In situ Metabolomics of Metabolic Reprogramming Involved in a Mouse Model of Type 2 Diabetic Kidney Disease.
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ABSTRACT:
SUBMITTER: Linnan B
PROVIDER: S-EPMC8670437 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Kidney cancer [or renal cell carcinoma (RCC)] is known as "the internist's tumor" because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel-Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburg effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Together, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC.
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Project description:Diabetic kidney disease and atherosclerotic disease are major causes of morbidity and mortality associated with type 2 diabetes (T2D), and diabetic kidney disease is a major cardiovascular risk factor. The black and tan, brachyury (BTBR) mouse strain with leptin deficiency (Lepob) has emerged as one of the best models of human diabetic kidney disease. However, no T2D mouse model of combined diabetic kidney disease and atherosclerosis exists. Our goal was to generate such a model. To this end, the low-density lipoprotein (LDL) receptor was targeted for degradation via inducible degrader of the LDL receptor (IDOL) overexpression, using liver-targeted adenoassociated virus serotype DJ/8 (AAV-DJ/8) in BTBR wild-type and BTBR Lepob mice. Liver-targeted IDOL-AAV-DJ/8 increased plasma LDL cholesterol compared with the control enhanced green fluorescent protein AAV-DJ/8. IDOL-induced dyslipidemia caused formation of atherosclerotic lesions of an intermediate stage, which contained both macrophages and smooth muscle cells. BTBR Lepob mice exhibited diabetic kidney disease. IDOL-induced dyslipidemia worsened albuminuria and glomerular macrophage accumulation but had no effect on mesangial expansion or podocyte numbers. Thus, by inducing hepatic degradation of the LDL receptor, we generated a T2D model of combined kidney disease and atherosclerosis. This model provides a new tool to study mechanisms, interactions, and treatment strategies of kidney disease and atherosclerosis in T2D.
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Project description:Detailed knowledge on tissue-specific metabolic reprogramming in diabetic nephropathy (DN) is vital for more accurate understanding the molecular pathological signature and developing novel therapeutic strategies. In the present study, a spatial-resolved metabolomics approach based on air flow-assisted desorption electrospray ionization (AFADESI) and matrix-assisted laser desorption ionization (MALDI) integrated mass spectrometry imaging (MSI) was proposed to investigate tissue-specific metabolic alterations in the kidneys of high-fat diet-fed and streptozotocin (STZ)-treated DN rats and the therapeutic effect of astragaloside IV, a potential anti-diabetic drug, against DN. As a result, a wide range of functional metabolites including sugars, amino acids, nucleotides and their derivatives, fatty acids, phospholipids, sphingolipids, glycerides, carnitine and its derivatives, vitamins, peptides, and metal ions associated with DN were identified and their unique distribution patterns in the rat kidney were visualized with high chemical specificity and high spatial resolution. These region-specific metabolic disturbances were ameliorated by repeated oral administration of astragaloside IV (100 mg/kg) for 12 weeks. This study provided more comprehensive and detailed information about the tissue-specific metabolic reprogramming and molecular pathological signature in the kidney of diabetic rats. These findings highlighted the promising potential of AFADESI and MALDI integrated MSI based metabolomics approach for application in metabolic kidney diseases.
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Project description:Background and purposeACE inhibitors (ACEIs) and AT1 receptor antagonists (ARBs) are first-line drugs that are believed to reduce the progression of end-stage renal disease in diabetic patients. Differences in the effects of ACEIs and ARBs are not well studied and the mechanisms responsible are not well understood.Experimental approachMale diabetic CD-1 mice were treated with ACEI, ARB, N-acetyl-seryl-aspartyl-lysyl-proline (AcSDKP), ACEI + AcSDKP, ARB + AcSDKP, glycolysis inhibitors or non-treatment. Moreover, prolyl oligopeptidase inhibitor (POPi)-injected male diabetic C57Bl6 mice were treated with ACEI, AcSDKP and ARB or non-treatment. Western blot and immunofluorescent staining were used to examine key enzymes and regulators of central metabolism.Key resultsThe antifibrotic action of ACEI imidapril is due to an AcSDKP-mediated antifibrotic mechanism, which reprograms the central metabolism including restoring SIRT3 protein and mitochondrial fatty acid oxidation and suppression of abnormal glucose metabolism in the diabetic kidney. Moreover, the POPi S17092 significantly blocked the AcSDKP synthesis, accelerated kidney fibrosis and disrupted the central metabolism. ACEI partly restored the kidney fibrosis and elevated the AcSDKP level, whereas the ARB (TA-606) did not show such effects in the POPi-injected mice. ACE inhibition and AcSDKP suppressed defective metabolism-linked mesenchymal transformations and reduced collagen-I and fibronectin accumulation in the diabetic kidneys.Conclusion and implicationsThe study envisages that AcSDKP is the endogenous antifibrotic mediator that controls the metabolic switch between glucose and fatty acid metabolism and that suppression of AcSDKP leads to disruption of kidney cell metabolism and activates mesenchymal transformations leading to severe fibrosis in the diabetic kidney.
