1
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Huang H, Lv Y, Chen Q, Huang X, Qin J, Liu Y, Liao Q, Xing X, Chen L, Liu Q, Li S, Long Z, Wang Q, Chen W, Wei Q, Hou M, Hu Q, Xiao Y. Empirical analysis of lead neurotoxicity mode of action and its application in health risk assessment. ENVIRONMENTAL RESEARCH 2024; 251:118708. [PMID: 38493858 DOI: 10.1016/j.envres.2024.118708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 02/28/2024] [Accepted: 03/11/2024] [Indexed: 03/19/2024]
Abstract
The mode of action (MOA) framework is proposed to inform a biological link between chemical exposures and adverse health effects. Despite a significant increase in knowledge and awareness, the application of MOA in human health risk assessment (RA) remains limited. This study aims to discuss the adoption of MOA for health RA within a regulatory context, taking our previously proposed but not yet validated MOA for lead neurotoxicity as an example. We first conducted a quantitative weight of evidence (qWOE) assessment, which revealed that the MOA has a moderate confidence. Then, targeted bioassays were performed within an in vitro blood-brain barrier (BBB) model to quantitatively validate the scientific validity of key events (KEs) in terms of essentiality and concordance of empirical support (dose/temporal concordance), which increases confidence in utilizing the MOA for RA. Building upon the quantitative validation data, we further conducted benchmark dose (BMD) analysis to map dose-response relationships for the critical toxicity pathways, and the lower limit of BMD at a 5% response (BMDL5) was identified as the point of departure (POD) value for adverse health effects. Notably, perturbation of the Aryl Hydrocarbon Receptor (AHR) signaling pathway exhibited the lowest POD value, measured at 0.0062 μM. Considering bioavailability, we further calculated a provisional health-based guidance value (HBGV) for children's lead intake, determining it to be 2.56 μg/day. Finally, the health risk associated with the HBGV was assessed using the hazard quotient (HQ) approach, which indicated that the HBGV established in this study is a relative safe reference value for lead intake. In summary, our study described the procedure for utilizing MOA in health RA and set an example for MOA-based human health risk regulation.
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Affiliation(s)
- Hehai Huang
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China; Department of Occupational Health, Public Health Service Center, Bao'an District, Shenzhen, 518126, China
| | - Yanrong Lv
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Qingfei Chen
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiaowei Huang
- Department of Toxicology, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Jingyao Qin
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yan Liu
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Qilong Liao
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiumei Xing
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Liping Chen
- Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Qing Liu
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Shuangqi Li
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Zihao Long
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Qing Wang
- Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Wen Chen
- Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Qing Wei
- Guangdong Provincial Key Laboratory of Food, Nutrition, and Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Mengjun Hou
- Guangdong Provincial Key Laboratory of Food, Nutrition, and Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Qiansheng Hu
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yongmei Xiao
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Food, Nutrition, and Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
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2
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Costa E, Johnson KJ, Walker CA, O’Brien JM. Transcriptomic point of departure determination: a comparison of distribution-based and gene set-based approaches. Front Genet 2024; 15:1374791. [PMID: 38784034 PMCID: PMC11112360 DOI: 10.3389/fgene.2024.1374791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/02/2024] [Indexed: 05/25/2024] Open
Abstract
A key step in assessing the potential human and environmental health risks of industrial and agricultural chemicals is to determine the toxicity point of departure (POD), which is the highest dose level that causes no adverse effect. Transcriptomic POD (tPOD) values have been suggested to accurately estimate toxicity POD values. One step in the most common approach for tPOD determination involves mapping genes to annotated gene sets, a process that might lead to substantial information loss particularly in species with poor gene annotation. Alternatively, methods that calculate tPOD values directly from the distribution of individual gene POD values omit this mapping step. Using rat transcriptome data for 79 molecules obtained from Open TG-GATEs (Toxicogenomics Project Genomics Assisted Toxicity Evaluation System), the hypothesis was tested that methods based on the distribution of all individual gene POD values will give a similar tPOD value to that obtained via the gene set-based method. Gene set-based tPOD values using four different gene set structures were compared to tPOD values from five different individual gene distribution methods. Results revealed a high tPOD concordance for all methods tested, especially for molecules with at least 300 dose-responsive probesets: for 90% of those molecules, the tPOD values from all methods were within 4-fold of each other. In addition, random gene sets based upon the structure of biological knowledge-derived gene sets produced tPOD values with a median absolute fold change of 1.3-1.4 when compared to the original biological knowledge-derived gene set counterparts, suggesting that little biological information is used in the gene set-based tPOD generation approach. These findings indicate using individual gene distributions to calculate a tPOD is a viable and parsimonious alternative to using gene sets. Importantly, individual gene distribution-based tPOD methods do not require knowledge of biological organization and can be applied to any species including those with poorly annotated gene sets.
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Affiliation(s)
| | | | | | - Jason M. O’Brien
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, Ottawa, ON, Canada
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3
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Guan M, Wang X, Xu X, Ling T, Wu J, Qian J, Ma F, Zhang X. Bioactivity assessment of organophosphate flame retardants via a dose-dependent yeast functional genomics approach. ENVIRONMENT INTERNATIONAL 2024; 186:108596. [PMID: 38522228 DOI: 10.1016/j.envint.2024.108596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 03/14/2024] [Accepted: 03/21/2024] [Indexed: 03/26/2024]
Abstract
Organophosphate flame retardants (OPFRs) have been widely detected in multiple environment media and have many adverse effects with complex toxicity mechanisms. However, the early molecular responses to OPFRs have not been fully elucidated, thereby making it difficult to assess their risks accurately. In this work, we systematically explored the point of departure (POD) of biological pathways at genome-wide level perturbed by 14 OPFRs with three substituents (alkyl, halogen, and aryl) using a dose-dependent functional genomics approach in Saccharomyces cerevisiae at 24 h exposure. Firstly, our results demonstrated that the overall biological potency at gene level (PODDRG20) ranged from 0.013 to 35.079 μM for 14 OPFRs, especially the tributyl phosphate (TnBP) exhibited the strongest biological potency with the least PODDRG20. Secondly, we found that structural characteristics of carbon number and logKow were significantly negatively correlated with POD, and carbon number and logKow also significantly affected lipid metabolism associated processes. Thirdly, these early biological pathways of OPFRs toxification were found to be involved in lipid metabolism, oxidative stress, DNA damage, MAPK signaling pathway, and amino acid and carbohydrate metabolism, among which the lipid metabolism was the most sensitive molecular response perturbed by most OPFRs. More importantly, we identified one resistant mutant strain with knockout of ERG2 (YMR202W) gene participated in steroid biosynthesis pathway, which can serve as a key yeast strain of OPFRs toxification. Overall, our study demonstrated an effective platform for accurately assessing OPFRs risks and provided a basis for further green OPFRs development.
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Affiliation(s)
- Miao Guan
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China
| | - Xiaoyang Wang
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China
| | - Xinyuan Xu
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China
| | - Tianqi Ling
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China
| | - Jing Wu
- Department of Psychology, College of Victoria College, University of Toronto, Toronto, ON, CA M5R 0A3, Canada
| | - Jinjun Qian
- School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Ave., Nanjing, Jiangsu 210023, China
| | - Fei Ma
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China.
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu 210023, China
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4
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Silva AC, Loizou GD, McNally K, Osborne O, Potter C, Gott D, Colbourne JK, Viant MR. A novel method to derive a human safety limit for PFOA by gene expression profiling and modelling. FRONTIERS IN TOXICOLOGY 2024; 6:1368320. [PMID: 38577564 PMCID: PMC10991825 DOI: 10.3389/ftox.2024.1368320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 03/01/2024] [Indexed: 04/06/2024] Open
Abstract
Perfluorooctanoic acid (PFOA) is a persistent environmental contaminant that can accumulate in the human body due to its long half-life. This substance has been associated with liver, pancreatic, testicular and breast cancers, liver steatosis and endocrine disruption. PFOA is a member of a large group of substances also known as "forever chemicals" and the vast majority of substances of this group lack toxicological data that would enable their effective risk assessment in terms of human health hazards. This study aimed to derive a health-based guidance value for PFOA intake (ng/kg BW/day) from in vitro transcriptomics data. To this end, we developed an in silico workflow comprising five components: (i) sourcing in vitro hepatic transcriptomics concentration-response data; (ii) deriving molecular points of departure using BMDExpress3 and performing pathway analysis using gene set enrichment analysis (GSEA) to identify the most sensitive molecular pathways to PFOA exposure; (iii) estimating freely-dissolved PFOA concentrations in vitro using a mass balance model; (iv) estimating in vivo doses by reverse dosimetry using a PBK model for PFOA as part of a quantitative in vitro to in vivo extrapolation (QIVIVE) algorithm; and (v) calculating a tolerable daily intake (TDI) for PFOA. Fourteen percent of interrogated genes exhibited in vitro concentration-response relationships. GSEA pathway enrichment analysis revealed that "fatty acid metabolism" was the most sensitive pathway to PFOA exposure. In vitro free PFOA concentrations were calculated to be 2.9% of the nominal applied concentrations, and these free concentrations were input into the QIVIVE workflow. Exposure doses for a virtual population of 3,000 individuals were estimated, from which a TDI of 0.15 ng/kg BW/day for PFOA was calculated using the benchmark dose modelling software, PROAST. This TDI is comparable to previously published values of 1.16, 0.69, and 0.86 ng/kg BW/day by the European Food Safety Authority. In conclusion, this study demonstrates the combined utility of an "omics"-derived molecular point of departure and in silico QIVIVE workflow for setting health-based guidance values in anticipation of the acceptance of in vitro concentration-response molecular measurements in chemical risk assessment.
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Affiliation(s)
- Arthur de Carvalho e Silva
- School of Biosciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Environmental Research and Justice (CERJ), University of Birmingham, Birmingham, United Kingdom
| | | | | | - Olivia Osborne
- Science Evidence and Research Division, Food Standards Agency, London, United Kingdom
| | - Claire Potter
- Science Evidence and Research Division, Food Standards Agency, London, United Kingdom
| | - David Gott
- Science Evidence and Research Division, Food Standards Agency, London, United Kingdom
| | - John K. Colbourne
- School of Biosciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Environmental Research and Justice (CERJ), University of Birmingham, Birmingham, United Kingdom
| | - Mark R. Viant
- School of Biosciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Environmental Research and Justice (CERJ), University of Birmingham, Birmingham, United Kingdom
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5
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Thienpont A, Cho E, Williams A, Meier MJ, Yauk CL, Rogiers V, Vanhaecke T, Mertens B. Unlocking the Power of Transcriptomic Biomarkers in Qualitative and Quantitative Genotoxicity Assessment of Chemicals. Chem Res Toxicol 2024; 37:465-475. [PMID: 38408751 PMCID: PMC10952014 DOI: 10.1021/acs.chemrestox.3c00318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/01/2024] [Accepted: 02/06/2024] [Indexed: 02/28/2024]
Abstract
To modernize genotoxicity assessment and reduce reliance on experimental animals, new approach methodologies (NAMs) that provide human-relevant dose-response data are needed. Two transcriptomic biomarkers, GENOMARK and TGx-DDI, have shown a high classification accuracy for genotoxicity. As these biomarkers were extracted from different training sets, we investigated whether combining the two biomarkers in a human-derived metabolically competent cell line (i.e., HepaRG) provides complementary information for the classification of genotoxic hazard identification and potency ranking. First, the applicability of GENOMARK to TempO-Seq, a high-throughput transcriptomic technology, was evaluated. HepaRG cells were exposed for 72 h to increasing concentrations of 10 chemicals (i.e., eight known in vivo genotoxicants and two in vivo nongenotoxicants). Gene expression data were generated using the TempO-Seq technology. We found a prediction performance of 100%, confirming the applicability of GENOMARK to TempO-Seq. Classification using TGx-DDI was then compared to GENOMARK. For the chemicals identified as genotoxic, benchmark concentration modeling was conducted to perform potency ranking. The high concordance observed for both hazard classification and potency ranking by GENOMARK and TGx-DDI highlights the value of integrating these NAMs in a weight of evidence evaluation of genotoxicity.
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Affiliation(s)
- Anouck Thienpont
- Department
of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium
- Department
of Chemical and Physical Health Risks, Sciensano, 1050 Brussels, Belgium
| | - Eunnara Cho
- Environmental
Health Science and Research Bureau, Health
Canada, Ottawa, ON K1A 0K9, Canada
| | - Andrew Williams
- Environmental
Health Science and Research Bureau, Health
Canada, Ottawa, ON K1A 0K9, Canada
| | - Matthew J. Meier
- Environmental
Health Science and Research Bureau, Health
Canada, Ottawa, ON K1A 0K9, Canada
| | - Carole L. Yauk
- Department
of Biology, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Vera Rogiers
- Department
of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium
| | - Tamara Vanhaecke
- Department
of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium
| | - Birgit Mertens
- Department
of Chemical and Physical Health Risks, Sciensano, 1050 Brussels, Belgium
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6
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Carpi D, Liska R, Malinowska JM, Palosaari T, Bouhifd M, Whelan M. Investigating the dependency of in vitro benchmark concentrations on exposure time in transcriptomics experiments. Toxicol In Vitro 2024; 95:105761. [PMID: 38081393 PMCID: PMC10879918 DOI: 10.1016/j.tiv.2023.105761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 11/10/2023] [Accepted: 12/05/2023] [Indexed: 12/22/2023]
Abstract
There is increasing interest to employ in vitro transcriptomics experiments in toxicological testing, for example to determine a point-of-departure (PoD) for chemical safety assessment. However current practices to derive PoD tend to utilise a single exposure time despite the importance of exposure time on the manifestation of toxicity caused by a chemical. Therefore it is important to investigate both concentration and exposure time to determine how these factors affect biological responses, and as a consequence, the derivation of PoDs. In this study, metabolically competent HepaRG cells were exposed to five known toxicants over a range of concentrations and time points for subsequent gene expression analysis, using a targeted RNA expression assay (TempO-Seq). A non-parametric factor-modelling approach was used to model the collective response of all significant genes, which exploited the interdependence of differentially expressed gene responses. This in turn allowed the determination of an isobenchmark response (isoBMR) curve for each chemical in a reproducible manner. For 2 of the 5 chemicals tested, the PoD was observed to vary by 0.5-1 log-order within the 48-h timeframe of the experiment. The approach and findings presented here clearly demonstrate the need to take both concentration and exposure time into account when designing in vitro toxicogenomics experiments to determine PoD. Doing so also provides a means to use concentration-time-response modelling as a basis to extrapolate a PoD from shorter to longer exposure durations, and to identify chemicals of concern that can cause cumulative effects over time.
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Affiliation(s)
- Donatella Carpi
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Roman Liska
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | | | - Taina Palosaari
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Mounir Bouhifd
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Maurice Whelan
- European Commission, Joint Research Centre (JRC), Ispra, Italy.
