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Multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation

New strategies to characterize the effects of engineered nanomaterials (ENMs) based on omics technologies are emerging. However, given the intricate interplay of multiple regulatory layers, the study of a single molecular species in exposed biological systems might not allow the needed granularity t...

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Autores principales: Scala, Giovanni, Kinaret, Pia, Marwah, Veer, Sund, Jukka, Fortino, Vittorio, Greco, Dario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043328/
https://www.ncbi.nlm.nih.gov/pubmed/32140619
http://dx.doi.org/10.1016/j.impact.2018.05.003
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author Scala, Giovanni
Kinaret, Pia
Marwah, Veer
Sund, Jukka
Fortino, Vittorio
Greco, Dario
author_facet Scala, Giovanni
Kinaret, Pia
Marwah, Veer
Sund, Jukka
Fortino, Vittorio
Greco, Dario
author_sort Scala, Giovanni
collection PubMed
description New strategies to characterize the effects of engineered nanomaterials (ENMs) based on omics technologies are emerging. However, given the intricate interplay of multiple regulatory layers, the study of a single molecular species in exposed biological systems might not allow the needed granularity to successfully identify the pathways of toxicity (PoT) and, hence, portraying adverse outcome pathways (AOPs). Moreover, the intrinsic diversity of different cell types composing the exposed organs and tissues in living organisms poses a problem when transferring in vivo experimentation into cell-based in vitro systems. To overcome these limitations, we have profiled genome-wide DNA methylation, mRNA and microRNA expression in three human cell lines representative of relevant cell types of the respiratory system, A549, BEAS-2B and THP-1, exposed to a low dose of ten carbon nanomaterials (CNMs) for 48 h. We applied advanced data integration and modelling techniques in order to build comprehensive regulatory and functional maps of the CNM effects in each cell type. We observed that different cell types respond differently to the same CNM exposure even at concentrations exerting similar phenotypic effects. Furthermore, we linked patterns of genomic and epigenomic regulation to intrinsic properties of CNM. Interestingly, DNA methylation and microRNA expression only partially explain the mechanism of action (MOA) of CNMs. Taken together, our results strongly support the implementation of approaches based on multi-omics screenings on multiple tissues/cell types, along with systems biology-based multi-variate data modelling, in order to build more accurate AOPs.
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spelling pubmed-70433282020-03-03 Multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation Scala, Giovanni Kinaret, Pia Marwah, Veer Sund, Jukka Fortino, Vittorio Greco, Dario NanoImpact Article New strategies to characterize the effects of engineered nanomaterials (ENMs) based on omics technologies are emerging. However, given the intricate interplay of multiple regulatory layers, the study of a single molecular species in exposed biological systems might not allow the needed granularity to successfully identify the pathways of toxicity (PoT) and, hence, portraying adverse outcome pathways (AOPs). Moreover, the intrinsic diversity of different cell types composing the exposed organs and tissues in living organisms poses a problem when transferring in vivo experimentation into cell-based in vitro systems. To overcome these limitations, we have profiled genome-wide DNA methylation, mRNA and microRNA expression in three human cell lines representative of relevant cell types of the respiratory system, A549, BEAS-2B and THP-1, exposed to a low dose of ten carbon nanomaterials (CNMs) for 48 h. We applied advanced data integration and modelling techniques in order to build comprehensive regulatory and functional maps of the CNM effects in each cell type. We observed that different cell types respond differently to the same CNM exposure even at concentrations exerting similar phenotypic effects. Furthermore, we linked patterns of genomic and epigenomic regulation to intrinsic properties of CNM. Interestingly, DNA methylation and microRNA expression only partially explain the mechanism of action (MOA) of CNMs. Taken together, our results strongly support the implementation of approaches based on multi-omics screenings on multiple tissues/cell types, along with systems biology-based multi-variate data modelling, in order to build more accurate AOPs. Elsevier B.V 2018-07 /pmc/articles/PMC7043328/ /pubmed/32140619 http://dx.doi.org/10.1016/j.impact.2018.05.003 Text en © 2018 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Scala, Giovanni
Kinaret, Pia
Marwah, Veer
Sund, Jukka
Fortino, Vittorio
Greco, Dario
Multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation
title Multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation
title_full Multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation
title_fullStr Multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation
title_full_unstemmed Multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation
title_short Multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation
title_sort multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043328/
https://www.ncbi.nlm.nih.gov/pubmed/32140619
http://dx.doi.org/10.1016/j.impact.2018.05.003
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