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Improving Phosphoproteomics Profiling Using Data-Independent Mass Spectrometry

Aparna Srinivasan, Justin Sing, Anne‐Claude Gingras, Hannes Röst

2022Journal of Proteome Research23 citationsDOI

Abstract

Mass spectrometry-based profiling of the phosphoproteome is a powerful method of identifying phosphorylation events at a systems level. Most phosphoproteomics studies have used data-dependent acquisition (DDA) mass spectrometry as their method of choice. In this Perspective, we review some recent studies benchmarking DDA and DIA methods for phosphoproteomics and discuss data analysis options for DIA phosphoproteomics. In order to evaluate the impact of data-dependent and data-independent acquisition (DIA) on identification and quantification, we analyze a previously published phosphopeptide-enriched data set consisting of 10 replicates acquired by DDA and DIA each. We find that though more unique identifications are made in DDA data, phosphopeptides are identified more consistently across replicates in DIA. We further discuss the challenges of identifying chromatographically coeluting phosphopeptide isomers and investigate the impact on reproducibility of identifying high-confidence site-localized phosphopeptides in replicates.

Topics & Concepts

PhosphoproteomicsPhosphopeptideMass spectrometryProfiling (computer programming)Computational biologyChemistryComputer scienceProteomicsChromatographyData miningProtein phosphorylationBiologyPhosphorylationBiochemistryProtein kinase AGeneOperating systemAdvanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and ApplicationsMetabolomics and Mass Spectrometry Studies
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