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- Publisher Website: 10.1021/acs.analchem.0c02148
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- PMID: 32628467
- WOS: WOS:000558761500074
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Article: rPTMDetermine: A Fully Automated Methodology for Endogenous Tyrosine Nitration Validation, Site-Localization, and Beyond
Title | rPTMDetermine: A Fully Automated Methodology for Endogenous Tyrosine Nitration Validation, Site-Localization, and Beyond |
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Authors | |
Keywords | Peptide identification Peptides and proteins Organic reactions Biological databases Ions |
Issue Date | 2020 |
Publisher | American Chemical Society. The Journal's web site is located at http://pubs.acs.org/ac |
Citation | Analytical Chemistry, 2020, v. 92 n. 15, p. 10768-10776 How to Cite? |
Abstract | We present herein rPTMDetermine, an adaptive and fully automated methodology for validation of the identification of rarely occurring post-translational modifications (PTMs), using a semisupervised approach with a linear discriminant analysis (LDA) algorithm. With this strategy, verification is enhanced through similarity scoring of tandem mass spectrometry (MS/MS) comparisons between modified peptides and their unmodified analogues. We applied rPTMDetermine to (1) perform fully automated validation steps for modified peptides identified from an in silico database and (2) retrieve potential yet-to-be-identified modified peptides from raw data (that had been missed through conventional database searches). In part (1), 99 of 125 3-nitrotyrosyl-containing (nitrated) peptides obtained from a ProteinPilot search were validated and localized. Twenty nitrated peptides were falsely assigned because of incorrect monoisotopic peak assignments, leading to erroneous identification of deamidation and nitration. Five additional nitrated peptides were, however, validated after performing nonmonoisotopic peak correction. In part (2), an additional 236 unique nitrated peptides were retrieved and localized, containing 113 previously unreported nitration sites; 25 endogenous nitrated peptides with novel sites were selected and verified by comparison with synthetic analogues. In summary, we identified and confidently validated 296 unique nitrated peptides—collectively representing the largest number of endogenously identified 3-nitrotyrosyl-containing peptides from the cerebral cortex proteome of a Macaca fascicularis model of stroke. Furthermore, we harnessed the rPTMDetermine strategy to complement conventional database searching and enhance the confidence of assigning rarely occurring PTMs, while recovering many missed peptides. In a final demonstration, we successfully extended the application of rPTMDetermine to peptides featuring tryptophan oxidation. |
Persistent Identifier | http://hdl.handle.net/10722/284019 |
ISSN | 2023 Impact Factor: 6.7 2023 SCImago Journal Rankings: 1.621 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Dong, N | - |
dc.contributor.author | Spencer, DM | - |
dc.contributor.author | Quan, Q | - |
dc.contributor.author | Le Blanc, JCY | - |
dc.contributor.author | Feng, J | - |
dc.contributor.author | LI, M | - |
dc.contributor.author | Siu, KWM | - |
dc.contributor.author | Chu, IK | - |
dc.date.accessioned | 2020-07-20T05:55:22Z | - |
dc.date.available | 2020-07-20T05:55:22Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Analytical Chemistry, 2020, v. 92 n. 15, p. 10768-10776 | - |
dc.identifier.issn | 0003-2700 | - |
dc.identifier.uri | http://hdl.handle.net/10722/284019 | - |
dc.description.abstract | We present herein rPTMDetermine, an adaptive and fully automated methodology for validation of the identification of rarely occurring post-translational modifications (PTMs), using a semisupervised approach with a linear discriminant analysis (LDA) algorithm. With this strategy, verification is enhanced through similarity scoring of tandem mass spectrometry (MS/MS) comparisons between modified peptides and their unmodified analogues. We applied rPTMDetermine to (1) perform fully automated validation steps for modified peptides identified from an in silico database and (2) retrieve potential yet-to-be-identified modified peptides from raw data (that had been missed through conventional database searches). In part (1), 99 of 125 3-nitrotyrosyl-containing (nitrated) peptides obtained from a ProteinPilot search were validated and localized. Twenty nitrated peptides were falsely assigned because of incorrect monoisotopic peak assignments, leading to erroneous identification of deamidation and nitration. Five additional nitrated peptides were, however, validated after performing nonmonoisotopic peak correction. In part (2), an additional 236 unique nitrated peptides were retrieved and localized, containing 113 previously unreported nitration sites; 25 endogenous nitrated peptides with novel sites were selected and verified by comparison with synthetic analogues. In summary, we identified and confidently validated 296 unique nitrated peptides—collectively representing the largest number of endogenously identified 3-nitrotyrosyl-containing peptides from the cerebral cortex proteome of a Macaca fascicularis model of stroke. Furthermore, we harnessed the rPTMDetermine strategy to complement conventional database searching and enhance the confidence of assigning rarely occurring PTMs, while recovering many missed peptides. In a final demonstration, we successfully extended the application of rPTMDetermine to peptides featuring tryptophan oxidation. | - |
dc.language | eng | - |
dc.publisher | American Chemical Society. The Journal's web site is located at http://pubs.acs.org/ac | - |
dc.relation.ispartof | Analytical Chemistry | - |
dc.rights | This document is the Accepted Manuscript version of a Published Work that appeared in final form in Analytical Chemistry, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/10.1021/acs.analchem.0c02148 | - |
dc.subject | Peptide identification | - |
dc.subject | Peptides and proteins | - |
dc.subject | Organic reactions | - |
dc.subject | Biological databases | - |
dc.subject | Ions | - |
dc.title | rPTMDetermine: A Fully Automated Methodology for Endogenous Tyrosine Nitration Validation, Site-Localization, and Beyond | - |
dc.type | Article | - |
dc.identifier.email | Dong, N: npdong@HKUCC-COM.hku.hk | - |
dc.identifier.email | Spencer, DM: dms305@hku.hk | - |
dc.identifier.email | Chu, IK: ivankchu@hkucc.hku.hk | - |
dc.identifier.authority | Chu, IK=rp00683 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1021/acs.analchem.0c02148 | - |
dc.identifier.pmid | 32628467 | - |
dc.identifier.scopus | eid_2-s2.0-85090823954 | - |
dc.identifier.hkuros | 311061 | - |
dc.identifier.volume | 92 | - |
dc.identifier.issue | 15 | - |
dc.identifier.spage | 10768 | - |
dc.identifier.epage | 10776 | - |
dc.identifier.isi | WOS:000558761500074 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 0003-2700 | - |