Department of Biochemistry & Molecular Biology and VILLUM Center for Bioanalytical Sciences, University of Southern Denmark, Campusvej 55, DK-5230, Odense M, Denmark.
Department of Biochemistry & Molecular Biology and VILLUM Center for Bioanalytical Sciences, University of Southern Denmark, Campusvej 55, DK-5230, Odense M, Denmark.
Mol Cell Proteomics. 2019 Nov;18(11):2324-2334. doi: 10.1074/mcp.TIR119.001434. Epub 2019 Aug 25.
We have developed ComplexBrowser, an open source, online platform for supervised analysis of quantitative proteomic data (label free and isobaric mass tag based) that focuses on protein complexes. The software uses manually curated information from CORUM and Complex Portal databases to identify protein complex components. For the first time, we provide a Complex Fold Change (CFC) factor that identifies up- and downregulated complexes based on the level of complex subunits coregulation. The software provides interactive visualization of protein complexes' composition and expression for exploratory analysis and incorporates a quality control step that includes normalization and statistical analysis based on the limma package. ComplexBrowser was tested on two published studies identifying changes in protein expression within either human adenocarcinoma tissue or activated mouse T-cells. The analysis revealed 1519 and 332 protein complexes, of which 233 and 41 were found coordinately regulated in the respective studies. The adopted approach provided evidence for a shift to glucose-based metabolism and high proliferation in adenocarcinoma tissues, and the identification of chromatin remodeling complexes involved in mouse T-cell activation. The results correlate with the original interpretation of the experiments and provide novel biological details about the protein complexes affected. ComplexBrowser is, to our knowledge, the first tool to automate quantitative protein complex analysis for high-throughput studies, providing insights into protein complex regulation within minutes of analysis.
我们开发了 ComplexBrowser,这是一个用于监督分析定量蛋白质组学数据(基于无标签和等压质量标记)的开源在线平台,专注于蛋白质复合物。该软件使用来自 CORUM 和 Complex Portal 数据库的手动整理信息来识别蛋白质复合物组件。我们首次提供了一种复合物倍数变化(CFC)因子,该因子基于复合物亚基的共同调控水平来识别上调和下调的复合物。该软件提供了蛋白质复合物组成和表达的交互式可视化,用于探索性分析,并结合了质量控制步骤,包括基于 limma 包的归一化和统计分析。我们在两项已发表的研究中测试了 ComplexBrowser,这些研究旨在确定人类腺癌组织或激活的小鼠 T 细胞中蛋白质表达的变化。分析揭示了 1519 个和 332 个蛋白质复合物,其中 233 个和 41 个在各自的研究中被发现协调调节。所采用的方法为腺癌组织中基于葡萄糖的代谢和高增殖提供了证据,并鉴定了参与小鼠 T 细胞激活的染色质重塑复合物。这些结果与实验的原始解释相吻合,并提供了有关受影响蛋白质复合物的新的生物学细节。据我们所知,ComplexBrowser 是第一个用于自动化高通量研究中定量蛋白质复合物分析的工具,可在分析后几分钟内深入了解蛋白质复合物的调节。