The Munich MIDY Pig Biobank - A unique resource for studying organ crosstalk in diabetes

Abstract

Objective: The prevalence of diabetes mellitus and associated complications is steadily increasing. As a resource for studying systemic consequences of chronic insulin insufficiency and hyperglycemia, we established a comprehensive biobank of long-term diabetic INS^C94Y transgenic pigs, a model of mutant INS gene-induced diabetes of youth (MIDY), and of wild-type (WT) littermates.

Methods: Female MIDY pigs (n = 4) were maintained with suboptimal insulin treatment for 2 years, together with female WT littermates (n = 5). Plasma insulin, C-peptide and glucagon levels were regularly determined using specific immunoassays. In addition, clinical chemical, targeted metabolomics, and lipidomics analyses were performed. At age 2 years, all pigs were euthanized, necropsied, and a broad spectrum of tissues was taken by systematic uniform random sampling procedures. Total beta cell volume was determined by stereological methods. A pilot proteome analysis of pancreas, liver, and kidney cortex was performed by label free proteomics.

Results: MIDY pigs had elevated fasting plasma glucose and fructosamine concentrations, C-peptide levels that decreased with age and were undetectable at 2 years, and an 82% reduced total beta cell volume compared to WT. Plasma glucagon and beta hydroxybutyrate levels of MIDY pigs were chronically elevated, reflecting hallmarks of poorly controlled diabetes in humans. In total, ∼1900 samples of different body fluids (blood, serum, plasma, urine, cerebrospinal fluid, and synovial fluid) as well as ∼17,000 samples from ∼50 different tissues and organs were preserved to facilitate a plethora of morphological and molecular analyses. Principal component analyses of plasma targeted metabolomics and lipidomics data and of proteome profiles from pancreas, liver, and kidney cortex clearly separated MIDY and WT samples.

Conclusions: The broad spectrum of well-defined biosamples in the Munich MIDY Pig Biobank that will be available to the scientific community provides a unique resource for systematic studies of organ crosstalk in diabetes in a multi-organ, multi-omics dimension.

Keywords: Biobank; CE, cholesterol ester; CPT1, carnitine O-palmitoyltransferase 1; ER, endoplasmic reticulum; FFA, free fatty acids; Hyperglycemia; Insulin insufficiency; MIDY; MIDY, mutant INS gene-induced diabetes of youth; Metabolomics; PC, phosphatidylcholine; PCA, principal component analysis; Pig model; Proteomics; Random systematic sampling; SM, sphingomyelin; Stereology; TAG, triacylglycerol; Transcriptomics; WT, wild-type.

Figure 1

Metabolic characterization and beta cell volume of MIDY and WT pigs. (A–F) Age-related differences in fasting plasma concentrations of glucose (A), insulin (B), C-peptide (C), fructosamine (D), glucagon (E), and beta hydroxybutyrate (F). Fasting times were 18–24 h. Means and standard deviations are shown. Data were statistically evaluated by analysis of variance (Proc GLM, SAS 8.2), taking the effects of Group (MIDY, WT), Animal within Group, Age, and the interaction Group*Age into account. Significant differences between MIDY and WT pigs of the same age are indicated by asterisks (*p < 0.05; **p < 0.01; ***p < 0.001). Borderline significance (p < 0.08) is indicated by ° (G–H) Quantification of beta cell volume in MIDY and WT pancreas. Pancreas samples were chosen by systematic random sampling and routinely processed for paraffin histology. Volume density and the total volume of beta cells within the pancreas were determined as described in Material and methods. Detection of insulin by immunohistochemistry revealed drastically reduced areas of insulin-positive beta cell profiles in pancreas sections of MIDY pigs, as compared to WT pigs (G). Paraffin sections, chromogen: 3,3′-diaminobenzidine. Bars = 100 μm (and = 50 μm in inset). In MIDY pigs, the volume density (H), as well as the absolute volume of beta cells in the pancreas (I) is significantly smaller as in WT animals. Means and standard deviations are shown. Data were statistically evaluated by Student's t-tests. Significant differences between MIDY and WT pigs are indicated by asterisks (**p < 0.01). (J–K) Representative islets from WT (J) and MIDY pigs (K). Insulin positive beta cells are stained with AlexaFluor488 (green), glucagon positive alpha cells are stained with Cy3 (red). Nuclei are stained with DAPI (blue). Bars = 50 μm.

Figure 2

Targeted metabolomics and lipidomics studies of plasma samples from MIDY and WT pigs. (A–B) Targeted metabolomics. (A) Principal component analysis (PCA) is applied to all metabolite concentrations present in Supplementary Table 2 after they were scaled and centered. The bar graph (B) shows selected significant (p < 0.05) metabolites and metabolic indicators as a percentage of the WT mean (gray striped line). The SEM for each metabolite and genotype is indicated with error bars. Abbreviations: H1, hexoses; PC, phosphatidylcholine; SFA, saturated fatty acids; MUFA, mono-unsaturated fatty acids; PUFA, poly-unsaturated fatty acids; SM, sphingomyelins; C18, octadecanoylcarnitine; C10, decanoylcarnitine; C4:1, butenylcarnitine; CPT1 ratio, ratio of long chain acylcarnitines to free carnitine; DMA, ratio of dimethylated arginine to total unmodified arginine. (C–D) Shotgun lipidomics of plasma from MIDY and WT pigs detected 230 lipid species from 13 different classes. C) PCA significantly separated MIDY and WT samples (p-value = 0.016). D) Mol% abundance of lipid classes in MIDY and WT plasma. Abbreviations: CE, cholesterol esters; Cer, ceramides; Chol, cholesterol; DAG, diacylglycerols; LPC, lysophosphatidylcholines; LPE, lysophosphatidylethanolamine; PC, phosphatidylcholines; PCO, PC plasmalogens; PE, phosphatidylethanolamines; PEO, PE plasmalogens; PI, phosphatidylinositols; SM, sphingomyelins; TAG, triacylglycerols.

Figure 3

Proteome profiles from a pilot study of pancreas (1574 identified proteins), liver (1263 identified proteins) and kidney cortex (2162 identified proteins) from MIDY and WT pigs. (A) Unsupervised hierarchical clustering of normalized expression values (z-score) of 827 proteins commonly identified in pancreas, liver and kidney cortex. The heatmap indicates clustering of the analyzed proteomes according to tissue type and genotype. Missing values were imputed. Heat map legend indicates normalized expression values. (B–D) Principal component analysis (PCA) of proteomics data from pancreas (B), liver (C) and kidney cortex (D) clearly separated MIDY and WT samples.