Obesity and type 2 diabetes mellitus (T2DM) are the leading causes of cardiovascular morbidity and mortality. Although insulin resistance is believed to underlie these disorders, anecdotal evidence contradicts this common belief. Accordingly, obese patients with cardiovascular disease have better prognoses relative to leaner patients with the same diagnoses, whereas treatment of T2DM patients with thiazolidinedione, one of the popular insulin-sensitizer drugs, significantly increases the risk of heart failure. Using mice with skeletal musclespecific ablation of the insulin receptor gene (MIRKO), we addressed this paradox by demonstrating that insulin signaling in skeletal muscles specifically mediated cross talk with the heart, but not other metabolic tissues, to prevent cardiac dysfunction in response to metabolic stress. Despite severe hyperinsulinemia and aggregating obesity, MIRKO mice were protected from myocardial insulin resistance, mitochondrial dysfunction, and metabolic reprogramming in response to diet-induced obesity. Consequently, the MIRKO mice were also protected from myocardial inflammation, cardiomyopathy, and left ventricle dysfunction. Together, our findings suggest that insulin resistance in skeletal muscle functions as a double-edged sword in metabolic diseases.
Lipids exert dynamic biological functions which are determined both by their fatty acyl compositions and precise spatiotemporal distributions inside the cell. There are more than 1000 lipid species in a typical mammalian cell. However, it remains a daunting task to investigate any of these features in live cells for each of the more than 1000 lipid species. Here we resolved this issue by developing a de novo lipid labeling method for major lipid species, including glycerolipids, glycerophospholipids, and cholesterol esters by using a single fluorescent probe. The method not only allowed us to probe the precise subcellular distribution and trafficking of individual lipid species in live cells, but also uncovered some unexpected biological functions of previously reported lipid metabolic enzymes that were not possible by conventional biochemical methods. We envision that this method will become an indispensable tool for the functional analysis of individual lipid species and numerous lipid metabolic enzymes and transporters in live cells.
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