6 research outputs found
Antibody panel used for multiplexed antibody-based imaging of Human Pancreas Analysis Program (HPAP) samples by CODEX
<p>This data file details antibodies applied to human pancreas tissue samples from the Human Pancreas Analysis Program (HPAP; RRID:SCR_016202) of the <a href="https://hirnetwork.org/">Human Islet Research Network</a> (HIRN; RRID:SCR_014393). Images will be uploaded for interactive analysis on <a href="https://pancreatlas.org/datasets">Pancreatlas</a> (RRID:SCR_018567) and made available for download via <a href="https://hpap.pmacs.upenn.edu/">PANC-DB</a>. Workflow is documented on protocols.io: <a href="https://dx.doi.org/10.17504/protocols.io.36wgq7dryvk5/v1">dx.doi.org/10.17504/protocols.io.36wgq7dryvk5/v1</a>.</p><p>Table format adapted from Radtke AJ, Quardokus EM, Saunders DC (2022), <a href="https://doi.org/10.5281/zenodo.7386417">SOP: Construction of Organ Mapping Antibody Panels for Multiplexed Antibody-Based Imaging of Human Tissues</a>. See also: Saunders D; Reihsmann R. <a href="https://doi.org/10.48539/HBM754.BHVR.258">OMAP-13: Organ Mapping Antibody Panel (OMAP) for Multiplexed Antibody-Based Imaging of Human Pancreas with CODEX, v1.0</a>.</p>
Multiplexed imaging analysis of human pancreatic islets from donors with and without type 2 diabetes
This dataset is part of the manuscript Genetic risk converges on regulatory networks mediating early type 2 diabetes (Walker, Saunders, & Rai et al., 2023), a body of work that includes tissue imaging, sorted islet cell transcriptomics, and islet functional analysis of donors with early-stage type 2 diabetes (T2D) and control donors.
Raw imaging data was acquired from 4% PFA-fixed, cryopreserved human pancreas tissue using the CODEX system (now PhenoCycler Open; Akoya Biosciences) integrated with a BZ-X810 epifluorescence microscope (Keyence) with a CFI plan Apo I 20x/0.75 objective (Nikon). Image alignment, stitching, background subtraction, and deconvolution were performed using the CODEX Processor v1.7.0.6 (Akoya Biosciences). Tissue and islet areas were annotated by hand to exclude out-of-focus regions and poor tissue quality. Islets (estimated diameter ≥50 μm; mean 42 islets/donor) were annotated based on DAPI and CHGA channels. Cell segmentation and cell type annotations were performed using the HALO HighPlex FL v3.2.1 module (Indica Labs). For cell neighborhood (CN) analysis, two methods were applied in parallel to CODEX data from annotated islets: a community detection method, termed Dynamic CF-IDF, and a k-means approach.
Processed imaging data is available via Pancreatlas (RRID:SCR_018567); packages used for cell neighborhood analyses are published in Github
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Human Pseudoislet System for Synchronous Assessment of Fluorescent Biosensor Dynamics and Hormone Secretory Profiles
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Integrated human pseudoislet system and microfluidic platform demonstrate differences in GPCR signaling in islet cells
Pancreatic islets secrete insulin from β cells and glucagon from α cells, and dysregulated secretion of these hormones is a central component of diabetes. Thus, an improved understanding of the pathways governing coordinated β and α cell hormone secretion will provide insight into islet dysfunction in diabetes. However, the 3D multicellular islet architecture, essential for coordinated islet function, presents experimental challenges for mechanistic studies of intracellular signaling pathways in primary islet cells. Here, we developed an integrated approach to study the function of primary human islet cells using genetically modified pseudoislets that resemble native islets across multiple parameters. Further, we developed a microperifusion system that allowed synchronous acquisition of GCaMP6f biosensor signal and hormone secretory profiles. We demonstrate the utility of this experimental approach by studying the effects of G
i
and G
q
GPCR pathways on insulin and glucagon secretion by expressing the designer receptors exclusively activated by designer drugs (DREADDs) hM4Di or hM3Dq. Activation of G
i
signaling reduced insulin and glucagon secretion, while activation of G
q
signaling stimulated glucagon secretion but had both stimulatory and inhibitory effects on insulin secretion, which occur through changes in intracellular Ca
2+
. The experimental approach of combining pseudoislets with a microfluidic system allowed the coregistration of intracellular signaling dynamics and hormone secretion and demonstrated differences in GPCR signaling pathways between human β and α cells.
Integration of a pseudoislet approach with a microfluidic perifusion system and live cell imaging provides an experimental platform to investigate human islet biology
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Human pseudoislet system enables detection of differences in G-protein-coupled-receptor signaling pathways between α and β cells
SUMMARY G-protein-coupled-receptors (GPCRs) modulate insulin secretion from β cells and glucagon secretion from α cells. Here, we developed an integrated approach to study the function of primary human islet cells using genetically modified pseudoislets that resemble native islets across multiple parameters. We studied the G i and G q GPCR pathways by expressing the designer receptors exclusively activated by designer drugs (DREADDs) hM4Di or hM3Dq. Activation of G i signaling reduced insulin and glucagon secretion, while activation of G q signaling stimulated glucagon secretion but had both stimulatory and inhibitory effects on insulin secretion. Further, we developed a microperifusion system that allowed synchronous acquisition of GCaMP6f biosensor signal and hormone secretory profiles and showed that the dual effects for G q signaling occur through changes in intracellular Ca 2+ . By combining pseudoislets with a microfluidic system, we co-registered intracellular signaling dynamics and hormone secretion and demonstrated differences in GPCR signaling pathways between human β and α cells
Genetic risk converges on regulatory networks mediating early type 2 diabetes.
Type 2 diabetes mellitus (T2D), a major cause of worldwide morbidity and mortality, is characterized by dysfunction of insulin-producing pancreatic islet β cells1,2. T2D genome-wide association studies (GWAS) have identified hundreds of signals in non-coding and β cell regulatory genomic regions, but deciphering their biological mechanisms remains challenging3–5. Here, to identify early disease-driving events, we performed traditional and multiplexed pancreatic tissue imaging, sorted-islet cell transcriptomics and islet functional analysis of early-stage T2D and control donors. By integrating diverse modalities, we show that early-stage T2D is characterized by
β cell-intrinsic defects that can be proportioned into gene regulatory modules with enrichment in signals of genetic risk. After identifying the β cell hub gene and transcription factor RFX6 within one such module, we demonstrated multiple layers of genetic risk that converge on an RFX6-mediated network to reduce insulin secretion by β cells. RFX6 perturbation in primary human islet cells alters β cell chromatin architecture at regions enriched for T2D GWAS signals, and population-scale genetic analyses causally link genetically predicted reduced RFX6 expression with increased T2D risk. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs and individuals, and thus we anticipate that this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits using GWAS data