Genetic variation in mouse islet Ca2+ oscillations reveals novel regulators of islet function
Creators: name: Emfinger, Christopher
name: Clark, Lauren
name: Yandell, Brian
name: Schueler, Kathryn
name: Simonett, Shane
name: Stapleton, Donnie
name: Mitok, Kelly
name: Merrins, Matthew
name: Keller, Mark
name: Attie, Alan
Publisher: name: Zenodo
Year: 2023
Subjects: calcium
Insulin secretion
genetics
Collaborative Cross
pancreatic islets
proteomics

description: Insufficient insulin secretion to meet metabolic demand results in diabetes. The intracellular flux of Ca<sup>2+</sup> into β-cells triggers insulin release. Since genetics strongly influences variation in islet secretory responses, we surveyed islet Ca<sup>2+</sup> dynamics in eight genetically diverse mouse strains. We found high strain variation in response to four conditions: 1) 8 mM glucose; 2) 8 mM glucose plus amino acids; 3) 8 mM glucose, amino acids, plus 10nM GIP; and 4) 2 mM glucose. These stimuli interrogate β-cell function, α-cell to β-cell signaling, and incretin responses. We then correlated components of the Ca<sup>2+</sup> waveforms to islet protein abundances in the same strains used for the Ca<sup>2+</sup> measurements. To focus on proteins relevant to human islet function, we identified human orthologues of correlated mouse proteins that are proximal to glycemic-associated SNPs in human GWAS. Several orthologues have previously been shown to regulate insulin secretion (e.g. ABCC8, PCSK1, and GCK), supporting our mouse-to-human integration as a discovery platform. By integrating these data, we nominated novel regulators of islet Ca<sup>2+</sup> oscillations and insulin secretion with potential relevance for human islet function. We also provide a resource for identifying appropriate mouse strains in which to study these regulators.
description: Microsoft Excel/ OpenOffice RFunding provided by: National Institute of Diabetes and Digestive and Kidney Diseases<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000062<br>Award Number: R01DK101573Funding provided by: National Institute of Diabetes and Digestive and Kidney Diseases<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000062<br>Award Number: R01DK113103Funding provided by: U.S. Department of Veterans Affairs<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000738<br>Award Number: I01B005113Funding provided by: National Institute of Diabetes and Digestive and Kidney Diseases<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000062<br>Award Number: R01DK127637
description: <strong>Chemicals:</strong> All general chemicals, amino acids, BSA, DMSO, glucose, gastric inhibitory polypeptide (GIP,G2269), cOmplete Mini EDTA-free Protease Inhibitor Cocktail Tablets (11836170001), and heat-inactivated FBS (12306C) were purchased from Sigma Aldrich. RPMI 1640 base medium (11-875-093), antibiotic–antimycotic solutions (15240112), NP-40 Alternative (492016), Fura Red Ca<sup>2+</sup> imaging dye (F3020), DiR (D12731), and agarose (BP1356-500) were purchased from ThermoFisher. Glass-bottomed culture dishes were ordered from Mattek (P35G-0-14-C). Fura Red stocks were prepared at 5 mM concentrations in DMSO, aliquoted into light-shielded tubes, and stored at -20°C until day of use (5 μM final concentration). DiR was prepared in DMSO at 2 mg/ mL, aliquoted to light-shielded tubes, and stored at 4°C until use. All imaging solutions were prepared in a bicarbonate/HEPES-buffered imaging medium (formula in Table 1). Amino acids were prepared as 100× stock in the biocarbonate/HEPES-buffered imaging medium, aliquoted into 1.5 mL tubes, and frozen at –20°C until day of use. Aliquots of GIP stock were prepared at 100 μM in water and kept at -20°C until day of use. <strong>Animals</strong> Animal care and experimental protocols were approved by the University of Wisconsin-Madison Animal Care and Use Committee. Most strains (B6, AJ, 129, NOD, PWK, and WSB) were bred in-house, although two strains (CAST and NZO) were purchased from Jackson Laboratory (Bar Harbor, ME). All mice were fed a high-fat, high-sucrose Western-style diet (WD, consisting of 44.6% kcal fat, 34% carbohydrate, and 17.3% protein) from Envigo Teklad (TD.08811) beginning at 4 weeks and continuing until sacrifice (aged ~19–20 weeks for all strains except the NZO males). The NZO males were sacrificed at 12 weeks of age owing to complications from severe diabetes. For each strain, 3–7 males and females from at least 2 litters were analyzed. Animals were sacrificed by cervical dislocation prior to islet isolation. <strong>In vivo measurements</strong> Fasting blood glucose and insulin levels were measured in mice at 19 weeks of age, except for the NZO males which were measured at 12 weeks of age. Glucose was analyzed by the glucose oxidase method using a commercially available kit (TR15221, Thermo Fisher Scientific), and insulin was measured by radioimmunoassay (RIA; SRI-13K, Millipore). <strong>Islet imaging</strong> Islets were isolated as previously described (72) and incubated in recovery medium (RPMI 1640, 11.1 mM glucose, 