Abstract
Mapping network analysis in cells and tissues can provide insights into metabolic adaptations to changes in external environment, pathological conditions, and nutrient deprivation. Here, we reconstructed a genome-scale metabolic network of the rat liver that will allow for exploration of systems-level physiology. The resulting in silico model (iRatLiver) contains 1,882 reactions, 1,448 metabolites, and 994 metabolic genes. We then used this model to characterize the response of the liver’s energy metabolism to a controlled perturbation in diet. Transcriptomics data were collected from the livers of Sprague Dawley rats at 4 or 14 days of being subjected to 15%, 30%, or 60% diet restriction. These data were integrated with the iRatLiver model to generate condition-specific metabolic models, allowing us to explore network differences under each condition. We observed different pathway usage between early and late time points. Network analysis identified several highly connected “hub” genes (Pklr, Hadha, Tkt, Pgm1, Tpi1, and Eno3) that showed differing trends between early and late time points. Taken together, our results suggest that the liver’s response varied with short- and long-term diet restriction. More broadly, we anticipate that the iRatLiver model can be exploited further to study metabolic changes in the liver under other conditions such as drug treatment, infection, and disease.
Highlights
Metabolic adaptation is critical for the ability of cells to maintain homeostasis following a physiological change
Because we are interested in studying human physiology, we used an existing GEnome-scale metabolic Models (GEMs) of the human liver[16] as a starting point for the homology-based reconstruction of rat liver metabolism; see Methods for details regarding the reconstruction process
We validated the iRatLiver model by comparing the predicted doubling time with literature values; the predicted doubling time of 16.3 hours was consistent with the reported doubling time of 16.9 hours of rat hepatocytes in cell culture[37]
Summary
Metabolic adaptation is critical for the ability of cells to maintain homeostasis following a physiological change. A later GEM, iHepatocytes[22,23], was used to predict serine deficiency in patients with non-alcoholic fatty liver disease and to identify genes that are potential therapeutic targets for treatment of non-alcoholic steatohepatitis[29] While these cell-specific models have been used to understand pathophysiology in humans, the limitations associated with perturbation experiments in humans have limited their utility in translation research. Organisms like Sprague Dawley rats (Rattus norvegicus) – small in size, easy to handle, high rate of reproduction, and similar physiology to humans – have been used as a primary model organism to study toxicology[30] and to model aspects of human physiology[30] Studying these diverse metabolic processes of the liver provides important www.nature.com/scientificreports/. Understanding the metabolic regulatory responses to such perturbations in various physiological models represents an important open area of research
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