1
|
Sostare E, Bowen TJ, Lawson TN, Freier A, Li X, Lloyd GR, Najdekr L, Jankevics A, Smith T, Varshavi D, Ludwig C, Colbourne JK, Weber RJM, Crizer DM, Auerbach SS, Bucher JR, Viant MR. Metabolomics Simultaneously Derives Benchmark Dose Estimates and Discovers Metabolic Biotransformations in a Rat Bioassay. Chem Res Toxicol 2024. [PMID: 38842447 DOI: 10.1021/acs.chemrestox.4c00002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
Benchmark dose (BMD) modeling estimates the dose of a chemical that causes a perturbation from baseline. Transcriptional BMDs have been shown to be relatively consistent with apical end point BMDs, opening the door to using molecular BMDs to derive human health-based guidance values for chemical exposure. Metabolomics measures the responses of small-molecule endogenous metabolites to chemical exposure, complementing transcriptomics by characterizing downstream molecular phenotypes that are more closely associated with apical end points. The aim of this study was to apply BMD modeling to in vivo metabolomics data, to compare metabolic BMDs to both transcriptional and apical end point BMDs. This builds upon our previous application of transcriptomics and BMD modeling to a 5-day rat study of triphenyl phosphate (TPhP), applying metabolomics to the same archived tissues. Specifically, liver from rats exposed to five doses of TPhP was investigated using liquid chromatography-mass spectrometry and 1H nuclear magnetic resonance spectroscopy-based metabolomics. Following the application of BMDExpress2 software, 2903 endogenous metabolic features yielded viable dose-response models, confirming a perturbation to the liver metabolome. Metabolic BMD estimates were similarly sensitive to transcriptional BMDs, and more sensitive than both clinical chemistry and apical end point BMDs. Pathway analysis of the multiomics data sets revealed a major effect of TPhP exposure on cholesterol (and downstream) pathways, consistent with clinical chemistry measurements. Additionally, the transcriptomics data indicated that TPhP activated xenobiotic metabolism pathways, which was confirmed by using the underexploited capability of metabolomics to detect xenobiotic-related compounds. Eleven biotransformation products of TPhP were discovered, and their levels were highly correlated with multiple xenobiotic metabolism genes. This work provides a case study showing how metabolomics and transcriptomics can estimate mechanistically anchored points-of-departure. Furthermore, the study demonstrates how metabolomics can also discover biotransformation products, which could be of value within a regulatory setting, for example, as an enhancement of OECD Test Guideline 417 (toxicokinetics).
Collapse
Affiliation(s)
- Elena Sostare
- Michabo Health Science Ltd., Union House, 111 New Union Street, Coventry CV1 2NT, U.K
| | - Tara J Bowen
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, U.K
| | - Thomas N Lawson
- Michabo Health Science Ltd., Union House, 111 New Union Street, Coventry CV1 2NT, U.K
| | - Anne Freier
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, U.K
| | - Xiaojing Li
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, U.K
| | - Gavin R Lloyd
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, U.K
| | - Lukáš Najdekr
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, U.K
| | - Andris Jankevics
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, U.K
| | - Thomas Smith
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, U.K
| | - Dorsa Varshavi
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, U.K
| | - Christian Ludwig
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, U.K
| | - John K Colbourne
- Michabo Health Science Ltd., Union House, 111 New Union Street, Coventry CV1 2NT, U.K
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, U.K
| | - Ralf J M Weber
- Michabo Health Science Ltd., Union House, 111 New Union Street, Coventry CV1 2NT, U.K
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, U.K
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, U.K
| | - David M Crizer
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park NC 27709, North Carolina, United States
| | - Scott S Auerbach
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park NC 27709, North Carolina, United States
| | - John R Bucher
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park NC 27709, North Carolina, United States
| | - Mark R Viant
- Michabo Health Science Ltd., Union House, 111 New Union Street, Coventry CV1 2NT, U.K
- School of Biosciences, University of Birmingham, Birmingham B15 2TT, U.K
- Phenome Centre Birmingham, University of Birmingham, Birmingham B15 2TT, U.K
| |
Collapse
|
2
|
Gao X, Johnson WE, Yourick MR, Campasino K, Sprando RL, Yourick JJ. Hepatotoxicity of Silver Nanoparticles: Benchmark Concentration Modeling of an In Vitro Transcriptomics Study in Human iPSC-derived Hepatocytes. Regul Toxicol Pharmacol 2024:105653. [PMID: 38825064 DOI: 10.1016/j.yrtph.2024.105653] [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: 12/13/2023] [Revised: 05/21/2024] [Accepted: 05/30/2024] [Indexed: 06/04/2024]
Abstract
Despite two decades of research on silver nanoparticle (AgNP) toxicity, a safe threshold for exposure has not yet been established, albeit being critically needed for risk assessment and regulatory decision-making. Traditionally, a point-of-departure (PoD) value is derived from dose response of apical endpoints in animal studies using either the no-observed-adverse-effect level (NOAEL) approach, or benchmark dose (BMD) modeling. To develop new approach methodologies (NAMs) to inform human risk assessment of AgNPs, we conducted a concentration response modeling of the transcriptomic changes in hepatocytes derived from human induced pluripotent stem cells (iPSCs) after being exposed to a wide range concentration (0.01-25 μg/ml) of AgNPs for 24 h. A plausible transcriptomic PoD of 0.21 μg/ml was derived for a pathway related to the mode-of-action (MOA) of AgNPs, and a more conservative PoD of 0.10 μg/ml for a gene ontology (GO) term not apparently associated with the MOA of AgNPs. A reference dose (RfD) could be calculated from either of the PoDs as a safe threshold for AgNP exposure. The current study illustrates the usefulness of in vitro transcriptomic concentration response study using human cells as a NAM for toxicity study of chemicals that lack adequate toxicity data to inform human risk assessment.
