Integrating Proteomic, Lipidomic and Metabolomic Data to Construct a Global Metabolic Network of Lethal Ventricular Tachyarrhythmias (LVTA) Induced by Aconitine.

Lethal ventricular tachyarrhythmias (LVTA)-related sudden cardiac death (SCD) is one of the major causes of death worldwide. However, the mechanisms underlying LVTA induced by myocardial ion channel diseases (MICDs) are not yet fully understood. Here, we produced an LVTA rat model induced by aconitine, to mimic MICDs-elicited LVTA, and constructed a global pathway network via integrating proteomic and lipidomic data, and our previously published metabolomic data. Results showed that both proteome and lipidome were disturbed during the LVTA process. Most of the differentially expressed proteins and lipid species were correlated. Proteomic data indicated disturbance of energy metabolism (e.g. fatty acid beta-oxidation and the tricarboxylic acid cycle) and activation of the protein kinase C and nicotinamide adenine dinucleotide phosphate (NAPDH) oxidase pathway; these alterations led to lowered ATP and elevated ROS, respectively. Altered levels of the Ca2+ handling proteins suggested aberrant intracellular Ca2+ homeostasis, which might also be secondary to the shortage of ATP and oxidative stress. Significantly, the disrupted pathways implied by proteomic data were largely confirmed by lipidomic and metabolomic data. Collectively, we have constructed a metabolic pathway network of aconitine-induced LVTA using a multi-omics strategy, which confers great promise for the deeper interpretation of the mechanisms underlying LVTA. Significance: In this study, we integrated proteomics, lipidomics and metabolomics to explore the pathophysiological processes of LVTA induced by aconitine. It is innovative to try to integrate these three omics in a study exploring the relative mechanisms. Here, based on the DEPs and differentially abundant lipid species (DALPs) between the LVTA groups and the controls, and the different metabolites discovered previously from the same model, we have successfully constructed a global metabolic network. Taken together, the multi-omics integration strategies used in this study show the potential for a new interpretation of the pathophysiological processes of LVTA induced by different conditions and open the possibility to explore deeper and broader mechanisms of other diseases.