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Interactions between endothelial selectins and the leukocyte counter-receptor PSGL1 mediates leukocyte recruitment to inflammation sites. PSGL1 is highly sialylated, making it a potential ligand for Siglec-5, a leukocyte-receptor that recognizes sialic acid structures. Binding assays using soluble Siglec-5 variants (sSiglec-5/C4BP and sSiglec-5/Fc) revealed a dose- and calcium-dependent binding to PSGL1. Pre-treatment of PSGL1 with sialidase reduced Siglec-5 binding by 79 ± 4%. In confocal immune-fluorescence assays, we observed that 50% of Peripheral Blood Mononuclear Cells (PBMCs) simultaneously express PSGL1 and Siglec-5. Duolink-proximity ligation analysis demonstrated that PSGL1 and Siglec-5 are in close proximity (<40 nm) in 31 ± 4% of PBMCs. In vitro perfusion assays revealed that leukocyte-rolling over E- and P-selectin was inhibited by sSiglec-5/Fc or sSiglec-5/C4BP, while adhesion onto VCAM1 was unaffected. When applied to healthy mice (0.8 mg/kg), sSiglec-5/C4BP significantly reduced the number of rolling leukocytes under basal conditions (10.9 ± 3.7 versus 23.5 ± 9.3 leukocytes/field/min for sSiglec-5/C4BP-treated and control mice, respectively; p  = 0.0093). Moreover, leukocyte recruitment was inhibited over a 5-h observation period in an in vivo model of TNFalpha-induced inflammation following injection sSiglec-5/C4BP (0.8 mg/kg). Our data identify PSGL1 as a ligand for Siglec-5, and soluble Siglec-5 variants appear efficient in blocking PSGL1-mediated leukocyte rolling and the inflammatory response in general.

The aim of our study was to determine whether granzyme B-expressing regulatory B cells (GZMB+ B cells) are enriched in the blood of transplant patients with renal graft tolerance. To achieve this goal, we analysed two single-cell RNA sequencing (scRNAseq) datasets: (1) peripheral blood mononuclear cells (PBMCs), including GZMB+ B cells from renal transplant patients, i.e., patients with stable graft function on conventional immunosuppressive treatment (STA, n = 3), drug-free tolerant patients (TOL, n = 3), and patients with antibody-mediated rejection (ABMR, n = 3), and (2) ex-vivo-induced GZMB+ B cells from these groups. In the patient PBMCs, we first showed that natural GZMB+ B cells were enriched in genes specific to Natural Killer (NK) cells (such as NKG7 and KLRD1) and regulatory B cells (such as GZMB, IL10, and CCL4). We performed a pseudotemporal trajectory analysis of natural GZMB+ B cells and showed that they were highly differentiated B cells with a trajectory that is very different from that of conventional memory B cells and linked to the transcription factor KLF13. By specifically analysing GZMB+ natural B cells in TOLs, we found that these cells had a very specific transcriptomic profile associated with a reduction in the expression of HLA molecules, apoptosis, and the inflammatory response (in general) in the blood and that this signature was conserved after ex vivo induction, with the induction of genes associated with migration processes, such as CCR7, CCL3, or CCL4. An analysis of receptor/ligand interactions between these GZMB+/− natural B cells and all of the immune cells present in PBMCs also demonstrated that GZMB+ B cells were the B cells that carried the most ligands and had the most interactions with other immune cells, particularly in tolerant patients. Finally, we showed that these GZMB+ B cells were able to infiltrate the graft under inflammatory conditions, thus suggesting that they can act in locations where immune events occur.

There is an urgent need to better understand the pathophysiology of Coronavirus disease 2019 (COVID-19), the global pandemic caused by SARS-CoV-2, which has infected more than three million people worldwide 1 . Approximately 20% of patients with COVID-19 develop severe disease and 5% of patients require intensive care 2 . Severe disease has been associated with changes in peripheral immune activity, including increased levels of pro-inflammatory cytokines 3 , 4 that may be produced by a subset of inflammatory monocytes 5 , 6 , lymphopenia 7 , 8 and T cell exhaustion 9 , 10 . To elucidate pathways in peripheral immune cells that might lead to immunopathology or protective immunity in severe COVID-19, we applied single-cell RNA sequencing (scRNA-seq) to profile peripheral blood mononuclear cells (PBMCs) from seven patients hospitalized for COVID-19, four of whom had acute respiratory distress syndrome, and six healthy controls. We identify reconfiguration of peripheral immune cell phenotype in COVID-19, including a heterogeneous interferon-stimulated gene signature, HLA class II downregulation and a developing neutrophil population that appears closely related to plasmablasts appearing in patients with acute respiratory failure requiring mechanical ventilation. Importantly, we found that peripheral monocytes and lymphocytes do not express substantial amounts of pro-inflammatory cytokines. Collectively, we provide a cell atlas of the peripheral immune response to severe COVID-19. Single-cell transcriptomic analysis identifies changes in peripheral immune cells in seven hospitalized patients with COVID-19, including HLA class II downregulation, a heterogeneous interferon-stimulated gene signature and low pro-inflammatory cytokine gene expression in monocytes and lymphocytes.

