: 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.

Auf Dem Keller, U., Prudova, A., Gioia, M., Butler, G.s., Overall, C.m. (2010). A statistics-based platform for quantitative N-terminome analysis and identification of protease cleavage products. MOLECULAR & CELLULAR PROTEOMICS, 9(5), 912-927 [10.1074/mcp.M000032-MCP201].

A statistics-based platform for quantitative N-terminome analysis and identification of protease cleavage products

Gioia M.;
2010-01-01

Abstract

: 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.
2010
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore BIO/05 - ZOOLOGIA
English
Amino Acid Sequence
Animals
Annexin A2
Catalytic Domain
Isotope Labeling
Matrix Metalloproteinase 2
Mice
Microtubule-Associated Proteins
Models, Biological
Peptide Hydrolases
Reproducibility of Results
S100 Proteins
Sequence Analysis, Protein
Substrate Specificity
Models, Statistical
Protein Processing, Post-Translational
Molecular Sequence Data
Auf Dem Keller, U., Prudova, A., Gioia, M., Butler, G.s., Overall, C.m. (2010). A statistics-based platform for quantitative N-terminome analysis and identification of protease cleavage products. MOLECULAR & CELLULAR PROTEOMICS, 9(5), 912-927 [10.1074/mcp.M000032-MCP201].
Auf Dem Keller, U; Prudova, A; Gioia, M; Butler, Gs; Overall, Cm
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/290451
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