1% antibiotic/antimycotic, 10% FBS) overnight at 37°C and 5% CO<sub>2</sub>. Islets were then incubated with Fura Red (5 μM in recovery medium) at 37°C for 45 minutes. Imaging dishes were created from glass-bottomed 10 cm<sup>2</sup> dishes that had been filled with agarose. A channel with a central well was cut into the agarose with expanded ports on either side of the well for inflow and outflow lines. Prior to loading, the chambers were perfused with the initial imaging solution (8 mM glucose in imaging medium). Islets were then loaded into these dishes. The imaging chamber was placed on a 37°C-heated microscope stage (Tokai Hit TIZ) of a Nikon A1R-Si+ confocal microscope. All solution reservoirs were kept in a 37°C water bath. Solutions were perfused through the chamber at 0.25 mL/min, with constant flow controlled by a Fluigent MCFS-EZ and M-switch valve assembly (Fluigent). The scope was integrated with a Nikon Eclipse-Ti Inverted scope and equipped with a Nikon CFI Apochromat Lambda D 10x/0.45 objective (Nikon Instruments), fluorescence spectral detector, and multiple laser lines (Nikon LU-NV laser unit; 405, 440, 488, 514, 561, 640nm). Bound dye was excited with the 405nm laser and the spectral detector's variable filter was set to 620–690nm. The free dye was excited with the 488nm laser and the variable filter collected from 640–690nm. Images were collected at 1 frame/sec at 6-second intervals. Each islet was considered a region of interest for further analysis. ROI intensity was collected by NIS Elements and exported for further analysis. All microscopy was performed at the University of Wisconsin-Madison Biochemistry Optical Core, which was established with support from the University of Wisconsin-Madison Department of Biochemistry Endowment. <strong>Islet perifusion </strong> Isolated islets were kept in RPMI-based medium (see above) overnight prior to perifusion, which was performed as previously described, with minor modifications. Islets were equilibrated in 2 mM glucose for 55 minutes, after which 100 μL fractions were collected every minute with the perifusion solutions set at a flow rate of 100 μL/min. All solutions and islet chambers were kept at 37°C. After the final fraction was collected, islet chambers were disconnected, inverted, and flushed with 2 mL of NP-40 Alternative lysis buffer containing protease inhibitors for islet insulin extraction. <strong>Secreted insulin assay</strong> Insulin in each perifusion fraction and islet insulin content were determined using a custom assay, as previously described. <strong>Imaging data analysis</strong> Trace segments for each solution condition were analyzed using Matlab and R. Traces were detrended using custom R scripts and Graphpad PRISM. Custom Matlab scripts (https://github.com/hrfoster/Merrins-Lab-Matlab-Scripts, also stored on Dryad https://doi.org/10.5281/zenodo.6540721) determined oscillation peak amplitude, pulse duration, active duration (the time when calcium is above 50% peak amplitude), silent duration (the difference between period and active duration). , plateau fraction (the fraction of overall time per pulse spent in the active duration), pulse period and other parameters. Spectral density deconvolution for the trace segments to determine principal frequencies was done using R. Animal averages for the different parameters defined by Matlab and R were computed and graphed using custom R scripts. Figures were created using CorelDraw and Biorender.com. All R scripts and the citations for the relevant packages used to generate them are available via Dryad. <strong>Correlation and Z-score calculations. </strong>Correlation analysis was performed using the imaging data measurements and our published islet protein abundance data, <em>ex vivo </em>static insulin secretion measurements, and <em>in vivo</em> measurements made in a separate cohort of mice on the WD from the same strains and sexes used in these studies. For each imaging parameter or previously published measurement, the Z-score was calculated using the formula <em>z = (x-μ) / σ</em> where <em>z </em>is the Z-score, <em>x </em>is the animal average for that trait given the strain and sex, <em>μ </em>is the average of all animals' values for that trait, and <em>σ </em>is the standard deviation for all animals' values for that trait. Z-scores were computed in R and excel for the imaging parameters and the previously published islet proteomic, <em>ex vivo </em>secretion, and <em>in vivo </em>measurements. Correlation coefficients between the Z-score values of the imaging parameters and Z-scores of the previously published protein abundance, islet secretion, and <em>in vivo </em>traits were computed in Excel using the CORREL function. The equation used for this function is: Where <em>X</em> and <em>Y</em> are the Z-scores for the correlated traits/parameters, <em>ẋ</em> is the population average for trait X and ẏ is the population average for trait Y. Traits were considered highly correlated if the absolute value for their Z-score correlation coefficients was ≥ 