(633a) A Combined Analysis of Metabolic Networks and Transcriptomic Data to Predict the Impacts of Copper Deficiency on the Liver Metabolism

Metabolic dysfunction-associated fatty liver disease is a widespread public health concern. While high-calorie intake and obesity are known risk factors for fatty liver disease, other contributors and modifiers remain characterized. Intriguingly, inadequate uptake or distribution of copper (Cu) leads to lipid and cholesterol metabolic disorders, and fatty liver disease and obesity dysregulate Cu levels. Cu is a vital mineral required for enzymes in several biological processes, including energy generation and redox balance; nevertheless, how Cu deficiency and toxicity induce metabolic disorders and the underlying mechanisms remain to be elucidated. For these reasons, identifying the metabolic pathways affected by Cu bioavailability to display macronutrient metabolic disorder followed by fatty liver disease is an important challenge. To fill in this knowledge gap, we aim to predict the impacts of Cu deficiency on metabolism in the liver, a central organ for Cu homeostasis and macronutrient metabolism, via a combined analysis of metabolic networks and transcriptomic data. We first experimentally characterized alterations in gene expression by Cu deficiency based on a comparative analysis of transcriptomic data collected from control and Cu-deficient mouse liver. Cu deficiency, specifically in hepatocytes of mice, was induced by knocking out the Ctr1 gene that encodes a high-affinity Cu importer. We subsequently performed flux balance analysis using a genome-scale hepatocyte network by constraining the actions of Cu-containing enzymes (cytochrome oxidase and superoxide dismutase) singly and in combination. This analysis predicted the changes in mitochondrial net activity from the Ctr1 gene knockout liver. Moreover, our data indicate that Cu deficiency leads to the regulation of several lipid metabolic pathways. The simulation shows an increase in a series of reactions for fatty acyl-CoA, acetyl-CoA, cholesterol, and steroid hormone synthesis; on the other hand, citric acid cycle activity is decreased with a less acetyl-CoA synthesis from citrate. These results identify metabolic pathways promoting lipid synthesis under Cu deficiency. For validation, we compare predicted flux distributions with transcriptomic data. Next, we integrate transcriptomic data into metabolic networks. As a follow-up step, we will examine the impacts of Cu deficiency on liver metabolism under different diet conditions. The results are expected to shed new light on the roles of Cu homeostasis in liver functions, fat metabolism, and the mechanisms behind fatty liver disease, which provides the fundamental knowledge needed for better treatment or prevention of metabolic dysfunction and fatty liver disease.