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Project description:Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD) worldwide. SGLT2 inhibitors are clinically effective in halting DKD progression. However, the underlying mechanisms remain unclear. The serum and kidneys of mice with DKD were analyzed using liquid chromatography with tandem mass spectrometry (LC-MS/MS)-based metabolomic and proteomic analyses. Three groups were established: placebo-treated littermate db/m mice, placebo-treated db/db mice and EMPA-treated db/db mice. Empagliflozin (EMPA) and placebo (10 mg/kg/d) were administered for 12 weeks. EMPA treatment decreased Cys-C and urinary albumin excretion compared with placebo by 78.60% and 57.12%, respectively (p < 0.001 in all cases). Renal glomerular area, interstitial fibrosis and glomerulosclerosis were decreased by 16.47%, 68.50% and 62.82%, respectively (p < 0.05 in all cases). Multi-omic analysis revealed that EMPA treatment altered the protein and metabolic profiles in the db/db group, including 32 renal proteins, 51 serum proteins, 94 renal metabolites and 37 serum metabolites. Five EMPA-related metabolic pathways were identified by integrating proteomic and metabolomic analyses, which are involved in renal purine metabolism; pyrimidine metabolism; tryptophan metabolism; nicotinate and nicotinamide metabolism, and glycine, serine and threonine metabolism in serum. In conclusion, this study demonstrated metabolic reprogramming in mice with DKD. EMPA treatment improved kidney function and morphology by regulating metabolic reprogramming, including regulation of renal reductive stress, alleviation of mitochondrial dysfunction and reduction in renal oxidative stress reaction.
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Project description:BackgroundAcute kidney injury (AKI) is one of the most common clinical emergencies characterized by rapid progression, difficulty in early diagnosis, and high mortality. Currently, there are no effective AKI early diagnostic methods and treatments. Therefore, identifying new mechanisms of AKI have become urgent for development new targets for early diagnosis and treatment of AKI in the current clinical setting.MethodsIn this study, systematic analysis and comparison of serum metabolic profiles of clinical AKI patients, chronic kidney disease (CKD) patients, and healthy subjects were performed using untargeted metabolomics. Moreover, the first spatial metabolomic analysis of kidney tissues in an AKI mouse model using MALDI-TOF MS technology was conducted. Differentially expressed metabolites were identified using a comprehensive, publicly available database. The metabolic data obtained were evaluated using principal component analysis, (orthogonal) partial least squares discriminant analysis, and metabolic pathway analysis to explore the unique serum metabolic profile of the patients, as well as to characterize the spatial distribution of differential metabolites in the kidneys of AKI mice.ResultsSignificant changes in the metabolite levels of amino acids, carnitine, and lipids were observed in the AKI and CKD groups versus the healthy population, suggesting that kidney injury may lead to abnormalities in various metabolic pathways, such as amino acids, fatty acids, and lipids. The significant difference between the AKI and CKD groups were found for the first time in these indexes including amino acid, carnitine, fatty acid, and lipid levels. Additionally, spatial metabolomics results revealed that amino acid, carnitine, organic acid, and fatty acid metabolites were more likely significantly altered in the renal cortex, while lipid metabolites were both differentially distributed in the cortex and medulla of the AKI group.ConclusionAbnormalities in the serum metabolism of amino acids, carnitine, and lipids in patients with kidney diseases, such as AKI and CKD, are closely associated with the physiological dysfunction of kidney injury. Metabolic differences between patients with AKI and CKD were compared for the first time, showing that fatty acid oxidative inhibition was more severe in patients with AKI. Furthermore, spatial metabolomics has revealed metabolic reprogramming with tissue heterogeneity in AKI mice model. Our study provides valuable information in the molecular pathological features of AKI in the kidney tissues.
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Project description:Background and Objectives. Diabetic kidney disease is a leading cause of chronic kidney disease and end-stage renal disease across the world. Early identification of DKD is vitally important for the effective prevention and control of it. However, the available indicators are doubtful in the early diagnosis of DKD. This study is aimed at determining novel sensitive and specific biomarkers to distinguish DKD from their counterparts effectively based on the widely targeted metabolomics approach. Materials and Method. This case-control study involved 44 T2DM patients. Among them, 24 participants with DKD were defined as the cases and another 20 without DKD were defined as the controls. The ultraperformance liquid chromatography-electrospray ionization-tandem mass spectrometry system was applied for the assessment of the serum metabolic profiles. Comprehensive analysis of metabolomics characteristics was conducted to detect the candidate metabolic biomarkers and assess their capability and feasibility. Result:A total of 11 differential metabolites, including Hexadecanoic Acid (C16:0), Linolelaidic Acid (C18:2N6T), Linoleic Acid (C18:2N6C), Trans-4-Hydroxy-L-Proline, 6-Aminocaproic Acid, L-Dihydroorotic Acid, 6-Methylmercaptopurine, Piperidine, Azoxystrobin Acid, Lysopc 20:4, and Cuminaldehyde, were determined as the potential biomarkers for the DKD early identification, based on the multivariable generalized linear regression model and receiver operating characteristic analysis. Conclusion:Serum metabolites might act as sensitive and specific biomarkers for DKD early detection. Further longitudinal studies are needed to confirm our findings.
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