Poly cystic ovary syndrome (PCOS) is a common reproductive endocrine disorder that affects between 5.5 – 19.9% of reproductive-aged women. In addition to reproductive issues such as infertility and pregnancy complications, women with PCOS are also susceptible to metabolic dysregulation such as type 2 diabetes, obesity, and non-alcoholic fatty liver disease (NAFLD). Studies have also shown that women with PCOS exhibit a difference in their gut microbiome and metabolome. Previous work using a letrozole-induced mouse model, which replicates the reproductive, metabolic, and the gut community characteristics of PCOS, confirmed that exposure to a healthy gut microbiome through cohousing alleviates PCOS reproductive and metabolic symptoms. To further explore the mechanisms behind PCOS and the alleviation of symptoms in the cohousing study, we used shotgun metagenome sequencing to explore the changes to the gut microbiome in the letrozole PCOS disease- and fecal microbiome exchanging cohoused- state. Using metagenomes, we performed beta-community analysis, differential expression analysis of gut microbial taxonomy, functional profiling, and targeted gene analysis. Through these analyses, we observed that there is differentiation in the gut microbiome treatment conditions. The overall composition of the gut microbiome differs between the experimental conditions, in particular we observed the cohoused conditions to develop into its own unique state. Differential abundance analysis also indicated important genera with metabolism and sex hormone function such as Lactobacillus, Bifidobacterium, and Bacteroides differed between treatment conditions. Similarly, we observed differences in functional analysis, particularly functions relating to metabolism, microbial growth, and sex hormones. In addition, we incorporated metabolites into the analysis to create a multiomics dataset. Using beta-community and random forest analysis, we observed the importance of the metabolome from their strong early onset differentiation between treatment conditions as compared to when using only the gut microbiome. Furthermore, both metagenomic and multiomics data highlight the importance of longitudinal sampling to provide insight into time dependent changes. Overall, through utilizing the metagenomes and multiomics in a longitudinal manner, this study explores the intricate and time dependent connections between the gut microbiome, metabolome, and sex hormones in PCOS.