Detecting functional novelty in microbial genomes: discovery and characterization of new metalloprotease and toxin families

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Nearly a million microbial genomes and metagenomic datasets are currently available in public databases, which together provide unprecedented access to the microbial protein universe and encoded capabilities of microorganisms. Despite this wealth of information, only a small fraction of microbial protein families have been characterized, and there is a tremendous opportunity to find functional novelty in this data. Over the last five years, my NSERC-funded research program has focused on the computational detection of functional novelty in microbial genomes. We have developed computational methods for functional exploration of genomic datasets, and applied these methods to discover and characterize novel proteins families, pathways, and species-function associations with significant implications for microbiology. Our work has led to the discovery of non-clostridial "botulinum-like" toxins, global vitamin B12 synthesis by the phylum Thaumarchaeota, and bacterial flagella with enzymatic activity. These discoveries have shed light on the origins of bacterial toxins, the microbial production of vitamins, and identified a new function for a fundamental bacterial organelle. Over the next five years, my team and I will build on this work by automating computational approaches to explore and detect new and unexpected functional traits in genomic/metagenomic datasets, and focus our experimental efforts on the characterization of novel microbial metalloproteases and toxins. Objective 1 will expand our computational methods by building a phylogenomics framework for the microbial tree of life that incorporates high-resolution functional annotations of protein families and genomic traits. This framework will facilitate the large-scale detection of novel gene families, domain fusions, and other genomic traits, and thereby power continued exploration and discovery of new protein families and functional capabilities. Objective 2 will focus on the discovery and biochemical characterization of novel bacterial metalloproteases, identifying those with unique substrate specificities. Using genomic mutants, microbiological methods, biomaging and proteomic approaches, Objective 3 will focus on characterizing the biological roles of these enzymes in the context of biofilm formation, development and dispersal. Together, these three Objectives will synergize to accelerate the discovery (bioinformatics) and characterization (biochemistry, proteomics, microbiology) of novel microbial toxins and proteolytic enzymes. This will provide new computational tools for genome and proteome analysis, generate insights into the diverse biology of microbial proteases and toxins, and lead to biotechnological applications using these proteins for the targeted inhibition and control of microbial growth. Finally, my research program will benefit Canada by generating HQP with valuable high-demand skills in data science/analytics, bioinformatics, and computational biology.