Header

UZH-Logo

Maintenance Infos

An integrated chemical, mass spectrometric and computational strategy for (quantitative) phosphoproteomics: application to Drosophila melanogaster Kc167 cells


Bodenmiller, Bernd; Mueller, Lukas N; Pedrioli, Patrick G A; Pflieger, Delphine; Jünger, Martin A; Eng, Jimmy K; Aebersold, Ruedi; Tao, W Andy (2007). An integrated chemical, mass spectrometric and computational strategy for (quantitative) phosphoproteomics: application to Drosophila melanogaster Kc167 cells. Molecular Biosystems, 3(4):275-286.

Abstract

Current methods for phosphoproteome analysis have several limitations. First, most methods for phosphopeptide enrichment lack the specificity to truly purify phosphopeptides. Second, fragmentation spectra of phosphopeptides, in particular those of phosphoserine and phosphothreonine containing peptides, are often dominated by the loss of the phosphate group(s) and therefore lack the information required to identify the peptide sequence and the site of phosphorylation, and third, sequence database search engines and statistical models for data validation are not optimized for the specific fragmentation properties of phosphorylated peptides. Consequently, phosphoproteomic data are characterized by large and unknown rates of false positive and false negative phosphorylation sites. Here we present an integrated chemical, mass spectrometric and computational strategy to improve the efficiency, specificity and confidence in the identification of phosphopeptides and their site(s) of phosphorylation. Phosphopeptides were isolated with high specificity through a simple derivatization procedure based on phosphoramidate chemistry. Identification of phosphopeptides, their site(s) of phosphorylation and the corresponding phosphoproteins was achieved by the optimization of the mass spectrometric data acquisition procedure, the computational tools for database searching and the data post processing. The strategy was applied to the mapping of phosphorylation sites of a purified transcription factor, dFOXO and for the global analysis of protein phosphorylation of Drosophila melanogaster Kc167 cells.

Abstract

Current methods for phosphoproteome analysis have several limitations. First, most methods for phosphopeptide enrichment lack the specificity to truly purify phosphopeptides. Second, fragmentation spectra of phosphopeptides, in particular those of phosphoserine and phosphothreonine containing peptides, are often dominated by the loss of the phosphate group(s) and therefore lack the information required to identify the peptide sequence and the site of phosphorylation, and third, sequence database search engines and statistical models for data validation are not optimized for the specific fragmentation properties of phosphorylated peptides. Consequently, phosphoproteomic data are characterized by large and unknown rates of false positive and false negative phosphorylation sites. Here we present an integrated chemical, mass spectrometric and computational strategy to improve the efficiency, specificity and confidence in the identification of phosphopeptides and their site(s) of phosphorylation. Phosphopeptides were isolated with high specificity through a simple derivatization procedure based on phosphoramidate chemistry. Identification of phosphopeptides, their site(s) of phosphorylation and the corresponding phosphoproteins was achieved by the optimization of the mass spectrometric data acquisition procedure, the computational tools for database searching and the data post processing. The strategy was applied to the mapping of phosphorylation sites of a purified transcription factor, dFOXO and for the global analysis of protein phosphorylation of Drosophila melanogaster Kc167 cells.

Statistics

Citations

Dimensions.ai Metrics
66 citations in Web of Science®
67 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

0 downloads since deposited on 24 Apr 2013
0 downloads since 12 months

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Molecular Life Sciences
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Life Sciences > Biotechnology
Life Sciences > Molecular Biology
Language:English
Date:2007
Deposited On:24 Apr 2013 11:24
Last Modified:24 Jan 2022 00:51
Publisher:RSC Publishing
ISSN:1742-2051
Additional Information:Persons who receive the PDF must not make it further available or distribute it.
OA Status:Closed
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1039/b617545g
PubMed ID:17372656