Cellular communication and heterogeneity in pancreatic islet insulin secretion dynamics

Expression profiling of preadipocyte microRNAs by deep sequencing on chicken lines divergently selected for abdominal fatness

Through posttranscriptional gene regulation, microRNA (miRNA) is linked to a wide variety of biological processes, including adipogenesis and lipid metabolism. Although miRNAs in mammalian adipogenesis have been worked on extensively, their study in chicken adipogenesis is still very limited. To find miRNAs potentially important for chicken preadipocyte development, we compared the preadipocyte miRNA expression profiles in two broiler lines divergently selected for abdominal fat content, by sequencing two small RNA libraries constructed for primary preadipocytes isolated from abdominal adipose tissues. After bioinformatics analyses, from chicken miRNAs deposited in miRBase 20.0, we identified 225 miRNAs to be expressed in preadipocytes, 185 in the lean line and 200 in the fat line (derived from 208 and 203 miRNA precursors, respectively), which corresponds to 114 miRNA families. The let-7 family miRNAs were the most abundant. Furthermore, we validated the sequencing results of 15 known miRNAs by qRT-PCR, and confirmed that the expression levels of most miRNAs correlated well with those of Solexa sequencing. A total of 33 miRNAs was significantly differentially expressed between the two chicken lines (P<0.05). Gene ontology analysis revealed that they could target genes enriched in the regulation of gene transcription and chromatin function, response to insulin stimulation, and IGF-1 signaling pathways, which could have important roles in preadipocyte development. Therefore, a valuable information and resource of miRNAs on chicken adipogenesis were provided in this study. Future functional investigations on these miRNAs could help explore related genes and molecular networks fundamental to preadipocyte development.

Beta cell connectivity in pancreatic islets: a type 2 diabetes target?

Beta cell connectivity describes the phenomenon whereby the islet context improves insulin secretion by providing a three-dimensional platform for intercellular signaling processes. Thus, the precise flow of information through homotypically interconnected beta cells leads to the large-scale organization of hormone release activities, influencing cell responses to glucose and other secretagogues. Although a phenomenon whose importance has arguably been underappreciated in islet biology until recently, a growing number of studies suggest that such cell-cell communication is a fundamental property of this micro-organ. Hence, connectivity may plausibly be targeted by both environmental and genetic factors in type 2 diabetes mellitus (T2DM) to perturb normal beta cell function and insulin release. Here, we review the mechanisms that contribute to beta cell connectivity, discuss how these may fail during T2DM, and examine approaches to restore insulin secretion by boosting cell communication.

Progressive glucose stimulation of islet beta cells reveals a transition from segregated to integrated modular functional connectivity patterns

Collective beta cell activity in islets of Langerhans is critical for the supply of insulin within an organism. Even though individual beta cells are intrinsically heterogeneous, the presence of intercellular coupling mechanisms ensures coordinated activity and a well-regulated exocytosis of insulin. In order to get a detailed insight into the functional organization of the syncytium, we applied advanced analytical tools from the realm of complex network theory to uncover the functional connectivity pattern among cells composing the intact islet. The procedure is based on the determination of correlations between long temporal traces obtained from confocal functional multicellular calcium imaging of beta cells stimulated in a stepwise manner with a range of physiological glucose concentrations. Our results revealed that the extracted connectivity networks are sparse for low glucose concentrations, whereas for higher stimulatory levels they become more densely connected. Most importantly, for all ranges of glucose concentration beta cells within the islets form locally clustered functional sub-compartments, thereby indicating that their collective activity profiles exhibit a modular nature. Moreover, we show that the observed non-linear functional relationship between different network metrics and glucose concentration represents a well-balanced setup that parallels physiological insulin release.