ObjectiveComplex local crosstalk amongst endocrine cells within the islet ensures tight coordination of their endocrine output. This is illustrated by the recent demonstration that the negative feedback control by delta cells within pancreatic islets determines the homeostatic set-point for plasma glucose during mouse postnatal development. However, the close association of islet endocrine cells that facilitates paracrine crosstalk also complicates the distinction between effects mediated directly on beta cells from indirect effects mediated via local intermediates, such as somatostatin from delta cells.MethodsTo resolve this problem, we generated reporter mice that allow collection of pure pancreatic delta cells along with alpha and beta cells from the same islets and generated comprehensive transcriptomes for each islet endocrine cell type. These transcriptomes afford an unparalleled view of the receptors expressed by delta, alpha and beta cells, and allow the prediction of which signal targets which endocrine cell type with great accuracy.ResultsFrom these transcriptomes, we discovered that the ghrelin receptor is expressed exclusively by delta cells within the islet, which was confirmed by fluorescent in situ hybridization and qPCR. Indeed, ghrelin increases intracellular calcium in delta cells in intact mouse islets, measured by GCaMP6 and robustly potentiates glucose-stimulated somatostatin secretion on mouse and human islets in both static and perfusion assays. In contrast, des-acyl-ghrelin at the same dose had no effect on somatostatin secretion and did not block the actions of ghrelin.ConclusionsThese results offer a straightforward explanation for the well-known insulinostatic actions of ghrelin. Rather than engaging beta cells directly, ghrelin engages delta cells to promote local inhibitory feedback that attenuates insulin release. These findings illustrate the power of our approach to resolve some of the long-standing conundrums with regard to the rich feedback that occurs within the islet that is integral to islet physiology and therefore highly relevant to diabetes.

No abstract

Hearing loss (HL) is the most common sensory deficit in humans with causative variants in over 140 genes. With few exceptions, however, the population-specific distribution for many of the identified variants/genes is unclear. Until recently, the extensive genetic and clinical heterogeneity of deafness precluded comprehensive genetic analysis. Here, using a custom capture panel (MiamiOtoGenes), we undertook a targeted sequencing of 180 genes in a multi-ethnic cohort of 342 GJB2 mutation-negative deaf probands from South Africa, Nigeria, Tunisia, Turkey, Iran, India, Guatemala and the United States (South Florida). We detected causative DNA variants in 25% of multiplex and 7% of simplex families. The detection rate varied between 0% and 57% based on ethnicity, with Guatemala and Iran at the lower and higher end of the spectrum, respectively. We detected causative variants within 27 genes without predominant recurring pathogenic variants. The most commonly implicated genes include MYO15A, SLC26A4, USH2A, MYO7A, MYO6 and TRIOBP. Overall, our study highlights the importance of family history and generation of databases for multiple ethnically discrete populations to improve our ability to detect and accurately interpret genetic variants for pathogenicity.

Islet gene expression has been widely studied to better understand the transcriptional features that define a healthy β-cell. Transcriptomes of FACS-purified α-, β-, and δ-cells using bulk RNA-sequencing have facilitated our understanding of the complex network of cross talk between islet cells and its effects on β-cell function. However, these approaches were by design not intended to resolve heterogeneity between individual cells. Several recent studies used single-cell RNA sequencing (scRNA-Seq) to report considerable heterogeneity within mouse and human β-cells. In this Perspective, we assess how this newfound ability to assess gene expression at single-cell resolution has enhanced our understanding of β-cell heterogeneity. We conduct a comprehensive assessment of several single human β-cell transcriptome data sets and ask if the heterogeneity reported by these studies showed overlap and concurred with previously known examples of β-cell heterogeneity. We also illustrate the impact of the inevitable limitations of working at or below the limit of detection of gene expression at single cell resolution and their consequences for the quality of single–islet cell transcriptome data. Finally, we offer some guidance on when to opt for scRNA-Seq and when bulk sequencing approaches may be better suited.