Next generation risk assessment for occupational chemical safety - A real world example with sodium-2-hydroxyethane sulfonate.

Next Generation Risk Assessment (NGRA) is an exposure-led approach to safety assessment that uses New Approach Methodologies (NAMs). Application of NGRA has been largely restricted to assessments of consumer use of cosmetics and is not currently implemented in occupational safety assessments, e.g. under EU REACH. By contrast, a large proportion of regulatory worker safety assessments are underpinned by toxicological studies using experimental animals. Consequently, occupational safety assessment represents an area that would benefit from increasing application of NGRA to safety decision making. Here, a workflow for conducting NGRA under an occupational safety context was developed, which is illustrated with a case study chemical; sodium 2-hydroxyethane sulphonate (sodium isethionate or SI). Exposures were estimated using a standard occupational exposure model following a comprehensive life cycle assessment of SI and considering factory-specific data. Outputs of this model were then used to estimate internal exposures using a Physiologically Based Kinetic (PBK) model, which was constructed with SI specific Absorption, Distribution, Metabolism and Excretion (ADME) data. PBK modelling indicated a worst-case plasma maximum concentration (Cmax) of 0.8 µM across the SI life cycle. SI bioactivity was assessed in a battery of NAMs relevant to systemic, reproductive, and developmental toxicity; a cell stress panel, high throughput transcriptomics in three cell lines (HepG2, HepaRG and MCF-7 cells), pharmacological profiling and specific assays relating to developmental toxicity (Reprotracker and devTOX quickPredict). Points of Departure (PoDs) for SI ranged from 104 to 5044 µM. Cmax values obtained from PBK modelling of occupational exposures to SI were compared with PoDs from the bioactivity assays to derive Bioactivity Exposure Ratios (BERs) which demonstrated the safety for workers exposed to SI under current levels of factory specific risk management. In summary, the tiered and iterative workflow developed here represents an opportunity for integrating non animal approaches for a large subset of substances for which systemic worker safety assessment is required. Such an approach could be followed to ensure that animal testing is only conducted as a "last resort" e.g. under EU REACH.

Are Non-animal Systemic Safety Assessments Protective? A Toolbox and Workflow.

An important question in toxicological risk assessment is whether non-animal new approach methodologies (NAMs) can be used to make safety decisions that are protective of human health, without being overly conservative. In this work, we propose a core NAM toolbox and workflow for conducting systemic safety assessments for adult consumers. We also present an approach for evaluating how protective and useful the toolbox and workflow are by benchmarking against historical safety decisions. The toolbox includes physiologically based kinetic (PBK) models to estimate systemic Cmax levels in humans, and 3 bioactivity platforms, comprising high-throughput transcriptomics, a cell stress panel, and in vitro pharmacological profiling, from which points of departure are estimated. A Bayesian model was developed to quantify the uncertainty in the Cmax estimates depending on how the PBK models were parameterized. The feasibility of the evaluation approach was tested using 24 exposure scenarios from 10 chemicals, some of which would be considered high risk from a consumer goods perspective (eg, drugs that are systemically bioactive) and some low risk (eg, existing food or cosmetic ingredients). Using novel protectiveness and utility metrics, it was shown that up to 69% (9/13) of the low risk scenarios could be identified as such using the toolbox, whilst being protective against all (5/5) the high-risk ones. The results demonstrated how robust safety decisions could be made without using animal data. This work will enable a full evaluation to assess how protective and useful the toolbox and workflow are across a broader range of chemical-exposure scenarios.

Latent Variables Capture Pathway-Level Points of Departure in High-Throughput Toxicogenomic Data.