Collapse
Affiliation(s)
- Xiugong Gao
- Division of Toxicology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, Laurel, MD, USA.
| | - W Evan Johnson
- Division of Infectious Disease, Center for Data Science, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Miranda R Yourick
- Division of Toxicology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, Laurel, MD, USA
| | - Kayla Campasino
- Division of Toxicology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, Laurel, MD, USA
| | - Robert L Sprando
- Division of Toxicology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, Laurel, MD, USA
| | - Jeffrey J Yourick
- Division of Toxicology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, Laurel, MD, USA
| |
Collapse
|
3
|
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.
Collapse
Affiliation(s)
| | | | | | - Jason M. O’Brien
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, Ottawa, ON, Canada
| |
Collapse
|
4
|
Flynn K, Le M, Hazemi M, Biales A, Bencic DC, Blackwell BR, Bush K, Flick R, Hoang JX, Martinson J, Morshead M, Rodriguez KS, Stacy E, Villeneuve DL. Comparing Transcriptomic Points of Departure to Apical Effect Concentrations For Larval Fathead Minnow Exposed to Chemicals with Four Different Modes Of Action. ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2024; 86:346-362. [PMID: 38743081 DOI: 10.1007/s00244-024-01064-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 04/04/2024] [Indexed: 05/16/2024]
Abstract
It is postulated that below a transcriptomic-based point of departure, adverse effects are unlikely to occur, thereby providing a chemical concentration to use in screening level hazard assessment. The present study extends previous work describing a high-throughput fathead minnow assay that can provide full transcriptomic data after exposure to a test chemical. One-day post-hatch fathead minnows were exposed to ten concentrations of three representatives of four chemical modes of action: organophosphates, ecdysone receptor agonists, plant photosystem II inhibitors, and estrogen receptor agonists for 24 h. Concentration response modeling was performed on whole body gene expression data from each exposure, using measured chemical concentrations when available. Transcriptomic points of departure in larval fathead minnow were lower than apical effect concentrations across fish species but not always lower than toxic effect concentrations in other aquatic taxa like crustaceans and insects. The point of departure was highly dependent on measured chemical concentration which were often lower than the nominal concentration. Differentially expressed genes between chemicals within modes of action were compared and often showed statistically significant overlap. In addition, reproducibility between identical exposures using a positive control chemical (CuSO4) and variability associated with the transcriptomic point of departure using in silico sampling were considered. Results extend a transcriptomic-compatible fathead minnow high-throughput assay for possible use in ecological hazard screening.
Collapse
Affiliation(s)
- Kevin Flynn
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, US EPA GLTED, 6201 Congdon Blvd, Duluth, MN, 55804, USA.
| | - Michelle Le
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, MN, 55804, USA
| | - Monique Hazemi
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, MN, 55804, USA
| | - Adam Biales
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Cincinnati, OH, 45220, USA
| | - David C Bencic
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Cincinnati, OH, 45220, USA
| | - Brett R Blackwell
- Biochemistry and Biotechnology Group, Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA
| | - Kendra Bush
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, MN, 55804, USA
| | - Robert Flick
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Cincinnati, OH, 45220, USA
| | - John X Hoang
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, MN, 55804, USA
| | - John Martinson
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Cincinnati, OH, 45220, USA
| | - Mackenzie Morshead
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, MN, 55804, USA
| | - Kelvin Santana Rodriguez
- Oak Ridge Institute for Science and Education (ORISE) Research Participant, Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, MN, 55804, USA
| | - Emma Stacy
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, US EPA GLTED, 6201 Congdon Blvd, Duluth, MN, 55804, USA
| | - Daniel L Villeneuve
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, US EPA GLTED, 6201 Congdon Blvd, Duluth, MN, 55804, USA
| |
Collapse
|
5
|
Ankley GT, Berninger JP, Maloney EM, Olker JH, Schaupp CM, Villeneuve DL, LaLone CA. Linking Mechanistic Effects of Pharmaceuticals and Personal Care Products to Ecologically Relevant Outcomes: A Decade of Progress. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2024; 43:537-548. [PMID: 35735070 PMCID: PMC11036122 DOI: 10.1002/etc.5416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/02/2022] [Accepted: 06/16/2022] [Indexed: 06/15/2023]
Abstract
There are insufficient toxicity data to assess the ecological risks of many pharmaceuticals and personal care products (PPCPs). While data limitations are not uncommon for contaminants of environmental concern, PPCPs are somewhat unique in that an a priori understanding of their biological activities in conjunction with measurements of molecular, biochemical, or histological responses could provide a foundation for understanding mode(s) of action and predicting potential adverse apical effects. Over the past decade significant progress has been made in the development of new approach methodologies (NAMs) to efficiently quantify these types of endpoints using computational models and pathway-based in vitro and in vivo assays. The availability of open-access knowledgebases to curate biological response (including NAM) data and sophisticated bioinformatics tools to help interpret the information also has significantly increased. Finally, advances in the development and implementation of the adverse outcome pathway framework provide the critical conceptual underpinnings needed to translate NAM data into predictions of the ecologically relevant outcomes required by risk assessors and managers. The evolution and convergence of these various data streams, tools, and concepts provides the basis for a fundamental change in how ecological risks of PPCPs can be pragmatically assessed. Environ Toxicol Chem 2024;43:537-548. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
