Artikel ; Online: Proteomic Analysis of Adenovirus 5 by UHPLC-MS/MS: Development of a Robust and Reproducible Sample Preparation Workflow.
ACS omega
2022 Band 7, Heft 41, Seite(n) 36825–36835
Abstract: Adenoviruses (AdVs) have recently become widely used therapeutic vectors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine. AdVs are large, nonenveloped viruses with an icosahedral capsid formed from several proteins that encloses ... ...
Abstract | Adenoviruses (AdVs) have recently become widely used therapeutic vectors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine. AdVs are large, nonenveloped viruses with an icosahedral capsid formed from several proteins that encloses double-stranded DNA. These proteins are the main components and key players in initial stages of infection by the virus particles, so their heterogeneity and content must be evaluated to ensure product and process consistency. Peptide mapping can provide detailed information on these proteins, e.g., their amino acid sequences and post-translational modifications (PTMs), which is crucial for the development and optimization of the manufacturing processes. However, sample preparation remains the main bottleneck for successful proteomic analysis of the viral proteins (VPs) of AdVs due to their low concentrations and vast stoichiometric ranges. To address this problem, we have developed a fast and efficient protocol for preparing samples for proteomic analysis of VPs of AdV5 that requires no cleaning step prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS). The approach enabled identification of 92% of amino acids in AdV5 VPs on average and quantification of 53 PTMs in a single LC-MS/MS experiment using trypsin protease. The data obtained demonstrate the method's potential utility for supporting the development of novel AdV-based gene therapy products (GTPs). |
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Sprache | Englisch |
Erscheinungsdatum | 2022-10-05 |
Erscheinungsland | United States |
Dokumenttyp | Journal Article |
ISSN | 2470-1343 |
ISSN (online) | 2470-1343 |
DOI | 10.1021/acsomega.2c05325 |
Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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