ABSTRACT
We examine the cellular and soluble determinants of coronavirus disease 2019 (COVID-19) relative to aging by performing mass cytometry in parallel with clinical blood testing and plasma proteomic profiling of ~4,700 proteins from 71 individuals with pulmonary disease and 148 healthy donors (25-80 years old). Distinct cell populations were associated with age (GZMK+CD8+ T cells and CD25low CD4+ T cells) and with COVID-19 (TBET-EOMES- CD4+ T cells, HLA-DR+CD38+ CD8+ T cells and CD27+CD38+ B cells). A unique population of TBET+EOMES+ CD4+ T cells was associated with individuals with COVID-19 who experienced moderate, rather than severe or lethal, disease. Disease severity correlated with blood creatinine and urea nitrogen levels. Proteomics revealed a major impact of age on the disease-associated plasma signatures and highlighted the divergent contribution of hepatocyte and muscle secretomes to COVID-19 plasma proteins. Aging plasma was enriched in matrisome proteins and heart/aorta smooth muscle cell-specific proteins. These findings reveal age-specific and disease-specific changes associated with COVID-19, and potential soluble mediators of the physiological impact of COVID-19.
ABSTRACT
CD4+ T cells are critical to the immune system and perform multiple functions; therefore, their identification and characterization are crucial to better understanding the immune system in both health and disease states. However, current methods rarely preserve their ex vivo phenotype, thus limiting our understanding of their in vivo functions. Here we introduce a flexible, rapid, and robust platform for ex vivo CD4+ T cell identification. By combining MHCII allele purification, allele-independent peptide loading, and multiplexed flow cytometry technologies, we can enable high-throughput personalized CD4+ T cell identification, immunophenotyping, and sorting. Using this platform in combination with single-cell sorting and multimodal analyses, we identified and characterized antigen-specific CD4+ T cells relevant to COVID-19 and cancer neoantigen immunotherapy. Overall, our platform can be used to detect and characterize CD4+ T cells across multiple diseases, with potential to guide CD4+ T cell epitope design for any disease-specific immunization strategy.
ABSTRACT
Emergence of mutant SARS-CoV-2 strains associated with an increased risk of COVID-19-related death necessitates better understanding of the early viral dynamics, host responses and immunopathology. Single cell RNAseq (scRNAseq) allows for the study of individual cells, uncovering heterogeneous and variable responses to environment, infection and inflammation. While studies have reported immune profiling using scRNAseq in terminal human COVID-19 patients, performing longitudinal immune cell dynamics in humans is challenging. Macaques are a suitable model of SARS-CoV-2 infection. Our longitudinal scRNAseq of bronchoalveolar lavage (BAL) cell suspensions from young rhesus macaques infected with SARS-CoV-2 (n = 6) demonstrates dynamic changes in transcriptional landscape 3 days post- SARS-CoV-2-infection (3dpi; peak viremia), relative to 14-17dpi (recovery phase) and pre-infection (baseline) showing accumulation of distinct populations of both macrophages and T-lymphocytes expressing strong interferon-driven inflammatory gene signature at 3dpi. Type I interferon response is induced in the plasmacytoid dendritic cells with appearance of a distinct HLADR+CD68+CD163+SIGLEC1+ macrophage population exhibiting higher angiotensin-converting enzyme 2 (ACE2) expression. These macrophages are significantly enriched in the lungs of macaques at 3dpi and harbor SARS-CoV-2 while expressing a strong interferon-driven innate anti-viral gene signature. The accumulation of these responses correlated with decline in viremia and recovery.