Gene expression profiling of cultured human islet preparations

Discovery of novel glucose-regulated proteins in isolated human pancreatic islets using LC-MS/MS-based proteomics

The prevalence of diabetes mellitus is increasing dramatically throughout the world, and the disease has become a major public health issue. The most common form of the disease, type 2 diabetes, is characterized by insulin resistance and insufficient insulin production from the pancreatic beta-cell. Since glucose is the most potent regulator of beta-cell function under physiological conditions, identification of the insulin secretory defect underlying type 2 diabetes requires a better understanding of glucose regulation of human beta-cell function. To this aim, a bottom-up LC-MS/MS-based proteomics approach was used to profile pooled islets from multiple donors under basal (5 mM) or high (15 mM) glucose conditions. Our analysis discovered 256 differentially abundant proteins (∼p < 0.05) after 24 h of high glucose exposure from more than 4500 identified in total. Several novel glucose-regulated proteins were elevated under high glucose conditions, including regulators of mRNA splicing (pleiotropic regulator 1), processing (retinoblastoma binding protein 6), and function (nuclear RNA export factor 1), in addition to neuron navigator 1 and plasminogen activator inhibitor 1. Proteins whose abundances markedly decreased during incubation at 15 mM glucose included Bax inhibitor 1 and synaptotagmin-17. Up-regulation of dicer 1 and SLC27A2 and down-regulation of phospholipase Cβ4 were confirmed by Western blots. Many proteins found to be differentially abundant after high glucose stimulation are annotated as uncharacterized or hypothetical. These findings expand our knowledge of glucose regulation of the human islet proteome and suggest many hitherto unknown responses to glucose that require additional studies to explore novel functional roles.

Gene expression of purified beta-cell tissue obtained from human pancreas with laser capture microdissection

CONTEXT

Human beta-cell gene profiling is a powerful tool for understanding beta-cell biology in normal and pathological conditions. Assessment is complicated when isolated islets are studied because of contamination by non-beta-cells and the trauma of the isolation procedure.

OBJECTIVE

The objective was to use laser capture microdissection (LCM) of human beta-cells from pancreases of cadaver donors and compare their gene expression with that of handpicked isolated islets.

DESIGN

Endogenous autofluorescence of beta-cells facilitated procurement of purified beta-cell tissue from frozen pancreatic sections with LCM. Gene expression profiles of three microdissected beta-cell samples and three isolated islet preparations were obtained. The array data were normalized using DNA-Chip Analyzer software (Harvard School of Public Health, Boston, MA), and the lower confidence bound evaluated differentially expressed genes. Real-time PCR was performed on selected acinar genes and on the duct cell markers, carbonic anhydrase II and keratin 19.

RESULTS

Endogenous autofluorescence facilitates the microdissection of beta-cell rich tissue in human pancreas. When compared with array profiles of purified beta-cell tissue, with lower confidence bound set at 1.2, there were 4560 genes up-regulated and 1226 genes down-regulated in the isolated islets. Among the genes up-regulated in isolated islets were pancreatic acinar and duct genes, chemokine genes, and genes associated with hypoxia, apoptosis, and stress. Quantitative RT-PCR confirmed the differential expression of acinar gene transcripts and the duct marker carbonic anhydrase II in isolated islets.

CONCLUSION

LCM makes it possible to obtain beta-cell enriched tissue from human pancreas sections without the trauma and ischemia of islet isolation.

Integrating global proteomic and genomic expression profiles generated from islet alpha cells: opportunities and challenges to deriving reliable biological inferences

Systematic profiling of expressed gene products represents a promising research strategy for elucidating the molecular phenotypes of islet cells. To this end, we have combined complementary genomic and proteomic methods to better assess the molecular composition of murine pancreatic islet glucagon-producing alphaTC-1 cells as a model system, with the expectation of bypassing limitations inherent to either technology alone. Gene expression was measured with an Affymetrix MG_U74Av2 oligonucleotide array, while protein expression was examined by performing high-resolution gel-free shotgun MS/MS on a nuclear-enriched cell extract. Both analyses were carried out in triplicate to control for experimental variability. Using a stringent detection p value cutoff of 0.04, 48% of all potential mRNA transcripts were predicted to be expressed (probes classified as present in at least two of three replicates), while 1,651 proteins were identified with high-confidence using rigorous database searching. Although 762 of 888 cross-referenced cognate mRNA-protein pairs were jointly detected by both platforms, a sizeable number (126) of gene products was detected exclusively by MS alone. Conversely, marginal protein identifications often had convincing microarray support. Based on these findings, we present an operational framework for both interpreting and integrating dual genomic and proteomic datasets so as to obtain a more reliable perspective into islet alpha cell function.