Functional analysis of MS-based proteomics data: from protein groups to networks.

IF 6.1 2区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Molecular & Cellular Proteomics Pub Date : 2024-10-30 DOI:10.1016/j.mcpro.2024.100871

Marie Locard-Paulet, Nadezhda T Doncheva, John H Morris, Lars Juhl Jensen

引用次数: 0

Abstract

Mass-spectrometry-based proteomics allows the quantification of thousands of proteins, protein variants, and their modifications, in many biological samples. These are derived from the measurement of peptide relative quantities, and it is not always possible to distinguish proteins with similar sequences due to the absence of protein-specific peptides. In such cases, peptide signals are reported in protein groups that can correspond to several genes. Here, we show that multi-gene protein groups have a limited impact on GO-term enrichment, but selecting only one gene per group affects network analysis. We thus present the Cytoscape app Proteo Visualizer (https://apps.cytoscape.org/apps/ProteoVisualizer) that is designed for retrieving protein interaction networks from STRING using protein groups as input and thus allows visualisation and network analysis of bottom-up MS-based proteomics data sets.

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基于 MS 的蛋白质组学数据的功能分析：从蛋白质组到网络。

基于质谱的蛋白质组学可以对许多生物样本中的数千种蛋白质、蛋白质变体及其修饰进行定量。由于缺乏蛋白质特异性肽，并不总能区分具有相似序列的蛋白质。在这种情况下，蛋白质组中的肽信号可能对应多个基因。在这里，我们发现多基因蛋白质组对 GO 项富集的影响有限，但每组只选择一个基因会影响网络分析。因此，我们推出了 Cytoscape 应用程序 Proteo Visualizer (https://apps.cytoscape.org/apps/ProteoVisualizer)，该程序旨在使用蛋白质组作为输入，从 STRING 中检索蛋白质相互作用网络，从而对基于 MS 的自下而上蛋白质组学数据集进行可视化和网络分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Molecular & Cellular Proteomics 生物-生化研究方法

CiteScore

11.50

自引率

4.30%

发文量

131

审稿时长

84 days

期刊介绍： The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action. The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data. Scope: -Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights -Novel experimental and computational technologies -Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes -Pathway and network analyses of signaling that focus on the roles of post-translational modifications -Studies of proteome dynamics and quality controls, and their roles in disease -Studies of evolutionary processes effecting proteome dynamics, quality and regulation -Chemical proteomics, including mechanisms of drug action -Proteomics of the immune system and antigen presentation/recognition -Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease -Clinical and translational studies of human diseases -Metabolomics to understand functional connections between genes, proteins and phenotypes