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Profiling SARS-CoV-2 Infection by High-Throughput Shotgun Proteomics.
Grenga, Lucia; Gouveia, Duarte; Armengaud, Jean.
  • Grenga L; Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France.
  • Gouveia D; Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France.
  • Armengaud J; Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France. jean.armengaud@cea.fr.
Methods Mol Biol ; 2452: 167-182, 2022.
Article in English | MEDLINE | ID: covidwho-1844266
ABSTRACT
A comprehensive cartography of viral and host proteins expressed during the different stages of SARS-CoV-2 infection is key to decipher the molecular mechanisms of pathogenesis. For the most detailed analysis, proteins should be first purified and then proteolyzed with trypsin in the presence of detergents. The resulting peptide mixtures are resolved by reverse phase ultrahigh pressure liquid chromatography and then identified by a high-resolution tandem mass spectrometer. The thousands of spectra acquired for each fraction can then be assigned to peptide sequences using a relevant protein sequence database, comprising viral and host proteins and potential contaminants from the growth medium or from the operator. The peptides are evidencing proteins and their intensities are used to infer the abundance of their corresponding proteins. Data analysis allows for highlighting the viral and host proteins dynamics. Here, we describe the sample preparation method adapted to profile SARS-CoV-2 -infected cell models, the shotgun proteomics pipeline to record experimental data, and the workflow for data interpretation to analyze infection-induced proteomic changes in a time-resolved manner.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Proteomics / COVID-19 Limits: Humans Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2022 Document Type: Article Affiliation country: 978-1-0716-2111-0_11

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Proteomics / COVID-19 Limits: Humans Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2022 Document Type: Article Affiliation country: 978-1-0716-2111-0_11