GZMK+CD8+ T cells Target A Specific Acinar Cell Type in Sjögren’s Disease

GZMK+CD8+ T cells Target A Specific Acinar Cell Type in Sjögren’s Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article GZMK+CD8+ T cells Target A Specific Acinar Cell Type in Sjögren’s Disease Thomas JF Pranzatelli, Paola Perez, Anson Ku, Bruno Fernandes Matuck, and 39 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3601404/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Sjögren's Disease (SjD) is a systemic autoimmune disease without a clear etiology or effective therapy. Utilizing unbiased single-cell and spatial transcriptomics to analyze human minor salivary glands in health and disease we developed a comprehensive understanding of the cellular landscape of healthy salivary glands and how that landscape changes in SjD patients. We identified novel seromucous acinar cell types and identified a population of PRR4+CST3+WFDC2- seromucous acinar cells that are particularly targeted in SjD. Notably, GZMK +CD8 T cells, enriched in SjD, exhibited a cytotoxic phenotype and were physically associated with immune-engaged epithelial cells in disease. These findings shed light on the immune response's impact on transitioning acinar cells with high levels of secretion and explain the loss of this specific cell population in SjD. This study explores the complex interplay of varied cell types in the salivary glands and their role in the pathology of Sjögren's Disease. Health sciences/Diseases/Immunological disorders/Autoimmune diseases Health sciences/Medical research/Translational research Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Full Text Additional Declarations The authors declare no competing interests. Supplementary Files NMSupplementaryDataTable1.docx Supplemental Data Table 1 NMSupplementaryDataTable2.docx Supplemental Data Table 2 NMSupplementalDataTable3.docx Supplemental Data Table 3 SF1.pdf Figure S1. (a) Barplot of changes in cell proportion in disease and SSA positivity across all cell types. (b) Dotplot of genes found to be specific to Leiden clusters and used to annotate those clusters. (c) Dotplots of differentially expressed genes in Sjögren's and the cell types those genes are differentially expressed in. (d) Dotplots of differentially expressed genes in SSA+/- and the cell types those genes are differentially expressed in. (e) Dotplots of genes differentially expressed across Sjögren's and anti-SSA positivity and the cell types those genes are differentially expressed in. SF2new.pdf Figure S2. (a) Distribution of marker genes in SjD and non-SjD ISH samples. Samples are downsampled so that an equal number of cells are taken from all samples. (b) UMAP of the cells from ISH. There is a clear division by patient diagnosis. (c) UMAP colored by ISH quantification. SF3.pdf Figure S3. (a) UMAP colored by Gaussian mixture model (GMM) cluster. The sample number of clusters were used as input channels from the ISH data. (b) Distribution of ISH quantification for each cluster of cells. (c) Samples with cells colored by GMM cluster. GMM clusters broadly correspond to acinar, interstitial or immune tissue from one of three groups of patients: patients with a high focus score, patients with a low focus score or no focus score and antibody positivity, or patients who were antibody negative and had no focus score. Two non-SjD patients were outliers and clustered uniquely. SF4.pdf Figure S4. Transforming scRNA-seq data from gene expression to indices (a) reveals new organizations of cells and clinical feature-specific clusters. (b) UMAP of cells after transformation to an index S-score space with coloring by a new application of the Leiden clustering algorithm. (c) Proportions of index clusters that represent annotations in the original single-cell space. Some clusters are close to a single cell type; others contain a variety of cell types. There are no one-to-one mappings between index clusters and original annotations. (d) UMAP on index S-scores colored by original annotation. Some clusters are enriched for clinical features and multiple regions are homogenous in their clinical phenotype. (e) The original scRNA-seq UMAP overlaid with the index clusters. The two most specific index clusters are both found in the T cell island in the UMAP as well as the clusters associated with antigen-presenting cells. (f) Ratios of Sjögren's to non-Sjögren's and anti-SSA positive to negative patients in each of the index clusters. Two index clusters are found at the extremes of the plot: one with high SjD specificity and the other with high anti-SSA positive specificity. These