Estimation of points of departure (PoDs) from high-throughput transcriptomic data (HTTr) represents a key step in the development of next-generation risk assessment (NGRA). Current approaches mainly rely on single key gene targets, which are constrained by the information currently available in the knowledge base and make interpretation challenging as scientists need to interpret PoDs for thousands of genes or hundreds of pathways. In this work, we aimed to address these issues by developing a computational workflow to investigate the pathway concentration-response relationships in a way that is not fully constrained by known biology and also facilitates interpretation. We employed the Pathway-Level Information ExtractoR (PLIER) to identify latent variables (LVs) describing biological activity and then investigated in vitro LVs' concentration-response relationships using the ToxCast pipeline. We applied this methodology to a published transcriptomic concentration-response data set for 44 chemicals in MCF-7 cells and showed that our workflow can capture known biological activity and discriminate between estrogenic and antiestrogenic compounds as well as activity not aligning with the existing knowledge base, which may be relevant in a risk assessment scenario. Moreover, we were able to identify the known estrogen activity in compounds that are not well-established ER agonists/antagonists supporting the use of the workflow in read-across. Next, we transferred its application to chemical compounds tested in HepG2, HepaRG, and MCF-7 cells and showed that PoD estimates are in strong agreement with those estimated using a recently developed Bayesian approach (cor = 0.89) and in weak agreement with those estimated using a well-established approach such as BMDExpress2 (cor = 0.57). These results demonstrate the effectiveness of using PLIER in a concentration-response scenario to investigate pathway activity in a way that is not fully constrained by the knowledge base and to ease the biological interpretation and support the development of an NGRA framework with the ability to improve current risk assessment strategies for chemicals using new approach methodologies.

Implementing organ-on-chip in a next-generation risk assessment of chemicals: a review.

Organ-on-chip (OoC) technology is full of engineering and biological challenges, but it has the potential to revolutionize the Next-Generation Risk Assessment of novel ingredients for consumer products and chemicals. A successful incorporation of OoC technology into the Next-Generation Risk Assessment toolbox depends on the robustness of the microfluidic devices and the organ tissue models used. Recent advances in standardized device manufacturing, organ tissue cultivation and growth protocols offer the ability to bridge the gaps towards the implementation of organ-on-chip technology. Next-Generation Risk Assessment is an exposure-led and hypothesis-driven tiered approach to risk assessment using detailed human exposure information and the application of appropriate new (non-animal) toxicological testing approaches. Organ-on-chip presents a promising in vitro approach by combining human cell culturing with dynamic microfluidics to improve physiological emulation. Here, we critically review commercial organ-on-chip devices, as well as recent tissue culture model studies of the skin, intestinal barrier and liver as the main metabolic organ to be used on-chip for Next-Generation Risk Assessment. Finally, microfluidically linked tissue combinations such as skin-liver and intestine-liver in organ-on-chip devices are reviewed as they form a relevant aspect for advancing toxicokinetic and toxicodynamic studies. We point to recent achievements and challenges to overcome, to advance non-animal, human-relevant safety studies.

A Next-Generation Risk Assessment Case Study for Coumarin in Cosmetic Products.

Next-Generation Risk Assessment is defined as an exposure-led, hypothesis-driven risk assessment approach that integrates new approach methodologies (NAMs) to assure safety without the use of animal testing. These principles were applied to a hypothetical safety assessment of 0.1% coumarin in face cream and body lotion. For the purpose of evaluating the use of NAMs, existing animal and human data on coumarin were excluded. Internal concentrations (plasma Cmax) were estimated using a physiologically based kinetic model for dermally applied coumarin. Systemic toxicity was assessed using a battery of in vitro NAMs to identify points of departure (PoDs) for a variety of biological effects such as receptor-mediated and immunomodulatory effects (Eurofins SafetyScreen44 and BioMap Diversity 8 Panel, respectively), and general bioactivity (ToxCast data, an in vitro cell stress panel and high-throughput transcriptomics). In addition, in silico alerts for genotoxicity were followed up with the ToxTracker tool. The PoDs from the in vitro assays were plotted against the calculated in vivo exposure to calculate a margin of safety with associated uncertainty. The predicted Cmax values for face cream and body lotion were lower than all PoDs with margin of safety higher than 100. Furthermore, coumarin was not genotoxic, did not bind to any of the 44 receptors tested and did not show any immunomodulatory effects at consumer-relevant exposures. In conclusion, this case study demonstrated the value of integrating exposure science, computational modeling and in vitro bioactivity data, to reach a safety decision without animal data.

Implementing Toxicity Testing in the 21st Century (TT21C): Making safety decisions using toxicity pathways, and progress in a prototype risk assessment.

