Fig 2: Integration of serum EV proteomics, scRNA-seq of PBMCs, and snRNA-seq of lung tissue. a–c KeyMolnet generated a highly complex network of targets with possible relationships by using the “start points and end-points” network search algorithm. In each molecular networks, the top 10 pathways with the highest involvement are listed in order of HScore. Left panel; examination of the molecular network upstream of MACROH2A1. Right panel; examination of the molecular network downstream of MACROH2A1. a The top 10 pathways in the networks of EV proteins with p < 0.05 and fold change > 1.5 or < 0.67 in comparison of Group 2 and 3 cases. b The top 10 pathways in the networks of genes with significantly upregulated or downregulated in differential expression analysis in scRNA-seq of monocytes from PBMCs in comparison of Group 2 and 3 cases and Group 1 cases. c The top 10 pathways in the networks of genes with significantly upregulated or downregulated in differential expression analysis in snRNA-seq of monocytes from lungs in comparison of fatal COVID-19 and controls. d A graphical abstract of our study. We have identified the protein MACROH2A1, as a potential biomarker for predicting severe COVID-19 infections refractory to anti-inflammatory therapy. First, we have successfully identified several biomarker candidates by performing “next-generation proteomics,” a high-throughput non-targeted quantitative proteomics by data-independent acquisition using serum EVs, and identified MACROH2A1 as the best biomarker molecule among them. Furthermore, scRNA-seq of peripheral blood mononuclear cells and single-nucleus RNA sequencing of lung tissues revealed that this molecule is highly expressed and upregulated in monocytes and macrophages, with pathological pathways which were also reflected in EV proteomics, suggesting its deep involvement in the pathogenesis of severe COVID-19 infections in these cells

Fig 3: Increased level of MACROH2A1, especially MACROH2A1.2 in response to Toll-like receptor 7 ligand and IFN-gamma. a Immunoblot analysis of PMA-differentiated THP-1 cells after treatment with 1 µg /mL R848 with or without 1 µg/mL IFN-gamma for 48 h. med; with no stimulation. The images were cropped from the original full-length blot images in Supplementary Fig. 10c-g. The data are representative of 2 independent experiments. b In response to SARS-CoV-2 infection, immune response including TLR signaling and cytokine secretion such as INF-gamma enhances expression of MACROH2A1 in monocytes. Subsequently, MACROH2A1 is secreted in circulating exosomes, which are more abundant in severely ill patients with COVID-19 than in those who are not

Fig 4: Expression of MACROH2A1 is enhanced in serum EVs and lungs of patients with severe COVID-19. a Levels of MACROH2A1 as determined by non-targeted proteomic analysis in patients with COVID-19 and healthy controls. Data are presented as a box plot. **p < 0.001. b The levels of MACROH2A1 and CD9, determined by immunoblotting of EVs isolated from sera collected in equal volumes from critical cases with COVID-19 (Groups 2 and 3) and healthy controls. The images were cropped from the original full-length blot image in Supplementary Fig. 10a and b. The data is representative of 2 independent experiments. c Histological analysis of lung sections of patients with COVID-19 and controls. Lung sections subjected to hematoxylin–eosin staining are in the left panel and those subjected to immunohistochemistry revealing MACROH2A1-positive cells (brown) are in the right panel. The figures are representative of 3 patients with COVID-19 and 3 controls. d Percentages of MACROH2A1-positive cells in lung sections as in c, determined using BZ-X Analyzer software. Data are presented as a box plot. n = 3 per group (COVID-19), n = 3 per group (COVID-19). *p < 0.05

Fig 5: Enhanced expression of MACROH2A1 in monocytes of severely ill COVID-19 patients revealed by scRNA-seq of PBMCs. a Overview of single-cell analysis of PBMCs transcriptome obtained from patients with COVID-19 and healthy controls. b UMAP visualization of all 91,830 PBMCs from patients with COVID-19 and healthy controls. c Projection of MACROH2A1 gene expression. d Dot plots of MACROH2A1 expression for each cell of PBMCs. The color is scaled by average expression and the size of the dot is proportional to the percentage of the population expressing MACROH2A1. e Differential expression analysis of MACROH2A1 between indicated groups in each cell of PBMCs. f Differential expression analysis of MACROH2A1 between indicated groups in each subpopulation of monocytes. e,f The y-axis indicates expression changes of overall COVID-19 patient groups relative to healthy controls (blue), Groups 2 and 3 relative to healthy controls (red), Groups 2 and 3 relative to Group 1 (green), and Group 3 and Group 2 (purple), respectively. ncMono: non-classical monocytes, intMono: intermediate monocytes, cMono: classical monocytes, *p < 0.05, **p < 0.01, ***p < 0.001