Wilkes Edmund, Cutillas Pedro R
Integrative Cell Signalling and Proteomics, Centre for Haemato-Oncology, Barts Cancer Institute, John Vane Science Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
Department of Clinical Biochemistry, University College London Hospitals, NHS Foundation Trust, Whitfield Street, London, UK.
Methods Mol Biol. 2017;1636:199-217. doi: 10.1007/978-1-4939-7154-1_13.
Phosphoproteomics is a powerful platform for the unbiased profiling of kinase-driven signaling pathways. Quantitation of phosphorylation can be performed by means of either labeling or label-free mass spectrometry (MS) methods. Because of their simplicity and universality, label-free methodology is gaining acceptance and popularity in molecular biology research. Analytical workflows for label-free quantification of phosphorylation, however, need to overcome several hurdles for the technique to be accurate and precise. These include the use of biochemical extraction procedures that efficiently and reproducibly isolate phosphopeptides from complex peptide matrices and an analytical strategy that can cope with missing MS/MS phosphopeptide spectra in a subset of the samples being compared. Testing the accuracy of the developed workflows is an essential prerequisite in the analysis of small molecules by MS, and this is achieved by constructing calibration curves to demonstrate linearity of quantification for each analyte. This level of analytical rigor is rarely shown in large-scale quantification of proteins using either label-based or label-free techniques. In this chapter we show an approach to test linearity of quantification of each phosphopeptide quantified by liquid chromatography (LC)-MS without the need to synthesize standards or label proteins. We further describe the appropriate sample handling techniques required for the reproducible recovery of phosphopeptides and explore the essential algorithmic features that enable the handling of missing MS/MS spectra and thus make label-free data suitable for such analyses. The combined technology described in this chapter expands the applicability of phosphoproteomics to questions not previously tractable with other methodologies.
磷酸化蛋白质组学是一种强大的平台，可用于对激酶驱动的信号通路进行无偏分析。磷酸化的定量分析可通过标记或无标记质谱（MS）方法进行。由于其简单性和通用性，无标记方法在分子生物学研究中越来越受到认可和欢迎。然而，用于磷酸化无标记定量的分析工作流程需要克服几个障碍，才能使该技术准确且精确。这些障碍包括使用能从复杂肽基质中高效且可重复地分离磷酸肽的生化提取程序，以及一种能够应对被比较样本子集中缺失的MS/MS磷酸肽谱的分析策略。测试所开发工作流程的准确性是通过MS分析小分子的必要前提，这是通过构建校准曲线来证明每种分析物定量的线性来实现的。在使用基于标记或无标记技术进行蛋白质大规模定量分析中，这种分析严谨性水平很少见。在本章中，我们展示了一种无需合成标准品或标记蛋白质即可测试通过液相色谱（LC）-MS定量的每种磷酸肽定量线性的方法。我们进一步描述了可重复回收磷酸肽所需的适当样本处理技术，并探讨了能够处理缺失MS/MS谱从而使无标记数据适用于此类分析的基本算法特征。本章中描述的组合技术扩展了磷酸化蛋白质组学在以前其他方法难以解决的问题上的适用性。
