Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark.
Anal Chem. 2015 Jun 16;87(12):6319-27. doi: 10.1021/acs.analchem.5b01166. Epub 2015 Jun 3.
SuperQuant is a quantitative proteomics data processing approach that uses complementary fragment ions to identify multiple coisolated peptides in tandem mass spectra allowing for their quantification. This approach can be applied to any shotgun proteomics data set acquired with high mass accuracy for quantification at the MS(1) level. The SuperQuant approach was developed and implemented as a processing node within the Thermo Proteome Discoverer 2.x. The performance of the developed approach was tested using dimethyl-labeled HeLa lysate samples having a ratio between channels of 10(heavy):4(medium):1(light). Peptides were fragmented with collision-induced dissociation using isolation windows of 1, 2, and 4 Th while recording data both with high-resolution and low-resolution. The results obtained using SuperQuant were compared to those using the conventional ion trap-based approach (low mass accuracy MS(2) spectra), which is known to achieve high identification performance. Compared to the common high-resolution approach, the SuperQuant approach identifies up to 70% more peptide-spectrum matches (PSMs), 40% more peptides, and 20% more proteins at the 0.01 FDR level. It identifies more PSMs and peptides than the ion trap-based approach. Improvements in identifications resulted in up to 10% more PSMs, 15% more peptides, and 10% more proteins quantified on the same raw data. The developed approach does not affect the accuracy of the quantification and observed coefficients of variation between replicates of the same proteins were close to the values typical for other precursor ion-based quantification methods. The raw data is deposited to ProteomeXchange (PXD001907). The developed node is available for testing at https://github.com/caetera/SuperQuantNode.
SuperQuant 是一种定量蛋白质组学数据处理方法，它使用互补的片段离子来识别串联质谱中多个共分离的肽，从而实现其定量。这种方法可以应用于任何具有高质量准确度的 shotgun 蛋白质组学数据集，用于在 MS(1) 水平进行定量。SuperQuant 方法是作为 Thermo Proteome Discoverer 2.x 中的一个处理节点开发和实现的。该方法的性能使用具有 10(重):4(中):1(轻)通道比的二甲基标记 HeLa 溶胞产物样品进行了测试。使用 1、2 和 4 Th 的隔离窗口进行碰撞诱导解离来碎片化肽，同时使用高分辨率和低分辨率记录数据。使用 SuperQuant 获得的结果与使用常规基于离子阱的方法（低质量准确度 MS(2) 谱）进行了比较，后者已知具有较高的鉴定性能。与常见的高分辨率方法相比，SuperQuant 方法在 FDR 为 0.01 的水平上可识别多达 70%的肽谱匹配 (PSM)、40%的肽和 20%的蛋白质。与基于离子阱的方法相比，它可以识别更多的 PSM 和肽。鉴定方面的改进导致在相同的原始数据上定量的 PSM 增加了 10%，肽增加了 15%，蛋白质增加了 10%。该方法不会影响定量的准确性，并且观察到相同蛋白质重复之间的变异系数接近其他基于前体离子的定量方法的典型值。原始数据已存储在 ProteomeXchange（PXD001907）中。开发的节点可在 https://github.com/caetera/SuperQuantNode 上进行测试。
