Abstract

Desorption electrospray ionization mass spectrometry (DESI-MS) is an emerging analytical tool for rapid in situ assessment of metabolomic profiles on tissue sections without tissue pretreatment or labeling. We applied DESI-MS to identify candidate metabolic biomarkers associated with kidney injury at the early stage. DESI-MS was performed on sections of kidneys from 80 mice over a time course following unilateral ureteral obstruction (UUO) and compared to sham controls. A predictive model of renal damage was constructed using the LASSO (least absolute shrinkage and selection operator) method. Levels of lipid and small metabolites were significantly altered and glycerophospholipids comprised a significant fraction of altered species. These changes correlate with altered expression of lipid metabolic genes, with most genes showing decreased expression. However, rapid upregulation of PG(22:6/22:6) level appeared to be a hitherto unknown feature of the metabolic shift observed in UUO. Using LASSO and SAM (significance analysis of microarrays), we identified a set of well-measured metabolites that accurately predicted UUO-induced renal damage that was detectable by 12 h after UUO, prior to apparent histological changes. Thus, DESI-MS could serve as a useful adjunct to histology in identifying renal damage and demonstrates early and broad changes in membrane associated lipids.

Highlights

  • Renal biopsy is used commonly to assess the etiology of renal failure, where it has been reported to alter clinical management in approximately 40% of all patients and up to 70% of cases with acute kidney injury[1,2]

  • The metabolic changes over the time course were more prominent in kidneys subject to ureteral obstruction (UUO) than those observed in the sham controls (Fig. 1)

  • Desorption electrospray ionization mass spectrometry (DESI-MS) provides rapid, an in-depth assessment of metabolic changes after injury, revealing metabolic shifts that occur at time points well before morphological changes and inflammatory infiltrates are visible histologically in this model system

Read more

Summary

Introduction

Renal biopsy is used commonly to assess the etiology of renal failure, where it has been reported to alter clinical management in approximately 40% of all patients and up to 70% of cases with acute kidney injury[1,2]. DESI-MS has been used as a discovery platform to define spatial and temporal metabolomic changes in oncogene-induced cancer model systems[13,17,18,19] In these studies, previously unknown metabolic changes, in lipids that have potential roles in cell signaling, have been revealed and have possible therapeutic implications. To evaluate whether DESI-MS could provide information from renal tissues, such as those obtained from a renal biopsy, we tested a commonly used mouse model of renal damage, unilateral ureteral obstruction (UUO). This well-characterized model system allows assessment of metabolic changes over a time course. We were interested to determine whether metabolic changes could be observed in renal tissues after injury and whether they could be used to develop predictive models that identified renal compromise early

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call