Abstract
Human microbiome communities consist of variety of bacteria, fungi and archaea, which are integral part of the human body. These microbial communities can greatly vary from one part of the body to the other and help us maintain healthy environment. Most microbiome interacts with their host and each other via metabolic products, but how it interacts with complex various human metabolic pathways still remains unknown. Slight changes in the microbial communities could be important indicator of potential disease and can be served as Biomarker. For this study two separate specimens of human saliva microbial DNA short read sequences retrieved from the HMP (Human Metabiome Project) [1]. After appropriate quality control, both sequences aligned against the KEGG database for identification of known metabolic pathways these communities were involved. The Human Metabolic Reconstruction HUMAnN pipeline [2] from the Hutten hower Lab used to derive metabolic pathway network involved in the human microbiome. Further information on statistical significance on each metabolic pathway analyzed and compared against both control and test Specimens. Finally 3M [3] comparative visual analytics and manual curation capabilities were developed using Oracle Apex rapid web development technology [4]. As a conclusion of this case study various surprising facts uncovered between both specimens. With the help of KEGG BRITE Metabolic Hierarchy [5] pathways abundance/coverage with Orthology, Enzyme and chemical function visualized more effectively. Such type of comparative metagenomics studies performed on large pool of patient cohort can be beneficial to discover effective biomarker for the diagnosis and prognosis of various diseases.
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