RESUMEN
Niemann-Pick disease Type C (NPC) is a lysosomal storage disorder caused by mutation of the NPC1/NPC2 genes, which ultimately results in the accumulation of unesterified cholesterol (UEC) in lysosomes, thereby inducing symptoms such as progressive neurodegeneration and hepatosplenomegaly. This study determines the effects of 6-O-α-maltosyl-ß cyclodextrin (Mal-ßCD) on lipid levels and synthesis in Npc1-deficient (Npc1-KO cells) and vehicle CHO cells. Compared to vehicle cells, Npc1-KO cells exhibited high level of UEC, and low levels of esterified cholesterols (ECs) and long-chain fatty acids (LCFAs). The difference in lipid levels between Npc1-KO and CHO cells was largely ameliorated by Mal-ßCD administration. Moreover, the effects of Mal-ßCD were reproduced in the lysosomes prepared from Npc1-KO cells. Stable isotope tracer analysis with extracellular addition of D4-deuterated palmitic acid (D4-PA) to Npc1-KO cells increased the synthesis of D4-deuterated LCFAs (D4-LCFAs) and D4-deuterated ECs (D4-ECs) in a Mal-ßCD-dependent manner. Simultaneous addition of D6-deuterated UEC (D6-UEC) and D4-PA promoted the Mal-ßCD-dependent synthesis of D6-/D4-ECs, consisting of D6-UEC and D4-PA, D4-deuterated stearic acid, or D4-deuterated myristic acid, in Npc1-KO cells. These results suggest that Mal-ßCD helps to maintain normal lipid metabolism by restoring balance among UEC, ECs, and LCFAs through acting on behalf of NPC1 in Npc1-KO cells and may therefore be useful in designing effective therapies for NPC.
Asunto(s)
Enfermedad de Niemann-Pick Tipo C , beta-Ciclodextrinas , Animales , Cricetinae , Humanos , Enfermedad de Niemann-Pick Tipo C/genética , Enfermedad de Niemann-Pick Tipo C/metabolismo , Cricetulus , Células CHO , Metabolismo de los Lípidos , beta-Ciclodextrinas/farmacología , Colesterol/metabolismo , Proteína Niemann-Pick C1/metabolismoRESUMEN
Macrophages reprogram their lipid metabolism in response to activation signals. However, a systems-level understanding of how different pro-inflammatory stimuli reshape the macrophage lipidome is lacking. Here, we use complementary "shotgun" and isotope tracer mass spectrometry approaches to define the changes in lipid biosynthesis, import, and composition of macrophages induced by various Toll-like receptors (TLRs) and inflammatory cytokines. "Shotgun" lipidomics data revealed that different TLRs and cytokines induce macrophages to acquire distinct lipidomes, indicating their specificity in reshaping lipid composition. Mechanistic studies showed that differential reprogramming of lipid composition is mediated by the opposing effects of MyD88- and TRIF-interferon-signaling pathways. Finally, we applied these insights to show that perturbing reprogramming of lipid composition can enhance inflammation and promote host defense to bacterial challenge. These studies provide a framework for understanding how inflammatory stimuli reprogram lipid composition of macrophages while providing a knowledge platform to exploit differential lipidomics to influence immunity.
Asunto(s)
Lipidómica , Macrófagos/metabolismo , Receptores Toll-Like/metabolismo , Animales , Línea Celular , Masculino , Ratones , Ratones Noqueados , Ratones Transgénicos , Transducción de SeñalRESUMEN
INTRODUCTION: Untargeted and targeted analyses are two classes of metabolic study. Both strategies have been advanced by high resolution mass spectrometers coupled with chromatography, which have the advantages of high mass sensitivity and accuracy. State-of-art methods for mass spectrometric data sets do not always quantify metabolites of interest in a targeted assay efficiently and accurately. OBJECTIVES: TarMet can quantify targeted metabolites as well as their isotopologues through a reactive and user-friendly graphical user interface. METHODS: TarMet accepts vendor-neutral data files (NetCDF, mzXML and mzML) as inputs. Then it extracts ion chromatograms, detects peak position and bounds and confirms the metabolites via the isotope patterns. It can integrate peak areas for all isotopologues automatically. RESULTS: TarMet detects more isotopologues and quantify them better than state-of-art methods, and it can process isotope tracer assay well. CONCLUSION: TarMet is a better tool for targeted metabolic and stable isotope tracer analyses.