Evaluation and Improvement of Quantification Accuracy in Isobaric Mass 
Tag-Based Protein Quantification Experiments

Ahrne, Erik; Glatter, Timo; Vigano, Cristina; von Schubert, Conrad; Nigg, Erich A.; Schmidt, Alexander

doi:10.1021/acs.jproteome.6b00066

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Evaluation and Improvement of Quantification Accuracy in Isobaric Mass Tag-Based Protein Quantification Experiments

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Ahrne, E., Glatter, T., Vigano, C., von Schubert, C., Nigg, E. A., & Schmidt, A. (2016). Evaluation and Improvement of Quantification Accuracy in Isobaric Mass Tag-Based Protein Quantification Experiments. JOURNAL OF PROTEOME RESEARCH, 15(8), 2537-2547. doi:10.1021/acs.jproteome.6b00066.

Cite as: https://hdl.handle.net/21.11116/0000-000C-0429-2

Abstract

The multiplexing capabilities of isobaric mass tag based protein quantification, such as Tandem Mass Tags or Isobaric Tag for Relative and Absolute Quantitation have dramatically increased the scope of mass spectrometry-based proteomics studies. Not only does the technology allow for the simultaneous quantification of multiple samples in a single MS injection, but its seamless compatibility with extensive sample prefractionation methods allows for comprehensive studies of complex proteomes. However, reporter ion-based quantification has often been criticized for limited quantification accuracy due to interference from coeluting peptides and peptide fragments. In this study, we investigate the extent of this problem and propose an effective and easy-to-implement remedy that relies on spiking a 6-protein calibration mixture to the samples. We evaluated our ratio adjustment approach using two large scale TMT 10-plex data sets derived from a human cancer and noncancer cell line as well as E. coli cells grown at two different conditions. Furthermore, we analyzed a complex 2-proteome artificial sample mixture and investigated the precision of TMT and precursor ion intensity-based label free quantification. Studying the protein set identified by both methods, we found that differentially abundant proteins were assigned dramatically higher statistical significance when quantified using TMT. Data are available via ProteomeXchange with identifier PXD003346.