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      Identifying biological pathways that underlie primordial short stature using network analysis

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          Abstract

          Mutations in CUL7, OBSL1 and CCDC8, leading to disordered ubiquitination, cause one of the commonest primordial growth disorders, 3-M syndrome. This condition is associated with i) abnormal p53 function, ii) GH and/or IGF1 resistance, which may relate to failure to recycle signalling molecules, and iii) cellular IGF2 deficiency. However the exact molecular mechanisms that may link these abnormalities generating growth restriction remain undefined. In this study, we have used immunoprecipitation/mass spectrometry and transcriptomic studies to generate a 3-M ‘interactome’, to define key cellular pathways and biological functions associated with growth failure seen in 3-M. We identified 189 proteins which interacted with CUL7, OBSL1 and CCDC8, from which a network including 176 of these proteins was generated. To strengthen the association to 3-M syndrome, these proteins were compared with an inferred network generated from the genes that were differentially expressed in 3-M fibroblasts compared with controls. This resulted in a final 3-M network of 131 proteins, with the most significant biological pathway within the network being mRNA splicing/processing. We have shown using an exogenous insulin receptor ( INSR) minigene system that alternative splicing of exon 11 is significantly changed in HEK293 cells with altered expression of CUL7, OBSL1 and CCDC8 and in 3-M fibroblasts. The net result is a reduction in the expression of the mitogenic INSR isoform in 3-M syndrome. From these preliminary data, we hypothesise that disordered ubiquitination could result in aberrant mRNA splicing in 3-M; however, further investigation is required to determine whether this contributes to growth failure.

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          Insulin receptor isoforms and insulin receptor/insulin-like growth factor receptor hybrids in physiology and disease.

          In mammals, the insulin receptor (IR) gene has acquired an additional exon, exon 11. This exon may be skipped in a developmental and tissue-specific manner. The IR, therefore, occurs in two isoforms (exon 11 minus IR-A and exon 11 plus IR-B). The most relevant functional difference between these two isoforms is the high affinity of IR-A for IGF-II. IR-A is predominantly expressed during prenatal life. It enhances the effects of IGF-II during embryogenesis and fetal development. It is also significantly expressed in adult tissues, especially in the brain. Conversely, IR-B is predominantly expressed in adult, well-differentiated tissues, including the liver, where it enhances the metabolic effects of insulin. Dysregulation of IR splicing in insulin target tissues may occur in patients with insulin resistance; however, its role in type 2 diabetes is unclear. IR-A is often aberrantly expressed in cancer cells, thus increasing their responsiveness to IGF-II and to insulin and explaining the cancer-promoting effect of hyperinsulinemia observed in obese and type 2 diabetic patients. Aberrant IR-A expression may favor cancer resistance to both conventional and targeted therapies by a variety of mechanisms. Finally, IR isoforms form heterodimers, IR-A/IR-B, and hybrid IR/IGF-IR receptors (HR-A and HR-B). The functional characteristics of such hybrid receptors and their role in physiology, in diabetes, and in malignant cells are not yet fully understood. These receptors seem to enhance cell responsiveness to IGFs.
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            The BioGRID interaction database: 2013 update

            The Biological General Repository for Interaction Datasets (BioGRID: http//thebiogrid.org) is an open access archive of genetic and protein interactions that are curated from the primary biomedical literature for all major model organism species. As of September 2012, BioGRID houses more than 500 000 manually annotated interactions from more than 30 model organisms. BioGRID maintains complete curation coverage of the literature for the budding yeast Saccharomyces cerevisiae, the fission yeast Schizosaccharomyces pombe and the model plant Arabidopsis thaliana. A number of themed curation projects in areas of biomedical importance are also supported. BioGRID has established collaborations and/or shares data records for the annotation of interactions and phenotypes with most major model organism databases, including Saccharomyces Genome Database, PomBase, WormBase, FlyBase and The Arabidopsis Information Resource. BioGRID also actively engages with the text-mining community to benchmark and deploy automated tools to expedite curation workflows. BioGRID data are freely accessible through both a user-defined interactive interface and in batch downloads in a wide variety of formats, including PSI-MI2.5 and tab-delimited files. BioGRID records can also be interrogated and analyzed with a series of new bioinformatics tools, which include a post-translational modification viewer, a graphical viewer, a REST service and a Cytoscape plugin.
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              A protein-protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration.

              Many human inherited neurodegenerative disorders are characterized by loss of balance due to cerebellar Purkinje cell (PC) degeneration. Although the disease-causing mutations have been identified for a number of these disorders, the normal functions of the proteins involved remain, in many cases, unknown. To gain insight into the function of proteins involved in PC degeneration, we developed an interaction network for 54 proteins involved in 23 inherited ataxias and expanded the network by incorporating literature-curated and evolutionarily conserved interactions. We identified 770 mostly novel protein-protein interactions using a stringent yeast two-hybrid screen; of 75 pairs tested, 83% of the interactions were verified in mammalian cells. Many ataxia-causing proteins share interacting partners, a subset of which have been found to modify neurodegeneration in animal models. This interactome thus provides a tool for understanding pathogenic mechanisms common for this class of neurodegenerative disorders and for identifying candidate genes for inherited ataxias.

                Author and article information

                Journal
                J Mol Endocrinol
                J. Mol. Endocrinol
                JME
                Journal of Molecular Endocrinology
                Bioscientifica Ltd (Bristol )
                0952-5041
                1479-6813
                June 2014
                7 April 2014
                : 52
                : 3
                : 333-344
                Affiliations
                [1 ]Institute of Human Development, Faculty of Medical and Human Sciences, The University of Manchester Oxford Road, Manchester, M13 9WLUK
                [2 ]Manchester Academic Health Sciences Centre (MAHSC), Central Manchester University Hospitals NHS Foundation Trust Manchester, M13 9WLUK
                Author notes
                Correspondence should be addressed to D Hanson; Email: Daniel.hanson@ 123456manchester.ac.uk
                Article
                JME140029
                10.1530/JME-14-0029
                4045235
                24711643
                6af79b87-e09a-439f-843f-eeb89b3c8f47
                © 2014 The authors

                This work is licensed under a Creative Commons Attribution 3.0 Unported License

                History
                : 21 March 2014
                : 28 March 2014
                Categories
                Research

                Endocrinology & Diabetes
                insulin receptor,igf,growth factors,molecular genetics
                Endocrinology & Diabetes
                insulin receptor, igf, growth factors, molecular genetics

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