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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=745684
• 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一百万个微生物基因组和宏基因组数据集，它们共同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质家族得到了表征，并且有巨大的机会在这些数据中发现功能新颖性。在过去的五年里，我的 NSERC 资助的研究项目重点关注微生物基因组功能新颖性的计算检测。我们开发了用于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对微生物学具有重大影响的新蛋白质家族、途径和物种功能关联。我们的工作发现了非梭菌“肉毒杆菌样”毒素、奇古菌门合成的维生素 B12 以及具有酶活性的细菌鞭毛。这些发现揭示了细菌毒素的起源、维生素的微生物生产，并确定了基本细菌细胞器的新功能。 在接下来的五年中，我和我的团队将在这项工作的基础上，通过自动化计算方法来探索和检测基因组/宏基因组数据集中新的和意想不到的功能特征，并将我们的实验工作重点放在新型微生物金属蛋白酶和毒素的表征上。目标 1 将通过构建微生物生命树的系统基因组学框架来扩展我们的计算方法，该框架结合了蛋白质家族和基因组特征的高分辨率功能注释。该框架将促进新基因家族、结构域融合和其他基因组特征的大规模检测，从而推动新蛋白质家族和功能能力的持续探索和发现。目标 2 将重点关注新型细菌金属蛋白酶的发现和生化表征，鉴定具有独特底物特异性的酶。目标 3 将利用基因组突变体、微生物学方法、生物成像和蛋白质组学方法，重点描述这些酶在生物膜形成、发育和扩散中的生物学作用。这三个目标将协同作用，加速新型微生物毒素和蛋白水解酶的发现（生物信息学）和表征（生物化学、蛋白质组学、微生物学）。这将为基因组和蛋白质组分析提供新的计算工具，深入了解微生物蛋白酶和毒素的多样性生物学，并导致使用这些蛋白质来有针对性地抑制和控制微生物生长的生物技术应用。最后，我的研究项目将通过培养具有数据科学/分析、生物信息学和计算生物学方面宝贵的高需求技能的 HQP 来使加拿大受益。