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Inflammation of non-barrier immunologically quiescent tissues is associated with a massive influx of blood-borne innate and adaptive immune cells. Cues from the latter are likely to alter and expand activated states of the resident cells. However, local communications between immigrant and resident cell types in human inflammatory disease remain poorly understood. Here, we explored drivers of fibroblast-like synoviocyte (FLS) heterogeneity in inflamed joints of patients with rheumatoid arthritis using paired single-cell RNA and ATAC sequencing, multiplexed imaging and spatial transcriptomics along with in vitro modeling of cell-extrinsic factor signaling. These analyses suggest that local exposures to myeloid and T cell-derived cytokines, TNF, IFN-γ, IL-1β or lack thereof, drive four distinct FLS states some of which closely resemble fibroblast states in other disease-affected tissues including skin and colon. Our results highlight a role for concurrent, spatially distributed cytokine signaling within the inflamed synovium. Smith et al. present a resource detailing drivers of transcriptional heterogeneity of synovial fibroblasts cell states in the inflamed joints of human patients with rheumatoid arthritis.

Background Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies. Methods To identify cellular phenotypes that may be shared across tissues affected by disparate inflammatory diseases, we developed a meta-analysis and integration pipeline that models and removes the effects of technology, tissue of origin, and donor that confound cell-type identification. Using this approach, we integrated > 300,000 single-cell transcriptomic profiles from COVID-19-affected lungs and tissues from healthy subjects and patients with five inflammatory diseases: rheumatoid arthritis (RA), Crohn’s disease (CD), ulcerative colitis (UC), systemic lupus erythematosus (SLE), and interstitial lung disease. We tested the association of shared immune states with severe/inflamed status compared to healthy control using mixed-effects modeling. To define environmental factors within these tissues that shape shared macrophage phenotypes, we stimulated human blood-derived macrophages with defined combinations of inflammatory factors, emphasizing in particular antiviral interferons IFN-beta (IFN-β) and IFN-gamma (IFN-γ), and pro-inflammatory cytokines such as TNF. Results We built an immune cell reference consisting of > 300,000 single-cell profiles from 125 healthy or disease-affected donors from COVID-19 and five inflammatory diseases. We observed a CXCL10+ CCL2+ inflammatory macrophage state that is shared and strikingly abundant in severe COVID-19 bronchoalveolar lavage samples, inflamed RA synovium, inflamed CD ileum, and UC colon. These cells exhibited a distinct arrangement of pro-inflammatory and interferon response genes, including elevated levels of CXCL10 , CXCL9 , CCL2 , CCL3 , GBP1, STAT1 , and IL1B . Further, we found this macrophage phenotype is induced upon co-stimulation by IFN-γ and TNF-α. Conclusions Our integrative analysis identified immune cell states shared across inflamed tissues affected by inflammatory diseases and COVID-19. Our study supports a key role for IFN-γ together with TNF-α in driving an abundant inflammatory macrophage phenotype in severe COVID-19-affected lungs, as well as inflamed RA synovium, CD ileum, and UC colon, which may be targeted by existing immunomodulatory therapies.

Droplet-based single-cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While this approach offers the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we developed a 3D-printed, low-cost droplet microfluidic control instrument and deploy it in a clinical environment to perform single-cell transcriptome profiling of disaggregated synovial tissue from five rheumatoid arthritis patients. We sequence 20,387 single cells revealing 13 transcriptomically distinct clusters. These encompass an unsupervised draft atlas of the autoimmune infiltrate that contribute to disease biology. Additionally, we identify previously uncharacterized fibroblast subpopulations and discern their spatial location within the synovium. We envision that this instrument will have broad utility in both research and clinical settings, enabling low-cost and routine application of microfluidic techniques. Droplet-based single-cell RNA-seq is a powerful tool for cellular heterogeneity profiling in disease but is limited by instrumentation required. Here the authors develop a 3D printed microfluidic platform for massive parallel sequencing of rheumatoid arthritis tissues.

