tetano
Editor, Senior Moderator
Immunohorizons
. 2020 Dec 11;4(12):774-788.
doi: 10.4049/immunohorizons.1900097.
Mass Cytometry Defines Virus-Specific CD4 [SUP]+[/SUP] T Cells in Influenza Vaccination
Priyanka B Subrahmanyam[SUP] 1 [/SUP], Tyson H Holmes[SUP] 1 [/SUP], Dongxia Lin[SUP] 1 [/SUP], Laura F Su[SUP] 1 [/SUP], Gerlinde Obermoser[SUP] 2 [/SUP], Jacques Banchereau[SUP] 3 [/SUP], Virginia Pascual[SUP] 2 [/SUP], Adolfo Garc?a-Sastre[SUP] 4 5 6 [/SUP], Randy A Albrecht[SUP] 4 [/SUP], Karolina Palucka[SUP] 2 [/SUP], Mark M Davis[SUP] 1 [/SUP], Holden T Maecker[SUP] 7 [/SUP]
Affiliations
Abstract
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[SUP]+[/SUP] 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[SUP]+[/SUP] 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[SUP]+[/SUP] 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.
. 2020 Dec 11;4(12):774-788.
doi: 10.4049/immunohorizons.1900097.
Mass Cytometry Defines Virus-Specific CD4 [SUP]+[/SUP] T Cells in Influenza Vaccination
Priyanka B Subrahmanyam[SUP] 1 [/SUP], Tyson H Holmes[SUP] 1 [/SUP], Dongxia Lin[SUP] 1 [/SUP], Laura F Su[SUP] 1 [/SUP], Gerlinde Obermoser[SUP] 2 [/SUP], Jacques Banchereau[SUP] 3 [/SUP], Virginia Pascual[SUP] 2 [/SUP], Adolfo Garc?a-Sastre[SUP] 4 5 6 [/SUP], Randy A Albrecht[SUP] 4 [/SUP], Karolina Palucka[SUP] 2 [/SUP], Mark M Davis[SUP] 1 [/SUP], Holden T Maecker[SUP] 7 [/SUP]
Affiliations
- PMID: 33310880
- DOI: 10.4049/immunohorizons.1900097
Abstract
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[SUP]+[/SUP] 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[SUP]+[/SUP] 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[SUP]+[/SUP] 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.