Building a robust 21st century chemical testing program at the U.S. Environmental Protection Agency: recommendations for strengthening scientific engagement

Environmental disruption of reproductive rhythms

Reproduction is a key biological function requiring a precise synchronization with annual and daily cues to cope with environmental fluctuations. Therefore, humans and animals have developed well-conserved photoneuroendocrine pathways to integrate and process daily and seasonal light signals within the hypothalamic-pituitary-gonadal axis. However, in the past century, industrialization and the modern 24/7 human lifestyle have imposed detrimental changes in natural habitats and rhythms of life. Indeed, exposure to an excessive amount of artificial light at inappropriate timing because of shift work and nocturnal urban lighting, as well as the ubiquitous environmental contamination by endocrine-disrupting chemicals, threaten the integrity of the daily and seasonal timing of biological functions. Here, we review recent epidemiological, field and experimental studies to discuss how light and chemical pollution of the environment can disrupt reproductive rhythms by interfering with the photoneuroendocrine timing system.

Emergence of a techno-legal specialty: Animal tests to assess chemical safety in the UK, 1945-1960

It has been suggested that knowledge domains which emerge within regulatory science represent a compromise between technical knowledge and policy priorities. This article investigates the claim through consideration of the emergence of animal tests to evaluate chemical safety in the UK between 1945 and 1960. During this period there was a proliferation of new chemical-based innovations in consumer products. The situation gave rise to concerns about the potential impact on public health. Solutions required development of a knowledge domain that would fulfil policy requirements, outside the remit of academic science. Lack of consensus in the scientific field gave rise to debate over the best means to collect accurate data. This resulted in emergence of the new specialty of safety testing, in response to political and industrial needs. The socio-political context of this case illustrates the impact that organisational setting can have on shaping knowledge claims.

Animal models of endocrine disruption

Endocrine disrupting chemicals (EDCs) are compounds that alter the structure and function of the endocrine system and may be contributing to disorders of the reproductive, metabolic, neuroendocrine and other complex systems. Typically, these outcomes cannot be modeled in cell-based or other simple systems necessitating the use of animal testing. Appropriate animal model selection is required to effectively recapitulate the human experience, including relevant dosing and windows of exposure, and ensure translational utility and reproducibility. While classical toxicology heavily relies on inbred rats and mice, and focuses on apical endpoints such as tumor formation or birth defects, EDC researchers have used a greater diversity of species to effectively model more subtle but significant outcomes such as changes in pubertal timing, mammary gland development, and social behaviors. Advances in genomics, neuroimaging and other tools are making a wider range of animal models more widely available to EDC researchers.

Functional classification of protein toxins as a basis for bioinformatic screening

Proteins are fundamental to life and exhibit a wide diversity of activities, some of which are toxic. Therefore, assessing whether a specific protein is safe for consumption in foods and feeds is critical. Simple BLAST searches may reveal homology to a known toxin, when in fact the protein may pose no real danger. Another challenge to answer this question is the lack of curated databases with a representative set of experimentally validated toxins. Here we have systematically analyzed over 10,000 manually curated toxin sequences using sequence clustering, network analysis, and protein domain classification. We also developed a functional sequence signature method to distinguish toxic from non-toxic proteins. The current database, combined with motif analysis, can be used by researchers and regulators in a hazard screening capacity to assess the potential of a protein to be toxic at early stages of development. Identifying key signatures of toxicity can also aid in redesigning proteins, so as to maintain their desirable functions while reducing the risk of potential health hazards.

Elucidating environmental dimensions of neurological disorders and disease: Understanding new tools from federal chemical testing programs

BACKGROUND

Federal agencies are making significant investments to advance predictive approaches to evaluate chemical hazards and risks. Environmental Defense Fund (EDF) believes that engagement with the broader scientific community is critical to building and maintaining a strong biological foundation for these approaches.

OBJECTIVES

On June 18-19, 2015, EDF organized a meeting to 1) foster a conversation between federal scientists advancing predictive approaches and environmental health researchers investigating environmental exposures and neurological outcomes, and 2) explore opportunities and challenges for the use of federal chemical high-throughput in vitro screening (HTS) data in hypothesis-driven research toward, ultimately, improved data for public health decision-making.