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7
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Harrill JA, Everett LJ, Haggard DE, Bundy JL, Willis CM, Shah I, Friedman KP, Basili D, Middleton A, Judson RS. Exploring the effects of experimental parameters and data modeling approaches on in vitro transcriptomic point-of-departure estimates. Toxicology 2024; 501:153694. [PMID: 38043774 DOI: 10.1016/j.tox.2023.153694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 11/24/2023] [Accepted: 11/29/2023] [Indexed: 12/05/2023]
Abstract
Multiple new approach methods (NAMs) are being developed to rapidly screen large numbers of chemicals to aid in hazard evaluation and risk assessments. High-throughput transcriptomics (HTTr) in human cell lines has been proposed as a first-tier screening approach for determining the types of bioactivity a chemical can cause (activation of specific targets vs. generalized cell stress) and for calculating transcriptional points of departure (tPODs) based on changes in gene expression. In the present study, we examine a range of computational methods to calculate tPODs from HTTr data, using six data sets in which MCF7 cells cultured in two different media formulations were treated with a panel of 44 chemicals for 3 different exposure durations (6, 12, 24 hr). The tPOD calculation methods use data at the level of individual genes and gene set signatures, and compare data processed using the ToxCast Pipeline 2 (tcplfit2), BMDExpress and PLIER (Pathway Level Information ExtractoR). Methods were evaluated by comparing to in vitro PODs from a validated set of high-throughput screening (HTS) assays for a set of estrogenic compounds. Key findings include: (1) for a given chemical and set of experimental conditions, tPODs calculated by different methods can vary by several orders of magnitude; (2) tPODs are at least as sensitive to computational methods as to experimental conditions; (3) in comparison to an external reference set of PODs, some methods give generally higher values, principally PLIER and BMDExpress; and (4) the tPODs from HTTr in this one cell type are mostly higher than the overall PODs from a broad battery of targeted in vitro ToxCast assays, reflecting the need to test chemicals in multiple cell types and readout technologies for in vitro hazard screening.
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Affiliation(s)
- Joshua A Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Logan J Everett
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Derik E Haggard
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA; Oak Ridge Institute for Science and Education (ORISE), USA
| | - Joseph L Bundy
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Clinton M Willis
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA; Oak Ridge Associated Universities (ORAU), USA
| | - Imran Shah
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Katie Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Danilo Basili
- Unilever Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Alistair Middleton
- Unilever Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Richard S Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA.
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8
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Chen P, Li Y, Long Q, Zuo T, Zhang Z, Guo J, Xu D, Li K, Liu S, Li S, Yin J, Chang L, Kukic P, Liddell M, Tulum L, Carmichael P, Peng S, Li J, Zhang Q, Xu P. The phosphoproteome is a first responder in tiered cellular adaptation to chemical stress followed by proteomics and transcriptomics alteration. CHEMOSPHERE 2023; 344:140329. [PMID: 37783352 DOI: 10.1016/j.chemosphere.2023.140329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 09/20/2023] [Accepted: 09/28/2023] [Indexed: 10/04/2023]
Abstract
Next-generation risk assessment (NGRA) for environmental chemicals involves a weight of evidence (WoE) framework integrating a suite of new approach methodologies (NAMs) based on points of departure (PoD) obtained from in vitro assays. Among existing NAMs, the omic-based technologies are of particular importance based on the premise that any apical endpoint change indicative of impaired health must be underpinned by some alterations at the omics level, such as transcriptome, proteome, metabolome, epigenome and genome. Transcriptomic assay plays a leading role in providing relatively conservative PoDs compared with apical endpoints. However, it is unclear whether and how parameters measured with other omics techniques predict the cellular response to chemical perturbations, especially at exposure levels below the transcriptomically defined PoD. Multi-omics coverage may provide additional sensitive or confirmative biomarkers to complement and reduce the uncertainty in safety decisions made using targeted and transcriptomics assays. In the present study, we conducted multi-omics studies of transcriptomics, proteomics and phosphoproteomics on two prototype compounds, coumarin and 2,4-dichlorophenoxyacetic acid (2,4-D), with multiple chemical concentrations and time points, to understand the sensitivity of the three omics techniques in response to chemically-induced changes in HepG2. We demonstrated that, phosphoproteomics alterations occur not only earlier in time, but also more sensitive to lower concentrations than proteomics and transcriptomics when the HepG2 cells were exposed to various chemical treatments. The phosphoproteomics changes appear to approach maximum when the transcriptomics alterations begin to initiate. Therefore, it is proximal to the very early effects induced by chemical exposure. We concluded that phosphoproteomics can be utilized to provide a more complete coverage of chemical-induced cellular alteration and supplement transcriptomics-based health safety decision making.
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Affiliation(s)
- Peiru Chen
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China; Hebei Province Key Lab of Research and Application on Microbial Diversity, College of Life Sciences, Hebei University, Baoding, 071002, China
| | - Yuan Li
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China; Department of Biomedicine, Medical College, Guizhou University, Guiyang, 550025, China; Guizhou Provincial People's Hospital, Affiliated Hospital of Guizhou University, Guiyang, 550002, China
| | - Qi Long
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China; School of Basic Medicine, Anhui Medical University, Hefei, 230032, China
| | - Tao Zuo
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Zhenpeng Zhang
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Jiabin Guo
- Evaluation and Research Centre for Toxicology, Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, 100071, China
| | - Danyang Xu
- Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Kaixuan Li
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China; Hebei Province Key Lab of Research and Application on Microbial Diversity, College of Life Sciences, Hebei University, Baoding, 071002, China
| | - Shu Liu
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Suzhen Li
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China; School of Basic Medicine, Anhui Medical University, Hefei, 230032, China
| | - Jian Yin
- Evaluation and Research Centre for Toxicology, Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, 100071, China
| | - Lei Chang
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Predrag Kukic
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK
| | - Mark Liddell
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK
| | - Liz Tulum
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK
| | - Paul Carmichael
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK
| | - Shuangqing Peng
- Evaluation and Research Centre for Toxicology, Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, 100071, China
| | - Jin Li
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK.
| | - Qiang Zhang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, USA, GA, 30322.
| | - Ping Xu
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China; Hebei Province Key Lab of Research and Application on Microbial Diversity, College of Life Sciences, Hebei University, Baoding, 071002, China; Department of Biomedicine, Medical College, Guizhou University, Guiyang, 550025, China; School of Basic Medicine, Anhui Medical University, Hefei, 230032, China; Program of Environmental Toxicology, School of Public Health, China Medical University, Shenyang, 110122, China.
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9
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Barutcu AR, Black MB, Nong A. Mining toxicogenomic data for dose-responsive pathways: implications in advancing next-generation risk assessment. FRONTIERS IN TOXICOLOGY 2023; 5:1272364. [PMID: 38046401 PMCID: PMC10691261 DOI: 10.3389/ftox.2023.1272364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 11/02/2023] [Indexed: 12/05/2023] Open
Abstract
Introduction: While targeted investigation of key toxicity pathways has been instrumental for biomarker discovery, unbiased and holistic analysis of transcriptomic data provides a complementary systems-level perspective. However, in a systematic context, this approach has yet to receive comprehensive and methodical implementation. Methods: Here, we took an integrated bioinformatic approach by re-analyzing publicly available MCF7 cell TempO-seq data for 44 ToxCast chemicals using an alternative pipeline to demonstrate the power of this approach. The original study has focused on analyzing the gene signature approach and comparing them to in vitro biological pathway altering concentrations determined from ToxCast HTS assays. Our workflow, in comparison, involves sequential differential expression, gene set enrichment, benchmark dose modeling, and identification of commonly perturbed pathways by network visualization. Results: Using this approach, we identified dose-responsive molecular changes, biological pathways, and points of departure in an untargeted manner. Critically, benchmark dose modeling based on pathways recapitulated points of departure for apical endpoints, while also revealing additional perturbed mechanisms missed by single endpoint analyses. Discussion: This systems-toxicology approach provides multifaceted insights into the complex effects of chemical exposures. Our work highlights the importance of unbiased data-driven techniques, alongside targeted methods, for comprehensively evaluating molecular initiating events, dose-response relationships, and toxicity pathways. Overall, integrating omics assays with robust bioinformatics holds promise for improving chemical risk assessment and advancing new approach methodologies (NAMs).
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10
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Wang X, Rowan-Carroll A, Meier MJ, Williams A, Yauk CL, Hales BF, Robaire B. Toxicological Mechanisms and Potencies of Organophosphate Esters in KGN Human Ovarian Granulosa Cells as Revealed by High-throughput Transcriptomics. Toxicol Sci 2023; 197:kfad114. [PMID: 37941476 PMCID: PMC10823774 DOI: 10.1093/toxsci/kfad114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023] Open
Abstract
Despite the growing number of studies reporting potential risks associated with exposure to organophosphate esters (OPEs), their molecular mechanisms of action remain poorly defined. We used the high-throughput TempO-Seq™ platform to investigate the effects of frequently detected OPEs on the expression of ∼3000 environmentally responsive genes in KGN human ovarian granulosa cells. Cells were exposed for 48 h to one of five OPEs (0.1 to 50 μM): tris(methylphenyl) phosphate (TMPP), isopropylated triphenyl phosphate (IPPP), tert-butylphenyl diphenyl phosphate (BPDP), triphenyl phosphate (TPHP), or tris(2-butoxyethyl) phosphate (TBOEP). The sequencing data indicate that four OPEs induced transcriptional changes, whereas TBOEP had no effect within the concentration range tested. Multiple pathway databases were used to predict alterations in biological processes based on differentially expressed genes. At lower concentrations, inhibition of the cholesterol biosynthetic pathway was the predominant effect of OPEs; this was likely a consequence of intracellular cholesterol accumulation. At higher concentrations, BPDP and TPHP had distinct effects, primarily affecting pathways involved in cell cycle progression and other stress responses. Benchmark concentration (BMC) modelling revealed that BPDP had the lowest transcriptomic point of departure. However, in vitro to in vivo extrapolation modeling indicated that TMPP was bioactive at lower concentrations than the other OPEs. We conclude that these new approach methodologies provide information on the mechanism(s) underlying the effects of data-poor compounds and assist in the derivation of protective points of departure for use in chemical read-across and decision-making.
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Affiliation(s)
- Xiaotong Wang
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec H3G 1Y6, Canada
| | - Andrea Rowan-Carroll
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Matthew J Meier
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, Ontario K1N 9A7, Canada
| | - Barbara F Hales
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec H3G 1Y6, Canada
| | - Bernard Robaire
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec H3G 1Y6, Canada
- Department of Obstetrics and Gynecology, McGill University, Montréal, Québec H3G 1Y6, Canada
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11
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Guan M, Cao Y, Wang X, Xu X, Ning C, Qian J, Ma F, Zhang X. Characterizing temporal variability and repeatability of dose-dependent functional genomics approach for evaluating triclosan toxification. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 895:165209. [PMID: 37391155 DOI: 10.1016/j.scitotenv.2023.165209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Revised: 06/21/2023] [Accepted: 06/27/2023] [Indexed: 07/02/2023]
Abstract
Dose-dependent functional genomics approach has shown great advantage in identifying the molecular initiating event (MIE) of chemical toxification and yielding point of departure (POD) at genome-wide scale. However, POD variability and repeatability derived from experimental design (settings of dose, replicate number, and exposure time) has not been fully determined. In this work, we evaluated POD profiles perturbed by triclosan (TCS) using dose-dependent functional genomics approach in Saccharomyces cerevisiae at multiple time points (9 h, 24 h and 48 h). The full dataset (total 9 concentrations with 6 replicates per treatment) at 9 h was subsampled 484 times to generate subsets of 4 dose groups (Dose A - Dose D with varied concentration range and spacing) and 5 replicate numbers (2 reps - 6 reps). Firstly, given the accuracy of POD and the experimental cost, the POD profiles from 484 subsampled datasets demonstrated that the Dose C group (space narrow at high concentrations and wide dose range) with three replicates was best choice at both gene and pathway levels. Secondly, the variability of POD was found to be relatively robustness and stability across different experimental designs, but POD was more dependent on the dose range and interval than the number of replicates. Thirdly, MIE of TCS toxification was identified to be the glycerophospholipid metabolism pathway at all-time points, supporting the ability of our approach to accurately recognize MIE of chemical toxification at both short- and long-term exposure. Finally, we identified and validated 13 key mutant strains involved in MIE of TCS toxification, which could serve as biomarkers for TCS exposure. Taken together, our work evaluated the repeatability of dose-dependent functional genomics approach and the variability of POD and MIE of TCS toxification, which will benefit the experimental design for future dose-dependent functional genomics study.
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Affiliation(s)
- Miao Guan
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China
| | - Yuqi Cao
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China
| | - Xiaoyang Wang
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China
| | - Xinyuan Xu
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China
| | - Can Ning
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China
| | - Jinjun Qian
- School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Ave., Nanjing, Jiangsu 210023, China.
| | - Fei Ma
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China.
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu 210023, China
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12
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Gant TW, Auerbach SS, Von Bergen M, Bouhifd M, Botham PA, Caiment F, Currie RA, Harrill J, Johnson K, Li D, Rouquie D, van Ravenzwaay B, Sistare F, Tralau T, Viant MR, van de Laan JW, Yauk C. Applying genomics in regulatory toxicology: a report of the ECETOC workshop on omics threshold on non-adversity. Arch Toxicol 2023; 97:2291-2302. [PMID: 37296313 PMCID: PMC10322787 DOI: 10.1007/s00204-023-03522-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 05/11/2023] [Indexed: 06/12/2023]
Abstract
In a joint effort involving scientists from academia, industry and regulatory agencies, ECETOC's activities in Omics have led to conceptual proposals for: (1) A framework that assures data quality for reporting and inclusion of Omics data in regulatory assessments; and (2) an approach to robustly quantify these data, prior to interpretation for regulatory use. In continuation of these activities this workshop explored and identified areas of need to facilitate robust interpretation of such data in the context of deriving points of departure (POD) for risk assessment and determining an adverse change from normal variation. ECETOC was amongst the first to systematically explore the application of Omics methods, now incorporated into the group of methods known as New Approach Methodologies (NAMs), to regulatory toxicology. This support has been in the form of both projects (primarily with CEFIC/LRI) and workshops. Outputs have led to projects included in the workplan of the Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) group of the Organisation for Economic Co-operation and Development (OECD) and to the drafting of OECD Guidance Documents for Omics data reporting, with potentially more to follow on data transformation and interpretation. The current workshop was the last in a series of technical methods development workshops, with a sub-focus on the derivation of a POD from Omics data. Workshop presentations demonstrated that Omics data developed within robust frameworks for both scientific data generation and analysis can be used to derive a POD. The issue of noise in the data was discussed as an important consideration for identifying robust Omics changes and deriving a POD. Such variability or "noise" can comprise technical or biological variation within a dataset and should clearly be distinguished from homeostatic responses. Adverse outcome pathways (AOPs) were considered a useful framework on which to assemble Omics methods, and a number of case examples were presented in illustration of this point. What is apparent is that high dimension data will always be subject to varying processing pipelines and hence interpretation, depending on the context they are used in. Yet, they can provide valuable input for regulatory toxicology, with the pre-condition being robust methods for the collection and processing of data together with a comprehensive description how the data were interpreted, and conclusions reached.
