Assessment of Drug-Induced Liver Injury through Cell Morphology and Gene Expression Analysis.

Drug-induced liver injury (DILI) is a significant concern in drug development, often leading to drug withdrawal. Although many studies aim to identify biomarkers and gene/pathway signatures related to liver toxicity and aim to predict DILI compounds, this remains a challenge in drug discovery. With a strong development of high-content screening/imaging (HCS/HCI) for phenotypic screening, we explored the morphological cell perturbations induced by DILI compounds. In the first step, cell morphological signatures were associated with two datasets of DILI chemicals (DILIRank and eTox). The mechanisms of action were then analyzed for chemicals having transcriptomics data and sharing similar morphological perturbations. Signaling pathways associated with liver toxicity (cell cycle, cell growth, apoptosis, ...) were then captured, and a hypothetical relation between cell morphological perturbations and gene deregulation was illustrated within our analysis. Finally, using the cell morphological signatures, machine learning approaches were developed to predict chemicals with a potential risk of DILI. Some models showed relevant performance with validation set balanced accuracies between 0.645 and 0.739. Overall, our findings demonstrate the utility of combining HCI with transcriptomics data to identify the morphological and gene expression signatures related to DILI chemicals. Moreover, our protocol could be extended to other toxicity end points, offering a promising avenue for comprehensive toxicity assessment in drug discovery.

Applying genomics in regulatory toxicology: a report of the ECETOC workshop on omics threshold on non-adversity.

In a joint effort involving scientists from academia, industry and regulatory agencies, ECETOC's activities in Omics have led to conceptual proposals for: (1) A framework that assures data quality for reporting and inclusion of Omics data in regulatory assessments; and (2) an approach to robustly quantify these data, prior to interpretation for regulatory use. In continuation of these activities this workshop explored and identified areas of need to facilitate robust interpretation of such data in the context of deriving points of departure (POD) for risk assessment and determining an adverse change from normal variation. ECETOC was amongst the first to systematically explore the application of Omics methods, now incorporated into the group of methods known as New Approach Methodologies (NAMs), to regulatory toxicology. This support has been in the form of both projects (primarily with CEFIC/LRI) and workshops. Outputs have led to projects included in the workplan of the Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) group of the Organisation for Economic Co-operation and Development (OECD) and to the drafting of OECD Guidance Documents for Omics data reporting, with potentially more to follow on data transformation and interpretation. The current workshop was the last in a series of technical methods development workshops, with a sub-focus on the derivation of a POD from Omics data. Workshop presentations demonstrated that Omics data developed within robust frameworks for both scientific data generation and analysis can be used to derive a POD. The issue of noise in the data was discussed as an important consideration for identifying robust Omics changes and deriving a POD. Such variability or "noise" can comprise technical or biological variation within a dataset and should clearly be distinguished from homeostatic responses. Adverse outcome pathways (AOPs) were considered a useful framework on which to assemble Omics methods, and a number of case examples were presented in illustration of this point. What is apparent is that high dimension data will always be subject to varying processing pipelines and hence interpretation, depending on the context they are used in. Yet, they can provide valuable input for regulatory toxicology, with the pre-condition being robust methods for the collection and processing of data together with a comprehensive description how the data were interpreted, and conclusions reached.

Versatile and flexible microfluidic qPCR test for high-throughput SARS-CoV-2 and cellular response detection in nasopharyngeal swab samples.

The emergence and quick spread of SARS-CoV-2 has pointed at a low capacity response for testing large populations in many countries, in line of material, technical and staff limitations. The traditional RT-qPCR diagnostic test remains the reference method and is by far the most widely used test. These assays are limited to a few probe sets, require large sample PCR reaction volumes, along with an expensive and time-consuming RNA extraction step. Here we describe a quantitative nanofluidic assay that overcomes some of these shortcomings, based on the BiomarkTM instrument from Fluidigm. This system offers the possibility of performing 4608 qPCR end-points in a single run, equivalent to 192 clinical samples combined with 12 pairs of primers/probe sets in duplicate, thus allowing the monitoring of SARS-CoV-2 including the detection of specific SARS-CoV-2 variants, as well as the detection other pathogens and/or host cellular responses (virus receptors, response markers, microRNAs). The 10 nL-range volume of BiomarkTM reactions is compatible with sensitive and reproducible reactions that can be easily and cost-effectively adapted to various RT-qPCR configurations and sets of primers/probe. Finally, we also evaluated the use of inactivating lysis buffers composed of various detergents in the presence or absence of proteinase K to assess the compatibility of these buffers with a direct reverse transcription enzymatic step and we propose several protocols, bypassing the need for RNA purification. We advocate that the combined utilization of an optimized processing buffer and a high-throughput real-time PCR device would contribute to improve the turn-around-time to deliver the test results to patients and increase the SARS-CoV-2 testing capacities.

