GeoMx Digital Spatial Profiler Immuno-oncology (IO) Proteome Atlas (IPA) Assay for Human Pancreas v1

2025-06-11

Purpose: This protocol details processing fixed paraffin sections from human pancreas for the Nanostring GeoMX digital spatial profiler (DSP) immuno-oncology proteome atlas (IPA). This technology is based upon a defined antibody panel of 575 markers. Each antibody is conjugated to an RNA probe. The RNA probes are designed with UV cleavable linkers and DSP barcodes. Fluorescent-labeled antibodies against antigens that define specific cell types were used as morphology markers. Morphology markers are used to identify cell types of interest with nuclear counterstaining permitting tissue spatial information. Sample regions of interest (ROI) are defined based on the three morphology markers and each ROI is illuminated with UV light thereby cleaving hybridized RNA probes. Cleaved probes are aspirated via microcapillary and deposited into a unique well of a 96-well collection plate. The collection plate is used for next generation sequencing (NGS). Scope: This document was written following GeoMX NGS guidelines (university.nanostring.com) with minor modifications for the University of Florida Molecular Pathology Core. The entire workflow is described for manual slide staining and GeoMX DSP instrument use. Steps for library construction, sequencing, bioinformatics, and data analysis are in outline form only. Library preparation and sequencing are outsourced to the University of Florida ICBR facility. Expected outcome: Targeted-protein quantification via bulk RNA-sequencing will be obtained from fixed human pancreas sections within regions of interest and subareas defined by cell morphology markers.

Exploring endothelial cell environments across organs in spatially resolved omics data

bioRxiv (Cold Spring Harbor Laboratory) · 2025-09-25 · 2 citations

Endothelial cells are ubiquitously present in the human body and line the luminal surface of blood and lymphatic vessels. The oxygen-dependence of cells impacts their proximity to blood vessels, and consequently, to endothelial cells depending on their functional properties and priorities. This paper presents cell-to-nearest-endothelial-cell distance distributions for various cell types using 399 spatially resolved omics datasets from 14 studies comprising 12 tissue types with a total of 47,349,496 cells. Additionally, we developed an open-source web-based interactive tool, Cell Distance Explorer, that allows researchers to interactively visualize cell graphs and linkages in 2D and 3D datasets. Finally, we present a hierarchical neighborhood analysis focused on the endothelial cell neighborhoods in small and large intestine datasets. This paper provides an open-access resource (datasets, tools, and analyses) to characterize and compare cell distances and cell neighborhoods in spatially resolved omics data.

27-OR: Identification of Novel Drivers of Type 1 Diabetes via Integration of Whole-Islet Transcriptomics from Human and Mouse

Diabetes · 2025-06-13

Introduction and Objective: Type 1 diabetes (T1D) is a polygenic, autoimmune disease characterized by pancreatic β-cell dysfunction and loss. We have recently demonstrated that β-cell dysfunction in T1D is independent of T cell infiltration into islets. To define β-cell changes in T1D, we employed an islet-centric approach to identify differentially expressed genes (DEGs) that change during T1D pathogenesis in insulin (INS)+ CD3- islets of at-risk cases. We hypothesize these DEGs contribute to β-cell failure. Methods: To nominate genetic drivers, human islet gene expression data from single AAb+, multiple AAb+ and T1D cases were integrated with the Diversity Outbred (DO) mice. This enabled us to identify strong cis-eQTL associated with alleles from the T1D-prone NOD mouse, one of eight founder strains of the DO. Results: We filtered 827 human DEGs to identify 142 DEGs with strong NOD-driven cis-eQTL. From those, 88 DEGs showed associations with diabetes in human genome-wide association studies. Remarkably, 49 cis-eQTL mapped within mouse diabetes susceptibility loci. Those genes were associated with transcription-translation (Gatc, Creb3, Fam133b, H1f3, Niban1, Smad4), glucose metabolism (Pgm1), mitochondrial function (Suclg2, Atp5e, Atp5g1, Pdhb, Acly, Coa5), insulin-granule biogenesis and exocytosis (Pcsk1, Rab2a, Cadps2. Atp2a2), and amino acid and metal transport and homeostasis (Slc36a4, Slc39a8, Slc4a7, Fth1). Conclusion: By leveraging genetics of DO mice, our functional genomics approach has identified genetic elements as specific genetic drivers of human T1D (in transcription/translation, glycolysis, mitochondria, and insulin secretion). By restricting the analysis to islets without immune infiltration these loci promote loss of β-cell function in the absence of T cell infiltration. Disclosure A.E. Cuaycal: None. M. Keller: None. E.A. Butterworth: None. J. Chen: None. M. Campbell-Thompson: None. P. Smadbeck: None. J. Flannick: None. I.C. Gerling: None. C.E. Mathews: None. Funding JDRF, NIH (P01 AI42288, UC4 DK104194, UC4 DK104167, UC4 DK104155)

3D imaging of human pancreas suggests islet size and endocrine composition influence their loss in type 1 diabetes