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Affiliation(s)
- Timothy W Gant
- United Kingdom Health Security Agency, Harwell Science Campus, Didcot, Oxfordshire, United Kingdom.
- Imperial College London School of Public Health, London, United Kingdom.
| | - Scott S Auerbach
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, RTP, Durham, NC, USA
| | - Martin Von Bergen
- Department for Molecular Systems Biology, Helmholtz Centre for Environmental Research, Leipzig, Germany
| | | | | | - Florian Caiment
- Department of Toxicogenomics, Maastricht University, Maastricht, The Netherlands
| | | | - Joshua Harrill
- Cellular and Molecular Toxicologist, Center for Computational Toxicology and Exposure (CCTE), U.S. Environmental Protection Agency, Durham, NC, USA
| | - Kamin Johnson
- Predictive Safety Center, Corteva Agriscience, Indianapolis, IN, USA
| | - Dongying Li
- National Center for Toxicological Research, U.S. Food and Drug Administration (FDA), 3900 NCTR Road, Jefferson, AR, 72079, USA
| | - David Rouquie
- Bayer SAS, Bayer Crop Science, 355 Rue Dostoïevski, CS 90153, 06906, Valbonne Sophia-Antipolis, France
| | | | | | - Tewes Tralau
- Department of Pesticides Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Mark R Viant
- School of Biosciences, University of Birmingham, Birmingham, UK
| | | | - Carole Yauk
- Department of Biology, University of Ottawa, Ottawa, Canada
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13
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Tsai HHD, House JS, Wright FA, Chiu WA, Rusyn I. A tiered testing strategy based on in vitro phenotypic and transcriptomic data for selecting representative petroleum UVCBs for toxicity evaluation in vivo. Toxicol Sci 2023; 193:219-233. [PMID: 37079747 PMCID: PMC10230285 DOI: 10.1093/toxsci/kfad041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023] Open
Abstract
Hazard evaluation of substances of "unknown or variable composition, complex reaction products and biological materials" (UVCBs) remains a major challenge in regulatory science because their chemical composition is difficult to ascertain. Petroleum substances are representative UVCBs and human cell-based data have been previously used to substantiate their groupings for regulatory submissions. We hypothesized that a combination of phenotypic and transcriptomic data could be integrated to make decisions as to selection of group-representative worst-case petroleum UVCBs for subsequent toxicity evaluation in vivo. We used data obtained from 141 substances from 16 manufacturing categories previously tested in 6 human cell types (induced pluripotent stem cell [iPSC]-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, and MCF7 and A375 cell lines). Benchmark doses for gene-substance combinations were calculated, and both transcriptomic and phenotype-derived points of departure (PODs) were obtained. Correlation analysis and machine learning were used to assess associations between phenotypic and transcriptional PODs and to determine the most informative cell types and assays, thus representing a cost-effective integrated testing strategy. We found that 2 cell types-iPSC-derived-hepatocytes and -cardiomyocytes-contributed the most informative and protective PODs and may be used to inform selection of representative petroleum UVCBs for further toxicity evaluation in vivo. Overall, although the use of new approach methodologies to prioritize UVCBs has not been widely adopted, our study proposes a tiered testing strategy based on iPSC-derived hepatocytes and cardiomyocytes to inform selection of representative worst-case petroleum UVCBs from each manufacturing category for further toxicity evaluation in vivo.
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Affiliation(s)
- Han-Hsuan Doris Tsai
- Interdisciplinary Faculty of Toxicology, College Station, Texas 77843, USA
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, USA
| | - John S House
- National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA
| | - Fred A Wright
- Interdisciplinary Faculty of Toxicology, College Station, Texas 77843, USA
- Department of Statistics and Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27603, USA
- Department of Biological Sciences and Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27603, USA
| | - Weihsueh A Chiu
- Interdisciplinary Faculty of Toxicology, College Station, Texas 77843, USA
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, USA
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology, College Station, Texas 77843, USA
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, USA
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14
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Reardon AJF, Farmahin R, Williams A, Meier MJ, Addicks GC, Yauk CL, Matteo G, Atlas E, Harrill J, Everett LJ, Shah I, Judson R, Ramaiahgari S, Ferguson SS, Barton-Maclaren TS. From vision toward best practices: Evaluating in vitro transcriptomic points of departure for application in risk assessment using a uniform workflow. FRONTIERS IN TOXICOLOGY 2023; 5:1194895. [PMID: 37288009 PMCID: PMC10242042 DOI: 10.3389/ftox.2023.1194895] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 05/03/2023] [Indexed: 06/09/2023] Open
Abstract
The growing number of chemicals in the current consumer and industrial markets presents a major challenge for regulatory programs faced with the need to assess the potential risks they pose to human and ecological health. The increasing demand for hazard and risk assessment of chemicals currently exceeds the capacity to produce the toxicity data necessary for regulatory decision making, and the applied data is commonly generated using traditional approaches with animal models that have limited context in terms of human relevance. This scenario provides the opportunity to implement novel, more efficient strategies for risk assessment purposes. This study aims to increase confidence in the implementation of new approach methods in a risk assessment context by using a parallel analysis to identify data gaps in current experimental designs, reveal the limitations of common approaches deriving transcriptomic points of departure, and demonstrate the strengths in using high-throughput transcriptomics (HTTr) to derive practical endpoints. A uniform workflow was applied across six curated gene expression datasets from concentration-response studies containing 117 diverse chemicals, three cell types, and a range of exposure durations, to determine tPODs based on gene expression profiles. After benchmark concentration modeling, a range of approaches was used to determine consistent and reliable tPODs. High-throughput toxicokinetics were employed to translate in vitro tPODs (µM) to human-relevant administered equivalent doses (AEDs, mg/kg-bw/day). The tPODs from most chemicals had AEDs that were lower (i.e., more conservative) than apical PODs in the US EPA CompTox chemical dashboard, suggesting in vitro tPODs would be protective of potential effects on human health. An assessment of multiple data points for single chemicals revealed that longer exposure duration and varied cell culture systems (e.g., 3D vs. 2D) lead to a decreased tPOD value that indicated increased chemical potency. Seven chemicals were flagged as outliers when comparing the ratio of tPOD to traditional POD, thus indicating they require further assessment to better understand their hazard potential. Our findings build confidence in the use of tPODs but also reveal data gaps that must be addressed prior to their adoption to support risk assessment applications.
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Affiliation(s)
- Anthony J. F. Reardon
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Reza Farmahin
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Matthew J. Meier
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Gregory C. Addicks
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Carole L. Yauk
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Geronimo Matteo
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Ella Atlas
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
- Department of Biochemistry, University of Ottawa, Ottawa, ON, Canada
| | - Joshua Harrill
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Logan J. Everett
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Imran Shah
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Richard Judson
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Sreenivasa Ramaiahgari
- Division of Translational Toxicology, Mechanistic Toxicology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Stephen S. Ferguson
- Division of Translational Toxicology, Mechanistic Toxicology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Tara S. Barton-Maclaren
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
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15
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Guan M, Wang X, Pan Y, Xu Y, Cao Y, Yan L, Ma L, Ma F, Zhang X. Delving into the molecular initiating event of cadmium toxification via the dose-dependent functional genomics approach in Saccharomyces cerevisiae. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 323:121287. [PMID: 36791950 DOI: 10.1016/j.envpol.2023.121287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 02/03/2023] [Accepted: 02/12/2023] [Indexed: 06/18/2023]
Abstract
Determining dose-response relationship is essential for comprehensively revealing chemical-caused effects on organisms. However, uncertainty and complexity of gene/protein interactions cause the inability of traditional toxicogenomic methods (e.g., transcriptomics, proteomics and metabolomics) to effectively establish the direct relationship between chemical exposure and genes. In this work, we built an effective dose-dependent yeast functional genomics approach, which can clearly identify the direct gene-chemical link in the process of cadmium (Cd) toxification from a genome-wide scale with wide range concentrations (0.83, 2.49, 7.48, 22.45, 67.34, 202.03 and 606.1 μM). Firstly, we identified 220 responsive strains, and found that 142, 110, 91, 34, 8, 0 and 0 responsive strains can be respectively modulated by seven different Cd exposure concentrations ranging from high to low. Secondly, our results demonstrated that these genes induced by the high Cd exposure were mainly enriched in the process of cell autophagy, but ones caused by the low Cd exposure were primarily involved in oxidative stress. Thirdly, we found that the top-ranked GO biological processes with the lowest point of departure (POD) were transmembrane transporter complex and mitochondrial respiratory chain complex III, suggesting that mitochondrion might be the toxicity target of Cd. Similarly, nucleotide excision repair was ranked first in KEGG pathway with the least POD, indicating that this dose-dependent functional genomics approach can effectively detect the molecular initiating event (MIE) of cadmium toxification. Fourthly, we identified four key mutant strains (RIP1, QCR8, CYT1 and QCR2) as biomarkers for Cd exposure. Finally, the dose-dependent functional genomics approach also performed well in identifying MIE for additional genotoxicity chemical 4-nitroquinoline-1-oxide (4-NQO) data. Overall, our study developed a dose-dependent functional genomics approach, which is powerful to delve into the MIE of chemical toxification and is beneficial for guiding further chemical risk assessment.
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Affiliation(s)
- Miao Guan
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu, 210023, China
| | - Xiaoyang Wang
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu, 210023, China
| | - Yi Pan
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu, 210023, China
| | - Yue Xu
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu, 210023, China
| | - Yuqi Cao
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu, 210023, China
| | - Lu Yan
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu, 210023, China
| | - Lili Ma
- Jiangsu Engineering Lab of Water and Soil Eco-remediation, School of the Environment, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu, 210023, China.
| | - Fei Ma
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu, 210023, China
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu, 210023, China
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16
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Chauhan V, Yu J, Vuong N, Haber LT, Williams A, Auerbach SS, Beaton D, Wang Y, Stainforth R, Wilkins RC, Azzam EI, Richardson RB, Khan MGM, Jadhav A, Burtt JJ, Leblanc J, Randhawa K, Tollefsen KE, Yauk CL. Considerations for application of benchmark dose modeling in radiation research: workshop highlights. Int J Radiat Biol 2023; 99:1320-1331. [PMID: 36881459 DOI: 10.1080/09553002.2023.2181998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 01/18/2023] [Accepted: 02/06/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop's objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples. CONCLUSIONS Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work.
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Affiliation(s)
- Vinita Chauhan
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Jihang Yu
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
| | - Ngoc Vuong
- Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Lynne T Haber
- Department of Environmental and Public Health Sciences, Risk Science Center, University of Cincinnati, Cincinnati, OH, USA
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health Science and Research Bureau, Health Canada, Ottawa, Canada
| | - Scott S Auerbach
- National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Danielle Beaton
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
| | - Yi Wang
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Canada
| | | | - Ruth C Wilkins
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Edouard I Azzam
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
- Department of Radiology, New Jersey Medical School, Rutgers University, Newark, NJ, USA
| | - Richard B Richardson
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
- Medical Physics Unit, McGill University, Montreal, QC, Canada
| | | | - Ashok Jadhav
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
| | - Julie J Burtt
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Julie Leblanc
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Kristi Randhawa
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Knut Erik Tollefsen
- Norwegian Institute for Water Research (NIVA), Oslo, Norway
- Norwegian University of Life Sciences (NMBU), Ås, Norway
- Centre for Environmental Radioactivity, Norwegian University of Life Sciences (NMBU), Ås, Norway
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, Canada
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17
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Kuepfer L, Fuellen G, Stahnke T. Quantitative systems pharmacology of the eye: Tools and data for ocular QSP. CPT Pharmacometrics Syst Pharmacol 2023; 12:288-299. [PMID: 36708082 PMCID: PMC10014063 DOI: 10.1002/psp4.12918] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 12/21/2022] [Accepted: 01/02/2023] [Indexed: 01/29/2023] Open
Abstract
Good eyesight belongs to the most-valued attributes of health, and diseases of the eye are a significant healthcare burden. Case numbers are expected to further increase in the next decades due to an aging society. The development of drugs in ophthalmology, however, is difficult due to limited accessibility of the eye, in terms of drug administration and in terms of sampling of tissues for drug pharmacokinetics (PKs) and pharmacodynamics (PDs). Ocular quantitative systems pharmacology models provide the opportunity to describe the distribution of drugs in the eye as well as the resulting drug-response in specific segments of the eye. In particular, ocular physiologically-based PK (PBPK) models are necessary to describe drug concentration levels in different regions of the eye. Further, ocular effect models using molecular data from specific cellular systems are needed to develop dose-response correlations. We here describe the current status of PK/PBPK as well as PD models for the eyes and discuss cellular systems, data repositories, as well as animal models in ophthalmology. The application of the various concepts is highlighted for the development of new treatments for postoperative fibrosis after glaucoma surgery.
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Affiliation(s)
- Lars Kuepfer
- Institute for Systems Medicine with Focus on Organ Interaction, University Hospital RWTH Aachen, Aachen, Germany
| | - Georg Fuellen
- Institute for Biostatistics and Informatics in Medicine and Aging Research (IBIMA), Rostock University Medical Center, Rostock, Germany
| | - Thomas Stahnke
- Institute for ImplantTechnology and Biomaterials e.V., Rostock, Germany.,Department of Ophthalmology, Rostock University Medical Center, Rostock, Germany
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18
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Matteo G, Leingartner K, Rowan-Carroll A, Meier M, Williams A, Beal MA, Gagné M, Farmahin R, Wickramasuriya S, Reardon AJF, Barton-Maclaren T, Christopher Corton J, Yauk CL, Atlas E. In vitro transcriptomic analyses reveal pathway perturbations, estrogenic activities, and potencies of data-poor BPA alternative chemicals. Toxicol Sci 2023; 191:266-275. [PMID: 36534918 PMCID: PMC9936204 DOI: 10.1093/toxsci/kfac127] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Since initial regulatory action in 2010 in Canada, bisphenol A (BPA) has been progressively replaced by structurally related alternative chemicals. Unfortunately, many of these chemicals are data-poor, limiting toxicological risk assessment. We used high-throughput transcriptomics to evaluate potential hazards and compare potencies of BPA and 15 BPA alternative chemicals in cultured breast cancer cells. MCF-7 cells were exposed to BPA and 15 alternative chemicals (0.0005-100 µM) for 48 h. TempO-Seq (BioSpyder Inc) was used to examine global transcriptomic changes and estrogen receptor alpha (ERα)-associated transcriptional changes. Benchmark concentration (BMC) analysis was conducted to identify 2 global transcriptomic points of departure: (1) the lowest pathway median gene BMC and (2) the 25th lowest rank-ordered gene BMC. ERα activation was evaluated using a published transcriptomic biomarker and an ERα-specific transcriptomic point of departure was derived. Genes fitting BMC models were subjected to upstream regulator and canonical pathway analysis in Ingenuity Pathway Analysis. Biomarker analysis identified BPA and 8 alternative chemicals as ERα active. Global and ERα transcriptomic points of departure produced highly similar potency rankings with bisphenol AF as the most potent chemical tested, followed by BPA and bisphenol C. Further, BPA and transcriptionally active alternative chemicals enriched similar gene sets associated with increased cell division and cancer-related processes. These data provide support for future read-across applications of transcriptomic profiling for risk assessment of data-poor chemicals and suggest that several BPA alternative chemicals may cause hazards at similar concentrations to BPA.