Exploring the Use of Compound-Induced Transcriptomic Data Generated From Cell Lines to Predict Compound Activity Toward Molecular Targets.

Pharmaceutical or phytopharmaceutical molecules rely on the interaction with one or more specific molecular targets to induce their anticipated biological responses. Nonetheless, these compounds are also prone to interact with many other non-intended biological targets, also known as off-targets. Unfortunately, off-target identification is difficult and expensive. Consequently, QSAR models predicting the activity on a target have gained importance in drug discovery or in the de-risking of chemicals. However, a restricted number of targets are well characterized and hold enough data to build such in silico models. A good alternative to individual target evaluations is to use integrative evaluations such as transcriptomics obtained from compound-induced gene expression measurements derived from cell cultures. The advantage of these particular experiments is to capture the consequences of the interaction of compounds on many possible molecular targets and biological pathways, without having any constraints concerning the chemical space. In this work, we assessed the value of a large public dataset of compound-induced transcriptomic data, to predict compound activity on a selection of 69 molecular targets. We compared such descriptors with other QSAR descriptors, namely the Morgan fingerprints (similar to extended-connectivity fingerprints). Depending on the target, active compounds could show similar signatures in one or multiple cell lines, whether these active compounds shared similar or different chemical structures. Random forest models using gene expression signatures were able to perform similarly or better than counterpart models built with Morgan fingerprints for 25% of the target prediction tasks. These performances occurred mostly using signatures produced in cell lines showing similar signatures for active compounds toward the considered target. We show that compound-induced transcriptomic data could represent a great opportunity for target prediction, allowing to overcome the chemical space limitation of QSAR models.

'All In': a pragmatic framework for COVID-19 testing and action on a global scale.

Current demand for SARS-CoV-2 testing is straining material resource and labor capacity around the globe. As a result, the public health and clinical community are hindered in their ability to monitor and contain the spread of COVID-19. Despite broad consensus that more testing is needed, pragmatic guidance toward realizing this objective has been limited. This paper addresses this limitation by proposing a novel and geographically agnostic framework (the 4Ps framework) to guide multidisciplinary, scalable, resource-efficient, and achievable efforts toward enhanced testing capacity. The 4Ps (Prioritize, Propagate, Partition, and Provide) are described in terms of specific opportunities to enhance the volume, diversity, characterization, and implementation of SARS-CoV-2 testing to benefit public health. Coordinated deployment of the strategic and tactical recommendations described in this framework has the potential to rapidly expand available testing capacity, improve public health decision-making in response to the COVID-19 pandemic, and/or to be applied in future emergent disease outbreaks.

De novo generation of hit-like molecules from gene expression signatures using artificial intelligence.

Finding new molecules with a desired biological activity is an extremely difficult task. In this context, artificial intelligence and generative models have been used for molecular de novo design and compound optimization. Herein, we report a generative model that bridges systems biology and molecular design, conditioning a generative adversarial network with transcriptomic data. By doing so, we can automatically design molecules that have a high probability to induce a desired transcriptomic profile. As long as the gene expression signature of the desired state is provided, this model is able to design active-like molecules for desired targets without any previous target annotation of the training compounds. Molecules designed by this model are more similar to active compounds than the ones identified by similarity of gene expression signatures. Overall, this method represents an alternative approach to bridge chemistry and biology in the long and difficult road of drug discovery.

Stacked Generalization with Applicability Domain Outperforms Simple QSAR on in Vitro Toxicological Data.

