👤 Andrew M Cowie

Branched-chain α-keto acids (BCKAs) are catabolites of branched-chain amino acids (BCAAs). Intracellular BCKAs are cleared by branched-chain ketoacid dehydrogenase (BCKDH), which is sensitive to inhibitory phosphorylation by BCKD kinase (BCKDK). Accumulation of BCKAs is an indicator of defective BCAA catabolism and has been correlated with glucose intolerance and cardiac dysfunction. However, it is unclear whether BCKAs directly alter insulin signaling and function in the skeletal and cardiac muscle cell. Furthermore, the role of excess fatty acids (FAs) in perturbing BCAA catabolism and BCKA availability merits investigation. By using immunoblotting and ultra-performance liquid chromatography MS/MS to analyze the hearts of fasted mice, we observed decreased BCAA-catabolizing enzyme expression and increased circulating BCKAs, but not BCAAs. In mice subjected to diet-induced obesity (DIO), we observed similar increases in circulating BCKAs with concomitant changes in BCAA-catabolizing enzyme expression only in the skeletal muscle. Effects of DIO were recapitulated by simulating lipotoxicity in skeletal muscle cells treated with saturated FA, palmitate. Exposure of muscle cells to high concentrations of BCKAs resulted in inhibition of insulin-induced AKT phosphorylation, decreased glucose uptake, and mitochondrial oxygen consumption. Altering intracellular clearance of BCKAs by genetic modulation of BCKDK and BCKDHA expression showed similar effects on AKT phosphorylation. BCKAs increased protein translation and mTORC1 activation. Pretreating cells with mTORC1 inhibitor rapamycin restored BCKA's effect on insulin-induced AKT phosphorylation. This study provides evidence for FA-mediated regulation of BCAA-catabolizing enzymes and BCKA content and highlights the biological role of BCKAs in regulating muscle insulin signaling and function. Show less

The herbicide linuron (LIN) is an endocrine disruptor with an anti-androgenic mode of action. The objectives of this study were to (1) improve knowledge of androgen and anti-androgen signaling in the teleostean ovary and to (2) assess the ability of gene networks and machine learning to classify LIN as an anti-androgen using transcriptomic data. Ovarian explants from vitellogenic fathead minnows (FHMs) were exposed to three concentrations of either 5α-dihydrotestosterone (DHT), flutamide (FLUT), or LIN for 12h. Ovaries exposed to DHT showed a significant increase in 17β-estradiol (E2) production while FLUT and LIN had no effect on E2. To improve understanding of androgen receptor signaling in the ovary, a reciprocal gene expression network was constructed for DHT and FLUT using pathway analysis and these data suggested that steroid metabolism, translation, and DNA replication are processes regulated through AR signaling in the ovary. Sub-network enrichment analysis revealed that FLUT and LIN shared more regulated gene networks in common compared to DHT. Using transcriptomic datasets from different fish species, machine learning algorithms classified LIN successfully with other anti-androgens. This study advances knowledge regarding molecular signaling cascades in the ovary that are responsive to androgens and anti-androgens and provides proof of concept that gene network analysis and machine learning can classify priority chemicals using experimental transcriptomic data collected from different fish species. Show less