Benchmarking LFQ, SILAC and MS2/MS3-based TMT quantification strategies for large-scale phosphoproteomics

Comprehensive mass spectrometry (MS)-based proteomics is now feasible, but reproducible and multiplexed quantification remains challenging especially for analysis of post-translational modifications (PTMs), such as phosphorylation. Here we compared the most popular quantification techniques for phosphoproteomics in context of cell-signaling studies: label-free quantification (LFQ), stable isotope labeling by amino acids in cell culture (SILAC) and MS2- and MS3-measured tandem mass tags (TMT). In a mixed species comparison with fixed phosphopeptide-ratios, we found LFQ and SILAC to be the most accurate techniques. MS2-based TMT suffered from substantial ratio compression, which MS3-based TMT could partly rescue. However, when analyzing phosphoproteome changes in the DNA damage response (DDR), we found that MS3-based TMT was outperformed by MS2-based TMT as it identified most significantly regulated phosphopeptides due to its higher precision and higher number of identifications. Finally, we show that the high accuracy of MS3-based TMT is crucial for determination of phosphorylation site stoichiometry using a novel multiplexing-dependent algorithm.

基于质谱（MS）的全蛋白质组学研究现已具备可行性，但可重现且支持多路复用的定量分析仍面临诸多挑战，尤其是针对磷酸化等翻译后修饰（PTMs）的分析场景。本研究针对细胞信号转导研究场景下的磷酸化蛋白质组学常用定量技术展开对比，涵盖无标记定量（LFQ）、细胞培养氨基酸稳定同位素标记（SILAC），以及基于MS2和MS3级质谱检测的串联质量标签（TMT）。在固定磷酸肽比例的混合物种对照实验中，我们发现LFQ与SILAC是定量准确性最高的技术。基于MS2级的TMT存在显著的比例压缩问题，而基于MS3级的TMT可部分缓解该缺陷。然而在分析DNA损伤应答（DDR）过程中的磷酸化蛋白质组变化时，基于MS2级的TMT表现更优：因其具备更高的定量精度与更多的鉴定数目，故而可鉴定出数量最多的显著调控磷酸肽。最后，本研究证实，借助一种新型的多路复用依赖型算法，基于MS3级的TMT所具备的高定量准确性，对于测定磷酸化位点的化学计量比至关重要。