Immunohorizons 2020 Dec 11; 4(12):774-788
The antiviral response to influenza virus is complex and multifaceted, involving many immune cell subsets. There is an urgent need to understand the role of CD4+ T cells, which orchestrate an effective antiviral response, to improve vaccine design strategies. In this study, we analyzed PBMCs from human participants immunized with influenza vaccine, using high-dimensional single-cell proteomic immune profiling by mass cytometry. Data were analyzed using a novel clustering algorithm, denoised ragged pruning, to define possible influenza virus-specific clusters of CD4+ T cells. Denoised ragged pruning identified six clusters of cells. Among these, one cluster (Cluster 3) was found to increase in abundance following stimulation with influenza virus peptide ex vivo. A separate cluster (Cluster 4) was found to expand in abundance between days 0 and 7 postvaccination, indicating that it is vaccine responsive. We examined the expression profiles of all six clusters to characterize their lineage, functionality, and possible role in the response to influenza vaccine. Clusters 3 and 4 consisted of effector memory cells, with high CD154 expression. Cluster 3 expressed cytokines like IL-2, IFN-γ, and TNF-α, whereas Cluster 4 expressed IL-17. Interestingly, some participants had low abundance of Clusters 3 and 4, whereas others had higher abundance of one of these clusters compared with the other. Taken together, we present an approach for identifying novel influenza virus-reactive CD4+ T cell subsets, a method that could help advance understanding of the immune response to influenza, predict responsiveness to vaccines, and aid in better vaccine design.
Subrahmanyam, Priyanka B; Holmes, Tyson H; Lin, Dongxia; Su, Laura F; Obermoser, Gerlinde; Banchereau, Jacques; Pascual, Virginia; García-Sastre, Adolfo; Albrecht, Randy A; Palucka, Karolina; Davis, Mark M; and Maecker, Holden T, "Mass Cytometry Defines Virus-Specific CD4 + T Cells in Influenza Vaccination" (2020). Faculty Research 2020. 256.