1
|
Cohn EF, Clayton BLL, Madhavan M, Lee KA, Yacoub S, Fedorov Y, Scavuzzo MA, Paul Friedman K, Shafer TJ, Tesar PJ. Pervasive environmental chemicals impair oligodendrocyte development. Nat Neurosci 2024; 27:836-845. [PMID: 38528201 PMCID: PMC11088982 DOI: 10.1038/s41593-024-01599-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 02/05/2024] [Indexed: 03/27/2024]
Abstract
Exposure to environmental chemicals can impair neurodevelopment, and oligodendrocytes may be particularly vulnerable, as their development extends from gestation into adulthood. However, few environmental chemicals have been assessed for potential risks to oligodendrocytes. Here, using a high-throughput developmental screen in cultured cells, we identified environmental chemicals in two classes that disrupt oligodendrocyte development through distinct mechanisms. Quaternary compounds, ubiquitous in disinfecting agents and personal care products, were potently and selectively cytotoxic to developing oligodendrocytes, whereas organophosphate flame retardants, commonly found in household items such as furniture and electronics, prematurely arrested oligodendrocyte maturation. Chemicals from each class impaired oligodendrocyte development postnatally in mice and in a human 3D organoid model of prenatal cortical development. Analysis of epidemiological data showed that adverse neurodevelopmental outcomes were associated with childhood exposure to the top organophosphate flame retardant identified by our screen. This work identifies toxicological vulnerabilities for oligodendrocyte development and highlights the need for deeper scrutiny of these compounds' impacts on human health.
Collapse
Affiliation(s)
- Erin F Cohn
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Benjamin L L Clayton
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Mayur Madhavan
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin A Lee
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Sara Yacoub
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Yuriy Fedorov
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Marissa A Scavuzzo
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Katie Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Timothy J Shafer
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Paul J Tesar
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
| |
Collapse
|
2
|
Xie R, Wang X, Xu Y, Zhang L, Ma M, Wang Z. In vitro to in vivo extrapolation for predicting human equivalent dose of phenolic endocrine disrupting chemicals: PBTK model development, biological pathways, outcomes and performance. Sci Total Environ 2023; 897:165271. [PMID: 37422235 DOI: 10.1016/j.scitotenv.2023.165271] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/12/2023] [Accepted: 06/30/2023] [Indexed: 07/10/2023]
Abstract
In vitro to in vivo (IVIVE) leverages in vitro high-throughput biological responses to predict the corresponding in vivo exposures and further estimate the human safe dose. However, for phenolic endocrine disrupting chemicals (EDCs) linked with complicated biological pathways and adverse outcomes (AO), such as bisphenol A (BPA) and 4-nonylphenol (4-NP), plausible estimation of human equivalent doses (HED) by IVIVE approaches considering various biological pathways and endpoints is still challenging. To explore the capabilities and limitations of IVIVE, this study conducted physiologically based toxicokinetic (PBTK)-IVIVE approaches to derive pathway-specific HEDs using BPA and 4-NP as examples. In vitro HEDs of BPA and 4-NP varied in different adverse outcomes, pathways, and testing endpoints and ranged from 0.0013 to 1.0986 mg/kg bw/day and 0.0551 to 1.7483 mg/kg bw/day, respectively. In vitro HEDs associated with reproductive AOs initiated by PPARα activation and ER agonism were the most sensitive. Model verification suggested the potential of using effective in vitro data to determine reasonable approximation of in vivo HEDs for the same AO (fold differences of most AOs ranged in 0.14-2.74 and better predictions for apical endpoints). Furthermore, system-specific parameters of cardiac output and its fraction, body weight, as well as chemical-specific parameters of partition coefficient and liver metabolic were most sensitive for the PBTK simulations. The results indicated that the application of fit for-purpose PBTK-IVIVE approach could provide credible pathway-specific HEDs and contribute to high throughput prioritization of chemicals in a more realistic scenario.
Collapse
Affiliation(s)
- Ruili Xie
- Key Laboratory of Drinking Water Science and Technology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaodan Wang
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Yiping Xu
- Key Laboratory of Drinking Water Science and Technology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Lei Zhang
- China National Center for Food Safety Risk Assessment, Beijing 100022, China.
| | - Mei Ma
- Key Laboratory of Drinking Water Science and Technology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zijian Wang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| |
Collapse
|
3
|
Schaupp CM, Maloney EM, Mattingly KZ, Olker JH, Villeneuve DL. Comparison of in silico, in vitro, and in vivo toxicity benchmarks suggests a role for ToxCast data in ecological hazard assessment. Toxicol Sci 2023; 195:145-154. [PMID: 37490521 DOI: 10.1093/toxsci/kfad072] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023] Open
Abstract
Large repositories of in vitro bioactivity data such as US EPA's Toxicity Forecaster (ToxCast) provide a wealth of publicly accessible toxicity information for thousands of chemicals. These data can be used to calculate point-of-departure (POD) estimates via concentration-response modeling that may serve as lower bound, protective estimates of in vivo effects. However, the data are predominantly based on mammalian models and discussions to date about their utility have largely focused on potential integration into human hazard assessment, rather than application to ecological risk assessment. The goal of the present study was to compare PODs based on (1) quantitative structure-activity relationships (QSARs), (2) the 5th centile of the activity concentration at cutoff (ACC), and (3) lower-bound cytotoxic burst (LCB) from ToxCast, with the distribution of in vivo PODs compiled in the Ecotoxicology Knowledgebase (ECOTOX). While overall correlation between ToxCast ACC5 and ECOTOX PODs for 649 chemicals was weak, there were significant associations among PODs based on LCB and ECOTOX, LCB and QSARs, and ECOTOX and QSARs. Certain classes of compounds showed moderate correlation across datasets (eg, antimicrobials/disinfectants), while others, such as organophosphate insecticides, did not. Unsurprisingly, more precise classifications of the data based on ECOTOX effect and endpoint type (eg, apical vs biochemical; acute vs chronic) had a significant effect on overall relationships. Results of this research help to define appropriate roles for data from new approach methodologies in chemical prioritization and screening of ecological hazards.
Collapse
Affiliation(s)
- Christopher M Schaupp
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota 55804, USA
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee 37830, USA
| | - Erin M Maloney
- Integrated Biological Sciences Program, University of Minnesota-Duluth, Duluth, Minnesota 55804, USA
| | | | - Jennifer H Olker
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota 55804, USA
| | - Daniel L Villeneuve
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota 55804, USA
| |
Collapse
|
4
|
Feshuk M, Kolaczkowski L, Dunham K, Davidson-Fritz SE, Carstens KE, Brown J, Judson RS, Paul Friedman K. The ToxCast pipeline: updates to curve-fitting approaches and database structure. Front Toxicol 2023; 5:1275980. [PMID: 37808181 PMCID: PMC10552852 DOI: 10.3389/ftox.2023.1275980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 09/08/2023] [Indexed: 10/10/2023] Open
Abstract
Introduction: The US Environmental Protection Agency Toxicity Forecaster (ToxCast) program makes in vitro medium- and high-throughput screening assay data publicly available for prioritization and hazard characterization of thousands of chemicals. The assays employ a variety of technologies to evaluate the effects of chemical exposure on diverse biological targets, from distinct proteins to more complex cellular processes like mitochondrial toxicity, nuclear receptor signaling, immune responses, and developmental toxicity. The ToxCast data pipeline (tcpl) is an open-source R package that stores, manages, curve-fits, and visualizes ToxCast data and populates the linked MySQL Database, invitrodb. Methods: Herein we describe major updates to tcpl and invitrodb to accommodate a new curve-fitting approach. The original tcpl curve-fitting models (constant, Hill, and gain-loss models) have been expanded to include Polynomial 1 (Linear), Polynomial 2 (Quadratic), Power, Exponential 2, Exponential 3, Exponential 4, and Exponential 5 based on BMDExpress and encoded by the R package dependency, tcplfit2. Inclusion of these models impacted invitrodb (beta version v4.0) and tcpl v3 in several ways: (1) long-format storage of generic modeling parameters to permit additional curve-fitting models; (2) updated logic for winning model selection; (3) continuous hit calling logic; and (4) removal of redundant endpoints as a result of bidirectional fitting. Results and discussion: Overall, the hit call and potency estimates were largely consistent between invitrodb v3.5 and 4.0. Tcpl and invitrodb provide a standard for consistent and reproducible curve-fitting and data management for diverse, targeted in vitro assay data with readily available documentation, thus enabling sharing and use of these data in myriad toxicology applications. The software and database updates described herein promote comparability across multiple tiers of data within the US Environmental Protection Agency CompTox Blueprint.
Collapse
Affiliation(s)
- M. Feshuk
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - L. Kolaczkowski
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
- National Student Services Contractor, Oak Ridge Associated Universities, Oak Ridge, TN, United States
| | - K. Dunham
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
- National Student Services Contractor, Oak Ridge Associated Universities, Oak Ridge, TN, United States
| | - S. E. Davidson-Fritz
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - K. E. Carstens
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - J. Brown
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - R. S. Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - K. Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| |
Collapse
|
5
|
Law J, Orbach SM, Weston BR, Steele PA, Rajagopalan P, Murali TM. Computational Construction of Toxicant Signaling Networks. Chem Res Toxicol 2023; 36:1267-1277. [PMID: 37471124 PMCID: PMC10445288 DOI: 10.1021/acs.chemrestox.2c00422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Indexed: 07/21/2023]
Abstract
Humans and animals are regularly exposed to compounds that may have adverse effects on health. The Toxicity Forecaster (ToxCast) program was developed to use high throughput screening assays to quickly screen chemicals by measuring their effects on many biological end points. Many of these assays test for effects on cellular receptors and transcription factors (TFs), under the assumption that a toxicant may perturb normal signaling pathways in the cell. We hypothesized that we could reconstruct the intermediate proteins in these pathways that may be directly or indirectly affected by the toxicant, potentially revealing important physiological processes not yet tested for many chemicals. We integrate data from ToxCast with a human protein interactome to build toxicant signaling networks that contain physical and signaling protein interactions that may be affected as a result of toxicant exposure. To build these networks, we developed the EdgeLinker algorithm, which efficiently finds short paths in the interactome that connect the receptors to TFs for each toxicant. We performed multiple evaluations and found evidence suggesting that these signaling networks capture biologically relevant effects of toxicants. To aid in dissemination and interpretation, interactive visualizations of these networks are available at http://graphspace.org.
Collapse
Affiliation(s)
- Jeffrey
N. Law
- Interdisciplinary
Ph.D. Program in Genetics, Bioinformatics, and Computational Biology, Blacksburg, Virginia 24061, United States
| | - Sophia M. Orbach
- Department
of Chemical Engineering, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Bronson R. Weston
- Interdisciplinary
Ph.D. Program in Genetics, Bioinformatics, and Computational Biology, Blacksburg, Virginia 24061, United States
| | - Peter A. Steele
- Department
of Computer Science, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Padmavathy Rajagopalan
- Department
of Chemical Engineering, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - T. M. Murali
- Department
of Computer Science, Virginia Tech, Blacksburg, Virginia 24061, United States
| |
Collapse
|
6
|
Melching-Kollmuss S, Bothe K, Charlton A, Gangadharan B, Ghaffari R, Jacobi S, Marty S, Marxfeld HA, McInnes EF, Sauer UG, Sheets LP, Strupp C, Tinwell H, Wiemann C, Botham PA, van Ravenzwaay B. Towards a science-based testing strategy to identify maternal thyroid hormone imbalance and neurodevelopmental effects in the progeny - Part IV: the ECETOC and CLE Proposal for a Thyroid Function-Related Neurodevelopmental Toxicity Testing and Assessment Scheme (Thyroid-NDT-TAS). Crit Rev Toxicol 2023; 53:339-371. [PMID: 37554099 DOI: 10.1080/10408444.2023.2231033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 06/22/2023] [Accepted: 06/22/2023] [Indexed: 08/10/2023]
Abstract
Following the European Commission Endocrine Disruptor Criteria, substances shall be considered as having endocrine disrupting properties if they (a) elicit adverse effects, (b) have endocrine activity, and (c) the two are linked by an endocrine mode-of-action (MoA) unless the MoA is not relevant for humans. A comprehensive, structured approach to assess whether substances meet the Endocrine Disruptor Criteria for the thyroid modality (EDC-T) is currently unavailable. Here, the European Centre for Ecotoxicology and Toxicology of Chemicals Thyroxine Task Force and CropLife Europe propose a Thyroid Function-Related Neurodevelopmental Toxicity Testing and Assessment Scheme (Thyroid-NDT-TAS). In Tier 0, before entering the Thyroid-NDT-TAS, all available in vivo, in vitro and in silico data are submitted to weight-of-evidence (WoE) evaluations to determine whether the substance of interest poses a concern for thyroid disruption. If so, Tier 1 of the Thyroid-NDT-TAS includes an initial MoA and human relevance assessment (structured by the key events of possibly relevant adverse outcome pathways) and the generation of supportive in vitro/in silico data, if relevant. Only if Tier 1 is inconclusive, Tier 2 involves higher-tier testing to generate further thyroid- and/or neurodevelopment-related data. Tier 3 includes the final MoA and human relevance assessment and an overarching WoE evaluation to draw a conclusion on whether, or not, the substance meets the EDC-T. The Thyroid-NDT-TAS is based on the state-of-the-science, and it has been developed to minimise animal testing. To make human safety assessments more accurate, it is recommended to apply the Thyroid-NDT-TAS during future regulatory assessments.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | - Ursula G Sauer
- Scientific Consultancy - Animal Welfare, Neubiberg, Germany
| | | | | | | | | | | | | |
Collapse
|
7
|
Cohn EF, Clayton BL, Madhavan M, Yacoub S, Federov Y, Paul-Friedman K, Shafer TJ, Tesar PJ. Pervasive environmental chemicals impair oligodendrocyte development. bioRxiv 2023:2023.02.10.528042. [PMID: 36798415 PMCID: PMC9934656 DOI: 10.1101/2023.02.10.528042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/14/2023]
Abstract
Exposure to environmental chemicals can impair neurodevelopment1-4. Oligodendrocytes that wrap around axons to boost neurotransmission may be particularly vulnerable to chemical toxicity as they develop throughout fetal development and into adulthood5,6. However, few environmental chemicals have been assessed for potential risks to oligodendrocyte development. Here, we utilized a high-throughput developmental screen and human cortical brain organoids, which revealed environmental chemicals in two classes that disrupt oligodendrocyte development through distinct mechanisms. Quaternary compounds, ubiquitous in disinfecting agents, hair conditioners, and fabric softeners, were potently and selectively cytotoxic to developing oligodendrocytes through activation of the integrated stress response. Organophosphate flame retardants, commonly found in household items such as furniture and electronics, were non-cytotoxic but prematurely arrested oligodendrocyte maturation. Chemicals from each class impaired human oligodendrocyte development in a 3D organoid model of prenatal cortical development. In analysis of epidemiological data from the CDC's National Health and Nutrition Examination Survey, adverse neurodevelopmental outcomes were associated with childhood exposure to the top organophosphate flame retardant identified by our oligodendrocyte toxicity platform. Collectively, our work identifies toxicological vulnerabilities specific to oligodendrocyte development and highlights common household chemicals with high exposure risk to children that warrant deeper scrutiny for their impact on human health.
