Optimization of protein-level tandem mass tag (TMT) labeling conditions in complex samples with top-down proteomics

Highlights

• Systematic optimization of protein-level TMT labeling in complex sample.

• > 90% labeling efficiency with optimal conditions.

• Double labeling technique for low concentration samples labeling.

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.

Introduction

The ability to identify and relatively quantify intact proteoforms using quantitative top-down proteomics techniques has enabled the study of diverse biological processes that are mediated by post-translational modifications (PTMs) [1,2]. Various quantitative techniques have been adapted and applied to top-down proteomics, including label-free quantitation, metabolic labeling, and isobaric chemical labeling. However, isobaric chemical tag labeling methods including relative and absolute quantitation (iTRAQ) [3], tandem mass tags (TMT) [4,5], and N, N-dimethylleucine (DiLeu) isobaric tags [6,7] have been widely applied to the quantification of peptides and proteins in bottom-up proteomics studies, the application to top-down proteomics has been limited.

Previously, intact protein-level isobaric tag labeling has been coupled with bottom-up proteomics methods to improve proteome coverage or characterize protein structures. iTRAQ was first applied to protein-level labeling using standard proteins by Wiese et al. to measure the labeling efficiency of intact proteins using matrix-assisted laser desorption ionization-time-of-flight (MALDI-TOF) mass spectrometry analysis [8]. Sinclair et al. further applied protein-level TMT labeling to human serum samples; the TMT labeled proteins were separated using strong anion exchange (SAX) chromatography and digested to achieve a higher proteome coverage [9]. Nie et al. applied isobaric chemical tag labeling for serum glycoprotein quantification and evaluated the effect of various digestion enzymes, isobaric chemical tags, and organic solvents on the identification and quantification of peptides [10]. TMT was also applied to whole cells for protein quantification with combination of enrichment using anti-TMT antibody [11]. Kaiwen et al. also developed a native protein TMT method to profile Lys accessibility and applied it to investigate structural change in Alzheimer's disease brain specimens [12].

Top-down proteomics on protein-level isobaric chemical tag labeled standard proteins has been previously performed by Hung et al.,. [13] however, the application of protein-level isobaric tag labeling to complex samples has been limited. One major challenge has been protein precipitation during labeling due to the presence of organic solvent which limits labeling efficiency. We previously demonstrated that the removal of large proteins by coupling molecular weight cutoff (MWCO) and size exclusion chromatography prevents intact proteins from precipitating under labeling conditions and allows for the identification and quantification of smaller proteoforms (≤35 kDa) in E. coli cell lysate [14]. Moreover, the application of thiol-directed isobaric labeling for quantification and identification using top-down proteomics has also been demonstrated for E. coli and combined E. coli/yeast samples [15].

Another challenge for protein-level TMT labeling is the production of side products (i.e., overlabeled and underlabeled species) during the labeling reaction. Overlabeling (labeling of residues other than lysine or the N-terminal) may occur on residues with side chains containing hydroxyl groups (Ser, Thr, Tyr). Underlabeling (missing labels) may occur on the N-terminal or lysine residues. Over and underlabeling does not have a significant impact on quantification results; however, the side products will decrease the signal-to-noise ratio and increase the sample complexity [8,13].

Recently, the TMT labeling condition for peptides was optimized by Zecha et al. and the impact of labeling reaction parameters was evaluated to achieve >99% labeling efficiency [8]. Considering protein-level labeling is more complicated than peptide-level labeling, it is necessary to optimize protein-level labeling conditions to increase the labeling efficiency. In this study, we systematically optimized the parameters of the protein-level TMT labeling reaction to maximize the production of the completely labeled species. Overall, we evaluated the effect of TMT-to-protein ratio (w/w), labeling reaction conditions (i.e., quenching buffer, reaction time, and reaction buffer), and protein concentration on protein-level TMT labeling efficiency. Our results demonstrated an optimized condition for intact protein-level TMT labeling of complex samples. We also innovated a double labeling strategy as an alternative approach to achieve sufficient labeling efficiency for mass limited samples that did not have adequate concentrations to implement the optimized labeling conditions (e.g., clinical samples).