Inhibition of BCAT1-mediated cytosolic leucine metabolism regulates Th17 responses via the mTORC1-HIF1α pathway.

Branched-chain amino acids (BCAAs), particularly leucine, are indispensable AAs for immune regulation through metabolic rewiring. However, the molecular mechanism underlying this phenomenon remains unclear. Our investigation revealed that T-cell receptor (TCR)-activated human CD4+ T cells increase the expression of BCAT1, a cytosolic enzyme responsible for BCAA catabolism, and SLC7A5, a major BCAA transporter. This upregulation facilitates increased leucine influx and catabolism, which are particularly crucial for Th17 responses. Activated CD4+ T cells induce an alternative pathway of cytosolic leucine catabolism, generating a pivotal metabolite, ß-hydroxy ß-methylbutyric acid (HMB), by acting on BCAT1 and 4-hydroxyphenylpyruvate dioxygenase (HPD)/HPD-like protein (HPDL). Inhibition of BCAT1-mediated cytosolic leucine metabolism, either with BCAT1 inhibitor 2 (Bi2) or through BCAT1, HPD, or HPDL silencing using shRNA, attenuates IL-17 production, whereas HMB supplementation abrogates this effect. Mechanistically, HMB contributes to the regulation of the mTORC1-HIF1α pathway, a major signaling pathway for IL-17 production, by increasing the mRNA expression of HIF1α. This finding was corroborated by the observation that treatment with L-ß-homoleucine (LßhL), a leucine analog and competitive inhibitor of BCAT1, decreased IL-17 production by TCR-activated CD4+ T cells. In an in vivo experimental autoimmune encephalomyelitis (EAE) model, blockade of BCAT1-mediated leucine catabolism, either through a BCAT1 inhibitor or LßhL treatment, mitigated EAE severity by decreasing HIF1α expression and IL-17 production in spinal cord mononuclear cells. Our findings elucidate the role of BCAT1-mediated cytoplasmic leucine catabolism in modulating IL-17 production via HMB-mediated regulation of mTORC1-HIF1α, providing insights into its relevance to inflammatory conditions.

Differences in Brain Metabolite Profiles Between Normothermia and Hypothermia.

BACKGROUND: This study evaluated the difference in brain metabolite profiles between normothermia and hypothermia reaching 25°C in humans in vivo. METHODS: Thirteen patients who underwent thoracic aorta surgery under moderate hypothermia were prospectively enrolled. Plasma samples were collected simultaneously from the arteries and veins to estimate metabolite uptake or release. Targeted metabolomics based on liquid chromatographic mass spectrometry and direct flow injection were performed, and changes in the profiles of respective metabolites from normothermia to hypothermia were compared. The ratios of metabolite concentrations in venous blood samples to those in arterial blood samples (V/A ratios) were calculated, and log2 transformation of the ratios [log2(V/A)] was performed for comparison between the temperature groups. RESULTS: Targeted metabolomics were performed for 140 metabolites, including 20 amino acids, 13 biogenic amines, 10 acylcarnitines, 82 glycerophospholipids, 14 sphingomyelins, and 1 hexose. Of the 140 metabolites analyzed, 137 metabolites were released from the brain in normothermia, and the release of 132 of these 137 metabolites was decreased in hypothermia. Two metabolites (dopamine and hexose) showed constant release from the brain in hypothermia, and 3 metabolites (2 glycophospholipids and 1 sphingomyelin) showed conversion from release to uptake in hypothermia. Glutamic acid demonstrated a distinct brain metabolism in that it was taken up by the brain in normothermia, and the uptake was increased in hypothermia. CONCLUSION: Targeted metabolomics demonstrated various degrees of changes in the release of metabolites by the hypothermic brain. The release of most metabolites was decreased in hypothermia, whereas glutamic acid showed a distinct brain metabolism.

Complex influences of gut microbiome metabolism on various drug responses.

The gut microbiome closely interacts with the host, and it has a major influence on drug response. Many studies have reported the possible microbial influences on drugs and the possible influences of drugs on the microbiome. This knowledge has led to a better understanding of intra- and inter-individual variabilities in clinical pharmacology. For a more precise understanding of the complex correlation between the microbiome and drugs, in this review, we summarized the current knowledge on the interactions between the gut microbiome and drug response. Moreover, we suggest gut microbiome-derived metabolites as possible modulators of drug response and recommend metabolomics as a powerful tool to achieve such understanding.