Chair of Bioanalytics, Institute of Biotechnology, Technische Universität Berlin , 13355 Berlin, Germany.
Wellcome Trust Centre for Cell Biology, University of Edinburgh , Edinburgh EH9 3BF, United Kingdom.
Anal Chem. 2017 May 16;89(10):5311-5318. doi: 10.1021/acs.analchem.6b04935. Epub 2017 Apr 26.
We compared the five different ways of fragmentation available on a tribrid mass spectrometer and optimized their collision energies with regard to optimal sequence coverage of cross-linked peptides. We created a library of bis(sulfosuccinimidyl)suberate (BS3/DSS) cross-linked precursors, derived from the tryptic digests of three model proteins (Human Serum Albumin, creatine kinase, and myoglobin). This enabled in-depth targeted analysis of the fragmentation behavior of 1065 cross-linked precursors using the five fragmentation techniques: collision-induced dissociation (CID), beam-type CID (HCD), electron-transfer dissociation (ETD), and the combinations ETciD and EThcD. EThcD gave the best sequence coverage for cross-linked m/z species with high charge density, while HCD was optimal for all others. We tested the resulting data-dependent decision tree against collision energy-optimized single methods on two samples of differing complexity (a mix of eight proteins and a highly complex ribosomal cellular fraction). For the high complexity sample the decision tree gave the highest number of identified cross-linked peptide pairs passing a 5% false discovery rate (on average ∼21% more than the second best, HCD). For the medium complexity sample, the higher speed of HCD proved decisive. Currently, acquisition speed plays an important role in allowing the detection of cross-linked peptides against the background of linear peptides. Enrichment of cross-linked peptides will reduce this role and favor methods that provide spectra of higher quality. Data are available via ProteomeXchange with identifier PXD006131.
我们比较了三种串联质谱仪上的五种不同的碎片化方式,并针对交联肽的最佳序列覆盖度优化了它们的碰撞能量。我们创建了一个双(磺基琥珀酰亚胺基)丁二酸酯(BS3/DSS)交联前体库,这些前体是由三种模型蛋白(人血清白蛋白、肌酸激酶和肌红蛋白)的胰蛋白酶消化物衍生而来。这使得我们能够使用五种碎片化技术(碰撞诱导解离(CID)、束型 CID(HCD)、电子转移解离(ETD)以及 ETciD 和 EThcD 组合)对 1065 个交联前体的碎片化行为进行深入的靶向分析。EThcD 对高电荷密度的交联 m/z 物种具有最佳的序列覆盖度,而 HCD 则对所有其他物种最佳。我们在两个复杂度不同的样本(一种混合了八种蛋白质和一种高度复杂的核糖体细胞级分)上测试了由此产生的数据依赖决策树与经过碰撞能量优化的单一方法。对于高复杂度样本,决策树的鉴定通过 5%假发现率的交联肽对数量最多(平均比第二好的方法 HCD 多约 21%)。对于中等复杂度的样本,HCD 的更高速度证明是决定性的。目前,采集速度在允许在线性肽背景下检测交联肽方面起着重要作用。交联肽的富集将减少这种作用,并有利于提供更高质量谱的方法。数据可通过 ProteomeXchange 以标识符 PXD006131 获取。