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

检测微生物基因组中的功能新颖性：新金属蛋白酶和毒素家族的发现和表征

• 批准号: RGPIN-2019-04266
• 负责人: Doxey, Andrew
• 金额: $ 3.64万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=714746
• 关键词: Detecting; functional; novelty; microbial; genomes

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.

目前，公共数据库中有近100万个微生物基因组和宏基因组数据集，这些数据集提供了前所未有的微生物蛋白质宇宙和微生物编码能力。尽管有如此丰富的信息，但只有一小部分微生物蛋白家族被表征，并且在这些数据中发现功能新颖性的机会很大。在过去的五年里，我的nserc资助的研究项目集中在微生物基因组功能新颖性的计算检测上。我们已经开发了基因组数据集功能探索的计算方法，并应用这些方法来发现和表征新的蛋白质家族，途径和物种功能关联，对微生物学具有重要意义。我们的工作导致了非梭菌“肉毒杆菌样”毒素的发现，全球维生素B12合成门Thaumarchaeota，细菌鞭毛具有酶活性。这些发现揭示了细菌毒素的起源，微生物生产维生素，并确定了基本细菌细胞器的新功能。