Tandem mass tag (TMT)-based liquid chromatography-tandem mass spectrometry (LC–MS/MS) is a proven approach for large-scale multiplexed protein quantification. However, the identification of TMT-labeled peptides is compromised by the labeling during traditional sequence database searches. In this study, we aim to use a spectral library search to increase the sensitivity and specificity of peptide identification for TMT-based MS data. Compared to MS/MS spectra of unlabeled peptides, the spectra of TMT-labeled counterparts usually display intensified b ions, suggesting that TMT labeling can alter product ion patterns during MS/MS fragementation. We compiled a human TMT spectral library of 401,168 unique peptides of high quality from millions of peptide-spectrum matches in tens of profiling projects, matching to 14,048 nonredundant proteins (13,953 genes). A mouse TMT spectral library of similar size was also constructed. The libraries were subsequently appended with decoy spectra to evaluate the false discovery rate, which was validated by a simulated null TMT data set. The performance of the library search was further optimized by removing TMT reporter ions and selecting an appropriate library construction method. Finally, we searched a human TMT data set against the spectral library to demonstrate that the spectral library outperformed the sequence database. Both human and mouse TMT libraries were made publicly available to the research community.

中文翻译：

---

光谱库搜索可改善TMT标记的MS / MS光谱的分配

基于串联质谱（TMT）的液相色谱-串联质谱（LC-MS / MS）是一种用于大规模多重蛋白质定量的行之有效的方法。但是，在传统序列数据库搜索过程中，标记会损害TMT标记的肽的识别。在这项研究中，我们旨在使用光谱库搜索来提高针对基于TMT的MS数据进行肽鉴定的敏感性和特异性。与未标记肽段的MS / MS谱图相比，TMT标记对应物的谱图通常显示出增强的b离子，表明TMT标记可以在MS / MS裂解过程中改变产物离子模式。我们从数十个分析项目中的数百万个肽谱匹配中，编译了高质量的401,168个独特肽的人TMT光谱库，与14,048个非冗余蛋白（13,953个基因）匹配。还构建了大小相似的小鼠TMT光谱库。这些库随后附加了诱饵光谱以评估错误发现率，该错误发现率已通过模拟的空TMT数据集进行了验证。通过去除TMT报告离子并选择合适的文库构建方法，进一步优化了文库搜索的性能。最后，我们针对光谱库搜索了人类TMT数据集，以证明光谱库的性能优于序列数据库。