Automated gas-phase purification for accurate, multiplexed quantification on a stand-alone ion-trap mass spectrometer

Catherine E. Vincent, Jarred W. Rensvold, Michael S. Westphall, David J. Pagliarini, Joshua J. Coon

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

Isobaric tagging enables the acquisition of highly multiplexed proteome quantification, but it is hindered by the pervasive problem of precursor interference. The elimination of coisolated contaminants prior to reporter tag generation can be achieved through the use of gas-phase purification via proton transfer ion/ion reactions (QuantMode); however, the original QuantMode technique was implemented on the high-resolution linear ion-trap-Orbitrap hybrid mass spectrometer enabled with electron transfer dissociation (ETD). Here we extend this technology to stand-alone linear ion-trap systems (trapQuantMode, trapQM). Facilitated by the use of inlet beam-type activation (i.e., trapHCD) for production and observation of the low mass-to-charge reporter region, this scan sequence comprises three separate events to maximize peptide identifications, minimize duty cycle requirements, and increase quantitative accuracy, precision, and dynamic range. Significant improvements in quantitative accuracy were attained over standard methods when using trapQM to analyze an interference model system comprising tryptic peptides of yeast that we contaminated with human peptides. Finally, we demonstrate practical benefits of this method by analysis of the proteomic changes that occur during mouse skeletal muscle myoblast differentiation. While the reduced duty cycle of trapQM led to the identification of fewer proteins than conventional operation (4050 vs 2964), trapQM identified more significant differences (>1.5 fold, 1362 vs 1132, respectively; p < 0.05) between the proteomes of undifferentiated myoblasts and differentiated myotubes and nearly 10-fold more differences with changes greater than 5-fold (96 vs 12). We further show that our trapQM dataset is superior for identifying changes in protein abundance that are consistent with the metabolic and structural changes known to accompany myotube formation.

Original languageEnglish
Pages (from-to)2079-2086
Number of pages8
JournalAnalytical Chemistry
Volume85
Issue number4
DOIs
StatePublished - Feb 19 2013
Externally publishedYes

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