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Anal Chem. 2010 Feb 1;82(3):848-58. doi: 10.1021/ac901854k.

Isobaric tagging-based selection and quantitation of cerebrospinal fluid tryptic peptides with reporter calibration curves.

Author information

1
Biomedical Proteomics Group, Department of Structural Biology and Bioinformatics, Faculty of Medicine, University of Geneva, Geneva, Switzerland.

Abstract

In the past few years, mass spectrometry (MS) has emerged as an efficient tool for the multiplexed peptide and protein concentration determination by isotope dilution. Despite the growing use of isobaric tagging to perform relative quantitation for the discovery of potential biomarkers in biological fluids, no real application has so far been presented for their absolute quantitation. Isobaric tandem mass tags (TMTs) were used herein for the selection and quantitation of tryptic peptides derived from brain damage related proteins in cerebrospinal fluid (CSF). Proteotypic tryptic peptide analogues were synthesized, prepared in four reference amounts, differentially labeled with four isobaric TMTs with reporter-ions at m/z = 128.1, 129.1, 130.1, and 131.1, and mixed with CSF sample previously labeled with TMT 126.1. Off-gel electrophoresis (OGE) was used as first-dimension separation of the pooled sample. The resulting fractions were analyzed with reversed-phase liquid chromatography (RP-LC) tandem mass spectrometry (MS/MS), using tandem time-of-flight (TOF/TOF) and hybrid linear ion trap-orbitrap (LTQ-OT) instruments. Under collision-induced dissociation (CID) or higher-energy C-trap dissociation (HCD), the release of the reporter fragments from the TMT-labeled peptide standards provided an internal calibration curve to assess the concentration of these peptides in the CSF. This tool also allowed identifying selectively these peptides in CSF as only the targeted peptides showed specific fragmentation pattern in the TMT reporter-ion zone of the tandem mass spectra. Assays for the concentration measurements of peptides from PARK7, GSTP1, NDKA, and S100B proteins in CSF were further characterized using this novel, efficient, and straightforward approach.

PMID:
20058875
DOI:
10.1021/ac901854k
[Indexed for MEDLINE]

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