Research Square · 2025-06-04 · 5 citations

Single-Islet Proteomics Maps Pseudo-Temporal Islet Immune Responses and Dysfunction in Stage 1 Type 1 Diabetes

bioRxiv (Cold Spring Harbor Laboratory) · 2025-11-12

Progressive β-cell dysfunction precedes the onset of type 1 diabetes (T1D), yet the molecular mechanisms driving early T1D development remain poorly understood. Although single-cell RNA-sequencing has uncovered transcript-level changes in human islet cells, it offers limited insight into the heterogeneity of distinct islet microenvironments. Here, we applied a single-islet proteomics workflow to profile intra-donor islet heterogeneity in three stage 1 T1D cases with matched non-diabetic controls and define in situ protein signatures of pseudo-temporal islet dysfunction. Intra-donor analyses of ~100 individual islets per donor revealed highly consistent proteomic patterns reflecting pseudo-time progression of islet immune responses and β-cell dysfunction. Several pathways, including extracellular matrix remodeling and mRNA processing, were identified as closely associated with progressive islet immune activation and loss of β-cell function. These findings provide robust proteome-wide evidence of the progression of islet dysfunction, offer a valuable resource for investigating early mechanisms of T1D pathogenesis-including novel candidates for functional studies-and underscore the utility of single-islet spatial proteomics for examining islet heterogeneity in T1D.

Transcriptome-guided GLP-1 receptor therapy rescues metabolic and behavioral disruptions in a Bardet-Biedl syndrome mouse model

Journal of Clinical Investigation · 2025-04-15 · 6 citations

Bardet-Biedl syndrome (BBS), a ciliopathy characterized by obesity, hyperphagia, and learning deficits, arises from mutations in Bbs genes. Exacerbated symptoms occur with mutations in genes encoding the BBSome, a complex regulating primary cilia function. We investigated the mechanisms underlying BBS-induced obesity using a Bbs5-knockout (Bbs5-/-) mouse model. Bbs5-/- mice were characterized by hyperphagia, learning deficits, glucose/insulin intolerance, and disrupted metabolic hormones, phenocopying human BBS. White adipose tissue in these mice had a unique immunophenotype, with increased proinflammatory macrophages and dysfunctional Tregs, suggesting a mechanism for adiposity distinct from those of typical obesity models. Additionally, Bbs5-/- mice exhibited pancreatic islet hyperplasia but failed to normalize blood glucose, suggesting defective insulin action. Hypothalamic transcriptomics revealed dysregulation of endocrine signaling pathways, with functional analyses confirming defects in insulin, leptin, and cholecystokinin (CCK) signaling, while glucagon-like peptide-1 receptor (GLP-1R) responsiveness was preserved. Notably, treatment with a GLP-1RA effectively alleviated hyperphagia and body weight gain, improved glucose tolerance, and regulated circulating metabolic hormones in Bbs5-/- mice. This study suggests that Bbs5-/- mice represent a valuable translational model of BBS for understanding pathogenesis and developing better treatments. Our findings highlight the therapeutic potential of GLP-1RAs for managing BBS-associated metabolic dysregulation, indicating that further investigation for clinical application is warranted.

3D imaging of human pancreas suggests islet size and endocrine composition influence their loss in type 1 diabetes

Nature Communications · 2025-12-11 · 3 citations

A high-definition description of pancreatic islets would prove beneficial for understanding the pathophysiology of type 1 diabetes (T1D), yet significant knowledge gaps exist in terms of their size, endocrine cell composition, and number in both health and disease. Here, 3-dimensional (3D) analyses of pancreata from control persons without diabetes (ND) demonstrate approximately 50% of islets are insulin-positive (INS + ) glucagon-negative (GCG-). Non-diabetic individuals positive for a single Glutamic acid decarboxylase autoantibody (GADA + ) yet at increased risk for disease consistently demonstrate endocrine features, including islet volume and cell composition, closely resembling the age-matched ND controls. In contrast, pancreata from individuals with short-duration T1D demonstrate significantly reduced islet density and a dramatic loss of INS + GCG- islets with preservation of large INS + GCG+ islets. The size and cellular composition of pancreatic islets may, therefore, represent influential factors that impact β-cell loss during T1D disease progression. LSFM imaging revealed 3D islet maps: GADA+ cases mirrored controls, while short-duration T1D showed loss of small INS + GCG– islets but preserved larger mixed INS + GCG+ ones, highlighting islet size- and composition-dependent vulnerability

Enterovirus VP1 protein and HLA class I hyperexpression in pancreatic islet cells of organ donors with type 1 diabetes