Collapse
Affiliation(s)
- Gerald T Ankley
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA
| | - Jason P Berninger
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA
| | - Erin M Maloney
- University of Minnesota-Duluth, Integrated Biological Sciences Program, Duluth, Minnesota, USA
| | - Jennifer H Olker
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA
| | | | - Daniel L Villeneuve
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA
| | - Carlie A LaLone
- US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA
| |
Collapse
|
6
|
Villeneuve DL, Bush K, Hazemi M, Hoang JX, Le M, Blackwell BR, Stacy E, Flynn KM. Derivation of Transcriptomics-Based Points of Departure for 20 Per- or Polyfluoroalkyl Substances Using a Larval Fathead Minnow (Pimephales promelas) Reduced Transcriptome Assay. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2024. [PMID: 38415853 DOI: 10.1002/etc.5825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 12/18/2023] [Accepted: 01/08/2024] [Indexed: 02/29/2024]
Abstract
Traditional toxicity testing has been unable to keep pace with the introduction of new chemicals into commerce. Consequently, there are limited or no toxicity data for many chemicals to which fish and wildlife may be exposed. Per- and polyfluoroalkyl substances (PFAS) are emblematic of this issue in that ecological hazards of most PFAS remain uncharacterized. The present study employed a high-throughput assay to identify the concentration at which 20 PFAS, with diverse properties, elicited a concerted gene expression response (termed a transcriptomics-based point of departure [tPOD]) in larval fathead minnows (Pimephales promelas; 5-6 days postfertilization) exposed for 24 h. Based on a reduced transcriptome approach that measured whole-body expression of 1832 genes, the median tPOD for the 20 PFAS tested was 10 µM. Longer-chain carboxylic acids (12-13 C-F); an eight-C-F dialcohol, N-alkyl sulfonamide; and telomer sulfonic acid were among the most potent PFAS, eliciting gene expression responses at concentrations <1 µM. With a few exceptions, larval fathead minnow tPODs were concordant with those based on whole-transcriptome response in human cell lines. However, larval fathead minnow tPODs were often greater than those for Daphnia magna exposed to the same PFAS. The tPODs overlapped concentrations at which other sublethal effects have been reported in fish (available for 10 PFAS). Nonetheless, fathead minnow tPODs were orders of magnitude higher than aqueous PFAS concentrations detected in tributaries of the North American Great Lakes, suggesting a substantial margin of safety. Overall, results broadly support the use of a fathead minnow larval transcriptomics assay to derive screening-level potency estimates for use in ecological risk-based prioritization. Environ Toxicol Chem 2024;00:1-16. © 2024 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
Collapse
Affiliation(s)
- Daniel L Villeneuve
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota
| | - Kendra Bush
- Research Participant at Great Lakes Toxicology and Ecology Division, Oak Ridge Institute for Science and Education, Duluth, Minnesota, USA
| | - Monique Hazemi
- Research Participant at Great Lakes Toxicology and Ecology Division, Oak Ridge Institute for Science and Education, Duluth, Minnesota, USA
| | - John X Hoang
- Research Participant at Great Lakes Toxicology and Ecology Division, Oak Ridge Institute for Science and Education, Duluth, Minnesota, USA
| | - Michelle Le
- Research Participant at Great Lakes Toxicology and Ecology Division, Oak Ridge Institute for Science and Education, Duluth, Minnesota, USA
| | - Brett R Blackwell
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota
- Bioscience Division, Biochemistry and Biotechnology Group, Los Alamos National Laboratory, Los Alamos, Minnesota, USA
| | - Emma Stacy
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota
| | - Kevin M Flynn
- Great Lakes Toxicology and Ecology Division, US Environmental Protection Agency, Duluth, Minnesota
| |
Collapse
|
7
|
Silva MH. Investigating open access new approach methods (NAM) to assess biological points of departure: A case study with 4 neurotoxic pesticides. Curr Res Toxicol 2024; 6:100156. [PMID: 38404712 PMCID: PMC10891343 DOI: 10.1016/j.crtox.2024.100156] [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: 08/14/2023] [Revised: 12/28/2023] [Accepted: 02/09/2024] [Indexed: 02/27/2024] Open
Abstract
Open access new approach methods (NAM) in the US EPA ToxCast program and NTP Integrated Chemical Environment (ICE) were used to investigate activities of four neurotoxic pesticides: endosulfan, fipronil, propyzamide and carbaryl. Concordance of in vivo regulatory points of departure (POD) adjusted for interspecies extrapolation (AdjPOD) to modelled human Administered Equivalent Dose (AEDHuman) was assessed using 3-compartment or Adult/Fetal PBTK in vitro to in vivo extrapolation. Model inputs were from Tier 1 (High throughput transcriptomics: HTTr, high throughput phenotypic profiling: HTPP) and Tier 2 (single target: ToxCast) assays. HTTr identified gene expression signatures associated with potential neurotoxicity for endosulfan, propyzamide and carbaryl in non-neuronal MCF-7 and HepaRG cells. The HTPP assay in U-2 OS cells detected potent effects on DNA endpoints for endosulfan and carbaryl, and mitochondria with fipronil (propyzamide was inactive). The most potent ToxCast assays were concordant with specific components of each chemical mode of action (MOA). Predictive adult IVIVE models produced fold differences (FD) < 10 between the AEDHuman and the measured in vivo AdjPOD. The 3-compartment model was concordant (i.e., smallest FD) for endosulfan, fipronil and carbaryl, and PBTK was concordant for propyzamide. The most potent AEDHuman predictions for each chemical showed HTTr, HTPP and ToxCast were mainly concordant with in vivo AdjPODs but assays were less concordant with MOAs. This was likely due to the cell types used for testing and/or lack of metabolic capabilities and pathways available in vivo. The Fetal PBTK model had larger FDs than adult models and was less predictive overall.