index clusters are composed of T cells, B cells, dendritic cells, and macrophages. SF5.pdf Figure S5. Interferon response increased across cell types with SSA positivity. (a) Cells in the index UMAP colored by patient’s diagnosis and SSA positivity. (b) Changes in index expression with disease diagnosis and SSA positivity. (c) Feature plots of IFN score in SSA+ and SSA- patients. Except in M2 macrophages and endothelial populations, IFN response score is low across cell types in SSA negative individuals. (d) Barplot of IFN response S-score across cell types in SSA positive and negative patients. IFN response increases in every cell population. SF6.pdf Figure S6. PhenoCycler-Fusion 35-plex spatial proteomics confirms changes in glandular composition and cellular interactions. (a) Dot plot of multiple protein expression of cellular phenotypes (left-side of dot plot; EPCAM to CD20) and cellular state markers (right side of dot plot; HHP3 to IFNG). (b) Cellular proportion changes in SjD compared with nonSjD. (c) Per-cell log2 fold-changes in protein expression in SjD compared with non-SjD were calculated for all phenotype and segmented cells. (d) Cellular neighborhoods in SjD compared with non-SjD. (e) CellChat ligand-receptor analysis corroborating neighborhood analysis and the importance of B- and T-lymphocyte co-stimulatory signaling in SjD. (f) Representative PhenoCycler-Fusion immunofluorescent images from a lymphocytic focus showing infiltration with T- and B-lymphocytes around ducts and acini. SF7.pdf Figure S7. (a) Evaluation of the induction of apoptosis after transfection of recombinant GZMK, GZMB, β-Gal, or Naive (mock) in immortalized NS-SV-TTAC Acinar Cells using Annexin V/PI staining and flow cytometric analysis. 100,000 events were measured and performed in biological duplicate (except for 𝛽-Gal) *- p <0.05, ANOVA. (b) Optimization of protein transfection with GZMK in HSG cells. Granzyme K levels were normalized to 𝛽-Actin and determined ratios are compared to control. (c) Transfection of GZMK and GZMB into NS-SV-TTAC exhibits time-dependent degradation over 48 hours. Granzyme K and B levels were normalized to 𝛽-Actin and determined ratios are compared to naive sample. (d) GZMK transfection induced dose-dependent increases in pIRF3 by Western immunoblot in pSGEC. (e) THP1-macrophages were transfected with proteins (i.e., GZMK, GZMB, GFP, and mock) and analyzed by fluorescence microscopy showing GZMK induces cytosolic relocalization of mtDNA to the cytosol. Image is representative of the findings from three biological replicates. (f) Engineered cell lines were used to measure IRF Pathway and Type I IFN induction using THP1-ISH Lucia and HEK-IFNa/b SEAP cells, respectively. Assays were performed on technical triplicates from biological duplicates and compared using ANOVA; results presented are a single representative experiment from the three experimental replicates. SF8.pdf Figure S8. (a) Representative marker genes spatial plots for seromucous ( MUC7 ) and mucous ( MUC5B ) acini, fibroblasts ( LUM ), and T cells ( CD3E ). Note SjD accompanies major shifts in seromucous acinar cell (SMAC) cell composition, T cells, and fibrosis. (b) Cartoon depicting cellular colocalization and cooccurrence analyses. Reference cell types were integrated from existing scRNA-seq (Figure 1e) data using Cell2Location to infer cell type locations in spRNA-seq. (c) Autocorrelations of cell types form a colocalization matrix that reconstructs the usual architecture of the glands. In SjD, the general architecture remains preserved; however, shifts in colocalizations can be appreciated in multiple cell types. (d) Shown are CD8+ exhausted T cells and P RR4+CST3+WFDC2- seromucous acinar cells (SMACs) along with manually annotated ducts and immune infiltrates. Top tissue is from a healthy volunteer and bottom tissue is from a patient with a diagnosis for Sjögren’s. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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salivary gland biopsies on all subjects. Single-cell RNA-sequencing data from 94,227 cells was gathered across 25 patients with and without SjD disease. (a) A cartoon depicting the sample collection from subjects and the creation of scRNA-seq and spRNA-seq libraries. Histological interpretations were rendered on all subjects and patients’ glands. Additional subjects, not included in the scRNAseq analyses, were used for flow cytometry, 10X Visium spatial transcriptomics, multiplex fluorescent in situ hybridization (PhenoCycler-Fusion), and multiplex immunofluorescence microscopy. (b) The microscopic appearance of minor salivary glands from non-SjD and SjD patients. Note the multiple scattered lymphocytic foci, periductal fibrosis, and atrophy characteristic of SjD. (c) A heatmap of clinical features for the scRNA-seq patients exhibiting the intrinsic clinical heterogeneity of subject phenotypes (e.g., SjD, non-SjD sicca). (d) PCA of patients using five of the clinical features. Importantly, the second principal component of the PCA analysis divides the patients on autoantibody positivity for anti-SSA autoantibodies (SSA+).