Biology subjects

Campbell-Thompson, M.

Publications and source records attributed to Campbell-Thompson, M..

10 recordsLinked to original sources

bioRxiv2026

Mitochondrial and protein homeostasis pathways are transcriptionally impaired in islets during type 1 diabetes pathogenesis

The decline in first-phase insulin response (FPIR) during the presymptomatic period of type 1 diabetes (T1D) is well established. In-situ functional studies with pancreas tissue slices showed that {beta}-cell loss of glucose-responsiveness was independent of T-cell infiltration into islets in recent-onset T1D cases. However, the mechanisms driving {beta}-cell dysfunction before the onset of T1D remain unclear. In pancreas tissue from donors across the natural history of T1D, we utilized an in-situ, whole-islet phenotypical and transcriptomic approach to unravel novel targets in the glucose-stimulus coupled secretion pathway that are similarly impaired in T-cell infiltrated and non-infiltrated islets. Specifically, we observed that islets from autoantibody positive (single(s) or multiple(m) AAb+) donors exhibited activation of post-transcriptional gene regulation along with reduced protein translation, processing in the endoplasmic reticulum (ER), and ER stress. Disrupted mitochondrial metabolism and bioenergetics were prominent in islets from multiple AAb+ and T1D donors with disease durations [≤]7 years. In addition, T1D islets presented reduced mitochondrial protein import, quality control, and dynamics, together with downregulated genes in insulin secretory pathways. During infiltration, these pathways remain dysregulated while immune/inflammatory transcripts were increased. These studies identified novel mechanisms of {beta}-cell dysregulation before symptomatic onset and independent of T-cell infiltration in T1D pathogenesis.

physiology↗

bioRxiv2025

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

Progressive {beta}-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 {beta}-cell dysfunction. Several pathways, including extracellular matrix remodeling and mRNA processing, were identified as closely associated with progressive islet immune activation and loss of {beta}-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.

systems biology↗

bioRxiv2025

Exploring endothelial cell environments across organs in spatially resolved omics data

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.

bioinformatics↗

bioRxiv2025

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

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-{beta} (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.

immunology↗

bioRxiv2025

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

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 {beta}-cell loss during T1D disease progression. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/654045v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1d2fdeaorg.highwire.dtl.DTLVardef@11c43edorg.highwire.dtl.DTLVardef@af8a82org.highwire.dtl.DTLVardef@ae8c58_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LI3D imaging of non-diabetic (ND) pancreas suggests up to 50% of INS+ islets lack GCG C_LIO_LIINS+GCG- islets are typically small-sized in ND and preferentially lost in T1D C_LIO_LIIn T1D pancreas, INS+ beta cells are preserved in large INS+GCG+ islets C_LIO_LIIslets from GADA+ individuals appear similar to ND for size and {beta}-to- cell ratios C_LI

pathology↗

bioRxiv2024

Beta cell dysfunction occurs independently of insulitis in type 1 diabetes pathogenesis

The loss of insulin secretory function associated with type 1 diabetes (T1D) is attributed to the immune-mediated destruction of beta cells. Yet, at onset of T1D, patients often have a significant beta cell mass remaining while T cell infiltration of pancreatic islets is sporadic. Thus, we investigated the hypothesis that the remaining beta cells in T1D are largely dysfunctional using live human pancreas tissue slices prepared from organ donors with recently diagnosed T1D. Beta cells in slices from donors with T1D had significantly diminished Ca2+ mobilization and insulin secretion responses to glucose. Beta cell function was equally impaired in T cell-infiltrated and non-infiltrated islets. Fixed tissue staining and gene expression profiling of laser-capture microdissected islets revealed significant decreases of proteins and genes in the glucose stimulus secretion coupling pathway. From these data, we posit that functional defects occur in the remaining mass of beta cells during human T1D pathogenesis.

physiology↗

bioRxiv2024

Increased Inflammation as well as Decreased Endoplasmic Reticulum Stress and Translation Differentiate Pancreatic Islets of Pre-symptomatic Stage 1 Type 1 Diabetes and Non-diabetic Cases