The development of in silico tools able to predict bioactivity and toxicity of chemical substances is a powerful solution envisioned to assess toxicity as early as possible. To enable the development of such tools, the ToxCast program has generated and made publicly available in vitro bioactivity data for thousands of compounds. The goal of the present study is to characterize and explore the data from ToxCast in terms of Machine Learning capability. For this, a large scale analysis on the entire database has been performed to build models to predict bioactivities measured in in vitro assays. Simple classical QSAR algorithms (ANN, SVM, LDA, random forest, and Bayesian) were first applied on the data, and the results of these algorithms suggested that they do not seem to be well-suited for data sets with a high proportion of inactive compounds. The study then showed for the first time that the use of an ensemble method named "Stacked generalization" could improve the model performance on this type of data. Indeed, for 61% of 483 models, the Stacked method led to models with higher performance. Moreover, the combination of this ensemble method with an applicability domain filter allows one to assess the reliability of the predictions for further compound prioritization. In particular we showed that for 50% of the models, the ROC score is better if we do not consider the compounds that are not within the applicability domain.

Inter-laboratory optimization of protein extraction, separation, and fluorescent detection of endogenous rice allergens.

In rice, several allergens have been identified such as the non-specific lipid transfer protein-1, the α-amylase/trypsin-inhibitors, the α-globulin, the 33 kDa glyoxalase I (Gly I), the 52-63 kDa globulin, and the granule-bound starch synthetase. The goal of the present study was to define optimal rice extraction and detection methods that would allow a sensitive and reproducible measure of several classes of known rice allergens. In a three-laboratory ring-trial experiment, several protein extraction methods were first compared and analyzed by 1D multiplexed SDS-PAGE. In a second phase, an inter-laboratory validation of 2D-DIGE analysis was conducted in five independent laboratories, focusing on three rice allergens (52 kDa globulin, 33 kDa glyoxalase I, and 14-16 kDa α-amylase/trypsin inhibitor family members). The results of the present study indicate that a combination of 1D multiplexed SDS-PAGE and 2D-DIGE methods would be recommended to quantify the various rice allergens.

Contribution of new technologies to characterization and prediction of adverse effects.

Identification of the potential hazards of chemicals has traditionally relied on studies in laboratory animals where changes in clinical pathology and histopathology compared to untreated controls defined an adverse effect. In the past decades, increased consistency in the definition of adversity with chemically-induced effects in laboratory animals, as well as in the assessment of human relevance has been reached. More recently, a paradigm shift in toxicity testing has been proposed, mainly driven by concerns over animal welfare but also thanks to the development of new methods. Currently, in vitro approaches, toxicogenomic technologies and computational tools, are available to provide mechanistic insight in toxicological Mode of Action (MOA) of the adverse effects observed in laboratory animals. The vision described as Tox21c (Toxicity Testing in the 21st century) aims at predicting in vivo toxicity using a bottom-up-approach, starting with understanding of MOA based on in vitro data to ultimately predict adverse effects in humans. At present, a practical application of the Tox21c vision is still far away. While moving towards toxicity prediction based on in vitro data, a stepwise reduction of in vivo testing is foreseen by combining in vitro with in vivo tests. Furthermore, newly developed methods will also be increasingly applied, in conjunction with established methods in order to gain trust in these new methods. This confidence is based on a critical scientific prerequisite: the establishment of a causal link between data obtained with new technologies and adverse effects manifested in repeated-dose in vivo toxicity studies. It is proposed to apply the principles described in the WHO/IPCS framework of MOA to obtain this link. Finally, an international database of known MOAs obtained in laboratory animals using data-rich chemicals will facilitate regulatory acceptance and could further help in the validation of the toxicity pathway and adverse outcome pathway concepts.

Comparison of early morphological and molecular changes induced by 17-alpha-methyltestosterone and estradiol benzoate in the rat ovary.

Repeated exposure to 17-α-methyltestosterone (17MT) and estradiol benzoate (EB) for 28 or 90 days in rats induce similar ovarian atrophy. The objective of the present work was to identify and compare the early effects induced by 17MT and EB on the ovary using molecular and histopathological tools. Female rats were evaluated after 1, 3 or 7 days following an oral exposure by gavage at a daily dose of 600 mg/kg/day for 17MT and 5 mg/kg/day for EB. All animals were found to be acyclic after 3 or 7 days of treatment with 17MT and EB. Histopathological changes were present in the ovary, uterus, vagina and mammary gland after both treatments. Ovarian atrophy known as the long term effect of 17MT and EB was not yet detected after 7 days of treatment. But non regressive corpora lutea and cystic follicles were identically observed in the ovary of 17MT and EB treated females. Both compounds induced a decrease of LH transcripts together with an increase of plasma progesterone and prolactin levels. Differences in the profile of regulation of the aromatase were noted after 1 and 3 days of treatment in 17MT treated animals (upregulated) when compared to EB treated animals (downregulated). In summary, we have shown that despite the different nature of hormonal activity, EB and 17MT induce very early endocrine perturbation which presents several similarities. Our work indicated that the detection of early key hormonal markers in short term studies can help to predict the adverse long term effects on target tissues.

