title: Multi-tissue computational modeling analyzes pathophysiology of type 2 diabetes in MKR mice.
abstract: Computational models using metabolic reconstructions for in silico simulation of metabolic disorders such as type 2 diabetes mellitus (T2DM) can provide a better understanding of disease pathophysiology and avoid high experimentation costs. There is a limited amount of computational work, using metabolic reconstructions, performed in this field for the better understanding of T2DM. In this study, a new algorithm for generating tissue-specific metabolic models is presented, along with the resulting multi-confidence level (MCL) multi-tissue model. The effect of T2DM on liver, muscle, and fat in MKR mice was first studied by microarray analysis and subsequently the changes in gene expression of frank T2DM MKR mice versus healthy mice were applied to the multi-tissue model to test the effect. Using the first multi-tissue genome-scale model of all metabolic pathways in T2DM, we found out that branched-chain amino acids' degradation and fatty acids oxidation pathway is downregulated in T2DM MKR mice. Microarray data showed low expression of genes in MKR mice versus healthy mice in the degradation of branched-chain amino acids and fatty-acid oxidation pathways. In addition, the flux balance analysis using the MCL multi-tissue model showed that the degradation pathways of branched-chain amino acid and fatty acid oxidation were significantly downregulated in MKR mice versus healthy mice. Validation of the model was performed using data derived from the literature regarding T2DM. Microarray data was used in conjunction with the model to predict fluxes of various other metabolic pathways in the T2DM mouse model and alterations in a number of pathways were detected. The Type 2 Diabetes MCL multi-tissue model may explain the high level of branched-chain amino acids and free fatty acids in plasma of Type 2 Diabetic subjects from a metabolic fluxes perspective.
authors.affiliation: Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America; Biotechnology Core Laboratory, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Health, Bethesda, Maryland, United States of America.
authors.forename: Amit
authors.initials: A
authors.lastname: Kumar
authors.affiliation: Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.
authors.forename: Thomas
authors.initials: T
authors.lastname: Harrelson
authors.affiliation: Department of Biology, Brigham Young University, Provo, Utah, United States of America.
authors.forename: Nathan E
authors.initials: NE
authors.lastname: Lewis
authors.affiliation: Division of Endocrinology, Diabetes and Bone Disease and the Diabetes, Obesity, Metabolism Institute, Icahn School of Medicine at Sinai, New York, New York, United States of America.
authors.forename: Emily J
authors.initials: EJ
authors.lastname: Gallagher
authors.affiliation: Division of Endocrinology, Diabetes and Bone Disease and the Diabetes, Obesity, Metabolism Institute, Icahn School of Medicine at Sinai, New York, New York, United States of America.
authors.forename: Derek
authors.initials: D
authors.lastname: LeRoith
authors.affiliation: Biotechnology Core Laboratory, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Health, Bethesda, Maryland, United States of America.
authors.forename: Joseph
authors.initials: J
authors.lastname: Shiloach
authors.affiliation: Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Betenbaugh
mesh_terms: D000273:Adipose Tissue / Q000378:metabolism; D000465:Algorithms; D000596:Amino Acids / Q000378:metabolism; D000818:Animals; D003198:Computer Simulation; D003924:Diabetes Mellitus, Type 2 / Q000503:physiopathology*; D004195:Disease Models, Animal; D005227:Fatty Acids / Q000378:metabolism; D005786:Gene Expression Regulation / Q000502:physiology*; D008099:Liver / Q000378:metabolism; D064688:Metabolic Flux Analysis; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D051379:Mice; D008822:Mice, Transgenic; D046228:Microarray Analysis; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000378:metabolism; D020125:Mutation, Missense / Q000235:genetics; D017526:Receptor, IGF Type 1; D017451:Receptors, Somatomedin / Q000235:genetics*
chemical_list: D000596:Amino Acids; D005227:Fatty Acids; C000597236:IGF1R protein, human; D017451:Receptors, Somatomedin; D017526:Receptor, IGF Type 1