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A high throughput imaging database of toxicological effects of nanomaterials tested on HepaRG cells.

ABSTRACT: The large amount of existing nanomaterials demands rapid and reliable methods for testing their potential toxicological effect on human health, preferably by means of relevant in vitro techniques in order to reduce testing on animals. Combining high throughput workflows with automated high content imaging techniques allows deriving much more information from cell-based assays than the typical readouts (i.e. one measurement per well) with optical plate-readers. We present here a dataset including data based on a maximum of 14 different read outs (including viable cell count, cell membrane permeability, apoptotic cell death, mitochondrial membrane potential and steatosis) of the human hepatoma HepaRG cell line treated with a large set of nanomaterials, coatings and supernatants at different concentrations. The database, given its size, can be utilized in the development of in silico hazard assessment and prediction tools or can be combined with toxicity results from other in vitro test systems.

SUBMITTER: Joossens E

PROVIDER: S-EPMC6497662 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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A high throughput imaging database of toxicological effects of nanomaterials tested on HepaRG cells.

Joossens Elisabeth E Macko Peter P Palosaari Taina T Gerloff Kirsten K Ojea-Jiménez Isaac I Gilliland Douglas D Novak Jaroslav J Fortaner Torrent Salvador S Gineste Jean-Michel JM Römer Isabella I Briffa Sophie Marie SM Valsami-Jones Eugenia E Lynch Iseult I Whelan Maurice M

Scientific data 20190502 1

The large amount of existing nanomaterials demands rapid and reliable methods for testing their potential toxicological effect on human health, preferably by means of relevant in vitro techniques in order to reduce testing on animals. Combining high throughput workflows with automated high content imaging techniques allows deriving much more information from cell-based assays than the typical readouts (i.e. one measurement per well) with optical plate-readers. We present here a dataset including ...[more]

PMID: 31048742

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Project description:With thousands of chemicals in commerce and the environment, rapid identification of potential hazards is a critical need. Combining broad molecular profiling with targeted in vitro assays, such as high-throughput transcriptomics (HTTr) and receptor screening assays, could improve identification of chemicals that perturb key molecular targets associated with adverse outcomes. We aimed to link transcriptomic readouts to individual molecular targets and integrate transcriptomic predictions with orthogonal receptor-level assays in a proof-of-concept framework for chemical hazard prioritization. Transcriptomic profiles generated via TempO-Seq in U-2 OS and HepaRG cell lines were used to develop signatures comprised of genes uniquely responsive to reference chemicals for distinct molecular targets. These signatures were applied to 75 reference and 1,126 non-reference chemicals screened via HTTr in both cell lines. Selective bioactivity towards each signature was determined by comparing potency estimates against the bulk of transcriptomic bioactivity for each chemical. Chemicals predicted by transcriptomics were confirmed for target bioactivity and selectivity using available orthogonal assay data from US EPA’s ToxCast program. A subset of 37 selectively acting chemicals from HTTr that did not have sufficient orthogonal data were prospectively tested using one of five receptor-level assays. Of the 1,126 non-reference chemicals screened, 201 demonstrated selective bioactivity in at least one transcriptomic signature, and 57 were confirmed as selective nuclear receptor agonists. Chemicals bioactive for each signature were significantly associated with orthogonal assay bioactivity, and signature-based points-of-departure were equally or more sensitive than biological pathway altering concentrations in 81.2% of signature-prioritized chemicals. Prospective profiling found that 18 of 37 (49%) chemicals without prior orthogonal assay data were bioactive against the predicted receptor. Our work demonstrates that integrating transcriptomics with targeted orthogonal assays in a tiered framework can support Next Generation Risk Assessment by informing putative molecular targets and prioritizing chemicals for further testing. NOTE: this GEO entry only includes the HepaRG cell line data; the U-2 OS cell line data can be located via GEO accession number GSE274318.

Dataset Information

A high throughput imaging database of toxicological effects of nanomaterials tested on HepaRG cells.

Publications

A high throughput imaging database of toxicological effects of nanomaterials tested on HepaRG cells.

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