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MethylQuant: A Tool for Sensitive Validation of Enzyme-Mediated Protein Methylation Sites from Heavy-Methyl SILAC Data.
Tay, Aidan P; Geoghegan, Vincent; Yagoub, Daniel; Wilkins, Marc R; Hart-Smith, Gene.
Afiliação
  • Tay AP; NSW Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales , Sydney, New South Wales 2052, Australia.
  • Geoghegan V; Centre for Immunology and Infection, University of York , Heslington, York YO10 5DD, United Kingdom.
  • Yagoub D; NSW Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales , Sydney, New South Wales 2052, Australia.
  • Wilkins MR; NSW Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales , Sydney, New South Wales 2052, Australia.
  • Hart-Smith G; NSW Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales , Sydney, New South Wales 2052, Australia.
J Proteome Res ; 17(1): 359-373, 2018 01 05.
Article em En | MEDLINE | ID: mdl-29057651
ABSTRACT
The study of post-translational methylation is hampered by the fact that large-scale LC-MS/MS experiments produce high methylpeptide false discovery rates (FDRs). The use of heavy-methyl stable isotope labeling by amino acids in cell culture (heavy-methyl SILAC) can drastically reduce these FDRs; however, this approach is limited by a lack of heavy-methyl SILAC compatible software. To fill this gap, we recently developed MethylQuant. Here, using an updated version of MethylQuant, we demonstrate its methylpeptide validation and quantification capabilities and provide guidelines for its best use. Using reference heavy-methyl SILAC data sets, we show that MethylQuant predicts with statistical significance the true or false positive status of methylpeptides in samples of varying complexity, degree of methylpeptide enrichment, and heavy to light mixing ratios. We introduce methylpeptide confidence indicators, MethylQuant Confidence and MethylQuant Score, and demonstrate their strong performance in complex samples characterized by a lack of methylpeptide enrichment. For these challenging data sets, MethylQuant identifies 882 of 1165 true positive methylpeptide spectrum matches (i.e., >75% sensitivity) at high specificity (<2% FDR) and achieves near-perfect specificity at 41% sensitivity. We also demonstrate that MethylQuant produces high accuracy relative quantification data that are tolerant of interference from coeluting peptide ions. Together MethylQuant's capabilities provide a path toward routine, accurate characterizations of the methylproteome using heavy-methyl SILAC.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Proteína Pós-Traducional / Proteômica / Metilação Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: J Proteome Res Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Proteína Pós-Traducional / Proteômica / Metilação Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: J Proteome Res Ano de publicação: 2018 Tipo de documento: Article