Potential new targets involved in 1,3-dinitrobenzene induced testicular toxicity.

1,3-Dinitrobenzene (DNB) causes testicular injury, particularly to Sertoli cells, and induces apoptosis in the surrounding germinal cells in rodents; however, the mechanisms causing this toxicity are poorly understood. Our studies, using standard and molecular tools, were conducted to better understand the pathogenesis of the testicular effects. Four daily oral doses of 0.1-8mg/kg/day caused marked testicular lesions in rats from 4mg/kg/day. Global transcriptomics revealed cell cycle and cell death as the major biological processes affected with the expression of genes associated with cell cycle progression ("mitotic roles of polo-like kinase") being particularly altered. In a single dose time course study (4mg/kg), no adverse changes were recorded; however, in contrast to the data from the multiple dose study, plasma testosterone and testicular steroidogenesis-related gene expression were affected. These steroid hormone effects were confirmed in vitro using the H295R steroidogenesis assay. With this global approach we show that DNB not only induces apoptosis and interferes with cell cycle in the testes but that DNB can also modulate steroid hormone biosynthesis, suggesting an interference with the endocrine system. However, the contribution of the endocrine changes to the severe testicular lesions is presently unknown and requires further investigation.

A molecular and phenotypic integrative approach to identify a no-effect dose level for antiandrogen-induced testicular toxicity.

The safety assessment of chemicals for humans relies on identifying no-observed adverse effect levels (NOAELs) in animal toxicity studies using standard methods. With the advent of high information content technologies, especially microarrays, it is pertinent to determine the impact of molecular data on the NOAELs. Consequently, we conducted an integrative study to identify a no-transcriptomic effect dose using microarray analyses coupled with quantitative reverse transcriptase PCR (RT-qPCR) and determined how this correlated with the NOAEL. We assessed the testicular effects of the antiandrogen, flutamide (FM), in a rat 28-day toxicity study using doses of 0.2-30 mg/kg/day. Plasma testosterone levels and testicular histopathology indicated a NOAEL of 1 mg/kg/day. A no-effect dose of 0.2 mg/kg/day was established based on molecular data relevant to the phenotypic changes. We observed differential gene expression starting from 1 mg/kg/day and a deregulation of more than 1500 genes at 30 mg/kg/day. Dose-related changes were identified for the major pathways (e.g., fatty acid metabolism) associated with the testicular lesion (Leydig cell hyperplasia) that were confirmed by RT-qPCR. These data, along with protein accumulation profiles and FM metabolite concentrations in testis, supported the no-effect dose of 0.2 mg/kg/day. Furthermore, the microarray data indicated a dose-dependent change in the fatty acid catabolism pathway, a biological process described for the first time to be affected by FM in testicular tissue. In conclusion, the present data indicate the existence of a transcriptomic threshold, which must be exceeded to progress from a normal state to an adaptative state and subsequently to adverse toxicity.

Investigation of endogenous soybean food allergens by using a 2-dimensional gel electrophoresis approach.

As part of the safety assessment of genetically modified (GM) soybean, 2-dimensional gel electrophoresis analyses were performed with the isoxaflutole and glyphosate tolerant soybean FG72, its non-GM near-isogenic counterpart (Jack) and three commercial non-GM soybean lines. The objective was to compare the known endogenous human food allergens in seeds in the five different soybean lines in order to evaluate any potential unintended effect(s) of the genetic modification. In total, 37 protein spots representing five well known soybean food allergen groups were quantified in each genotype. Qualitatively, all the allergenic proteins were detected in the different genetic backgrounds. Quantitatively, among 37 protein spots, the levels of accumulation of three allergens were slightly lower in the GM soybean than in the non-GM counterparts. Specifically, while the levels of two of these three allergens fell within the normal range of variation observed in the four non-GM varieties, the level of the third allergen was slightly below the normal range. Overall, there was no significant increase in the level of allergens in FG72 soybean seeds. Therefore, the FG72 soybean can be considered as safe as its non-GM counterpart with regards to endogenous allergenicity. Additional research is needed to evaluate the biological variability in the levels of endogenous soybean allergens and the correlation between level of allergens and allergenic potential in order to improve the interpretation of these data in the safety assessment of GM soybean context.

