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Abstract: TH-PO871

DESI-MSI Based Spatial Metabolomics and METASPACE Indicates RNA and Mitochondrial Dysfunction in Renal Proximal Tubules of Mice with Diabetes

Session Information

Category: Diabetic Kidney Disease

  • 601 Diabetic Kidney Disease: Basic

Authors

  • Zhang, Guanshi, University of Texas Health San Antonio, San Antonio, Texas, United States
  • Darshi, Manjula, University of Texas Health San Antonio, San Antonio, Texas, United States
  • Sharma, Kumar, University of Texas Health San Antonio, San Antonio, Texas, United States
Background

Diabetic kidney disease (DKD) remains the largest contributor to end stage renal disease and insightful biomarkers are required for identifying pathways to target for prognosis and therapeutics. Knowledge about the spatial distribution of metabolites in kidney tissues of DKD patients/animals will enhance the cellular contribution of biomarkers.

Methods

In the current study, we employed an ambient desorption electrospray ionization - mass spectrometry imaging (DESI-MSI) approach to characterize the metabolome in kidney tissue sections in a model of DKD. The data output was coupled to a novel bioinformatics platform (METASPACE). 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). MetaboAnalyst 3.0 was employed for statistical analysis, metabolic pathway analysis, and biomarker analysis.

Results

Mice with DKD had increased relative abundances of pseudouridine, accumulation of free polyunsaturated fatty acids (PUFAs), and decreased relative abundances of phospholipids in cortical proximal tubules when compared with healthy controls. In the biomarker analysis, a five-metabolite biomarker set (i.e., phosphatidylglycerol (PG) 32:0, pseudouridine, hexose, phosphatidylserine (PS) 34:1, and diphenyl disulfide) was developed for diagnosing DKD. The AUC for the ROC curve is 0.994 (95% CI, 0.981-1; Empirical P < 0.001), which indicates that the biomarker set has excellent diagnostic ability for DKD in mice.

Conclusion

In summary, this new study demonstrates that DESI-MSI can be successfully used to distinguish cortical proximal tubules in healthy and diabetic tissues based on altered relative abundance of lipid profiles. DESI-MSI technology coupled with the METASPACE will serve as a powerful tool to shed new light on fundamental pathways in DKD.

Funding

  • NIDDK Support