A data-independent acquisition-based global phosphoproteomics system enables deep profiling.
Reta Birhanu KitataWai-Kok ChoongChia-Feng TsaiPei-Yi LinBo-Shiun ChenYun-Chien ChangAlexey I NesvizhskiiTing-Yi SungYi-Ju ChenPublished in: Nature communications (2021)
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.
Keyphrases
- electronic health record
- drug resistant
- mass spectrometry
- big data
- multidrug resistant
- high resolution
- optical coherence tomography
- gene expression
- induced apoptosis
- acinetobacter baumannii
- data analysis
- single cell
- poor prognosis
- liquid chromatography
- machine learning
- magnetic resonance
- gas chromatography
- ms ms
- endoplasmic reticulum stress
- capillary electrophoresis