Collapse
Affiliation(s)
- Erin F. Cohn
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106, USA
| | - Benjamin L.L. Clayton
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106, USA
| | - Mayur Madhavan
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106, USA
| | - Sara Yacoub
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106, USA
| | - Yuriy Federov
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106, USA
| | - Katie Paul-Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
| | - Timothy J. Shafer
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
| | - Paul J. Tesar
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106, USA
| |
Collapse
|
8
|
Borghoff SJ, Cohen SS, Jiang X, Lea IA, Klaren WD, Chappell GA, Britt JK, Rivera BN, Choski NY, Wikoff DS. Updated systematic assessment of human, animal and mechanistic evidence demonstrates lack of human carcinogenicity with consumption of aspartame. Food Chem Toxicol 2023; 172:113549. [PMID: 36493943 DOI: 10.1016/j.fct.2022.113549] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/23/2022] [Accepted: 12/02/2022] [Indexed: 12/12/2022]
Abstract
Aspartame has been studied extensively and evaluated for its safety in foods and beverages yet concerns for its potential carcinogenicity have persisted, driven primarily by animal studies conducted at the Ramazzini Institute (RI). To address this controversy, an updated systematic review of available human, animal, and mechanistic data was conducted leveraging critical assessment tools to consider the quality and reliability of data. The evidence base includes 12 animal studies and >40 epidemiological studies reviewed by the World Health Organization which collectively demonstrate a lack of carcinogenic effect. Assessment of >1360 mechanistic endpoints, including many guideline-based genotoxicity studies, demonstrate a lack of activity associated with endpoints grouped to key characteristics of carcinogens. Other non-specific mechanistic data (e.g., mixed findings of oxidative stress across study models, tissues, and species) do not provide evidence of a biologically plausible carcinogenic pathway associated with aspartame. Taken together, available evidence supports that aspartame consumption is not carcinogenic in humans and that the inconsistent findings of the RI studies may be explained by flaws in study design and conduct (despite additional analyses to address study limitations), as acknowledged by authoritative bodies.
Collapse
Affiliation(s)
| | - Sarah S Cohen
- EpidStrategies, A Division of ToxStrategies, RTP, NC, USA
| | - Xiaohui Jiang
- EpidStrategies, A Division of ToxStrategies, RTP, NC, USA
| | - Isabel A Lea
- ToxStrategies, Inc., Research Triangle Park, NC, USA
| | | | | | | | | | | | | |
Collapse
|
9
|
Drake C, Wehr MM, Zobl W, Koschmann J, De Lucca D, Kühne BA, Hansen T, Knebel J, Ritter D, Boei J, Vrieling H, Bitsch A, Escher SE. Substantiate a read-across hypothesis by using transcriptome data-A case study on volatile diketones. Front Toxicol 2023; 5:1155645. [PMID: 37206915 PMCID: PMC10188990 DOI: 10.3389/ftox.2023.1155645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 04/17/2023] [Indexed: 05/21/2023] Open
Abstract
This case study explores the applicability of transcriptome data to characterize a common mechanism of action within groups of short-chain aliphatic α-, β-, and γ-diketones. Human reference in vivo data indicate that the α-diketone diacetyl induces bronchiolitis obliterans in workers involved in the preparation of microwave popcorn. The other three α-diketones induced inflammatory responses in preclinical in vivo animal studies, whereas beta and gamma diketones in addition caused neuronal effects. We investigated early transcriptional responses in primary human bronchiolar (PBEC) cell cultures after 24 h and 72 h of air-liquid exposure. Differentially expressed genes (DEGs) were assessed based on transcriptome data generated with the EUToxRisk gene panel of Temp-O-Seq®. For each individual substance, genes were identified displaying a consistent differential expression across dose and exposure duration. The log fold change values of the DEG profiles indicate that α- and β-diketones are more active compared to γ-diketones. α-diketones in particular showed a highly concordant expression pattern, which may serve as a first indication of the shared mode of action. In order to gain a better mechanistic understanding, the resultant DEGs were submitted to a pathway analysis using ConsensusPathDB. The four α-diketones showed very similar results with regard to the number of activated and shared pathways. Overall, the number of signaling pathways decreased from α-to β-to γ-diketones. Additionally, we reconstructed networks of genes that interact with one another and are associated with different adverse outcomes such as fibrosis, inflammation or apoptosis using the TRANSPATH-database. Transcription factor enrichment and upstream analyses with the geneXplain platform revealed highly interacting gene products (called master regulators, MRs) per case study compound. The mapping of the resultant MRs on the reconstructed networks, visualized similar gene regulation with regard to fibrosis, inflammation and apoptosis. This analysis showed that transcriptome data can strengthen the similarity assessment of compounds, which is of particular importance, e.g., in read-across approaches. It is one important step towards grouping of compounds based on biological profiles.
Collapse
Affiliation(s)
- Christina Drake
- Fraunhofer Institute for Toxicology and Experimental Medicine, Chemical Safety and Toxicology, Hannover, Germany
- *Correspondence: Christina Drake,
| | - Matthias M. Wehr
- Fraunhofer Institute for Toxicology and Experimental Medicine, Chemical Safety and Toxicology, Hannover, Germany
| | - Walter Zobl
- Fraunhofer Institute for Toxicology and Experimental Medicine, Chemical Safety and Toxicology, Hannover, Germany
| | | | | | - Britta A. Kühne
- Fraunhofer Institute for Toxicology and Experimental Medicine, Chemical Safety and Toxicology, Hannover, Germany
| | - Tanja Hansen
- Fraunhofer Institute for Toxicology and Experimental Medicine, Chemical Safety and Toxicology, Hannover, Germany
| | - Jan Knebel
- Fraunhofer Institute for Toxicology and Experimental Medicine, Chemical Safety and Toxicology, Hannover, Germany
| | - Detlef Ritter
- Fraunhofer Institute for Toxicology and Experimental Medicine, Chemical Safety and Toxicology, Hannover, Germany
| | - Jan Boei
- Leiden University Medical Center, Leiden, Netherlands
| | | | - Annette Bitsch
- Fraunhofer Institute for Toxicology and Experimental Medicine, Chemical Safety and Toxicology, Hannover, Germany
| | - Sylvia E. Escher
- Fraunhofer Institute for Toxicology and Experimental Medicine, Chemical Safety and Toxicology, Hannover, Germany
| |
Collapse
|
10
|
Pierro JD, Ahir BK, Baker NC, Kleinstreuer NC, Xia M, Knudsen TB. Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling. Front Pharmacol 2022; 13:971296. [PMID: 36172177 PMCID: PMC9511990 DOI: 10.3389/fphar.2022.971296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 07/21/2022] [Indexed: 11/13/2022] Open
Abstract
All-trans retinoic acid (ATRA) gradients determine skeletal patterning morphogenesis and can be disrupted by diverse genetic or environmental factors during pregnancy, leading to fetal skeleton defects. Adverse Outcome Pathway (AOP) frameworks for ATRA metabolism, signaling, and homeostasis allow for the development of new approach methods (NAMs) for predictive toxicology with less reliance on animal testing. Here, a data-driven model was constructed to identify chemicals associated with both ATRA pathway bioactivity and prenatal skeletal defects. The phenotype data was culled from ToxRefDB prenatal developmental toxicity studies and produced a list of 363 ToxRefDB chemicals with altered skeletal observations. Defects were classified regionally as cranial, post-cranial axial, appendicular, and other (unspecified) features based on ToxRefDB descriptors. To build a multivariate statistical model, high-throughput screening bioactivity data from >8,070 chemicals in ToxCast/Tox21 across 10 in vitro assays relevant to the retinoid signaling system were evaluated and compared to literature-based candidate reference chemicals in the dataset. There were 48 chemicals identified for effects on both in vivo skeletal defects and in vitro ATRA pathway targets for computational modeling. The list included 28 chemicals with prior evidence of skeletal defects linked to retinoid toxicity and 20 chemicals without prior evidence. The combination of thoracic cage defects and DR5 (direct repeats of 5 nucleotides for RAR/RXR transactivation) disruption was the most frequently occurring phenotypic and target disturbance, respectively. This data model provides valuable AOP elucidation and validates current mechanistic understanding. These findings also shed light on potential avenues for new mechanistic discoveries related to ATRA pathway disruption and associated skeletal dysmorphogenesis due to environmental exposures.
Collapse
Affiliation(s)
- Jocylin D. Pierro
- Center for Computational Toxicology and Exposure (CCTE), Computational Toxicology and Bioinformatics Branch (CTBB), Office of Research and Development (ORD), U.S. Environmental Protection Agency (USEPA), Research Triangle Park, NC, United States
| | - Bhavesh K. Ahir
- Eurofins Medical Device Testing, Lancaster, PA, United States
| | - Nancy C. Baker
- Scientific Computing and Data Curation Division (SCDCD), Leidos Contractor, Center for Computational Toxicology and Exposure (CCTE), USEPA/ORD, Research Triangle Park, NC, United States
| | - Nicole C. Kleinstreuer
- Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), National Toxicology Program, National Institutes of Health, Research Triangle Park, NC, United States
| | - Menghang Xia
- Division for Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, United States
| | - Thomas B. Knudsen
- Center for Computational Toxicology and Exposure (CCTE), Computational Toxicology and Bioinformatics Branch (CTBB), Office of Research and Development (ORD), U.S. Environmental Protection Agency (USEPA), Research Triangle Park, NC, United States
- *Correspondence: Thomas B. Knudsen, , orcid.org/0000-0002-5036-596x
| |
Collapse
|
11
|
El-Masri H, Paul Friedman K, Isaacs K, Wetmore BA. Advances in computational methods along the exposure to toxicological response paradigm. Toxicol Appl Pharmacol 2022; 450:116141. [PMID: 35777528 PMCID: PMC9619339 DOI: 10.1016/j.taap.2022.116141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 05/27/2022] [Accepted: 06/23/2022] [Indexed: 10/17/2022]
Abstract
Human health risk assessment is a function of chemical toxicity, bioavailability to reach target biological tissues, and potential environmental exposure. These factors are complicated by many physiological, biochemical, physical and lifestyle factors. Furthermore, chemical health risk assessment is challenging in view of the large, and continually increasing, number of chemicals found in the environment. These challenges highlight the need to prioritize resources for the efficient and timely assessment of those environmental chemicals that pose greatest health risks. Computational methods, either predictive or investigative, are designed to assist in this prioritization in view of the lack of cost prohibitive in vivo experimental data. Computational methods provide specific and focused toxicity information using in vitro high throughput screening (HTS) assays. Information from the HTS assays can be converted to in vivo estimates of chemical levels in blood or target tissue, which in turn are converted to in vivo dose estimates that can be compared to exposure levels of the screened chemicals. This manuscript provides a review for the landscape of computational methods developed and used at the U.S. Environmental Protection Agency (EPA) highlighting their potentials and challenges.
Collapse
Affiliation(s)
- Hisham El-Masri
- Center for Computational Toxicology and Exposure, Office of Research and Development, U. S. Environmental Protection Agency, Research Triangle Park, NC, USA.
| | - Katie Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, U. S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Kristin Isaacs
- Center for Computational Toxicology and Exposure, Office of Research and Development, U. S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Barbara A Wetmore
- Center for Computational Toxicology and Exposure, Office of Research and Development, U. S. Environmental Protection Agency, Research Triangle Park, NC, USA
| |
Collapse
|
12
|
Carberry CK, Turla T, Koval LE, Hartwell H, Fry RC, Rager JE. Chemical Mixtures in Household Environments: In Silico Predictions and In Vitro Testing of Potential Joint Action on PPARγ in Human Liver Cells. Toxics 2022; 10:199. [PMID: 35622613 PMCID: PMC9146550 DOI: 10.3390/toxics10050199] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 04/16/2022] [Indexed: 01/27/2023]
Abstract
There are thousands of chemicals that humans can be exposed to in their everyday environments, the majority of which are currently understudied and lack substantial testing for potential exposure and toxicity. This study aimed to implement in silico methods to characterize the chemicals that co-occur across chemical and product uses in our everyday household environments that also target a common molecular mediator, thus representing understudied mixtures that may exacerbate toxicity in humans. To detail, the Chemical and Products Database (CPDat) was queried to identify which chemicals co-occur across common exposure sources. Chemicals were preselected to include those that target an important mediator of cell health and toxicity, the peroxisome proliferator activated receptor gamma (PPARγ), in liver cells that were identified through query of the ToxCast/Tox21 database. These co-occurring chemicals were thus hypothesized to exert potential joint effects on PPARγ. To test this hypothesis, five commonly co-occurring chemicals (namely, benzyl cinnamate, butyl paraben, decanoic acid, eugenol, and sodium dodecyl sulfate) were tested individually and in combination for changes in the expression of PPARγ and its downstream target, insulin receptor (INSR), in human liver HepG2 cells. Results showed that these likely co-occurring chemicals in household environments increased both PPARγ and INSR expression more significantly when the exposures occurred as mixtures vs. as individual chemicals. Future studies will evaluate such chemical combinations across more doses, allowing for further quantification of the types of joint action while leveraging this method of chemical combination prioritization. This study demonstrates the utility of in silico-based methods to identify chemicals that co-occur in the environment for mixtures toxicity testing and highlights relationships between understudied chemicals and changes in PPARγ-associated signaling.
Collapse
|
13
|
Hsieh JH. Accounting for Artifacts in High-Throughput Toxicity Assays. Methods Mol Biol 2022; 2474:155-167. [PMID: 35294764 DOI: 10.1007/978-1-0716-2213-1_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Compound activity identification is the primary goal in high throughput screening (HTS) assays. However, assay artifacts including both systematic (e.g., compound autofluorescence) and nonsystematic (e.g., noise) complicate activity interpretation. In addition, other than the traditional potency parameter, half-maximal effect concentration [EC50], additional activity parameters (e.g., point-of-departure [POD] and weighted area-under-the-curve [wAUC]) could be derived from HTS data for activity profiling. A data analysis pipeline has been developed to handle the artifacts, and to provide compound activity characterization with either binary or continuous metrics. This chapter outlines the steps in the pipeline using Tox21 estrogen receptor (ER) β-lactamase assays, including the formats to identify either agonists or antagonists, as well as the counterscreen assays for identifying artifacts as examples. The steps can be applied to other lower throughput assays with concentration-response data.
