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Analyst. 2010 Oct;135(10):2643-52. doi: 10.1039/c0an00267d. Epub 2010 Aug 10.

Gaining efficiency by parallel quantification and identification of iTRAQ-labeled peptides using HCD and decision tree guided CID/ETD on an LTQ Orbitrap.

Author information

1
Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands.

Abstract

Isobaric stable isotope labeling of peptides using iTRAQ is an important method for MS based quantitative proteomics. Traditionally, quantitative analysis of iTRAQ labeled peptides has been confined to beam-type instruments because of the weak detection capabilities of ion traps for low mass ions. Recent technical advances in fragmentation techniques on linear ion traps and the hybrid linear ion trap-orbitrap allow circumventing this limitation. Namely, PQD and HCD facilitate iTRAQ analysis on these instrument types. Here we report a method for iTRAQ-based relative quantification on the ETD enabled LTQ Orbitrap XL, which is based on parallel peptide quantification and peptide identification. iTRAQ reporter ion generation is performed by HCD, while CID and ETD provide peptide identification data in parallel in the LTQ ion trap. This approach circumvents problems accompanying iTRAQ reporter ion generation with ETD and allows quantitative, decision tree-based CID/ETD experiments. Furthermore, the use of HCD solely for iTRAQ reporter ion read out significantly reduces the number of ions needed to obtain informative spectra, which significantly reduces the analysis time. Finally, we show that integration of this method, both with existing CID and ETD methods as well as with existing iTRAQ data analysis workflows, is simple to realize. By applying our approach to the analysis of the synapse proteome from human brain biopsies, we demonstrate that it outperforms a latest generation MALDI TOF/TOF instrument, with improvements in both peptide and protein identification and quantification. Conclusively, our work shows how HCD, CID and ETD can be beneficially combined to enable iTRAQ-based quantification on an ETD-enabled LTQ Orbitrap XL.

PMID:
20714520
DOI:
10.1039/c0an00267d
[Indexed for MEDLINE]

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