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Autoimmune connective tissue diseases arise in a stepwise fashion from asymptomatic preclinical autoimmunity. Type I interferons have a crucial role in the progression to established autoimmune diseases. The cellular source and regulation in disease initiation of these cytokines is not clear, but plasmacytoid dendritic cells have been thought to contribute to excessive type I interferon production. Here, we show that in preclinical autoimmunity and established systemic lupus erythematosus, plasmacytoid dendritic cells are not effector cells, have lost capacity for Toll-like-receptor-mediated cytokine production and do not induce T cell activation, independent of disease activity and the blood interferon signature. In addition, plasmacytoid dendritic cells have a transcriptional signature indicative of cellular stress and senescence accompanied by increased telomere erosion. In preclinical autoimmunity, we show a marked enrichment of an interferon signature in the skin without infiltrating immune cells, but with interferon-κ production by keratinocytes. In conclusion, non-hematopoietic cellular sources, rather than plasmacytoid dendritic cells, are responsible for interferon production prior to clinical autoimmunity. Type I interferon drives autoimmune pathology in SLE and has been assumed to come predominantly from plasmacytoid dendritic cells (pDCs). Here, the authors show that prior to the onset of SLE, pDCs lose multiple immunogenic functions and, instead, non-hematopoietic cells such as keratinocytes are a major source of type I interferons.

N6-methyladenosine (m6A) is the most abundant internal RNA modification of cellular mRNAs. m6A is recognised by YTH domain-containing proteins, which selectively bind to m6A-decorated RNAs regulating their turnover and translation. Using an m6A-modified hairpin present in the Kaposi’s sarcoma associated herpesvirus (KSHV) ORF50 RNA, we identified seven members from the ‘Royal family’ as putative m6A readers, including SND1. RIP-seq and eCLIP analysis characterised the SND1 binding profile transcriptome-wide, revealing SND1 as an m6A reader. We further demonstrate that the m6A modification of the ORF50 RNA is critical for SND1 binding, which in turn stabilises the ORF50 transcript. Importantly, SND1 depletion leads to inhibition of KSHV early gene expression showing that SND1 is essential for KSHV lytic replication. This work demonstrates that members of the ‘Royal family’ have m6A-reading ability, greatly increasing their epigenetic functions beyond protein methylation. When a cell needs to make a protein, it reads from the master copy of the gene in the DNA and prints out temporary duplicates called mRNA. These duplicates then act as templates for protein production. Both DNA and mRNA can be further modified by adding on chemical tags that recruit specific proteins. While chemical modifications in DNA are known to control the activity of genes, their role in mRNA is only just being uncovered. One of the most common chemical modifications in mRNA is the addition of a methyl group called m6A. This methyl group has also been found in the mRNA of certain viruses, including the Kaposi’s sarcoma-associated herpesvirus (KSHV) which causes cancer. Recent work has shown that a family of proteins, known as the YTH family, can recognise and bind to this specific methyl group and regulate the rate at which mRNA degrades. To investigate whether other proteins can recognise m6A, Baquero-Pérez et al. mapped the m6A residues of mRNAs encoded by KSHV genes and looked at which proteins the methyl mark interacts with. The experiments revealed that a family of proteins – nicknamed the ‘Royal family’ – that recognise methyl groups in proteins, can also bind to mRNA that contains m6A. Baquero-Pérez et al. showed that a member of this family, SND1, can read the m6A methyl mark on mRNAs from both the virus and the host cell. Further experiments showed that SND1 binds to and stabilises a viral mRNA which provides the template for a protein that the virus needs to replicate. When SND1 was removed from human immune cells infected with KSHV, this caused the virus to replicate less efficiently. The discovery that the Royal family of proteins can recognise methylated mRNA as well as methylated proteins suggests that there may be a common feature that allows proteins to read methylation. Understanding the shape of this feature could lead to new treatments that block viruses from making the proteins they need to replicate.

Meta-analysis of single-cell RNA sequencing datasets identifies core fibroblasts present in all organs that may give rise to more specialized organ-specific subtypes.