Safety evaluation of the double mutant 5-enol pyruvylshikimate-3-phosphate synthase (2mEPSPS) from maize that confers tolerance to glyphosate herbicide in transgenic plants.

Glyphosate tolerance can be conferred by decreasing the herbicide's ability to inhibit the enzyme 5-enol pyruvylshikimate-3-phosphate synthase, which is essential for the biosynthesis of aromatic amino acids in all plants, fungi, and bacteria. Glyphosate tolerance is based upon the expression of the double mutant 5-enol pyruvylshikimate-3-phosphate synthase (2mEPSPS) protein. The 2mEPSPS protein, with a lower binding affinity for glyphosate, is highly resistant to the inhibition by glyphosate and thus allows sufficient enzyme activity for the plants to grow in the presence of herbicides that contain glyphosate. Based on both a review of published literature and experimental studies, the potential safety concerns related to the transgenic 2mEPSPS protein were assessed. The safety evaluation supports that the expressed protein is innocuous. The 2mEPSPS enzyme does not possess any of the properties associated with known toxins or allergens, including a lack of amino acid sequence similarity to known toxins and allergens, a rapid degradation in simulated gastric and intestinal fluids, and no adverse effects in mice after intravenous or oral administration (at 10 or 2000 mg/kg body weight, respectively). In conclusion, there is a reasonable certainty of no harm resulting from the inclusion of the 2mEPSPS protein in human food or in animal feed.

Standard and molecular NOAELs for rat testicular toxicity induced by flutamide.

An important step in the safety assessment of chemicals for humans is to determine the no observed adverse effect level (NOAEL) in toxicity studies conducted in animal models. With the increasing use of molecular tools in toxicity studies, a question often posed is how a NOAEL derived from molecular data compares to a NOAEL established using standard methods. The objective of the present study was to address this question when considering testicular toxicity. To do this, we assessed the effects of the reference antiandrogen flutamide on rat testes in a standard 28-day toxicity study using doses of 0.04-150 mg/kg/day. At necropsy, blood samples were collected for testosterone measurements. The testes were collected for histopathological assessment as well as for the evaluation of gene expression changes using quantitative PCR analyses. Results showed that increases in plasma testosterone level and Leydig cell hyperplasia were detected from 6 mg/kg/day. An alteration in the level of accumulation of a selection of genes was also detected from 6 mg/kg/day. This was the case for genes functionally associated with the testicular lesion, such as lipid metabolism and cell death/cell proliferation, as well as for genes not functionally associated with the lesion. Contrary to the misgivings, these data show that, using a standard 28-day toxicity study and a well-characterized adverse effect, the NOAEL based on transcript changes is similar to the NOAELs based on testosterone levels and histopathological examination.

Evaluation of the antiandrogenic effects of flutamide, DDE, and linuron in the weanling rat assay using organ weight, histopathological, and proteomic approaches.

The Organization for Economic Cooperation and Development (OECD) is currently funding the validation of the Hershberger assay as a rapid in vivo means of identifying (anti-) androgens. However, as the assay measures weight changes in the androgen-sensitive tissues of castrated rats, the evaluation of the androgen-stimulated intact weanling as a more ethical model to use in the assay has been requested. As part of the OECD validation exercise two weak antiandrogens, 1,1-dichloro-2,2-bis(4 chlorophenyl)ethane (DDE) and linuron (LIN), were investigated in our laboratory at several dose levels in the testosterone propionate (TP)-stimulated weanling using flutamide (FM) as a positive control. In addition to weight measurements (sex accessory tissues [SATs], epididymides, and testes), histopathological assessment of the seminal vesicles, prostate, and testes was conducted for vehicle control, TP-stimulated, and TP-stimulated animals treated with FM or the top dose level of DDE or LIN. The modulation of a novel prostate protein associated with apoptosis, L-amino acid oxidase (LAO), was evaluated in these same treatment groups. Our gravimetric data (supported by the histopathology data) indicated that the weanling assay can detect SAT and epididymal weight changes induced by the antiandrogens evaluated. Inconsistent and variable data were recorded for the testicular weight and histopathological effects, suggesting that the testis is of little value in the identification of antiandrogens using this model. Three isoforms of LAO were identified, and all were regulated by TP. Modulation of LAO by the antiandrogens indicated that this protein could be a biomarker for endocrine disruption in male rodents.

