Orexin-1 Receptor Co-Localizes with Pancreatic Hormones in Islet Cells and Modulates the Outcome of Streptozotocin-Induced Diabetes Mellitus

Recent studies have shown that orexins play a critical role in the regulation of sleep/wake states, feeding behaviour, and reward processes. The exocrine and endocrine pancreas are involved in the regulation of food metabolism and energy balance. This function is deranged in diabetes mellitus. This study examined the pattern of distribution of orexin-1 receptor (OX1R) in the endocrine cells of the pancreas of normal and diabetic Wistar (a model of type 1 diabetes), Goto-Kakizaki (GK, a model of type 2 diabetes) rats and in orexin-deficient (OX−/−) and wild type mice. Diabetes mellitus (DM) was induced in Wistar rats and mice by streptozotocin (STZ). At different time points (12 h, 24 h, 4 weeks, 8 months and 15 months) after the induction of DM, pancreatic fragments of normal and diabetic rats were processed for immunohistochemistry and Western blotting. OX1R-immunoreactive nerves were observed in the pancreas of normal and diabetic Wistar rats. OX1R was also discernible in the pancreatic islets of normal and diabetic Wistar and GK rats, and wild type mice. OX1R co-localized with insulin (INS) and glucagon (GLU) in the pancreas of Wistar and GK rats. The number of OX1R-positive cells in the islets increased markedly (p<0.0001) after the onset of DM. The increase in the number of OX1R-positive cells is associated with a high degree of co-localization with GLU. The number of GLU- positive cells expressing OX1R was significantly (p<0.0001) higher after the onset of DM. The tissue level of OX1R protein increased with the duration of DM especially in type 1 diabetes where it co-localized with cleaved caspase 3 in islet cells. In comparison to STZ-treated wild type mice, STZ-treated OX−/− animals exhibited reduced hyperglycemia and handled glucose more efficiently in glucose tolerance test. The findings suggest an important role for the OX-OX1R pathway in STZ-induced experimental diabetes

The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability.

BackgroundThe Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies.Construction and contentRecent work on the CL has&nbsp;focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class 'cell in vitro' have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning.Utility and discussionThe CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs.ConclusionsThe ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the CL both among developers and within the user community

The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability.

BackgroundThe Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies.Construction and contentRecent work on the CL has&nbsp;focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class 'cell in vitro' have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning.Utility and discussionThe CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs.ConclusionsThe ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the CL both among developers and within the user community

The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability.

BACKGROUND: The Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies. CONSTRUCTION AND CONTENT: Recent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class \u27cell in vitro\u27 have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning. UTILITY AND DISCUSSION: The CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs. CONCLUSIONS: The ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the CL both among developers and within the user community. J Biomed Semantics 2016 Jul 4; 7(1):4