The identification of potential factors associated with the development of type 2 diabetes: a quantitative proteomics approach

Abstract

Type 2 diabetes (T2D) arises when pancreatic beta-cells fail to compensate for systemic insulin resistance with appropriate insulin secretion. However, the link between insulin resistance and beta-cell failure in T2D is not fully understood. To explore this association, we studied transgenic MKR mice that initially develop insulin resistance in skeletal muscle but by 8 weeks of age have T2D. In the present study, global islet protein and gene expression changes were characterized in diabetic MKR versus non-diabetic control mice at 10 weeks of age. Using a quantitative proteomics approach (isobaric tags for relative and absolute quantification (iTRAQ)), 159 proteins were differentially expressed in MKR compared with control islets. Marked up-regulation of protein biosynthesis and endoplasmic reticulum stress pathways and parallel down-regulation in insulin processing/secretion, energy utilization, and metabolism were observed. A fraction of the differentially expressed proteins identified (including GLUT2, DNAJC3, VAMP2, RAB3A, and PC1/3) were linked previously to insulin-secretory defects and T2D. However, many proteins for the first time were associated with islet dysfunction, including the unfolded protein response proteins (ERP72, ERP44, ERP29, PPIB, FKBP2, FKBP11, and DNAJB11), endoplasmic reticulum-associated degradation proteins (VCP and UFM1), and multiple proteins associated with mitochondrial energy metabolism (NDUFA9, UQCRH, COX2, COX4I1, COX5A, ATP6V1B2, ATP6V1H, ANT1, ANT2, ETFA, and ETFB). The mRNA expression level corresponding to these proteins was examined by microarray, and then a small subset was validated using quantitative real time PCR and Western blot analyses. Importantly approximately 54% of differentially expressed proteins in MKR islets (including proteins involved in proinsulin processing, protein biosynthesis, and mitochondrial oxidation) showed changes in the proteome but not transcriptome, suggesting post-transcriptional regulation. These results underscore the importance of integrated mRNA and protein expression measurements and validate the use of the iTRAQ method combined with microarray to assess global protein and gene changes involved in the development of T2D.

Fig. 1.

Morphological characterization of MKR and WT pancreatic islets at 3 and 10 weeks of age. A, images of freshly isolated islets were taken with a confocal microscope. B, immunostaining for insulin (magnification, ×100) in pancreatic sections. C and D, glucose-stimulated insulin secretion from isolated islets was determined in response to 2.8 and 20 mm glucose (Error bars indicate the standard error of the mean calculated on the insulin secretion from three independent experiments with >5 mice per genotype). ***, p < 0.001.

Fig. 2.

Quantitative iTRAQ proteomics approach. A, flow chart of iTRAQ proteomics approach. B and C, PDI was up-regulated 2.43-fold in MKR islets. Quantitative information is encoded in the low mass-to-charge ratio portion of the MS/MS spectrum. The MKR islet sample was labeled with iTRAQ-117, and the WT islet sample was labeled with iTRAQ-114. Relative peak areas of the two marker ions were used to quantify the PDI levels (B). For each MS/MS spectrum, y- and b-type fragment ions (containing the C and N termini of the peptide, respectively) enable the identification of the peptide sequence (C).

Fig. 3.

Functional categorization and relative protein ratios of differentially expressed proteins in MKR islets. Differentially expressed proteins in diabetic MKR islets were sorted into subcellular location (A) and functional categories (B). Relative changes in the levels of proteins in MKR islets related to protein synthesis (C), ER stress (D), secretion (E), and mitochondrial defects (F).

Fig. 4.

Representative Western blotting images and quantification for differentially expressed proteins in MKR versus WT control islets. There was good correlation between iTRAQ and Western blot data, and this information is presented in Table III (n = 3–5 independent experiments with >5 mice per genotype). **, p < 0.01; ***, p < 0.001.

Fig. 5.

Correlation of mRNA ratios and protein levels of differentially expressed proteins in MKR islets. A and B, scatter plots of average protein ratios determined by the iTRAQ method and mRNA ratios determined by the microarray study. C, a pictorial comparison of changed protein ratios detected by iTRAQ and microarray analysis together with functional cluster analysis. Hierarchical clustering was performed using the GoMiner program (44) based on the biological process category in the Gene Ontology Consortium. Colors represent average gene/protein expression changes (MKR/WT) relative to the median (46) with red and green representing an increase or decrease in fold expression, respectively. “iTRAQ” and “MA” represent protein -fold and gene -fold (MKR/WT), respectively.

Fig. 6.

A proposed model for the molecular and protein expression defects that lead to the dysfunctional islet metabolic phenotype in diabetic MKR islets. The proteins highlighted in the gray boxes were significantly changed in MKR islets.