Correlation between protein accumulation profiles and conventional toxicological findings using a model antiandrogenic compound, flutamide.

In conventional rodent toxicity studies the characterization of the adverse effects of a chemical relies primarily on gravimetric, and histopathological data. The aim of this study was to evaluate if the use of two-dimensional gel electrophoresis could generate protein accumulation profiles, which were in accordance with conventional toxicological findings by investigating a model antiandrogen, flutamide (FM), whose toxic effects, as measured using standard approaches, are well characterized. Male Sprague-Dawley rats were orally exposed to FM (0, 6, 30, and 150 mg/kg/day) for 28 days. The expected inhibition of androgen-dependent tissue stimulation, increased luteinizing hormone and testosterone plasma levels, and Leydig cell hyperplasia were observed. Changes in testicular protein accumulation profiles were evaluated in rats exposed to 150 mg/kg/day FM. Several proteins involved in steroidogenesis (e.g., StAR, ApoE, Hmgcs1, Idi1), cell cycle, and cancer (e.g., Ddx1, Hspd1) were modulated by FM, and these data provided molecular evidence for the hormonal and testicular histopathology changes recorded. Changes in proteins associated with spermatogenesis were also recorded, and these are discussed within the context of the testicular phenotype observed following FM treatment (i.e., normal spermatogenesis but Leydig cell hyperplasia). Overall, our data indicate that the combination of conventional toxicology measurements with omic observations has the potential to improve our global understanding of the toxicity of a compound.

Protein profiling of rat ventral prostate following chronic finasteride administration: identification and localization of a novel putative androgen-regulated protein.

To better understand the effects of antiandrogens on the prostate, we investigated the changes in the proteome of rat ventral prostate (VP) following treatment with a well characterized 5alpha-reductase inhibitor, finasteride. Sprague-Dawley rats were treated daily by gavage with finasteride at 0, 1, 5, 25, and 125 mg/kg/day. Changes in plasma hormone levels as well as the weight and histology of sex accessory tissues were determined after 28 days of treatment and showed a dose-related decrease of VP weights together with a marked atrophy of the tissue visible at the macroscopic and microscopic levels. In addition, significant reductions in seminal vesicle and epididymis weights were noted. VP proteins were analyzed by two-dimensional gel electrophoresis: 37 proteins, mainly involved in protein synthesis, processing, and cellular trafficking and in metabolism, detoxification, and oxidative stress, were identified as modulated by finasteride. The prominent feature of this study is the demonstration of finasteride dose-dependent up-regulation of a protein similar to l-amino-acid oxidase 1 (Lao1). An up-regulation of this protein was also observed with the antiandrogen flutamide. Lao1 expression occurred as early as 48 h after antiandrogen administration and persisted throughout the treatment duration. Immunohistochemistry showed that this protein was only detectable in epithelial cells and secretory vesicles. Altogether these data point to a potential use of Lao1 to reveal antiandrogen-induced prostate injury.

Polar PIN localization directs auxin flow in plants.

Polar flow of the phytohormone auxin requires plasma membrane-associated PIN proteins and underlies multiple developmental processes in plants. Here we address the importance of the polarity of subcellular PIN localization for the directionality of auxin transport in Arabidopsis thaliana. Expression of different PINs in the root epidermis revealed the importance of PIN polar positions for directional auxin flow and root gravitropic growth. Interfering with sequence-embedded polarity signals directly demonstrates that PIN polarity is a primary factor in determining the direction of auxin flow in meristematic tissues. This finding provides a crucial piece in the puzzle of how auxin flow can be redirected via rapid changes in PIN polarity.