\u0026nbsp; (e) Leiden clustering followed by manual annotation based on gene expression and UMAP embeddings enables granular distinctions between cell types. Cells clustered with Leiden clustering in scanpy are labeled along with manual embeddings based on cell expression and boundaries in UMAP embeddings in boxes. In total, 31 unique cell types, including seven types of seromucous acinar cells, were identified. Two PRR4- SMAC populations were combined into one “transitioning” population. (f) Cells by the diagnosis of the patient, with and without SjD. (g) Cells clustered by anti-SSA autoantibody positivity from patients.\u003c/p\u003e","description":"","filename":"F1.tif","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/5b18e42fbd088e0b86b3ceb2.tif"},{"id":60095727,"identity":"7e19ab1c-4941-4369-befe-4445a9ccf274","added_by":"auto","created_at":"2024-07-11 17:26:54","extension":"tif","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1437271,"visible":true,"origin":"","legend":"\u003cp\u003eOne seromucous acinar cell population represents the greatest loss of epithelium in disease. (a) Expression of acinar cell type markers in the scRNAseq data including in the six distinct populations of seromucous acinar cell types and two populations of mucous acinar cells. (b) Cell trajectory for ductal and seromucous acinar cells using wishbone, starting with the cell most positive for \u003cem\u003eKRT5\u003c/em\u003e, a marker of progenitor state. The cell trajectory starts with a small population of ductal progenitors and proceeds along the ducts to the seromucous acinar cells, ending in the CST3- populations. (c) Gene expression (after log-transformation) for marker genes along the wishbone trajectory as a fraction of maximum expression. \u003cem\u003eWFDC2\u003c/em\u003e expression is lost first, followed by \u003cem\u003eCST3\u003c/em\u003e. \u003cem\u003eMUC7\u003c/em\u003e expression peaks in the center and \u003cem\u003eLYZ\u003c/em\u003e and \u003cem\u003eZG16B\u003c/em\u003e are highest in the most differentiated SMACs. (d) Statistically significant changes in cell proportions between SjD and nonSjD. PRR4+CST3+WFDC2- SMACs were the most abundant population in non-SjD patients and presented the greatest loss in SjD. (e) Representative images showing multiplex in-situ RNA hybridization of acinar and disease marker genes in salivary glands.\u003c/p\u003e","description":"","filename":"lowF2.tif","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/592241a80095907f0b43eebd.tif"},{"id":60095728,"identity":"443f9ab2-9e6f-4952-b70d-fb0e60e99c30","added_by":"auto","created_at":"2024-07-11 17:26:54","extension":"tif","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1395500,"visible":true,"origin":"","legend":"\u003cp\u003eClinical research investigations for 25 subjects included comprehensive oral, rheumatological, and ophthalmologic investigations applying American College of Rheumatology 2016 Sjögren's Disease Classification Criteria including salivary gland biopsies on all subjects. Single-cell RNA-sequencing data from 94,227 cells was gathered across 25 patients with and without SjD disease. (a) A cartoon depicting the sample collection from subjects and the creation of scRNA-seq and spRNA-seq libraries. Histological interpretations were rendered on all subjects and patients’ glands. Additional subjects, not included in the scRNAseq analyses, were used for flow cytometry, 10X Visium spatial transcriptomics, multiplex fluorescent in situ hybridization (PhenoCycler-Fusion), and multiplex immunofluorescence microscopy. (b) The microscopic appearance of minor salivary glands from non-SjD and SjD patients. Note the multiple scattered lymphocytic foci, periductal fibrosis, and atrophy characteristic of SjD. (c) A heatmap of clinical features for the scRNA-seq patients exhibiting the intrinsic clinical heterogeneity of subject phenotypes (e.g., SjD, non-SjD sicca). (d) PCA of patients using five of the clinical features. Importantly, the second principal component of the PCA analysis divides the patients on autoantibody positivity for anti-SSA autoantibodies (SSA+).