Dataset Information

Brannmark2010_InsulinSignalling_Mifamodel

ABSTRACT: This model is from the article: Mass and information feedbacks through receptor endocytosis govern insulin signaling as revealed using a parameter-free modeling framework. Brannmark C, Palmer R, Glad ST, Cedersund G, Stralfors P. J Biol Chem.2010 Jun 25;285(26):20171-9. 20421297, Abstract: Insulin and other hormones control target cells through a network of signal-mediating molecules. Such networks are extremely complex due to multiple feedback loops in combination with redundancy, shared signal mediators, and cross-talk between signal pathways. We present a novel framework that integrates experimental work and mathematical modeling to quantitatively characterize the role and relation between co-existing submechanisms in complex signaling networks. The approach is independent of knowing or uniquely estimating model parameters because it only relies on (i) rejections and (ii) core predictions (uniquely identified properties in unidentifiable models). The power of our approach is demonstrated through numerous iterations between experiments, model-based data analyses, and theoretical predictions to characterize the relative role of co-existing feedbacks governing insulin signaling. We examined phosphorylation of the insulin receptor and insulin receptor substrate-1 and endocytosis of the receptor in response to various different experimental perturbations in primary human adipocytes. The analysis revealed that receptor endocytosis is necessary for two identified feedback mechanisms involving mass and information transfer, respectively. Experimental findings indicate that interfering with the feedback may substantially increase overall signaling strength, suggesting novel therapeutic targets for insulin resistance and type 2 diabetes. Because the central observations are present in other signaling networks, our results may indicate a general mechanism in hormonal control.

DISEASE(S): Diabetes Mellitus

SUBMITTER: Ishan Ajmera

PROVIDER: BIOMD0000000343 | BioModels | 2011-07-14

REPOSITORIES: BioModels

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Publications

Mass and information feedbacks through receptor endocytosis govern insulin signaling as revealed using a parameter-free modeling framework.

Brännmark Cecilia C Palmér Robert R Glad S Torkel ST Cedersund Gunnar G Strålfors Peter P

The Journal of biological chemistry 20100426 26

Insulin and other hormones control target cells through a network of signal-mediating molecules. Such networks are extremely complex due to multiple feedback loops in combination with redundancy, shared signal mediators, and cross-talk between signal pathways. We present a novel framework that integrates experimental work and mathematical modeling to quantitatively characterize the role and relation between co-existing submechanisms in complex signaling networks. The approach is independent of k ...[more]

PMID: 20421297

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Project description:Drosophila Lnk is the single ancestral orthologue of a highly conserved family of structurally-related intracellular adaptor proteins, the SH2B proteins. As adaptors, they lack catalytic activity but contain several protein-protein interaction domains, thus playing a critical role in signal transduction from receptor tyrosine kinases to form protein networks. Physiological studies of SH2B function in mammals have produced conflicting data. However, a recent study in Drosophila has shown that Lnk is an important regulator of the insulin/insulin-like growth factor (IGF)-1 signaling (IIS) pathway during growth, functioning in parallel to the insulin receptor substrate, Chico. As this pathway also has an evolutionary conserved role in the determination of organism lifespan, we investigated whether Lnk is required for normal lifespan in Drosophila. Phenotypic analysis of mutants for Lnk revealed that loss of Lnk function results in increased lifespan and improved survival under conditions of oxidative stress and starvation. Starvation resistance was found to be associated with increased metabolic stores of carbohydrates and lipids indicative of impaired metabolism. Biochemical and genetic data suggest that Lnk functions in both the IIS and Ras/Mitogen activated protein Kinase (MapK) signaling pathways. Microarray studies support this model, showing transcriptional feedback onto genes in both pathways as well as indicating global changes in both lipid and carbohydrate metabolism. Finally, our data also suggest that Lnk itself may be a direct target of the IIS responsive transcription factor, dFoxo, and that dFoxo may repress Lnk expression. We therefore describe novel functions for a member of the SH2B protein family and provide the first evidence for potential mechanisms of SH2B regulation. Our findings suggest that IIS signaling in Drosophila may require the activity of a second intracellular adaptor, thereby yielding fundamental new insights into the functioning and role of the IIS pathway in ageing and metabolism.