Citrullinated peptides are used for measuring anticitrullinated protein antibodies (ACPA) in rheumatoid arthritis (RA). Accumulation of citrullinated proteins in the inflamed synovium suggests that they may be good targets for inducing peripheral tolerance. In view of the multiplicity of citrullinated autoantigens described as ACPA targets, we generated a multiepitope citrullinated peptide (Cit-ME) from the sequences of major citrullinated autoantigens: filaggrin, β-fibrinogen, vimentin, and collagen type II. We assessed the ability of Cit-ME or the citrullinated β60-74 fibrinogen peptide (β60-74-Fib-Cit) which bears immunodominant citrullinated epitopes (i) to modify cytokine gene expression and (ii) to modulate Treg and Th17 subsets in PBMC derived from newly diagnosed untreated RA patients. RA patient’s PBMC incubated with Cit-ME or β60-74-Fib-Cit, showed upregulation of TGF-β expression (16% and 8%, resp.), and increased CD4+Foxp3+ Treg (22% and 19%, resp.). Both peptides were shown to downregulate the TNF-α and IL-1β expression; in addition, Cit-ME reduced CD3+IL17+ T cells. We showed that citrullinated peptides can modulate the expression of anti- and proinflammatory cytokines in PBMC from RA patients as well as the proportions of Treg and Th17 cells. These results indicate that citrullinated peptides could be active in vivo and therefore might be used as immunoregulatory agents in RA patients.

Clearance of invading microbes requires phagocytes of the innate immune system. However, successful pathogens have evolved sophisticated strategies to evade immune killing. The opportunistic human fungal pathogen Candida albicans is efficiently phagocytosed by macrophages, but causes inflammasome activation, host cytolysis, and escapes after hypha formation. Previous studies suggest that macrophage lysis by C . albicans results from early inflammasome-dependent cell death (pyroptosis), late damage due to glucose depletion and membrane piercing by growing hyphae. Here we show that Candidalysin, a cytolytic peptide toxin encoded by the hypha-associated gene ECE1 , is both a central trigger for NLRP3 inflammasome-dependent caspase-1 activation via potassium efflux and a key driver of inflammasome-independent cytolysis of macrophages and dendritic cells upon infection with C . albicans . This suggests that Candidalysin-induced cell damage is a third mechanism of C . albicans -mediated mononuclear phagocyte cell death in addition to damage caused by pyroptosis and the growth of glucose-consuming hyphae. Phagocytic cells of the innate immune system play critical roles in defence against invading pathogens including the opportunistic pathogen Candida albicans . Here the authors show that C . albicans derived Candidalysin in addition to being a cell-damaging toxin to mononuclear phagocytes is a trigger of NLRP3 inflammasome activation in these cells.

Recent technological advances have enabled massively parallel chromatin profiling with scATAC-seq (single-cell assay for transposase accessible chromatin by sequencing). Here we present ATAC with select antigen profiling by sequencing (ASAP-seq), a tool to simultaneously profile accessible chromatin and protein levels. Our approach pairs sparse scATAC-seq data with robust detection of hundreds of cell surface and intracellular protein markers and optional capture of mitochondrial DNA for clonal tracking, capturing three distinct modalities in single cells. ASAP-seq uses a bridging approach that repurposes antibody:oligonucleotide conjugates designed for existing technologies that pair protein measurements with single-cell RNA sequencing. Together with DOGMA-seq, an adaptation of CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) for measuring gene activity across the central dogma of gene regulation, we demonstrate the utility of systematic multi-omic profiling by revealing coordinated and distinct changes in chromatin, RNA and surface proteins during native hematopoietic differentiation and peripheral blood mononuclear cell stimulation and as a combinatorial decoder and reporter of multiplexed perturbations in primary T cells. Chromatin accessibility, gene expression and protein levels are measured in the same single cell.

