Literature DB >> 31722432

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

Venkat R Pannala1,2, Kalyan C Vinnakota1,2, Shanea K Estes3, Irina Trenary4, Tracy P OˈBrien3, Richard L Printz3, Jason A Papin5, Jaques Reifman1, Tatsuya Oyama1,2, Masakazu Shiota3, Jamey D Young3,4, Anders Wallqvist1.   

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.
© The Author(s) 2020. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  aminoaciduria; biomarkers; genome-scale models; gentamicin; metabolic pathways; urine

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Year:  2020        PMID: 31722432      PMCID: PMC8000070          DOI: 10.1093/toxsci/kfz228

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  81 in total

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Authors:  Zhiwu Lin; Yvonne Will
Journal:  Toxicol Sci       Date:  2011-12-13       Impact factor: 4.849

Review 2.  Metabolomics in toxicology: preclinical and clinical applications.

Authors:  Donald G Robertson; Paul B Watkins; Michael D Reily
Journal:  Toxicol Sci       Date:  2010-12-02       Impact factor: 4.849

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Authors:  Michael A Ferguson; Sushrut S Waikar
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Review 5.  Metabonomics for discovering biomarkers of hepatotoxicity and nephrotoxicity.

Authors:  Aihua Zhang; Hui Sun; Ping Wang; Ying Han; Xijun Wang
Journal:  Pharmazie       Date:  2012-02       Impact factor: 1.267

6.  Organization of GC/MS and LC/MS metabolomics data into chemical libraries.

Authors:  Corey D Dehaven; Anne M Evans; Hongping Dai; Kay A Lawton
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7.  Discovery of metabolomics biomarkers for early detection of nephrotoxicity.

Authors:  Kurt J Boudonck; Matthew W Mitchell; László Német; Lilla Keresztes; Abraham Nyska; Doron Shinar; Moti Rosenstock
Journal:  Toxicol Pathol       Date:  2009-04       Impact factor: 1.902

8.  A molecular model of human branched-chain amino acid metabolism.

Authors:  A Suryawan; J W Hawes; R A Harris; Y Shimomura; A E Jenkins; S M Hutson
Journal:  Am J Clin Nutr       Date:  1998-07       Impact factor: 7.045

9.  Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions.

Authors:  Edik M Blais; Kristopher D Rawls; Bonnie V Dougherty; Zhuo I Li; Glynis L Kolling; Ping Ye; Anders Wallqvist; Jason A Papin
Journal:  Nat Commun       Date:  2017-02-08       Impact factor: 14.919

10.  Predicting metabolic biomarkers of human inborn errors of metabolism.

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Journal:  Mol Syst Biol       Date:  2009-04-28       Impact factor: 11.429

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  1 in total

1.  Toxicant-Induced Metabolic Alterations in Lipid and Amino Acid Pathways Are Predictive of Acute Liver Toxicity in Rats.

Authors:  Venkat R Pannala; Shanea K Estes; Mohsin Rahim; Irina Trenary; Tracy P O'Brien; Chiyo Shiota; Richard L Printz; Jaques Reifman; Masakazu Shiota; Jamey D Young; Anders Wallqvist
Journal:  Int J Mol Sci       Date:  2020-11-04       Impact factor: 5.923

  1 in total

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