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SteatoNet: the first integrated human metabolic model with multi-layered regulation to investigate liver-associated pathologies.

ABSTRACT: Current state-of-the-art mathematical models to investigate complex biological processes, in particular liver-associated pathologies, have limited expansiveness, flexibility, representation of integrated regulation and rely on the availability of detailed kinetic data. We generated the SteatoNet, a multi-pathway, multi-tissue model and in silico platform to investigate hepatic metabolism and its associated deregulations. SteatoNet is based on object-oriented modelling, an approach most commonly applied in automotive and process industries, whereby individual objects correspond to functional entities. Objects were compiled to feature two novel hepatic modelling aspects: the interaction of hepatic metabolic pathways with extra-hepatic tissues and the inclusion of transcriptional and post-transcriptional regulation. SteatoNet identification at normalised steady state circumvents the need for constraining kinetic parameters. Validation and identification of flux disturbances that have been proven experimentally in liver patients and animal models highlights the ability of SteatoNet to effectively describe biological behaviour. SteatoNet identifies crucial pathway branches (transport of glucose, lipids and ketone bodies) where changes in flux distribution drive the healthy liver towards hepatic steatosis, the primary stage of non-alcoholic fatty liver disease. Cholesterol metabolism and its transcription regulators are highlighted as novel steatosis factors. SteatoNet thus serves as an intuitive in silico platform to identify systemic changes associated with complex hepatic metabolic disorders.

SUBMITTER: Naik A

PROVIDER: S-EPMC4263370 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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SteatoNet: the first integrated human metabolic model with multi-layered regulation to investigate liver-associated pathologies.

Naik Adviti A Rozman Damjana D Belič Aleš A

PLoS computational biology 20141211 12

Current state-of-the-art mathematical models to investigate complex biological processes, in particular liver-associated pathologies, have limited expansiveness, flexibility, representation of integrated regulation and rely on the availability of detailed kinetic data. We generated the SteatoNet, a multi-pathway, multi-tissue model and in silico platform to investigate hepatic metabolism and its associated deregulations. SteatoNet is based on object-oriented modelling, an approach most commonly ...[more]

PMID: 25500563

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Project description:Aims/hypothesisIRS2 is an important molecular switch that mediates insulin signalling in the liver. IRS2 dysregulation is responsible for the phenomenon of selective insulin resistance that is observed in type 2 diabetes. We hypothesise that epigenetic mechanisms are involved in the regulation of IRS2 in the liver of obese and type 2 diabetic individuals.MethodsDNA methylation of seven CpG sites was studied by bisulphite pyrosequencing and mRNA and microRNA (miRNA) expression was assessed by quantitative real-time PCR in liver biopsies of 50 obese non-diabetic and 31 obese type 2 diabetic participants, in a cross-sectional setting. Methylation-sensitive luciferase assays and electrophoretic mobility shift assays were performed. Furthermore, HepG2 cells were treated with insulin and high glucose concentrations to induce miRNA expression and IRS2 downregulation.ResultsWe found a significant downregulation of IRS2 expression in the liver of obese individuals with type 2 diabetes (0.84 ± 0.08-fold change; p = 0.0833; adjusted p value [pa] = 0.0417; n = 31) in comparison with non-diabetic obese participants (n = 50). This downregulation correlated with hepatic IRS2 DNA methylation at CpG5. Additionally, CpG6, which is located in intron 1 of IRS2, was hypomethylated in type 2 diabetes; this site spans the sterol regulatory element binding transcription factor 1 (SREBF1) recognition motif, which likely acts as transcriptional repressor. The adjacent polymorphism rs4547213 (G>A) was significantly associated with DNA methylation at a specificity-protein-1 (SP1) binding site (CpG3). Moreover, DNA methylation of cg25924746, a CpG site located in the shore region of the IRS2 promoter-associated CpG island, was increased in the liver of individuals with type 2 diabetes, as compared with those without diabetes. A second epigenetic mechanism, upregulation of hepatic miRNA hsa-let-7e-5p (let-7e-5p) in obese individuals with type 2 diabetes (n = 29) vs non-diabetic obese individuals (n = 49) (1.2 ± 0.08-fold change; p = 0.0332; pa = 0.0450), is likely to act synergistically with altered IRS2 DNA methylation to decrease IRS2 expression. Mechanistic in vitro experiments demonstrated an acute upregulation of let-7e-5p expression and simultaneous IRS2 downregulation in a liver (HepG2) cell line upon hyperinsulinaemic and hyperglycaemic conditions.Conclusions/interpretationOur study highlights a new multi-layered epigenetic network that could be involved in subtle dysregulation of IRS2 in the liver of individuals with type 2 diabetes. This might lead to fine-tuning of IRS2 expression and is likely to be supplementary to the already known factors regulating IRS2 expression. Thereby, our findings could support the discovery of new diagnostic and therapeutic strategies for type 2 diabetes. Graphical abstract.

Dataset Information

SteatoNet: the first integrated human metabolic model with multi-layered regulation to investigate liver-associated pathologies.

Publications

SteatoNet: the first integrated human metabolic model with multi-layered regulation to investigate liver-associated pathologies.

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