Clasen Milan Avila, Ruwolt Max, Wang Cong, Ruta Julia, Bogdanow Boris, Kurt Louise U, Zhang Zehong, Wang Shuai, Gozzo Fabio C, Chen Tao, Carvalho Paulo C, Lima Diogo Borges, Liu Fan
Carlos Chagas Institute, Fiocruz Paraná, Curitiba, Brazil.
Department of Structural Biology, Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Berlin, Germany.
Nat Methods. 2024 Dec;21(12):2327-2335. doi: 10.1038/s41592-024-02478-1. Epub 2024 Oct 31.
Advancing data analysis tools for proteome-wide cross-linking mass spectrometry (XL-MS) requires ground-truth standards that mimic biological complexity. Here we develop well-controlled XL-MS standards comprising hundreds of recombinant proteins that are systematically mixed for cross-linking. We use one standard dataset to guide the development of Scout, a search engine for XL-MS with MS-cleavable cross-linkers. Using other, independent standard datasets and published datasets, we benchmark the performance of Scout and existing XL-MS software. We find that Scout offers an excellent combination of speed, sensitivity and false discovery rate control. The results illustrate how our large recombinant standard can support the development of XL-MS analysis tools and evaluation of XL-MS results.
推进用于全蛋白质组交联质谱分析(XL-MS)的数据分析工具需要模拟生物复杂性的真实标准。在这里,我们开发了精心控制的XL-MS标准,其包含数百种重组蛋白,这些蛋白经过系统混合用于交联。我们使用一个标准数据集来指导Scout的开发,Scout是一款用于带有可被质谱裂解的交联剂的XL-MS的搜索引擎。使用其他独立的标准数据集和已发表的数据集,我们对Scout和现有XL-MS软件的性能进行了基准测试。我们发现Scout在速度、灵敏度和错误发现率控制方面表现出色。结果表明,我们的大型重组标准如何能够支持XL-MS分析工具的开发以及XL-MS结果的评估。