Predicting Shifts in Cardiomyocyte Metabolism during Heart Failure

Contextualizing the human metabolic network to model the metabolic states of specific tissue- and cell-types has generated novel hypotheses and tremendous insight into the role of metabolism in disease. Here, we use a recently published human GENRE, iHsa, to model cardiomyocyte metabolism through the integration of proteomics data available in the Human Protein Atlas (HPA). We validate the cardiomyocyte model through completion of pre-defined cardiomyocyte relevant tasks as well as evaluation of general tasks published with the original human metabolic network reconstruction. Both sets of tasks have provided a starting point for manual curation of the cardiomyocyte model. Next, we use the cardiomyocyte model to identify reactions, pathways, and genes differentially affected in heart failure through the utilization of different carbon sources for ATP production, an established phenotype in heart failure. The cardiomyocyte model demonstrates enrichment for carbon-source specific pathways, demonstrating the ability of the model to connect genotype to phenotype using the phenotypic changes observed in carbon substrate utilization that occur in heart failure.