Fibroblasts regulate tissue homeostasis, coordinate inflammatory responses, and mediate tissue damage. In rheumatoid arthritis (RA), synovial fibroblasts maintain chronic inflammation which leads to joint destruction. Little is known about fibroblast heterogeneity or if aberrations in fibroblast subsets relate to pathology. Here, we show functional and transcriptional differences between fibroblast subsets from human synovial tissues using bulk transcriptomics of targeted subpopulations and single-cell transcriptomics. We identify seven fibroblast subsets with distinct surface protein phenotypes, and collapse them into three subsets by integrating transcriptomic data. One fibroblast subset, characterized by the expression of proteins podoplanin, THY1 membrane glycoprotein and cadherin-11, but lacking CD34, is threefold expanded in patients with RA relative to patients with osteoarthritis. These fibroblasts localize to the perivascular zone in inflamed synovium, secrete proinflammatory cytokines, are proliferative, and have an in vitro phenotype characteristic of invasive cells. Our strategy may be used as a template to identify pathogenic stromal cellular subsets in other complex diseases. Synovial fibroblasts are thought to be central mediators of joint destruction in rheumatoid arthritis (RA). Here the authors use single-cell transcriptomics and flow cytometry to identify synovial fibroblast subsets that are expanded and display distinct tissue distribution and function in patients with RA.

The immune mechanisms that mediate synovitis and joint destruction in rheumatoid arthritis (RA) remain poorly defined. Although increased levels of CD8 + T cells have been described in RA, their function in pathogenesis remains unclear. Here we perform single cell transcriptome and T cell receptor (TCR) sequencing of CD8 + T cells derived from anti-citrullinated protein antibodies (ACPA)+ RA blood. We identify GZMB + CD8 + subpopulations containing large clonal lineage expansions that express cytotoxic and tissue homing transcriptional programs, while a GZMK + CD8 + memory subpopulation comprises smaller clonal expansions that express effector T cell transcriptional programs. We demonstrate RA citrullinated autoantigens presented by MHC class I activate RA blood-derived GZMB + CD8 + T cells to expand, express cytotoxic mediators, and mediate killing of target cells. We also demonstrate that these clonally expanded GZMB + CD8 + cells are present in RA synovium. These findings suggest that cytotoxic CD8 + T cells targeting citrullinated antigens contribute to synovitis and joint tissue destruction in ACPA+ RA. The immune mechanisms underlying synovitis and joint tissue destruction in rheumatoid arthritis (RA) remain incompletely defined. Here, the authors demonstrate that ACPA+ RA patients have activated clonally expanded cytotoxic GZMB + CD8+ T cells in blood and synovium that target and are activated by citrullinated antigens to mediate cell killing.

Key Points Type I interferon (IFN) responses are regulated by host, pathogen and environmental factors. These factors calibrate the host defences while limiting tissue damage and preventing autoimmunity. Type I IFNs signal via the IFNα receptor (IFNAR) to activate receptor-associated Janus kinase 1 (JAK1) and tyrosine kinase 2 (TYK2) kinases and downstream signal transducer and activator of transcription (STAT) transcription factors; these transcription factors then induce the expression of IFN-stimulated genes (ISGs). Type I IFNs activate the IFN-stimulated gene factor 3 (ISGF3) complex, which is comprised of STAT1, STAT2 and IFN-regulatory factor 9 (IRF9); the ISGF3 complex binds to IFN-stimulated response elements (ISREs) to induce the expression of antiviral genes. Type I IFN signalling is regulated in a quantitative and qualitative manner. The magnitude of signalling is increased by induction of STAT1 and IRF9 expression and amplification of JAK signalling by spleen tyrosine kinase (SYK) and protein tyrosine kinase 2 (PYK2). Conversely, the magnitude of signalling is decreased by suppressor of cytokine signalling (SOCS) and ubiquitin carboxy-terminal hydrolase 18 (USP18) proteins and by the downregulation and internalization of IFNAR. The qualitative nature of type I IFN responses is determined by the balance between the activation of various STATs and ISGF3. Type I IFN-induced transcription is regulated by the post-translational modification of STATs, chromatin remodelling, the epigenetic landscape and cooperation with other transcription factors, co-activators and co-repressors. ISGs encode proteins that regulate the translation of IFNAR and JAK–STAT signalling components and of ISGs themselves. Type I IFNs also induce the expression of microRNAs that regulate the IFN response. Chronic type I IFN responses can promote autoimmunity by increasing antigen presentation, lymphocyte-mediated adaptive immune responses and chemokine expression. In chronic infections, type I IFNs can induce immunosuppression in part by increasing expression of interleukin-10 and programmed cell death 1 ligand 1 (PDL1). This Review describes the intricate signalling and epigenetic mechanisms that regulate cellular responses to type I interferons. The authors also discuss how persistent interferon-mediated signalling can have detrimental outcomes in autoimmune disease and chronic infections. Type I interferons (IFNs) activate intracellular antimicrobial programmes and influence the development of innate and adaptive immune responses. Canonical type I IFN signalling activates the Janus kinase (JAK)–signal transducer and activator of transcription (STAT) pathway, leading to transcription of IFN-stimulated genes (ISGs). Host, pathogen and environmental factors regulate the responses of cells to this signalling pathway and thus calibrate host defences while limiting tissue damage and preventing autoimmunity. Here, we summarize the signalling and epigenetic mechanisms that regulate type I IFN-induced STAT activation and ISG transcription and translation. These regulatory mechanisms determine the biological outcomes of type I IFN responses and whether pathogens are cleared effectively or chronic infection or autoimmune disease ensues.

