With the growing numbers of nanomaterials (NMs), there is a great demand for rapid and reliable ways of testingNMsafety—preferably usingin vitroapproaches, to avoid the ethical dilemmas associated with animal research. Data are needed for developing intelligent testing strategies for risk assessment ofNMs, based on grouping and read‐across approaches. The adoption of high throughput screening (HTS) and high content analysis (HCA) forNMtoxicity testing allows the testing of numerous materials at different concentrations and on different types of cells, reduces the effect of inter‐experimental variation, and makes substantial savings in time and cost.HTS/HCAapproaches facilitate the classification of key biological indicators ofNM‐cell interactions. Validation ofin vitroHTStests is required, taking account of relevance toin vivoresults.HTS/HCAapproaches are needed to assess dose‐ and time‐dependent toxicity, allowing prediction ofin vivoadverse effects. SeveralHTS/HCAmethods are being validated and applied forNMtesting in theFP7projectNANoREG, including Label‐free cellular screening ofNMuptake, HCA, High throughput flow cytometry, Impedance‐based monitoring, Multiplex analysis of secreted products, and genotoxicity methods—namely High throughput comet assay, High throughputin vitromicronucleus assay, andγH2AXassay. There are several technical challenges withHTS/HCAforNMtesting, as toxicity screening needs to be coupled with characterization ofNMsin exposure medium prior to the test; possible interference ofNMswithHTS/HCAtechniques is another concern. Advantages and challenges ofHTS/HCAapproaches inNMsafety are discussed.WIREs Nanomed Nanobiotechnol2017, 9:e1413. doi: 10.1002/wnan.1413This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials

Background: Recently, we used cell-free assays to demonstrate the toxic effects of complex mixtures of organic extracts from urban air particles (PM2.5) collected in four localities of the Czech Republic (Ostrava-Bartovice, Ostrava-Poruba, Karvina and Trebon) which differed in the extent and sources of air pollution. To obtain further insight into the biological mechanisms of action of the extractable organic matter (EOM) from ambient air particles, human embryonic lung fibroblasts (HEL12469) were treated with the same four EOMs to assess changes in the genome-wide expression profiles compared to DMSO treated controls. Method: For this purpose, HEL cells were incubated with subtoxic EOM concentrations of 10, 30, and 60 μg EOM/ml for 24 hours and global gene expression changes were analyzed using human whole genome microarrays (Illumina). The expression of selected genes was verified by quantitative real-time PCR. Results: Dose-dependent increases in the number of significantly deregulated transcripts as well as dose-response relationships in the levels of individual transcripts were observed. The transcriptomic data did not differ substantially between the localities, suggesting that the air pollution originating mainly from various sources may have similar biological effects. This was further confirmed by the analysis of deregulated pathways and by identification of the most contributing gene modulations. The number of significantly deregulated KEGG pathways, as identified by Goeman's global test, varied, depending on the locality, between 12 to 29. The Metabolism of xenobiotics by cytochrome P450 exhibited the strongest upregulation in all 4 localities and CYP1B1 had a major contribution to the upregulation of this pathway. Other important deregulated pathways in all 4 localities were ABC transporters (involved in the translocation of exogenous and endogenous metabolites across membranes and DNA repair), the Wnt and TGF-β signaling pathways (associated particularly with tumor promotion and progression), Steroid hormone biosynthesis (involved in the endocrine-disrupting activity of chemicals), and Glycerolipid metabolism (pathways involving the lipids with a glycerol backbone including lipid signaling molecules). Conclusion: The microarray data suggested a prominent role of activation of aryl hydrocarbon receptor-dependent gene expression.