Research article summary (published 30 Aug 2009):

A MS data search method for improved 15N-labeled protein identification.

Full Abstract

Quantitative proteomics using stable isotope labeling strategies combined with MS is an important tool for biomarker discovery. Methods involving stable isotope metabolic labeling result in optimal quantitative accuracy, since they allow the immediate combination of two or more samples. Unfortunately, stable isotope incorporation rates in metabolic labeling experiments using mammalian organisms usually do not reach 100%. As a consequence, protein identifications in (15)N database searches have poor success rates. We report on a strategy that significantly improves the number of (15)N-labeled protein identifications and results in a more comprehensive and accurate relative peptide quantification workflow.

Author information

Author/s: Zhang, Yaoyang (Y); Webhofer, Christian (C); Reckow, Stefan (S); Filiou, Michaela D (MD); Maccarrone, Giuseppina (G); Turck, Christoph W (CW);

Affiliation: Max Planck Institute of Psychiatry, Proteomics and Biomarkers, Munich, Germany.

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Proteomics (Proteomics), published in Germany. (Language: eng)

Reference: 2009-Sep; vol 9 (issue 17) : pp 4265-70

Dates: Created 2009/09/07; Completed 2009/11/04;

PMID: 19722194, status: MEDLINE (last retrieval date: 11/4/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Amino Acid Sequence Animals Databases, Protein Isotope Labeling - methods Mass Spectrometry - methods

Mice Molecular Sequence Data Nitrogen Isotopes Peptides - analysis; chemistry Proteins - analysis; chemistry

Associated Chemicals: Nitrogen Isotopes (0) ; Peptides (0) ; Proteins (0)

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