Severe acute respiratory syndrome-coronavirus (SARS-CoV) and SARS-like coronavirus are a potential threat to global health. However, reviews of the long-term effects of clinical treatments in SARS patients are lacking. Here a total of 25 recovered SARS patients were recruited 12 years after infection. Clinical questionnaire responses and examination findings indicated that the patients had experienced various diseases, including lung susceptibility to infections, tumors, cardiovascular disorders, and abnormal glucose metabolism. As compared to healthy controls, metabolomic analyses identified significant differences in the serum metabolomes of SARS survivors. The most significant metabolic disruptions were the comprehensive increase of phosphatidylinositol and lysophospha tidylinositol levels in recovered SARS patients, which coincided with the effect of methylprednisolone administration investigated further in the steroid treated non-SARS patients with severe pneumonia. These results suggested that high-dose pulses of methylprednisolone might cause long-term systemic damage associated with serum metabolic alterations. The present study provided information for an improved understanding of coronavirus-associated pathologies, which might permit further optimization of clinical treatments.
A reversed-phase liquid chromatography-linear ion trap-Fourier transform ion cyclotron resonance-mass spectrometric method was developed for the profiling of lipids in human and mouse plasma. With the use of a fused-core C 8 column and a binary gradient, more than 160 lipids belonging to eight different classes were detected in a single LC-MS run. The method was fully validated and the analytical characteristics such as linearity ( R (2), 0.994-1.000), limit of detection (0.08-1.28 microg/mL plasma), repeatability (RSD, 2.7-7.9%) and intermediate precision (RSD, 2.7-15.6%) were satisfactory. The method was successfully applied to p53 mutant mice plasma for studying some phenotypic effects of p53 expression.
Major depressive disorder (MDD) is a debilitating mental disease with a pronounced impact on the quality of life of many people; however, it is still difficult to diagnose MDD accurately. In this study, a nontargeted metabolomics approach based on ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was used to find the differential metabolites in plasma samples from patients with MDD and healthy controls. Furthermore, a validation analysis focusing on the differential metabolites was performed in another batch of samples using a targeted approach based on the dynamic multiple reactions monitoring method. Levels of acyl carnitines, ether lipids, and tryptophan pronouncedly decreased, whereas LPCs, LPEs, and PEs markedly increased in MDD subjects as compared with the healthy controls. Disturbed pathways, mainly located in acyl carnitine metabolism, lipid metabolism, and tryptophan metabolism, were clearly brought to light in MDD subjects. The binary logistic regression result showed that carnitine C10:1, PE-O 36:5, LPE 18:1 sn-2, and tryptophan can be used as a combinational biomarker to distinguish not only moderate but also severe MDD from healthy control with good sensitivity and specificity. Our findings, on one hand, provide critical insight into the pathological mechanism of MDD and, on the other hand, supply a combinational biomarker to aid the diagnosis of MDD in clinical usage.
Lipid coverage is crucial in comprehensive lipidomics studies challenged by high diversity in lipid structures and wide dynamic range in lipid levels. Current state-of-the-art lipidomics technologies are mostly based on mass spectrometry (MS), including direct-infusion MS, chromatography-MS, and matrix-assisted laser desorption ionization (MALDI) imaging MS, each with its pros and cons. Due to the need or favorability for measurement of isomers and isobars, chromatography-MS is preferable for lipid profiling. The ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS)-based nontargeted lipidomics approach and UHPLC-tandem MS (UHPLC-MS/MS)-based targeted approach are two representative methodological platforms for chromatography-MS. In the present study, we developed a high coverage pseudotargeted lipidomics method combining the advantages of nontargeted and targeted lipidomics approaches. The high coverage of lipids was achieved by integration of the detected lipids derived from nontargeted UHPLC-HRMS lipidomics analysis of multiple matrices (e.g., plasma, cell, and tissue) and the predicted lipids speculated on the basis of the structure and chromatographic retention behavior of the known lipids. A total of 3377 targeted lipid ion pairs with over 7000 lipid molecular structures were defined. The pseudotargeted lipidomics method was well validated with satisfactory analytical characteristics in terms of linearity, precision, reproducibility, and recovery for lipidomics profiling. Importantly, it showed better repeatability and higher coverage of lipids than the nontargeted lipidomics method. The applicability of the developed pseudotargeted lipidomics method was testified in defining differential lipids related to diabetes. We believe that comprehensive lipidomics studies will benefit from the developed high coverage pseudotargeted lipidomics approach.