\u0026nbsp; (e) Leiden clustering followed by manual annotation based on gene expression and UMAP embeddings enables granular distinctions between cell types. Cells clustered with Leiden clustering in scanpy are labeled along with manual embeddings based on cell expression and boundaries in UMAP embeddings in boxes. In total, 31 unique cell types, including seven types of seromucous acinar cells, were identified. Two PRR4- SMAC populations were combined into one “transitioning” population. (f) Cells by the diagnosis of the patient, with and without SjD. (g) Cells clustered by anti-SSA autoantibody positivity from patients.\u003c/p\u003e","description":"","filename":"F1.tif","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/143814b4dc6509dad101db59.tif"},{"id":60095184,"identity":"27e18f43-901f-49de-89ce-a9e4515b6ce4","added_by":"auto","created_at":"2024-07-11 17:18:54","extension":"tif","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4441524,"visible":true,"origin":"","legend":"\u003cp\u003eCD8 T Exhausted T cells are enriched in the immune infiltrates of SjD and exhibit an effector phenotype. (a) Highly multiplexed (4/35-plex shown) immunofluorescence microscopy shows distribution of CD4+ and CD8+ T cells, as well as, CD68+ macrophages in the glands of SjD and nonSjD. (b,c) scRNAseq UMAPs of expression using only T cells, with disease diagnosis and anti-SSA positivity visualized. T cells from anti-SSA positive individuals cluster on the periphery while SjD-positive T cells are distributed throughout. (d) Expression of key T cell genes in exhausted and effector CD8+ T cells across disease severity. (e) Single cell pathway enrichment analysis shows similar activated profiles between \u003cem\u003eGZMK\u003c/em\u003e+ CD8+ Exhausted T cells and CD8+ Effector T cells in SjD. (f) The potential for degranulation and cytotoxicity of T cells was measured \u003cem\u003eex vivo\u003c/em\u003e using flow cytometry-based T-lymphocyte cytotoxicity assay. CD45+ immune cells were dissociated from patients’ salivary glands (nonSjD: n=5 patients; SjD: n=6 patients). (g) Spatial plots of segmented and phenotyped multiplex immunofluorescence data confirm alterations in the cellular arrangement of the glands, and highlight T cells at the epithelial interface in SjD. (h) CellChat Ligand-receptor analysis of scRNAseq data shows enriched signaling pathways (e.g.,\u0026nbsp; “MHC-I signaling”) is specific to anti-SSA+ SjD with connections to multiple cell types and the physical location of CD8+ T cells to immune-involved epithelia is shown.\u003c/p\u003e","description":"","filename":"lowF4.tif","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/055d85325ccfce2c2e77662e.tif"},{"id":60095181,"identity":"bfaac4a0-3a37-43d6-8ea6-762a812eee7a","added_by":"auto","created_at":"2024-07-11 17:18:54","extension":"tif","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5826185,"visible":true,"origin":"","legend":"\u003cp\u003eGZMK drives cellular innate immune signaling in SjD. (a) Multiplex immunofluorescence of salivary glands sections from SjD and nonSjD hybridized with anti-GZMK, -GZMB, and -CD8. Immune infiltrates enriched with GZMK+CD8+ T cells in close proximity to acinar structures and ducts are shown. (b) Fluorescent confocal microscopy was used to measure cytosolic mitochondrial DNA after GZMK protein transfection. The transfection of recombinant GZMK and GZMB were monitored by their His tag.\u0026nbsp; Image analysis demonstrates increased mtDNA in the cytoplasm. (c) Multiplex immunofluorescence microscopy shows cytosolic transfection of GZMK drives phosphorylation IRF3 (pIRF3) and nuclear translocation in pSGEC.\u003c/p\u003e","description":"","filename":"F5.tif","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/c58d71e41d0feecfe9025884.tif"},{"id":60095731,"identity":"df025396-a266-496c-b9e1-e90b8512a588","added_by":"auto","created_at":"2024-07-11 17:26:55","extension":"tif","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1080405,"visible":true,"origin":"","legend":"\u003cp\u003eThe quantification of cell types per spot according to Cell2Location. (a) Cell cooccurrence scores most different in disease. Immune cell colocalization with the \u003cem\u003ePRR4+CST3+WFDC2-\u003c/em\u003e seromucous population is highest in SSA+ Sjögren's patients. (b) Cooccurrence score spatial plots depict the altered cooccurrences between cell types including loss of cooccurrence of ductal cells with fibroblasts and increased cooccurrence of ductal cells with ductal progenitors, CD8+ Exhausted T cells with \u003cem\u003ePRR4+CST3+WFDC2-\u003c/em\u003e SMACS, and high \u003cem\u003eZG16B\u003c/em\u003e SMACS with \u003cem\u003ePRR4+CST3-WFDC2-\u003c/em\u003e SMACS.