Chen Zhuo A, Fischer Lutz, Cox Jürgen, Rappsilber Juri
From the ‡Wellcome Trust Centre for Cell Biology, Institute of Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3BF, UK;
§Computational Systems Biochemistry, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany;
Mol Cell Proteomics. 2016 Aug;15(8):2769-78. doi: 10.1074/mcp.M115.056481. Epub 2016 Jun 14.
The conceptually simple step from cross-linking/mass spectrometry (CLMS) to quantitative cross-linking/mass spectrometry (QCLMS) is compounded by technical challenges. Currently, quantitative proteomics software is tightly integrated with the protein identification workflow. This prevents automatically quantifying other m/z features in a targeted manner including those associated with cross-linked peptides. Here we present a new release of MaxQuant that permits starting the quantification process from an m/z feature list. Comparing the automated quantification to a carefully manually curated test set of cross-linked peptides obtained by cross-linking C3 and C3b with BS(3) and isotope-labeled BS(3)-d4 revealed a number of observations: (1) Fully automated process using MaxQuant can quantify cross-links in our reference data set with 68% recall rate and 88% accuracy. (2) Hidden quantification errors can be converted into exposed failures by label-swap replica, which makes label-swap replica an essential part of QCLMS. (3) Cross-links that failed during automated quantification can be recovered by semi-automated re-quantification. The integrated workflow of MaxQuant and semi-automated assessment provides the maximum of quantified cross-links. In contrast, work on larger data sets or by less experienced users will benefit from full automation in MaxQuant.
从交联/质谱分析（CLMS）到定量交联/质谱分析（QCLMS），概念上简单的一步却因技术挑战而变得复杂。目前，定量蛋白质组学软件与蛋白质鉴定工作流程紧密集成。这使得无法以靶向方式自动定量其他质荷比特征，包括与交联肽相关的特征。在此，我们展示了MaxQuant的一个新版本，它允许从质荷比特征列表开始定量过程。将自动定量与通过用双（磺基琥珀酰亚胺）辛二酸酯（BS(3)）和同位素标记的双（磺基琥珀酰亚胺）辛二酸酯-d4（BS(3)-d4）交联C3和C3b获得的一组精心手动整理的交联肽测试集进行比较，得到了一些观察结果：（1）使用MaxQuant的全自动化过程能够以68%的召回率和88%的准确率对我们参考数据集中的交联进行定量。（2）隐藏的定量误差可通过标记交换复制品转化为明显的失败情况，这使得标记交换复制品成为QCLMS的一个重要部分。（3）自动定量过程中失败的交联可通过半自动重新定量来恢复。MaxQuant的集成工作流程和半自动评估提供了最多的定量交联。相比之下，处理更大数据集或经验较少的用户将受益于MaxQuant中的全自动化。