Collapse
Affiliation(s)
- Jui-Hua Hsieh
- National Institute of Environmental Health Sciences, Durham, NC, USA.
| |
Collapse
|
14
|
Armitage JM, Sangion A, Parmar R, Looky AB, Arnot JA. Update and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.0. Toxics 2021; 9:toxics9110315. [PMID: 34822706 PMCID: PMC8625852 DOI: 10.3390/toxics9110315] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 11/15/2021] [Accepted: 11/17/2021] [Indexed: 11/16/2022]
Abstract
This study demonstrates the utility of an updated mass balance model for predicting the distribution of organic chemicals in in vitro test systems (IV-MBM EQP v2.0) and evaluates its performance with empirical data. The IV-MBM EQP v2.0 tool was parameterized and applied to four independent data sets with measured ratios of bulk medium or freely-dissolved to initial nominal concentrations (e.g., C24/C0 where C24 is the measured concentration after 24 h of exposure and C0 is the initial nominal concentration). Model performance varied depending on the data set, chemical properties (e.g., "volatiles" vs. "non-volatiles", neutral vs. ionizable organics), and model assumptions but overall is deemed acceptable. For example, the r2 was greater than 0.8 and the mean absolute error (MAE) in the predictions was less than a factor of two for most neutral organics included. Model performance was not as good for the ionizable organic chemicals included but the r2 was still greater than 0.7 and the MAE less than a factor of three. The IV-MBM EQP v2.0 model was subsequently applied to several hundred chemicals on Canada's Domestic Substances List (DSL) with nominal effects data (AC50s) reported for two in vitro assays. We report the frequency of chemicals with AC50s corresponding to predicted cell membrane concentrations in the baseline toxicity range (i.e., >20-60 mM) and tabulate the number of chemicals with "volatility issues" (majority of chemical in headspace) and "solubility issues" (freely-dissolved concentration greater than water solubility after distribution). In addition, the predicted "equivalent EQP blood concentrations" (i.e., blood concentration at equilibrium with predicted cellular concentration) were compared to the AC50s as a function of hydrophobicity (log octanol-water partition or distribution ratio). The predicted equivalent EQP blood concentrations exceed the AC50 by up to a factor of 100 depending on hydrophobicity and assay conditions. The implications of using AC50s as direct surrogates for human blood concentrations when estimating the oral equivalent doses using a toxicokinetic model (i.e., reverse dosimetry) are then briefly discussed.
Collapse
Affiliation(s)
- James M. Armitage
- AES Armitage Environmental Sciences, Inc., Ottawa, ON K1L 8C3, Canada
- Correspondence:
| | - Alessandro Sangion
- ARC Arnot Research and Consulting, Inc., Toronto, ON M4M 1W4, Canada; (A.S.); (R.P.); (A.B.L.); (J.A.A.)
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON M1C 1A4, Canada
| | - Rohan Parmar
- ARC Arnot Research and Consulting, Inc., Toronto, ON M4M 1W4, Canada; (A.S.); (R.P.); (A.B.L.); (J.A.A.)
| | - Alexandra B. Looky
- ARC Arnot Research and Consulting, Inc., Toronto, ON M4M 1W4, Canada; (A.S.); (R.P.); (A.B.L.); (J.A.A.)
| | - Jon A. Arnot
- ARC Arnot Research and Consulting, Inc., Toronto, ON M4M 1W4, Canada; (A.S.); (R.P.); (A.B.L.); (J.A.A.)
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON M1C 1A4, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada
| |
Collapse
|
15
|
Borghoff SJ, Fitch SE, Black MB, McMullen PD, Andersen ME, Chappell GA. A systematic approach to evaluate plausible modes of actions for mouse lung tumors in mice exposed to 4-methylimidozole. Regul Toxicol Pharmacol 2021; 124:104977. [PMID: 34174380 DOI: 10.1016/j.yrtph.2021.104977] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 06/07/2021] [Accepted: 06/21/2021] [Indexed: 12/27/2022]
Abstract
The National Toxicology Program (NTP) reported that chronic dietary exposure to 4-methylimidazole (4-MeI) increased the incidence of lung adenomas/carcinomas beyond the normally high spontaneous rate in B6C3F1 mice. To examine plausible modes of action (MoAs) for mouse lung tumors (MLTs) upon exposure to high levels of 4-MeI, and their relevance in assessing human risk, a systematic approach was used to identify and evaluate mechanistic data (in vitro and in vivo) in the primary and secondary literature, along with high-throughput screening assay data. Study quality, relevance, and activity of mechanistic data identified across the evidence-base were organized according to key characteristics of carcinogens (KCCs) to identify potential key events in known or novel MLT MoAs. Integration of these evidence streams provided confirmation that 4-MeI lacks genotoxic and cytotoxic activity with some evidence to support a lack of mitogenic activity. Further evaluation of contextual and chemical-specific characteristics of 4-MeI was consequently undertaken. Due to lack of genotoxicity, along with transcriptomic and histopathological lung changes up to 28 and 90 days of exposure, the collective evidence suggests MLTs observed following exposure to high levels of 4-MeI develop at a late stage in the mouse chronic bioassay, albeit the exact MoA remains unclear.
Collapse
|
16
|
Ring C, Sipes NS, Hsieh JH, Carberry C, Koval LE, Klaren WD, Harris MA, Auerbach SS, Rager JE. Predictive modeling of biological responses in the rat liver using in vitro Tox21 bioactivity: Benefits from high-throughput toxicokinetics. Comput Toxicol 2021; 18:100166. [PMID: 34013136 PMCID: PMC8130852 DOI: 10.1016/j.comtox.2021.100166] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Computational methods are needed to more efficiently leverage data from in vitro cell-based models to predict what occurs within whole body systems after chemical insults. This study set out to test the hypothesis that in vitro high-throughput screening (HTS) data can more effectively predict in vivo biological responses when chemical disposition and toxicokinetic (TK) modeling are employed. In vitro HTS data from the Tox21 consortium were analyzed in concert with chemical disposition modeling to derive nominal, aqueous, and intracellular estimates of concentrations eliciting 50% maximal activity. In vivo biological responses were captured using rat liver transcriptomic data from the DrugMatrix and TG-Gates databases and evaluated for pathway enrichment. In vivo dosing data were translated to equivalent body concentrations using HTTK modeling. Random forest models were then trained and tested to predict in vivo pathway-level activity across 221 chemicals using in vitro bioactivity data and physicochemical properties as predictor variables, incorporating methods to address imbalanced training data resulting from high instances of inactivity. Model performance was quantified using the area under the receiver operator characteristic curve (AUC-ROC) and compared across pathways for different combinations of predictor variables. All models that included toxicokinetics were found to outperform those that excluded toxicokinetics. Biological interpretation of the model features revealed that rather than a direct mapping of in vitro assays to in vivo pathways, unexpected combinations of multiple in vitro assays predicted in vivo pathway-level activities. To demonstrate the utility of these findings, the highest-performing model was leveraged to make new predictions of in vivo biological responses across all biological pathways for remaining chemicals tested in Tox21 with adequate data coverage (n = 6617). These results demonstrate that, when chemical disposition and toxicokinetics are carefully considered, in vitro HT screening data can be used to effectively predict in vivo biological responses to chemicals.
Collapse
Affiliation(s)
- Caroline Ring
- ToxStrategies, Inc., Austin, TX 78751, United States
| | - Nisha S. Sipes
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, United States
| | - Jui-Hua Hsieh
- Kelly Government Solutions, Durham, NC 27709, United States
| | - Celeste Carberry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Lauren E. Koval
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - William D. Klaren
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77840, United States
| | | | - Scott S. Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, United States
| | - Julia E. Rager
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
- Curriculum in Toxicology and Environmental Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| |
Collapse
|
17
|
Harrill JA, Everett LJ, Haggard DE, Sheffield T, Bundy JL, Willis CM, Thomas RS, Shah I, Judson RS. High-Throughput Transcriptomics Platform for Screening Environmental Chemicals. Toxicol Sci 2021; 181:68-89. [PMID: 33538836 DOI: 10.1093/toxsci/kfab009] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
New approach methodologies (NAMs) that efficiently provide information about chemical hazard without using whole animals are needed to accelerate the pace of chemical risk assessments. Technological advancements in gene expression assays have made in vitro high-throughput transcriptomics (HTTr) a feasible option for NAMs-based hazard characterization of environmental chemicals. In this study, we evaluated the Templated Oligo with Sequencing Readout (TempO-Seq) assay for HTTr concentration-response screening of a small set of chemicals in the human-derived MCF7 cell model. Our experimental design included a variety of reference samples and reference chemical treatments in order to objectively evaluate TempO-Seq assay performance. To facilitate analysis of these data, we developed a robust and scalable bioinformatics pipeline using open-source tools. We also developed a novel gene expression signature-based concentration-response modeling approach and compared the results to a previously implemented workflow for concentration-response analysis of transcriptomics data using BMDExpress. Analysis of reference samples and reference chemical treatments demonstrated highly reproducible differential gene expression signatures. In addition, we found that aggregating signals from individual genes into gene signatures prior to concentration-response modeling yielded in vitro transcriptional biological pathway altering concentrations (BPACs) that were closely aligned with previous ToxCast high-throughput screening assays. Often these identified signatures were associated with the known molecular target of the chemicals in our test set as the most sensitive components of the overall transcriptional response. This work has resulted in a novel and scalable in vitro HTTr workflow that is suitable for high-throughput hazard evaluation of environmental chemicals.
Collapse
Affiliation(s)
- Joshua A Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Logan J Everett
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Derik E Haggard
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA.,Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee, USA
| | - Thomas Sheffield
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA.,Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee, USA
| | - Joseph L Bundy
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Clinton M Willis
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA.,Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee, USA
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Imran Shah
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Richard S Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| |
Collapse
|
18
|
Ribeiro DL, Machado ART, Machado C, Ferro Aissa A, Dos Santos PW, Barcelos GRM, Antunes LMG. p-synephrine induces transcriptional changes via the cAMP/PKA pathway but not cytotoxicity or mutagenicity in human gastrointestinal cells. J Toxicol Environ Health A 2021; 84:196-212. [PMID: 33292089 DOI: 10.1080/15287394.2020.1855490] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
p-Synephrine (SN) is an alkaloid added to thermogenic formulations for weight loss that is predominantly absorbed in the human gastrointestinal tract (GI). As the adverse effects of SN on GI cells remain unclear, the aim of present study was to examine whether SN affected cell viability, cell cycle kinetics, genomic stability, redox status, and expression of cAMP/PKA pathway genes related to metabolism/energy homeostasis in stomach mucosa (MNP01) and colon adenocarcinoma (Caco-2) human cells. p-Synephrine at 25-5000 μM was not cytotoxic to both cell lines. At 2-200 μM, SN increased the formation of reactive oxygen species (ROS) but also enhanced levels of antioxidant defense molecules glutathione (GSH) and catalase (CAT) activity, which may account for the absence of cytotoxicity/mutagenicity in both cell lines. SN induced expression of the cAMP/PKA pathway genes ADCY3 and MAPK1 in MNP01 cells and MAPK1, GNAS, PRKACA, and PRKAR2A in Caco-2 cells, as well as modulated the transcription of genes related to cell proliferation (JUN; AKT1) and inflammation (RELA; TNF) in both cell lines. Therefore, the improved antioxidant state mitigated pro-oxidative effects attributed to SN. Evidence indicates that SN does not appear to exhibit adverse potential but modulated the cAMP/PKA pathway in human GI cell lines.
Collapse
Affiliation(s)
- Diego Luis Ribeiro
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo ,Ribeirão Preto, Brazil
| | - Ana Rita Thomazela Machado
- Department Of Clinical Analyses, Toxicology, And Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo , : Ribeirão Preto, Brazil
| | - Carla Machado
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo ,Ribeirão Preto, Brazil
| | - Alexandre Ferro Aissa
- Department Of Clinical Analyses, Toxicology, And Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo , : Ribeirão Preto, Brazil
| | - Patrick Wellington Dos Santos
- Department Of Clinical Analyses, Toxicology, And Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo , : Ribeirão Preto, Brazil
| | | | - Lusânia Maria Greggi Antunes
- Department Of Clinical Analyses, Toxicology, And Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo , : Ribeirão Preto, Brazil
| |
Collapse
|
19
|
Jaeschke H, Murray FJ, Monnot AD, Jacobson-Kram D, Cohen SM, Hardisty JF, Atillasoy E, Hermanowski-Vosatka A, Kuffner E, Wikoff D, Chappell GA, Bandara SB, Deore M, Pitchaiyan SK, Eichenbaum G. Assessment of the biochemical pathways for acetaminophen toxicity: Implications for its carcinogenic hazard potential. Regul Toxicol Pharmacol 2021; 120:104859. [PMID: 33388367 DOI: 10.1016/j.yrtph.2020.104859] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 12/22/2020] [Accepted: 12/28/2020] [Indexed: 02/07/2023]
Abstract
In 2019 California's Office of Environmental Health Hazard Assessment (OEHHA) initiated a review of the carcinogenic hazard potential of acetaminophen. In parallel with this review, herein we evaluated the mechanistic data related to the steps and timing of cellular events following therapeutic recommended (≤4 g/day) and higher doses of acetaminophen that may cause hepatotoxicity to evaluate whether these changes indicate that acetaminophen is a carcinogenic hazard. At therapeutic recommended doses, acetaminophen forms limited amounts of N-acetyl-p-benzoquinone-imine (NAPQI) without adverse cellular effects. Following overdoses of acetaminophen, there is potential for more extensive formation of NAPQI and depletion of glutathione, which may result in mitochondrial dysfunction and DNA damage, but only at doses that result in cell death - thus making it implausible for acetaminophen to induce the kind of stable, genetic damage in the nucleus indicative of a genotoxic or carcinogenic hazard in humans. The collective data demonstrate a lack of a plausible mechanism related to carcinogenicity and are consistent with rodent cancer bioassays, epidemiological results reviewed in companion manuscripts in this issue, as well as conclusions of multiple international health authorities.
