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J Biomol Tech. 2010 September; 21(3 Suppl): S61.
PMCID: PMC2918085

Optimized Quantification and Identification on LTQ Orbitrap using Peptide Labeling with Isobaric Tags

T. Köcher,1 J. Holzmann,1 M. Mazanek,1 T. Taus,1 T. Möhring,4 G. Ammerer,4,5 and P. Pichler3
1Research Institute of Molecular Pathology, Vienna, Austria;
2Institute of Molecular Biotechnology, Vienna, Austria;
3Christian Doppler Laboratory for Proteome Analysis, University of Vienna, Vienna, Austria;
4Thermo Fisher Scientific, Bremen, Germany;
5Max F. Perutz Laboratories, University of Vienna, Vienna, Austria



Important goals of ongoing developments in quantitative proteomics are improved precision of quantification and a high rate of successful peptide identifications. We evaluated both aspects with regard to two types of tryptic digests labeled with isobaric tags: a well-defined protein mixture and a sample derived from two states of HeLa cells. Both an ion trap spectrum and a HCD Orbitrap spectrum were acquired from the four most intense precursor ions. The ion trap spectrum was used for peptide identification. Therefore HCD settings could be chosen freely as the HCD scan served for quantification only. We show that a new HCD cell with an axial field reduced the variability in the quantification of reporter ion areas derived from isobaric tags. The new HCD cell, which is mounted in current LTQ Orbitrap Velos and XL ETD instruments, was designed to push fragment ions into the C-trap for improved transmission and readout. Notably, adequate precision of HCD-based quantification with the new HCD cell is maintained even for low reporter and precursor ion intensities. We further show that the number of peptides and proteins that can be identified in a Mascot search of CID spectra was largest with the use of iTRAQ 4-plex for peptide labeling followed by TMT 6-plex, and smallest with iTRAQ 8-plex. These findings may help labs in the design of quantitative proteomics studies using isobaric tags, and establish HCD-based quantification on the LTQ Orbitrap as an attractive and precise approach in quantitative proteomics.

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