Validation of Transcriptomics-Based In Vitro Methods

Prenatal Alcohol Exposure Impairs the Placenta-Cortex Transcriptomic Signature, Leading to Dysregulation of Angiogenic Pathways

Although alcohol consumption during pregnancy is a major cause of behavioral and learning disabilities, most FASD infants are late- or even misdiagnosed due to clinician's difficulties achieving early detection of alcohol-induced neurodevelopmental impairments. Neuroplacentology has emerged as a new field of research focusing on the role of the placenta in fetal brain development. Several studies have reported that prenatal alcohol exposure (PAE) dysregulates a functional placenta-cortex axis, which is involved in the control of angiogenesis and leads to neurovascular-related defects. However, these studies were focused on PlGF, a pro-angiogenic factor. The aim of the present study is to provide the first transcriptomic "placenta-cortex" signature of the effects of PAE on fetal angiogenesis. Whole mouse genome microarrays of paired placentas and cortices were performed to establish the transcriptomic inter-organ "placenta-cortex" signature in control and PAE groups at gestational day 20. Genespring comparison of the control and PAE signatures revealed that 895 and 1501 genes were only detected in one of two placenta-cortex expression profiles, respectively. Gene ontology analysis indicated that 107 of these genes were associated with vascular development, and String protein-protein interaction analysis showed that they were associated with three functional clusters. PANTHER functional classification analysis indicated that "intercellular communication" was a significantly enriched biological process, and 27 genes were encoded for neuroactive ligand/receptors interactors. Protein validation experiments involving Western blot for one ligand-receptor couple (Agt/AGTR1/2) confirmed the transcriptomic data, and Pearson statistical analysis of paired placentas and fetal cortices revealed a negative correlation between placental Atg and cortical AGTR1, which was significantly impacted by PAE. In humans, a comparison of a 38WG control placenta with a 36WG alcohol-exposed placenta revealed low Agt immunolabeling in the syncytiotrophoblast layer of the alcohol case. In conclusion, this study establishes the first transcriptomic placenta-cortex signature of a developing mouse. The data show that PAE markedly unbalances this inter-organ signature; in particular, several ligands and/or receptors involved in the control of angiogenesis. These data support that PAE modifies the existing communication between the two organs and opens new research avenues regarding the impact of placental dysfunction on the neurovascular development of fetuses. Such a signature would present a clinical value for early diagnosis of brain defects in FASD.

A novel human stem cell-based biomarker assay for in vitro assessment of developmental toxicity

BACKGROUND

Testing for developmental toxicity according to the current regulatory guidelines requires large numbers of animals, making these tests very resource intensive, time-consuming, and ethically debatable. Over the past decades, several alternative in vitro assays have been developed, but these often suffered from low predictability and the inability to provide a mechanistic understanding of developmental toxicity.

METHODS

To identify embryotoxic compounds, we developed a human induced pluripotent stem cells (hiPSCs)-based biomarker assay. The assay is based on the differentiation of hiPSCs into functional cardiomyocytes and hepatocytes. Proper stem cell differentiation is investigated by morphological profiling and assessment of time-dependent expression patterns of cell-specific biomarkers. In this system, a decrease in the expression of the biomarker genes and morphology disruption of the differentiated cells following compound treatment indicated teratogenicity.

RESULTS

The hiPSCs-based biomarker assay was validated with 21 well-established in vivo animal teratogenic and non-teratogenic compounds during cardiomyocyte and hepatocyte differentiation. The in vivo teratogenic compounds (e.g., thalidomide and valproic acid) markedly disrupted morphology, functionality, and the expression pattern of the biomarker genes in either one or both cell types. Non-teratogenic chemicals generally had no effect on the morphology of differentiated cells, nor on the expression of the biomarker genes. Compared to the in vivo classification, the assay achieved high accuracy (91%), sensitivity (91%), and specificity (90%).

CONCLUSION

The assay, which we named ReproTracker®, is a state-of-the-art in vitro method that can identify the teratogenicity potential of new pharmaceuticals and chemicals and signify the outcome of in vivo test systems.