Major depressive disorder (MDD) is a grave debilitating mental disease with a high incidence and severely impairs quality of life. Therefore, its physiopathological basis study and diagnostic biomarker discovery are extremely valuable. In this study, a non-targeted lipidomics strategy using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was performed to reveal differential lipids between MDD (n = 60) and healthy controls (HCs, n = 60). Validation of changed lipid species was performed in an independent batch including 75 MDD and 52 HC using the same lipidomic method. Pronouncedly changed lipid species in MDD were discovered, which mainly were lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI), 1-O-alkyl-2-acyl-PE (PE O), 1-O-alkyl-2-acyl-PC (PC O), sphingomyelin (SM), diacylglycerol (DG), and triacylglycerol (TG). Among these lipid species, LPC, LPE, PC, PE, PI, TG, etc. remarkably increased in MDD and showed pronounced positive relationships with depression severity, while 1-O-alkyl-2-acyl-PE and SM with odd summed carbon number significantly decreased in MDD and demonstrated negative relationships with depression severity. A combinational lipid panel including LPE 20:4, PC 34:1, PI 40:4, SM 39:1, 2, and TG 44:2 was defined as potential diagnostic biomarker with a good sensitivity and specificity for distinguishing MDD from HCs. Our study brings insights into lipid metabolism disorder in MDD and provides a specific potential biomarker for MDD diagnose.
Metabolic reprogramming is frequently identified in hepatocellular carcinoma (HCC), which is the most common type of liver malignancy. The reprogrammed cellular metabolisms promote tumor cell survival, proliferation, angiogenesis, and metastasis. However, the mechanisms of this process remain unclear in HCC. The global nontargeted metabolic study in 69 paired hepatic carcinomas and adjacent tissue specimens was performed using capillary electrophoresis-time of flight mass spectrometry-based approach. Key findings were validated by targeted metabolomic approach. Biological studies were also performed to investigate the role of proline biosynthesis in HCC pathogenesis. Proline metabolism was markedly changed in HCC tumor tissue, characterized with accelerated consumption of proline and accumulation of hydroxyproline, which significantly correlated with α-fetoprotein levels and poor prognosis in HCC. In addition, we found that hydroxyproline promoted hypoxia- and HIF-dependent phenotype in HCC. Moreover, we demonstrated that hypoxia activated proline biosynthesis via upregulation of , subsequently leading to accumulation of hydroxyproline via attenuated activity. More importantly, we showed that glutamine, proline, and hydroxyproline metabolic axis supported HCC cell survival through modulating HIF1α stability in response to hypoxia. Finally, inhibition of proline biosynthesis significantly enhanced cytotoxicity of sorafenib and Our results demonstrate that hypoxic microenvironment activates proline metabolism, resulting in accumulation of hydroxyproline that promotes HCC tumor progression and sorafenib resistance through modulating HIF1α. These findings provide the proof of concept for targeting proline metabolism as a potential therapeutic strategy for HCC. .
Mutations in isocitrate dehydrogenase (IDH) 1 are high-frequency events in low-grade glioma and secondary glioblastoma, and IDH1 mutant gliomas are vulnerable to interventions. Metabolic reprogramming is a hallmark of cancer. In this study, comprehensive metabolism investigation of clinical IDH1 mutant glioma specimens was performed to explore its specific metabolic reprogramming in real microenvironment. Massive metabolic alterations from glycolysis to lipid metabolism were identified in the IDH1 mutant glioma tissue when compared to IDH1 wild-type glioma. Of note, tricarboxylic acid (TCA) cycle intermediates were in similar levels in both groups, with more pyruvate found entering the TCA cycle in IDH1 mutant glioma. The pool of fatty acyl chains was also reduced, displayed as decreased triglycerides and sphingolipids, although membrane phosphatidyl lipids were not changed. The lower fatty acyl pool may be mediated by the lower protein expression levels of long-chain acyl-CoA synthetase 1 (ACSL1), ACSL4, and very long-chain acyl-CoA synthetase 3 (ACSVL3) in IDH1 mutant glioma. Lower ACSL1 was further found to contribute to the better survival of IDH1 mutant glioma patients based on the The Cancer Genome Atlas (TCGA) RNA sequencing data. Our research provides valuable insights into the tissue metabolism of human IDH1 mutant glioma and unravels new lipid-related targets.
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