The colonic epithelium facilitates host–microorganism interactions to control mucosal immunity, coordinate nutrient recycling and form a mucus barrier. Breakdown of the epithelial barrier underpins inflammatory bowel disease (IBD). However, the specific contributions of each epithelial-cell subtype to this process are unknown. Here we profile single colonic epithelial cells from patients with IBD and unaffected controls. We identify previously unknown cellular subtypes, including gradients of progenitor cells, colonocytes and goblet cells within intestinal crypts. At the top of the crypts, we find a previously unknown absorptive cell, expressing the proton channel OTOP2 and the satiety peptide uroguanylin, that senses pH and is dysregulated in inflammation and cancer. In IBD, we observe a positional remodelling of goblet cells that coincides with downregulation of WFDC2—an antiprotease molecule that we find to be expressed by goblet cells and that inhibits bacterial growth. In vivo, WFDC2 preserves the integrity of tight junctions between epithelial cells and prevents invasion by commensal bacteria and mucosal inflammation. We delineate markers and transcriptional states, identify a colonic epithelial cell and uncover fundamental determinants of barrier breakdown in IBD. Profiling of single epithelial cells in healthy and inflamed colons identifies specialized cellular subpopulations, including a type of goblet cell that secretes the antibacterial protein WFDC2, which preserves the integrity of the epithelial barrier layer.

Colonic antigen-experienced lymphocytes such as tissue-resident memory CD8 + T cells can respond rapidly to repeated antigen exposure. However, their cellular phenotypes and the mechanisms by which they drive immune regulation and inflammation remain unclear. Here we compiled an unbiased atlas of human colonic CD8 + T cells in health and ulcerative colitis (UC) using single-cell transcriptomics with T-cell receptor repertoire analysis and mass cytometry. We reveal extensive heterogeneity in CD8 + T-cell composition, including expanded effector and post-effector terminally differentiated CD8 + T cells. While UC-associated CD8 + effector T cells can trigger tissue destruction and produce tumor necrosis factor (TNF)-α, post-effector cells acquire innate signatures to adopt regulatory functions that may mitigate excessive inflammation. Thus, we identify colonic CD8 + T-cell phenotypes in health and UC, define their clonal relationships and characterize terminally differentiated dysfunctional UC CD8 + T cells expressing IL-26, which attenuate acute colitis in a humanized IL-26 transgenic mouse model. Multimodal single-cell profiling reveals heterogeneity of colonic CD8 + T cells in patients with ulcerative colitis, including expansion of a chronically activated IL-26-expressing subpopulation with innate-like features.

The colonic epithelial turnover is driven by crypt-base stem cells that express the R-spondin receptor Lgr5. Signals that regulate epithelial regeneration upon stem cell injury are largely unknown. Here, we explore the dynamics of Wnt signaling in the colon. We identify two populations of cells with active Wnt signaling: highly proliferative Lgr5 + /Axin2 + cells, as well as secretory Lgr5 − /Axin2 + cells. Upon Lgr5 + cell depletion, these cells are recruited to contribute to crypt regeneration. Chemical injury induced by DSS leads to a loss of both Lgr5 + cells and Axin2 + cells and epithelial regeneration is driven by Axin2 −  cells, including differentiated Krt20 + surface enterocytes. Regeneration requires stromal Rspo3, which is present at increased levels upon injury and reprograms Lgr5 − but Lgr4 + differentiated cells. In contrast, depletion of stromal Rspo3 impairs crypt regeneration, even upon mild injury. We demonstrate that Rspo3 is essential for epithelial repair via induction of Wnt signaling in differentiated cells. Epithelial turnover in the colon requires stem cells in the crypt that express the R-spondin receptor Lgr5. Here, the authors show that regeneration after colon injury involving loss of Lgr5 + and Axin2 + cells requires stromal derived Rspo3-dependent reprogramming of Lgr4 + differentiated cells, including Krt20 + enterocytes.

Abstract The intestinal mucosa represents a unique environment where the coordinated function of diverse epithelial, mesenchymal, and immune cells maintains a physiologically balanced environment in the presence of gut microbiota. The intestinal mucosa plays a central role in the pathogenesis of inflammatory bowel disease (IBD), yet the molecular and cellular composition of this diverse environment is poorly understood. However, the recent advent of multimodal single-cell technologies, including single-cell RNA sequencing (scRNA-seq), now provides an opportunity to accurately map the tissue architecture, characterize rare cell types that were previously overlooked, and define function at a single-cell level. In this review, we summarize key advances in single-cell technology and provide an overview of important aspects of computational analysis. We describe emerging data in the field of IBD and discuss how the characterization of novel intestinal mucosa cell populations is reshaping our understanding of this complex disease. We conclude by considering the potential clinical applications, including the definition of novel drug targets and the opportunity for personalization of care in this exciting new era of precision medicine. This review describes the recent advent of multimodal single-cell technologies, including single-cell RNA sequencing, and discusses how characterization of novel intestinal mucosa cell populations in health and IBD may have potential clinical applications, including drug discovery and personalization of care.

