Abstract：
Strains across the Lactobacillaceae family form the basis for a trillion-dollar industry. Our understanding of the genomic basis for their key traits is fragmented, however, including the metabolism that is foundational to their industrial uses. Pangenome analysis of publicly available Lactobacillaceae genomes allowed us to generate genome-scale metabolic network reconstructions for 26 species of industrial importance. Their manual curation led to more than 75,000 gene-protein-reaction associations that were deployed to generate 2,446 genome-scale metabolic models. Cross-referencing genomes and known metabolic traits allowed for manual metabolic network curation and validation of the metabolic models. As a result, we provide the first pangenomic basis for metabolism in the Lactobacillaceae family and a collection of predictive computational metabolic models that enable a variety of practical uses.IMPORTANCELactobacillaceae, a bacterial family foundational to a trillion-dollar industry, is increasingly relevant to biosustainability initiatives. Our study, leveraging approximately 2,400 genome sequences, provides a pangenomic analysis of Lactobacillaceae metabolism, creating over 2,400 curated and validated genome-scale models (GEMs). These GEMs successfully predict (i) unique, species-specific metabolic reactions; (ii) niche-enriched reactions that increase organism fitness; (iii) essential media components, offering insights into the global amino acid essentiality of Lactobacillaceae; and (iv) fermentation capabilities across the family, shedding light on the metabolic basis of Lactobacillaceae-based commercial products. This quantitative understanding of Lactobacillaceae metabolic properties and their genomic basis will have profound implications for the food industry and biosustainability, offering new insights and tools for strain selection and manipulation.
摘要：
乳杆菌科的菌株构成了万亿美元产业的基础。我们对其关键性状的基因组基础的理解是支离破碎的，然而,包括其工业用途的新陈代谢。公开可用的乳杆菌科基因组的Pangenome分析使我们能够为26种具有工业重要性的物种生成基因组规模的代谢网络重建。他们的手工策展导致了超过75,000个基因-蛋白质反应关联，这些关联被用于生成2,446个基因组规模的代谢模型。交叉引用基因组和已知的代谢性状允许手动代谢网络管理和代谢模型的验证。因此,我们为乳杆菌科的代谢提供了第一个全基因组基础，并收集了可用于各种实际用途的预测性计算代谢模型。重要乳杆菌科，一万亿美元产业的细菌家族，与生物可持续性倡议越来越相关。我们的研究,利用大约2400个基因组序列，提供了乳杆菌科代谢的全基因组分析，创建超过2,400个经过策划和验证的基因组规模模型(GEM)。这些GEM成功地预测了(I)独特的，物种特异性代谢反应；（ii）增加生物体适应性的生态位富集反应；（iii）基本培养基成分，提供对乳杆菌科全球氨基酸重要性的见解；和（iv）整个家族的发酵能力，基于乳杆菌科的商业产品的代谢基础上发光。这种对乳酸杆菌科代谢特性及其基因组基础的定量理解将对食品工业和生物可持续性产生深远的影响。为菌株选择和操纵提供新的见解和工具。