\u003c/p\u003e","description":"","filename":"F6.tif","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/d56f958b91ff871900c7b711.tif"},{"id":60097130,"identity":"8f767965-8f62-48bb-ad1b-11ab88b100aa","added_by":"auto","created_at":"2024-07-11 17:51:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2201475,"visible":true,"origin":"","legend":"","description":"","filename":"SingleCellPaperclean.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2_covered_20ab686f-7aca-4c72-bbb5-55ca34b005b0.pdf"},{"id":60095178,"identity":"4e34accb-1c15-4291-a9a4-c3fdb66b82d9","added_by":"auto","created_at":"2024-07-11 17:18:54","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22050,"visible":true,"origin":"","legend":"\u003cp\u003eSupplemental Data Table 1\u003c/p\u003e","description":"","filename":"NMSupplementaryDataTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/ab6096cc3b33a74b3be3585f.docx"},{"id":60095192,"identity":"d8580167-8a6e-4eed-bf4a-7570f6043ae5","added_by":"auto","created_at":"2024-07-11 17:18:55","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":28469,"visible":true,"origin":"","legend":"\u003cp\u003eSupplemental Data Table 2\u003c/p\u003e","description":"","filename":"NMSupplementaryDataTable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/a30a78d40b8faa2183a33a64.docx"},{"id":60095180,"identity":"ab978a1d-2d6e-4a5e-9aa4-763b3e1de8b5","added_by":"auto","created_at":"2024-07-11 17:18:54","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":15834,"visible":true,"origin":"","legend":"\u003cp\u003eSupplemental Data Table 3\u003c/p\u003e","description":"","filename":"NMSupplementalDataTable3.docx","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/34d25d2bdeb0f39d51d58a97.docx"},{"id":60096077,"identity":"22d9e69a-e019-4a2e-b1e6-a077c143e516","added_by":"auto","created_at":"2024-07-11 17:34:55","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2175209,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S1. (a) Barplot of changes in cell proportion in disease and SSA positivity across all cell types. (b) Dotplot of genes found to be specific to Leiden clusters and used to annotate those clusters. (c) Dotplots of differentially expressed genes in Sjögren's and the cell types those genes are differentially expressed in. (d) Dotplots of differentially expressed genes in SSA+/- and the cell types those genes are differentially expressed in. (e) Dotplots of genes differentially expressed across Sjögren's and anti-SSA positivity and the cell types those genes are differentially expressed in.\u003c/p\u003e","description":"","filename":"SF1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/38f79cfd52fa9b2ce369ab21.pdf"},{"id":60095186,"identity":"ee1abfaa-7177-4856-82fe-050c2bda91ca","added_by":"auto","created_at":"2024-07-11 17:18:55","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":4396412,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S2. (a) Distribution of marker genes in SjD and non-SjD ISH samples. Samples are downsampled so that an equal number of cells are taken from all samples. (b) UMAP of the cells from ISH. There is a clear division by patient diagnosis. (c) UMAP colored by ISH quantification.\u003c/p\u003e","description":"","filename":"SF2new.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/f0af497d113aa1bc6ac1c923.pdf"},{"id":60095193,"identity":"52bf8896-3d0a-4506-954f-3c6052eb6c5e","added_by":"auto","created_at":"2024-07-11 17:18:56","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":72790786,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S3. (a) UMAP colored by Gaussian mixture model (GMM) cluster. The sample number of clusters were used as input channels from the ISH data. (b) Distribution of ISH quantification for each cluster of cells. (c) Samples with cells colored by GMM cluster. GMM clusters broadly correspond to acinar, interstitial or immune tissue from one of three groups of patients: patients with a high focus score, patients with a low focus score or no focus score and antibody positivity, or patients who were antibody negative and had no focus score. Two non-SjD patients were outliers and clustered uniquely.