Linked Life Data

17402769

Source:http://linkedlifedata.com/resource/pubmed/id/17402769

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2007-5-4
pubmed:abstractText
Protein phosphorylation is a key post-translational modification that governs biological processes. Despite the fact that a number of analytical strategies have been exploited for the characterization of protein phosphorylation, the identification of protein phosphorylation sites is still challenging. We proposed here an alternative approach to mine phosphopeptide signals generated from a mixture of proteins when liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis is involved. The approach combined dephosphorylation reaction, accurate mass measurements from a quadrupole/time-of-flight mass spectrometer, and a computing algorithm to differentiate possible phosphopeptide signals obtained from the LC-MS analyses by taking advantage of the mass shift generated by alkaline phosphatase treatment. The retention times and m/z values of these selected LC-MS signals were used to facilitate subsequent LC-MS/MS experiments for phosphorylation site determination. Unlike commonly used neutral loss scan experiments for phosphopeptide detection, this strategy may not bias against tyrosine-phosphorylated peptides. We have demonstrated the applicability of this strategy to sequence more, in comparison with conventional data-dependent LC-MS/MS experiments, phosphopeptides in a mixture of alpha- and beta-caseins. The analytical scheme was applied to characterize the nasopharyngeal carcinoma (NPC) cellular phosphoproteome and yielded 221 distinct phosphorylation sites. Our data presented in this paper demonstrated the merits of computation in mining phosphopeptide signals from a complex mass spectrometric data set.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1535-3893
pubmed:author
pubmed:issnType
Print
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1812-21
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Mining phosphopeptide signals in liquid chromatography-mass spectrometry data for protein phosphorylation analysis.
pubmed:affiliation
Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't