ABSTRACT Microbial genes in gut and diseased tissues were recently linked with progression and outcomes of different human diseases, including cancer and immune diseases. Deciphering the pathogenic roles of different microbial genes can improve diagnosis, prognostication, and treatment of human diseases. Yet, current methods for RNA and shotgun metagenomic sequencing focus on microbial species, and do not allow a systematic detection or quantification of microbial genes. Therefore, current methods for disease prognostication and biomarker discovery are unable to consider microbial genes that influence human diseases. Our overarching hypothesis is that there are unknown associations between human diseases and the microbial genes in diseased tissues and in the gut. Our long-term goal is to unravel these associations using novel computational approaches that will allow detection and quantification of microbial genes in diseases. In Aim 1 we will develop methods that harness RNA sequencing to detect microbial gene expression in diseased tissues. This will allow microbial biomarker discovery and provide a comprehensive database of the microbial genes that are expressed in various human tissues and conditions. In Aim 2 we will develop methods to quantify gut microbial gene capacity in human diseases. This will allow identification of gut microbial proteins, peptides, and domains that are important in human diseases, to ultimately yield new diagnostic and treatment strategies based on gut microbiomes. Overall, this project will provide innovative methods to allow detection and quantification of microbial genes from abundantly used sequencing technologies. We will establish user friendly software and databases, allowing new discoveries with existing sequencing platforms. We expect that the methods developed through this project will be extensively adopted by the relevant research communities, improving our understanding of the roles of microbes in human diseases and ultimately allowing the development of new disease detection and intervention strategies based on microbial genes.