In Silico Approaches In Carcinogenicity Hazard Assessment: Current Status and Future Needs

Historically, identifying carcinogens has relied primarily on tumor studies in rodents, which require enormous resources in both money and time. In silico models have been developed for predicting rodent carcinogens but have not yet found general regulatory acceptance, in part due to the lack of a generally accepted protocol for performing such an assessment as well as limitations in predictive performance and scope. There remains a need for additional, improved in silico carcinogenicity models, especially ones that are more human-relevant, for use in research and regulatory decision-making. As part of an international effort to develop in silico toxicological protocols, a consortium of toxicologists, computational scientists, and regulatory scientists across several industries and governmental agencies evaluated the extent to which in silico models exist for each of the recently defined 10 key characteristics (KCs) of carcinogens. This position paper summarizes the current status of in silico tools for the assessment of each KC and identifies the data gaps that need to be addressed before a comprehensive in silico carcinogenicity protocol can be developed for regulatory use.

Renal Transcriptomics Reveals the Carcinogenic Mechanism of Ethyl Carbamate in Musalais

INTRODUCTION

Musalais is a traditional fermented wine produced in southern Xinjiang (a province of China) and is protected as a form of national intangible cultural heritage. However, ethyl carbamate (EC), which is naturally produced during the fermentation process, has been shown to induce carcinogenesis and was classified as a group 2A carcinogen by The World Health Organization's International Agency for Research on Cancer.

METHODS

In this work, rats were treated with musalais containing EC at varying contents (0.1, 1, or 10 mg/kg). To evaluate the toxicity of EC in musalais, the liver and kidney of the rats were subjected to transcriptomics sequencing. Differentially expressed genes (DEGs) between treated and untreated rats were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed on these genes to investigate the biological functions affected by EC in musalais.

RESULTS

The results demonstrated that high EC content in musalais is possibly involved in the regulation of cytochrome P450 metabolism, chemical carcinogenesis, metabolism of xenobiotics by cytochrome P450, Wnt signaling, and p53 signaling by targeting Mgst1, Gstp1, Gsta5, Gsta1, Adh1, Gsta2, and Ccnd1, thereby inducing cancer.

CONCLUSION

The present work predicted the potential carcinogenic mechanism of high EC content in musalais, providing a reference for its safety evaluation.

Comparison of Approaches for Determining Bioactivity Hits from High-Dimensional Profiling Data

Phenotypic profiling assays are untargeted screening assays that measure a large number (hundreds to thousands) of cellular features in response to a stimulus and often yield diverse and unanticipated profiles of phenotypic effects, leading to challenges in distinguishing active from inactive treatments. Here, we compare a variety of different strategies for hit identification in imaging-based phenotypic profiling assays using a previously published Cell Painting data set. Hit identification strategies based on multiconcentration analysis involve curve fitting at several levels of data aggregation (e.g., individual feature level, aggregation of similarly derived features into categories, and global modeling of all features) and on computed metrics (e.g., Euclidean and Mahalanobis distance metrics and eigenfeatures). Hit identification strategies based on single-concentration analysis included measurement of signal strength (e.g., total effect magnitude) and correlation of profiles among biological replicates. Modeling parameters for each approach were optimized to retain the ability to detect a reference chemical with subtle phenotypic effects while limiting the false-positive rate to 10%. The percentage of test chemicals identified as hits was highest for feature-level and category-based approaches, followed by global fitting, whereas signal strength and profile correlation approaches detected the fewest number of active hits at the fixed false-positive rate. Approaches involving fitting of distance metrics had the lowest likelihood for identifying high-potency false-positive hits that may be associated with assay noise. Most of the methods achieved a 100% hit rate for the reference chemical and high concordance for 82% of test chemicals, indicating that hit calls are robust across different analysis approaches.

Toward Rigorous Materials Production: New Approach Methodologies Have Extensive Potential to Improve Current Safety Assessment Practices

Advanced material development, including at the nanoscale, comprises costly and complex challenges coupled to ensuring human and environmental safety. Governmental agencies regulating safety have announced interest toward acceptance of safety data generated under the collective term New Approach Methodologies (NAMs), as such technologies/approaches offer marked potential to progress the integration of safety testing measures during innovation from idea to product launch of nanomaterials. Divided in overall eight main categories, searchable databases for grouping and read across purposes, exposure assessment and modeling, in silico modeling of physicochemical structure and hazard data, in vitro high-throughput and high-content screening assays, dose-response assessments and modeling, analyses of biological processes and toxicity pathways, kinetics and dose extrapolation, consideration of relevant exposure levels and biomarker endpoints typify such useful NAMs. Their application generally agrees with articulated stakeholder needs for improvement of safety testing procedures. They further fit for inclusion and add value in nanomaterials risk assessment tools. Overall 37 of 50 evaluated NAMs and tiered workflows applying NAMs are recommended for considering safer-by-design innovation, including guidance to the selection of specific NAMs in the eight categories. An innovation funnel enriched with safety methods is ultimately proposed under the central aim of promoting rigorous nanomaterials innovation.

