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模拟的核糖体蛋白合成复合物,用于基准交联质谱工作流程。

Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows.

机构信息

Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria.

Institute of Molecular Biotechnology, Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria.

出版信息

Nat Commun. 2022 Jul 8;13(1):3975. doi: 10.1038/s41467-022-31701-w.

Abstract

Cross-linking mass spectrometry has matured to a frequently used tool for the investigation of protein structures as well as interactome studies up to a system-wide level. The growing community generated a broad spectrum of applications, linker types, acquisition strategies and specialized data analysis tools, which makes it challenging to decide for an appropriate analysis workflow. Here, we report a large and flexible synthetic peptide library as reliable instrument to benchmark crosslink workflows. Additionally, we provide a tool, IMP-X-FDR, that calculates the real, experimentally validated, FDR, compares results across search engine platforms and analyses crosslink properties in an automated manner. We apply the library with 6 commonly used linker reagents and analyse the data with 6 established search engines. We thereby show that the correct algorithm and search setting choice is highly important to improve identification rate and reliability. We reach identification rates of up to ~70 % of the theoretical maximum (i.e. 700 unique lysine-lysine cross-links) while maintaining a real false-discovery-rate of <3 % at cross-link level with high reproducibility, representatively showing that our test system delivers valuable and statistically solid results.

摘要

交联质谱已发展成为研究蛋白质结构以及互作组学的常用工具,其应用范围广泛,包括连接体类型、采集策略和专门的数据分析工具,这使得选择合适的分析工作流程具有一定挑战性。在这里,我们报告了一个大型且灵活的合成肽文库,可作为交联工作流程的基准测试工具。此外,我们还提供了一种名为 IMP-X-FDR 的工具,可计算真实的、经实验验证的 FDR,并在跨搜索引擎平台比较结果,以及以自动化方式分析交联特性。我们使用该文库结合 6 种常用的连接试剂,并使用 6 种已建立的搜索引擎对数据进行分析。因此,我们证明了正确的算法和搜索设置选择对于提高鉴定率和可靠性非常重要。我们达到了高达~70%的理论最大鉴定率(即 700 个独特的赖氨酸-赖氨酸交联),同时在交联水平上保持<3%的真实假阳性率,具有很高的重现性,这表明我们的测试系统提供了有价值且具有统计学意义的可靠结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0193/9270371/01ca48af9aaf/41467_2022_31701_Fig1_HTML.jpg

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