How Structured Metadata Acquisition Contributes to the Reproducibility of Nanosafety Studies: Evaluation by a Round-Robin Test.

It has been widely recognized that nanosafety studies are limited in reproducibility, caused by missing or inadequate information and data gaps. Reliable and comprehensive studies should be performed supported by standards or guidelines, which need to be harmonized and usable for the multidisciplinary field of nanosafety research. The previously described minimal information table (MIT), based on existing standards or guidelines, represents one approach towards harmonization. Here, we demonstrate the applicability and advantages of the MIT by a round-robin test. Its modular structure enables describing individual studies comprehensively by a combination of various relevant aspects. Three laboratories conducted a WST-1 cell viability assay using A549 cells to analyze the effects of the reference nanomaterials NM101 and NM110 according to predefined (S)OPs. The MIT contains relevant and defined descriptive information and quality criteria and thus supported the implementation of the round-robin test from planning, investigation to analysis and data interpretation. As a result, we could identify sources of variability and justify deviating results attributed to differences in specific procedures. Consequently, the use of the MIT contributes to the acquisition of reliable and comprehensive datasets and therefore improves the significance and reusability of nanosafety studies.

Digital research data: from analysis of existing standards to a scientific foundation for a modular metadata schema in nanosafety.

BACKGROUND: Assessing the safety of engineered nanomaterials (ENMs) is an interdisciplinary and complex process producing huge amounts of information and data. To make such data and metadata reusable for researchers, manufacturers, and regulatory authorities, there is an urgent need to record and provide this information in a structured, harmonized, and digitized way. RESULTS: This study aimed to identify appropriate description standards and quality criteria for the special use in nanosafety. There are many existing standards and guidelines designed for collecting data and metadata, ranging from regulatory guidelines to specific databases. Most of them are incomplete or not specifically designed for ENM research. However, by merging the content of several existing standards and guidelines, a basic catalogue of descriptive information and quality criteria was generated. In an iterative process, our interdisciplinary team identified deficits and added missing information into a comprehensive schema. Subsequently, this overview was externally evaluated by a panel of experts during a workshop. This whole process resulted in a minimum information table (MIT), specifying necessary minimum information to be provided along with experimental results on effects of ENMs in the biological context in a flexible and modular manner. The MIT is divided into six modules: general information, material information, biological model information, exposure information, endpoint read out information and analysis and statistics. These modules are further partitioned into module subdivisions serving to include more detailed information. A comparison with existing ontologies, which also aim to electronically collect data and metadata on nanosafety studies, showed that the newly developed MIT exhibits a higher level of detail compared to those existing schemas, making it more usable to prevent gaps in the communication of information. CONCLUSION: Implementing the requirements of the MIT into e.g., electronic lab notebooks (ELNs) would make the collection of all necessary data and metadata a daily routine and thereby would improve the reproducibility and reusability of experiments. Furthermore, this approach is particularly beneficial regarding the rapidly expanding developments and applications of novel non-animal alternative testing methods.

Definition of transcriptome-based indices for quantitative characterization of chemically disturbed stem cell development: introduction of the STOP-Toxukn and STOP-Toxukk tests.

Stem cell-based in vitro test systems can recapitulate specific phases of human development. In the UKK test system, human pluripotent stem cells (hPSCs) randomly differentiate into cells of the three germ layers and their derivatives. In the UKN1 test system, hPSCs differentiate into early neural precursor cells. During the normal differentiation period (14 days) of the UKK system, 570 genes [849 probe sets (PSs)] were regulated >fivefold; in the UKN1 system (6 days), 879 genes (1238 PSs) were regulated. We refer to these genes as 'developmental genes'. In the present study, we used genome-wide expression data of 12 test substances in the UKK and UKN1 test systems to understand the basic principles of how chemicals interfere with the spontaneous transcriptional development in both test systems. The set of test compounds included six histone deacetylase inhibitors (HDACis), six mercury-containing compounds ('mercurials') and thalidomide. All compounds were tested at the maximum non-cytotoxic concentration, while valproic acid and thalidomide were additionally tested over a wide range of concentrations. In total, 242 genes (252 PSs) in the UKK test system and 793 genes (1092 PSs) in the UKN1 test system were deregulated by the 12 test compounds. We identified sets of 'diagnostic genes' appropriate for the identification of the influence of HDACis or mercurials. Test compounds that interfered with the expression of developmental genes usually antagonized their spontaneous development, meaning that up-regulated developmental genes were suppressed and developmental genes whose expression normally decreases were induced. The fraction of compromised developmental genes varied widely between the test compounds, and it reached up to 60 %. To quantitatively describe disturbed development on a genome-wide basis, we recommend a concept of two indices, 'developmental potency' (D p) and 'developmental index' (D i), whereby D p is the fraction of all developmental genes that are up- or down-regulated by a test compound, and D i is the ratio of overrepresentation of developmental genes among all genes deregulated by a test compound. The use of D i makes hazard identification more sensitive because some compounds compromise the expression of only a relatively small number of genes but have a high propensity to deregulate developmental genes specifically, resulting in a low D p but a high D i. In conclusion, the concept based on the indices D p and D i offers the possibility to quantitatively express the propensity of test compounds to interfere with normal development.

