DESI-MSI and METASPACE indicates lipid abnormalities and altered mitochondrial membrane components in diabetic renal proximal tubules
Metabolomics, 2020•Springer
Introduction Diabetic kidney disease (DKD) is the most prevalent complication in diabetic
patients, which contributes to high morbidity and mortality. Urine and plasma metabolomics
studies have been demonstrated to provide valuable insights for DKD. However, limited
information on spatial distributions of metabolites in kidney tissues have been reported.
Objectives In this work, we employed an ambient desorption electrospray ionization-mass
spectrometry imaging (DESI-MSI) coupled to a novel bioinformatics platform (METASPACE) …
patients, which contributes to high morbidity and mortality. Urine and plasma metabolomics
studies have been demonstrated to provide valuable insights for DKD. However, limited
information on spatial distributions of metabolites in kidney tissues have been reported.
Objectives In this work, we employed an ambient desorption electrospray ionization-mass
spectrometry imaging (DESI-MSI) coupled to a novel bioinformatics platform (METASPACE) …
Introduction
Diabetic kidney disease (DKD) is the most prevalent complication in diabetic patients, which contributes to high morbidity and mortality. Urine and plasma metabolomics studies have been demonstrated to provide valuable insights for DKD. However, limited information on spatial distributions of metabolites in kidney tissues have been reported.
Objectives
In this work, we employed an ambient desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) coupled to a novel bioinformatics platform (METASPACE) to characterize the metabolome in a mouse model of DKD.
Methods
DESI-MSI was performed for spatial untargeted metabolomics analysis in kidneys of mouse models (F1 C57BL/6J-Ins2Akita male mice at 17 weeks of age) of type 1 diabetes (T1D, n = 5) and heathy controls (n = 6).
Results
Multivariate analyses (i.e., PCA and PLS-DA (a 2000 permutation test: P < 0.001)) showed clearly separated clusters for the two groups of mice on the basis of 878 measured m/z’s in kidney cortical tissues. Specifically, mice with T1D had increased relative abundances of pseudouridine, accumulation of free polyunsaturated fatty acids (PUFAs), and decreased relative abundances of cardiolipins in cortical proximal tubules when compared with healthy controls.
Conclusion
Results from the current study support potential key roles of pseudouridine and cardiolipins for maintaining normal RNA structure and normal mitochondrial function, respectively, in cortical proximal tubules with DKD. DESI-MSI technology coupled with METASPACE could serve as powerful new tools to provide insight on fundamental pathways in DKD.
Springer