Type 2 Diabetes (T2D) is a complex metabolic disorder influenced by both genetic and environmental factors, including the gut microbiome. Recent studies indicate that alterations in the gut microbiome play a crucial role in T2D progression, but the specific interactions and functional consequences remain poorly understood. This project aims to comprehensively analyze microbiome changes and interactions in T2D by leveraging high-throughput sequencing data and advanced computational tools. We will utilize metagenomic sequencing datasets to investigate microbial community composition, functional potential, and strain-level variations in individuals with and without T2D. The study will integrate various bioinformatics approaches, including assembly-based and read-mapping methods, to ensure robust characterization of microbial dynamics. A particular focus will be on strain-level diversity, horizontal gene transfer events, and virome interactions within the microbiome. These analyses will provide deeper insights into how microbial communities evolve in the context of T2D and their potential role in disease progression. The results from this study will enhance our understanding of the gut microbiome’s role in T2D and may contribute to the development of microbiome-based therapeutic strategies. The computational resources provided by NAISS will be essential for processing and analyzing large-scale sequencing data efficiently.