PNNL

Abstract

Diabetic kidney disease (DKD) is the most prevalent complication in diabetic patients, which contributes to high morbidity and mortality. However, spatial distribution of metabolites in kidney tissues are only in its infancy and bioinformatics and search engines for interrogation of MSI data are limited. In the present study, we employed an ambient ionization DESI-MSI approach to characterize the metabolome in a mouse model of DKD coupled to a novel bioinformatics platform - METASPACE. DESI-MSI was performed for spatial untargeted metabolomics analysis in kidneys of mouse of type 1 diabetes (T1D, n = 5) and heathy controls (n = 6). Multivariate analyses 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 abundance of pseudouridine, accumulation of free PUFAs, and decreased relative abundances of cardiolipins in cortical proximal tubules when compared with healthy controls. Results from the current study supports key roles for structural RNA and mitochondrial dysfunction in cortical proximal tubules with DKD. DESI-MSI technology coupled with METASPACE may serve as powerful new tools to shed new light on fundamental pathways in DKD.