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Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins.
Ahn, Seong Beom; Kamath, Karthik S; Mohamedali, Abidali; Noor, Zainab; Wu, Jemma X; Pascovici, Dana; Adhikari, Subash; Cheruku, Harish R; Guillemin, Gilles J; McKay, Matthew J; Nice, Edouard C; Baker, Mark S.
Afiliação
  • Ahn SB; Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Macquarie Park, NSW 2109, Australia.
  • Kamath KS; Australian Proteome Analysis Facility (APAF), Department of Molecular Sciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW 2109, Australia.
  • Mohamedali A; Department of Molecular Sciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW 2109, Australia.
  • Noor Z; ProCan, Children's Medical Research Institute, The University of Sydney, Westmead, Newtown, NSW 2042, Australia.
  • Wu JX; Australian Proteome Analysis Facility (APAF), Department of Molecular Sciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW 2109, Australia.
  • Pascovici D; Australian Proteome Analysis Facility (APAF), Department of Molecular Sciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW 2109, Australia.
  • Adhikari S; Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Macquarie Park, NSW 2109, Australia.
  • Cheruku HR; Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Macquarie Park, NSW 2109, Australia.
  • Guillemin GJ; Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Macquarie Park, NSW 2109, Australia.
  • McKay MJ; Australian Proteome Analysis Facility (APAF), Department of Molecular Sciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW 2109, Australia.
  • Nice EC; Department of Biochemistry and Molecular Biology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC 3800, Australia.
  • Baker MS; Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Macquarie Park, NSW 2109, Australia.
J Proteome Res ; 20(5): 2374-2389, 2021 05 07.
Article em En | MEDLINE | ID: mdl-33752330
ABSTRACT
Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteoma / Proteômica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteoma / Proteômica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article