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Affiliation(s)
- Geronimo Matteo
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K2K 0K9, Canada.,Department of Biology, Faculty of Science, University of Ottawa, Ottawa, Ontario K1N 9A7, Canada
| | - Karen Leingartner
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K2K 0K9, Canada.,Department of Biology, Faculty of Science, University of Ottawa, Ottawa, Ontario K1N 9A7, Canada
| | - Andrea Rowan-Carroll
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K2K 0K9, Canada.,Department of Biology, Faculty of Science, University of Ottawa, Ottawa, Ontario K1N 9A7, Canada
| | - Matthew Meier
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K2K 0K9, Canada.,Department of Biology, Faculty of Science, University of Ottawa, Ottawa, Ontario K1N 9A7, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K2K 0K9, Canada.,Department of Biology, Faculty of Science, University of Ottawa, Ottawa, Ontario K1N 9A7, Canada
| | - Marc A Beal
- Bureau of Chemical Safety, Health Canada.,Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Matthew Gagné
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Reza Farmahin
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Shamika Wickramasuriya
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Anthony J F Reardon
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Tara Barton-Maclaren
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - J Christopher Corton
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Carole L Yauk
- Department of Biology, Faculty of Science, University of Ottawa, Ottawa, Ontario K1N 9A7, Canada
| | - Ella Atlas
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K2K 0K9, Canada.,Department of Biochemistry, Faculty of Medicine, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada
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19
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Li Y, Zhang Z, Jiang S, Xu F, Tulum L, Li K, Liu S, Li S, Chang L, Liddell M, Tu F, Gu X, Carmichael PL, White A, Peng S, Zhang Q, Li J, Zuo T, Kukic P, Xu P. Using transcriptomics, proteomics and phosphoproteomics as new approach methodology (NAM) to define biological responses for chemical safety assessment. CHEMOSPHERE 2023; 313:137359. [PMID: 36427571 DOI: 10.1016/j.chemosphere.2022.137359] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 11/19/2022] [Accepted: 11/21/2022] [Indexed: 06/16/2023]
Abstract
Omic-based technologies are of particular interest and importance for hazard identification and health risk characterization of chemicals. Their application in the new approach methodologies (NAMs) anchored on cellular toxicity pathways is based on the premise that any apical health endpoint change must be underpinned by some alterations at the omic levels. In the present study we examined the cellular responses to two chemicals, caffeine and coumarin, by generating and integrating multi-omic data from multi-dose and multi-time point transcriptomic, proteomic and phosphoproteomic experiments. We showed that the methodology presented here was able to capture the complete chain of events from the first chemical-induced changes at the phosphoproteome level, to changes in gene expression, and lastly to changes in protein abundance, each with vastly different points of departure (PODs). In HepG2 cells we found that the metabolism of lipids and general cellular stress response to be the dominant biological processes in response to caffeine and coumarin exposure, respectively. The phosphoproteomic changes were detected early in time, at very low doses and provided a fast, adaptive cellular response to chemical exposure with 7-37-fold lower points of departure comparing to the transcriptomics. Changes in protein abundance were found much less frequently than transcriptomic changes. While challenges remain, our study provides strong and novel evidence supporting the notion that these three omic technologies can be used in an integrated manner to facilitate a more complete understanding of pathway perturbations and POD determinations for risk assessment of chemical exposures.
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Affiliation(s)
- Yuan Li
- Department of Biomedicine, Medical College, Guizhou University, Guiyang, 550025, China; State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Zhenpeng Zhang
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Songhao Jiang
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China; Hebei Province Key Lab of Research and Application on Microbial Diversity, College of Life Sciences, Hebei University, Baoding, 071002, China
| | - Feng Xu
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Liz Tulum
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK
| | - Kaixuan Li
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Shu Liu
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Suzhen Li
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Lei Chang
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China
| | - Mark Liddell
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK
| | - Fengjuan Tu
- Unilever Research & Development Centre Shanghai, Shanghai, 200335, China
| | - Xuelan Gu
- Unilever Research & Development Centre Shanghai, Shanghai, 200335, China
| | - Paul Lawford Carmichael
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK
| | - Andrew White
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK
| | - Shuangqing Peng
- Evaluation and Research Centre for Toxicology, Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, 100071, China
| | - Qiang Zhang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | - Jin Li
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK
| | - Tao Zuo
- State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China.
| | - Predrag Kukic
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK.
| | - Ping Xu
- Department of Biomedicine, Medical College, Guizhou University, Guiyang, 550025, China; State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Beijing Proteome Research Center, Institute of Lifeomics, Beijing, 102206, China; Hebei Province Key Lab of Research and Application on Microbial Diversity, College of Life Sciences, Hebei University, Baoding, 071002, China; Program of Environmental Toxicology, School of Public Health, China Medical University, Shenyang, 110122, China.
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20
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Morash MG, Kirzinger MW, Achenbach JC, Venkatachalam AB, Cooper JP, Ratzlaff DE, Woodland CLA, Ellis LD. The contribution of larval zebrafish transcriptomics to chemical risk assessment. Regul Toxicol Pharmacol 2023; 138:105336. [PMID: 36642323 DOI: 10.1016/j.yrtph.2023.105336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/22/2022] [Accepted: 01/10/2023] [Indexed: 01/15/2023]
Abstract
In Canada, the Canadian Environmental Protection Act (1999) requires human health and environmental risk assessments be conducted for new substances prior to their manufacture or import. While this toxicity data is historically obtained using rodents, in response to the international effort to eliminate animal testing, Health Canada is collaborating with the National Research Council (NRC) of Canada to develop a New Approach Method by refining existing NRC zebrafish models. The embryo/larval zebrafish model evaluates systemic (whole body) general toxicity which is currently unachievable with cell-based testing. The model is strengthened using behavioral, toxicokinetic and transcriptomic responses to assess non-visible indicators of toxicity following chemical exposure at sub-phenotypic concentrations. In this paper, the predictive power of zebrafish transcriptomics is demonstrated using two chemicals; Raloxifene and Resorcinol. Raloxifene exposure produced darkening of the liver and malformation of the nose/mandible, while Resorcinol exposure produced increased locomotor activity. Transcriptomic analysis correlated differentially expressed genes with the phenotypic effects and benchmark dose calculations determined that the transcriptomic Point of Departure (POD) occurred at subphenotypic concentrations. Correlating gene expression with apical (phenotypic) effects strengthens confidence in evaluation of chemical toxicity, thereby demonstrating the significant advancement that the larval zebrafish transcriptomics model represents in chemical risk assessment.
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Affiliation(s)
- Michael G Morash
- Aquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, Canada.
| | - Morgan W Kirzinger
- Aquatic and Crop Resource Development, National Research Council of Canada, Saskatoon, SK S7N 0W9, Canada.
| | - J C Achenbach
- Aquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, Canada.
| | - Ananda B Venkatachalam
- Aquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, Canada.
| | | | - Deborah E Ratzlaff
- New Substances Assessment Control Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada.
| | - Cindy L A Woodland
- New Substances Assessment Control Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada.
| | - Lee D Ellis
- Aquatic and Crop Resource Development, National Research Council of Canada, Halifax, NS B3H 3Z1, Canada.
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21
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Fortin AMV, Long AS, Williams A, Meier MJ, Cox J, Pinsonnault C, Yauk CL, White PA. Application of a new approach methodology (NAM)-based strategy for genotoxicity assessment of data-poor compounds. FRONTIERS IN TOXICOLOGY 2023; 5:1098432. [PMID: 36756349 PMCID: PMC9899896 DOI: 10.3389/ftox.2023.1098432] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 01/02/2023] [Indexed: 01/24/2023] Open
Abstract
The conventional battery for genotoxicity testing is not well suited to assessing the large number of chemicals needing evaluation. Traditional in vitro tests lack throughput, provide little mechanistic information, and have poor specificity in predicting in vivo genotoxicity. New Approach Methodologies (NAMs) aim to accelerate the pace of hazard assessment and reduce reliance on in vivo tests that are time-consuming and resource-intensive. As such, high-throughput transcriptomic and flow cytometry-based assays have been developed for modernized in vitro genotoxicity assessment. This includes: the TGx-DDI transcriptomic biomarker (i.e., 64-gene expression signature to identify DNA damage-inducing (DDI) substances), the MicroFlow® assay (i.e., a flow cytometry-based micronucleus (MN) test), and the MultiFlow® assay (i.e., a multiplexed flow cytometry-based reporter assay that yields mode of action (MoA) information). The objective of this study was to investigate the utility of the TGx-DDI transcriptomic biomarker, multiplexed with the MicroFlow® and MultiFlow® assays, as an integrated NAM-based testing strategy for screening data-poor compounds prioritized by Health Canada's New Substances Assessment and Control Bureau. Human lymphoblastoid TK6 cells were exposed to 3 control and 10 data-poor substances, using a 6-point concentration range. Gene expression profiling was conducted using the targeted TempO-Seq™ assay, and the TGx-DDI classifier was applied to the dataset. Classifications were compared with those based on the MicroFlow® and MultiFlow® assays. Benchmark Concentration (BMC) modeling was used for potency ranking. The results of the integrated hazard calls indicate that five of the data-poor compounds were genotoxic in vitro, causing DNA damage via a clastogenic MoA, and one via a pan-genotoxic MoA. Two compounds were likely irrelevant positives in the MN test; two are considered possibly genotoxic causing DNA damage via an ambiguous MoA. BMC modeling revealed nearly identical potency rankings for each assay. This ranking was maintained when all endpoint BMCs were converted into a single score using the Toxicological Prioritization (ToxPi) approach. Overall, this study contributes to the establishment of a modernized approach for effective genotoxicity assessment and chemical prioritization for further regulatory scrutiny. We conclude that the integration of TGx-DDI, MicroFlow®, and MultiFlow® endpoints is an effective NAM-based strategy for genotoxicity assessment of data-poor compounds.
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Affiliation(s)
- Anne-Marie V. Fortin
- Department of Biology, University of Ottawa, Ottawa, ON, Canada,Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Alexandra S. Long
- Existing Substances Risk Assessment Bureau, Health Canada, Ottawa, ON, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Matthew J. Meier
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Julie Cox
- Bureau of Gastroenterology, Infection and Viral Diseases, Health Canada, Ottawa, ON, Canada
| | - Claire Pinsonnault
- New Substances Assessment and Control Bureau, Health Canada, Ottawa, ON, Canada
| | - Carole L. Yauk
- Department of Biology, University of Ottawa, Ottawa, ON, Canada,*Correspondence: Carole L. Yauk, ; Paul A. White,
| | - Paul A. White
- Department of Biology, University of Ottawa, Ottawa, ON, Canada,Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada,*Correspondence: Carole L. Yauk, ; Paul A. White,
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22
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Derivation of metabolic point of departure using high-throughput in vitro metabolomics: investigating the importance of sampling time points on benchmark concentration values in the HepaRG cell line. Arch Toxicol 2023; 97:721-735. [PMID: 36683062 PMCID: PMC9968698 DOI: 10.1007/s00204-022-03439-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 12/21/2022] [Indexed: 01/23/2023]
Abstract
Amongst omics technologies, metabolomics should have particular value in regulatory toxicology as the measurement of the molecular phenotype is the closest to traditional apical endpoints, whilst offering mechanistic insights into the biological perturbations. Despite this, the application of untargeted metabolomics for point-of-departure (POD) derivation via benchmark concentration (BMC) modelling is still a relatively unexplored area. In this study, a high-throughput workflow was applied to derive PODs associated with a chemical exposure by measuring the intracellular metabolome of the HepaRG cell line following treatment with one of four chemicals (aflatoxin B1, benzo[a]pyrene, cyclosporin A, or rotenone), each at seven concentrations (aflatoxin B1, benzo[a]pyrene, cyclosporin A: from 0.2048 μM to 50 μM; rotenone: from 0.04096 to 10 μM) and five sampling time points (2, 6, 12, 24 and 48 h). The study explored three approaches to derive PODs using benchmark concentration modelling applied to single features in the metabolomics datasets or annotated metabolites or lipids: (1) the 1st rank-ordered unannotated feature, (2) the 1st rank-ordered putatively annotated feature (using a recently developed HepaRG-specific library of polar metabolites and lipids), and (3) 25th rank-ordered feature, demonstrating that for three out of four chemical datasets all of these approaches led to relatively consistent BMC values, varying less than tenfold across the methods. In addition, using the 1st rank-ordered unannotated feature it was possible to investigate temporal trends in the datasets, which were shown to be chemical specific. Furthermore, a possible integration of metabolomics-driven POD derivation with the liver steatosis adverse outcome pathway (AOP) was demonstrated. The study highlights that advances in technologies enable application of in vitro metabolomics at scale; however, greater confidence in metabolite identification is required to ensure PODs are mechanistically anchored.
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23
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Lambert JC. Adverse Outcome Pathway 'Footprinting': A Novel Approach to the Integration of 21st Century Toxicology Information into Chemical Mixtures Risk Assessment. TOXICS 2022; 11:37. [PMID: 36668763 PMCID: PMC9860797 DOI: 10.3390/toxics11010037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/23/2022] [Accepted: 12/28/2022] [Indexed: 06/17/2023]
Abstract
For over a decade, New Approach Methodologies (NAMs) such as structure-activity/read-across, -omics technologies, and Adverse Outcome Pathway (AOP), have been considered within regulatory communities as alternative sources of chemical and biological information potentially relevant to human health risk assessment. Integration of NAMs into applications such as chemical mixtures risk assessment has been limited due to the lack of validation of qualitative and quantitative application to adverse health outcomes in vivo, and acceptance by risk assessors. However, leveraging existent hazard and dose-response information, including NAM-based data, for mixture component chemicals across one or more levels of biological organization using novel approaches such as AOP 'footprinting' proposed herein, may significantly advance mixtures risk assessment. AOP footprinting entails the systematic stepwise profiling and comparison of all known or suspected AOPs involved in a toxicological effect at the level of key event (KE). The goal is to identify key event(s) most proximal to an adverse outcome within each AOP suspected of contributing to a given health outcome at which similarity between mixture chemicals can be confidently determined. These key events are identified as the 'footprint' for a given AOP. This work presents the general concept, and a hypothetical example application, of AOP footprinting as a key methodology for the integration of NAM data into mixtures risk assessment.
