional fermented food production. Genome-scale metabolic modelling provides a systems biology framework for rationally designing starter cultures with targeted metabolic capabilities. This study develops genome-scale metabolic models for three lactic acid bacteria strains, specifically Lactobacillus fermentum NIG1, Leuconostoc mesenteroides NIG3, and Pediococcus pentosaceus NIG7, isolated from traditional fermented sorghum and cassava products in Kano and Enugu States. Genome sequencing was conducted using Illumina short-read and Oxford Nanopore long-read platforms with hybrid assembly. Draft genome-scale models were reconstructed using the ModelSEED platform and subjected to gap-filling and curation using experimental growth phenotype data from Biolog phenotype microarray analysis. Flux balance analysis was applied to predict growth rates, by-product profiles, and stress tolerance under varying substrate and environmental conditions. The models were used to identify metabolic engineering targets for improved lactic acid production and anti-fungal compound synthesis. Selected predicted phenotypes were validated by shake-flask fermentation experiments on sorghum and cassava hydrolysate substrates. The study represents the first genome-scale metabolic modelling effort for lactic acid bacteria strains isolated from Nigerian food fermentation systems, contributing both the annotated genome sequences and validated metabolic models as public datasets. Findings advance starter culture design for the Nigerian fermented food industry. Keywords: genome-scale metabolic modelling, lactic acid bacteria, fermented foods, starter culture, systems biology