Differential abundance of mDC subsets predict response to Hepatitis B vaccination

Abstract

Abstract Vaccination as a strategy for the prevention of infectious disease has been one of the greatest success stories in modern medicine, resulting in the complete eradication of smallpox, the near eradication of polio, and the drastic lowering in the incidences of measles, mumps, influenza and other common diseases. In contrast to these remarkable successes, recent failures in the development of effective vaccines against other major public health threats, including HIV, TB and malaria have highlighted the limitations to the current approach of empirical vaccine design and the need to better understand the basic principles of how to recognize and elicit immune responses that generate effective and durable protective immunity. Single cell transcriptional profiling by RNA sequencing (scRNAseq) is a powerful tool for exploring the phenotypic diversity of cell populations present in peripheral blood and other tissue specimens in an unbiased fashion. We applied scRNAseq to FACS sorted blood samples collected from participants before and after challenge with the licensed Hepatitis B vaccine, and identified several innate cell subtypes using unbiased clustering analysis. Marker genes specific for each cell subtype were identified using random forest machine learning for use in qPCR. Our results suggest that the relative levels of myeloid dendritic cells (mDCs) specifically expressing the N-myc target gene, NDRG2, prior to vaccination predict serum antibody responses to the HepB vaccine.