Computer Science Events
CS Tea Talk Series
Dr. Tonya Ward, Postdoctoral Associate at the University of Minnesota will be giving talk.
BugBase - a tool to predict organism-level microbiome phenotypes
Changes in microbial community structure and function are associated with many major chronic human diseases, and have been implicated in important environmental and industrial applications including carbon cycling and bioremediation. Microbiome studies increasingly focus on identifying functional mechanisms linked to disease or experimental conditions. Shotgun metagenomics and marker gene amplicon sequencing can be used to measure directly or predict the functional repertoire of the microbiota en masse, but current methods do not readily estimate the functional capability of individual organisms within the microbiome. BugBase addresses these challenges as an algorithm that predicts organism-level coverage of functional pathways within complex microbiomes using either whole-genome shotgun or marker gene sequencing data. We find organism-level pathway coverage predictions for inferred phenotypes from BugBase to be statistically higher powered than current ‘bag-of-genes’ approaches for discerning functional changes in both host-associated and environmental microbiomes. In addition to predicting the presence of user-defined pathways in microbiome samples, BugBase also predicts biologically interpretable organism-level phenotypes such as oxygen tolerance, Gram staining and pathogenic potential by utilizing databases of experimentally-annotated bacterial phenotypes. BugBase enables novel biological insights and generation of new mechanistic hypotheses across a broad range of microbiome types with potential applications in medical, agricultural, industrial, and environmental research.
Sponsored by Computer Science. Contact: Sue Jandro, x4360