Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada.
Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
Nat Methods. 2019 Aug;16(8):737-742. doi: 10.1038/s41592-019-0461-4. Epub 2019 Jul 15.
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 fractionation-mass spectrometry, CF-MS), 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 CF-MS 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/).
蛋白质复合物是细胞的关键大分子机器，但它们的描述仍然不完整。我们和其他人之前报道了一种基于生物提取物的色谱分离结合精确质谱分析（色谱分离-质谱，CF-MS）对天然蛋白质复合物进行全局表征的实验策略，但得到的数据处理和解释具有挑战性。在这里，我们描述了 EPIC（基于洗脱曲线推断复合物），这是一个用于自动评分大规模 CF-MS 数据的软件工具包，用于从各种生物样本中定义高可信度的多成分大分子。作为一个案例研究，我们使用 EPIC 绘制了秀丽隐杆线虫的全局相互作用组图谱，定义了 612 个可能与不同生物过程相关的虫蛋白复合物。其中包括我们使用正交方法验证的新型线虫特有亚基和复合物。开源 EPIC 软件可作为一个 Jupyter 笔记本免费获得，并打包在一个 Docker 容器中（https://hub.docker.com/r/baderlab/bio-epic/）。