Collapse
|
8
|
Martin R, Hazemi M, Flynn K, Villeneuve D, Wehmas L. Short-Term Transcriptomic Points of Departure Are Consistent with Chronic Points of Departure for Three Organophosphate Pesticides across Mouse and Fathead Minnow. TOXICS 2023; 11:820. [PMID: 37888672 PMCID: PMC10611195 DOI: 10.3390/toxics11100820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 09/20/2023] [Accepted: 09/22/2023] [Indexed: 10/28/2023]
Abstract
New approach methods (NAMs) can reduce the need for chronic animal studies. Here, we apply benchmark dose (concentration) (BMD(C))-response modeling to transcriptomic changes in the liver of mice and in fathead minnow larvae after short-term exposures (7 days and 1 day, respectively) to several dose/concentrations of three organophosphate pesticides (OPPs): fenthion, methidathion, and parathion. The mouse liver transcriptional points of departure (TPODs) for fenthion, methidathion, and parathion were 0.009, 0.093, and 0.046 mg/Kg-bw/day, while the fathead minnow larva TPODs were 0.007, 0.115, and 0.046 mg/L, respectively. The TPODs were consistent across both species and reflected the relative potencies from traditional chronic toxicity studies with fenthion identified as the most potent. Moreover, the mouse liver TPODs were more sensitive than or within a 10-fold difference from the chronic apical points of departure (APODs) for mammals, while the fathead minnow larva TPODs were within an 18-fold difference from the chronic APODs for fish species. Short-term exposure to OPPs significantly impacted acetylcholinesterase mRNA abundance (FDR p-value <0.05, |fold change| ≥2) and canonical pathways (IPA, p-value <0.05) associated with organism death and neurological/immune dysfunctions, indicating the conservation of key events related to OPP toxicity. Together, these results build confidence in using short-term, molecular-based assays for the characterization of chemical toxicity and risk, thereby reducing reliance on chronic animal studies.
Collapse
Affiliation(s)
- Rubia Martin
- Office of Research and Development, Center for Computational Toxicology and Exposure, Chemical Characterization and Exposure Division, Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, Durham, NC 27709, USA;
| | - Monique Hazemi
- Office of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Ecology Division, Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, Duluth, MN 55804, USA;
| | - Kevin Flynn
- Office of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Ecology Division, U.S. Environmental Protection Agency, Duluth, MN 55804, USA; (K.F.); (D.V.)
| | - Daniel Villeneuve
- Office of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Ecology Division, U.S. Environmental Protection Agency, Duluth, MN 55804, USA; (K.F.); (D.V.)
| | - Leah Wehmas
- Office of Research and Development, Center for Computational Toxicology and Exposure, Chemical Characterization and Exposure Division, U.S. Environmental Protection Agency, Durham, NC 27709, USA
| |
Collapse
|
9
|
Feshuk M, Kolaczkowski L, Dunham K, Davidson-Fritz SE, Carstens KE, Brown J, Judson RS, Paul Friedman K. The ToxCast pipeline: updates to curve-fitting approaches and database structure. FRONTIERS IN TOXICOLOGY 2023; 5:1275980. [PMID: 37808181 PMCID: PMC10552852 DOI: 10.3389/ftox.2023.1275980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 09/08/2023] [Indexed: 10/10/2023] Open
Abstract
Introduction: The US Environmental Protection Agency Toxicity Forecaster (ToxCast) program makes in vitro medium- and high-throughput screening assay data publicly available for prioritization and hazard characterization of thousands of chemicals. The assays employ a variety of technologies to evaluate the effects of chemical exposure on diverse biological targets, from distinct proteins to more complex cellular processes like mitochondrial toxicity, nuclear receptor signaling, immune responses, and developmental toxicity. The ToxCast data pipeline (tcpl) is an open-source R package that stores, manages, curve-fits, and visualizes ToxCast data and populates the linked MySQL Database, invitrodb. Methods: Herein we describe major updates to tcpl and invitrodb to accommodate a new curve-fitting approach. The original tcpl curve-fitting models (constant, Hill, and gain-loss models) have been expanded to include Polynomial 1 (Linear), Polynomial 2 (Quadratic), Power, Exponential 2, Exponential 3, Exponential 4, and Exponential 5 based on BMDExpress and encoded by the R package dependency, tcplfit2. Inclusion of these models impacted invitrodb (beta version v4.0) and tcpl v3 in several ways: (1) long-format storage of generic modeling parameters to permit additional curve-fitting models; (2) updated logic for winning model selection; (3) continuous hit calling logic; and (4) removal of redundant endpoints as a result of bidirectional fitting. Results and discussion: Overall, the hit call and potency estimates were largely consistent between invitrodb v3.5 and 4.0. Tcpl and invitrodb provide a standard for consistent and reproducible curve-fitting and data management for diverse, targeted in vitro assay data with readily available documentation, thus enabling sharing and use of these data in myriad toxicology applications. The software and database updates described herein promote comparability across multiple tiers of data within the US Environmental Protection Agency CompTox Blueprint.
