Probes for SST

The ghrelin producing ε-cell represents the fifth endocrine cell type in human pancreatic islets. The abundance of ε-cells in adult pancreas is extremely low, which has hampered the investigation on the molecular pathways regulating the development and the function of this cell type. In this study, we explored the molecular features defining the function of pancreatic ε-cells isolated from adult non-diabetic donors using single-cell RNA sequencing technology. We focus on transcription factors, cell surface receptors and genes involved in metabolic pathways that contribute to regulation of cellular function. Furthermore, the genes that separate ε-cells from the other islet endocrine cell types are presented. This study expands prior knowledge about the genes important for the function of the ε-cell during development and provides a resource to interrogate the transcriptome of this rare human islet cell type.

Despite notable genetic influences, obesity mainly results from the overconsumption of food, which arises from the interplay of physiological, cognitive and environmental factors. In patients with obesity, eating is determined more by external cues than by internal physiological needs. However, how environmental context drives non-homeostatic feeding is elusive. Here, we identify a population of somatostatin (TNSST) neurons in the mouse hypothalamic tuberal nucleus that are preferentially activated by palatable food. Activation of TNSST neurons enabled a context to drive non-homeostatic feeding in sated mice and required inputs from the subiculum. Pairing a context with palatable food greatly potentiated synaptic transmission between the subiculum and TNSST neurons and drove non-homeostatic feeding that could be selectively suppressed by inhibiting TNSST neurons or the subiculum but not other major orexigenic neurons. These results reveal how palatable food, through a specific hypothalamic circuit, empowers environmental context to drive non-homeostatic feeding.

Polycystic ovary syndrome (PCOS) is a female endocrine disorder that is associated with prenatal exposure to excess androgens. In prenatally androgenized (PNA) mice that model PCOS, GABAergic neural transmission to and innervation of GnRH neurons is increased. Evidence suggests that elevated GABAergic innervation originates in the arcuate nucleus (ARC). We hypothesised that GABA-GnRH circuit abnormalities are a direct consequence of PNA, resulting from DHT binding to androgen receptor (AR) in the prenatal brain. However, whether prenatal ARC neurons express AR at the time of PNA treatment is presently unknown. We used RNAScope _in situ_ hybridization to localize AR mRNA (_Ar_)-expressing cells in healthy gestational day (GD) 17.5 female mouse brains and to assess co-expression levels in specific neuronal phenotypes. Our study revealed that less than 10% of ARC GABA cells expressed _Ar_. In contrast, we found that ARC kisspeptin neurons, critical regulators of GnRH neurons, were highly co-localised with _Ar_. Approximately 75% of ARC _Kiss1_-expressing cells also expressed _Ar_ at GD17.5, suggesting that ARC kisspeptin neurons are potential targets of PNA. Investigating other neuronal populations in the ARC we found that approximately 50% of pro-opiomelanocortin (_Pomc_) cells, 22% of tyrosine hydroxylase (_Th_) cells, 8% of agouti-related protein (_Agrp_) cells and 8% of somatostatin (_Sst_) cells express _Ar_. Lastly, RNAscope in coronal sections showed _Ar_ expression in the medial preoptic area (mPOA), and the ventral part of the lateral septum (vLS). These _Ar_-expressing regions were highly GABAergic, and 22% of GABA cells in the mPOA and 25% of GABA cells in the vLS also expressed _Ar_. Our findings identify specific neuronal phenotypes in the ARC, mPOA and vLS that are androgen sensitive in late gestation. PNA-induced functional changes in these neurons may be related to the development of impaired central mechanisms associated with PCOS-like features.

Pancreatic islets depend on cytosolic calcium (Ca2+) to trigger the secretion of glucoregulatory hormones and trigger transcriptional regulation of genes important for islet response to stimuli. To date, there has not been an attempt to profile Ca2+-regulated gene expression in all islet cell types. Our aim was to construct a large single-cell transcriptomic dataset from human islets exposed to conditions that would acutely induce or inhibit intracellular Ca2+ signalling, while preserving biological heterogeneity.We exposed intact human islets from three donors to the following conditions: (1) 2.8 mmol/l glucose; (2) 16 mmol/l glucose and 40 mmol/l KCl to maximally stimulate Ca2+ signalling; and (3) 16 mmol/l glucose, 40 mmol/l KCl and 5 mmol/l EGTA (Ca2+ chelator) to inhibit Ca2+ signalling, for 1 h. We sequenced 68,650 cells from all islet cell types, and further subsetted the cells to form an endocrine cell-specific dataset of 59,373 cells expressing INS, GCG, SST or PPY. We compared transcriptomes across conditions to determine the differentially expressed Ca2+-regulated genes in each endocrine cell type, and in each endocrine cell subcluster of alpha and beta cells.Based on the number of Ca2+-regulated genes, we found that each alpha and beta cell cluster had a different magnitude of Ca2+ response. We also showed that polyhormonal clusters expressing both INS and GCG, or both INS and SST, are defined by Ca2+-regulated genes specific to each cluster. Finally, we identified the gene PCDH7 from the beta cell clusters that had the highest number of Ca2+-regulated genes, and showed that cells expressing cell surface PCDH7 protein have enhanced glucose-stimulated insulin secretory function.Here we use our large-scale, multi-condition, single-cell dataset to show that human islets have cell-type-specific Ca2+-regulated gene expression profiles, some of them specific to subpopulations. In our dataset, we identify PCDH7 as a novel marker of beta cells having an increased number of Ca2+-regulated genes and enhanced insulin secretory function.A searchable and user-friendly format of the data in this study, specifically designed for rapid mining of single-cell RNA sequencing data, is available at https://lynnlab.shinyapps.io/Human_Islet_Atlas/ . The raw data files are available at NCBI Gene Expression Omnibus (GSE196715).