Dynamic Cellular Proteome Remodeling during SARS-CoV-2 Infection. Identification of Plasma Protein Readouts
The outbreak of COVID-19, led to an ongoing pandemic with devastating consequences for the global economy and human health. With the global spread of SARS-CoV-2, multidisciplinary initiatives were launched to explore new diagnostic, therapeutic, and vaccination strategies. From this perspective, pro...
| Autores: | , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/375788 |
| Acceso en línea: | http://hdl.handle.net/10261/375788 https://api.elsevier.com/content/abstract/scopus_id/85210290299 |
| Access Level: | acceso abierto |
| Palabra clave: | COVID-19 SARS-CoV-2 Machine learning Proteomics http://metadata.un.org/sdg/3 Ensure healthy lives and promote well-being for all at all ages |
| Sumario: | The outbreak of COVID-19, led to an ongoing pandemic with devastating consequences for the global economy and human health. With the global spread of SARS-CoV-2, multidisciplinary initiatives were launched to explore new diagnostic, therapeutic, and vaccination strategies. From this perspective, proteomics could help to understand the mechanisms associated with SARS-CoV-2 infection and to identify new therapeutic options. A TMT-based quantitative proteomics and phosphoproteomics analysis was performed to study the proteome remodeling of human lung alveolar cells expressing human ACE2 (A549-ACE2) after infection with SARS-CoV-2. Detectability and the prognostic value of selected proteins was analyzed by targeted PRM. A total of 6802 proteins and 6428 phospho-sites were identified in A549-ACE2 cells after infection with SARS-CoV-2. The differential proteins here identified revealed that A549-ACE2 cells undergo a time-dependent regulation of essential processes, delineating the precise intervention of the cellular machinery by the viral proteins. From this mechanistic background and by applying machine learning modeling, 29 differential proteins were selected and detected in the serum of COVID-19 patients, 14 of which showed promising prognostic capacity. Targeting these proteins and the protein kinases responsible for the reported phosphorylation changes may provide efficient alternative strategies for the clinical management of COVID-19. |
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