Collapse
Affiliation(s)
- M. Feshuk
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - L. Kolaczkowski
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
- National Student Services Contractor, Oak Ridge Associated Universities, Oak Ridge, TN, United States
| | - K. Dunham
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
- National Student Services Contractor, Oak Ridge Associated Universities, Oak Ridge, TN, United States
| | - S. E. Davidson-Fritz
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - K. E. Carstens
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - J. Brown
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - R. S. Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - K. Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| |
Collapse
|
10
|
Nelson GM, Carswell GK, Swartz CD, Recio L, Yauk CL, Chorley BN. Early microRNA responses in rodent liver mediated by furan exposure establish dose thresholds for later adverse outcomes. Toxicol Lett 2023; 384:105-114. [PMID: 37517673 PMCID: PMC10530563 DOI: 10.1016/j.toxlet.2023.07.015] [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: 07/10/2023] [Accepted: 07/27/2023] [Indexed: 08/01/2023]
Abstract
To reduce reliance on long-term in vivo studies, short-term data linking early molecular-based measurements to later adverse health effects is needed. Although transcriptional-based benchmark dose (BMDT) modeling has been used to estimate potencies and stratify chemicals based on potential to induce later-life effects, dose-responsive epigenetic alterations have not been routinely considered. Here, we evaluated the utility of microRNA (miRNA) profiling in mouse liver and blood, as well as in mouse primary hepatocytes in vitro, to indicate mechanisms of liver perturbation due to short-term exposure of the known rodent liver hepatotoxicant and carcinogen, furan. Benchmark dose modeling of miRNA measurements (BMDmiR) were compared to the referent transcriptional (BMDT) and apical (BMDA) estimates. These analyses indicate a robust dose response for 34 miRNAs to furan and involvement of p53-linked pathways in furan-mediated hepatotoxicity, supporting mRNA and apical measurements. Liver-sourced miRNAs were also altered in the blood and primary hepatocytes. Overall, these results indicate mechanistic involvement of miRNA in furan carcinogenicity and provide evidence of their potential utility as accessible biomarkers of exposure and disease.
Collapse
Affiliation(s)
- Gail M Nelson
- US Environmental Protection Agency, Research Triangle Park, NC 27709, USA
| | - Gleta K Carswell
- US Environmental Protection Agency, Research Triangle Park, NC 27709, USA
| | - Carol D Swartz
- Inotiv Co., 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA
| | - Leslie Recio
- ScitoVation, 100 Capitola Drive Suite 106, Durham, NC 27713, USA
| | - Carole L Yauk
- Dept. Of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
| | - Brian N Chorley
- US Environmental Protection Agency, Research Triangle Park, NC 27709, USA.
| |
Collapse
|
11
|
Li J, Zagorski JW, Kaminski NE. Establishment of a point of departure for CBD hepatotoxicity employing human HepaRG spheroids. Toxicology 2023; 488:153469. [PMID: 36863504 DOI: 10.1016/j.tox.2023.153469] [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: 01/27/2023] [Revised: 02/17/2023] [Accepted: 02/26/2023] [Indexed: 03/04/2023]
Abstract
The United States Food and Drug Administration recently approved the use of Cannabis sativa derived cannabidiol (CBD) in the treatment of Dravet Syndrome and Lennox-Gastaut Syndrome, under the trade name, Epidiolex. In double-blinded, placebo-controlled clinical trials, elevated ALT levels were observed in some patients, but these findings could not be uncoupled from the confounds of potential drug-drug interactions with co-administration of valproate and clobazam. Given the uncertainty of the potential hepatatoxic effects of CBD, the objective of the present study was to determine a point of departure for CBD, using human HepaRG spheroid cultures, followed by transcriptomic benchmark dose analysis. Treatment of HepaRG spheroids with CBD for 24 and 72 h, resulted in EC50 concentrations for cytotoxicity of 86.27 µM and 58.04 µM, respectively. Subsequent transcriptomic analysis at these timepoints demonstrated little alteration of gene and pathway data sets at a CBD concentration at or below 10 µM. Although this current analysis was conducted using liver cells, interestingly the findings at 72 h post CBD treatment showed suppression of many genes more commonly associated with immune regulation. Indeed, the immune system is a well-established target for CBD based on immune function assays. Collectively, in the present studies a point of departure was derived using transcriptomic changes produced by CBD in a human cell-based model system, which has been shown to accurately translate to human hepatotoxicity modeling.
