Discrete immune response signature to SARS-CoV-2 mRNA vaccination versus infection

Both SARS-CoV-2 infection and vaccination elicit potent immune responses, but the durability and scope of immune responses remain to be elucidated. Here, we performed multimodal single- cell profiling of peripheral blood of patients with acute COVID-19 and healthy volunteers before and after receiving the SARS-CoV-2 BNT162b2 mRNA vaccine to compare the immune responses elicited by the virus and by the vaccine. Phenotypic and transcriptional profiling of immune cells, coupled with reconstruction of B and T cell receptor repertoires, enabled us to characterize and compare the host responses to the virus and to defined viral antigens. In COVID-19 patients, immune responses were characterized by a highly augmented interferon response which was largely absent in vaccine recipients. Increased interferon signaling likely contributed to the dramatic upregulation of cytotoxic genes in the peripheral T cells and innate- like lymphocytes observed in COVID-19 patients. Analysis of B and T cell repertoires revealed that while the majority of clonal lymphocytes in COVID-19 patients were effector cells, in vaccine recipients clonal expansion was primarily restricted to circulating memory cells. Taken together, our analysis of immune responses to the mRNA vaccine reveals that despite the lack of dramatic inflammation observed during infection, the vaccine elicits a robust adaptive immune response.

Integrated analysis of multimodal single-cell data

The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce weighted-nearest neighbor analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. AvailabilityInstallation instructions, documentation, tutorials, and CITE-seq datasets are available at http://www.satijalab.org/seurat