A data-independent acquisition-based global phosphoproteomics system enables deep profiling

• Published in: Nature communications Vol. 12; no. 1; p. 2539
• Main Authors: Kitata, Reta Birhanu, Choong, Wai-Kok, Tsai, Chia-Feng, Lin, Pei-Yi, Chen, Bo-Shiun, Chang, Yun-Chien, Nesvizhskii, Alexey I., Sung, Ting-Yi, Chen, Yu-Ju
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 05-05-2021; Nature Publishing Group; Nature Portfolio
• Subjects: 631/1647/296; 631/45/475; 631/67/1612/1350; 631/80/458/1733; 82/16; 82/58; 82/80; 96/95; Biotechnology; Cell Line, Tumor; Coefficient of variation; Depth profiling; Drug resistance; Humanities and Social Sciences; Humans; INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Libraries; Localization; Lung cancer; Lung Neoplasms - metabolism; Mass spectrometry; Mass spectroscopy; MATHEMATICS AND COMPUTING; multidisciplinary; Phosphopeptides - metabolism; Phosphorylation; Proteins - metabolism; Proteome - analysis; Proteomics; Science; Science (multidisciplinary); Sensitivity; Signaling; Spectra; Tandem Mass Spectrometry - methods; Tumor cell lines; Workflow
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-021-22759-z

Phosphoproteomics can provide insights into cellular signaling dynamics. To achieve deep and robust quantitative phosphoproteomics profiling for minute amounts of sample, we here develop a global phosphoproteomics strategy based on data-independent acquisition (DIA) mass spectrometry and hybrid spectral libraries derived from data-dependent acquisition (DDA) and DIA data. Benchmarking the method using 166 synthetic phosphopeptides shows high sensitivity (<0.1 ng), accurate site localization and reproducible quantification (~5% median coefficient of variation). As a proof-of-concept, we use lung cancer cell lines and patient-derived tissue to construct a hybrid phosphoproteome spectral library covering 159,524 phosphopeptides (88,107 phosphosites). Based on this library, our single-shot streamlined DIA workflow quantifies 36,350 phosphosites (19,755 class 1) in cell line samples within two hours. Application to drug-resistant cells and patient-derived lung cancer tissues delineates site-specific phosphorylation events associated with resistance and tumor progression, showing that our workflow enables the characterization of phosphorylation signaling with deep coverage, high sensitivity and low between-run missing values.
Phosphoproteomics can provide systematic insights into disease-associated cell signaling changes. Here, the authors present a sensitive workflow integrating library-based and direct data-independent acquisition approaches, and a hybrid spectral library resource for in-depth phosphoproteomic profiling.