Collapse
Affiliation(s)
- Jinpeng Li
- Center for Research on Ingredient Safety, Michigan State University, East Lansing, MI 48824, United States; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI 48824, United States
| | - Joseph W Zagorski
- Center for Research on Ingredient Safety, Michigan State University, East Lansing, MI 48824, United States; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI 48824, United States
| | - Norbert E Kaminski
- Center for Research on Ingredient Safety, Michigan State University, East Lansing, MI 48824, United States; Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, United States; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI 48824, United States.
| |
Collapse
|
12
|
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.
Collapse
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
| |
Collapse
|
13
|
Serra A, del Giudice G, Kinaret PAS, Saarimäki LA, Poulsen SS, Fortino V, Halappanavar S, Vogel U, Greco D. Characterization of ENM Dynamic Dose-Dependent MOA in Lung with Respect to Immune Cells Infiltration. NANOMATERIALS 2022; 12:nano12122031. [PMID: 35745370 PMCID: PMC9228743 DOI: 10.3390/nano12122031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 06/08/2022] [Accepted: 06/09/2022] [Indexed: 02/01/2023]
Abstract
The molecular effects of exposures to engineered nanomaterials (ENMs) are still largely unknown. In classical inhalation toxicology, cell composition of bronchoalveolar lavage (BAL) is a toxicity indicator at the lung tissue level that can aid in interpreting pulmonary histological changes. Toxicogenomic approaches help characterize the mechanism of action (MOA) of ENMs by investigating the differentially expressed genes (DEG). However, dissecting which molecular mechanisms and events are directly induced by the exposure is not straightforward. It is now generally accepted that direct effects follow a monotonic dose-dependent pattern. Here, we applied an integrated modeling approach to study the MOA of four ENMs by retrieving the DEGs that also show a dynamic dose-dependent profile (dddtMOA). We further combined the information of the dddtMOA with the dose dependency of four immune cell populations derived from BAL counts. The dddtMOA analysis highlighted the specific adaptation pattern to each ENM. Furthermore, it revealed the distinct effect of the ENM physicochemical properties on the induced immune response. Finally, we report three genes dose-dependent in all the exposures and correlated with immune deregulation in the lung. The characterization of dddtMOA for ENM exposures, both for apical endpoints and molecular responses, can further promote toxicogenomic approaches in a regulatory context.
Collapse
Affiliation(s)
- Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, 33520 Tampere, Finland; (A.S.); (G.d.G.); (L.A.S.)
- BioMediTech Institute, Tampere University, 33520 Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), 33520 Tampere, Finland
| | - Giusy del Giudice
- Faculty of Medicine and Health Technology, Tampere University, 33520 Tampere, Finland; (A.S.); (G.d.G.); (L.A.S.)
- BioMediTech Institute, Tampere University, 33520 Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), 33520 Tampere, Finland
| | | | - Laura Aliisa Saarimäki
- Faculty of Medicine and Health Technology, Tampere University, 33520 Tampere, Finland; (A.S.); (G.d.G.); (L.A.S.)
- BioMediTech Institute, Tampere University, 33520 Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), 33520 Tampere, Finland
| | - Sarah Søs Poulsen
- National Research Centre for the Working Environment, 2100 Copenhagen, Denmark; (S.S.P.); (U.V.)
| | - Vittorio Fortino
- Institute of Biomedicine, University of Eastern Finland, 70211 Kuopio, Finland;
| | - Sabina Halappanavar
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada;
| | - Ulla Vogel
- National Research Centre for the Working Environment, 2100 Copenhagen, Denmark; (S.S.P.); (U.V.)
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, 33520 Tampere, Finland; (A.S.); (G.d.G.); (L.A.S.)
- BioMediTech Institute, Tampere University, 33520 Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), 33520 Tampere, Finland
- Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland;
- Correspondence:
| |
Collapse
|
14
|
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]
|
15
|
Kim S, White SM, Radke EG, Dean JL. Harmonization of transcriptomic and methylomic analysis in environmental epidemiology studies for potential application in chemical risk assessment. ENVIRONMENT INTERNATIONAL 2022; 164:107278. [PMID: 35537365 DOI: 10.1016/j.envint.2022.107278] [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] [Received: 03/03/2022] [Revised: 04/27/2022] [Accepted: 05/02/2022] [Indexed: 06/14/2023]
Abstract
Recent efforts have posited the utility of transcriptomic-based approaches to understand chemical-related perturbations in the context of human health risk assessment. Epigenetic modification (e.g., DNA methylation) can influence gene expression changes and is known to occur as a molecular response to some chemical exposures. Characterization of these methylation events is critical to understand the molecular consequences of chemical exposures. In this context, a novel workflow was developed to interrogate publicly available epidemiological transcriptomic and methylomic data to identify relevant pathway level changes in response to chemical exposure, using inorganic arsenic as a case study. Gene Set Enrichment Analysis (GSEA) was used to identify causal methylation events that result in concomitant downstream transcriptional deregulation. This analysis demonstrated an unequal distribution of differentially methylated regions across the human genome. After mapping these events to known genes, significant enrichment of a subset of these pathways suggested that arsenic-mediated methylation may be both specific and non-specific. Parallel GSEA performed on matched transcriptomic samples determined that a substantially reduced subset of these pathways are enriched and that not all chemically-induced methylation results in a downstream alteration in gene expression. The resulting pathways were found to be representative of well-established molecular events known to occur in response to arsenic exposure. The harmonization of enriched transcriptional patterns with those identified from the methylomic platform promoted the characterization of plausibly causal molecular signaling events. The workflow described here enables significant gene and methylation-specific pathways to be identified from whole blood samples of individuals exposed to environmentally relevant chemical levels. As future efforts solidify specific causal relationships between these molecular events and relevant apical endpoints, this novel workflow could aid risk assessments by identifying molecular targets serving as biomarkers of hazard, informing mechanistic understanding, and characterizing dose ranges that promote relevant molecular/epigenetic signaling events occuring in response to chemical exposures.
