Genome-scale metabolic reconstruction of urinary microbiome: Pathway for personalized medicine.

822 Background: The human microbiome significantly influences the efficacy and safety of various medications. To integrate microbial metabolism into precision medicine, it is crucial to develop strain- and molecule-specific computational models that can predict a patient's microbiome's ability to metabolize chemotherapy drugs. This study evaluates the potential of urine, pellet, and supernatant samples to identify microbial profiles and metabolizing genes in patients with bladder cancer. Methods: Catheterized urine, pellet, and supernatant samples from six patients (5 males and 1 female) with bladder cancer were analyzed to identify microbial species and strains, assess drug gene abundance, and predict drug metabolism. Whole-genome sequencing (WGS) was performed, and gene annotation was conducted using the PubSEED platform. Biosynthetic pathways were identified following the KEGG PATHWAY resource, and AGORA2 reconstruction was used for final metabolic reactions. Results: WGS revealed a diverse microbial community, with 1,024 species unique to urine, 386 unique to pellet, and 1,861 species common to both. The most prevalent species, Enterococcus faecalis and Staphylococcus epidermidis, accounted for over 60% of the microbial population in both urine and pellet samples. A detailed comparison of OTU abundance between paired urine and pellet samples showed significant variations in microbial composition, yet a strong correlation between the two sample types. The net metabolizing capacity of 13 chemotherapy-drug metabolites was assessed among the six patients. Mean flux calculations indicated highly variable metabolism of gemcitabine (median 773.57, IQR 380-1056), SN38 (irinotecan) (median 770.24, IQR 10.1-2234.5), and bile salt hydrolase (median 130.80, IQR 9.8-318.2). These findings highlight the microbiome's extensive role in influencing chemotherapy drug pharmacokinetics. Conclusions: This study demonstrates the potential of microbiome profiling in informing precision medicine, suggesting that microbiome modification could enhance chemotherapy drug pharmacokinetics and improve patient outcomes. Further research is needed to validate these findings and refine microbiome-based precision medicine in oncology.