Dataset Information

ZucAt: multi-compartment metabolic model of growing Arabidopsis thaliana

ABSTRACT: ZucAt: multi-compartment metabolic model of growing Arabidopsis thaliana

SUBMITTER: Maksim Zakhartsev

PROVIDER: 186 | FAIRDOMHub | 2016-06-04

REPOSITORIES: FAIRDOMHub

ACCESS DATA

Similar Datasets

Project description:Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, and can rapidly progress to non-alcoholic steatohepatitis (NASH). Accurate preclinical models and robust methodologies need to be established to understand the underlying metabolic mechanisms and develop treatment strategies. Based on our meta-analysis of currently available data on several mouse models, we hypothesized a diet- and chemical-induced NASH model closely resembles metabolic alteration in human. We developed an already established WD+CCl4-induced NASH model. We developed and performed transcriptomics driven metabolic pathway analysis (TDMPA) using differentially expressed genes in mouse NASH liver compared to control. We compared the altered metabolic pathways and enzymatic reactions to human NASH. We performed functional assays and lipidomics to confirm our findings related to metabolic alterations. Numerous metabolic pathways were altered in human NASH and mouse model. De novo triglyceride biosynthesis, fatty acid beta-oxidation, bile acid biosynthesis, cholesterol metabolism, and oxidative phosphorylation were the most influenced pathways. We confirmed significant reduction in mitochondrial functions and bioenergetics in NASH model, and in acylcarnitines. We identified a wide range of lipid species within the most perturbed pathways predicted by TDMPA. Triglycerides, phospholipids and bile acids were increased significantly in NASH, confirming our initial observations. We identified several metabolic pathways that typify NASH pathophysiology in human. By comparing human and mouse metabolic signatures, we evaluated metabolic resemblance of mouse model to human and its suitability for the study of the disease and potential usage for drug discovery and testing. We also presented TDMPA, a novel methodology to evaluate metabolic pathway alterations in metabolic disorders and a valuable tool for defining metabolic space to aid experimental design for lipidomics and metabolomics approaches.

Dataset Information

ZucAt: multi-compartment metabolic model of growing Arabidopsis thaliana

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets