From vision toward best practices: Evaluating in vitro transcriptomic points of departure for application in risk assessment using a uniform workflow

Empirical Characterization of False Discovery Rates of Differentially Expressed Genes and Transcriptomic Benchmark Concentrations in Zebrafish Embryos

High-throughput transcriptomics (HTTr) is increasingly applied to zebrafish embryos to survey the toxicological effects of environmental chemicals. Before the adoption of this approach in regulatory testing, it is essential to characterize background noise in order to guide experimental designs. We thus empirically quantified the HTTr false discovery rate (FDR) across different embryo pool sizes, sample sizes, and concentration groups for toxicology studies. We exposed zebrafish embryos to 0.1% dimethyl sulfoxide (DMSO) for 5 days. Pools of 1, 5, 10, and 20 embryos were created (n = 24 samples for each pool size). Samples were sequenced on the TempO-Seq platform and then randomly assigned to mock treatment groups before differentially expressed gene (DEG), pathway, and benchmark concentration (BMC) analyses. Given that all samples were treated with DMSO, any significant DEGs, pathways, or BMCs are false positives. As expected, we found decreasing FDRs for DEG and pathway analyses with increasing pool and sample sizes. Similarly, FDRs for BMC analyses decreased with increasing pool size and concentration groups, with more stringent BMC premodel filtering reducing BMC FDRs. Our study provides foundational data for determining appropriate experiment designs for regulatory toxicity testing with HTTr in zebrafish embryos.

A novel method to derive a human safety limit for PFOA by gene expression profiling and modelling

Perfluorooctanoic acid (PFOA) is a persistent environmental contaminant that can accumulate in the human body due to its long half-life. This substance has been associated with liver, pancreatic, testicular and breast cancers, liver steatosis and endocrine disruption. PFOA is a member of a large group of substances also known as "forever chemicals" and the vast majority of substances of this group lack toxicological data that would enable their effective risk assessment in terms of human health hazards. This study aimed to derive a health-based guidance value for PFOA intake (ng/kg BW/day) from in vitro transcriptomics data. To this end, we developed an in silico workflow comprising five components: (i) sourcing in vitro hepatic transcriptomics concentration-response data; (ii) deriving molecular points of departure using BMDExpress3 and performing pathway analysis using gene set enrichment analysis (GSEA) to identify the most sensitive molecular pathways to PFOA exposure; (iii) estimating freely-dissolved PFOA concentrations in vitro using a mass balance model; (iv) estimating in vivo doses by reverse dosimetry using a PBK model for PFOA as part of a quantitative in vitro to in vivo extrapolation (QIVIVE) algorithm; and (v) calculating a tolerable daily intake (TDI) for PFOA. Fourteen percent of interrogated genes exhibited in vitro concentration-response relationships. GSEA pathway enrichment analysis revealed that "fatty acid metabolism" was the most sensitive pathway to PFOA exposure. In vitro free PFOA concentrations were calculated to be 2.9% of the nominal applied concentrations, and these free concentrations were input into the QIVIVE workflow. Exposure doses for a virtual population of 3,000 individuals were estimated, from which a TDI of 0.15 ng/kg BW/day for PFOA was calculated using the benchmark dose modelling software, PROAST. This TDI is comparable to previously published values of 1.16, 0.69, and 0.86 ng/kg BW/day by the European Food Safety Authority. In conclusion, this study demonstrates the combined utility of an "omics"-derived molecular point of departure and in silico QIVIVE workflow for setting health-based guidance values in anticipation of the acceptance of in vitro concentration-response molecular measurements in chemical risk assessment.

