MOPRs in mouse islets of Langerhans modulate cell signaling and secretion
Keith, M.; Stander, C.; De Gregorio, D.; Huang, A.; Townsend, S.; Sheybani-Deloui, S.; Zigman, J.; Hughes, J.; Castro, D. C.
Show abstract
Article highlightsO_LIMu opioid receptors are expressed on multiple islets of Langerhans cell types C_LIO_LIMu opioid receptors on islets engage canonical Gi signaling cascades in islets C_LIO_LIMu opioid receptors on islets modulate calcium influx and oscillations C_LIO_LIMu opioid receptors on islets modulate insulin and glucagon secretion. C_LI Most clinically and recreationally used opioids drugs act on the endogenous mu opioid receptor (MOPR). While MOPR is typically studied in the context of addiction and analgesia, decades of evidence indicates that they have a strong modulatory role on metabolism and glycemia. However, whether these effects are directly driven by MOPR actions on pancreatic islets remains poorly understood. Here we sought to comprehensively profile MOPRs on islets to assess how their activity shapes cellular physiology and secretion. First, we used RNA-seq, fluorescent in situ hybridization, and immunoblotting approaches to map islet expression. We observed robust expression of MOPR across multiple cell types in islets. Next, using a FRET-based approach, we show that MOPRs recruit canonical inhibitory pathways, reducing cAMP accumulation. Correspondingly, islets from constitutive MOPR knockout mice showed increased calcium influx and oscillations. However, MOPR knockout had no effect on insulin secretion, instead increase glucagon secretion. Surprisingly, while MOPR antagonism increased overall calcium, it reduced calcium oscillations and suppressed insulin secretion. By contrast MOPR agonism suppressed calcium, increased oscillations, and had no effect on overall hormone secretion. Collectively, these results suggest that MOPR can profoundly shape islet activity, with these effects likely driven by their actions on distinct cell types.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Reduced somatostatin signalling leads to hypersecretion of glucagon in mice fed a high fat diet 96%
- Interruption of glucagon signaling augments islet non-alpha cell proliferation in SLC7A2- and mTOR-dependent manners 95%
- Chemical induction of gut β-like-cells by combined FoxO1/Notch inhibition as a glucose-lowering treatment for diabetes 94%
Similar papers in this journal
- β-Hydroxybutyrate promotes basal insulin secretion while decreasing glucagon secretion in mouse and human islets. 96%
- Small molecule-mediated insulin hypersecretion induces transient unfolded protein response and loss of beta cell function 95%
- Acute Inhibition of Adipose Triglyceride Lipase by NG497 Dysregulates Insulin and Glucagon Secretion from Human Islets 94%
Similar papers in this journal
- Heterogenous impairment of α-cell function in type 2 diabetes is linked to cell maturation state 95%
- Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease 94%
- Hyperinsulinemia acts via acinar insulin receptors to initiate pancreatic cancer by increasing digestive enzyme production and inflammation 93%
Similar papers in this journal
- Role of Complexin 2 in the regulation of hormone secretion from the islet of Langerhans 96%
- CYP1A1/1A2 enzymes mediate glucose homeostasis and insulin secretion in mice in a sex-specific manner 93%
- Glucose-dependent activation, activity, and deactivation of beta cell networks in acute mouse pancreas tissue slices 93%
Similar papers in this journal
- Pronounced proliferation of non-beta cells in response to beta-cell mitogens in isolated human islets of Langerhans 96%
- Generation and application of novel hES cell reporter lines for the differentiation and maturation of hPS cell-derived islet-like clusters 95%
- In vivo imaging of individual islets across the mouse pancreas reveals a heterogeneous insulin secretion response to glucose 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.