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Affiliation(s)
- Jason C Lambert
- United States Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Cincinnati, OH 45268, USA
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24
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Villeneuve DL, Le M, Hazemi M, Biales A, Bencic DC, Bush K, Flick R, Martinson J, Morshead M, Rodriguez KS, Vitense K, Flynn K. Pilot testing and optimization of a larval fathead minnow high throughput transcriptomics assay. Curr Res Toxicol 2022; 4:100099. [PMID: 36619288 PMCID: PMC9816907 DOI: 10.1016/j.crtox.2022.100099] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 11/03/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022] Open
Abstract
Concentrations at which global gene expression profiles in cells or animals exposed to a test substance start to differ significantly from those of controls have been proposed as an alternative point of departure for use in screening level hazard assessment. The present study describes pilot testing of a high throughput compatible transcriptomics assay with larval fathead minnows. One day post hatch fathead minnows were exposed to eleven different concentrations of three metals, three selective serotonin reuptake inhibitors, and four neonicotinoid-like compounds for 24 h and concentration response modeling was applied to whole body gene expression data. Transcriptomics-based points of departure (tPODs) were consistently lower than effect concentrations reported in apical endpoint studies in fish. However, larval fathead minnow-based tPODs were not always lower than concentrations reported to elicit apical toxicity in other aquatic organisms like crustaceans or insects. Random in silico subsampling of data from the pilot assays was used to evaluate various assay design and acceptance considerations such as transcriptome coverage, number of replicate individuals to sequence per treatment, and minimum number of differentially expressed genes to produce a reliable tPOD estimate. Results showed a strong association between the total number of genes for which a concentration response relationship could be derived and the overall variability in the resulting tPOD estimates. We conclude that, for our current assay design and analysis pipeline, tPODs based on fewer than 15 differentially expressed genes are likely to be unreliable for screening and that interindividual variability in gene expression profiles appears to be a more significant driver of tPOD variability than sample size alone. Results represent initial steps toward developing high throughput transcriptomics assays for use in ecological hazard screening.
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Key Words
- BMD, Benchmark dose
- Benchmark dose
- Computational toxicology
- DEGs, Differentially expressed genes
- ECOTOX knowledgebase
- Fish
- HTTr, High throughput transcriptomics
- RIN, RNA integrity number
- RNA sequencing
- RNAseq, RNA sequencing
- SSRI, Selective serotonin reuptake inhibitor
- ToxCast, US EPA Toxicity Forecaster
- Transcriptomics-based point of departure
- cDNA, Complementary DNA
- eco-HTTr, Ecological high throughput transcriptomics
- tPOD, Transcriptomics-based point of departure
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Affiliation(s)
- Daniel L. Villeneuve
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, MN 55804, USA,Corresponding author at: U.S. EPA Great Lakes Toxicology and Ecology Division, 6201 Congdon Blvd., Duluth, MN 55804-2595, USA.
| | - Michelle Le
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, US Environmental Protection Agency Great Lakes Toxicology and Ecology Division, Duluth, MN 55804, USA
| | - Monique Hazemi
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, US Environmental Protection Agency Great Lakes Toxicology and Ecology Division, Duluth, MN 55804, USA
| | - Adam Biales
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Cincinnati, OH 45220, USA
| | - David C. Bencic
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Cincinnati, OH 45220, USA
| | - Kendra Bush
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, US Environmental Protection Agency Great Lakes Toxicology and Ecology Division, Duluth, MN 55804, USA
| | - Robert Flick
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Cincinnati, OH 45220, USA
| | - John Martinson
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Cincinnati, OH 45220, USA
| | - Mackenzie Morshead
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, US Environmental Protection Agency Great Lakes Toxicology and Ecology Division, Duluth, MN 55804, USA
| | - Kelvin Santana Rodriguez
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, US Environmental Protection Agency Great Lakes Toxicology and Ecology Division, Duluth, MN 55804, USA
| | - Kelsey Vitense
- US Environmental Protection Agency, Scientific Computing and Data Curation Division, Duluth, MN 55804, USA
| | - Kevin Flynn
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, MN 55804, USA
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25
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Ewald JD, Basu N, Crump D, Boulanger E, Head J. Characterizing Variability and Uncertainty Associated with Transcriptomic Dose-Response Modeling. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:15960-15968. [PMID: 36268973 DOI: 10.1021/acs.est.2c04665] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Transcriptomics dose-response analysis (TDRA) has emerged as a promising approach for integrating toxicogenomics data into a risk assessment context; however, variability and uncertainty associated with experimental design are not well understood. Here, we evaluated n = 55 RNA-seq profiles derived from Japanese quail liver tissue following exposure to chlorpyrifos (0, 0.04, 0.1, 0.2, 0.4, 1, 2, 4, 10, 20, and 40 μg/g; n = 5 replicates per group) via egg injection. The full dataset was subsampled 637 times to generate smaller datasets with different dose ranges and spacing (designs A-E) and number of replicates (n = 2-5). TDRA of the 637 datasets revealed substantial variability in the gene and pathway benchmark doses, but relative stability in overall transcriptomic point-of-departure (tPOD) values when tPODs were calculated with the "pathway" and "mode" methods. Further, we found that tPOD values were more dependent on the dose range and spacing than on the number of replicates, suggesting that optimal experimental designs should use fewer replicates (n = 2 or 3) and more dose groups to reduce uncertainty in the results. Finally, tPOD values ranged by over ten times for all surveyed experimental designs and tPOD types, suggesting that tPODs should be interpreted as order-of-magnitude estimates.
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Affiliation(s)
- Jessica D Ewald
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue H9X 3V9, Canada
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue H9X 3V9, Canada
| | - Doug Crump
- Ecotoxicology and Wildlife Health Division, National Wildlife Research Centre, Environment and Climate Change Canada, Ottawa K1A 0H3, Canada
| | - Emily Boulanger
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue H9X 3V9, Canada
| | - Jessica Head
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue H9X 3V9, Canada
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26
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Adam N, Vuong NQ, Adams H, Kuo B, Beheshti A, Yauk C, Wilkins R, Chauhan V. Evaluating the Influences of Confounding Variables on Benchmark Dose using a Case Study in the Field of Ionizing Radiation. Int J Radiat Biol 2022; 98:1845-1855. [PMID: 35939396 DOI: 10.1080/09553002.2022.2110303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Purpose A vast amount of data regarding the effects of radiation stressors on transcriptional changes has been produced over the past few decades. These data have shown remarkable consistency across platforms and experimental design, enabling increased understanding of early molecular effects of radiation exposure. However, the value of transcriptomic data in the context of risk assessment is not clear and represents a gap that is worthy of further consideration. Recently, benchmark dose (BMD) modeling has shown promise in correlating a transcriptional point of departure (POD) to that derived using phenotypic outcomes relevant to human health risk assessment. Although frequently applied in chemical toxicity evaluation, our group has recently demonstrated application within the field of radiation research. This approach allows the possibility to quantitatively compare radiation-induced gene and pathway alterations across various datasets using BMD values and derive meaningful biological effects. However, before BMD modeling can confidently be used, an understanding of the impact of confounding variables on BMD outputs is needed. Methods: To this end, BMD modeling was applied to a publicly available microarray dataset (Gene Expression Omnibus #GSE23515) that used peripheral blood ex-vivo gamma-irradiated at 0.82 Gy/min, at doses of 0, 0.1, 0.5 or 2 Gy, and assessed 6 hours post-exposure. The dataset comprised six female smokers (F-S), six female non-smokers (F-NS), six male smokers (M-S), and six male non-smokers (M-NS). Results: A combined total of 412 genes were fit to models and the BMD distribution was noted to be bi-modal across the four groups. A total of 74, 41, 62 and 62 genes were unique to the F-NS, M-NS, F-S and M-S groups. Sixty-two BMD modeled genes and nine pathways were common across all four groups. There were no differential sensitivity of responses in the robust common genes and pathways. Conclusion: For radiation-responsive genes and pathways common across the study groups, the BMD distribution of transcriptional activity was unaltered by sex and smoking status. Although further validation of the data is needed, these initial findings suggest BMD values for radiation relevant genes and pathways are robust and could be explored further in future studies.
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Affiliation(s)
- Nadine Adam
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Ngoc Q Vuong
- Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Hailey Adams
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Byron Kuo
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Afshin Beheshti
- KBR, Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, 94035, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Carole Yauk
- University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
| | - Ruth Wilkins
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Vinita Chauhan
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
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27
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Middleton AM, Reynolds J, Cable S, Baltazar MT, Li H, Beven S, Carmichael PL, Dent MP, Hatherell S, Houghton J, Kukic P, Liddell M, Malcomber S, Nicol B, Park B, Patel H, Scott S, Sparham C, Walker P, White A. Are non-animal systemic safety assessments protective? A toolbox and workflow. Toxicol Sci 2022; 189:124-147. [PMID: 35822611 PMCID: PMC9412174 DOI: 10.1093/toxsci/kfac068] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
An important question in toxicological risk assessment is whether non-animal new approach methodologies (NAMs) can be used to make safety decisions that are protective of human health, without being overly conservative. In this work, we propose a core NAM toolbox and workflow for conducting systemic safety assessments for adult consumers. We also present an approach for evaluating how protective and useful the toolbox and workflow are by benchmarking against historical safety decisions. The toolbox includes physiologically based kinetic (PBK) models to estimate systemic Cmax levels in humans, and 3 bioactivity platforms, comprising high-throughput transcriptomics, a cell stress panel, and in vitro pharmacological profiling, from which points of departure are estimated. A Bayesian model was developed to quantify the uncertainty in the Cmax estimates depending on how the PBK models were parameterized. The feasibility of the evaluation approach was tested using 24 exposure scenarios from 10 chemicals, some of which would be considered high risk from a consumer goods perspective (eg, drugs that are systemically bioactive) and some low risk (eg, existing food or cosmetic ingredients). Using novel protectiveness and utility metrics, it was shown that up to 69% (9/13) of the low risk scenarios could be identified as such using the toolbox, whilst being protective against all (5/5) the high-risk ones. The results demonstrated how robust safety decisions could be made without using animal data. This work will enable a full evaluation to assess how protective and useful the toolbox and workflow are across a broader range of chemical-exposure scenarios.
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Affiliation(s)
- Alistair M Middleton
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Joe Reynolds
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Sophie Cable
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Maria Teresa Baltazar
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Hequn Li
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Samantha Beven
- Discovery Services, Charles River, Chesterford Research Park, CB10 1XL, United Kingdom
| | - Paul L Carmichael
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Matthew Philip Dent
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Sarah Hatherell
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Jade Houghton
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Predrag Kukic
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Mark Liddell
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Sophie Malcomber
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Beate Nicol
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Benjamin Park
- Discovery Services, Charles River, Chesterford Research Park, CB10 1XL, United Kingdom
| | - Hiral Patel
- Cyprotex Discovery Ltd, No. 24 Mereside, Alderley Park, Macclesfield, Cheshire, SK10 4TG, United Kingdom
| | - Sharon Scott
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Chris Sparham
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Paul Walker
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
| | - Andrew White
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, United Kingdom
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28
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Long Q, Feng L, Li Y, Zuo T, Chang L, Zhang Z, Xu P. Time-resolved quantitative phosphoproteomics reveals cellular responses induced by caffeine and coumarin. Toxicol Appl Pharmacol 2022; 449:116115. [PMID: 35691368 DOI: 10.1016/j.taap.2022.116115] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 05/27/2022] [Accepted: 06/06/2022] [Indexed: 11/30/2022]
Abstract
Protein phosphorylation is a critical way that cells respond to external signals and environmental stresses. However, the patterns of cellular response to chemicals at different times were largely unknown. Here, we used quantitative phosphoproteomics to analyze the cellular response of kinases and signaling pathways, as well as pattern change of phosphorylated substrates in HepG2 cells that were exposed to caffeine and coumarin for 10 min and 24 h. Comparing the 10 min and 24 h groups, 33 kinases were co-responded and 32 signaling pathways were co-enriched in caffeine treated samples, while 48 kinases and 34 signaling pathways were co-identified in coumarin treated samples. Instead, the percentage of co-identified phosphorylated substrates only accounted for 4.31% and 9.57% between 10 min and 24 h in caffeine and coumarin treated samples, respectively. The results showed that specific chemical exposure led to a bunch of the same kinases and signaling pathways changed in HepG2 cells, while the phosphorylated substrates were different. In addition, it was found that insulin signaling pathway was significantly enriched by both the caffeine and coumarin treatment. The pattern changes in phosphorylation of protein substrates, kinases and signaling pathways with varied chemicals and different time course shed light on the potential mechanism of cellular responses to endless chemical stimulation.
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Affiliation(s)
- Qi Long
- School of Basic Medicine, Anhui Medical University, Hefei 230032, China; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Institute of Lifeomics, Beijing 102206, China
| | - Lijie Feng
- School of Basic Medicine, Anhui Medical University, Hefei 230032, China
| | - Yuan Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Institute of Lifeomics, Beijing 102206, China; School of Medicine, Guizhou University, Guiyang 550025, China
| | - Tao Zuo
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Institute of Lifeomics, Beijing 102206, China
| | - Lei Chang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Institute of Lifeomics, Beijing 102206, China
| | - Zhenpeng Zhang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Institute of Lifeomics, Beijing 102206, China.
| | - Ping Xu
- School of Basic Medicine, Anhui Medical University, Hefei 230032, China; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Institute of Lifeomics, Beijing 102206, China; School of Medicine, Guizhou University, Guiyang 550025, China; School of Public Health, China Medical University, Shenyang 110122, China; Hebei Province Key Lab of Research and Application on Microbial Diversity, College of Life Sciences, Hebei University, Baoding 071002, China.
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29
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Assessing the neurotoxicity of airborne nano-scale particulate matter in human iPSC-derived neurons using a transcriptomics benchmark dose model. Toxicol Appl Pharmacol 2022; 449:116109. [DOI: 10.1016/j.taap.2022.116109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 05/26/2022] [Accepted: 06/02/2022] [Indexed: 11/23/2022]
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30
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Johnson KJ, Costa E, Marshall V, Sriram S, Venkatraman A, Stebbins K, LaRocca J. A microRNA or messenger RNA point of departure estimates an apical endpoint point of departure in a rat developmental toxicity model. Birth Defects Res 2022; 114:559-576. [PMID: 35596682 PMCID: PMC9324934 DOI: 10.1002/bdr2.2046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/02/2022] [Accepted: 05/04/2022] [Indexed: 11/10/2022]
Abstract
Traditional developmental toxicity testing practice examines fetal apical endpoints to identify a point of departure (POD) for risk assessment. A potential new testing paradigm involves deriving a POD from a comprehensive analysis of molecular-level change. Here, the rat ketoconazole endocrine-mediated developmental toxicity model was used to test the hypothesis that maternal epigenomic (miRNA) and transcriptomic (mRNA) PODs are similar to fetal apical endpoint PODs. Sprague-Dawley rats were exposed from gestation day (GD) 6-21 to 0, 0.063, 0.2, 0.63, 2, 6.3, 20, or 40 mg/kg/day ketoconazole. Dam systemic, liver, and placenta PODs, along with GD 21 fetal resorption, body weight, and skeletal apical PODs were derived using BMDS software. GD 21 dam liver and placenta miRNA and mRNA PODs were obtained using three methods: a novel individual molecule POD accumulation method, a first mode method, and a gene set method. Dam apical POD values ranged from 2.0 to 38.6 mg/kg/day; the lowest value was for placenta histopathology. Fetal apical POD values were 10.9-20.3 mg/kg/day; the lowest value was for fetal resorption. Dam liver miRNA and mRNA POD values were 0.34-0.69 mg/kg/day, and placenta miRNA and mRNA POD values were 2.53-6.83 mg/kg/day. Epigenomic and transcriptomic POD values were similar across liver and placenta. Deriving a molecular POD from dam liver or placenta was protective of a fetal apical POD. These data support the conclusion that a molecular POD can be used to estimate, or be protective of, a developmental toxicity apical POD.
