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Genome-Scale Model-Based Identification of Metabolite Indicators for Early Detection of Kidney Toxicity

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November 14 2019
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Toxicol Sci. 2020 Feb 1;173(2):293-312. doi: 10.1093/toxsci/kfz228.

ABSTRACT

Identifying early indicators of toxicant-induced organ damage is critical to provide effective treatment. To discover such indicators and the underlying mechanisms of toxicity, we used gentamicin as an exemplar kidney toxicant and performed systematic perturbation studies in Sprague Dawley rats. We obtained high-throughput data 7 and 13 h after administration of a single dose of gentamicin (0.5 g/kg) and identified global changes in genes in the liver and kidneys, metabolites in the plasma and urine, and absolute fluxes in central carbon metabolism. We used these measured changes in genes in the liver and kidney as constraints to a rat multitissue genome-scale metabolic network model to investigate the mechanism of gentamicin-induced kidney toxicity and identify metabolites associated with changes in tissue gene expression. Our experimental analysis revealed that gentamicin-induced metabolic perturbations could be detected as early as 7 h postexposure. Our integrated systems-level analyses suggest that changes in kidney gene expression drive most of the significant metabolite alterations in the urine. The analyses thus allowed us to identify several significantly enriched injury-specific pathways in the kidney underlying gentamicin-induced toxicity, as well as metabolites in these pathways that could serve as potential early indicators of kidney damage.

PMID:31722432 | PMC:PMC8000070 | DOI:10.1093/toxsci/kfz228

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Computational Systems Biology Laboratory; The research group of Dr. Jason Papin in the Department of Biomedical Engineering at the University of Virginia.

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The research group of Dr. Jason Papin in the Department of Biomedical Engineering at the University of Virginia

  • Email: papinlab@virginia.edu
  • Phone (434) 924-8195

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