Systematic characterization of bioactive molecules from the human microbiome

ABSTRACT
A complex interplay exists between the human microbiome and the host, resulting in clear effects on
human physiology and microbiome ecology. A promising avenue to dissect this interplay at a
mechanistic level is through the study of microbiome-derived molecules that mediate important
microbe-microbe and microbe-host interactions. In this application, we propose a hybrid computational-
synthetic biology approach to discover, rationally prioritize and systematically characterize microbiome-
derived molecules. We propose to apply this approach to three structurally diverse classes of bioactive
molecules that are widely encoded by the human microbiome but remain severely understudied in
terms of both structure and function. First, guided by the computational analysis of biosynthetic gene
clusters in metagenomic sequencing data from the human microbiome of thousands of subjects, we
will select specific members of the three molecular classes for experimental characterization. Second,
we will use genome editing of native members of the microbiome and synthetic biology in a multi-host
heterologous expression platform to characterize the selected pathways and their products. Finally, we
will employ an array of in vitro, cell-based and mouse colonization assays to interrogate the role of the
discovered molecules in mediating relevant host and microbiome functions. Taken together, our
approach will unveil an undermined section of the interplay between the human microbiome and the
host and provide diverse microbiome-derived bioactive molecules as tools for future mechanistic
studies and therapeutic interventions.

Grant Number: 4R01AI172144-04
NIH Institute/Center: NIH
Principal Investigator: Mohamed Abou Donia