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This dissertation aimed to document interactions between the bacterial taxa that comprise the gut microbiome of common marmosets and provide insight into the microbiome’s transition from healthy “eubiosis” to unhealthy “dysbiosis”. This was accomplished by using high-throughput sequencing to obtain a snapshot of microbial composition and comparing multiple snapshots across subjects and time points. Chapter 1 used correlation and network graphical analysis to assess longitudinal bacterial and metabolic interactions in healthy subjects. This analysis revealed bacteria and metabolites that were involved in many significant interactions and used a novel metric to rank bacteria by their perceived influence on the microbiome. The metric ranked Clostridium_sensu_stricto_1, Alloprevotella, and Parabacteroides as the most influential bacteria, and negative correlations suggested competition between high-ranking bacteria and numerically dominant Bifidobacterium. Chapter 2 used differential abundance and pathway enrichment analysis to identify bacteria and bacterial genes that exhibited major shifts in abundance during a period of antibiotic-induced dysbiosis. This analysis found that some bacteria such as Bifidobacterium were severely inhibited by antibiotics while others such as Fusobacterium and Clostridium_sensu_stricto_1 thrived, and that some bacteria possessed antibiotic resistance genes which contributed to their success. Dysregulated pathways for carbohydrate and amino acid metabolism highlighted the importance of microbial organisms in degrading complex molecules and indicated that antibiotics can impair digestion. Together, these findings indicate that Bifidobacterium is a valuable resident of the marmoset gut that can be easily displaced by other bacteria in response to microbiome perturbation. From a broader perspective, this dissertation argues for the importance of holistic microbiome studies that consider the composition of known and unknown bacterial species.