Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, 3584 CH Utrecht, The Netherlands.
Netherlands Proteomics Center, Padualaan 8, 3584 CH Utrecht, The Netherlands.
Nat Commun. 2017 May 19;8:15473. doi: 10.1038/ncomms15473.
We describe optimized fragmentation schemes and data analysis strategies substantially enhancing the depth and accuracy in identifying protein cross-links using non-restricted whole proteome databases. These include a novel hybrid data acquisition strategy to sequence cross-links at both MS2 and MS3 level and a new algorithmic design XlinkX v2.0 for data analysis. As proof-of-concept we investigated proteome-wide protein interactions in E. coli and HeLa cell lysates, respectively, identifying 1,158 and 3,301 unique cross-links at ∼1% false discovery rate. These protein interaction repositories provide meaningful structural information on many endogenous macromolecular assemblies, as we showcase on several protein complexes involved in translation, protein folding and carbohydrate metabolism.
我们描述了优化的片段化方案和数据分析策略,这些方案大大提高了使用非限制的全蛋白质组数据库识别蛋白质交联的深度和准确性。这些策略包括一种新颖的混合数据采集策略,用于在 MS2 和 MS3 水平上对交联进行测序,以及用于数据分析的新算法设计 XlinkX v2.0。作为概念验证,我们分别研究了大肠杆菌和 HeLa 细胞裂解物中的全蛋白质组蛋白相互作用,分别在约 1%的假发现率下鉴定出 1158 个和 3301 个独特的交联。这些蛋白质相互作用库提供了许多内源性大分子组装的有意义的结构信息,我们在几个涉及翻译、蛋白质折叠和碳水化合物代谢的蛋白质复合物上展示了这些信息。