A probability-based approach for high-throughput protein phosphorylation analysis and site localization

Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) ( Supplementary Figure 1 online). In this report we address challenges t...

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Bibliographic Details
Published in	Nature biotechnology Vol. 24; no. 10; pp. 1285 - 1292
Main Authors	Beausoleil, Sean A, Villén, Judit, Gerber, Scott A, Rush, John, Gygi, Steven P
Format	Journal Article
Language	English
Published	New York Nature Publishing Group US 01.10.2006 Nature Nature Publishing Group
Subjects	Agriculture Algorithms Analytical, structural and metabolic biochemistry Biochemistry Bioinformatics Biological and medical sciences Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Fundamental and applied biological sciences. Psychology General aspects, investigation methods HeLa Cells - drug effects Humans Image Processing, Computer-Assisted Ions letter Life Sciences Liquid chromatography Mass spectrometry Mass Spectrometry - methods Methods Nocodazole - pharmacology Peptide Mapping - methods Phosphorylation Probability Proteins Scientific imaging Validation Data analysis Phosphorylation Liquid chromatography Method Localization Hela cell line Mass spectrometry Protein
Online Access	Get full text
ISSN	1087-0156 1546-1696
DOI	10.1038/nbt1240

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Abstract	Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) ( Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%.
AbstractList	Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC- MS/MS) (Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%. Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) ( Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%. Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) (Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%.Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) (Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%.
Audience	Academic
Author	Beausoleil, Sean A Rush, John Villén, Judit Gygi, Steven P Gerber, Scott A
Author_xml	– sequence: 1 givenname: Sean A surname: Beausoleil fullname: Beausoleil, Sean A organization: Department of Cell Biology, Harvard Medical School – sequence: 2 givenname: Judit surname: Villén fullname: Villén, Judit organization: Department of Cell Biology, Harvard Medical School – sequence: 3 givenname: Scott A surname: Gerber fullname: Gerber, Scott A organization: Department of Genetics and Norris Cotton Cancer Center – sequence: 4 givenname: John surname: Rush fullname: Rush, John organization: Cell Signaling Technology, Inc – sequence: 5 givenname: Steven P surname: Gygi fullname: Gygi, Steven P email: steven_gygi@hms.harvard.edu organization: Department of Cell Biology, Harvard Medical School
BackLink	http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=18218435$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/16964243$$D View this record in MEDLINE/PubMed
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SubjectTerms	Agriculture Algorithms Analytical, structural and metabolic biochemistry Biochemistry Bioinformatics Biological and medical sciences Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Fundamental and applied biological sciences. Psychology General aspects, investigation methods HeLa Cells - drug effects Humans Image Processing, Computer-Assisted Ions letter Life Sciences Liquid chromatography Mass spectrometry Mass Spectrometry - methods Methods Nocodazole - pharmacology Peptide Mapping - methods Phosphorylation Probability Proteins Scientific imaging
Title	A probability-based approach for high-throughput protein phosphorylation analysis and site localization
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