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Affiliation(s)
| | | | - Valerie Marshall
- Labcorp Early Development Laboratories, Inc., Greenfield, Indiana, USA
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31
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Case study: Targeted RNA-sequencing of aged formalin-fixed paraffin-embedded samples for understanding chemical mode of action. Toxicol Rep 2022; 9:883-894. [DOI: 10.1016/j.toxrep.2022.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 04/12/2022] [Accepted: 04/13/2022] [Indexed: 11/19/2022] Open
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32
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Hoer D, Barton HA, Paini A, Bartels M, Ingle B, Domoradzki J, Fisher J, Embry M, Villanueva P, Miller D, Nguyen J, Zhang Q, Edwards SW, Tan YM. Predicting nonlinear relationships between external and internal concentrations with physiologically based pharmacokinetic modeling. Toxicol Appl Pharmacol 2022; 440:115922. [PMID: 35176293 PMCID: PMC10519136 DOI: 10.1016/j.taap.2022.115922] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/19/2022] [Accepted: 02/10/2022] [Indexed: 11/20/2022]
Abstract
Although external concentrations are more readily quantified and often used as the metric for regulating and mitigating exposures to environmental chemicals, the toxicological response to an environmental chemical is more directly related to its internal concentrations than the external concentration. The processes of absorption, distribution, metabolism, and excretion (ADME) determine the quantitative relationship between the external and internal concentrations, and these processes are often susceptible to saturation at high concentrations, which can lead to nonlinear changes in internal concentrations that deviate from proportionality. Using generic physiologically-based pharmacokinetic (PBPK) models, we explored how saturable absorption or clearance influence the shape of the internal to external concentration (IEC) relationship. We used the models for hypothetical chemicals to show how differences in kinetic parameters can impact the shape of an IEC relationship; and models for styrene and caffeine to explore how exposure route, frequency, and duration impact the IEC relationships in rat and human exposures. We also analyzed available plasma concentration data for 2,4-dichlorophenoxyacetic acid to demonstrate how a PBPK modeling approach can be an alternative to common statistical methods for analyzing dose proportionality. A PBPK modeling approach can be a valuable tool used in the early stages of a chemical safety assessment program to optimize the design of longer-term animal toxicity studies or to interpret study results.
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Affiliation(s)
- Daniel Hoer
- U.S. Environmental Protection Agency, Office of Pesticide Programs, Durham, NC, USA
| | | | - Alicia Paini
- European Commission, Joint Research Centre, Ispra, Italy.
| | | | - Brandall Ingle
- U.S. Environmental Protection Agency, Office of Pesticide Programs, Durham, NC, USA
| | | | | | - Michelle Embry
- Health and Environmental Sciences Institute, Washington, DC, USA
| | - Philip Villanueva
- U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA
| | - David Miller
- U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA
| | - James Nguyen
- U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA
| | - Qiang Zhang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | | | - Yu-Mei Tan
- U.S. Environmental Protection Agency, Office of Pesticide Programs, Durham, NC, USA.
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33
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Basili D, Reynolds J, Houghton J, Malcomber S, Chambers B, Liddell M, Muller I, White A, Shah I, Everett LJ, Middleton A, Bender A. Latent Variables Capture Pathway-Level Points of Departure in High-Throughput Toxicogenomic Data. Chem Res Toxicol 2022; 35:670-683. [PMID: 35333521 PMCID: PMC9019810 DOI: 10.1021/acs.chemrestox.1c00444] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
![]()
Estimation
of points of departure (PoDs) from high-throughput transcriptomic
data (HTTr) represents a key step in the development of next-generation
risk assessment (NGRA). Current approaches mainly rely on single key
gene targets, which are constrained by the information currently available
in the knowledge base and make interpretation challenging as scientists
need to interpret PoDs for thousands of genes or hundreds of pathways.
In this work, we aimed to address these issues by developing a computational
workflow to investigate the pathway concentration–response
relationships in a way that is not fully constrained by known biology
and also facilitates interpretation. We employed the Pathway-Level
Information ExtractoR (PLIER) to identify latent variables (LVs) describing
biological activity and then investigated in vitro LVs’ concentration–response
relationships using the ToxCast pipeline. We applied this methodology
to a published transcriptomic concentration–response data set
for 44 chemicals in MCF-7 cells and showed that our workflow can capture
known biological activity and discriminate between estrogenic and
antiestrogenic compounds as well as activity not aligning with the
existing knowledge base, which may be relevant in a risk assessment
scenario. Moreover, we were able to identify the known estrogen activity
in compounds that are not well-established ER agonists/antagonists
supporting the use of the workflow in read-across. Next, we transferred
its application to chemical compounds tested in HepG2, HepaRG, and
MCF-7 cells and showed that PoD estimates are in strong agreement
with those estimated using a recently developed Bayesian approach
(cor = 0.89) and in weak agreement with those estimated using a well-established
approach such as BMDExpress2 (cor = 0.57). These results demonstrate
the effectiveness of using PLIER in a concentration–response
scenario to investigate pathway activity in a way that is not fully
constrained by the knowledge base and to ease the biological interpretation
and support the development of an NGRA framework with the ability
to improve current risk assessment strategies for chemicals using
new approach methodologies.
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Affiliation(s)
- Danilo Basili
- Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, U.K.,Unilever, Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Joe Reynolds
- Unilever, Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Jade Houghton
- Unilever, Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Sophie Malcomber
- Unilever, Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Bryant Chambers
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States
| | - Mark Liddell
- Unilever, Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Iris Muller
- Unilever, Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Andrew White
- Unilever, Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Imran Shah
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States
| | - Logan J Everett
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States
| | - Alistair Middleton
- Unilever, Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Andreas Bender
- Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, U.K
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34
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Yamada T, Lake BG, Cohen SM. Evaluation of the human hazard of the liver and lung tumors in mice treated with permethrin based on mode of action. Crit Rev Toxicol 2022; 52:1-31. [PMID: 35275035 DOI: 10.1080/10408444.2022.2035316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
The non-genotoxic synthetic pyrethroid insecticide permethrin produced hepatocellular adenomas and bronchiolo-alveolar adenomas in female CD-1 mice, but not in male CD-1 mice or in female or male Wistar rats. Studies were performed to evaluate possible modes of action (MOAs) for permethrin-induced female CD-1 mouse liver and lung tumor formation. The MOA for liver tumor formation by permethrin involves activation of the peroxisome proliferator-activated receptor alpha (PPARα), increased hepatocellular proliferation, development of altered hepatic foci, and ultimately liver tumors. This MOA is similar to that established for other PPARα activators and is considered to be qualitatively not plausible for humans. The MOA for lung tumor formation by permethrin involves interaction with Club cells, followed by a mitogenic effect resulting in Club cell proliferation, with prolonged administration producing Club cell hyperplasia and subsequently formation of bronchiolo-alveolar adenomas. Although the possibility that permethrin exposure may potentially result in enhancement of Club cell proliferation in humans cannot be completely excluded, there is sufficient information on differences in basic lung anatomy, physiology, metabolism, and biologic behavior of tumors in the general literature to conclude that humans are quantitatively less sensitive to agents that increase Club cell proliferation and lead to tumor formation in mice. The evidence strongly indicates that Club cell mitogens are not likely to lead to increased susceptibility to lung tumor development in humans. Overall, based on MOA evaluation it is concluded that permethrin does not pose a tumorigenic hazard for humans, this conclusion being supported by negative data from permethrin epidemiological studies.
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Affiliation(s)
- Tomoya Yamada
- Environmental Health Science Laboratory, Sumitomo Chemical Company, Ltd., Osaka, Japan
| | - Brian G Lake
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Samuel M Cohen
- Department of Pathology and Microbiology, Havlik-Wall Professor of Oncology, University of Nebraska Medical Center, 983135 Nebraska Medical Center, Omaha, NE, USA
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35
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Hewitt NJ, Troutman J, Przibilla J, Schepky A, Ouédraogo G, Mahony C, Kenna G, Varçin M, Dent MP. Use of in vitro metabolism and biokinetics assays to refine predicted in vivo and in vitro internal exposure to the cosmetic ingredient, phenoxyethanol, for use in risk assessment. Regul Toxicol Pharmacol 2022; 131:105132. [PMID: 35217105 DOI: 10.1016/j.yrtph.2022.105132] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 12/20/2021] [Accepted: 01/31/2022] [Indexed: 01/04/2023]
Abstract
A novel approach was developed to help characterize the biokinetics of the cosmetic ingredient, phenoxyethanol, to help assess the safety of the parent and its major stable metabolite. In the first step of this non-animal tiered approach, primary human hepatocytes were used to confirm or refute in silico predicted metabolites, and elucidate the intrinsic clearance of phenoxyethanol. A key result was the identification of the major metabolite, phenoxyacetic acid (PAA), the exposure to which in the kidney was subsequently predicted to far exceed that of phenoxyethanol in blood or other tissues. Therefore, a novel aspect of this approach was to measure in the subsequent step the formation of PAA in the cells dosed with phenoxyethanol that were used to provide points of departure (PoDs) and express the intracellular exposure as the Cmax and AUC24. This enabled the calculation of the intracellular concentrations of parent and metabolite at the PoD in the cells used to derive this value. These concentrations can be compared with in vivo tissue levels to conclude on the safety margin. The lessons from this case study will help to inform the design of other non-animal safety assessments.
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Affiliation(s)
- Nicola J Hewitt
- Cosmetics Europe, Avenue Herrmann-Debroux 40, 1160, Auderghem, Belgium
| | | | - Julia Przibilla
- Pharmacelsus GmbH, Science Park 2, D-66123, Saarbrücken, Germany
| | | | - Gladys Ouédraogo
- L'Oréal, Research & Innovation, 9 rue Pierre Dreyfus, 92110, Clichy, France
| | | | - Gerry Kenna
- Drug Safety Consultant, 2 Farmfield Drive, Macclesfield, Cheshire, SK10 2TJ, UK
| | - Mustafa Varçin
- Cosmetics Europe, Avenue Herrmann-Debroux 40, 1160, Auderghem, Belgium
| | - Mathew P Dent
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire, MK44 1LQ, UK
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36
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ALOHA: Aggregated local extrema splines for high-throughput dose-response analysis. COMPUTATIONAL TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2022; 21:100196. [PMID: 35083394 PMCID: PMC8785973 DOI: 10.1016/j.comtox.2021.100196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Computational methods for genomic dose-response integrate dose-response modeling with bioinformatics tools to evaluate changes in molecular and cellular functions related to pathogenic processes. These methods use parametric models to describe each gene's dose-response, but such models may not adequately capture expression changes. Additionally, current approaches do not consider gene co-expression networks. When assessing co-expression networks, one typically does not consider the dose-response relationship, resulting in 'co-regulated' gene sets containing genes having different dose-response patterns. To avoid these limitations, we develop an analysis pipeline called Aggregated Local Extrema Splines for High-throughput Analysis (ALOHA), which computes individual genomic dose-response functions using a flexible class Bayesian shape constrained splines and clusters gene co-regulation based upon these fits. Using splines, we reduce information loss due to parametric lack-of-fit issues, and because we cluster on dose-response relationships, we better identify co-regulation clusters for genes that have co-expressed dose-response patterns from chemical exposure. The clustered pathways can then be used to estimate a dose associated with a pre-specified biological response, i.e., the benchmark dose (BMD), and approximate a point of departure dose corresponding to minimal adverse response in the whole tissue/organism. We compare our approach to current parametric methods and our biologically enriched gene sets to cluster on normalized expression data. Using this methodology, we can more effectively extract the underlying structure leading to more cohesive estimates of gene set potency.
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37
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Black MB, Stern A, Efremenko A, Mallick P, Moreau M, Hartman JK, McMullen PD. Biological system considerations for application of toxicogenomics in next-generation risk assessment and predictive toxicology. Toxicol In Vitro 2022; 80:105311. [PMID: 35038564 DOI: 10.1016/j.tiv.2022.105311] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 12/17/2021] [Accepted: 01/10/2022] [Indexed: 10/19/2022]
Abstract
There is increasing interest in using modern 'omics technologies, such as whole transcriptome sequencing, to inform decisions about human health safety and chemical toxicity hazard. High throughput methodologies using in vitro assays offer a path forward in reducing or eliminating animal testing. However, many aspects of these technologies need assessment before they will gain the trust of regulators and the public as viable alternative test methods for human health and safety. We used a high throughput whole transcriptome sequence assay (TempO-Seq) to assess the use of three widely used cancer cell lines (HepG2, MCF7, and Ishikawa cells) as in vitro systems for determination of cellular modes of action for two well studied compounds with canonical liver responses: ketoconazole and phenobarbital. We evaluated transcriptomic data to infer points of departure for use in risk analyses of compounds. Both compounds displayed shortcomings in evidence for canonical liver-related responses in any cell line, despite a strong dose response in all three. This raises questions about the competence of simple, mono-cultured cancer cell lines as appropriate surrogates for some adverse effects or toxic endpoints. Points of departure derived from benchmark doses were highly consistent across all three cell lines however, indicating the use of transcriptomic BMD analyses for such purposes would be a reliable and consistent approach.
