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Common Gene Expression Patterns in Environmental Model Organisms Exposed to Engineered Nanomaterials: A Meta-Analysis
[Image: see text] The use of omics is gaining importance in the field of nanoecotoxicology; an increasing number of studies are aiming to investigate the effects and modes of action of engineered nanomaterials (ENMs) in this way. However, a systematic synthesis of the outcome of such studies regardi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6950232/ https://www.ncbi.nlm.nih.gov/pubmed/31752483 http://dx.doi.org/10.1021/acs.est.9b05170 |
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author | Burkard, Michael Betz, Alexander Schirmer, Kristin Zupanic, Anze |
author_facet | Burkard, Michael Betz, Alexander Schirmer, Kristin Zupanic, Anze |
author_sort | Burkard, Michael |
collection | PubMed |
description | [Image: see text] The use of omics is gaining importance in the field of nanoecotoxicology; an increasing number of studies are aiming to investigate the effects and modes of action of engineered nanomaterials (ENMs) in this way. However, a systematic synthesis of the outcome of such studies regarding common responses and toxicity pathways is currently lacking. We developed an R-scripted computational pipeline to perform reanalysis and functional analysis of relevant transcriptomic data sets using a common approach, independent from the ENM type, and across different organisms, including Arabidopsis thaliana, Caenorhabditis elegans, and Danio rerio. Using the pipeline that can semiautomatically process data from different microarray technologies, we were able to determine the most common molecular mechanisms of nanotoxicity across extremely variable data sets. As expected, we found known mechanisms, such as interference with energy generation, oxidative stress, disruption of DNA synthesis, and activation of DNA-repair but also discovered that some less-described molecular responses to ENMs, such as DNA/RNA methylation, protein folding, and interference with neurological functions, are present across the different studies. Results were visualized in radar charts to assess toxicological response patterns allowing the comparison of different organisms and ENM types. This can be helpful to retrieve ENM-related hazard information and thus fill knowledge gaps in a comprehensive way in regard to the molecular underpinnings and mechanistic understanding of nanotoxicity. |
format | Online Article Text |
id | pubmed-6950232 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-69502322020-01-10 Common Gene Expression Patterns in Environmental Model Organisms Exposed to Engineered Nanomaterials: A Meta-Analysis Burkard, Michael Betz, Alexander Schirmer, Kristin Zupanic, Anze Environ Sci Technol [Image: see text] The use of omics is gaining importance in the field of nanoecotoxicology; an increasing number of studies are aiming to investigate the effects and modes of action of engineered nanomaterials (ENMs) in this way. However, a systematic synthesis of the outcome of such studies regarding common responses and toxicity pathways is currently lacking. We developed an R-scripted computational pipeline to perform reanalysis and functional analysis of relevant transcriptomic data sets using a common approach, independent from the ENM type, and across different organisms, including Arabidopsis thaliana, Caenorhabditis elegans, and Danio rerio. Using the pipeline that can semiautomatically process data from different microarray technologies, we were able to determine the most common molecular mechanisms of nanotoxicity across extremely variable data sets. As expected, we found known mechanisms, such as interference with energy generation, oxidative stress, disruption of DNA synthesis, and activation of DNA-repair but also discovered that some less-described molecular responses to ENMs, such as DNA/RNA methylation, protein folding, and interference with neurological functions, are present across the different studies. Results were visualized in radar charts to assess toxicological response patterns allowing the comparison of different organisms and ENM types. This can be helpful to retrieve ENM-related hazard information and thus fill knowledge gaps in a comprehensive way in regard to the molecular underpinnings and mechanistic understanding of nanotoxicity. American Chemical Society 2019-11-22 2020-01-07 /pmc/articles/PMC6950232/ /pubmed/31752483 http://dx.doi.org/10.1021/acs.est.9b05170 Text en Copyright © 2019 American Chemical Society This is an open access article published under a Creative Commons Non-Commercial No Derivative Works (CC-BY-NC-ND) Attribution License (http://pubs.acs.org/page/policy/authorchoice_ccbyncnd_termsofuse.html) , which permits copying and redistribution of the article, and creation of adaptations, all for non-commercial purposes. |
spellingShingle | Burkard, Michael Betz, Alexander Schirmer, Kristin Zupanic, Anze Common Gene Expression Patterns in Environmental Model Organisms Exposed to Engineered Nanomaterials: A Meta-Analysis |
title | Common Gene Expression Patterns in Environmental Model
Organisms Exposed to Engineered
Nanomaterials: A Meta-Analysis |
title_full | Common Gene Expression Patterns in Environmental Model
Organisms Exposed to Engineered
Nanomaterials: A Meta-Analysis |
title_fullStr | Common Gene Expression Patterns in Environmental Model
Organisms Exposed to Engineered
Nanomaterials: A Meta-Analysis |
title_full_unstemmed | Common Gene Expression Patterns in Environmental Model
Organisms Exposed to Engineered
Nanomaterials: A Meta-Analysis |
title_short | Common Gene Expression Patterns in Environmental Model
Organisms Exposed to Engineered
Nanomaterials: A Meta-Analysis |
title_sort | common gene expression patterns in environmental model
organisms exposed to engineered
nanomaterials: a meta-analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6950232/ https://www.ncbi.nlm.nih.gov/pubmed/31752483 http://dx.doi.org/10.1021/acs.est.9b05170 |
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