Cytokine release syndrome (CRS) is a major cause of the multi-organ injury and fatal outcome induced by SARS-CoV-2 infection in severe COVID-19 patients. Metabolism can modulate the immune responses against infectious diseases, yet our understanding remains limited on how host metabolism correlates with inflammatory responses and affects cytokine release in COVID-19 patients. Here we perform both metabolomics and cytokine/chemokine profiling on serum samples from healthy controls, mild and severe COVID-19 patients, and delineate their global metabolic and immune response landscape. Correlation analyses show tight associations between metabolites and proinflammatory cytokines/chemokines, such as IL-6, M-CSF, IL-1α, IL-1β, and imply a potential regulatory crosstalk between arginine, tryptophan, purine metabolism and hyperinflammation. Importantly, we also demonstrate that targeting metabolism markedly modulates the proinflammatory cytokines release by peripheral blood mononuclear cells isolated from SARS-CoV-2-infected rhesus macaques ex vivo, hinting that exploiting metabolic alterations may be a potential strategy for treating fatal CRS in COVID-19. Metabolism changes can modulate immune responses in many contexts, and vice versa. Here the authors associate metabolomic, as well as cytokine and chemokine, data from stratified COVID-19 patients to find that arginine, tryptophan and purine metabolic pathways correlate with hyperproliferation, thus hinting at potential therapeutic targets for severe COVID-19 patients.

Genome-wide association studies have identified thousands of genetic variants that are associated with disease 1 . Most of these variants have small effect sizes, but their downstream expression effects, so-called expression quantitative trait loci (eQTLs), are often large 2 and celltype-specific 3 – 5 . To identify these celltype-specific eQTLs using an unbiased approach, we used single-cell RNA sequencing to generate expression profiles of ~25,000 peripheral blood mononuclear cells from 45 donors. We identified previously reported cis-eQTLs, but also identified new celltype-specific cis-eQTLs. Finally, we generated personalized co-expression networks and identified genetic variants that significantly alter co-expression relationships (which we termed ‘co-expression QTLs’). Single-cell eQTL analysis thus allows for the identification of genetic variants that impact regulatory networks. Single-cell RNA sequencing (scRNA-seq) of ~25,000 peripheral blood mononuclear cells from 45 donors identifies new celltype-specific cis-eQTLs and genetic variants that significantly alter co-expression relationships (‘co-expression QTLs’).

Characterizing the transcriptome of individual cells is fundamental to understanding complex biological systems. We describe a droplet-based system that enables 3′ mRNA counting of tens of thousands of single cells per sample. Cell encapsulation, of up to 8 samples at a time, takes place in ∼6 min, with ∼50% cell capture efficiency. To demonstrate the system’s technical performance, we collected transcriptome data from ∼250k single cells across 29 samples. We validated the sensitivity of the system and its ability to detect rare populations using cell lines and synthetic RNAs. We profiled 68k peripheral blood mononuclear cells to demonstrate the system’s ability to characterize large immune populations. Finally, we used sequence variation in the transcriptome data to determine host and donor chimerism at single-cell resolution from bone marrow mononuclear cells isolated from transplant patients. Single-cell gene expression analysis is challenging. This work describes a new droplet-based single cell RNA-seq platform capable of processing tens of thousands of cells across 8 independent samples in minutes, and demonstrates cellular subtypes and host–donor chimerism in transplant patients.

The recent development of experimental methods for measuring chromatin state at single-cell resolution has created a need for computational tools capable of analyzing these datasets. Here we developed Signac, a comprehensive toolkit for the analysis of single-cell chromatin data. Signac enables an end-to-end analysis of single-cell chromatin data, including peak calling, quantification, quality control, dimension reduction, clustering, integration with single-cell gene expression datasets, DNA motif analysis and interactive visualization. Through its seamless compatibility with the Seurat package, Signac facilitates the analysis of diverse multimodal single-cell chromatin data, including datasets that co-assay DNA accessibility with gene expression, protein abundance and mitochondrial genotype. We demonstrate scaling of the Signac framework to analyze datasets containing over 700,000 cells.The Signac framework enables the end-to-end analysis of single-cell chromatin data and interoperability with the Seurat package for multimodal analysis.