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Affiliation(s)
- Michael B Black
- ScitoVation, 100 Capitola Drive, Suite 106, Durham, NC 27713, United States of America.
| | - Allysa Stern
- ScitoVation, 100 Capitola Drive, Suite 106, Durham, NC 27713, United States of America; Cell Microsystems, 801 Capitola Dr., Suite 10, Durham, NC 27713, United States of America
| | - Alina Efremenko
- ScitoVation, 100 Capitola Drive, Suite 106, Durham, NC 27713, United States of America
| | - Pankajini Mallick
- ScitoVation, 100 Capitola Drive, Suite 106, Durham, NC 27713, United States of America
| | - Marjory Moreau
- ScitoVation, 100 Capitola Drive, Suite 106, Durham, NC 27713, United States of America
| | - Jessica K Hartman
- ScitoVation, 100 Capitola Drive, Suite 106, Durham, NC 27713, United States of America; Cell Microsystems, 801 Capitola Dr., Suite 10, Durham, NC 27713, United States of America
| | - Patrick D McMullen
- ScitoVation, 100 Capitola Drive, Suite 106, Durham, NC 27713, United States of America
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38
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Beal MA, Gagne M, Kulkarni SA, Patlewicz G, Thomas RS, Barton-Maclaren TS. Implementing in vitro bioactivity data to modernize priority setting of chemical inventories. ALTEX 2022; 39:123-139. [PMID: 34818430 PMCID: PMC8973434 DOI: 10.14573/altex.2106171] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 11/22/2021] [Indexed: 01/03/2023]
Abstract
Internationally, there are thousands of existing and newly introduced chemicals in commerce, highlighting the ongoing importance of innovative approaches to identify emerging chemicals of concern. For many chemicals, there is a paucity of hazard and exposure data. Thus, there is a crucial need for efficient and robust approaches to address data gaps and support risk-based prioritization. Several studies have demonstrated the utility of in vitro bioactivity data from the ToxCast program in deriving points of departure (PODs). ToxCast contains data for nearly 1,400 endpoints per chemical, and the bioactivity concentrations, indicative of potential adverse outcomes, can be converted to human-equivalent PODs using high-throughput toxicokinetics (HTTK) modeling. However, data gaps need to be addressed for broader application: the limited chemical space of HTTK and quantitative high-throughput screening data. Here we explore the applicability of in silico models to address these data needs. Specifically, we used ADMET predictor for HTTK predictions and a generalized read-across approach to predict ToxCast bioactivity potency. We applied these models to profile 5,801 chemicals on Canada’s Domestic Substances List (DSL). To evaluate the approach’s performance, bioactivity PODs were compared with in vivo results from the EPA Toxicity Values database for 1,042 DSL chemicals. Comparisons demonstrated that the bioactivity PODs, based on ToxCast data or read-across, were conservative for 95% of the chemicals. Comparing bioactivity PODs to human exposure estimates supports the identification of chemicals of potential interest for further work. The bioactivity workflow shows promise as a powerful screening tool to support effective triaging of chemical inventories.
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Affiliation(s)
- Marc A. Beal
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Matthew Gagne
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Sunil A. Kulkarni
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Grace Patlewicz
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Russell S. Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
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39
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Desforges JP, Legrand E, Boulager E, Liu P, Xia J, Butler H, Chandramouli B, Ewald J, Basu N, Hecker M, Head J, Crump D. Using Transcriptomics and Metabolomics to Understand Species Differences in Sensitivity to Chlorpyrifos in Japanese Quail and Double-Crested Cormorant Embryos. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2021; 40:3019-3033. [PMID: 34293216 DOI: 10.1002/etc.5174] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 05/06/2021] [Accepted: 07/16/2021] [Indexed: 06/13/2023]
Abstract
Modern 21st-century toxicity testing makes use of omics technologies to address critical questions in toxicology and chemical management. Of interest are questions relating to chemical mechanisms of toxicity, differences in species sensitivity, and translation of molecular effects to observable apical endpoints. Our study addressed these questions by comparing apical outcomes and multiple omics responses in early-life stage exposure studies with Japanese quail (Coturnix japonica) and double-crested cormorant (Phalacrocorax auritus), representing a model and ecological species, respectively. Specifically, we investigated the dose-dependent response of apical outcomes as well as transcriptomics and metabolomics in the liver of each species exposed to chlorpyrifos, a widely used organophosphate pesticide. Our results revealed a clear pattern of dose-dependent disruption of gene expression and metabolic profiles in Japanese quail but not double-crested cormorant at similar chlorpyrifos exposure concentrations. The difference in sensitivity between species was likely due to higher metabolic transformation of chlorpyrifos in Japanese quail compared to double-crested cormorant. The most impacted biological pathways after chlorpyrifos exposure in Japanese quail included hepatic metabolism, oxidative stress, endocrine disruption (steroid and nonsteroid hormones), and metabolic disease (lipid and fatty acid metabolism). Importantly, we show consistent responses across biological scales, suggesting that significant disruption at the level of gene expression and metabolite profiles leads to observable apical responses at the organism level. Our study demonstrates the utility of evaluating effects at multiple biological levels of organization to understand how modern toxicity testing relates to outcomes of regulatory relevance, while also highlighting important, yet poorly understood, species differences in sensitivity to chemical exposure. Environ Toxicol Chem 2021;40:3019-3033. © 2021 SETAC.
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Affiliation(s)
- Jean-Pierre Desforges
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Elena Legrand
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Emily Boulager
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Peng Liu
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Jianguo Xia
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | | | | | - Jessica Ewald
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Markus Hecker
- Toxicology Centre and School of the Environment and Sustainability, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Jessica Head
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada
| | - Doug Crump
- Ecotoxicology and Wildlife Health Division, Environment Canada, National Wildlife Research Centre, Carleton University, Ottawa, Ontario, Canada
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40
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Reardon AJF, Rowan-Carroll A, Ferguson SS, Leingartner K, Gagne R, Kuo B, Williams A, Lorusso L, Bourdon-Lacombe JA, Carrier R, Moffat I, Yauk CL, Atlas E. Potency Ranking of Per- and Polyfluoroalkyl Substances Using High-Throughput Transcriptomic Analysis of Human Liver Spheroids. Toxicol Sci 2021; 184:154-169. [PMID: 34453843 DOI: 10.1093/toxsci/kfab102] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Per- and polyfluoroalkyl substances (PFAS) are some of the most prominent organic contaminants in human blood. Although the toxicological implications of human exposure to perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) are well established, data on lesser-understood PFAS are limited. New approach methodologies (NAMs) that apply bioinformatic tools to high-throughput data are being increasingly considered to inform risk assessment for data-poor chemicals. The aim of this study was to compare the potencies (ie, benchmark concentrations: BMCs) of PFAS in primary human liver microtissues (3D spheroids) using high-throughput transcriptional profiling. Gene expression changes were measured using TempO-seq, a templated, multiplexed RNA-sequencing platform. Spheroids were exposed for 1 or 10 days to increasing concentrations of 23 PFAS in 3 subgroups: carboxylates (PFCAs), sulfonates (PFSAs), and fluorotelomers and sulfonamides. PFCAs and PFSAs exhibited trends toward increased transcriptional potency with carbon chain-length. Specifically, longer-chain compounds (7-10 carbons) were more likely to induce changes in gene expression and have lower transcriptional BMCs. The combined high-throughput transcriptomic and bioinformatic analyses support the capability of NAMs to efficiently assess the effects of PFAS in liver microtissues. The data enable potency ranking of PFAS for human liver cell spheroid cytotoxicity and transcriptional changes, and assessment of in vitro transcriptomic points of departure. These data improve our understanding of the possible health effects of PFAS and will be used to inform read-across for human health risk assessment.
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Affiliation(s)
- Anthony J F Reardon
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Andrea Rowan-Carroll
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Stephen S Ferguson
- Biomolecular Screening Branch, Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, USA
| | - Karen Leingartner
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Remi Gagne
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Byron Kuo
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Luigi Lorusso
- Chemicals and Environmental Health Management Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Julie A Bourdon-Lacombe
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Richard Carrier
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Ivy Moffat
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada.,Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Ella Atlas
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada.,Department of Biochemistry, University of Ottawa, Ottawa, Ontario, Canada
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41
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Reardon AJF, Rowan-Carroll A, Ferguson SS, Leingartner K, Gagne R, Kuo B, Williams A, Lorusso L, Bourdon-Lacombe JA, Carrier R, Moffat I, Yauk CL, Atlas E. Potency Ranking of Per- and Polyfluoroalkyl Substances Using High-Throughput Transcriptomic Analysis of Human Liver Spheroids. Toxicol Sci 2021; 184:154-169. [PMID: 34453843 DOI: 10.1101/2020.10.15.341362] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023] Open
Abstract
Per- and polyfluoroalkyl substances (PFAS) are some of the most prominent organic contaminants in human blood. Although the toxicological implications of human exposure to perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) are well established, data on lesser-understood PFAS are limited. New approach methodologies (NAMs) that apply bioinformatic tools to high-throughput data are being increasingly considered to inform risk assessment for data-poor chemicals. The aim of this study was to compare the potencies (ie, benchmark concentrations: BMCs) of PFAS in primary human liver microtissues (3D spheroids) using high-throughput transcriptional profiling. Gene expression changes were measured using TempO-seq, a templated, multiplexed RNA-sequencing platform. Spheroids were exposed for 1 or 10 days to increasing concentrations of 23 PFAS in 3 subgroups: carboxylates (PFCAs), sulfonates (PFSAs), and fluorotelomers and sulfonamides. PFCAs and PFSAs exhibited trends toward increased transcriptional potency with carbon chain-length. Specifically, longer-chain compounds (7-10 carbons) were more likely to induce changes in gene expression and have lower transcriptional BMCs. The combined high-throughput transcriptomic and bioinformatic analyses support the capability of NAMs to efficiently assess the effects of PFAS in liver microtissues. The data enable potency ranking of PFAS for human liver cell spheroid cytotoxicity and transcriptional changes, and assessment of in vitro transcriptomic points of departure. These data improve our understanding of the possible health effects of PFAS and will be used to inform read-across for human health risk assessment.
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Affiliation(s)
- Anthony J F Reardon
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Andrea Rowan-Carroll
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Stephen S Ferguson
- Biomolecular Screening Branch, Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, USA
| | - Karen Leingartner
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Remi Gagne
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Byron Kuo
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Luigi Lorusso
- Chemicals and Environmental Health Management Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Julie A Bourdon-Lacombe
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Richard Carrier
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Ivy Moffat
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Ella Atlas
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
- Department of Biochemistry, University of Ottawa, Ottawa, Ontario, Canada
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42
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Reardon AJF, Rowan-Carroll A, Ferguson SS, Leingartner K, Gagne R, Kuo B, Williams A, Lorusso L, Bourdon-Lacombe JA, Carrier R, Moffat I, Yauk CL, Atlas E. Potency Ranking of Per- and Polyfluoroalkyl Substances Using High-Throughput Transcriptomic Analysis of Human Liver Spheroids. Toxicol Sci 2021; 184:154-169. [PMID: 34453843 DOI: 10.1101/2020.10.20.347328] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023] Open
Abstract
Per- and polyfluoroalkyl substances (PFAS) are some of the most prominent organic contaminants in human blood. Although the toxicological implications of human exposure to perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) are well established, data on lesser-understood PFAS are limited. New approach methodologies (NAMs) that apply bioinformatic tools to high-throughput data are being increasingly considered to inform risk assessment for data-poor chemicals. The aim of this study was to compare the potencies (ie, benchmark concentrations: BMCs) of PFAS in primary human liver microtissues (3D spheroids) using high-throughput transcriptional profiling. Gene expression changes were measured using TempO-seq, a templated, multiplexed RNA-sequencing platform. Spheroids were exposed for 1 or 10 days to increasing concentrations of 23 PFAS in 3 subgroups: carboxylates (PFCAs), sulfonates (PFSAs), and fluorotelomers and sulfonamides. PFCAs and PFSAs exhibited trends toward increased transcriptional potency with carbon chain-length. Specifically, longer-chain compounds (7-10 carbons) were more likely to induce changes in gene expression and have lower transcriptional BMCs. The combined high-throughput transcriptomic and bioinformatic analyses support the capability of NAMs to efficiently assess the effects of PFAS in liver microtissues. The data enable potency ranking of PFAS for human liver cell spheroid cytotoxicity and transcriptional changes, and assessment of in vitro transcriptomic points of departure. These data improve our understanding of the possible health effects of PFAS and will be used to inform read-across for human health risk assessment.
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Affiliation(s)
- Anthony J F Reardon
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Andrea Rowan-Carroll
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Stephen S Ferguson
- Biomolecular Screening Branch, Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, USA
| | - Karen Leingartner
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Remi Gagne
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Byron Kuo
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Luigi Lorusso
- Chemicals and Environmental Health Management Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Julie A Bourdon-Lacombe
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Richard Carrier
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Ivy Moffat
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Ella Atlas
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
- Department of Biochemistry, University of Ottawa, Ottawa, Ontario, Canada
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43
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Gilbert ME, O'Shaughnessy KL, Thomas SE, Riutta C, Wood CR, Smith A, Oshiro WO, Ford RL, Hotchkiss MG, Hassan I, Ford JL. Thyroid Disruptors: Extrathyroidal Sites of Chemical Action and Neurodevelopmental Outcome-An Examination Using Triclosan and Perfluorohexane Sulfonate. Toxicol Sci 2021; 183:195-213. [PMID: 34460931 PMCID: PMC9038230 DOI: 10.1093/toxsci/kfab080] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Many xenobiotics are identified as potential thyroid disruptors due to their action to reduce circulating levels of thyroid hormone, most notably thyroxine (T4). Developmental neurotoxicity is a primary concern for thyroid disrupting chemicals yet correlating the impact of chemically induced changes in serum T4 to perturbed brain development remains elusive. A number of thyroid-specific neurodevelopmental assays have been proposed, based largely on the model thyroid hormone synthesis inhibitor propylthiouracil (PTU). This study examined whether thyroid disrupting chemicals acting distinct from synthesis inhibition would result in the same alterations in brain as expected with PTU. The perfluoroalkyl substance perfluorohexane sulfonate (50 mg/kg/day) and the antimicrobial Triclosan (300 mg/kg/day) were administered to pregnant rats from gestational day 6 to postnatal day (PN) 21, and a number of PTU-defined assays for neurotoxicity evaluated. Both chemicals reduced serum T4 but did not increase thyroid stimulating hormone. Both chemicals increased expression of hepatic metabolism genes, while thyroid hormone-responsive genes in the liver, thyroid gland, and brain were largely unchanged. Brain tissue T4 was reduced in newborns, but despite persistent T4 reductions in serum, had recovered in the PN6 pup brain. Neither treatment resulted in a low dose PTU-like phenotype in either brain morphology or neurobehavior, raising questions for the interpretation of serum biomarkers in regulatory toxicology. They further suggest that reliance on serum hormones as prescriptive of specific neurodevelopmental outcomes may be too simplistic and to understand thyroid-mediated neurotoxicity we must expand our thinking beyond that which follows thyroid hormone synthesis inhibition.
