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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
Optimization of protein-level tandem mass tag (TMT) labeling conditions in complex samples with top-down proteomics
Yanting Guo1, Dahang Yu1, Kellye A Cupp-Sutton1
1Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA.
Abstract:
Isobaric chemical tag labels (e.g., iTRAQ and TMT) have been extensively utilized as a standard quantification approach in bottom-up proteomics, which provides high multiplexing capacity and enables MS2-level quantification while not complicating the MS1 scans. We recently demonstrated the feasibility of intact protein TMT labeling for the identification and quantification with top-down proteomics of smaller intact proteoforms (<35 kDa) in complex biological samples through the removal of large proteins prior to labeling. Still, the production of side products during TMT labeling (i.e., incomplete labeling or labeling of unintended residues) complicated the analysis of complex protein samples. In this study, we systematically evaluated the protein-level TMT labeling reaction parameters, including TMT-to-protein mass ratio, pH/concentration of quenching buffer, protein concentration, reaction time, and reaction buffer. Our results indicated that: (1) high TMT-to-protein mass ratio (e.g., 8:1, 4:1), (2) high pH/concentration of quenching buffer (pH > 9.1, final hydroxylamine concentration >0.3%), and (3) high protein concentration (e.g., > 1.0 μg/μL) resulted in optimal labeling efficiency and minimized production of over/underlabeled side products. >90% labeling efficiency was achieved for E. coli cell lysate after optimization of protein-level TMT labeling conditions. In addition, a double labeling approach was developed for efficiently labeling limited biological samples with low concentrations. This research provides practical guidance for efficient TMT labeling of complex intact protein samples, which can be readily adopted in the high-throughput quantification top-down proteomics.