Assessment of neurotoxic effects of tri-cresyl phosphates (TCPs) and cresyl saligenin phosphate (CBDP) using a combination of in vitro techniques.

Environmental exposures to tri-cresyl phosphates (TCPs) and the possible formation of toxic metabolites (e.g. cresyl saligenin phosphate; CBDP) may cause a variety of neurotoxic effects in humans. As reported for other organophosphorus compounds (OPs), the inhibition of acetylcholine esterase (AChE) has also been proposed as the underlying mechanism for TCP neurotoxicity. The ortho-isomer, ToCP and its metabolite CBDP are also known to affect neuropathy target esterase (NTE) leading to organophosphate-induced delayed neuropathy (OPIDN). Recently, in vitro testing has led to the identification of other molecular targets and alternative mechanisms of ToCP toxicity. The metabolite CBDP and other isomers, as well as commercial mixtures have not been tested for such additional modes of actions. Accordingly, the present study investigates alterations of neurobiological correlates of central nervous processes using different in vitro techniques. The three symmetric TCP isomers - ToCP, TpCP, and TmCP - that contain a methyl group at the ortho-, para-, or meta-position of the aromatic ring system, respectively, together with a commercial TCP mixture, and CBDP were all tested using concentrations not exceeding their cytotoxic concentrations. Isolated cortical neurons were kept in culture for 6days followed by 24h incubation with different concentrations of the test compounds. Thus, all endpoints were assessed after 7days in vitro (DIV 7), at which time cell viability, neurite microstructure, and the function of glutamate receptors and voltage-gated calcium cannels (VGCC) were measured. While the cytotoxic potential of the TCP isomers and their mixture were comparable (IC50≥80µM), CBDP was more cytotoxic (IC50: 15µM) to primary cortical neurons. In contrast, CBDP (up to 10µM) did not compromise the microstructure of neurites. Ten µM of ToCP significantly reduced the size and complexity of neurite networks, but neither TmCP and TpCP nor the mixture affected this second endpoint of neurotoxicity assessment. TCPs and their mixture significantly reduced the Ca2+ influx in response to glutamate and KCl stimulation in concentrations of 10µM. Only ToCP showed a specific effect on glutamate receptors with 100nM reducing the evoked Ca2+ influx. The effects of CBDP on the provoked Ca2+ influx were much weaker than those observed for TCPs. These results confirmed that ToCP has a unique mode of action on glutamate receptors that are not observed with the metabolite CBDP and the other symmetric TCP isomers. In addition, the TmCP isomer seems to have the lowest potency with respect to inducing neurotoxic effects. CBDP did not affect the neurospecific endpoints investigated in this study. Therefore, the specific affinity of CBDP for NTE and the reported general cytotoxicity might be the most relevant modes of action of this toxic metabolite in the context of ToCP-induced neurotoxicity, including OPIDN.

A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors.

Test systems to identify developmental toxicants are urgently needed. A combination of human stem cell technology and transcriptome analysis was to provide a proof of concept that toxicants with a related mode of action can be identified and grouped for read-across. We chose a test system of developmental toxicity, related to the generation of neuroectoderm from pluripotent stem cells (UKN1), and exposed cells for 6 days to the histone deacetylase inhibitors (HDACi) valproic acid, trichostatin A, vorinostat, belinostat, panobinostat and entinostat. To provide insight into their toxic action, we identified HDACi consensus genes, assigned them to superordinate biological processes and mapped them to a human transcription factor network constructed from hundreds of transcriptome data sets. We also tested a heterogeneous group of 'mercurials' (methylmercury, thimerosal, mercury(II)chloride, mercury(II)bromide, 4-chloromercuribenzoic acid, phenylmercuric acid). Microarray data were compared at the highest non-cytotoxic concentration for all 12 toxicants. A support vector machine (SVM)-based classifier predicted all HDACi correctly. For validation, the classifier was applied to legacy data sets of HDACi, and for each exposure situation, the SVM predictions correlated with the developmental toxicity. Finally, optimization of the classifier based on 100 probe sets showed that eight genes (F2RL2, TFAP2B, EDNRA, FOXD3, SIX3, MT1E, ETS1 and LHX2) are sufficient to separate HDACi from mercurials. Our data demonstrate how human stem cells and transcriptome analysis can be combined for mechanistic grouping and prediction of toxicants. Extension of this concept to mechanisms beyond HDACi would allow prediction of human developmental toxicity hazard of unknown compounds with the UKN1 test system.