DISCUSSION

The meeting achieved its objectives. Government scientists showcased their chemical testing programs and vision for how emerging data may be used to meet agency missions. Environmental health researchers shared their experiences using federal HTS data, offered recommendations for strengthening federal HTS platforms, and expressed great interest in continued engagement with evolving federal chemical testing initiatives.

CONCLUSIONS

The meeting provided an invaluable exchange between two scientific communities with a shared interest in protecting public health from harmful environmental exposures, but who have not sufficiently engaged with each other. Discussions identified opportunities and work ahead for the use of HTS data in hypothesis-driven research. Though the meeting focused on neurological outcomes, the purpose, objectives and experience of the meeting are broadly applicable. EDF strongly encourages more discourse and collaboration between federal and non-government scientists working to understand environmental influences on health outcomes.

Prediction of hepatotoxicity for drugs using human pluripotent stem cell-derived hepatocytes

Drug-induced liver toxicity is a main reason for withdrawals of new drugs in late clinical phases and post-launch of the drugs. Thus, hepatotoxicity screening of drug candidates in pre-clinical stage is important for reducing drug attrition rates during the clinical development process. Here, we show commercially available hepatocytes that could be used for early toxicity evaluation of drug candidates. From our hepatic differentiation technology, we obtained highly pure (≥98%) hepatocytes from human embryonic stem cells (hESCs) having mature phenotypes and similar gene expression profiles with those of primary human tissues. Furthermore, we optimized 96-well culture condition of hESC-derived hepatocytes suitable for toxicity tests in vitro. To this end, we demonstrated the efficacy of our optimized hepatocyte model for predicting hepatotoxicity against the Chinese herbal medicines and showed that toxicity patterns from our hepatocyte model was similar to those of human primary cultured hepatocytes. We conclude that toxicity test using our hepatocyte model could be a good alternative cell source for pre-clinical study to predict potential hepatotoxicity in drug discovery industries.

History of EPI Suite™ and future perspectives on chemical property estimation in US Toxic Substances Control Act new chemical risk assessments

Chemical property estimation is a key component in many industrial, academic, and regulatory activities, including in the risk assessment associated with the approximately 1000 new chemical pre-manufacture notices the United States Environmental Protection Agency (US EPA) receives annually. The US EPA evaluates fate, exposure and toxicity under the 1976 Toxic Substances Control Act (amended by the 2016 Frank R. Lautenberg Chemical Safety for the 21^st Century Act), which does not require test data with new chemical applications. Though the submission of data is not required, the US EPA has, over the past 40 years, occasionally received chemical-specific data with pre-manufacture notices. The US EPA has been actively using this and publicly available data to develop and refine predictive computerized models, most of which are housed in EPI Suite™, to estimate chemical properties used in the risk assessment of new chemicals. The US EPA develops and uses models based on (quantitative) structure-activity relationships ([Q]SARs) to estimate critical parameters. As in any evolving field, (Q)SARs have experienced successes, suffered failures, and responded to emerging trends. Correlations of a chemical structure with its properties or biological activity were first demonstrated in the late 19^th century and today have been encapsulated in a myriad of quantitative and qualitative SARs. The development and proliferation of the personal computer in the late 20^th century gave rise to a quickly increasing number of property estimation models, and continually improved computing power and connectivity among researchers via the internet are enabling the development of increasingly complex models.

Biochemical strategies for the detection and detoxification of toxic chemicals in the environment

