Proteome reveals antiviral host response and NETosis during acute COVID-19 in high-risk patients

SARS-CoV-2 remains an acute threat to human health, endangering hospital capacities worldwide. Many studies have aimed at informing pathophysiologic understanding and identification of disease indicators for risk assessment, monitoring, and therapeutic guidance. While findings start to emerge in the general population, observations in high-risk patients with complex pre-existing conditions are limited. To this end, we biomedically characterized quantitative proteomics in a hospitalized cohort of COVID-19 patients with mild to severe symptoms suffering from different (co)-morbidities in comparison to both healthy individuals and patients with non-COVID related inflammation. Deep clinical phenotyping enabled the identification of individual disease trajectories in COVID-19 patients. By the use of this specific disease phase assignment, proteome analysis revealed a severity dependent general type-2 centered host response side-by-side with a disease specific antiviral immune reaction in early disease. The identification of phenomena such as neutrophil extracellular trap (NET) formation and a pro-coagulatory response together with the regulation of proteins related to SARS-CoV-2-specific symptoms by unbiased proteome screening both confirms results from targeted approaches and provides novel information for biomarker and therapy development. Graphical AbstractSars-CoV-2 remains a challenging threat to our health care system with many pathophysiological mechanisms not fully understood, especially in high-risk patients. Therefore, we characterized a cohort of hospitalized COVID-19 patients with multiple comorbidities by quantitative plasma proteomics and deep clinical phenotyping. The individual patients disease progression was determined and the subsequently assigned proteome profiles compared with a healthy and a chronically inflamed control cohort. The identified disease phase and severity specific protein profiles revealed an antiviral immune response together with coagulation activation indicating the formation of NETosis side-by-side with tissue remodeling related to the inflammatory signature. O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/22271106v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@1e791faorg.highwire.dtl.DTLVardef@20d3d6org.highwire.dtl.DTLVardef@1339e42org.highwire.dtl.DTLVardef@1db3710_HPS_FORMAT_FIGEXP M_FIG C_FIG

Single-cell RNA sequencing reveals in vivo signatures of SARS-CoV-2-reactive T cells through 'reverse phenotyping'

The in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we used single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, we induced transcriptional shifts by antigenic stimulation in vitro and took advantage of natural T cell receptor (TCR) sequences of clonally expanded T cells as barcodes for reverse phenotyping. This allowed identification of SARS-CoV-2-reactive TCRs and revealed phenotypic effects introduced by antigen-specific stimulation. We characterized transcriptional signatures of currently and previously activated SARS-CoV-2-reactive T cells, and showed correspondence with phenotypes of T cells from the respiratory tract of patients with severe disease in the presence or absence of virus in independent cohorts. Reverse phenotyping is a powerful tool to provide an integrated insight into cellular states of SARS-CoV-2-reactive T cells across tissues and activation states.