Development of a neural rosette formation assay (RoFA) to identify neurodevelopmental toxicants and to characterize their transcriptome disturbances

The first in vitro tests for developmental toxicity made use of rodent cells. Newer teratology tests, e.g. developed during the ESNATS project, use human cells and measure mechanistic endpoints (such as transcriptome changes). However, the toxicological implications of mechanistic parameters are hard to judge, without functional/morphological endpoints. To address this issue, we developed a new version of the human stem cell-based test STOP-tox_(UKN). For this purpose, the capacity of the cells to self-organize to neural rosettes was assessed as functional endpoint: pluripotent stem cells were allowed to differentiate into neuroepithelial cells for 6 days in the presence or absence of toxicants. Then, both transcriptome changes were measured (standard STOP-tox_(UKN)) and cells were allowed to form rosettes. After optimization of staining methods, an imaging algorithm for rosette quantification was implemented and used for an automated rosette formation assay (RoFA). Neural tube toxicants (like valproic acid), which are known to disturb human development at stages when rosette-forming cells are present, were used as positive controls. Established toxicants led to distinctly different tissue organization and differentiation stages. RoFA outcome and transcript changes largely correlated concerning (1) the concentration-dependence, (2) the time dependence, and (3) the set of positive hits identified amongst 24 potential toxicants. Using such comparative data, a prediction model for the RoFA was developed. The comparative analysis was also used to identify gene dysregulations that are particularly predictive for disturbed rosette formation. This 'RoFA predictor gene set' may be used for a simplified and less costly setup of the STOP-tox_(UKN) assay.

Genetic toxicology in silico protocol

In silico toxicology (IST) approaches to rapidly assess chemical hazard, and usage of such methods is increasing in all applications but especially for regulatory submissions, such as for assessing chemicals under REACH as well as the ICH M7 guideline for drug impurities. There are a number of obstacles to performing an IST assessment, including uncertainty in how such an assessment and associated expert review should be performed or what is fit for purpose, as well as a lack of confidence that the results will be accepted by colleagues, collaborators and regulatory authorities. To address this, a project to develop a series of IST protocols for different hazard endpoints has been initiated and this paper describes the genetic toxicity in silico (GIST) protocol. The protocol outlines a hazard assessment framework including key effects/mechanisms and their relationships to endpoints such as gene mutation and clastogenicity. IST models and data are reviewed that support the assessment of these effects/mechanisms along with defined approaches for combining the information and evaluating the confidence in the assessment. This protocol has been developed through a consortium of toxicologists, computational scientists, and regulatory scientists across several industries to support the implementation and acceptance of in silico approaches.

3S - Systematic, systemic, and systems biology and toxicology

A biological system is more than the sum of its parts - it accomplishes many functions via synergy. Deconstructing the system down to the molecular mechanism level necessitates the complement of reconstructing functions on all levels, i.e., in our conceptualization of biology and its perturbations, our experimental models and computer modelling. Toxicology contains the somewhat arbitrary subclass "systemic toxicities"; however, there is no relevant toxic insult or general disease that is not systemic. At least inflammation and repair are involved that require coordinated signaling mechanisms across the organism. However, the more body components involved, the greater the challenge to reca-pitulate such toxicities using non-animal models. Here, the shortcomings of current systemic testing and the development of alternative approaches are summarized. We argue that we need a systematic approach to integrating existing knowledge as exemplified by systematic reviews and other evidence-based approaches. Such knowledge can guide us in modelling these systems using bioengineering and virtual computer models, i.e., via systems biology or systems toxicology approaches. Experimental multi-organ-on-chip and microphysiological systems (MPS) provide a more physiological view of the organism, facilitating more comprehensive coverage of systemic toxicities, i.e., the perturbation on organism level, without using substitute organisms (animals). The next challenge is to establish disease models, i.e., micropathophysiological systems (MPPS), to expand their utility to encompass biomedicine. Combining computational and experimental systems approaches and the chal-lenges of validating them are discussed. The suggested 3S approach promises to leverage 21st century technology and systematic thinking to achieve a paradigm change in studying systemic effects.