Article ; Online: Systems biology of B cells in COVID-19.
2024 Volume 72, Page(s) 101875
Abstract: The integration of multi-'omic datasets into complex systems-wide assessments has become a mainstay in immunologic investigation. This focus on high-dimensional data collection and analysis was on full display in the investigation of COVID-19, the ... ...
| Abstract | The integration of multi-'omic datasets into complex systems-wide assessments has become a mainstay in immunologic investigation. This focus on high-dimensional data collection and analysis was on full display in the investigation of COVID-19, the respiratory illness resulting from infection by the novel coronavirus SARS-CoV-2. Particularly in the area of B cell biology, tremendous efforts in both cellular and serologic investigation have resulted in an increasingly detailed mapping of the coordinated effector, memory, and antibody secreting cell responses that underpin the development of humoral immunity in response to primary viral infection. Further, the rapid development and deployment of effective vaccines has allowed for the assessment of developing memory responses across a wide variety of immune contexts, including in patients with compromised immune function. The result has been a period of rapid gains in the understanding of B cell biology unrestricted to the study of COVID-19. Here, we outline the systems-level technologies that have been routinely implemented in these investigations throughout the pandemic, and discuss how their use has led to clear and applicable gains in pursuance of the amelioration of human infectious disease and beyond. |
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| MeSH term(s) | Humans ; COVID-19 ; SARS-CoV-2 ; B-Lymphocytes ; Immunity, Humoral ; Systems Biology ; Antibodies, Viral |
| Chemical Substances | Antibodies, Viral |
| Language | English |
| Publishing date | 2024-03-14 |
| Publishing country | England |
| Document type | Journal Article ; Review |
| ZDB-ID | 1018141-6 |
| ISSN | 1096-3618 ; 1044-5323 |
| ISSN (online) | 1096-3618 |
| ISSN | 1044-5323 |
| DOI | 10.1016/j.smim.2024.101875 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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