Collapse
Affiliation(s)
- Stephanie Kim
- Superfund and Emergency Management Division, Region 2, U.S. Environmental Protection Agency, NY, USA.
| | - Shana M White
- Chemical and Pollutant Assessment Division, Center for Public Health and Environmental Assessment, U.S. Environmental Protection Agency, Cincinnati, USA.
| | - Elizabeth G Radke
- Chemical and Pollutant Assessment Division, Center for Public Health and Environmental Assessment, U.S. Environmental Protection Agency, D.C., USA.
| | - Jeffry L Dean
- Chemical and Pollutant Assessment Division, Center for Public Health and Environmental Assessment, U.S. Environmental Protection Agency, Cincinnati, USA.
| |
Collapse
|
16
|
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.
Collapse
Affiliation(s)
| | | | - Valerie Marshall
- Labcorp Early Development Laboratories, Inc., Greenfield, Indiana, USA
| | | | | | | | | |
Collapse
|
17
|
Speen AM, Murray JR, Krantz QT, Davies D, Evansky P, Harrill JA, Everett LJ, Bundy JL, Dailey LA, Hill J, Zander W, Carlsten E, Monsees M, Zavala J, Higuchi MA. Benchmark Dose Modeling Approaches for Volatile Organic Chemicals using a Novel Air-Liquid Interface In Vitro Exposure System. Toxicol Sci 2022; 188:88-107. [PMID: 35426944 DOI: 10.1093/toxsci/kfac040] [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: 11/14/2022] Open
Abstract
Inhalation is the most relevant route of volatile organic chemical (VOC) exposure; however, due to unique challenges posed by their chemical properties and poor solubility in aqueous solutions, in vitro chemical safety testing is predominantly performed using direct application dosing/submerged exposures. To address the difficulties in screening toxic effects of VOCs, our cell culture exposure system permits cells to be exposed to multiple concentrations at air-liquid interface (ALI) in a 24-well format. ALI exposure methods permit direct chemical-to-cell interaction with the test article at physiological conditions. In the present study, BEAS-2B and primary normal human bronchial epithelial cells (pHBEC) are used to assess gene expression, cytotoxicity, and cell viability responses to a variety of volatile chemicals including acrolein, formaldehyde, 1,3-butadiene, acetaldehyde, 1-bromopropane, carbon tetrachloride, dichloromethane, and trichloroethylene. BEAS-2B cells were exposed to all the test agents, while pHBECs were only exposed to the latter four listed above. The VOC concentrations tested elicited only slight cell viability changes in both cell types. Gene expression changes were analyzed using benchmark dose (BMD) modeling. The BMD for the most sensitive gene set was within one order of magnitude of the threshold-limit value reported by the American Conference of Governmental Industrial Hygienists, and the most sensitive gene sets impacted by exposure correlate to known adverse health effects recorded in epidemiologic and in vivo exposure studies. Overall, our study outlines a novel in vitro approach for evaluating molecular-based points-of-departure in human airway epithelial cell exposure to volatile chemicals.
Collapse
Affiliation(s)
- Adam M Speen
- Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee 37830, USA
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Jessica R Murray
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Quentin Todd Krantz
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - David Davies
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Paul Evansky
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Joshua A Harrill
- CCTE, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Logan J Everett
- CCTE, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Joseph L Bundy
- CCTE, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Lisa A Dailey
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Jazzlyn Hill
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
- Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee 37830, USA
| | - Wyatt Zander
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
- Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee 37830, USA
| | - Elise Carlsten
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
- Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee 37830, USA
| | - Michael Monsees
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
- Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee 37830, USA
| | - Jose Zavala
- MedTec BioLab Inc., Hillsborough, North Carolina 27278, USA
| | - Mark A Higuchi
- CPHEA, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| |
Collapse
|
18
|
Chen Q, Chou WC, Lin Z. Integration of Toxicogenomics and Physiologically Based Pharmacokinetic Modeling in Human Health Risk Assessment of Perfluorooctane Sulfonate. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:3623-3633. [PMID: 35194992 DOI: 10.1021/acs.est.1c06479] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Toxicogenomics and physiologically based pharmacokinetic (PBPK) models are useful approaches in chemical risk assessment, but the methodology to incorporate toxicogenomic data into a PBPK model to inform risk assessment remains to be developed. This study aimed to develop a probabilistic human health risk assessment approach by integrating toxicogenomic dose-response data and PBPK modeling using perfluorooctane sulfonate (PFOS) as a case study. Based on the available human in vitro and mouse in vivo toxicogenomic data, we identified the differentially expressed genes (DEGs) at each exposure paradigm/duration. Kyoto Encyclopedia of Genes and Genomes and disease ontology enrichment analyses were conducted on the DEGs to identify significantly enriched pathways and diseases. The dose-response data of DEGs were analyzed using the Bayesian benchmark dose (BMD) method. Using a previously published PBPK model, the gene BMDs were converted to human equivalent doses (HEDs), which were summarized to pathway and disease HEDs and then extrapolated to reference doses (RfDs) by considering an uncertainty factor of 30 for mouse in vivo data and 10 for human in vitro data. The results suggested that the median RfDs at different exposure paradigms were similar to the 2016 U.S. Environmental Protection Agency's recommended RfD, while the RfDs for the most sensitive pathways and diseases were closer to the recent European Food Safety Authority's guidance values. In conclusion, genomic dose-response data and PBPK modeling can be integrated to become a useful alternative approach in risk assessment of environmental chemicals. This approach considers multiple endpoints, provides toxicity mechanistic insights, and does not rely on apical toxicity endpoints.
