Abstract
Triglyceride accumulation is associated with obesity and type 2 diabetes. Genetic disruption of diacylglycerol acyltransferase 1 (DGAT1), which catalyzes the final reaction of triglyceride synthesis, confers dramatic resistance to high-fat diet induced obesity. Hence, DGAT1 is considered a potential therapeutic target for treating obesity and related metabolic disorders. However, the molecular events shaping the mechanism of action of DGAT1 pharmacological inhibition have not been fully explored yet. Here, we investigate the metabolic molecular mechanisms induced in response to pharmacological inhibition of DGAT1 using a recently developed computational systems biology approach, the Causal Reasoning Engine (CRE). The CRE algorithm utilizes microarray transcriptomic data and causal statements derived from the biomedical literature to infer upstream molecular events driving these transcriptional changes. The inferred upstream events (also called hypotheses) are aggregated into biological models using a set of analytical tools that allow for evaluation and integration of the hypotheses in context of their supporting evidence. In comparison to gene ontology enrichment analysis which pointed to high-level changes in metabolic processes, the CRE results provide detailed molecular hypotheses to explain the measured transcriptional changes. CRE analysis of gene expression changes in high fat habituated rats treated with a potent and selective DGAT1 inhibitor demonstrate that the majority of transcriptomic changes support a metabolic network indicative of reversal of high fat diet effects that includes a number of molecular hypotheses such as PPARG, HNF4A and SREBPs. Finally, the CRE-generated molecular hypotheses from DGAT1 inhibitor treated rats were found to capture the major molecular characteristics of DGAT1 deficient mice, supporting a phenotype of decreased lipid and increased insulin sensitivity.
Highlights
Triacylglycerol is a highly efficient energy storage form critical for surviving periods of starvation and extended physical activity
The objective of this study was to employ a novel computational platform to gain mechanistic insight into the molecular changes induced by pharmacological inhibition of diacylglycerol acyltransferase 1 (DGAT1)
Our analysis allows us to postulate the molecular network conferring these metabolic benefits to better understand the mechanism of action for pharmacological inhibition of DGAT1
Summary
Triacylglycerol is a highly efficient energy storage form critical for surviving periods of starvation and extended physical activity. Many industrialized societies maintain a diet rich in fat and carbohydrates, and a sedentary lifestyle leading to the excess storage of triglyceride in tissues. Diacylglycerol Acyltransferase (DGAT) enzymes catalyze the final step in the synthesis of triacylglycerol from diacylglycerol (DAG) and fatty acyl-coA making them attractive targets for reducing triglyceride storage [2]. Two separate genes encode for the DGAT1 and DGAT2 enzymes [3]. DGAT1 knock out (-/-) mice are lean, resistant to diet induced obesity and have increased insulin sensitivity, while the DGAT2 (-/-) genotype is lethal [4,5]. Out of a broad panel of human tissues DGAT1 was most abundant in the small intestine [2] We have confirmed these findings in human, rat and mouse tissues with gene chip profiling and RT-qPCR (data not shown). We sought to investigate the molecular changes occurring in the small intestine with pharmacological inhibition of DGAT1
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