Bifalgorithm post · Latest research covid · ARTICLE IN PRESS

Cytof Analysis

Cytof Analysis (Latest research covid · ARTICLE IN PRESS) — "To explore potential correlations between plasma ADCC activity and slow viral clearance, we aimed…

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  • Immune cell subsets were analyzed for relationships with ADCC efficiency and SARS-CoV-2 clearance.
  • The study aimed to determine how immune cell subsets relate to plasma ADCC activity and the rate of viral clearance.
  • PBMCs from COVID-19 patients were profiled by CyTOF, focusing on T cells, B cells, NK cells, and dendritic cells.
  • Canonical surface markers were used for lineage gating, followed by t-SNE and FlowSOM analysis of each major lineage.
  • Each lineage yielded 20 phenotypically distinct clusters, whose relative abundances were tested by regression analysis.
  • The analysis identified four coordinated immune modules with distinct correlation profiles.
  • The cytolytic killer cell module included NK_C6, NK_C12, and cytotoxic CD8⁺ T-cell subsets.
  • NK_C6 and NK_C12 expressed high levels of NKG2D, NKp30, NKp46, DNAM-1, granzyme B, and perforin.
  • These cytotoxic subsets strongly and positively correlated with the slope of viral clearance, supporting a role in rapid viral elimination.
  • NK_C9 had relatively low expression of NKp30, NKG2D, and DNAM-1 but showed a moderate positive correlation with ADCC efficiency.
  • NK_C6 and NK_C12 showed negative or negligible correlations with ADCC efficiency despite their high levels of activating receptors.
  • Lower-cytotoxicity NK subsets may still participate in antibody-dependent virus elimination without belonging to the primary ADCC-associated module.
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Cytof Analysis

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Latest research covid

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"To explore potential correlations between plasma ADCC activity and slow viral clearance, we aimed to investigate how immune cell subsets correlate with ADCC efficiency and the rate of SARS-CoV-2 clearance. We profiled peripheral blood mononuclear cells (PBMCs) from COVID-19 patients using mass cytometry (CyTOF), focusing on T cells, B cells, NK cells, and dendritic cells. Lineage gating was performed using canonical surface markers, and each major lineage was independently subjected to dimensionality reduction (t-SNE) and unsupervised clustering (FlowSOM), resulting in 20 phenotypically distinct clusters per lineage. For each individual, we quantified the relative abundance of each cluster and performed regression analyses to identify clusters whose frequencies significantly correlated with either viral clearance rates or ADCC efficiency. This analysis revealed four coordinated immune modules with distinct correlation profiles, including ADCC-associated features, a cytolytic killer cell module, a mixed population module, and plasmacytoid dendritic cell-enriched modules. Within the cytolytic killer cell module, NK_C6 and NK_C12 expressed high levels of activating receptors, including NKG2D, NKp30, NKp46, and DNAM-1, as well as effector molecules such as granzyme B and perforin. These cytotoxic NK subsets exhibited strong positive correlations with the slope of viral clearance, suggesting a key role in rapid viral elimination. This module also included cytotoxic CD8⁺ T-cell subsets expressing NKG2D, supporting the contribution of cytolytic effectors to early immune control. NK_C9 displayed relatively low expression of NKp30, NKG2D, and DNAM-1 and was not grouped within the ADCC-associated feature module. However, it still showed a moderate positive correlation with ADCC efficiency. This suggests that NK subsets with lower cytotoxicity may still participate in antibody-dependent virus elimination, despite not being part of the primary ADCC-associated features module. Inversely, NK_C6 and NK_C12, which exhibit higher levels of NK activating receptors, showed a negative or negligible correlation with ADCC efficiency."

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