Transcriptomics-Based Points of Departure for Daphnia magna Exposed to 18 Per- and Polyfluoroalkyl Substances

Per- and polyfluoroalkyl substances (PFAS) represent a large group of contaminants of concern based on their widespread use, environmental persistence, and potential toxicity. Many traditional models for estimating toxicity, bioaccumulation, and other toxicological properties are not well suited for PFAS. Consequently, there is a need to generate hazard information for PFAS in an efficient and cost-effective manner. In the present study, Daphnia magna were exposed to multiple concentrations of 22 different PFAS for 24 h in a 96-well plate format. Following exposure, whole-body RNA was extracted and extracts, each representing five exposed individuals, were subjected to RNA sequencing. Following analytical measurements to verify PFAS exposure concentrations and quality control on processed cDNA libraries for sequencing, concentration-response modeling was applied to the data sets for 18 of the tested compounds, and the concentration at which a concerted molecular response occurred (transcriptomic point of departure; tPOD) was calculated. The tPODs, based on measured concentrations of PFAS, generally ranged from 0.03 to 0.58 µM (9.9-350 µg/L; interquartile range). In most cases, these concentrations were two orders of magnitude lower than similarly calculated tPODs for human cell lines exposed to PFAS. They were also lower than apical effect concentrations reported for seven PFAS for which some crustacean or invertebrate toxicity data were available, although there were a few exceptions. Despite being lower than most other available hazard benchmarks, D. magna tPODs were, on average, four orders of magnitude greater than the maximum aqueous concentrations of PFAS measured in Great Lakes tributaries. Overall, this high-throughput transcriptomics assay with D. magna holds promise as a component of a tiered hazard evaluation strategy employing new approach methodologies. Environ Toxicol Chem 2024;00:1-16. © 2024 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Derivation of Transcriptomics-Based Points of Departure for 20 Per- or Polyfluoroalkyl Substances Using a Larval Fathead Minnow (Pimephales promelas) Reduced Transcriptome Assay

Traditional toxicity testing has been unable to keep pace with the introduction of new chemicals into commerce. Consequently, there are limited or no toxicity data for many chemicals to which fish and wildlife may be exposed. Per- and polyfluoroalkyl substances (PFAS) are emblematic of this issue in that ecological hazards of most PFAS remain uncharacterized. The present study employed a high-throughput assay to identify the concentration at which 20 PFAS, with diverse properties, elicited a concerted gene expression response (termed a transcriptomics-based point of departure [tPOD]) in larval fathead minnows (Pimephales promelas; 5-6 days postfertilization) exposed for 24 h. Based on a reduced transcriptome approach that measured whole-body expression of 1832 genes, the median tPOD for the 20 PFAS tested was 10 µM. Longer-chain carboxylic acids (12-13 C-F); an eight-C-F dialcohol, N-alkyl sulfonamide; and telomer sulfonic acid were among the most potent PFAS, eliciting gene expression responses at concentrations <1 µM. With a few exceptions, larval fathead minnow tPODs were concordant with those based on whole-transcriptome response in human cell lines. However, larval fathead minnow tPODs were often greater than those for Daphnia magna exposed to the same PFAS. The tPODs overlapped concentrations at which other sublethal effects have been reported in fish (available for 10 PFAS). Nonetheless, fathead minnow tPODs were orders of magnitude higher than aqueous PFAS concentrations detected in tributaries of the North American Great Lakes, suggesting a substantial margin of safety. Overall, results broadly support the use of a fathead minnow larval transcriptomics assay to derive screening-level potency estimates for use in ecological risk-based prioritization. Environ Toxicol Chem 2024;00:1-16. © 2024 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Exploring the effects of experimental parameters and data modeling approaches on in vitro transcriptomic point-of-departure estimates

Multiple new approach methods (NAMs) are being developed to rapidly screen large numbers of chemicals to aid in hazard evaluation and risk assessments. High-throughput transcriptomics (HTTr) in human cell lines has been proposed as a first-tier screening approach for determining the types of bioactivity a chemical can cause (activation of specific targets vs. generalized cell stress) and for calculating transcriptional points of departure (tPODs) based on changes in gene expression. In the present study, we examine a range of computational methods to calculate tPODs from HTTr data, using six data sets in which MCF7 cells cultured in two different media formulations were treated with a panel of 44 chemicals for 3 different exposure durations (6, 12, 24 hr). The tPOD calculation methods use data at the level of individual genes and gene set signatures, and compare data processed using the ToxCast Pipeline 2 (tcplfit2), BMDExpress and PLIER (Pathway Level Information ExtractoR). Methods were evaluated by comparing to in vitro PODs from a validated set of high-throughput screening (HTS) assays for a set of estrogenic compounds. Key findings include: (1) for a given chemical and set of experimental conditions, tPODs calculated by different methods can vary by several orders of magnitude; (2) tPODs are at least as sensitive to computational methods as to experimental conditions; (3) in comparison to an external reference set of PODs, some methods give generally higher values, principally PLIER and BMDExpress; and (4) the tPODs from HTTr in this one cell type are mostly higher than the overall PODs from a broad battery of targeted in vitro ToxCast assays, reflecting the need to test chemicals in multiple cell types and readout technologies for in vitro hazard screening.

