A Robust, Integrated Platform for Comprehensive Analyses of Acyl-Coenzyme As and Acyl-Carnitines Revealed Chain Length-Dependent Disparity in Fatty Acyl Metabolic Fates Across Drosophila Development
Sin Man Lam, Tianxing Zhou, Jie Li, Shaohua Zhang, Gek Huey Chua, Bowen Li, Guanghou Shui
Acyl-Coenzyme A thioesters (acyl-CoAs) denote a key class of intermediary metabolites that lies at the hub of major metabolic pathways. The great diversity in polarity between short- and long-chain acyl-CoAs makes it technically challenging to cover an inclusive range of acyl-CoAs within a single method. Levels of acyl-carnitines, which function to convey fatty acyls into mitochondria matrix for β-oxidation, indicate the efficiency of mitochondrial import and utilization of corresponding acyl-CoAs. Herein, we report a robust, integrated platform to allow simultaneous quantitation of endogenous acyl-CoAs and acyl-carnitines. Using this method, we monitored changes in intermediary lipid profiles across Drosophila development under control (ND) and high-fat diet (HFD). We observed specific accumulations of medium-chain (C8-C12) and long-chain (≥C16) acyl-carnitines distinct to L3 larval and pupal stages, respectively. These observations suggested development-specific, chain length-dependent disparity in metabolic fates of acyl-CoAs across Drosophila development, which was validated by deploying the same platform to monitor isotope incorporation introduced from labelled 12:0 and 16:0 fatty acids into extra- and intra-mitochondrial acyl-CoA pools. We found that pupal mitochondria preferentially import and oxidise C12:0-CoAs (accumulated as C12:0-carnitines in L3 stage) over C16:0-CoAs. Preferential oxidation of medium-chain acyl-CoAs limits mitochondrial utilization of long-chain acyl-CoAs (C16-C18), leading to pupal-specific accumulation of long-chain acyl-carnitines mediated by enhanced CPT1-6A activity. HFD skewed C16:0-CoAs towards catabolism over anabolism in pupa, thereby adversely affecting overall development. Our developed platform emphasizes the importance of integrating biological knowledge in the design of pathway-oriented platforms to derive maximal physiological insights from analysis of complex biological systems.