Aims/hypothesisProgression to type 1 diabetes (T1D) is associated with genetic factors, the presence of autoantibodies, and a decline in {beta} cell insulin secretion in response to glucose. Very little is known regarding the molecular changes that occur in human insulin-secreting {beta}-cells prior to the onset of T1D. Herein, we applied an unbiased proteomics approach to identify changes in proteins and potential mechanisms of islet dysfunction in islet autoantibody-positive organ donors with pre-symptomatic stage 1 T1D (HbA1c [≤] 6). We aimed to identify pathways in islets that are indicative of {beta}-cell dysfunction. MethodsMultiple islet sections were collected through laser microdissection of frozen pancreatic tissues of organ donors positive for islet autoantibodies (AAb+, n=5), compared to age/sex-matched nondiabetic controls (ND, n=5) obtained from the Network for Pancreatic Organ donors with Diabetes (nPOD). Islet sections were subjected to mass spectrometry-based proteomics and analyzed with label-free quantification followed by pathway and functional annotations. ResultsAnalyses resulted in [~]4,500 proteins identified with low false discovery rate (FDR) <1%, with 2,165 proteins reliably quantified in every islet sample. We observed large inter-donor variations that presented a challenge for statistical analysis of proteome changes between donor groups. We therefore focused on the three multiple AAb+ cases (mAAb+) with high genetic risk and their three matched controls for a final statistical analysis. Approximately 10% of the proteins (n=202) were significantly different between mAAb+ cases versus ND. The significant alterations clustered around major functions for upregulation in the immune response and glycolysis, and downregulation in endoplasmic reticulum (ER) stress response as well as protein translation and synthesis. The observed proteome changes were further supported by several independent published datasets, including proteomics dataset from in vitro proinflammatory cytokine-treated human islets and single cell RNA-seq data sets from AAb+ cases. Conclusion/interpretationIn-situ human islet proteome alterations at the stage 1 of AAb+ T1D centered around several major functional categories, including an expected increase in immune response genes (elevated antigen presentation / HLA), with decreases in protein synthesis and ER stress response, as well as compensatory metabolic response. The dataset serves as a proteomics resource for future studies on {beta} cell changes during T1D progression and pathogenesis.

pathology↗

bioRxiv2024

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of [~]3500 proteins at a spatial resolution of 50 {micro}m and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

systems biology↗

bioRxiv2020

ACE2 and SARS-CoV-2 Expression in the Normal and COVID-19 Pancreas

Diabetes is associated with increased mortality from Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Given literature suggesting a potential association between SARS-CoV-2 infection and diabetes induction, we examined pancreatic expression of the key molecule for SARS-CoV-2 infection of cells, angiotensin-converting enzyme-2 (ACE2). Specifically, we analyzed five public scRNAseq pancreas datasets and performed fluorescence in situ hybridization, Western blotting, and immunolocalization for ACE2 with extensive reagent validation on normal human pancreatic tissues across the lifespan, as well as those from coronavirus disease 2019 (COVID-19) patients. These in silico and ex vivo analyses demonstrated pancreatic expression of ACE2 is prominent in pancreatic ductal epithelium and the microvasculature, with rare endocrine cell expression of this molecule. Pancreata from COVID-19 patients demonstrated multiple thrombotic lesions with SARS-CoV-2 nucleocapsid protein expression primarily limited to ducts. SARS-CoV-2 infection of pancreatic endocrine cells, via ACE2, appears an unlikely central pathogenic feature of COVID-19 as it relates to diabetes.

pathology↗

bioRxiv2018

Detection of enterovirus protein and RNA in multiple tissues from nPOD organ donors with type 1 diabetes

Epidemiological studies have shown an association between enterovirus (EV) infections and type 1 diabetes (T1D), and EV protein has been detected in the pancreatic islets of T1D patients. Here we correlated the detection of EVs in lymphoid tissues (spleen and pancreatic lymph nodes) and small intestinal mucosa to the virus detection in the pancreas of T1D, autoantibody-positive (aab+) and non-diabetic control organ donors of the Network for Pancreatic Organ Donors with Diabetes (nPOD) study. Formalin-fixed paraffin-embedded tissue samples were screened for insulin and EV protein using immunohistochemistry, and frozen tissue for EV genome using RT-PCR. The presence of EV protein in the pancreatic islets correlated with the presence of insulin-positive cells. Altogether 62 % of T1D and aab+ donors were positive for EV protein in pancreatic islets (only insulin-positive donors included), 40 % in duodenum and 32 % in spleen, compared to 33 %, 14 %, and 27 % of non-diabetic controls. Pancreatic lymph nodes were positive for EV protein in 60 % of T1D and aab+ cases. T1D and aab+ donors were more frequently VP1-positive in multiple organs than control donors (39 % vs. 11 %; including only insulin-positive donors). EV RNA was found in selected donors and from multiple tissue types except for duodenum, and individual T1D and aab+ donors were EV RNA-positive in multiple organs. The role of extra-pancreatic organs and their interplay with EV in T1D pathogenesis remains to be solved, but we hypothesize that these organs may serve as a reservoir for the virus which may reside in these tissues in a slow-replicating persistent form.

epidemiology↗