Toxicological Mechanisms and Potencies of Organophosphate Esters in KGN Human Ovarian Granulosa Cells as Revealed by High-throughput Transcriptomics

Despite the growing number of studies reporting potential risks associated with exposure to organophosphate esters (OPEs), their molecular mechanisms of action remain poorly defined. We used the high-throughput TempO-Seq™ platform to investigate the effects of frequently detected OPEs on the expression of ∼3000 environmentally responsive genes in KGN human ovarian granulosa cells. Cells were exposed for 48 h to one of five OPEs (0.1 to 50 μM): tris(methylphenyl) phosphate (TMPP), isopropylated triphenyl phosphate (IPPP), tert-butylphenyl diphenyl phosphate (BPDP), triphenyl phosphate (TPHP), or tris(2-butoxyethyl) phosphate (TBOEP). The sequencing data indicate that four OPEs induced transcriptional changes, whereas TBOEP had no effect within the concentration range tested. Multiple pathway databases were used to predict alterations in biological processes based on differentially expressed genes. At lower concentrations, inhibition of the cholesterol biosynthetic pathway was the predominant effect of OPEs; this was likely a consequence of intracellular cholesterol accumulation. At higher concentrations, BPDP and TPHP had distinct effects, primarily affecting pathways involved in cell cycle progression and other stress responses. Benchmark concentration (BMC) modelling revealed that BPDP had the lowest transcriptomic point of departure. However, in vitro to in vivo extrapolation modeling indicated that TMPP was bioactive at lower concentrations than the other OPEs. We conclude that these new approach methodologies provide information on the mechanism(s) underlying the effects of data-poor compounds and assist in the derivation of protective points of departure for use in chemical read-across and decision-making.

CSL-Tox: an open-source analytical framework for the comparison of short-term and long-term toxicity end points and assessing the need of chronic studies in drug development

In-vivo toxicity assessment is an important step prior to clinical development and is still the main source of data for overall risk assessment of a new molecular entity (NCE). All in-vivo studies are performed according to regulatory requirements and many efforts have been exerted to minimize these studies in accordance with the (Replacement, Reduction and Refinement) 3Rs principle. Many aspects of in-vivo toxicology packages can be optimized to reduce animal use, including the number of studies performed as well as study durations, which is the main focus of this analysis. We performed a statistical comparison of adverse findings observed in 116 short-term versus 78 long-term in-house or in-house sponsored Contract Research Organizations (CRO) studies, in order to explore the possibility of using only short-term studies as a prediction tool for the longer-term effects. All the data analyzed in this study was manually extracted from the toxicology reports (in PDF formats) to construct the dataset. Annotation of treatment related findings was one of the challenges faced during this work. A specific focus was therefore put on the summary and conclusion sections of the reports since they contain expert assessments on whether the findings were considered adverse or were attributed to other reasons. Our analysis showed a general good concordance between short-term and long-term toxicity findings for large molecules and the majority of small molecules. Less concordance was seen for certain body organs, which can be named as "target organ systems' findings". While this work supports the minimization of long-term studies, a larger-scale effort would be needed to provide more evidence. We therefore present the steps performed in this study as an open-source R workflow for the Comparison of Short-term and Long-term Toxicity studies (CSL-Tox). The dataset used in the work is provided to allow researchers to reproduce such analysis, re-evaluate the statistical tools used and promote large-scale application of this study. Important aspects of animal research reproducibility are highlighted in this work, specifically, the necessity of a reproducible adverse effects reporting system and utilization of the controlled terminologies in-vivo toxicology reports and finally the importance of open-source analytical workflows that can be assessed by other scientists in the field of preclinical toxicology.