C. difficile, a spore-forming anaerobe, is a leading infectious cause of nosocomial diarrhea. The clinical outlook for C. difficile associated disease (CDAD) is highly variable and includes asymptomatic carriage, mild diarrheal illness, and pseudomembranous colitis. Symptomatic CDAD outcomes are associated with antibiotic-induced gut dysbiosis, so understanding the microbial ecology mediating colonization resistance against C. difficile may add valuable clinical context for infection control and treatment. The clinical use of multi-omic approaches, integrating shotgun metagenomic sequencing and metabolomic profiling directly from patient fecal samples, may have the potential to track the spread of and investigate the dynamics of C. difficile in real time. Despite this, the practical application of these tools in the clinic remains limited. As a step towards that goal, we optimized the powerful marker gene-based taxonomic profiling tool, MetaPhlAn4, and developed novel protocols for species level sensitivity tuning and strain-level C. difficile tracking. Using our locally optimized parameters, we investigated significant microbial and metabolic features discriminating CDI across diverse patient backgrounds. We then investigate the metabolic factors driving C. difficile inhibition by competing Clostridia spp. such as C. scindens, C. symbiosum, and C. sporogenes. Through these investigations, we observe strain-level variation in the inhibition of C. difficile by nutritional competition.