Collapse
Affiliation(s)
- Hartmut Jaeschke
- University of Kansas Medical Center, Department of Pharmacology, Toxicology & Therapeutics, Kansas City, KS, USA
| | | | | | | | - Samuel M Cohen
- University of Nebraska Medical Center, Havlik-Wall Professor of Oncology, Department of Pathology and Microbiology, Omaha, NE, USA
| | - Jerry F Hardisty
- Experimental Pathology Laboratories, Inc., Research Triangle Park, NC, USA
| | | | | | - Edwin Kuffner
- Johnson & Johnson Consumer Health, Fort Washington, PA, USA
| | | | | | | | | | | | | |
Collapse
|
20
|
Abstract
Cardiovascular (CV) disease is one of the most prevalent public health concerns, and mounting evidence supports the contribution of environmental chemicals to CV disease burden. In this study, we performed cardiotoxicity profiling for the Tox21 chemical library by focusing on high-throughput screening (HTS) assays whose targets are associated with adverse events related to CV failure modes. Our objective was to develop new hypotheses around environmental chemicals of potential interest for adverse CV outcomes using Tox21/ToxCast HTS data. Molecular and cellular events linked to six failure modes of CV toxicity were cross-referenced with 1399 Tox21/ToxCast assays to identify cardio-relevant bioactivity signatures. The resulting 40 targets, measured in 314 assays, were integrated via a ToxPi visualization tool and ranking system to prioritize 1138 chemicals based upon formal integration across multiple domains of information. Filtering was performed based on cytotoxicity and generalized cell stress endpoints to try and isolate chemicals with effects specific to CV biology, and bioactivity- and structure-based clustering identified subgroups of chemicals preferentially affecting targets such as ion channels and vascular tissue biology. Our approach identified drugs with known cardiotoxic effects, such as estrogenic modulators like clomiphene and raloxifene, anti-arrhythmic drugs like amiodarone and haloperidol, and antipsychotic drugs like chlorpromazine. Several classes of environmental chemicals such as organotins, bisphenol-like chemicals, pesticides, and quaternary ammonium compounds demonstrated strong bioactivity against CV targets; these were compared to existing data in the literature (e.g., from cardiomyocytes, animal data, or human epidemiological studies) and prioritized for further testing.
Collapse
Affiliation(s)
- Shagun Krishna
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, 530 Davis Drive, Research Triangle Park, North Carolina 27560, United States
| | - Brian Berridge
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, 530 Davis Drive, Research Triangle Park, North Carolina 27560, United States
| | - Nicole Kleinstreuer
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, 530 Davis Drive, Research Triangle Park, North Carolina 27560, United States
| |
Collapse
|
21
|
Hsieh CJ, Sun M, Osborne G, Ricker K, Tsai FC, Li K, Tomar R, Phuong J, Schmitz R, Sandy MS. Response to “Comment on Coumarin Hazard Identification”. Int J Toxicol 2020; 39:493-494. [DOI: 10.1177/1091581820945412] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- ChingYi Jennifer Hsieh
- Office of Environmental Health Hazard Assessment, CalEPA, Sacramento and Oakland, CA, USA
| | - Meng Sun
- Office of Environmental Health Hazard Assessment, CalEPA, Sacramento and Oakland, CA, USA
| | - Gwendolyn Osborne
- Office of Environmental Health Hazard Assessment, CalEPA, Sacramento and Oakland, CA, USA
| | - Karin Ricker
- Office of Environmental Health Hazard Assessment, CalEPA, Sacramento and Oakland, CA, USA
| | - Feng C. Tsai
- Office of Environmental Health Hazard Assessment, CalEPA, Sacramento and Oakland, CA, USA
| | - Kate Li
- Office of Environmental Health Hazard Assessment, CalEPA, Sacramento and Oakland, CA, USA
| | - Rajpal Tomar
- Office of Environmental Health Hazard Assessment, CalEPA, Sacramento and Oakland, CA, USA
- Retired
| | - Jimmy Phuong
- Department of Biomedical and Health Informatics, University of Washington, Seattle, WA, USA
| | - Rose Schmitz
- Office of Environmental Health Hazard Assessment, CalEPA, Sacramento and Oakland, CA, USA
| | - Martha S. Sandy
- Office of Environmental Health Hazard Assessment, CalEPA, Sacramento and Oakland, CA, USA
| |
Collapse
|
22
|
Krebs A, van Vugt-Lussenburg BMA, Waldmann T, Albrecht W, Boei J, Ter Braak B, Brajnik M, Braunbeck T, Brecklinghaus T, Busquet F, Dinnyes A, Dokler J, Dolde X, Exner TE, Fisher C, Fluri D, Forsby A, Hengstler JG, Holzer AK, Janstova Z, Jennings P, Kisitu J, Kobolak J, Kumar M, Limonciel A, Lundqvist J, Mihalik B, Moritz W, Pallocca G, Ulloa APC, Pastor M, Rovida C, Sarkans U, Schimming JP, Schmidt BZ, Stöber R, Strassfeld T, van de Water B, Wilmes A, van der Burg B, Verfaillie CM, von Hellfeld R, Vrieling H, Vrijenhoek NG, Leist M. The EU-ToxRisk method documentation, data processing and chemical testing pipeline for the regulatory use of new approach methods. Arch Toxicol 2020; 94:2435-61. [PMID: 32632539 DOI: 10.1007/s00204-020-02802-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 06/03/2020] [Indexed: 12/17/2022]
Abstract
Hazard assessment, based on new approach methods (NAM), requires the use of batteries of assays, where individual tests may be contributed by different laboratories. A unified strategy for such collaborative testing is presented. It details all procedures required to allow test information to be usable for integrated hazard assessment, strategic project decisions and/or for regulatory purposes. The EU-ToxRisk project developed a strategy to provide regulatorily valid data, and exemplified this using a panel of > 20 assays (with > 50 individual endpoints), each exposed to 19 well-known test compounds (e.g. rotenone, colchicine, mercury, paracetamol, rifampicine, paraquat, taxol). Examples of strategy implementation are provided for all aspects required to ensure data validity: (i) documentation of test methods in a publicly accessible database; (ii) deposition of standard operating procedures (SOP) at the European Union DB-ALM repository; (iii) test readiness scoring accoding to defined criteria; (iv) disclosure of the pipeline for data processing; (v) link of uncertainty measures and metadata to the data; (vi) definition of test chemicals, their handling and their behavior in test media; (vii) specification of the test purpose and overall evaluation plans. Moreover, data generation was exemplified by providing results from 25 reporter assays. A complete evaluation of the entire test battery will be described elsewhere. A major learning from the retrospective analysis of this large testing project was the need for thorough definitions of the above strategy aspects, ideally in form of a study pre-registration, to allow adequate interpretation of the data and to ensure overall scientific/toxicological validity.
Collapse
|
23
|
Bailey LA, Rhomberg LR. Incorporating ToxCast™ data into naphthalene human health risk assessment. Toxicol In Vitro 2020; 67:104913. [PMID: 32526344 DOI: 10.1016/j.tiv.2020.104913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 05/27/2020] [Accepted: 06/04/2020] [Indexed: 10/24/2022]
Abstract
Chronic inhalation of naphthalene causes nasal olfactory epithelial tumors in rats and benign lung adenomas in mice. The available human data do not establish an association between naphthalene and increased respiratory cancer risk. Therefore, cancer risk assessment of naphthalene in humans depends predominantly on experimental evidence from rodents. The United States Environmental Protection Agency's (US EPA) Toxicity Forecaster (ToxCast™) database contains data from 710 in vitro assays for naphthalene, the majority of which were conducted in human cells. Of these assays, only 18 were active for naphthalene, and all were in human liver cells. No assays were active in human bronchial epithelial cells. In our analysis, all of the active naphthalene ToxCast assay data were reviewed and used to: 1) determine naphthalene human inhalation concentrations corresponding to relevant activity concentrations for all active naphthalene assays, using a physiologically based pharmacokinetic (PBPK) model; and 2) evaluate the transcriptional responses for active assays in the context of consistency with the larger naphthalene data set and proposed modes of action (MoAs) for naphthalene toxicity and carcinogenicity. The transcriptional responses in liver cells largely reflect cellular activities related to oxidative stress and chronic inflammation. Overall, the results from our analysis of the active ToxCast assays for naphthalene are consistent with conclusions from our earlier weight-of-evidence evaluation for naphthalene carcinogenesis.
Collapse
Affiliation(s)
- Lisa A Bailey
- Gradient, One Beacon Street, Boston, MA 02108, United States of America.
| | - Lorenz R Rhomberg
- Gradient, One Beacon Street, Boston, MA 02108, United States of America
| |
Collapse
|
24
|
Chen Z, Liu Y, Wright FA, Chiu WA, Rusyn I. Rapid hazard characterization of environmental chemicals using a compendium of human cell lines from different organs. ALTEX 2020; 37:623-638. [PMID: 32521033 PMCID: PMC7941183 DOI: 10.14573/altex.2002291] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 06/08/2020] [Indexed: 02/07/2023]
Abstract
The lack of adequate toxicity data for the vast majority of chemicals in the environment has spurred the development of new approach methodologies (NAMs). This study aimed to develop a practical high-throughput in vitro model for rapidly evaluating potential hazards of chemicals using a small number of human cells. Forty-two compounds were tested using human induced pluripotent stem cell (iPSC)-derived cells (hepatocytes, neurons, cardiomyocytes and endothelial cells), and a primary endothelial cell line. Both functional and cytotoxicity endpoints were evaluated using high-content imaging. Concentration-response was used to derive points-of-departure (POD). PODs were integrated with ToxPi and used as surrogate NAM-based PODs for risk characterization. We found chemical class-specific similarity among the chemicals tested; metal salts exhibited the highest overall bioactivity. We also observed cell type-specific patterns among classes of chemicals, indicating the ability of the proposed in vitro model to recognize effects on different cell types. Compared to available NAM datasets, such as ToxCast/Tox21 and chemical structure-based descriptors, we found that the data from the five-cell-type model was as good or even better in assigning compounds to chemical classes. Additionally, the PODs from this model performed well as a conservative surrogate for regulatory in vivo PODs and were less likely to underestimate in vivo potency and potential risk compared to other NAM-based PODs. In summary, we demonstrate the potential of this in vitro screening model to inform rapid risk-based decision-making through ranking, clustering, and assessment of both hazard and risks of diverse environmental chemicals.
Collapse
Affiliation(s)
- Zunwei Chen
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
| | - Yizhong Liu
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
| | - Fred A. Wright
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
- Departments of Statistics and Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - Weihsueh A. Chiu
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
| |
Collapse
|
25
|
Chappell G, Britt J, Borghoff S. Systematic assessment of mechanistic data for FDA-certified food colors and neurodevelopmental processes. Food Chem Toxicol 2020; 140:111310. [DOI: 10.1016/j.fct.2020.111310] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 03/23/2020] [Accepted: 03/26/2020] [Indexed: 11/23/2022]
|
26
|
Huchthausen J, Mühlenbrink M, König M, Escher BI, Henneberger L. Experimental Exposure Assessment of Ionizable Organic Chemicals in In Vitro Cell-Based Bioassays. Chem Res Toxicol 2020; 33:1845-1854. [DOI: 10.1021/acs.chemrestox.0c00067] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Julia Huchthausen
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research − UFZ, Permoserstr. 15, 04318 Leipzig, Germany
| | - Marie Mühlenbrink
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research − UFZ, Permoserstr. 15, 04318 Leipzig, Germany
| | - Maria König
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research − UFZ, Permoserstr. 15, 04318 Leipzig, Germany
| | - Beate I. Escher
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research − UFZ, Permoserstr. 15, 04318 Leipzig, Germany
- Environmental Toxicology, Center for Applied Geoscience, Eberhard Karls University Tübingen, 72074 Tübingen, Germany
| | - Luise Henneberger
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research − UFZ, Permoserstr. 15, 04318 Leipzig, Germany
| |
Collapse
|
27
|
Abstract
Tox21 and ToxCast are high-throughput in vitro screening programs coordinated by the U.S. National Toxicology Program and the U.S. Environmental Protection Agency, respectively, with the goal of forecasting biological effects in vivo based on bioactivity profiling. The present study investigated whether mechanistic insights in the biological targets of food-relevant chemicals can be obtained from ToxCast results when the chemicals are grouped according to structural similarity. Starting from the 556 direct additives that have been identified in the ToxCast database by Karmaus et al. [Karmaus, A. L., Trautman, T. D., Krishan, M., Filer, D. L., and Fix, L. A. (2017). Curation of food-relevant chemicals in ToxCast. Food Chem. Toxicol. 103, 174-182.], the results showed that, despite the limited number of assays in which the chemical groups have been tested, sufficient results are available within so-called "DNA binding" and "nuclear receptor" target families to profile the biological activities of the defined chemical groups for these targets. The most obvious activity identified was the estrogen receptor-mediated actions of the chemical group containing parabens and structurally related gallates, as well the chemical group containing genistein and daidzein (the latter 2 being particularly active toward estrogen receptor β as a potential health benefit). These group effects, as well as the biological activities of other chemical groups, were evaluated in a series of case studies. Overall, the results of the present study suggest that high-throughput screening data could add to the evidence considered for regulatory risk assessment of food chemicals and to the evaluation of desirable effects of nutrients and phytonutrients. The data will be particularly useful for providing mechanistic information and to fill data gaps with read-across.
Collapse
Affiliation(s)
- Ans Punt
- Wageningen Food Safety Research, 6700 AE Wageningen, The Netherlands
| | - James Firman
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK
| | - Alan Boobis
- National Heart & Lung Institute, Imperial College London, London W12 0NN, UK
| | - Mark Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK
| | | | - Martin F Wilks
- Swiss Centre for Applied Human Toxicology, University of Basel, 4055 Basel, Switzerland
| | - Paul A Hepburn
- Unilever, Safety & Environmental Assurance Centre, Colworth Science Park, Sharnbrook MK44 1LQ, UK
| | - Anette Thiel
- DSM Nutritional Products, 4303 Kaiseraugst, Switzerland
| | | |
Collapse
|
28
|
Zavala J, Freedman AN, Szilagyi JT, Jaspers I, Wambaugh JF, Higuchi M, Rager JE. New Approach Methods to Evaluate Health Risks of Air Pollutants: Critical Design Considerations for In Vitro Exposure Testing. Int J Environ Res Public Health 2020; 17:E2124. [PMID: 32210027 DOI: 10.3390/ijerph17062124] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 03/11/2020] [Accepted: 03/19/2020] [Indexed: 12/20/2022]
Abstract
Air pollution consists of highly variable and complex mixtures recognized as major contributors to morbidity and mortality worldwide. The vast number of chemicals, coupled with limitations surrounding epidemiological and animal studies, has necessitated the development of new approach methods (NAMs) to evaluate air pollution toxicity. These alternative approaches include in vitro (cell-based) models, wherein toxicity of test atmospheres can be evaluated with increased efficiency compared to in vivo studies. In vitro exposure systems have recently been developed with the goal of evaluating air pollutant-induced toxicity; though the specific design parameters implemented in these NAMs-based studies remain in flux. This review aims to outline important design parameters to consider when using in vitro methods to evaluate air pollutant toxicity, with the goal of providing increased accuracy, reproducibility, and effectiveness when incorporating in vitro data into human health evaluations. This review is unique in that experimental considerations and lessons learned are provided, as gathered from first-hand experience developing and testing in vitro models coupled to exposure systems. Reviewed design aspects include cell models, cell exposure conditions, exposure chambers, and toxicity endpoints. Strategies are also discussed to incorporate in vitro findings into the context of in vivo toxicity and overall risk assessment.
