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Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions
The laboratory rat has been used as a surrogate to study human biology for more than a century. Here we present the first genome-scale network reconstruction of Rattus norvegicus metabolism, iRno, and a significantly improved reconstruction of human metabolism, iHsa. These curated models comprehensi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309818/ https://www.ncbi.nlm.nih.gov/pubmed/28176778 http://dx.doi.org/10.1038/ncomms14250 |
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author | Blais, Edik M. Rawls, Kristopher D. Dougherty, Bonnie V. Li, Zhuo I. Kolling, Glynis L. Ye, Ping Wallqvist, Anders Papin, Jason A. |
author_facet | Blais, Edik M. Rawls, Kristopher D. Dougherty, Bonnie V. Li, Zhuo I. Kolling, Glynis L. Ye, Ping Wallqvist, Anders Papin, Jason A. |
author_sort | Blais, Edik M. |
collection | PubMed |
description | The laboratory rat has been used as a surrogate to study human biology for more than a century. Here we present the first genome-scale network reconstruction of Rattus norvegicus metabolism, iRno, and a significantly improved reconstruction of human metabolism, iHsa. These curated models comprehensively capture metabolic features known to distinguish rats from humans including vitamin C and bile acid synthesis pathways. After reconciling network differences between iRno and iHsa, we integrate toxicogenomics data from rat and human hepatocytes, to generate biomarker predictions in response to 76 drugs. We validate comparative predictions for xanthine derivatives with new experimental data and literature-based evidence delineating metabolite biomarkers unique to humans. Our results provide mechanistic insights into species-specific metabolism and facilitate the selection of biomarkers consistent with rat and human biology. These models can serve as powerful computational platforms for contextualizing experimental data and making functional predictions for clinical and basic science applications. |
format | Online Article Text |
id | pubmed-5309818 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53098182017-02-27 Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions Blais, Edik M. Rawls, Kristopher D. Dougherty, Bonnie V. Li, Zhuo I. Kolling, Glynis L. Ye, Ping Wallqvist, Anders Papin, Jason A. Nat Commun Article The laboratory rat has been used as a surrogate to study human biology for more than a century. Here we present the first genome-scale network reconstruction of Rattus norvegicus metabolism, iRno, and a significantly improved reconstruction of human metabolism, iHsa. These curated models comprehensively capture metabolic features known to distinguish rats from humans including vitamin C and bile acid synthesis pathways. After reconciling network differences between iRno and iHsa, we integrate toxicogenomics data from rat and human hepatocytes, to generate biomarker predictions in response to 76 drugs. We validate comparative predictions for xanthine derivatives with new experimental data and literature-based evidence delineating metabolite biomarkers unique to humans. Our results provide mechanistic insights into species-specific metabolism and facilitate the selection of biomarkers consistent with rat and human biology. These models can serve as powerful computational platforms for contextualizing experimental data and making functional predictions for clinical and basic science applications. Nature Publishing Group 2017-02-08 /pmc/articles/PMC5309818/ /pubmed/28176778 http://dx.doi.org/10.1038/ncomms14250 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Blais, Edik M. Rawls, Kristopher D. Dougherty, Bonnie V. Li, Zhuo I. Kolling, Glynis L. Ye, Ping Wallqvist, Anders Papin, Jason A. Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions |
title | Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions |
title_full | Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions |
title_fullStr | Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions |
title_full_unstemmed | Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions |
title_short | Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions |
title_sort | reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5309818/ https://www.ncbi.nlm.nih.gov/pubmed/28176778 http://dx.doi.org/10.1038/ncomms14250 |
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