Diabetologia · 2025-03-16 · 14 citations

Abstract Aims/hypothesis Earlier studies of pancreases from donors with type 1 diabetes demonstrated enteroviral capsid protein VP1 in beta cells. In the context of a multidisciplinary approach undertaken by the nPOD-Virus group, we assessed VP1 positivity in pancreas and other tissues (spleen, duodenum and pancreatic lymph nodes) from 188 organ donors, including donors with type 1 diabetes and donors expressing autoantibody risk markers. We also investigated whether VP1 positivity is linked to the hyperexpression of HLA class I (HLA-I) molecules in islet cells. Methods Organ donor tissues were collected by the Network for Pancreatic Organ Donors with Diabetes (nPOD) from donors without diabetes (ND, n =76), donors expressing a single or multiple diabetes-associated autoantibodies (AAb + , n =20; AAb ++ , n =9) and donors with type 1 diabetes with residual insulin-containing islets (T1D-ICIs, n =41) or only insulin-deficient islets (T1D-IDIs, n =42). VP1 was assessed using immunohistochemistry (IHC) and HLA-I using IHC and immunofluorescence, in two independent laboratories. We determined assay concordance across laboratories and overall occurrence of positive assays, on a case-by-case basis and between donor groups. Results Islet cell VP1 positivity was detected in most T1D-ICI donors (77.5%) vs only 38.2% of ND donors ( p <0.001). VP1 positivity was associated with HLA-I hyperexpression. Of those donors assessed for HLA-I and VP1, 73.7% had both VP1 immunopositivity and HLA-I hyperexpression ( p <0.001 vs ND). Moreover, VP1 + cells were detected at higher frequency in donors with HLA-I hyperexpression ( p <0.001 vs normal HLA-I). Among VP1 + donors, the proportion with HLA-I hyperexpression was significantly higher in the AAb ++ and T1D-ICI groups (94.9%, p <0.001 vs ND); this was not restricted to individuals with recent-onset diabetes. Critically, for all donor groups combined, HLA-I hyperexpression occurred more frequently in VP1 + compared with VP1 − donors (45.8% vs 16%, p <0.001). Conclusions/interpretation We report the most extensive analysis to date of VP1 and HLA-I in pancreases from donors with preclinical and diagnosed type 1 diabetes. We find an association of VP1 with residual beta cells after diagnosis and demonstrate VP1 positivity during the autoantibody-positive preclinical stage. For the first time, we show that VP1 positivity and HLA-I hyperexpression in islet cells are both present during the preclinical stage. While the study of tissues does not allow us to demonstrate causality, our data support the hypothesis that enterovirus infections may occur throughout the natural history of type 1 diabetes and may be one of multiple mechanisms driving islet cell HLA-I hyperexpression. Graphical Abstract

3D imaging of human pancreas suggests islet size and endocrine composition influence their loss in type 1 diabetes

bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-18 · 3 citations

Summary A high-definition description of pancreatic islets would prove beneficial for understanding the pathophysiology of type 1 diabetes (T1D), yet significant knowledge voids exist in terms of their size, endocrine cell composition, and number in both health and disease. Here, 3-dimensional (3D) analyses of pancreata from control persons without diabetes (ND) revealed heretofore underappreciated frequencies (approximately 50%) of insulin-positive (INS+) glucagon-negative (GCG-) islets. Non-diabetic individuals positive for a single Glutamic acid decarboxylase autoantibody (GADA+) yet at increased risk for disease consistently demonstrated endocrine features, including islet volume and cell composition, closely resembling the age-matched ND controls. In contrast, pancreata from individuals with short-duration T1D demonstrated significantly reduced islet density and a dramatic loss of INS+GCG- islets with preservation of large INS+GCG+ islets. The size and cellular composition of pancreatic islets may, therefore, represent influential factors that impact β-cell loss during T1D disease progression. Graphical Abstract Highlights 3D imaging of non-diabetic (ND) pancreas suggests up to 50% of INS+ islets lack GCG INS+GCG- islets are typically small-sized in ND and preferentially lost in T1D In T1D pancreas, INS+ beta cells are preserved in large INS+GCG+ islets Islets from GADA+ individuals appear similar to ND for size and β-to-α cell ratios

Spatial transcriptomics from pancreas and local draining lymph node tissue reveals a lymphotoxin-β signature in human type 1 diabetes

bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-24

SUMMARY This study explores the inflammatory response observed in pancreata and pancreatic lymph node (pLN) samples obtained throughout the natural history of type 1 diabetes (T1D) including non-diabetic individuals and non-diabetic autoantibody positive individuals with high susceptibility using spatial transcriptomics (ST). Integration of ST with public single-cell RNA sequencing data enabled interrogation of transcriptional alterations in T1D pathogenesis across both tissues and cellular scales. In the T1D pancreas, we observed global upregulation of multiple inflammation-associated transcripts, including regenerating islet-derived ( REG ) family genes, complement factor 3 ( C3 ), SOD2 , and OLFM4 , and highlighted cellular candidates potentially contributing to these signatures. Within the T1D pLN, we observed spatially restricted upregulation of lymphotoxin-β ( LTB ) alongside follicular dendritic cell (FDC)-associated transcripts including FDCSP , CLU , and FCER2 . Collectively, these findings highlight distinct inflammation signatures in the pancreas and regional pLN which can help inform the development of future therapeutic interventions.