TOTAL LIPID EXTRACTION FROM ZEBRAFISH MODELS TO ASSESS DIET AND EXERCISE-INDUCED LIPIDOMIC CHANGES USING LC-MS AND CHEMOMETRICS

Obesity is a global health challenge which is associated with a range of clinical conditions. Understanding metabolism at the molecular level is essential for the prevention of obesity-related diseases. Lipidomic analyses provide valuable insights into the pathophysiological alterations occurring in living organisms. In this regard, Zebrafish (Danio rerio) has emerged as a valuable model for studying lipid profile changes owing to its genetic similarity to humans. This study aimed to evaluate lipid changes in zebrafish samples, providing insights into alterations related to different diets and exercise conditions via liquid chromatography coupled to mass spectrometry (LC-MS) analyses and chemometrics. Zebrafish subjects were categorized into four groups: normal-fat diet - NFD, normal-fat diet submitted to exercise - NFD-E, high-fat diet- HFD, and high-fat diet submitted to exercise - HFD-E. The total lipid extraction from zebrafish was performed using a liquid-liquid microextraction adapted from the Bligh & Dyer protocol, involving homogenization of the fish body in methanol (100 mg.mL^-1). 500 μL of chloroform, 200 μL of water, 250 μL of methanol and 250 μL of zebrafish homogenate were vortexed for 1 min. The organic phase was collected, evaporated and resuspended in methanol. Chromatographic separation was performed using a C18 column at 60 ºC, with the injection of 5 µL of the sample at a mobile phase flow rate of 0.300 mL.min^-1 in gradient elution mode. MS analyses were conducted in both positive and negative ion mode using electrospray ion source. LC-MS data revealed the metabolic profiles for each experimental condition showcasing that Bligh & Dyer organic phase yields a sample rich in mid to non-polar lipid compounds. Once LC-MS data generates thousands of variables, chemometric tools are essential for identifying significant variations induced by dietary and exercise conditions in zebrafish. Partial least squares discriminant analysis with ordered predictors selection for discriminant analysis classified each sample with 100% accuracy. Volcano plots were utilized alongside multivariate analyses to identify variables that were statistically significant. Important lipids for classification of each zebrafish group were putatively annotated, providing insights into lipid metabolism changes in different diet and exercise regimens. Findings reveal distinct lipid metabolic responses between sedentary and exercised groups under high-fat diets, highlighting the role of specific lipid classes, such as fatty acids and ceramides, in obesity-associated pathways and offering insights into potential metabolic targets for obesity management.