Connecting the universe of proteins to address annotation inequality in the microbial proteome

主要研究者（Wright，Erik S.） 摘要： 微生物基因组数量的迅速增加揭示了蛋白质的巨大多样性， 任何已知的功能。我们对典型细菌中一半以上的蛋白质编码仍然知之甚少 基因组，传统的实验室技术太耗时，即使是一小部分， 蛋白质的可观测宇宙这种被忽视的“暗蛋白质组”可能包含许多重要的 毒力、抗生素耐药性和疾病的决定因素。在黑暗的蛋白质组上投射一盏灯是可能的 通过比较基因组学，因为蛋白质在进化时间尺度上相互作用， 可以用来连接未知功能的蛋白质与已知功能的蛋白质的共同进化的签名 功能这种“关联性内疚”分析有助于产生关于未探索的细胞作用的假设。 proteins.在这里，我们开发了新的方法来量化共同进化信号，我们应用这些方法 到一个前所未有的庞大的基因组集合，跨越微生物生命之树。该项目将导致 共同进化基因的网络，我们将把它作为生物医学研究的网络工具公开。到 为了进一步利用比较基因组学的力量，我们将开发和部署网络应用程序， 对微生物蛋白质宇宙的更深入了解。

Principal Investigator (Wright, Erik S.) Abstract: The rapidly increasing number of microbial genomes has revealed an enormous diversity of proteins without any known function. We still know relatively little about over half the proteins encoded in a typical bacterial genome, and traditional laboratory techniques are too time consuming to characterize even a small fraction of the observable universe of proteins. This neglected "dark proteome" potentially contains many important determinants of virulence, antibiotic resistance, and disease. Casting a light on the dark proteome is possible through comparative genomics because proteins interacting across evolutionary timescales leave behind a signature of coevolution that can be used to connect proteins of unknown function with proteins of known function. This 'guilt-by-association' analysis helps to generate hypotheses about the cellular role of unexplored proteins. Here, we develop novel methods for quantifying coevolutionary signals, and we apply these methods to an unprecedently large collection of genomes spanning the microbial tree of life. This project will result in a network of coevolving genes that we will make publicly accessible as a web tool for biomedical research. To further harness the power of comparative genomics, we will develop and deploy web applications that provide deeper insights into the universe of microbial proteins.