Abstract
Colorectal cancer (CRC) is a common cancer accompanied by microbiome dysbiosis. Exploration of probiotics against oncogenic microorganisms is promising for CRC treatment. Here, differential microorganisms between CRC and healthy control were analyzed. Antibacterial experiments, whole-genome sequencing, and metabolic network reconstruction were combined to reveal the anti-Fusobacterium nucleatum mechanism, which was verified by co-culture assay and mendelian randomization analysis. Sequencing results showed that F. nucleatum was enriched in CRC, yet Bifidobacterium animalis decreased gradually from healthy to CRC. Additionally, F. nucleatum could be inhibited by B. animalis. Whole-genome sequencing of B. animalis showed high phylogenetic similarity with known probiotic strains and highlighted its functions for amino acid and carbohydrate metabolism. Metabolic network reconstruction demonstrated that cross-feeding and specific metabolites (acidic molecules, arginine) had a great influence on the coexistence relationship. Finally, the arginine supplement enhanced the competitive ability of F. nucleatum against B. animalis, and the mendelian randomization and metagenomic sequencing analysis confirmed the positive relationship among F. nucleatum, arginine metabolism, and CRC. Thus, whole-genome sequencing and metabolic network reconstruction are valuable for probiotic mining and patient dietary guidance.IMPORTANCEUsing probiotics to inhibit oncogenic microorganisms (Fusobacterium nucleatum) is promising for colorectal cancer (CRC) treatment. In this study, whole-genome sequencing and metabolic network reconstruction were combined to reveal the anti-F. nucleatum mechanism of Bifidobacterium animalis, which was verified by co-culture assay and mendelian randomization analysis. The result indicated that the arginine supplement enhanced the competitive ability of F. nucleatum, which may be harmful to F. nucleatum-infected CRC patients. B. animalis is a potential probiotic to relieve this dilemma. Thus, using in silico simulation methods based on flux balance analysis, such as genome-scale metabolic reconstruction, provides valuable insights for probiotic mining and dietary guidance for cancer patients.