Addressing the problems related to the widespread presence of an increasing number of chemicals released into the environment by human activities represents one of the most important challenges of this century. In the last few years, to replace the high cost, in terms of time and money, of conventional technologies, the scientific community has directed considerable research towards the development both of new detection systems for the measurement of the contamination levels of chemicals in people’s body fluids and tissue, as well as in the environment, and of new remediation strategies for the removal of such chemicals from the environment, as a means of the prevention of human diseases. New emerging biosensors for the analysis of environmental chemicals have been proposed, including VHH antibodies, that combine the antibody performance with the affinity for small molecules, genetically engineered microorganisms, aptamers and new highly stable enzymes. However, the advances in the field of chemicals monitoring are still far from producing a continuous real-time and on-line system for their detection. Better results have been obtained in the development of strategies which use organisms (microorganisms, plants and animals) or metabolic pathway-based approaches (single enzymes or more complex enzymatic solutions) for the fixation, degradation and detoxification of chemicals in the environment. Systems for enzymatic detoxification and degradation of toxic agents in wastewater from chemical and manufacturing industries, such as ligninolytic enzymes for the treatment of wastewater from the textile industry, have been proposed. Considering the high value of these research studies, in terms of the protection of human health and of the ecosystem, science must play a major role in guiding policy changes in this field.

Improving the prediction of organism-level toxicity through integration of chemical, protein target and cytotoxicity qHTS data

Prediction of compound toxicity is essential because covering the vast chemical space requiring safety assessment using traditional experimentally-based, resource-intensive techniques is impossible. However, such prediction is nontrivial due to the complex causal relationship between compound structure and in vivo harm. Protein target annotations and in vitro experimental outcomes encode relevant bioactivity information complementary to chemicals' structures. This work tests the hypothesis that utilizing three complementary types of data will afford predictive models that outperform traditional models built using fewer data types. A tripartite, heterogeneous descriptor set for 367 compounds was comprised of (a) chemical descriptors, (b) protein target descriptors generated using an algorithm trained on 190 000 ligand-protein interactions from ChEMBL, and (c) descriptors derived from in vitro cell cytotoxicity dose-response data from a panel of human cell lines. 100 random forests classification models for predicting rat LD50 were built using every combination of descriptors. Successive integration of data types improved predictive performance; models built using the full dataset had an average external correct classification rate of 0.82, compared to 0.73-0.80 for models built using two data types and 0.67-0.78 for models built using one. Pairwise comparisons of models trained on the same data showed that including a third data domain on top of chemistry improved average correct classification rate by 1.4-2.4 points, with p-values <0.01. Additionally, the approach enhanced the models' applicability domains and proved useful for generating novel mechanism hypotheses. The use of tripartite heterogeneous bioactivity datasets is a useful technique for improving toxicity prediction. Both protein target descriptors - which have the practical value of being derived in silico - and cytotoxicity descriptors derived from experiment are suitable contributors to such datasets.

High-Content Assay Multiplexing for Toxicity Screening in Induced Pluripotent Stem Cell-Derived Cardiomyocytes and Hepatocytes

Cell-based high-content screening (HCS) assays have become an increasingly attractive alternative to traditional in vitro and in vivo testing in pharmaceutical drug development and toxicological safety assessment. The time- and cost-effectiveness of HCS assays, combined with the organotypic nature of human induced pluripotent stem cell (iPSC)-derived cells, open new opportunities to employ physiologically relevant in vitro model systems to improve screening for potential chemical hazards. In this study, we used two human iPSC types, cardiomyocytes and hepatocytes, to test various high-content and molecular assay combinations for their applicability in a multiparametric screening format. Effects on cardiomyocyte beat frequency were characterized by calcium flux measurements for up to 90 min. Subsequent correlation with intracellular cAMP levels was used to determine if the effects on cardiac physiology were G-protein-coupled receptor dependent. In addition, we utilized high-content cell imaging to simultaneously determine cell viability, mitochondrial integrity, and reactive oxygen species (ROS) formation in both cell types. Kinetic analysis indicated that ROS formation is best detectable 30 min following initial treatment, whereas cytotoxic effects were most stable after 24 h. For hepatocytes, high-content imaging was also used to evaluate cytotoxicity and cytoskeletal integrity, as well as mitochondrial integrity and the potential for lipid accumulation. Lipid accumulation, a marker for hepatic steatosis, was most reliably detected 48 h following treatment with test compounds. Overall, our results demonstrate how a compendium of assays can be utilized for quantitative screening of chemical effects in iPSC cardiomyocytes and hepatocytes and enable rapid and cost-efficient multidimensional biological profiling of toxicity.