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

首席调查员(赖特，埃里克·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。我们对典型细菌中编码的一半以上的蛋白质知之甚少。 基因组，而传统的实验室技术太耗时，甚至无法表征一小部分 可观察到的蛋白质宇宙。这个被忽视的“黑暗蛋白质组”潜在地包含许多重要的 毒力、抗生素耐药性和疾病的决定因素。给黑暗的蛋白质组带来光明是可能的 通过比较基因组学，因为跨进化时间尺度相互作用的蛋白质会留下一个 共同进化的标志，可以用来连接未知功能的蛋白质和已知的蛋白质 功能。这种关联内疚的分析有助于产生关于未被探索的细胞角色的假说 蛋白质。在这里，我们开发了量化共同进化信号的新方法，并应用了这些方法 到一个空前庞大的跨越微生物生命树的基因组集合。这个项目将导致一个 共同进化的基因网络，我们将作为生物医学研究的网络工具公开访问。至 进一步利用比较基因组学的力量，我们将开发和部署Web应用程序，以提供 对微生物蛋白质宇宙的更深入的洞察。

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.