Understanding the microbiota profile, including its interactions with host genetics and metabolism, is critical for understanding host physiology and creating targeted therapeutics. The gut microbiota, which consists of many different kinds of bacterial and fungal species, is essential for nutrient absorption, immune function, and metabolic regulation. In this study, microbial species within the gut of the model organism Drosophila melanogaster were identified and quantified using NGS, qPCR, and LAMP molecular methods. Notably, A. pomorum and L. brevis were highly prevalent and significantly correlated with host lipid metabolism negatively (p <0.001 and p <0.01, respectively). Further contributing to the bacterial microbiota, a fungal microbiota composed primarily of Ascomycota and Basidiomycota phyla was discovered. Interestingly, the presence of the M. restricta demonstrated a negative correlation with triglyceride levels (p=9.4e-05), emphasizing the unique roles of fungi in metabolism. GWAS was employed to discover host genetic variants that influence microbiota composition and metabolic profiles. Important genes such as pyd and Myd88, which are required for intestinal barrier integrity and immune-mediated signaling, were revealed. Our research, which integrates modern molecular methods and genetic analyses, may contribute to the development of personalized therapies to reveal microbiota composition, and aimed improve metabolic health, disease management. Additionally, in this study, LAMP was successfully performed amplification of microbial species exist in the DNA obtained from very small Drosophila intestinal samples, with high sensitivity. Therefore, LAMP can facilitate microbiota-related diagnostics by minimizing time and technical requirements and simplifies detection strategies with wide applicability in microbiota research across various species and sample types.