Department of Chemistry & Chemical Biology, Harvard University, Cambridge, MA, USA.
School of Engineering & Applied Sciences, Harvard University, Cambridge, MA, USA.
Bioinformatics. 2018 Oct 15;34(20):3557-3565. doi: 10.1093/bioinformatics/bty370.
Protein evolution spans time scales and its effects span the length of an organism. A web app named ProteomeVis is developed to provide a comprehensive view of protein evolution in the Saccharomyces cerevisiae and Escherichia coli proteomes. ProteomeVis interactively creates protein chain graphs, where edges between nodes represent structure and sequence similarities within user-defined ranges, to study the long time scale effects of protein structure evolution. The short time scale effects of protein sequence evolution are studied by sequence evolutionary rate (ER) correlation analyses with protein properties that span from the molecular to the organismal level.
We demonstrate the utility and versatility of ProteomeVis by investigating the distribution of edges per node in organismal protein chain universe graphs (oPCUGs) and putative ER determinants. S.cerevisiae and E.coli oPCUGs are scale-free with scaling constants of 1.79 and 1.56, respectively. Both scaling constants can be explained by a previously reported theoretical model describing protein structure evolution. Protein abundance most strongly correlates with ER among properties in ProteomeVis, with Spearman correlations of -0.49 (P-value < 10-10) and -0.46 (P-value < 10-10) for S.cerevisiae and E.coli, respectively. This result is consistent with previous reports that found protein expression to be the most important ER determinant.
ProteomeVis is freely accessible at http://proteomevis.chem.harvard.edu.
Supplementary data are available at Bioinformatics online.
蛋白质进化跨越时间尺度，其影响跨越生物体的长度。开发了一个名为 ProteomeVis 的网络应用程序，以提供酿酒酵母和大肠杆菌蛋白质组中蛋白质进化的综合视图。ProteomeVis 交互式创建蛋白质链图，节点之间的边缘表示用户定义范围内的结构和序列相似性，以研究蛋白质结构进化的长时间尺度效应。通过与从分子到生物体水平的蛋白质特性的序列进化率 (ER) 相关分析来研究蛋白质序列进化的短时间尺度效应。
我们通过研究生物体蛋白质链宇宙图 (oPCUG) 和假定 ER 决定因素中的每个节点的边缘分布，展示了 ProteomeVis 的实用性和多功能性。酿酒酵母和大肠杆菌 oPCUG 分别具有 1.79 和 1.56 的无标度常数，呈无标度分布。这两个标度常数都可以用以前报道的描述蛋白质结构进化的理论模型来解释。在 ProteomeVis 中，蛋白质丰度与特性中的 ER 相关性最强，酿酒酵母和大肠杆菌的 Spearman 相关系数分别为-0.49（P 值 < 10-10）和-0.46（P 值 < 10-10）。这一结果与先前的报道一致，即发现蛋白质表达是最重要的 ER 决定因素。
ProteomeVis 可在 http://proteomevis.chem.harvard.edu 上免费访问。
补充数据可在 Bioinformatics 在线获得。
