加拿大多伦多大学Andrew Emili和Gary D. Bader课题组开发出EPIC:基于洗脱曲线的蛋白质复合物推断的软件工具包。 该研究于2019年8月发表于国际一流学术期刊《自然—方法学》杂志上。

研究组和其他人之前报道了一个基于生物提取物色谱分离和精确质谱分析的天然蛋白质组件全局表征的实验策略(色谱分离质谱,CFMS)，但结果数据比较难以处理和解释。这里，研究人员提出了EPIC(基于洗脱曲线的复合物推断)，这是一个用于大规模CFMS数据自动评分的软件工具包，用于定义来自不同生物样本的高置信度多组分大分子。作为一个案例研究，研究人员使用EPIC绘制了秀丽隐杆线虫的全局中间体，定义了612个与不同生物过程相关的假定蠕虫蛋白复合体其中包括线虫特有的新亚基和组件,课题组正交方法进行了验证。EPIC软件是作为开源的Jupyter notebook打包在Docker环境下，并且是可免费获得的（https://hub.docker.com/r/baderlab/bio-epic/）。

研究人员表示，细胞的蛋白复合物是细胞的关键大分子机器,但是对它们的描述仍然是不完整的。

附：英文原文

Title: EPIC: software toolkit for elution profile-based inference of protein complexes

Author: Lucas ZhongMing Hu, Florian Goebels, June H. Tan, Eric Wolf, Uros Kuzmanov, Cuihong Wan, Sadhna Phanse, Changjiang Xu, Mike Schertzberg, Andrew G. Fraser, Gary D. Bader, Andrew Emili

Issue&Volume: Volume 16 Issue 8

Abstract: Protein complexes are key macromolecular machines of the cell, but their description remains incomplete. We and others previously reported an experimental strategy for global characterization of native protein assemblies based on chromatographic fractionation of biological extracts coupled to precision mass spectrometry analysis (chromatographic fractionationmass spectrometry, CFMS), but the resulting data are challenging to process and interpret. Here, we describe EPIC (elution profile-based inference of complexes), a software toolkit for automated scoring of large-scale CFMS data to define high-confidence multi-component macromolecules from diverse biological specimens. As a case study, we used EPIC to map the global interactome of Caenorhabditis elegans, defining 612 putative worm protein complexes linked to diverse biological processes. These included novel subunits and assemblies unique to nematodes that we validated using orthogonal methods. The open source EPIC software is freely available as a Jupyter notebook packaged in a Docker container (https://hub.docker.com/r/baderlab/bio-epic/).

DOI: 10.1038/s41592-019-0461-4

Source:https://www.nature.com/articles/s41592-019-0461-4