An ancestral molecular response to nanomaterial particulates

Del Giudice, G.; Serra, A.; Saarimaki, L.A.; Kotsis, K.; Rouse, I.; Colibaba, S.A.; Jagiello, K.; Mikolajczyk, A.; Fratello, M.; Papadiamantis, A.G.; Sanabria, N.; Annala, M.E.; Morikka, J.; Kinaret, P.A.S.; Voyiatzis, E.; Melagraki, G.; Afantitis, A.; Tamm, K.; Puzyn, T.; Gulumian, M.; Lobaskin, V.; Lynch, I.; Federico, A.; Greco, D.

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An ancestral molecular response to nanomaterial particulates

Del Giudice, G.; Serra, A.; Saarimaki, L.A.; Kotsis, K.; Rouse, I.; Colibaba, S.A.; Jagiello, K.; Mikolajczyk, A.; Fratello, M.; Papadiamantis, A.G.; Sanabria, N.; Annala, M.E.; Morikka, J.; Kinaret, P.A.S.; Voyiatzis, E.; Melagraki, G.; Afantitis, A.; Tamm, K.; Puzyn, T.; Gulumian, M.; Lobaskin, V.; Lynch, I.; Federico, A.; Greco, D.

URI: http://hdl.handle.net/2263/97995

Date: 2023-08

Abstract:

The varied transcriptomic response to nanoparticles has hampered the understanding of the mechanism of action. Here, by performing a meta-analysis of a large collection of transcriptomics data from various engineered nanoparticle exposure studies, we identify common patterns of gene regulation that impact the transcriptomic response. Analysis identifies deregulation of immune functions as a prominent response across different exposure studies. Looking at the promoter regions of these genes, a set of binding sites for zinc finger transcription factors C2H2, involved in cell stress responses, protein misfolding and chromatin remodelling and immunomodulation, is identified. The model can be used to explain the outcomes of mechanism of action and is observed across a range of species indicating this is a conserved part of the innate immune system.

Description:

DATA AVAILABILITY : The pre-processed version of the transcriptomic datasets included in the discovery datasets, that is, ENM exposures of human and mouse samples, have been previously deposited at https://zenodo.org/ record/3949890#.YlPUri0RqH0. The original datasets can be accessed at Array Express (https://www.ebi.ac.uk/biostudies/arrayexpress) with the entry code EMTAB6396 and at GEO (https://www.ncbi.nlm.nih. gov/) under accession numbers GSE103101, GSE112780, GSE113088, GSE117056, GSE122197, GSE127773, GSE146708, GSE148705, GSE157266, GSE16727, GSE17676, GSE19487, GSE20692, GSE29042, GSE35193, GSE39330, GSE41041, GSE42066, GSE42067, GSE42068, GSE43515, GSE45322, GSE45598, GSE4567, GSE46998, GSE46999, GSE50176, GSE51186, GSE51417, GSE51421, GSE51636, GSE53700, GSE55286, GSE55349, GSE56324, GSE56325, GSE60797, GSE60798, GSE60799, GSE60800, GSE61366, GSE62253, GSE62769, GSE63552, GSE63806, GSE68036, GSE75429, GSE79766, GSE81564, GSE81565, GSE81566, GSE81567, GSE81568, GSE81569, GSE82062, GSE84982, GSE85711, GSE88786, GSE92563, GSE92900, GSE92987, GSE96720, GSE98236 and GSE99929. Transcriptomic datasets used for the eco-toxicological analysis are freely available at GEO under accession numbers GSE80461, GSE32521, GSE70509, GSE73427, GSE77148, GSE41333 and GSE47662. Transcriptomic datasets of small molecule exposure (Open-TG GATEs) have been downloaded from https://dbarchive.biosciencedbc.jp/en/ open-tggates/download.html in November 2020. Functional data were downloaded from https://www.gsea-msigdb.org/gsea/msigdb/ version 7.2. All the other relevant data and data supporting the findings of this study have been deposited in the online Zenodo repository (https://doi.org/10.5281/zenodo.7674574).

CODE AVAILABILITY : All the relevant and custom code supporting the findings of this study has been deposited in the online Zenodo repository (https://DOI. org/10.5281/zenodo.7674574) and on Github at https://github.com/ fhaive/metanalysis_toxicogenomic_data.

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