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Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles

BACKGROUND: A very large and rapidly growing collection of transcriptomic profiles in public repositories is potentially of great value to developing data-driven bioinformatics applications for toxicology/ecotoxicology. Modeled on human connectivity mapping (Cmap) in biomedical research, this study...

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Autores principales: Wang, Rong-Lin, Biales, Adam D., Garcia-Reyero, Natalia, Perkins, Edward J., Villeneuve, Daniel L., Ankley, Gerald T., Bencic, David C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4730593/
https://www.ncbi.nlm.nih.gov/pubmed/26822894
http://dx.doi.org/10.1186/s12864-016-2406-y
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author Wang, Rong-Lin
Biales, Adam D.
Garcia-Reyero, Natalia
Perkins, Edward J.
Villeneuve, Daniel L.
Ankley, Gerald T.
Bencic, David C.
author_facet Wang, Rong-Lin
Biales, Adam D.
Garcia-Reyero, Natalia
Perkins, Edward J.
Villeneuve, Daniel L.
Ankley, Gerald T.
Bencic, David C.
author_sort Wang, Rong-Lin
collection PubMed
description BACKGROUND: A very large and rapidly growing collection of transcriptomic profiles in public repositories is potentially of great value to developing data-driven bioinformatics applications for toxicology/ecotoxicology. Modeled on human connectivity mapping (Cmap) in biomedical research, this study was undertaken to investigate the utility of an analogous Cmap approach in ecotoxicology. Over 3500 zebrafish (Danio rerio) and fathead minnow (Pimephales promelas) transcriptomic profiles, each associated with one of several dozen chemical treatment conditions, were compiled into three distinct collections of rank-ordered gene lists (ROGLs) by species and microarray platforms. Individual query signatures, each consisting of multiple gene probes differentially expressed in a chemical condition, were used to interrogate the reference ROGLs. RESULTS: Informative connections were established at high success rates within species when, as defined by their mechanisms of action (MOAs), both query signatures and ROGLs were associated with the same or similar chemicals. Thus, a simple query signature functioned effectively as an exposure biomarker without need for a time-consuming process of development and validation. More importantly, a large reference database of ROGLs also enabled a query signature to cross-interrogate other chemical conditions with overlapping MOAs, leading to novel groupings and subgroupings of seemingly unrelated chemicals at a finer resolution. This approach confirmed the identities of several estrogenic chemicals, as well as a polycyclic aromatic hydrocarbon and a neuro-toxin, in the largely uncharacterized water samples near several waste water treatment plants, and thus demonstrates its future potential utility in real world applications. CONCLUSIONS: The power of Cmap should grow as chemical coverages of ROGLs increase, making it a framework easily scalable in the future. The feasibility of toxicity extrapolation across fish species using Cmap needs more study, however, as more gene expression profiles linked to chemical conditions common to multiple fish species are needed. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2406-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-47305932016-01-29 Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles Wang, Rong-Lin Biales, Adam D. Garcia-Reyero, Natalia Perkins, Edward J. Villeneuve, Daniel L. Ankley, Gerald T. Bencic, David C. BMC Genomics Research Article BACKGROUND: A very large and rapidly growing collection of transcriptomic profiles in public repositories is potentially of great value to developing data-driven bioinformatics applications for toxicology/ecotoxicology. Modeled on human connectivity mapping (Cmap) in biomedical research, this study was undertaken to investigate the utility of an analogous Cmap approach in ecotoxicology. Over 3500 zebrafish (Danio rerio) and fathead minnow (Pimephales promelas) transcriptomic profiles, each associated with one of several dozen chemical treatment conditions, were compiled into three distinct collections of rank-ordered gene lists (ROGLs) by species and microarray platforms. Individual query signatures, each consisting of multiple gene probes differentially expressed in a chemical condition, were used to interrogate the reference ROGLs. RESULTS: Informative connections were established at high success rates within species when, as defined by their mechanisms of action (MOAs), both query signatures and ROGLs were associated with the same or similar chemicals. Thus, a simple query signature functioned effectively as an exposure biomarker without need for a time-consuming process of development and validation. More importantly, a large reference database of ROGLs also enabled a query signature to cross-interrogate other chemical conditions with overlapping MOAs, leading to novel groupings and subgroupings of seemingly unrelated chemicals at a finer resolution. This approach confirmed the identities of several estrogenic chemicals, as well as a polycyclic aromatic hydrocarbon and a neuro-toxin, in the largely uncharacterized water samples near several waste water treatment plants, and thus demonstrates its future potential utility in real world applications. CONCLUSIONS: The power of Cmap should grow as chemical coverages of ROGLs increase, making it a framework easily scalable in the future. The feasibility of toxicity extrapolation across fish species using Cmap needs more study, however, as more gene expression profiles linked to chemical conditions common to multiple fish species are needed. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2406-y) contains supplementary material, which is available to authorized users. BioMed Central 2016-01-28 /pmc/articles/PMC4730593/ /pubmed/26822894 http://dx.doi.org/10.1186/s12864-016-2406-y Text en © Wang et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Wang, Rong-Lin
Biales, Adam D.
Garcia-Reyero, Natalia
Perkins, Edward J.
Villeneuve, Daniel L.
Ankley, Gerald T.
Bencic, David C.
Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles
title Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles
title_full Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles
title_fullStr Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles
title_full_unstemmed Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles
title_short Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles
title_sort fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4730593/
https://www.ncbi.nlm.nih.gov/pubmed/26822894
http://dx.doi.org/10.1186/s12864-016-2406-y
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