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Data-Independent Acquisition Protease-Multiplexing Enables Increased Proteome Sequence Coverage Across Multiple Fragmentation Modes.
Richards, Alicia L; Chen, Kuei-Ho; Wilburn, Damien B; Stevenson, Erica; Polacco, Benjamin J; Searle, Brian C; Swaney, Danielle L.
Afiliação
  • Richards AL; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, California 94158, United States.
  • Chen KH; J. David Gladstone Institutes, San Francisco, California 94158, United States.
  • Wilburn DB; Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, California 94158, United States.
  • Stevenson E; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, California 94158, United States.
  • Polacco BJ; J. David Gladstone Institutes, San Francisco, California 94158, United States.
  • Searle BC; Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, California 94158, United States.
  • Swaney DL; Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio 43210, United States.
J Proteome Res ; 21(4): 1124-1136, 2022 04 01.
Article em En | MEDLINE | ID: mdl-35234472
ABSTRACT
The use of multiple proteases has been shown to increase protein sequence coverage in proteomics experiments; however, due to the additional analysis time required, it has not been widely adopted in routine data-dependent acquisition (DDA) proteomic workflows. Alternatively, data-independent acquisition (DIA) has the potential to analyze multiplexed samples from different protease digests, but has been primarily optimized for fragmenting tryptic peptides. Here we evaluate a DIA multiplexing approach that combines three proteolytic digests (Trypsin, AspN, and GluC) into a single sample. We first optimize data acquisition conditions for each protease individually with both the canonical DIA fragmentation mode (beam type CID), as well as resonance excitation CID, to determine optimal consensus conditions across proteases. Next, we demonstrate that application of these conditions to a protease-multiplexed sample of human peptides results in similar protein identifications and quantitative performance as compared to trypsin alone, but enables up to a 63% increase in peptide detections, and a 45% increase in nonredundant amino acid detections. Nontryptic peptides enabled noncanonical protein isoform determination and resulted in 100% sequence coverage for numerous proteins, suggesting the utility of this approach in applications where sequence coverage is critical, such as protein isoform analysis.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteoma / Proteômica Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteoma / Proteômica Idioma: En Ano de publicação: 2022 Tipo de documento: Article