Single cell spatial interrogation of the immune-structural interactions in COVID −19 lungs is challenging, mainly because of the marked cellular infiltrate and architecturally distorted microstructure. To address this, we develop a suite of mathematical tools to search for statistically significant co-locations amongst immune and structural cells identified using 37-plex imaging mass cytometry. This unbiased method reveals a cellular map interleaved with an inflammatory network of immature neutrophils, cytotoxic CD8 T cells, megakaryocytes and monocytes co-located with regenerating alveolar progenitors and endothelium. Of note, a highly active cluster of immature neutrophils and CD8 T cells, is found spatially linked with alveolar progenitor cells, and temporally with the diffuse alveolar damage stage. These findings offer further insights into how immune cells interact in the lungs of severe COVID-19 disease. We provide our pipeline [Spatial Omics Oxford Pipeline (SpOOx)] and visual-analytical tool, Multi-Dimensional Viewer (MDV) software, as a resource for spatial analysis. Mathematical tools can be used to help identify pathological features from images of diseased lungs. Here, the authors used mathematical tools combined with high resolution multiplex imaging mass cytometry to show an association between immature neutrophils, CD8 T cells and proliferating alveolar epithelial cells in areas of maximal alveolar damage in COVID-19 lungs.

Healthy alveolar repair relies on the ability of alveolar stem cells to differentiate into specialized epithelial cells for gas exchange. In chronic fibrotic lung diseases such as idiopathic pulmonary fibrosis (IPF), this regenerative process is abnormal but the underlying mechanisms remain unclear. Here, using human lung tissue that represents different stages of disease and a 33-plex single-cell imaging mass cytometry (IMC), we present a high-resolution, temporo-spatial cell atlas of the regenerating alveolar niche. With unbiased mathematical methods which quantify statistically enriched interactions, CD206 hi macrophage subtype and an alveolar basal intermediate epithelial cell emerge as the most statistically robust spatial association in the epithelial and immune cell interactome, found across all stages of disease. Spatially resolved receptor–ligand analysis further offers an in silico mechanism by which these macrophages may influence epithelial regeneration. These findings provide a foundational step toward understanding immune–epithelial dynamics in aberrant alveolar regeneration in IPF. The cause of abnormal alveolar regeneration in idiopathic pulmonary fibrosis is unknown. Here, the authors generated a temporo-spatial cellular map of the regenerating niche and, using unbiased mathematical methods, identified a spatial interaction between a subset of macrophages and aberrant alveolar epithelial cells across all stages of the disease.

Background T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, which has sparked interest in the development of various T-cell-focused immunotherapies. However, the identification of antigens recognised by T-cells is low-throughput and laborious. To overcome some of these limitations, computational methods for predicting CD8 + T-cell epitopes have emerged. Despite recent developments, most immunogenicity algorithms struggle to learn features of peptide immunogenicity from small datasets, suffer from HLA bias and are unable to reliably predict pathology-specific CD8 + T-cell epitopes. Methods We developed TRAP (T-cell recognition potential of HLA-I presented peptides), a robust deep learning workflow for predicting CD8 + T-cell epitopes from MHC-I presented pathogenic and self-peptides. TRAP uses transfer learning, deep learning architecture and MHC binding information to make context-specific predictions of CD8 + T-cell epitopes. TRAP also detects low-confidence predictions for peptides that differ significantly from those in the training datasets to abstain from making incorrect predictions. To estimate the immunogenicity of pathogenic peptides with low-confidence predictions, we further developed a novel metric, RSAT (relative similarity to autoantigens and tumour-associated antigens), as a complementary to ‘dissimilarity to self’ from cancer studies. Results TRAP was used to identify epitopes from glioblastoma patients as well as SARS-CoV-2 peptides, and it outperformed other algorithms in both cancer and pathogenic settings. TRAP was especially effective at extracting immunogenicity-associated properties from restricted data of emerging pathogens and translating them onto related species, as well as minimising the loss of likely epitopes in imbalanced datasets. We also demonstrated that the novel metric termed RSAT was able to estimate immunogenic of pathogenic peptides of various lengths and species. TRAP implementation is available at: https://github.com/ChloeHJ/TRAP . Conclusions This study presents a novel computational workflow for accurately predicting CD8 + T-cell epitopes to foster a better understanding of antigen-specific T-cell response and the development of effective clinical therapeutics.