Collapse
|
29
|
Mansouri K, Kleinstreuer N, Abdelaziz AM, Alberga D, Alves VM, Andersson PL, Andrade CH, Bai F, Balabin I, Ballabio D, Benfenati E, Bhhatarai B, Boyer S, Chen J, Consonni V, Farag S, Fourches D, García-Sosa AT, Gramatica P, Grisoni F, Grulke CM, Hong H, Horvath D, Hu X, Huang R, Jeliazkova N, Li J, Li X, Liu H, Manganelli S, Mangiatordi GF, Maran U, Marcou G, Martin T, Muratov E, Nguyen DT, Nicolotti O, Nikolov NG, Norinder U, Papa E, Petitjean M, Piir G, Pogodin P, Poroikov V, Qiao X, Richard AM, Roncaglioni A, Ruiz P, Rupakheti C, Sakkiah S, Sangion A, Schramm KW, Selvaraj C, Shah I, Sild S, Sun L, Taboureau O, Tang Y, Tetko IV, Todeschini R, Tong W, Trisciuzzi D, Tropsha A, Van Den Driessche G, Varnek A, Wang Z, Wedebye EB, Williams AJ, Xie H, Zakharov AV, Zheng Z, Judson RS. CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity. Environ Health Perspect 2020; 128:27002. [PMID: 32074470 DOI: 10.23645/epacomptox.5176876] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
BACKGROUND Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling. OBJECTIVES In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP). METHODS The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast™ metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast™/Tox21 HTS in vitro assays. RESULTS The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set. DISCUSSION The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of ∼875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment. https://doi.org/10.1289/EHP5580.
Collapse
Affiliation(s)
- Kamel Mansouri
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
- ScitoVation LLC, Research Triangle Park, North Carolina, USA
- Integrated Laboratory Systems, Inc., Morrisville, North Carolina, USA
| | - Nicole Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Ahmed M Abdelaziz
- Technische Universität München, Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt, Department für Biowissenschaftliche Grundlagen, Weihenstephaner Steig 23, 85350 Freising, Germany
| | - Domenico Alberga
- Department of Pharmacy-Drug Sciences, University of Bari, Bari, Italy
| | - Vinicius M Alves
- Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, Brazil
- Laboratory for Molecular Modeling, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Carolina H Andrade
- Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, Brazil
| | - Fang Bai
- School of Pharmacy, Lanzhou University, China
| | - Ilya Balabin
- Information Systems & Global Solutions (IS&GS), Lockheed Martin, USA
| | - Davide Ballabio
- Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Emilio Benfenati
- Istituto di Ricerche Farmacologiche "Mario Negri", IRCCS, Milan, Italy
| | - Barun Bhhatarai
- QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences, University of Insubria, Varese, Italy
| | - Scott Boyer
- Swedish Toxicology Sciences Research Center, Karolinska Institutet, Södertälje, Sweden
| | - Jingwen Chen
- School of Environmental Science and Technology, Dalian University of Technology, Dalian, China
| | - Viviana Consonni
- Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Sherif Farag
- Laboratory for Molecular Modeling, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Denis Fourches
- Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, USA
| | | | - Paola Gramatica
- QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences, University of Insubria, Varese, Italy
| | - Francesca Grisoni
- Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Chris M Grulke
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
| | - Huixiao Hong
- Division of Bioinformatics and Biostatistics, National Center for Toxicology Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | - Dragos Horvath
- Laboratoire de Chémoinformatique-UMR7140, University of Strasbourg/CNRS, Strasbourg, France
| | - Xin Hu
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Ruili Huang
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | | | - Jiazhong Li
- School of Pharmacy, Lanzhou University, China
| | - Xuehua Li
- School of Environmental Science and Technology, Dalian University of Technology, Dalian, China
| | | | - Serena Manganelli
- Istituto di Ricerche Farmacologiche "Mario Negri", IRCCS, Milan, Italy
| | | | - Uko Maran
- Institute of Chemistry, University of Tartu, Tartu, Estonia
| | - Gilles Marcou
- Laboratoire de Chémoinformatique-UMR7140, University of Strasbourg/CNRS, Strasbourg, France
| | - Todd Martin
- National Risk Management Research Laboratory, U.S. EPA, Cincinnati, Ohio, USA
| | - Eugene Muratov
- Laboratory for Molecular Modeling, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Dac-Trung Nguyen
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Orazio Nicolotti
- Department of Pharmacy-Drug Sciences, University of Bari, Bari, Italy
| | - Nikolai G Nikolov
- Division of Risk Assessment and Nutrition, National Food Institute, Technical University of Denmark, Copenhagen, Denmark
| | - Ulf Norinder
- Swedish Toxicology Sciences Research Center, Karolinska Institutet, Södertälje, Sweden
| | - Ester Papa
- QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences, University of Insubria, Varese, Italy
| | - Michel Petitjean
- Computational Modeling of Protein-Ligand Interactions (CMPLI)-INSERM UMR 8251, INSERM ERL U1133, Functional and Adaptative Biology (BFA), Universite de Paris, Paris, France
| | - Geven Piir
- Institute of Chemistry, University of Tartu, Tartu, Estonia
| | - Pavel Pogodin
- Institute of Biomedical Chemistry IBMC, 10 Building 8, Pogodinskaya st., Moscow 119121, Russia
| | - Vladimir Poroikov
- Institute of Biomedical Chemistry IBMC, 10 Building 8, Pogodinskaya st., Moscow 119121, Russia
| | - Xianliang Qiao
- School of Environmental Science and Technology, Dalian University of Technology, Dalian, China
| | - Ann M Richard
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
| | | | - Patricia Ruiz
- Computational Toxicology and Methods Development Laboratory, Division of Toxicology and Human Health Sciences, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Chetan Rupakheti
- National Risk Management Research Laboratory, U.S. EPA, Cincinnati, Ohio, USA
- Department of Biochemistry and Molecular Biophysics, University of Chicago, Chicago, Illinois, USA
| | - Sugunadevi Sakkiah
- Division of Bioinformatics and Biostatistics, National Center for Toxicology Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | - Alessandro Sangion
- QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences, University of Insubria, Varese, Italy
| | - Karl-Werner Schramm
- Technische Universität München, Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt, Department für Biowissenschaftliche Grundlagen, Weihenstephaner Steig 23, 85350 Freising, Germany
| | - Chandrabose Selvaraj
- Division of Bioinformatics and Biostatistics, National Center for Toxicology Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | - Imran Shah
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
| | - Sulev Sild
- Institute of Chemistry, University of Tartu, Tartu, Estonia
| | - Lixia Sun
- Department of Pharmaceutical Sciences, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Olivier Taboureau
- Computational Modeling of Protein-Ligand Interactions (CMPLI)-INSERM UMR 8251, INSERM ERL U1133, Functional and Adaptative Biology (BFA), Universite de Paris, Paris, France
| | - Yun Tang
- Department of Pharmaceutical Sciences, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Igor V Tetko
- BIGCHEM GmbH, Neuherberg, Germany
- Helmholtz Zentrum Muenchen - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Roberto Todeschini
- Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicology Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | | | - Alexander Tropsha
- Laboratory for Molecular Modeling, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - George Van Den Driessche
- Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, USA
| | - Alexandre Varnek
- Laboratoire de Chémoinformatique-UMR7140, University of Strasbourg/CNRS, Strasbourg, France
| | - Zhongyu Wang
- School of Environmental Science and Technology, Dalian University of Technology, Dalian, China
| | - Eva B Wedebye
- Division of Risk Assessment and Nutrition, National Food Institute, Technical University of Denmark, Copenhagen, Denmark
| | - Antony J Williams
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
| | - Hongbin Xie
- School of Environmental Science and Technology, Dalian University of Technology, Dalian, China
| | - Alexey V Zakharov
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Ziye Zheng
- Chemistry Department, Umeå University, Umeå, Sweden
| | - Richard S Judson
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
| |
Collapse
|
30
|
Mansouri K, Kleinstreuer N, Abdelaziz AM, Alberga D, Alves VM, Andersson PL, Andrade CH, Bai F, Balabin I, Ballabio D, Benfenati E, Bhhatarai B, Boyer S, Chen J, Consonni V, Farag S, Fourches D, García-Sosa AT, Gramatica P, Grisoni F, Grulke CM, Hong H, Horvath D, Hu X, Huang R, Jeliazkova N, Li J, Li X, Liu H, Manganelli S, Mangiatordi GF, Maran U, Marcou G, Martin T, Muratov E, Nguyen DT, Nicolotti O, Nikolov NG, Norinder U, Papa E, Petitjean M, Piir G, Pogodin P, Poroikov V, Qiao X, Richard AM, Roncaglioni A, Ruiz P, Rupakheti C, Sakkiah S, Sangion A, Schramm KW, Selvaraj C, Shah I, Sild S, Sun L, Taboureau O, Tang Y, Tetko IV, Todeschini R, Tong W, Trisciuzzi D, Tropsha A, Van Den Driessche G, Varnek A, Wang Z, Wedebye EB, Williams AJ, Xie H, Zakharov AV, Zheng Z, Judson RS. CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity. Environ Health Perspect 2020; 128:27002. [PMID: 32074470 PMCID: PMC7064318 DOI: 10.1289/ehp5580] [Citation(s) in RCA: 92] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 11/27/2019] [Accepted: 12/05/2019] [Indexed: 05/04/2023]
Abstract
BACKGROUND Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling. OBJECTIVES In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP). METHODS The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast™ metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast™/Tox21 HTS in vitro assays. RESULTS The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set. DISCUSSION The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of ∼ 875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment. https://doi.org/10.1289/EHP5580.
Collapse
Affiliation(s)
- Kamel Mansouri
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
- ScitoVation LLC, Research Triangle Park, North Carolina, USA
- Integrated Laboratory Systems, Inc., Morrisville, North Carolina, USA
| | - Nicole Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Ahmed M. Abdelaziz
- Technische Universität München, Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt, Department für Biowissenschaftliche Grundlagen, Weihenstephaner Steig 23, 85350 Freising, Germany
| | - Domenico Alberga
- Department of Pharmacy-Drug Sciences, University of Bari, Bari, Italy
| | - Vinicius M. Alves
- Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, Brazil
- Laboratory for Molecular Modeling, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Carolina H. Andrade
- Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, Brazil
| | - Fang Bai
- School of Pharmacy, Lanzhou University, China
| | - Ilya Balabin
- Information Systems & Global Solutions (IS&GS), Lockheed Martin, USA
| | - Davide Ballabio
- Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Emilio Benfenati
- Istituto di Ricerche Farmacologiche “Mario Negri”, IRCCS, Milan, Italy
| | - Barun Bhhatarai
- QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences, University of Insubria, Varese, Italy
| | - Scott Boyer
- Swedish Toxicology Sciences Research Center, Karolinska Institutet, Södertälje, Sweden
| | - Jingwen Chen
- School of Environmental Science and Technology, Dalian University of Technology, Dalian, China
| | - Viviana Consonni
- Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Sherif Farag
- Laboratory for Molecular Modeling, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Denis Fourches
- Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, USA
| | | | - Paola Gramatica
- QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences, University of Insubria, Varese, Italy
| | - Francesca Grisoni
- Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Chris M. Grulke
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
| | - Huixiao Hong
- Division of Bioinformatics and Biostatistics, National Center for Toxicology Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | - Dragos Horvath
- Laboratoire de Chémoinformatique—UMR7140, University of Strasbourg/CNRS, Strasbourg, France
| | - Xin Hu
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Ruili Huang
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | | | - Jiazhong Li
- School of Pharmacy, Lanzhou University, China
| | - Xuehua Li
- School of Environmental Science and Technology, Dalian University of Technology, Dalian, China
| | | | - Serena Manganelli
- Istituto di Ricerche Farmacologiche “Mario Negri”, IRCCS, Milan, Italy
| | | | - Uko Maran
- Institute of Chemistry, University of Tartu, Tartu, Estonia
| | - Gilles Marcou
- Laboratoire de Chémoinformatique—UMR7140, University of Strasbourg/CNRS, Strasbourg, France
| | - Todd Martin
- National Risk Management Research Laboratory, U.S. EPA, Cincinnati, Ohio, USA
| | - Eugene Muratov
- Laboratory for Molecular Modeling, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Dac-Trung Nguyen
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Orazio Nicolotti
- Department of Pharmacy-Drug Sciences, University of Bari, Bari, Italy
| | - Nikolai G. Nikolov
- Division of Risk Assessment and Nutrition, National Food Institute, Technical University of Denmark, Copenhagen, Denmark
| | - Ulf Norinder
- Swedish Toxicology Sciences Research Center, Karolinska Institutet, Södertälje, Sweden
| | - Ester Papa
- QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences, University of Insubria, Varese, Italy
| | - Michel Petitjean
- Computational Modeling of Protein-Ligand Interactions (CMPLI)–INSERM UMR 8251, INSERM ERL U1133, Functional and Adaptative Biology (BFA), Universite de Paris, Paris, France
| | - Geven Piir
- Institute of Chemistry, University of Tartu, Tartu, Estonia
| | - Pavel Pogodin
- Institute of Biomedical Chemistry IBMC, 10 Building 8, Pogodinskaya st., Moscow 119121, Russia
| | - Vladimir Poroikov
- Institute of Biomedical Chemistry IBMC, 10 Building 8, Pogodinskaya st., Moscow 119121, Russia
| | - Xianliang Qiao
- School of Environmental Science and Technology, Dalian University of Technology, Dalian, China
| | - Ann M. Richard
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
| | | | - Patricia Ruiz
- Computational Toxicology and Methods Development Laboratory, Division of Toxicology and Human Health Sciences, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Chetan Rupakheti
- National Risk Management Research Laboratory, U.S. EPA, Cincinnati, Ohio, USA
- Department of Biochemistry and Molecular Biophysics, University of Chicago, Chicago, Illinois, USA
| | - Sugunadevi Sakkiah
- Division of Bioinformatics and Biostatistics, National Center for Toxicology Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | - Alessandro Sangion
- QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences, University of Insubria, Varese, Italy
| | - Karl-Werner Schramm
- Technische Universität München, Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt, Department für Biowissenschaftliche Grundlagen, Weihenstephaner Steig 23, 85350 Freising, Germany
| | - Chandrabose Selvaraj
- Division of Bioinformatics and Biostatistics, National Center for Toxicology Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | - Imran Shah
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
| | - Sulev Sild
- Institute of Chemistry, University of Tartu, Tartu, Estonia
| | - Lixia Sun
- Department of Pharmaceutical Sciences, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Olivier Taboureau
- Computational Modeling of Protein-Ligand Interactions (CMPLI)–INSERM UMR 8251, INSERM ERL U1133, Functional and Adaptative Biology (BFA), Universite de Paris, Paris, France
| | - Yun Tang
- Department of Pharmaceutical Sciences, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Igor V. Tetko
- BIGCHEM GmbH, Neuherberg, Germany
- Helmholtz Zentrum Muenchen – German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Roberto Todeschini
- Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicology Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | | | - Alexander Tropsha
- Laboratory for Molecular Modeling, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - George Van Den Driessche
- Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, USA
| | - Alexandre Varnek
- Laboratoire de Chémoinformatique—UMR7140, University of Strasbourg/CNRS, Strasbourg, France
| | - Zhongyu Wang
- School of Environmental Science and Technology, Dalian University of Technology, Dalian, China
| | - Eva B. Wedebye
- Division of Risk Assessment and Nutrition, National Food Institute, Technical University of Denmark, Copenhagen, Denmark
| | - Antony J. Williams
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
| | - Hongbin Xie
- School of Environmental Science and Technology, Dalian University of Technology, Dalian, China
| | - Alexey V. Zakharov
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Ziye Zheng
- Chemistry Department, Umeå University, Umeå, Sweden
| | - Richard S. Judson
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, North Carolina, USA
| |
Collapse
|
31
|
Wikoff D, Chappell G, Fitch S, Doepker C, Borghoff S. Lack of potential carcinogenicity for aspartame – Systematic evaluation and integration of mechanistic data into the totality of the evidence. Food Chem Toxicol 2020; 135:110866. [DOI: 10.1016/j.fct.2019.110866] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 09/24/2019] [Accepted: 10/01/2019] [Indexed: 12/30/2022]
|
32
|
Chappell GA, Borghoff SJ, Pham LL, Doepker CL, Wikoff DS. Lack of potential carcinogenicity for sucralose - Systematic evaluation and integration of mechanistic data into the totality of the evidence. Food Chem Toxicol 2019; 135:110898. [PMID: 31654706 DOI: 10.1016/j.fct.2019.110898] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 10/15/2019] [Accepted: 10/18/2019] [Indexed: 12/16/2022]
Abstract
Sucralose is widely used as a sugar substitute. Many studies and authoritative reviews have concluded that sucralose is non-carcinogenic, based primarily on animal cancer bioassays and genotoxicity data. To add to the body of knowledge on the potential carcinogenicity of sucralose, a systematic assessment of mechanistic data was conducted. This entailed using a framework developed for the quantitative integration of data related to the proposed key characteristics of carcinogens (KCCs). Data from peer-reviewed literature and the ToxCast/Tox21 database were evaluated using an algorithm that weights data for quality and relevance. The resulting integration demonstrated an overall lack of activity for sucralose across the KCCs, with no "strong" activity observed for any KCC. Almost all data collected demonstrated inactivity, including those conducted in human models. The overall lack of activity in mechanistic data is consistent with findings from animal cancer bioassays. The few instances of activity across the KCC were generally accompanied by limitations in study design in the context of either quality and/or dose and model relevance, highlighted upon integration of the totality of the evidence. The findings from this comprehensive and integrative evaluation of mechanistic data support prior conclusions that sucralose is unlikely to be carcinogenic in humans.
