Systems Modeling of the Oral Metabiome

Abstract

Deciphering the underlying biological processes comprising the Human Oral Metabiome is important to the understanding of Human Immunodeficiency Virus (HIV) disease. The National Institute of Health has launched the Human Microbiome Project (HMP) to accelerate research and discovery techniques for five microbiome sites on the human body. Knowledge discovery techniques are needed to point researchers to follow-on hypotheses to quickly pinpoint areas of great promise. We developed the Differential Correlation Network (DCN) as a technique for researcher's to perform knowledge discovery in the oral mycobiome field. Using data from the Oral Microbiome, Differential Correlation Networks were applied to metabolites, bacteria, and fungi sampled from 12 Controls and 12 HIV Patients. By analyzing 100's of features across disease vs. control classes, statistically significant feature pair differences are captured and presented in Cytoscape. Several interesting differences are discovered and their possible biological significance is presented. The Systems model in conjunction with known biological metadata can identify promising difference networks and direct follow-on research based on DCN generated hypothesis.