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Affiliation(s)
- Mary E Gilbert
- Center for Public Health and Environmental Assessment, Public Health Integrated Toxicology Division, US Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Katherine L O'Shaughnessy
- Center for Public Health and Environmental Assessment, Public Health Integrated Toxicology Division, US Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Susan E Thomas
- Oak Ridge Institute for Science Education, Oak Ridge, Tennesse 37830, USA
| | - Cal Riutta
- Oak Ridge Institute for Science Education, Oak Ridge, Tennesse 37830, USA
| | - Carmen R Wood
- Center for Public Health and Environmental Assessment, Public Health Integrated Toxicology Division, US Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Alicia Smith
- Oak Ridge Institute for Science Education, Oak Ridge, Tennesse 37830, USA
| | - Wendy O Oshiro
- Center for Public Health and Environmental Assessment, Public Health Integrated Toxicology Division, US Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Richard L Ford
- Oak Ridge Institute for Science Education, Oak Ridge, Tennesse 37830, USA
| | - Michelle Gatien Hotchkiss
- Center for Public Health and Environmental Assessment, Public Health Integrated Toxicology Division, US Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Iman Hassan
- Center for Public Health and Environmental Assessment, Public Health Integrated Toxicology Division, US Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Jermaine L Ford
- Center for Computational Toxicology and Exposure, Chemical Characterization and Exposure Division, US Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
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44
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Rowan-Carroll A, Reardon A, Leingartner K, Gagné R, Williams A, Meier MJ, Kuo B, Bourdon-Lacombe J, Moffat I, Carrier R, Nong A, Lorusso L, Ferguson SS, Atlas E, Yauk C. High-Throughput Transcriptomic Analysis of Human Primary Hepatocyte Spheroids Exposed to Per- and Polyfluoroalkyl Substances as a Platform for Relative Potency Characterization. Toxicol Sci 2021; 181:199-214. [PMID: 33772556 DOI: 10.1093/toxsci/kfab039] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Per- and poly-fluoroalkyl substances (PFAS) are widely found in the environment because of their extensive use and persistence. Although several PFAS are well studied, most lack toxicity data to inform human health hazard and risk assessment. This study focused on 4 model PFAS: perfluorooctanoic acid (PFOA; 8 carbon), perfluorobutane sulfonate (PFBS; 4 carbon), perfluorooctane sulfonate (PFOS; 8 carbon), and perfluorodecane sulfonate (PFDS; 10 carbon). Human primary liver cell spheroids (pooled from 10 donors) were exposed to 10 concentrations of each PFAS and analyzed at 4 time points. The approach aimed to: (1) identify gene expression changes mediated by the PFAS, (2) identify similarities in biological responses, (3) compare PFAS potency through benchmark concentration analysis, and (4) derive bioactivity exposure ratios (ratio of the concentration at which biological responses occur, relative to daily human exposure). All PFAS induced transcriptional changes in cholesterol biosynthesis and lipid metabolism pathways, and predicted PPARα activation. PFOS exhibited the most transcriptional activity and had a highly similar gene expression profile to PFDS. PFBS induced the least transcriptional changes and the highest benchmark concentration (ie, was the least potent). The data indicate that these PFAS may have common molecular targets and toxicities, but that PFOS and PFDS are the most similar. The transcriptomic bioactivity exposure ratios derived here for PFOA and PFOS were comparable to those derived using rodent apical endpoints in risk assessments. These data provide a baseline level of toxicity for comparison with other known PFAS using this testing strategy.
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Affiliation(s)
- Andrea Rowan-Carroll
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Anthony Reardon
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Karen Leingartner
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Remi Gagné
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Matthew J Meier
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Byron Kuo
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Julie Bourdon-Lacombe
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Ivy Moffat
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Richard Carrier
- Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Andy Nong
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Luigi Lorusso
- Chemicals and Environmental Health Management Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Stephen S Ferguson
- U.S. National Institute of Environmental Health Sciences (NIEHS), Ottawa, Ontario K1N 6N5, Canada
| | - Ella Atlas
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada
| | - Carole Yauk
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch (HECSB) Health Canada, Ottawa, Ontario K1N 6N5, Canada.,Department of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
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Dent MP, Vaillancourt E, Thomas RS, Carmichael PL, Ouedraogo G, Kojima H, Barroso J, Ansell J, Barton-Maclaren TS, Bennekou SH, Boekelheide K, Ezendam J, Field J, Fitzpatrick S, Hatao M, Kreiling R, Lorencini M, Mahony C, Montemayor B, Mazaro-Costa R, Oliveira J, Rogiers V, Smegal D, Taalman R, Tokura Y, Verma R, Willett C, Yang C. Paving the way for application of next generation risk assessment to safety decision-making for cosmetic ingredients. Regul Toxicol Pharmacol 2021; 125:105026. [PMID: 34389358 PMCID: PMC8547713 DOI: 10.1016/j.yrtph.2021.105026] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 07/22/2021] [Accepted: 08/06/2021] [Indexed: 11/30/2022]
Abstract
Next generation risk assessment (NGRA) is an exposure-led, hypothesis-driven approach that has the potential to support animal-free safety decision-making. However, significant effort is needed to develop and test the in vitro and in silico (computational) approaches that underpin NGRA to enable confident application in a regulatory context. A workshop was held in Montreal in 2019 to discuss where effort needs to be focussed and to agree on the steps needed to ensure safety decisions made on cosmetic ingredients are robust and protective. Workshop participants explored whether NGRA for cosmetic ingredients can be protective of human health, and reviewed examples of NGRA for cosmetic ingredients. From the limited examples available, it is clear that NGRA is still in its infancy, and further case studies are needed to determine whether safety decisions are sufficiently protective and not overly conservative. Seven areas were identified to help progress application of NGRA, including further investments in case studies that elaborate on scenarios frequently encountered by industry and regulators, including those where a ‘high risk’ conclusion would be expected. These will provide confidence that the tools and approaches can reliably discern differing levels of risk. Furthermore, frameworks to guide performance and reporting should be developed.
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Affiliation(s)
- M P Dent
- Unilever Safety and Environmental Assurance Centre, Sharnbrook, Bedfordshire, MK44 1LQ, UK.
| | - E Vaillancourt
- Health Canada, Healthy Environments and Consumer Safety Branch, 269 Laurier Ave. W., Ottawa, ON K1A 0K9, Canada.
| | - R S Thomas
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research, Triangle Park, NC, 27711, USA.
| | - P L Carmichael
- Unilever Safety and Environmental Assurance Centre, Sharnbrook, Bedfordshire, MK44 1LQ, UK.
| | - G Ouedraogo
- l'Oréal, Research and Development, Paris, France.
| | - H Kojima
- National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, 158-8501, Tokyo, Japan.
| | - J Barroso
- European Commission, Joint Research Centre (JRC), Ispra, VA, Italy.
| | - J Ansell
- US Personal Care Products Council (PCPC), 1620 L St. NW, Suite 1200, Washington, D.C, 20036, USA.
| | - T S Barton-Maclaren
- Health Canada, Healthy Environments and Consumer Safety Branch, 269 Laurier Ave. W., Ottawa, ON K1A 0K9, Canada.
| | - S H Bennekou
- National Food Institute, Technical University of Denmark (DTU), Copenhagen, Denmark.
| | - K Boekelheide
- Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA.
| | - J Ezendam
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
| | - J Field
- Health Canada, Healthy Environments and Consumer Safety Branch, 269 Laurier Ave. W., Ottawa, ON K1A 0K9, Canada.
| | - S Fitzpatrick
- US Food and Drug Administration (US FDA), Center for Food Safety and Applied Nutrition (CFSAN), 5001 Campus Drive, College Park, MD, 20740, USA.
| | - M Hatao
- Japan Cosmetic Industry Association (JCIA), Metro City Kamiyacho 6F, 5-1-5, Toranomon, Minato-ku, Tokyo, 105-0001 Japan.
| | - R Kreiling
- Clariant Produkte (Deutschland) GmbH, Am Unisyspark 1, 65843, Sulzbach, Germany.
| | - M Lorencini
- Grupo Boticário, Research & Development, São José dos Pinhais, Brazil.
| | - C Mahony
- Procter & Gamble Technical Centres Ltd, Reading, RG2 0RX, UK.
| | - B Montemayor
- Cosmetics Alliance Canada, 420 Britannia Road East Suite 102, Mississauga, ON L4Z 3L5, Canada.
| | - R Mazaro-Costa
- Departament of Pharmacology, Universidade Federal de Goiás, Goiânia, GO, 74.690-900, Brazil.
| | - J Oliveira
- Brazilian Health Regulatory Agency (ANVISA), Gerência de Produtos de Higiene, Perfumes, Cosméticos e Saneantes, Setor de Indústria e Abastecimento (SIA), Trecho 5, Área Especial 57, CEP 71205-050, Brasília, DF, Brazil.
| | - V Rogiers
- Vrije Universiteit Brussel, Brussels, Belgium.
| | - D Smegal
- US Food and Drug Administration (US FDA), Center for Food Safety and Applied Nutrition (CFSAN), 5001 Campus Drive, College Park, MD, 20740, USA.
| | - R Taalman
- Cosmetics Europe, Avenue Herrmann-Debroux 40, 1160 Auderghem, Belgium.
| | - Y Tokura
- Allergic Disease Research Center, Chutoen General Medical Center, Kakegawa, Japan.
| | - R Verma
- US Food and Drug Administration (US FDA), Center for Food Safety and Applied Nutrition (CFSAN), 5001 Campus Drive, College Park, MD, 20740, USA.
| | - C Willett
- Humane Society International, Washington, DC, USA.
| | - C Yang
- Taiwan Cosmetic Industry Association (TWCIA), 8F No. 136, Bo'ai Rd., Zhongzheng Dist., Taipei City, 100, Taiwan, ROC.
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46
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Alcaraz AJG, Mikulášek K, Potěšil D, Park B, Shekh K, Ewald J, Burbridge C, Zdráhal Z, Schneider D, Xia J, Crump D, Basu N, Hecker M. Assessing the Toxicity of 17α-Ethinylestradiol in Rainbow Trout Using a 4-Day Transcriptomics Benchmark Dose (BMD) Embryo Assay. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:10608-10618. [PMID: 34292719 DOI: 10.1021/acs.est.1c02401] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
There is an urgent demand for more efficient and ethical approaches in ecological risk assessment. Using 17α-ethinylestradiol (EE2) as a model compound, this study established an embryo benchmark dose (BMD) assay for rainbow trout (RBT; Oncorhynchus mykiss) to derive transcriptomic points-of-departure (tPODs) as an alternative to live-animal tests. Embryos were exposed to graded concentrations of EE2 (measured: 0, 1.13, 1.57, 6.22, 16.3, 55.1, and 169 ng/L) from hatch to 4 and up to 60 days post-hatch (dph) to assess molecular and apical responses, respectively. Whole proteome analyses of alevins did not show clear estrogenic effects. In contrast, transcriptomics revealed responses that were in agreement with apical effects, including excessive accumulation of intravascular and hepatic proteinaceous fluid and significant increases in mortality at 55.1 and 169 ng/L EE2 at later time points. Transcriptomic BMD analysis estimated the median of the 20th lowest geneBMD to be 0.18 ng/L, the most sensitive tPOD. Other estimates (0.78, 3.64, and 1.63 ng/L for the 10th percentile geneBMD, first peak geneBMD distribution, and median geneBMD of the most sensitive over-represented pathway, respectively) were within the same order of magnitude as empirically derived apical PODs for EE2 in the literature. This 4-day alternative RBT embryonic assay was effective in deriving tPODs that are protective of chronic effects of EE2.
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Affiliation(s)
- Alper James G Alcaraz
- Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5B3
| | - Kamil Mikulášek
- Central European Institute of Technology, Masaryk University, Brno CZ-625 00, Czech Republic
| | - David Potěšil
- Central European Institute of Technology, Masaryk University, Brno CZ-625 00, Czech Republic
| | - Bradley Park
- Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5B3
| | - Kamran Shekh
- Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5B3
| | - Jessica Ewald
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec, Canada H9X 3V9
| | - Connor Burbridge
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 0W9
| | - Zbyněk Zdráhal
- Central European Institute of Technology, Masaryk University, Brno CZ-625 00, Czech Republic
| | - David Schneider
- Global Institute for Food Security, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 0W9
- School of the Environment and Sustainability, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5C8
| | - Jianguo Xia
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec, Canada H9X 3V9
| | - Doug Crump
- Environment and Climate Change Canada, National Wildlife Research Centre, Ottawa, Ontario, Canada K1A 0H3
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec, Canada H9X 3V9
| | - Markus Hecker
- Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5B3
- School of the Environment and Sustainability, University of Saskatchewan, Saskatoon, Saskatchewan, Canada S7N 5C8
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47
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Ewald J, Soufan O, Xia J, Basu N. FastBMD: an online tool for rapid benchmark dose-response analysis of transcriptomics data. Bioinformatics 2021; 37:1035-1036. [PMID: 32761065 PMCID: PMC8128449 DOI: 10.1093/bioinformatics/btaa700] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 07/07/2020] [Accepted: 07/28/2020] [Indexed: 12/13/2022] Open
Abstract
MOTIVATION Transcriptomics dose-response analysis is a promising new approach method for toxicity testing. While international regulatory agencies have spent substantial effort establishing a standardized statistical approach, existing software that follows this approach is computationally inefficient and must be locally installed. RESULTS FastBMD is a web-based tool that implements standardized methods for transcriptomics benchmark dose-response analysis in R. It is >60 times faster than the current leading software, supports transcriptomics data from 13 species, and offers a comprehensive analytical pipeline that goes from processing and normalization of raw gene expression values to interactive exploration of pathway-level benchmark dose results. AVAILABILITY AND IMPLEMENTATION FastBMD is freely available at www.fastbmd.ca. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jessica Ewald
- Department of Natural Resource Sciences, McGill University, Montreal, QC H9X 3V9, Canada
| | - Othman Soufan
- Institute of Parasitology, McGill University, Montreal, QC H9X 3V9, Canada
| | - Jianguo Xia
- Institute of Parasitology, McGill University, Montreal, QC H9X 3V9, Canada
| | - Niladri Basu
- Department of Natural Resource Sciences, McGill University, Montreal, QC H9X 3V9, Canada
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48
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Crizer DM, Ramaiahgari SC, Ferguson SS, Rice JR, Dunlap PE, Sipes NS, Auerbach SS, Merrick BA, DeVito MJ. Benchmark Concentrations for Untargeted Metabolomics Versus Transcriptomics for Liver Injury Compounds in In Vitro Liver Models. Toxicol Sci 2021; 181:175-186. [PMID: 33749773 PMCID: PMC8163038 DOI: 10.1093/toxsci/kfab036] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Interpretation of untargeted metabolomics data from both in vivo and physiologically relevant in vitro model systems continues to be a significant challenge for toxicology research. Potency-based modeling of toxicological responses has served as a pillar of interpretive context and translation of testing data. In this study, we leverage the resolving power of concentration-response modeling through benchmark concentration (BMC) analysis to interpret untargeted metabolomics data from differentiated cultures of HepaRG cells exposed to a panel of reference compounds and integrate data in a potency-aligned framework with matched transcriptomic data. For this work, we characterized biological responses to classical human liver injury compounds and comparator compounds, known to not cause liver injury in humans, at 10 exposure concentrations in spent culture media by untargeted liquid chromatography-mass spectrometry analysis. The analyte features observed (with limited metabolites identified) were analyzed using BMC modeling to derive compound-induced points of departure. The results revealed liver injury compounds produced concentration-related increases in metabolomic response compared to those rarely associated with liver injury (ie, sucrose, potassium chloride). Moreover, the distributions of altered metabolomic features were largely comparable with those observed using high throughput transcriptomics, which were further extended to investigate the potential for in vitro observed biological responses to be observed in humans with exposures at therapeutic doses. These results demonstrate the utility of BMC modeling of untargeted metabolomics data as a sensitive and quantitative indicator of human liver injury potential.
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Affiliation(s)
- David M Crizer
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Sreenivasa C Ramaiahgari
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Stephen S Ferguson
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Julie R Rice
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Paul E Dunlap
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Nisha S Sipes
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Scott S Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Bruce Alex Merrick
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Michael J DeVito
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
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49
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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. COMPUTATIONAL TOXICOLOGY (AMSTERDAM, NETHERLANDS) 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] [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.
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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
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50
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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: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [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.
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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
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