Collapse
Affiliation(s)
| | | | - L L Pham
- ToxStrategies, Inc., Asheville, NC, USA
| | | | | |
Collapse
|
33
|
Rooney JP, Chorley B, Kleinstreuer N, Corton JC. Identification of Androgen Receptor Modulators in a Prostate Cancer Cell Line Microarray Compendium. Toxicol Sci 2019; 166:146-162. [PMID: 30085300 DOI: 10.1093/toxsci/kfy187] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
High-throughput transcriptomic (HTTr) technologies are increasingly being used to screen environmental chemicals in vitro to identify molecular targets and provide mechanistic context for regulatory testing. Here, we describe the development and validation of a novel gene expression biomarker to identify androgen receptor (AR)-modulating chemicals using a pattern matching method. Androgen receptor biomarker genes were identified by their consistent expression after exposure to 4 AR agonists and 4 AR antagonists and included only those genes that were regulated by AR. The 51 gene biomarker was evaluated as a predictive tool using the fold-change, rank-based Running Fisher algorithm. Using 158 comparisons from cells treated with 95 chemicals, the biomarker gave balanced accuracies for prediction of AR activation or AR suppression of 97% or 98%, respectively. The biomarker correctly classified 16 out of the 17 AR reference antagonists including those that are "weak" and "very weak". Predictions based on microarray profiles from AR-positive LAPC-4 cells treated with 28 chemicals in antagonist mode were compared with those from an AR pathway model which used 11 in vitro HT assays. The balanced accuracy for suppression was 93%. Using our approach, we identified conditions in which AR was modulated in a large collection of microarray profiles from prostate cancer cell lines including (1) constitutively active mutants or knockdown of AR, (2) decreases in availability of androgens by castration or removal from media, and (3) exposure to chemical modulators that work through indirect mechanisms including suppression of AR expression. These results demonstrate that the AR gene expression biomarker could be a useful tool in HTTr to identify AR modulators.
Collapse
Affiliation(s)
- John P Rooney
- Oak Ridge Institute for Science and Education (ORISE), Research Triangle Park, North Carolina 27711.,Integrated Systems Toxicology Division, US-EPA, Research Triangle Park, North Carolina 27711
| | - Brian Chorley
- Integrated Systems Toxicology Division, US-EPA, Research Triangle Park, North Carolina 27711
| | - Nicole Kleinstreuer
- NTP Interagency Center for the Evaluation of Alternative Toxicological Methods, NTP, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina
| | - J Christopher Corton
- Integrated Systems Toxicology Division, US-EPA, Research Triangle Park, North Carolina 27711
| |
Collapse
|
34
|
Paul-Friedman K, Martin M, Crofton KM, Hsu CW, Sakamuru S, Zhao J, Xia M, Huang R, Stavreva DA, Soni V, Varticovski L, Raziuddin R, Hager GL, Houck KA. Limited Chemical Structural Diversity Found to Modulate Thyroid Hormone Receptor in the Tox21 Chemical Library. Environ Health Perspect 2019; 127:97009. [PMID: 31566444 PMCID: PMC6792352 DOI: 10.1289/ehp5314] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
BACKGROUND Thyroid hormone receptors (TRs) are critical endocrine receptors that regulate a multitude of processes in adult and developing organisms, and thyroid hormone disruption is of high concern for neurodevelopmental and reproductive toxicities in particular. To date, only a small number of chemical classes have been identified as possible TR modulators, and the receptors appear highly selective with respect to the ligand structural diversity. Thus, the question of whether TRs are an important screening target for protection of human and wildlife health remains. OBJECTIVE Our goal was to evaluate the hypothesis that there is limited structural diversity among environmentally relevant chemicals capable of modulating TR activity via the collaborative interagency Tox21 project. METHODS We screened the Tox21 chemical library (8,305 unique structures) in a quantitative high-throughput, cell-based reporter gene assay for TR agonist or antagonist activity. Active compounds were further characterized using additional orthogonal assays, including mammalian one-hybrid assays, coactivator recruitment assays, and a high-throughput, fluorescent imaging, nuclear receptor translocation assay. RESULTS Known agonist reference chemicals were readily identified in the TR transactivation assay, but only a single novel, direct agonist was found, the pharmaceutical betamipron. Indirect activation of TR through activation of its heterodimer partner, the retinoid-X-receptor (RXR), was also readily detected by confirmation in an RXR agonist assay. Identifying antagonists with high confidence was a challenge with the presence of significant confounding cytotoxicity and other, non-TR-specific mechanisms common to the transactivation assays. Only three pharmaceuticals-mefenamic acid, diclazuril, and risarestat-were confirmed as antagonists. DISCUSSION The results support limited structural diversity for direct ligand effects on TR and imply that other potential target sites in the thyroid hormone axis should be a greater priority for bioactivity screening for thyroid axis disruptors. https://doi.org/10.1289/EHP5314.
Collapse
Affiliation(s)
- Katie Paul-Friedman
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Matt Martin
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Kevin M Crofton
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Chia-Wen Hsu
- Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Washington, DC, USA
| | - Srilatha Sakamuru
- National Center for Advancing Translational Sciences, National Institutes of Health (NIH), Bethesda, Maryland, USA
| | - Jinghua Zhao
- National Center for Advancing Translational Sciences, National Institutes of Health (NIH), Bethesda, Maryland, USA
| | - Menghang Xia
- National Center for Advancing Translational Sciences, National Institutes of Health (NIH), Bethesda, Maryland, USA
| | - Ruili Huang
- National Center for Advancing Translational Sciences, National Institutes of Health (NIH), Bethesda, Maryland, USA
| | - Diana A Stavreva
- Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Vikas Soni
- Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Lyuba Varticovski
- Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Razi Raziuddin
- Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Gordon L Hager
- Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Keith A Houck
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| |
Collapse
|
35
|
Cooper DJ, Schürer S. Improving the Utility of the Tox21 Dataset by Deep Metadata Annotations and Constructing Reusable Benchmarked Chemical Reference Signatures. Molecules 2019; 24:E1604. [PMID: 31018579 DOI: 10.3390/molecules24081604] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 04/16/2019] [Accepted: 04/19/2019] [Indexed: 02/03/2023] Open
Abstract
The Toxicology in the 21st Century (Tox21) project seeks to develop and test methods for high-throughput examination of the effect certain chemical compounds have on biological systems. Although primary and toxicity assay data were readily available for multiple reporter gene modified cell lines, extensive annotation and curation was required to improve these datasets with respect to how FAIR (Findable, Accessible, Interoperable, and Reusable) they are. In this study, we fully annotated the Tox21 published data with relevant and accepted controlled vocabularies. After removing unreliable data points, we aggregated the results and created three sets of signatures reflecting activity in the reporter gene assays, cytotoxicity, and selective reporter gene activity, respectively. We benchmarked these signatures using the chemical structures of the tested compounds and obtained generally high receiver operating characteristic (ROC) scores, suggesting good quality and utility of these signatures and the underlying data. We analyzed the results to identify promiscuous individual compounds and chemotypes for the three signature categories and interpreted the results to illustrate the utility and re-usability of the datasets. With this study, we aimed to demonstrate the importance of data standards in reporting screening results and high-quality annotations to enable re-use and interpretation of these data. To improve the data with respect to all FAIR criteria, all assay annotations, cleaned and aggregate datasets, and signatures were made available as standardized dataset packages (Aggregated Tox21 bioactivity data, 2019).
Collapse
|
36
|
Klaren WD, Ring C, Harris MA, Thompson CM, Borghoff S, Sipes NS, Hsieh JH, Auerbach SS, Rager JE. Identifying Attributes That Influence In Vitro-to-In Vivo Concordance by Comparing In Vitro Tox21 Bioactivity Versus In Vivo DrugMatrix Transcriptomic Responses Across 130 Chemicals. Toxicol Sci 2019; 167:157-171. [PMID: 30202884 PMCID: PMC6317427 DOI: 10.1093/toxsci/kfy220] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Recent efforts aimed at integrating in vitro high-throughput screening (HTS) data into chemical toxicity assessments are necessitating increased understanding of concordance between chemical-induced responses observed in vitro versus in vivo. This investigation set out to (1) measure concordance between in vitro HTS data and transcriptomic responses observed in vivo, focusing on the liver, and (2) identify attributes that can influence concordance. Signal response profiles from 130 substances were compared between in vitro data produced through Tox21 and liver transcriptomic data through DrugMatrix, collected from rats exposed to a chemical for ≤5 days. A global in vitro-to-in vivo comparative analysis based on pathway-level responses resulted in an overall average percent agreement of 79%, ranging on a per-chemical basis between 41% and 100%. Whereas concordance amongst inactive chemicals was high (89%), concordance amongst chemicals showing in vitro activity was only 13%, suggesting that follow-up in vivo and/or orthogonal in vitro assays would improve interpretations of in vitro activity. Attributes identified to influence concordance included experimental design attributes (eg, cell type), target pathways, and physicochemical properties (eg, logP). The attribute that most consistently increased concordance was dose applicability, evaluated by filtering for experimental doses administered to rats that were within 10-fold of those related to likely bioactivity, derived using Tox21 data and high-throughput toxicokinetic modeling. Together, findings suggest that in vitro screening approaches to predict in vivo toxicity are viable particularly when certain attributes are considered, including whether activity versus inactivity is observed, experimental design, chemical properties, and dose applicability.
Collapse
Affiliation(s)
- William D Klaren
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas 77840
| | | | | | | | | | - Nisha S Sipes
- National Toxicology Program, National Institutes of Health, Research Triangle Park, North Carolina 27709and
| | - Jui-Hua Hsieh
- Kelly Government Solutions, Durham, North Carolina 27709
| | - Scott S Auerbach
- National Toxicology Program, National Institutes of Health, Research Triangle Park, North Carolina 27709and
| | | |
Collapse
|
37
|
Wikoff DS, Rager JE, Chappell GA, Fitch S, Haws L, Borghoff SJ. A Framework for Systematic Evaluation and Quantitative Integration of Mechanistic Data in Assessments of Potential Human Carcinogens. Toxicol Sci 2018; 167:322-335. [DOI: 10.1093/toxsci/kfy279] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
|
38
|
Borghoff SJ, Fitch S, Rager JE, Huggett D. A hypothesis-driven weight-of-evidence analysis to evaluate potential endocrine activity of perfluorohexanoic acid. Regul Toxicol Pharmacol 2018; 99:168-181. [PMID: 30240830 DOI: 10.1016/j.yrtph.2018.09.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 08/31/2018] [Accepted: 09/01/2018] [Indexed: 12/11/2022]
Abstract
Perfluorohexanoic acid (PFHxA) is a potential impurity and environmental degradation product of C6-based fluorotelomer products. Considering the potential endocrine activity of perfluoroalkyl acids, a hypothesis-driven weight-of-evidence (WoE) analysis was conducted to evaluate the potential endocrine disruptor activity of PFHxA, as defined by World Health Organization (WHO), across estrogen (E), androgen (A), thyroid (T), and steroidogenesis (S) pathways. A comprehensive literature search identified primary and secondary studies across species for review. The ToxCast/Tox21 database provided in vitro data. Studies identified were reviewed for reliability, and relevance, with endocrine endpoints ranked, and lines of evidence evaluated across pathways. Overall, PFHxA showed no endocrine effects in Japanese medaka, juvenile rainbow trout, chickens or reproductive parameters in northern bobwhite with no significant activity in rodent repeated-dose toxicity, lifetime cancer, or reproductive and developmental studies. In vitro, there was weak or negative activity for T transport protein or activation of E, A or T receptors. PFHxA was also negative in vitro and in vivo for disrupting steroidogenesis. Based on this WoE endocrine analysis, PFHxA exposure did not cause adverse effects associated with alterations in endocrine activity in these models, as such would not be characterized as an endocrine disruptor according to the WHO definition.
