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A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products
Terminal amine isotopic labeling of substrates (TAILS), our recently introduced platform for quantitative N-terminome analysis, enables wide dynamic range identification of original mature protein N-termini and protease cleavage products. Modifying TAILS by use of isobaric tag for relative and absol...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
The American Society for Biochemistry and Molecular Biology
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2871423/ https://www.ncbi.nlm.nih.gov/pubmed/20305283 http://dx.doi.org/10.1074/mcp.M000032-MCP201 |
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author | auf dem Keller, Ulrich Prudova, Anna Gioia, Magda Butler, Georgina S. Overall, Christopher M. |
author_facet | auf dem Keller, Ulrich Prudova, Anna Gioia, Magda Butler, Georgina S. Overall, Christopher M. |
author_sort | auf dem Keller, Ulrich |
collection | PubMed |
description | Terminal amine isotopic labeling of substrates (TAILS), our recently introduced platform for quantitative N-terminome analysis, enables wide dynamic range identification of original mature protein N-termini and protease cleavage products. Modifying TAILS by use of isobaric tag for relative and absolute quantification (iTRAQ)-like labels for quantification together with a robust statistical classifier derived from experimental protease cleavage data, we report reliable and statistically valid identification of proteolytic events in complex biological systems in MS2 mode. The statistical classifier is supported by a novel parameter evaluating ion intensity-dependent quantification confidences of single peptide quantifications, the quantification confidence factor (QCF). Furthermore, the isoform assignment score (IAS) is introduced, a new scoring system for the evaluation of single peptide-to-protein assignments based on high confidence protein identifications in the same sample prior to negative selection enrichment of N-terminal peptides. By these approaches, we identified and validated, in addition to known substrates, low abundance novel bioactive MMP-2 targets including the plasminogen receptor S100A10 (p11) and the proinflammatory cytokine proEMAP/p43 that were previously undescribed. |
format | Text |
id | pubmed-2871423 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | The American Society for Biochemistry and Molecular Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-28714232010-05-26 A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products auf dem Keller, Ulrich Prudova, Anna Gioia, Magda Butler, Georgina S. Overall, Christopher M. Mol Cell Proteomics Proteolysis/Degradomics Terminal amine isotopic labeling of substrates (TAILS), our recently introduced platform for quantitative N-terminome analysis, enables wide dynamic range identification of original mature protein N-termini and protease cleavage products. Modifying TAILS by use of isobaric tag for relative and absolute quantification (iTRAQ)-like labels for quantification together with a robust statistical classifier derived from experimental protease cleavage data, we report reliable and statistically valid identification of proteolytic events in complex biological systems in MS2 mode. The statistical classifier is supported by a novel parameter evaluating ion intensity-dependent quantification confidences of single peptide quantifications, the quantification confidence factor (QCF). Furthermore, the isoform assignment score (IAS) is introduced, a new scoring system for the evaluation of single peptide-to-protein assignments based on high confidence protein identifications in the same sample prior to negative selection enrichment of N-terminal peptides. By these approaches, we identified and validated, in addition to known substrates, low abundance novel bioactive MMP-2 targets including the plasminogen receptor S100A10 (p11) and the proinflammatory cytokine proEMAP/p43 that were previously undescribed. The American Society for Biochemistry and Molecular Biology 2010-05 2010-03-20 /pmc/articles/PMC2871423/ /pubmed/20305283 http://dx.doi.org/10.1074/mcp.M000032-MCP201 Text en © 2010 by The American Society for Biochemistry and Molecular Biology, Inc. Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) applies to Author Choice Articles |
spellingShingle | Proteolysis/Degradomics auf dem Keller, Ulrich Prudova, Anna Gioia, Magda Butler, Georgina S. Overall, Christopher M. A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products |
title | A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products |
title_full | A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products |
title_fullStr | A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products |
title_full_unstemmed | A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products |
title_short | A Statistics-based Platform for Quantitative N-terminome Analysis and Identification of Protease Cleavage Products |
title_sort | statistics-based platform for quantitative n-terminome analysis and identification of protease cleavage products |
topic | Proteolysis/Degradomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2871423/ https://www.ncbi.nlm.nih.gov/pubmed/20305283 http://dx.doi.org/10.1074/mcp.M000032-MCP201 |
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