Risk assessment methodologies in toxicology have remained largely unchanged for decades. The default approach uses high dose animal studies, together with human exposure estimates, and conservative assessment (uncertainty) factors or linear extrapolations to determine whether a specific chemical exposure is 'safe' or 'unsafe'. Although some incremental changes have appeared over the years, results from all new approaches are still judged against this process of extrapolating high-dose effects in animals to low-dose exposures in humans. The US National Research Council blueprint for change, entitled Toxicity Testing in the 21st Century: A Vision and Strategy called for a transformation of toxicity testing from a system based on high-dose studies in laboratory animals to one founded primarily on in vitro methods that evaluate changes in normal cellular signalling pathways using human-relevant cells or tissues. More recently, this concept of pathways-based approaches to risk assessment has been expanded by the description of 'Adverse Outcome Pathways' (AOPs). The question, however, has been how to translate this AOP/TT21C vision into the practical tools that will be useful to those expected to make safety decisions. We have sought to provide a practical example of how the TT21C vision can be implemented to facilitate a safety assessment for a commercial chemical without the use of animal testing. To this end, the key elements of the TT21C vision have been broken down to a set of actions that can be brought together to achieve such a safety assessment. Such components of a pathways-based risk assessment have been widely discussed, however to-date, no worked examples of the entire risk assessment process exist. In order to begin to test the process, we have taken the approach of examining a prototype toxicity pathway (DNA damage responses mediated by the p53 network) and constructing a strategy for the development of a pathway based risk assessment for a specific chemical in a case study mode. This contribution represents a 'work-in-progress' and is meant to both highlight concepts that are well-developed and identify aspects of the overall process which require additional development. To guide our understanding of what a pathways-based risk assessment could look like in practice, we chose to work on a case study chemical (quercetin) with a defined human exposure and to bring a multidisciplinary team of chemists, biologists, modellers and risk assessors to work together towards a safety assessment. Our goal was to see if the in vitro dose response for quercetin could be sufficiently understood to construct a TT21C risk assessment without recourse to rodent carcinogenicity study data. The data presented include high throughput pathway biomarkers (p-H2AX, p-ATM, p-ATR, p-Chk2, p53, p-p53, MDM2 and Wip1) and markers of cell-cycle, apoptosis and micronuclei formation, plus gene transcription in HT1080 cells. Eighteen point dose response curves were generated using flow cytometry and imaging to determine the concentrations that resulted in significant perturbation. NOELs and BMDs were compared to the output from biokinetic modelling and the potential for in vitro to in vivo extrapolation explored. A first tier risk assessment was performed comparing the total quercetin concentration in the in vitro systems with the predicted total quercetin concentration in plasma and tissues. The shortcomings of this approach and recommendations for improvement are described. This paper therefore describes the current progress in an ongoing research effort aimed at providing a pathways-based, proof-of-concept in vitro-only safety assessment for a consumer use product.

Integrated in silico approaches for the prediction of Ames test mutagenicity.

The bacterial reverse mutation assay (Ames test) is a biological assay used to assess the mutagenic potential of chemical compounds. In this paper approaches for the development of an in silico mutagenicity screening tool are described. Three individual in silico models, which cover both structure activity relationship methods (SARs) and quantitative structure activity relationship methods (QSARs), were built using three different modelling techniques: (1) an in-house alert model: which uses SAR approach where alerts are generated based on experts judgements; (2) a kNN approach (k-Nearest Neighbours), which is a QSAR model where a prediction is given based on outcomes of its k chemical neighbours; (3) a naive Bayesian model (NB), which is another QSAR model, where a prediction is derived using a Bayesian formula through preselected identified informative chemical features (e.g., physico-chemical, structural descriptors). These in silico models, were compared against two well-known alert models (DEREK and ToxTree) and also against three different consensus approaches (Categorical Bayesian Integration Approach (CBI), Partial Least Squares Discriminate Analysis (PLS-DA) and simple majority vote approach). By applying these integration methods on the validation sets it was shown that both integration models (PLS-DA and CBI) achieved better performance than any of the individual models or consensus obtained by simple majority rule. In conclusion, the recommendation of this paper is that when obtaining consensus predictions for Ames mutagenicity, approaches like PLS-DA or CBI should be the first choice for the integration as compared to a simple majority vote approach.

Compartmentalization of VP16 in cells infected with recombinant herpes simplex virus expressing VP16-green fluorescent protein fusion proteins.