Collapse
Affiliation(s)
| | - S Fitch
- ToxStrategies, Katy, TX, USA
| | | | | |
Collapse
|
39
|
Sobus JR, Wambaugh JF, Isaacs KK, Williams AJ, McEachran AD, Richard AM, Grulke CM, Ulrich EM, Rager JE, Strynar MJ, Newton SR. Integrating tools for non-targeted analysis research and chemical safety evaluations at the US EPA. J Expo Sci Environ Epidemiol 2018; 28:411-426. [PMID: 29288256 PMCID: PMC6661898 DOI: 10.1038/s41370-017-0012-y] [Citation(s) in RCA: 130] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2017] [Revised: 08/04/2017] [Accepted: 08/25/2017] [Indexed: 05/18/2023]
Abstract
Tens-of-thousands of chemicals are registered in the U.S. for use in countless processes and products. Recent evidence suggests that many of these chemicals are measureable in environmental and/or biological systems, indicating the potential for widespread exposures. Traditional public health research tools, including in vivo studies and targeted analytical chemistry methods, have been unable to meet the needs of screening programs designed to evaluate chemical safety. As such, new tools have been developed to enable rapid assessment of potentially harmful chemical exposures and their attendant biological responses. One group of tools, known as "non-targeted analysis" (NTA) methods, allows the rapid characterization of thousands of never-before-studied compounds in a wide variety of environmental, residential, and biological media. This article discusses current applications of NTA methods, challenges to their effective use in chemical screening studies, and ways in which shared resources (e.g., chemical standards, databases, model predictions, and media measurements) can advance their use in risk-based chemical prioritization. A brief review is provided of resources and projects within EPA's Office of Research and Development (ORD) that provide benefit to, and receive benefits from, NTA research endeavors. A summary of EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) is also given, which makes direct use of ORD resources to benefit the global NTA research community. Finally, a research framework is described that shows how NTA methods will bridge chemical prioritization efforts within ORD. This framework exists as a guide for institutions seeking to understand the complexity of chemical exposures, and the impact of these exposures on living systems.
Collapse
Affiliation(s)
- Jon R Sobus
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA.
| | - John F Wambaugh
- U.S. Environmental Protection Agency, Office of Research and Development, National Center for Computational Toxicology, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA
| | - Kristin K Isaacs
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA
| | - Antony J Williams
- U.S. Environmental Protection Agency, Office of Research and Development, National Center for Computational Toxicology, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA
| | - Andrew D McEachran
- Oak Ridge Institute for Science and Education (ORISE) Participant, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA
| | - Ann M Richard
- U.S. Environmental Protection Agency, Office of Research and Development, National Center for Computational Toxicology, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA
| | - Christopher M Grulke
- U.S. Environmental Protection Agency, Office of Research and Development, National Center for Computational Toxicology, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA
| | - Elin M Ulrich
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA
| | - Julia E Rager
- Oak Ridge Institute for Science and Education (ORISE) Participant, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA
- ToxStrategies, Inc., 9390 Research Blvd., Suite 100, Austin, TX, 78759, USA
| | - Mark J Strynar
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA
| | - Seth R Newton
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 T.W. Alexander Drive, Research Triangle Park, NC, 27709, USA
| |
Collapse
|
40
|
Suh M, Proctor D, Chappell G, Rager J, Thompson C, Borghoff S, Finch L, Ellis-Hutchings R, Wiench K. A review of the genotoxic, mutagenic, and carcinogenic potentials of several lower acrylates. Toxicology 2018; 402-403:50-67. [PMID: 29689363 DOI: 10.1016/j.tox.2018.04.006] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 03/28/2018] [Accepted: 04/19/2018] [Indexed: 01/29/2023]
Abstract
Lower alkyl acrylate monomers include methyl-, ethyl-, n-butyl-, and 2-ethylhexyl acrylate. These acrylates are used in the manufacture of acrylic polymers and copolymers for plastics, food packaging, adhesives, and cosmetic formulations. Although there is limited potential for human environmental exposure, occupational exposure can occur via inhalation and dermal contact. Recently, new genotoxicity data have been generated, along with in silico and in vitro read-cross analyses, for these acrylates. The availability of high-throughput screening (HTS) data through the ToxCast™/Tox21 databases allows for consideration of computational toxicology and organization of these data according to the ten key characteristics of carcinogens. Therefore, we conducted a comprehensive review to evaluate the mechanistic, toxicokinetic, animal, and human data, including HTS data, for characterizing the potential carcinogenicity, mutagenicity, and genotoxicity of these acrylates. Toxicokinetic data demonstrate that these acrylates are metabolized rapidly by carboxylesterase hydrolysis and conjugation with glutathione. HTS data demonstrated an overall lack of bioactivity in cancer-related pathways. Overall, the genotoxicity and mutagenicity data support a cytotoxic, non-genotoxic mechanism for these acrylates. Cancer bioassay studies conducted by the oral, dermal, and inhalation routes in animal models with these acrylates did not show any increase in tumor incidence, with two exceptions. At high doses, and secondary to chronic site-of-contact irritation and corrosion, rodent forestomach tumors were induced by oral gavage dosing with ethyl acrylate, and skin tumors were observed following chronic dermal dosing with 2-ethylhexyl acrylate in C3H/HeJ inbred mice (a strain with deficiencies in wound healing), but not in the outbred NMRI strain. For both dermal and forestomach cancers, tumorigenesis is secondary to high doses and long-term tissue damage, shown to be reversible. With evidence that these chemicals are not genotoxic, and that they cause forestomach and dermal tumors through chronic irritation and regenerative proliferation mechanisms, these acrylates are unlikely to pose a human cancer hazard.
Collapse
Affiliation(s)
- Mina Suh
- ToxStrategies, Inc., Mission Viejo, CA 92692, United States
| | | | | | - Julia Rager
- ToxStrategies, Inc., Austin, TX 78759, United States
| | | | | | | | | | | |
Collapse
|
41
|
Abstract
Recent studies have demonstrated that a number of environmental contaminants can act as metabolic disruptors and modulate metabolic function both in vitro and in vivo. 3T3-L1 mouse preadipocytes are commonly utilized to assess perturbations to adipogenesis, providing insight into environmental contaminants that may impact in vivo metabolic health. This study sought to assess whether various alkylphenol ethoxylates and alcohol ethoxylates (APEOs and AEOs, respectively), ubiquitous contaminants used in common household products, could disrupt metabolic health. 3T3-L1 cells were exposed to increasing concentrations of individual ethoxylated surfactants and base hydrophobes, and assessed for triglyceride accumulation (relative to a rosiglitazone-induced maximum response) and preadipocyte proliferation (relative to a differentiated vehicle control). We report herein that nonionic APEOs and AEOs promoted triglyceride accumulation and/or preadipocyte proliferation in 3T3-L1 cells at concentrations from 0.1 to 10 μM. Activity appeared to be an effect of the polyethoxylate chain length, as the alkylphenol/alcohol hydrophobes exhibited minimal or no adipogenic activity. In addition, nonylphenol ethoxylates (NPEO) of various ethoxylate chain lengths exhibited biphasic adipogenic activity, with increasing triglyceride accumulation and preadipocyte proliferation from NPEO (0, average ethoxylate number) through NPEO (4), and then decreasing activities from NPEO (4) through NPEO (20). Our results suggest potential metabolic impacts of these compounds at environmentally relevant concentrations, demonstrating a need to further assess molecular mechanisms and better characterize environmental concentrations of the specific AEOs and APEOs that are inducing the greatest degree of adipogenic activity herein.
Collapse
Affiliation(s)
| | - Erin M Kollitz
- Nicholas School of the Environment, Duke University, Durham, North Carolina 27708
| | - Patrick Lee Ferguson
- Nicholas School of the Environment, Duke University, Durham, North Carolina 27708
| | - Heather M Stapleton
- Nicholas School of the Environment, Duke University, Durham, North Carolina 27708
| |
Collapse
|
42
|
Truong L, Ouedraogo G, Pham L, Clouzeau J, Loisel-Joubert S, Blanchet D, Noçairi H, Setzer W, Judson R, Grulke C, Mansouri K, Martin M. Predicting in vivo effect levels for repeat-dose systemic toxicity using chemical, biological, kinetic and study covariates. Arch Toxicol 2018; 92:587-600. [PMID: 29075892 PMCID: PMC5818596 DOI: 10.1007/s00204-017-2067-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 09/18/2017] [Indexed: 11/29/2022]
Abstract
In an effort to address a major challenge in chemical safety assessment, alternative approaches for characterizing systemic effect levels, a predictive model was developed. Systemic effect levels were curated from ToxRefDB, HESS-DB and COSMOS-DB from numerous study types totaling 4379 in vivo studies for 1247 chemicals. Observed systemic effects in mammalian models are a complex function of chemical dynamics, kinetics, and inter- and intra-individual variability. To address this complex problem, systemic effect levels were modeled at the study-level by leveraging study covariates (e.g., study type, strain, administration route) in addition to multiple descriptor sets, including chemical (ToxPrint, PaDEL, and Physchem), biological (ToxCast), and kinetic descriptors. Using random forest modeling with cross-validation and external validation procedures, study-level covariates alone accounted for approximately 15% of the variance reducing the root mean squared error (RMSE) from 0.96 log10 to 0.85 log10 mg/kg/day, providing a baseline performance metric (lower expectation of model performance). A consensus model developed using a combination of study-level covariates, chemical, biological, and kinetic descriptors explained a total of 43% of the variance with an RMSE of 0.69 log10 mg/kg/day. A benchmark model (upper expectation of model performance) was also developed with an RMSE of 0.5 log10 mg/kg/day by incorporating study-level covariates and the mean effect level per chemical. To achieve a representative chemical-level prediction, the minimum study-level predicted and observed effect level per chemical were compared reducing the RMSE from 1.0 to 0.73 log10 mg/kg/day, equivalent to 87% of predictions falling within an order-of-magnitude of the observed value. Although biological descriptors did not improve model performance, the final model was enriched for biological descriptors that indicated xenobiotic metabolism gene expression, oxidative stress, and cytotoxicity, demonstrating the importance of accounting for kinetics and non-specific bioactivity in predicting systemic effect levels. Herein, we generated an externally predictive model of systemic effect levels for use as a safety assessment tool and have generated forward predictions for over 30,000 chemicals.
Collapse
Affiliation(s)
- Lisa Truong
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
- Currently at Oregon State University, Corvallis, USA
| | - Gladys Ouedraogo
- L'Oréal Safety Research Department, 1 Avenue E. Schueller, 93600, Aulnay-Sous-Bois, France
| | - LyLy Pham
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Jacques Clouzeau
- L'Oréal Safety Research Department, 1 Avenue E. Schueller, 93600, Aulnay-Sous-Bois, France
| | - Sophie Loisel-Joubert
- L'Oréal Safety Research Department, 1 Avenue E. Schueller, 93600, Aulnay-Sous-Bois, France
| | - Delphine Blanchet
- L'Oréal Safety Research Department, 1 Avenue E. Schueller, 93600, Aulnay-Sous-Bois, France
| | - Hicham Noçairi
- L'Oréal Safety Research Department, 1 Avenue E. Schueller, 93600, Aulnay-Sous-Bois, France
| | - Woodrow Setzer
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Richard Judson
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Chris Grulke
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Kamel Mansouri
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
- Currently at Scitovation LLC, Research Triangle Park, NC, USA
| | - Matthew Martin
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711, USA.
- Currently at Pfizer, Inc, Drug Safety Research and Development, 445 Eastern Point Road, MS 8274-1224, Groton, CT, 06340, USA.
| |
Collapse
|
43
|
Shin DY, Jeong MH, Bang IJ, Kim HR, Chung KH. MicroRNA regulatory networks reflective of polyhexamethylene guanidine phosphate-induced fibrosis in A549 human alveolar adenocarcinoma cells. Toxicol Lett 2018; 287:49-58. [PMID: 29337256 DOI: 10.1016/j.toxlet.2018.01.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 12/26/2017] [Accepted: 01/11/2018] [Indexed: 12/28/2022]
Abstract
Polyhexamethylene guanidine phosphate (PHMG-phosphate), an active component of humidifier disinfectant, is suspected to be a major cause of pulmonary fibrosis. Fibrosis, induced by recurrent epithelial damage, is significantly affected by epigenetic regulation, including microRNAs (miRNAs). The aim of this study was to investigate the fibrogenic mechanisms of PHMG-phosphate through the profiling of miRNAs and their target genes. A549 cells were treated with 0.75 μg/mL PHMG-phosphate for 24 and 48 h and miRNA microarray expression analysis was conducted. The putative mRNA targets of the miRNAs were identified and subjected to Gene Ontology analysis. After exposure to PHMG-phosphate for 24 and 48 h, 46 and 33 miRNAs, respectively, showed a significant change in expression over 1.5-fold compared with the control. The integrated analysis of miRNA and mRNA microarray results revealed the putative targets that were prominently enriched were associated with the epithelial-mesenchymal transition (EMT), cell cycle changes, and apoptosis. The dose-dependent induction of EMT by PHMG-phosphate exposure was confirmed by western blot. We identified 13 putative EMT-related targets that may play a role in PHMG-phosphate-induced fibrosis according to the Comparative Toxicogenomic Database. Our findings contribute to the comprehension of the fibrogenic mechanism of PHMG-phosphate and will aid further study on PHMG-phosphate-induced toxicity.
