Optimized Workflow for Multiplexed Phosphorylation Analysis of TMT-Labeled Peptides Using High-Field Asymmetric Waveform Ion Mobility Spectrometry

Phosphorylation is a post-translational modification with a vital role in cellular signaling. Isobaric labeling-based strategies, such as tandem mass tags (TMT), can measure the relative phosphorylation states of peptides in a multiplexed format. However, the low stoichiometry of protein phosphoryla...

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Bibliographic Details
Published in:Journal of proteome research 2020-01, Vol.19 (1), p.554-560
Main Authors: Schweppe, Devin K, Rusin, Scott F, Gygi, Steven P, Paulo, Joao A
Format: Article
Language:English
Subjects:
Ion Mobility Spectrometry - instrumentation
Ion Mobility Spectrometry - methods
Phosphopeptides - analysis
Phosphopeptides - chemistry
Phosphopeptides - metabolism
Phosphorylation
Proteomics - instrumentation
Proteomics - methods
Workflow
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Summary:Phosphorylation is a post-translational modification with a vital role in cellular signaling. Isobaric labeling-based strategies, such as tandem mass tags (TMT), can measure the relative phosphorylation states of peptides in a multiplexed format. However, the low stoichiometry of protein phosphorylation constrains the depth of phosphopeptide analysis by mass spectrometry. As such, robust and sensitive workflows are required. Here we evaluate and optimize high-Field Asymmetric waveform Ion Mobility Spectrometry (FAIMS) coupled to Orbitrap Tribrid mass spectrometers for the analysis of TMT-labeled phosphopeptides. We determined that using FAIMS-MS3 with three compensation voltages (CV) in a single method (e.g., CV = −40/–60/–80 V) maximizes phosphopeptide coverage while minimizing inter-CV overlap. Furthermore, consecutive analyses using MSA-CID (multistage activation collision-induced dissociation) and HCD (higher-energy collisional dissociation) fragmentation at the MS2 stage increases the depth of phosphorylation analysis. The methodology and results outlined herein provide a template for tailoring optimized FAIMS-based methods.
ISSN:1535-3893
1535-3907
DOI:10.1021/acs.jproteome.9b00759