\u003c/p\u003e","description":"","filename":"SF3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/62ff88215300e2e4b502c257.pdf"},{"id":60095195,"identity":"ee4b64f7-fa90-4973-bb65-4093c7c82828","added_by":"auto","created_at":"2024-07-11 17:18:56","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":90086871,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S4. Transforming scRNA-seq data from gene expression to indices (a) reveals new organizations of cells and clinical feature-specific clusters. (b) UMAP of cells after transformation to an index S-score space with coloring by a new application of the Leiden clustering algorithm. (c) Proportions of index clusters that represent annotations in the original single-cell space. Some clusters are close to a single cell type; others contain a variety of cell types. There are no one-to-one mappings between index clusters and original annotations. (d) UMAP on index S-scores colored by original annotation. Some clusters are enriched for clinical features and multiple regions are homogenous in their clinical phenotype. (e) The original scRNA-seq UMAP overlaid with the index clusters. The two most specific index clusters are both found in the T cell island in the UMAP as well as the clusters associated with antigen-presenting cells. (f) Ratios of Sjögren's to non-Sjögren's and anti-SSA positive to negative patients in each of the index clusters. Two index clusters are found at the extremes of the plot: one with high SjD specificity and the other with high anti-SSA positive specificity. These index clusters are composed of T cells, B cells, dendritic cells, and macrophages.\u003c/p\u003e","description":"","filename":"SF4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/c3560c37e56ef45a850f697c.pdf"},{"id":60095733,"identity":"c913e921-d876-4cd4-980b-34d7a80d1381","added_by":"auto","created_at":"2024-07-11 17:26:56","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":95737949,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S5. Interferon response increased across cell types with SSA positivity. (a) Cells in the index UMAP colored by patient’s diagnosis and SSA positivity. (b) Changes in index expression with disease diagnosis and SSA positivity. (c) Feature plots of IFN score in SSA+ and SSA- patients. Except in M2 macrophages and endothelial populations, IFN response score is low across cell types in SSA negative individuals. (d) Barplot of IFN response S-score across cell types in SSA positive and negative patients. IFN response increases in every cell population.\u003c/p\u003e","description":"","filename":"SF5.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/bea2e51c87fd378e2682bc9c.pdf"},{"id":60095730,"identity":"498aff1e-0c2d-4162-b772-0a493485d8a0","added_by":"auto","created_at":"2024-07-11 17:26:54","extension":"pdf","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":12474243,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S6. PhenoCycler-Fusion 35-plex spatial proteomics confirms changes in glandular composition and cellular interactions. (a) Dot plot of multiple protein expression of cellular phenotypes (left-side of dot plot; EPCAM to CD20) and cellular state markers (right side of dot plot; HHP3 to IFNG). (b) Cellular proportion changes in SjD compared with nonSjD. (c) Per-cell log2 fold-changes in protein expression in SjD compared with non-SjD were calculated for all phenotype and segmented cells. (d) Cellular neighborhoods in SjD compared with non-SjD. (e) CellChat ligand-receptor analysis corroborating neighborhood analysis and the importance of B- and T-lymphocyte co-stimulatory signaling in SjD. (f) Representative PhenoCycler-Fusion immunofluorescent images from a lymphocytic focus showing infiltration with T- and B-lymphocytes around ducts and acini.\u003c/p\u003e","description":"","filename":"SF6.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/60bb0306b397bffea8607728.pdf"},{"id":60095189,"identity":"18134ac5-2fab-49e7-8ed8-bf1a8aacadd2","added_by":"auto","created_at":"2024-07-11 17:18:55","extension":"pdf","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":37502060,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S7. (a) Evaluation of the induction of apoptosis after transfection of recombinant GZMK, GZMB, β-Gal, or Naive (mock) in immortalized NS-SV-TTAC Acinar Cells using Annexin V/PI staining and flow cytometric analysis. 