0.5. <strong>Gene enrichment and human GWAS analysis. </strong>Proteins highly correlated or anticorrelated to imaging parameters were further analyzed using pathway enrichment and presence of human GWAS SNPs. Briefly, for a given parameter, pathway analysis for the highly correlated or anti-correlated proteins to that parameter was done using Enrichr. For GWAS analysis, human orthologues for genes encoding the previously measured islet proteins were identified using BioMart. For highly correlated proteins, the protein was deemed of human interest if its orthologue had SNPs for glycemia-related traits (see table 2) either along the gene body, within +/- 100 kbp of the gene start or end, or if any region in the gene body was connected to regions with SNPs by chromatin looping. SNPs were queried using Lunaris tool of the Common Metabolic Diseases Knowledge Portal (cmdkp.org). Chromatin loop anchor points for the relevant gene orthologues were identified using previously published human islet promoter-capture HiC data and the alignment between these anchor loops and orthologues of interest was done using R scripts. For those proteins having ortholgoues with SNPs via this analysis, we conducted further literature searches using Pubmed, Google Scholar, ChEMBL, canSAR, Uniprot, Tabula Muris, and the Human Protein Atlas, and other resources to determine tissue expression and identify any prior roles in islet biology. Figures for the relevant protein examples were created using Prism, CorelDraw, and the WashU Epigenome Browser. <strong>Web resource</strong> A web resource was created to explore the islet calcium and proteomic data and their relationships (https://rstudio.it.wisc.edu/FounderCalciumStudy). This resource sits on an RStudio/Connect server (see https://posit.co/). It enables the user to select traits from the calcium and protein datasets to plot by strain, sex, and calcium parameters. Distinct mice were assayed for <strong>calcium</strong> and <strong>protein</strong>. Individual strains can be selected on the main menu using the checkboxes, or all strains (default) can be viewed. The different datasets available in the main menu are: 1) <strong>calcium</strong>: calcium parameters &amp; spectral density data, with stimulatory secretion conditions 2) <strong>protein</strong>: islet proteomic measurements 3) <strong>basal</strong>: average calcium in 2mM glucose The <strong>calcium</strong> data have three stimulatory conditions (8G, 8G/QLA, and 8G/QLA/GIP) that are displayed together for each calcium parameter. The proteomic data (<strong>protein</strong>) are displayed for each identified peptide. In rare cases of multiple peptides per gene, both gene symbol and peptide identifier (PP number) are included (e.g. Pkm_PP_1521 for the M1 isoform of the protein PKM). Desired proteins can be selected simultaneously with desired calcium parameters for correlation analysis and paired display by both datasets. The <strong>basal</strong> elements retained from the calcium data include the Average Calcium measurement for 2mM glucose. Proteomic data were log10-transformed. All traits were transformed into normal scores, keeping the sample mean and variance the same. Scatter plots display data across sex and calcium conditions. When plotting calcium against protein or basal traits, means by strain and sex are used, as the two experiments used different mice. Correlation of selected traits with all other traits in the resource use Pearson correlation on pairwise-complete data. The user can order traits by their significance or by their correlation to other selected traits. Statistical modeling terms include strain, sex, and the strain:sex interation, plus additional terms for comparing calcium condition with respect to strain and sex. Users can view volcano plots displaying deviation of term effects, measured as the standard deviation (SD = square root of mean square error) divided by the raw SD for that trait, against their significance (p-value after adjusting for all other model terms, presented on -log10 scale). In addition to the terms, a composite "signal" captures the combined effect of terms strain:condition + strain:condition:sex using a general F test computation. All data handling and web app construction for the resource was performed using R scripts in publicly available GitHub repositories, with specifics for the calcium study at https://github.com/byandell/FounderCalciumStudy and the general purpose analysis and web deployment package at https://github.com/byandell/foundr. <strong>Statistics. </strong>For the islet perifusion insulin measurements, statistics were determined in GraphPad Prism. Fractional secretion area-under-the-curve (AUC) was determined using Prism and differences in AUCs analyzed using post-tests following 2-way ANOVA for the indicated trace segments. Islet total insulins between strains were compared using a two-tailed Student's t-test with Welch's correction. <strong>Study approval</strong>. All protocols were approved by the University of Wisconsin-Madison IACUC (Protocol A005821-R01).