VP16 is an essential structural protein of herpes simplex virus. It plays important roles in immediate-early transcriptional regulation, in the modulation of the activities of other viral components, and in the pathway of assembly and egress of infectious virions. To gain further insight into the compartmentalization of this multifunctional protein we constructed and characterized recombinant viruses expressing VP16 linked to the green fluorescent protein (GFP). These viruses replicate with virtually normal kinetics and yields and incorporate the fusion protein into the virion, resulting in autofluorescent particles. De novo-synthesized VP16-GFP was first detected in a diffuse pattern within the nucleus. Nuclear VP16-GFP was progressively recruited to replication compartments, which coalesced into large globular domains. By 10 to 12 h after infection additional distinct foci containing VP16-GFP could be seen, almost exclusively located at the periphery of the replication compartments. At the same time pronounced accumulation was observed in the cytoplasm, first in a diffuse pattern and then accumulating in vesicle-like compartments which were concentrated in an asymmetric fashion reminiscent of the Golgi. Inhibition of DNA replication resulted in prolonged diffuse nuclear distribution with minimal cytoplasmic accumulation. Treatment with brefeldin disrupted the cytoplasm vesicular pattern, resulting in redistributed large foci. Time-lapse microscopy demonstrated various dynamic features of infection, including the active induction of very long cellular projections (up to 100 microM). Vesicular clusters containing VP16 were transported within projections to the termini, which developed bulbous ends and appeared to embed into the membranes of adjacent uninfected cells.

A C-terminal targeting signal controls differential compartmentalisation of Caenorhabditis elegans host cell factor (HCF) to the nucleus or mitochondria.

HCF-1 (host cell factor 1) is a human protein originally identified as a component of the VP16 transcription complex. A related protein HCF-2 is also present in humans and while at least HCF-1 appears to be required for normal cell growth there is currently little information on the precise cellular role(s) of these proteins. C. elegans contains a single HCF orthologue (CeHCF) which is very closely related to human HCF-2. To contribute to an understanding of the activities of these proteins here we analyse the subcellular localisation of the CeHCF protein in live transgenic worms and in mammalian cells. We constructed a green fluorescent protein (GFP) fusion of CeHCF and studied localisation after ectopic expression under the control of a heat shock protein promoter. The CeHCF-GFP protein accumulated in the cell nuclei at every stage of development and in a wide variety of cell types. Nuclear accumulation with nucleolar sparing was evident on the larvae and adult stages, but not earlier in development in which the protein accumulated diffusely in the nucleoplasm. Surprisingly the same protein accumulated in the mitochondria of a stable HeLa cell line, suggesting a differential localisation of CeHCF in mammalian cells. Furthermore, when overexpressed in transient transfection the CeHCF accumulated in both nuclear and mitochondrial compartments. We have refined the targeting determinants of CeHCF to the last 23 amino acids at the extreme C-terminus and show that they contain interdigitated amino acids involved in both nuclear and mitochondrial targeting. This novel targeting signal is sufficient to redirect HCF-2 into mitochondria. It can also be transferred to an unrelated protein, resulting in its targeting to both the mitochondrial and nuclear compartments.

Primary structure and compartmentalization of Drosophila melanogaster host cell factor.

Human host cell factor-1 (HCF-1) is a large, 2035-residue nuclear protein that interacts with cellular and viral transcription factors. It contains an N-terminal kelch domain, C-terminal fibronectin type III (FnIII) domain, and a central region including tandem repeats which act as cleavage sites. A second human HCF-1 related gene encodes a protein with a high degree of homology in both the N-terminal kelch domain and C-terminal FnIII domain, but lacks the central portion and as a result is considerably smaller at 792 residues. A unique HCF orthologue has been found in Caenorhabditis elegans which is structurally more related to HCF-2 than HCF-1. Here we report the cloning and expression of the single Drosophila melanogaster host cell factor orthologue (dHCF). The dHCF is 1500 residues in size, intermediate between HCF-1 and HCF-2 and contains an N-terminal kelch domain, and C-terminal FnIII domain both of which show a very high degree of identity, and a central region of some 700 residues with more limited homology. Despite containing a central region no repeat-related motifs were apparent. The dHCF is expressed as a single unprocessed polypeptide consistent with the lack of the internal HCF-1 processing sites, and exhibits a predominantly nuclear localization. We show that this nuclear localization is dependent on a bipartite nuclear localization signal at the C-terminus of the protein, which contains a long spacer of 20 amino acids between two basic clusters. Finally, we also show that dHCF is unable to rescue the tsBN67 cell cycle arrest phenotype. These results indicate that dHCF is an orthologue of HCF-1, although both proteins might not be functionally exchangeable.