Abstract

ObjectivesThe mechanistic Target of Rapamycin Complexes (mTORC1/mTORC2) are critical nodes for metabolism. We applied an HRMS-based untargeted metabolomics approach to determine the role of mTORC1/mTORC2 on the internal exposome in pancreatic cell line (β-TC6). mTORC1 is a nutrient-sensing network, while mTORC2 phosphorylates Akt on Ser473 and modulates energy metabolism, thus mTORC1/mTORC2 are targets for precision nutrition.MethodsWe used glucose-responsive, insulin-secreting, pancreatic beta-cell lines. mTORC1/mTORC2 were inhibited by RapaLink-1, a third-generation inhibitor encompassing rapamycin linked to an mTOR kinase inhibitor, or rapamycin, compared to the control. We compared the HRMS-based untargeted metabolomics (LC-MS/MS) between groups to identify the differentially expressed metabolites, predictive metabolic networks, and systems biology pathways. We employed the XCMS online cloud-based bioinformatics platform to link mTOR-regulated metabolites to biological pathways using the python mummichog algorithm. Statistical significance (P < 0.001) was assessed by ANOVA followed by adhoc unpaired t-test.ResultsPCA dimension reduction and cloud plot clustering machine learning showed differential expression of metabolites between RapaLink and rapamycin-treated pancreatic beta cells. RapaLink significantly increased aminobutyrate (P < 0.001), D-glucose (p = 0.02), and O-phosphoryl ethanolamine (p = 0.003), compared to rapamycin. RapaLink also decreased glycine level (P < 0.000001) compared to the control. While both RapaLink and rapamycin decreased alanine (p = 0.003), L-asparagine (p = 0.01), L- aspartate (p < 0.001), taurine (p = 0.003), and uridine monophosphate (p = 0.004) compared to the control. The predictive metabolic pathways affected included malate-aspartate shuttle, adenosine nucleotide degradation, and glucose degradation.ConclusionsmTORC1 and mTORC2 have differential effects on glucose, bile acids, short-chain fatty acids, nucleotides, and amino acid metabolism, and thus could serve as targets for precision nutrition in pancreatic diseases and type 2 diabetes interventions.Funding SourcesFunded by the City University of New York, GC Advanced Science Research Center Seed Grant Award # 95,649–00. XCMS online is a cloud-based open-source bioinformatics platform developed by the Scripps Institute.

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