Collapse
Affiliation(s)
- Da Young Shin
- School of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Mi Ho Jeong
- School of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - In Jae Bang
- School of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Ha Ryong Kim
- College of Pharmacy, Catholic University of Daegu, Gyeongsan, Gyeongsangbuk-do, 38430, Republic of Korea.
| | - Kyu Hyuck Chung
- School of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea.
| |
Collapse
|
44
|
Strickland JD, Martin MT, Richard AM, Houck KA, Shafer TJ. Screening the ToxCast phase II libraries for alterations in network function using cortical neurons grown on multi-well microelectrode array (mwMEA) plates. Arch Toxicol 2018; 92:487-500. [PMID: 28766123 PMCID: PMC6438628 DOI: 10.1007/s00204-017-2035-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 07/12/2017] [Indexed: 12/12/2022]
Abstract
Methods are needed for rapid screening of environmental compounds for neurotoxicity, particularly ones that assess function. To demonstrate the utility of microelectrode array (MEA)-based approaches as a rapid neurotoxicity screening tool, 1055 chemicals from EPA's phase II ToxCast library were evaluated for effects on neural function and cell health. Primary cortical networks were grown on multi-well microelectrode array (mwMEA) plates. On day in vitro 13, baseline activity (40 min) was recorded prior to exposure to each compound (40 µM). Changes in spontaneous network activity [mean firing rate (MFR)] and cell viability (lactate dehydrogenase and CellTiter Blue) were assessed within the same well following compound exposure. Following exposure, 326 compounds altered (increased or decreased) normalized MFR beyond hit thresholds based on 2× the median absolute deviation of DMSO-treated wells. Pharmaceuticals, pesticides, fungicides, chemical intermediates, and herbicides accounted for 86% of the hits. Further, changes in MFR occurred in the absence of cytotoxicity, as only eight compounds decreased cell viability. ToxPrint chemotype analysis identified several structural domains (e.g., biphenyls and alkyl phenols) significantly enriched with MEA actives relative to the total test set. The top 5 enriched ToxPrint chemotypes were represented in 26% of the MEA hits, whereas the top 11 ToxPrints were represented in 34% of MEA hits. These results demonstrate that large-scale functional screening using neural networks on MEAs can fill a critical gap in assessment of neurotoxicity potential in ToxCast assay results. Further, a data-mining approach identified ToxPrint chemotypes enriched in the MEA-hit subset, which define initial structure-activity relationship inferences, establish potential mechanistic associations to other ToxCast assay endpoints, and provide working hypotheses for future studies.
Collapse
Affiliation(s)
- Jenna D Strickland
- Axion Biosystems, Atlanta, GA, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI, USA
| | - Matthew T Martin
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, MD D143-02, Research Triangle Park, NC, 27711, USA
- Pfizer Inc, Groton, CT, USA
| | - Ann M Richard
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, MD D143-02, Research Triangle Park, NC, 27711, USA
| | - Keith A Houck
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, MD D143-02, Research Triangle Park, NC, 27711, USA
| | - Timothy J Shafer
- Integrated Systems Toxicology Division, U.S. Environmental Protection Agency, MD105-05, Research Triangle Park, NC, 27711, USA.
| |
Collapse
|
45
|
Berggren E, White A, Ouedraogo G, Paini A, Richarz AN, Bois FY, Exner T, Leite S, Grunsven LAV, Worth A, Mahony C. Ab initio chemical safety assessment: A workflow based on exposure considerations and non-animal methods. Comput Toxicol 2017; 4:31-44. [PMID: 29214231 PMCID: PMC5695905 DOI: 10.1016/j.comtox.2017.10.001] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 10/09/2017] [Accepted: 10/10/2017] [Indexed: 12/12/2022]
Abstract
We describe and illustrate a workflow for chemical safety assessment that completely avoids animal testing. The workflow, which was developed within the SEURAT-1 initiative, is designed to be applicable to cosmetic ingredients as well as to other types of chemicals, e.g. active ingredients in plant protection products, biocides or pharmaceuticals. The aim of this work was to develop a workflow to assess chemical safety without relying on any animal testing, but instead constructing a hypothesis based on existing data, in silico modelling, biokinetic considerations and then by targeted non-animal testing. For illustrative purposes, we consider a hypothetical new ingredient x as a new component in a body lotion formulation. The workflow is divided into tiers in which points of departure are established through in vitro testing and in silico prediction, as the basis for estimating a safe external dose in a repeated use scenario. The workflow includes a series of possible exit (decision) points, with increasing levels of confidence, based on the sequential application of the Threshold of Toxicological (TTC) approach, read-across, followed by an "ab initio" assessment, in which chemical safety is determined entirely by new in vitro testing and in vitro to in vivo extrapolation by means of mathematical modelling. We believe that this workflow could be applied as a tool to inform targeted and toxicologically relevant in vitro testing, where necessary, and to gain confidence in safety decision making without the need for animal testing.
Collapse
Affiliation(s)
- Elisabet Berggren
- Chemical Safety and Alternative Methods Unit, & EURL ECVAM, Directorate F – Health, Consumers and Reference Materials, Joint Research Centre, European Commission, Ispra, Italy
| | | | | | - Alicia Paini
- Chemical Safety and Alternative Methods Unit, & EURL ECVAM, Directorate F – Health, Consumers and Reference Materials, Joint Research Centre, European Commission, Ispra, Italy
| | - Andrea-Nicole Richarz
- Chemical Safety and Alternative Methods Unit, & EURL ECVAM, Directorate F – Health, Consumers and Reference Materials, Joint Research Centre, European Commission, Ispra, Italy
| | | | | | - Sofia Leite
- Liver Cell Biology Laboratory, Vrije Universiteit Brussel, Brussels, Belgium
| | - Leo A. van Grunsven
- Liver Cell Biology Laboratory, Vrije Universiteit Brussel, Brussels, Belgium
| | - Andrew Worth
- Chemical Safety and Alternative Methods Unit, & EURL ECVAM, Directorate F – Health, Consumers and Reference Materials, Joint Research Centre, European Commission, Ispra, Italy
| | | |
Collapse
|
46
|
Embryonic vascular disruption adverse outcomes: Linking high throughput signaling signatures with functional consequences. Reprod Toxicol 2017; 71:16-31. [DOI: 10.1016/j.reprotox.2017.04.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Revised: 04/03/2017] [Accepted: 04/07/2017] [Indexed: 11/23/2022]
|
47
|
Rager JE, Ring CL, Fry RC, Suh M, Proctor DM, Haws LC, Harris MA, Thompson CM. High-Throughput Screening Data Interpretation in the Context of In Vivo Transcriptomic Responses to Oral Cr(VI) Exposure. Toxicol Sci 2017; 158:199-212. [PMID: 28472532 PMCID: PMC5837509 DOI: 10.1093/toxsci/kfx085] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
The toxicity of hexavalent chromium [Cr(VI)] in drinking water has been studied extensively, and available in vivo and in vitro studies provide a robust dataset for application of advanced toxicological tools to inform the mode of action (MOA). This study aimed to contribute to the understanding of Cr(VI) MOA by evaluating high-throughput screening (HTS) data and other in vitro data relevant to Cr(VI), and comparing these findings to robust in vivo data, including transcriptomic profiles in target tissues. Evaluation of Tox21 HTS data for Cr(VI) identified 11 active assay endpoints relevant to the Ten Key Characteristics of Carcinogens (TKCCs) that have been proposed by other investigators. Four of these endpoints were related to TP53 (tumor protein 53) activation mapping to genotoxicity (KCC#2), and four were related to cell death/proliferation (KCC#10). HTS results were consistent with other in vitro data from the Comparative Toxicogenomics Database. In vitro responses were compared to in vivo transcriptomic responses in the most sensitive target tissue, the duodenum, of mice exposed to ≤ 180 ppm Cr(VI) for 7 and 90 days. Pathways that were altered both in vitro and in vivo included those relevant to cell death/proliferation. In contrast, pathways relevant to p53/DNA damage were identified in vitro but not in vivo. Benchmark dose modeling and phenotypic anchoring of in vivo transcriptomic responses strengthened the finding that Cr(VI) causes cell stress/injury followed by proliferation in the mouse duodenum at high doses. These findings contribute to the body of evidence supporting a non-mutagenic MOA for Cr(VI)-induced intestinal cancer.
Collapse
Affiliation(s)
| | | | - Rebecca C. Fry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health
- Curriculum in Toxicology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27516
| | - Mina Suh
- ToxStrategies Inc, Mission Viejo, California 92692
| | | | | | | | | |
Collapse
|
48
|
Gwinn MR, Axelrad DA, Bahadori T, Bussard D, Cascio WE, Deener K, Dix D, Thomas RS, Kavlock RJ, Burke TA. Chemical Risk Assessment: Traditional vs Public Health Perspectives. Am J Public Health 2017; 107:1032-1039. [PMID: 28520487 DOI: 10.2105/ajph.2017.303771] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Preventing adverse health effects of environmental chemical exposure is fundamental to protecting individual and public health. When done efficiently and properly, chemical risk assessment enables risk management actions that minimize the incidence and effects of environmentally induced diseases related to chemical exposure. However, traditional chemical risk assessment is faced with multiple challenges with respect to predicting and preventing disease in human populations, and epidemiological studies increasingly report observations of adverse health effects at exposure levels predicted from animal studies to be safe for humans. This discordance reinforces concerns about the adequacy of contemporary risk assessment practices for protecting public health. It is becoming clear that to protect public health more effectively, future risk assessments will need to use the full range of available data, draw on innovative methods to integrate diverse data streams, and consider health endpoints that also reflect the range of subtle effects and morbidities observed in human populations. Considering these factors, there is a need to reframe chemical risk assessment to be more clearly aligned with the public health goal of minimizing environmental exposures associated with disease.
Collapse
Affiliation(s)
- Maureen R Gwinn
- At the time of the writing of this article, all of the authors were with the US Environmental Protection Agency, Washington, DC
| | - Daniel A Axelrad
- At the time of the writing of this article, all of the authors were with the US Environmental Protection Agency, Washington, DC
| | - Tina Bahadori
- At the time of the writing of this article, all of the authors were with the US Environmental Protection Agency, Washington, DC
| | - David Bussard
- At the time of the writing of this article, all of the authors were with the US Environmental Protection Agency, Washington, DC
| | - Wayne E Cascio
- At the time of the writing of this article, all of the authors were with the US Environmental Protection Agency, Washington, DC
| | - Kacee Deener
- At the time of the writing of this article, all of the authors were with the US Environmental Protection Agency, Washington, DC
| | - David Dix
- At the time of the writing of this article, all of the authors were with the US Environmental Protection Agency, Washington, DC
| | - Russell S Thomas
- At the time of the writing of this article, all of the authors were with the US Environmental Protection Agency, Washington, DC
| | - Robert J Kavlock
- At the time of the writing of this article, all of the authors were with the US Environmental Protection Agency, Washington, DC
| | - Thomas A Burke
- At the time of the writing of this article, all of the authors were with the US Environmental Protection Agency, Washington, DC
| |
Collapse
|
49
|
Ellis-Hutchings RG, Settivari RS, McCoy AT, Kleinstreuer N, Franzosa J, Knudsen TB, Carney EW. Embryonic vascular disruption adverse outcomes: Linking high throughput signaling signatures with functional consequences. Reprod Toxicol 2017; 70:82-96. [PMID: 28527947 DOI: 10.1016/j.reprotox.2017.05.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Embryonic vascular disruption is an important adverse outcome pathway (AOP) as chemical disruption of cardiovascular development induces broad prenatal defects. High throughput screening (HTS) assays aid AOP development although linking in vitro data to in vivo apical endpoints remains challenging. This study evaluated two anti-angiogenic agents, 5HPP-33 and TNP-470, across the ToxCastDB HTS assay platform and anchored the results to complex in vitro functional assays: the rat aortic explant assay (AEA), rat whole embryo culture (WEC), and the zebrafish embryotoxicity (ZET) assay. Both were identified as putative vascular disruptive compounds (pVDCs) in ToxCastDB and disrupted angiogenesis and embryogenesis in the functional assays. Differences were observed in potency and adverse effects: 5HPP-33 was embryolethal (WEC and ZET); TNP-470 produced caudal defects at lower concentrations. This study demonstrates how a tiered approach using HTS signatures and complex functional in vitro assays might be used to prioritize further in vivo developmental toxicity testing.
Collapse
Affiliation(s)
- Robert G Ellis-Hutchings
- Toxicology and Environmental Research and Consulting, The Dow Chemical Company, 1803 Building, Midland, MI 48674, United States.
| | - Raja S Settivari
- Toxicology and Environmental Research and Consulting, The Dow Chemical Company, 1803 Building, Midland, MI 48674, United States
| | - Alene T McCoy
- Toxicology and Environmental Research and Consulting, The Dow Chemical Company, 1803 Building, Midland, MI 48674, United States
| | - Nicole Kleinstreuer
- National Toxicology Program Interagency Center for Evaluation of Alternative Toxicological Methods, Research Triangle Park, NC, 27711, United States
| | - Jill Franzosa
- National Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC, 27711, United States
| | - Thomas B Knudsen
- National Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC, 27711, United States
| | - Edward W Carney
- Toxicology and Environmental Research and Consulting, The Dow Chemical Company, 1803 Building, Midland, MI 48674, United States
| |
Collapse
|
50
|
Nyffeler J, Dolde X, Krebs A, Pinto-Gil K, Pastor M, Behl M, Waldmann T, Leist M. Combination of multiple neural crest migration assays to identify environmental toxicants from a proof-of-concept chemical library. Arch Toxicol 2017; 91:3613-32. [PMID: 28477266 DOI: 10.1007/s00204-017-1977-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2016] [Accepted: 04/26/2017] [Indexed: 12/18/2022]
Abstract
Many in vitro tests have been developed to screen for potential neurotoxicity. However, only few cell function-based tests have been used for comparative screening, and thus experience is scarce on how to confirm and evaluate screening hits. We addressed these questions for the neural crest cell migration test (cMINC). After an initial screen, a hit follow-up strategy was devised. A library of 75 compounds plus internal controls (NTP80-list), assembled by the National Toxicology Program of the USA (NTP) was used. It contained some known classes of (developmental) neurotoxic compounds. The primary screen yielded 23 confirmed hits, which comprised ten flame retardants, seven pesticides and six drug-like compounds. Comparison of concentration-response curves for migration and viability showed that all hits were specific. The extent to which migration was inhibited was 25-90%, and two organochlorine pesticides (DDT, heptachlor) were most efficient. In the second part of this study, (1) the cMINC assay was repeated under conditions that prevent proliferation; (2) a transwell migration assay was used as a different type of migration assay; (3) cells were traced to assess cell speed. Some toxicants had largely varying effects between assays, but each hit was confirmed in at least one additional test. This comparative study allows an estimate on how confidently the primary hits from a cell function-based screen can be considered as toxicants disturbing a key neurodevelopmental process. Testing of the NTP80-list in more assays will be highly interesting to assemble a test battery and to build prediction models for developmental toxicity.
Collapse
|