MaXLinker: Proteome-wide Cross-link Identifications with High Specificity and Sensitivity.
MaXLinker: Proteome-wide Cross-link Identifications with High Specificity and Sensitivity.
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MaXLinker：具有高特异性和灵敏度的全蛋白质组交联鉴定。
DOI：
10.1074/mcp.tir119.001847
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Yu,Haiyuan
中科院分区：
文献类型：
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作者：
Yugandhar,Kumar;Wang,Ting-Yi;Leung,AldenKing-Yung;Lanz,MichaelCharles;Motorykin,Ievgen;Liang,Jin;Shayhidin,ElnurElyar;Smolka,MarcusBustamante;Zhang,Sheng;Yu,Haiyuan
蛋白质-蛋白质相互作用在几乎所有的细胞功能中起着至关重要的作用。因此，了解它们的相互作用模式和三维结构构象可以为许多疾病表型的各种生物学过程和潜在分子机制提供重要的见解。交联质谱（XL-MS）具有独特的能力，以检测蛋白质-蛋白质相互作用在大规模沿着与相互作用伙伴之间的空间限制。MS-可裂解交联剂的出现使得MS 2-MS 3 XL-MS采集策略能够提供MS 2和MS 3水平的交联信息。然而，当前可用于MS 2-MS 3策略的交叉链路搜索算法遵循“以MS 2为中心”的方法，并且遭受高错误识别率的交叉链路。我们证明了问题，使用两个新的质量评估指标[“错误识别分数”（FMI）和“已知相互作用的蛋白质间交联分数”（FKI）]。然后，我们解决这个问题，通过设计一种新的“以MS 3为中心”的交叉链接识别方法，并将其实现为一个名为MaXLinker的搜索引擎。MaXLinker优于目前流行的搜索引擎，具有更低的错误识别率，更高的灵敏度和特异性。此外，我们使用K562细胞进行了人蛋白质组范围的交联质谱。采用MaXLinker，我们以1%的错误发现率鉴定了9319个独特的交联，包括8051个蛋白内交联和1268个蛋白间交联。最后，我们通过实验验证了我们研究中发现的大量新型相互作用的质量，为MaXLinker的强大性能提供了确凿的证据。
Protein-protein interactions play a vital role in nearly all cellular functions. Hence, understanding their interaction patterns and three-dimensional structural conformations can provide crucial insights about various biological processes and underlying molecular mechanisms for many disease phenotypes. Cross-linking mass spectrometry (XL-MS) has the unique capability to detect protein-protein interactions at a large scale along with spatial constraints between interaction partners. The inception of MS-cleavable cross-linkers enabled the MS2-MS3 XL-MS acquisition strategy that provides cross-link information from both MS2 and MS3 level. However, the current cross-link search algorithm available for MS2-MS3 strategy follows a “MS2-centric” approach and suffers from a high rate of mis-identified cross-links. We demonstrate the problem using two new quality assessment metrics [“fraction of mis-identifications” (FMI) and “fraction of interprotein cross-links from known interactions” (FKI)]. We then address this problem, by designing a novel “MS3-centric” approach for cross-link identification and implementing it as a search engine named MaXLinker. MaXLinker outperforms the currently popular search engine with a lower mis-identification rate, and higher sensitivity and specificity. Moreover, we performed human proteome-wide cross-linking mass spectrometry using K562 cells. Employing MaXLinker, we identified a comprehensive set of 9319 unique cross-links at 1% false discovery rate, comprising 8051 intraprotein and 1268 interprotein cross-links. Finally, we experimentally validated the quality of a large number of novel interactions identified in our study, providing a conclusive evidence for MaXLinker's robust performance.