RESUMEN
Somatostatin secreted by pancreatic δ cells mediates important paracrine interactions in Langerhans islets, including maintenance of glucose metabolism through the control of reciprocal insulin and glucagon secretion. Disruption of this circuit contributes to the development of diabetes. However, the precise mechanisms that control somatostatin secretion from islets remain elusive. Here, we found that a super-complex comprising the cullin 4B-RING E3 ligase (CRL4B) and polycomb repressive complex 2 (PRC2) epigenetically regulates somatostatin secretion in islets. Constitutive ablation of CUL4B, the core component of the CRL4B-PRC2 complex, in δ cells impaired glucose tolerance and decreased insulin secretion through enhanced somatostatin release. Moreover, mechanistic studies showed that the CRL4B-PRC2 complex, under the control of the δ cell-specific transcription factor hematopoietically expressed homeobox (HHEX), determines the levels of intracellular calcium and cAMP through histone posttranslational modifications, thereby altering expression of the Cav1.2 calcium channel and adenylyl cyclase 6 (AC6) and modulating somatostatin secretion. In response to high glucose levels or urocortin 3 (UCN3) stimulation, increased expression of cullin 4B (CUL4B) and the PRC2 subunit histone-lysine N-methyltransferase EZH2 and reciprocal decreases in Cav1.2 and AC6 expression were found to regulate somatostatin secretion. Our results reveal an epigenetic regulatory mechanism of δ cell paracrine interactions in which CRL4B-PRC2 complexes, Cav1.2, and AC6 expression fine-tune somatostatin secretion and facilitate glucose homeostasis in pancreatic islets.
Asunto(s)
Proteínas Cullin/metabolismo , Insulina/metabolismo , Complejos Multienzimáticos/metabolismo , Comunicación Paracrina , Células Secretoras de Somatostatina/metabolismo , Somatostatina/metabolismo , Adenilil Ciclasas/genética , Adenilil Ciclasas/metabolismo , Animales , Calcio/metabolismo , Canales de Calcio Tipo L/genética , Canales de Calcio Tipo L/metabolismo , Proteínas Cullin/genética , AMP Cíclico/metabolismo , Epigénesis Genética , Proteínas de Homeodominio/genética , Proteínas de Homeodominio/metabolismo , Insulina/genética , Secreción de Insulina , Ratones , Ratones Noqueados , Complejos Multienzimáticos/genética , Somatostatina/genética , Células Secretoras de Somatostatina/citología , Factores de Transcripción/genética , Factores de Transcripción/metabolismoRESUMEN
The heavy metal cadmium is a non-degradable pollutant. By screening the effects of a panel of metal ions on the phosphatase activity, we unexpectedly identified cadmium as a potent inhibitor of PPM1A and PPM1G. In contrast, low micromolar concentrations of cadmium did not inhibit PP1 or tyrosine phosphatases. Kinetic studies revealed that cadmium inhibits PPM phosphatases through the M1 metal ion binding site. In particular, the negative charged D441 in PPM1G specific recognized cadmium. Our results suggest that cadmium is likely a potent inhibitor of most PPM family members except for PHLPPs. Furthermore, we demonstrated that cadmium inhibits PPM1A-regulated MAPK signaling and PPM1G-regulated AKT signaling potently in vivo. Cadmium reversed PPM1A-induced cell cycle arrest and cadmium insensitive PPM1A mutant rescued cadmium induced cell death. Taken together, these findings provide a better understanding of the effects of the toxicity of cadmium in the contexts of human physiology and pathology.
Asunto(s)
Cadmio/química , Cadmio/farmacocinética , Modelos Químicos , Fosfoproteínas Fosfatasas/antagonistas & inhibidores , Fosfoproteínas Fosfatasas/metabolismo , Sitios de Unión , Simulación por Computador , Activación Enzimática , Células HEK293 , Humanos , Cinética , Unión Proteica , Proteína Fosfatasa 2CRESUMEN
Prototype based learning offers an intuitive interface to inspect large quantities of electronic data in supervised or unsupervised settings. Recently, many techniques have been extended to data described by general dissimilarities rather than Euclidean vectors, so-called relational data settings. Unlike the Euclidean counterparts, the techniques have quadratic time complexity due to the underlying quadratic dissimilarity matrix. Thus, they are infeasible already for medium sized data sets. The contribution of this article is twofold: On the one hand we propose a novel supervised prototype based classification technique for dissimilarity data based on popular learning vector quantization (LVQ), on the other hand we transfer a linear time approximation technique, the Nyström approximation, to this algorithm and an unsupervised counterpart, the relational generative topographic mapping (GTM). This way, linear time and space methods result. We evaluate the techniques on three examples from the biomedical domain.