Mass Cytometry Defines Virus-Specific CD4+ T Cells in Influenza Vaccination

Priyanka B. Subrahmanyam, Tyson H. Holmes, Dongxia Lin, Laura F. Su, Gerlinde Obermoser, Jacques Banchereau, Virginia Pascual, Adolfo Garcíá-Sastre, Randy A. Albrecht, Karolina Palucka, Mark M. Davis, Holden T. Maecker

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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.

Original languageEnglish
Pages (from-to)774-788
Number of pages15
Issue number12
StatePublished - 1 Dec 2020


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