Project description:Brännmark2013 - Insulin signalling in human adipocytes (diabetic condition) The paper describes insulin signalling in human adipocytes under normal and diabetic states using mathematical models based on experimental data. This model corresponds to insulin signalling under diabetic condtion This model is described in the article: Insulin Signaling in Type 2 Diabetes: EXPERIMENTAL AND MODELING ANALYSES REVEAL MECHANISMS OF INSULIN RESISTANCE IN HUMAN ADIPOCYTES. Brännmark C, Nyman E, Fagerholm S, Bergenholm L, Ekstrand EM, Cedersund G, Strålfors P. J Biol Chem. 2013 Apr 5;288(14):9867-80. Abstract: Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems level mechanistic understanding of insulin resistance, using systems wide and internally consistent data from human adipocytes. Based on quantitative steady-state and dynamic time course data on signaling intermediaries, normally and in diabetes, we developed a dynamic mathematical model of insulin signaling. The model structure and parameters are identical in the normal and diabetic states of the model, except for three parameters that change in diabetes: (i) reduced concentration of insulin receptor, (ii) reduced concentration of insulin-regulated glucose transporter GLUT4, and (iii) changed feedback from mammalian target of rapamycin in complex with raptor (mTORC1). Modeling reveals that at the core of insulin resistance in human adipocytes is attenuation of a positive feedback from mTORC1 to the insulin receptor substrate-1, which explains reduced sensitivity and signal strength throughout the signaling network. Model simulations with inhibition of mTORC1 are comparable with experimental data on inhibition of mTORC1 using rapamycin in human adipocytes. We demonstrate the potential of the model for identification of drug targets, e.g. increasing the feedback restores insulin signaling, both at the cellular level and, using a multilevel model, at the whole body level. Our findings suggest that insulin resistance in an expanded adipose tissue results from cell growth restriction to prevent cell necrosis. This model is hosted on BioModels Database and identified by: MODEL1304160000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Brännmark2013 - Insulin signalling in human adipocytes (normal condition) The paper describes insulin signalling in human adipocytes under normal and diabetic states using mathematical models based on experimental data. This model corresponds to insulin signalling under normal condtion This model is described in the article: Insulin Signaling in Type 2 Diabetes: EXPERIMENTAL AND MODELING ANALYSES REVEAL MECHANISMS OF INSULIN RESISTANCE IN HUMAN ADIPOCYTES. Brännmark C, Nyman E, Fagerholm S, Bergenholm L, Ekstrand EM, Cedersund G, Strålfors P. J Biol Chem. 2013 Apr 5;288(14):9867-80. Abstract: Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems level mechanistic understanding of insulin resistance, using systems wide and internally consistent data from human adipocytes. Based on quantitative steady-state and dynamic time course data on signaling intermediaries, normally and in diabetes, we developed a dynamic mathematical model of insulin signaling. The model structure and parameters are identical in the normal and diabetic states of the model, except for three parameters that change in diabetes: (i) reduced concentration of insulin receptor, (ii) reduced concentration of insulin-regulated glucose transporter GLUT4, and (iii) changed feedback from mammalian target of rapamycin in complex with raptor (mTORC1). Modeling reveals that at the core of insulin resistance in human adipocytes is attenuation of a positive feedback from mTORC1 to the insulin receptor substrate-1, which explains reduced sensitivity and signal strength throughout the signaling network. Model simulations with inhibition of mTORC1 are comparable with experimental data on inhibition of mTORC1 using rapamycin in human adipocytes. We demonstrate the potential of the model for identification of drug targets, e.g. increasing the feedback restores insulin signaling, both at the cellular level and, using a multilevel model, at the whole body level. Our findings suggest that insulin resistance in an expanded adipose tissue results from cell growth restriction to prevent cell necrosis. This model is hosted on BioModels Database and identified by: MODEL1304190000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Background: Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer in the adult population. Late diagnosis, resistance to therapeutics and recurrence of metastatic lesions account for the highest mortality rate among kidney cancer patients. Identifying novel biomarkers for early cancer detection and elucidating the mechanisms underlying ccRCC growth and progression will provide clues to treat this aggressive malignant tumor. Method: Expression studies of RING ligase praja2 and tyrosine kinase receptors (RTKs) in renal cell carcinoma was evaluated by immunoblot and immunohistochemistry. Gene transcription profiling in RCC cells was evaluated by RNA sequencing and Ingenuity Pathway Analysis. Imunofluorescence assays were used to evaluate the intracellular distribution and clearance of membrane receptors in cells devoid of praja2. Ubiquitin modifications and protein-protein interaction networks were monitored by IP, western blot, mass spectrometry and proteomic analysis. Experiments in vitro and in vivo were performed to define the role of praja2 in RTKs turnover, metabolism, renal cell carcinoma growth and metastatic diffusion. Results: We report here that the ubiquitin ligase praja2 controls endocytosis and the signal strength of different types of receptors (EGFR, VEGFR, TfR). Praja2 forms a complex with- and ubiquitinates the adaptor protein AP2m required for the activity of ATPase and acidification of endosomes and lysosomes necessary for receptor endocytosis and clearance. Downregulation of praja2 blocks the endocytosis of several membrane receptors, including EGFR, VEGFR and TfR and amplifies mitogenic and proliferative signaling as shown in the clear cell renal cell carcinoma (ccRCC). Restoring praja2 expression in RCC cells reduces EGFR levels, rewires cancer cell metabolism and inhibits growth and metastatic diffusion. In vivo, praja2 knockout mice show upregulation of tyrosine kinase receptors (RTKs) and pronounced histopathological renal alterations. Conclusion: Our findings identify praja2 as an important regulator of tyrosine kinase receptor(s) turnover and can be considered a bona fide oncosuppressor because it finely regulates signaling of several types of receptors and its loss supports kidney cancer growth and diffusion.

Dataset Information

Brannmark2010_InsulinSignalling_Mifamodel

Publications

Mass and information feedbacks through receptor endocytosis govern insulin signaling as revealed using a parameter-free modeling framework.

Similar Datasets

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