Biopsies from synovial joints — and the abundance of B cells and macrophages therein — may instruct more effective treatment decisions for individuals with rheumatoid arthritis.

The synovial tissue pathotype may determine the treatment response in rheumatoid arthritis (RA); however, biopsies are not widely available. Synovial fluid is a promising tissue surrogate. Our purpose was to compare RA synovial fluid cell counts with histopathology and use synovial fluid to predict tissue inflammation. Synovial fluid and tissue were collected during knee arthroplasty. Patients were stratified based on their medication treatment history. Synovial lymphocytic inflammation (SLI) was graded from low to high. Synovial fluid white blood cell (WBC) count and differentials were performed in the clinical laboratory. Descriptive statistics, correlations, receiver operating characteristic curve analysis, and multivariable regression were performed to determine the associations with tissue SLI. Sixty-four patients with RA had paired synovial tissue and synovial fluid data available. The mean Clinical Disease Activity Index (CDAI) score was 17.9. High tissue SLI was observed in 29 patients, and low SLI was observed in 35 patients, with roughly equal distribution among treatment groups. The mean synovial fluid WBC count was 5,661 cells/μL and was not correlated with CDAI but correlated positively with SLI and percentage polymorphonuclear cells (PMN%). Synovial fluid WBC count ≥1,400 cells/μL was sensitive (0.86) and specific (0.91) for high SLI (area under the curve 0.91). In a multivariable regression, PMN% was associated with high SLI (odds ratio [OR] 1.46 [95% confidence interval (CI) 1.14-1.85]). Synovial fluid monocyte percentage was negatively associated with high SLI (OR 0.44 [95% CI 0.27-0.73]). Synovial fluid WBC count is sensitive and specific for differentiating high and low lymphocytic synovial inflammation. Further analysis of the synovial fluid as it relates to the adjacent tissue in different cohorts is needed.

To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90) + HLA-DRA hi sublining fibroblasts, IL1B + pro-inflammatory monocytes, ITGAX + TBX21 + autoimmune-associated B cells and PDCD1 + peripheral helper T (T PH ) cells and follicular helper T (T FH ) cells. We defined distinct subsets of CD8 + T cells characterized by GZMK + , GZMB + , and GNLY + phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1 + HLA-DRA hi fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis. Defining cell types and their activation status in rheumatoid arthritis (RA) is critical to understanding this disease. Raychaudhuri and colleagues leverage several single-cell -omics approaches to define the cellular processes and pathways in the human RA joint.

The synovium is a mesenchymal tissue composed mainly of fibroblasts, with a lining and sublining that surround the joints. In rheumatoid arthritis the synovial tissue undergoes marked hyperplasia, becomes inflamed and invasive, and destroys the joint 1 , 2 . It has recently been shown that a subset of fibroblasts in the sublining undergoes a major expansion in rheumatoid arthritis that is linked to disease activity 3 – 5 ; however, the molecular mechanism by which these fibroblasts differentiate and expand is unknown. Here we identify a critical role for NOTCH3 signalling in the differentiation of perivascular and sublining fibroblasts that express CD90 (encoded by THY1 ). Using single-cell RNA sequencing and synovial tissue organoids, we found that NOTCH3 signalling drives both transcriptional and spatial gradients—emanating from vascular endothelial cells outwards—in fibroblasts. In active rheumatoid arthritis, NOTCH3 and Notch target genes are markedly upregulated in synovial fibroblasts. In mice, the genetic deletion of Notch3 or the blockade of NOTCH3 signalling attenuates inflammation and prevents joint damage in inflammatory arthritis. Our results indicate that synovial fibroblasts exhibit a positional identity that is regulated by endothelium-derived Notch signalling, and that this stromal crosstalk pathway underlies inflammation and pathology in inflammatory arthritis. NOTCH3 signalling is shown to be the underlying driver of the differentiation and expansion of a subset of synovial fibroblasts implicated in the pathogenesis of rheumatoid arthritis.