100,000 events were measured and performed in biological duplicate (except for 𝛽-Gal) *- \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ANOVA. (b) Optimization of protein transfection with GZMK in HSG cells. Granzyme K levels were normalized to 𝛽-Actin and determined ratios are compared to control. (c) Transfection of GZMK and GZMB into NS-SV-TTAC exhibits time-dependent degradation over 48 hours. Granzyme K and B levels were normalized to 𝛽-Actin and determined ratios are compared to naive sample. (d) GZMK transfection induced dose-dependent increases in pIRF3 by Western immunoblot in pSGEC. (e) THP1-macrophages were transfected with proteins (i.e., GZMK, GZMB, GFP, and mock) and analyzed by fluorescence microscopy showing GZMK induces cytosolic relocalization of mtDNA to the cytosol. Image is representative of the findings from three biological replicates. (f) Engineered cell lines were used to measure IRF Pathway and Type I IFN induction using THP1-ISH Lucia and HEK-IFNa/b SEAP cells, respectively. Assays were performed on technical triplicates from biological duplicates and compared using ANOVA; results presented are a single representative experiment from the three experimental replicates.\u003c/p\u003e","description":"","filename":"SF7.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/091bb7c4c3ba7515d941bcbc.pdf"},{"id":60095191,"identity":"7a1a807f-3f03-43ab-898a-8c18f8c98c4d","added_by":"auto","created_at":"2024-07-11 17:18:55","extension":"pdf","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":16540975,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S8. (a) Representative marker genes spatial plots for seromucous (\u003cem\u003eMUC7\u003c/em\u003e) and mucous (\u003cem\u003eMUC5B\u003c/em\u003e) acini, fibroblasts (\u003cem\u003eLUM\u003c/em\u003e), and T cells (\u003cem\u003eCD3E\u003c/em\u003e). Note SjD accompanies major shifts in seromucous acinar cell (SMAC) cell composition, T cells, and fibrosis. (b) Cartoon depicting cellular colocalization and cooccurrence analyses. Reference cell types were integrated from existing scRNA-seq (Figure 1e) data using Cell2Location to infer cell type locations in spRNA-seq. (c) Autocorrelations of cell types form a colocalization matrix that reconstructs the usual architecture of the glands. In SjD, the general architecture remains preserved; however, shifts in colocalizations can be appreciated in multiple cell types. (d) Shown are CD8+ exhausted T cells and P\u003cem\u003eRR4+CST3+WFDC2-\u003c/em\u003e seromucous acinar cells (SMACs) along with manually annotated ducts and immune infiltrates. Top tissue is from a healthy volunteer and bottom tissue is from a patient with a diagnosis for Sjögren’s.\u003c/p\u003e","description":"","filename":"SF8.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3601404/v2/7b7e9e35de7b409f1aa9a441.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eGZMK+CD8+ T cells Target A Specific Acinar Cell Type in Sjögren’s Disease\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3601404/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3601404/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSjögren's Disease (SjD) is a systemic autoimmune disease without a clear etiology or effective therapy. Utilizing unbiased single-cell and spatial transcriptomics to analyze human minor salivary glands in health and disease we developed a comprehensive understanding of the cellular landscape of healthy salivary glands and how that landscape changes in SjD patients. We identified novel seromucous acinar cell types and identified a population of \u003cem\u003ePRR4+CST3+WFDC2-\u003c/em\u003eseromucous acinar cells that are particularly targeted in SjD. Notably, \u003cem\u003eGZMK\u003c/em\u003e+CD8 T cells, enriched in SjD, exhibited a cytotoxic phenotype and were physically associated with immune-engaged epithelial cells in disease. These findings shed light on the immune response's impact on transitioning acinar cells with high levels of secretion and explain the loss of this specific cell population in SjD. This study explores the complex interplay of varied cell types in the salivary glands and their role in the pathology of Sjögren's Disease.\u003c/p\u003e","manuscriptTitle":"GZMK+CD8+ T cells Target A Specific Acinar Cell Type in Sjögren’s Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2024-07-11 17:18:49","doi":"10.21203/rs.3.rs-3601404/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2023-12-19 16:27:35","doi":"10.21203/rs.3.rs-3601404/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4349fe8b-47f8-46e4-afd0-46df5e888ded","owner":[],"postedDate":"July 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":34470959,"name":"Health sciences/Diseases/Immunological disorders/Autoimmune diseases"},{"id":34470960,"name":"Health sciences/Medical research/Translational research"}],"tags":[],"updatedAt":"2024-02-01T18:05:50+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-11 17:18:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-3601404","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3601404","identity":"rs-3601404","version":["v2"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}