Collapse
Affiliation(s)
- Qiran Chen
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida 32610, United States
- Center for Environmental and Human Toxicology, University of Florida, Gainesville, Florida 32608, United States
| | - Wei-Chun Chou
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida 32610, United States
- Center for Environmental and Human Toxicology, University of Florida, Gainesville, Florida 32608, United States
| | - Zhoumeng Lin
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida 32610, United States
- Center for Environmental and Human Toxicology, University of Florida, Gainesville, Florida 32608, United States
| |
Collapse
|
19
|
Serra A, Saarimäki LA, Pavel A, del Giudice G, Fratello M, Cattelani L, Federico A, Laurino O, Marwah VS, Fortino V, Scala G, Sofia Kinaret PA, Greco D. Nextcast: a software suite to analyse and model toxicogenomics data. Comput Struct Biotechnol J 2022; 20:1413-1426. [PMID: 35386103 PMCID: PMC8956870 DOI: 10.1016/j.csbj.2022.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 03/16/2022] [Accepted: 03/16/2022] [Indexed: 11/28/2022] Open
Abstract
Toxicogenomics is emerging as a valid approach to characterise the mechanism of action of chemicals. Structured pipelines for toxicogenomics increase standardisation and regulatory acceptance. We developed the Nextcast software suite for robust analysis and modelling of toxicogenomic data. Nextcast offers customisable modular pipelines to tackle multiple biological questions.
The recent advancements in toxicogenomics have led to the availability of large omics data sets, representing the starting point for studying the exposure mechanism of action and identifying candidate biomarkers for toxicity prediction. The current lack of standard methods in data generation and analysis hampers the full exploitation of toxicogenomics-based evidence in regulatory risk assessment. Moreover, the pipelines for the preprocessing and downstream analyses of toxicogenomic data sets can be quite challenging to implement. During the years, we have developed a number of software packages to address specific questions related to multiple steps of toxicogenomics data analysis and modelling. In this review we present the Nextcast software collection and discuss how its individual tools can be combined into efficient pipelines to answer specific biological questions. Nextcast components are of great support to the scientific community for analysing and interpreting large data sets for the toxicity evaluation of compounds in an unbiased, straightforward, and reliable manner. The Nextcast software suite is available at: ( https://github.com/fhaive/nextcast).
Collapse
Affiliation(s)
- Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Laura Aliisa Saarimäki
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Alisa Pavel
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Giusy del Giudice
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Michele Fratello
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Luca Cattelani
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Antonio Federico
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | | | - Veer Singh Marwah
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
| | - Vittorio Fortino
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Giovanni Scala
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Department of Biology, University of Naples Federico II, Naples, Italy
| | - Pia Anneli Sofia Kinaret
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
- Corresponding author.
| |
Collapse
|
20
|
Sheffield T, Brown J, Davidson S, Friedman KP, Judson R. tcplfit2: an R-language general purpose concentration-response modeling package. Bioinformatics 2022; 38:1157-1158. [PMID: 34791027 DOI: 10.1093/bioinformatics/btab779] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 10/14/2021] [Accepted: 11/09/2021] [Indexed: 02/03/2023] Open
Abstract
SUMMARY Many applications of chemical screening are performed in concentration or dose-response mode, and it is necessary to extract appropriate parameters, including whether the chemical/assay pair is active and if so, what are concentrations where activity is seen. Typically, multiple mathematical models or curve shapes are tested against the data to assess the best fit. There are several commercial programs used for this purpose as well as open-source libraries. A widely used system for managing high-throughput screening (HTS) concentration-response data is tcpl (ToxCast Pipeline). The current implementation of tcpl has the concentration-response modeling code tightly integrated with the data management and databasing aspects of HTS data processing. Tcplfit2 is a stand-alone version of the curve-fitting and hitcalling core of tcpl that has been extended to include a large number of standard curve classes and to use benchmark dose modeling. This package will be useful for HTS concentration-response data such as high-throughput whole genome transcriptomics. AVAILABILITY AND IMPLEMENTATION tcplfit2 is written in R and is available from CRAN.
Collapse
Affiliation(s)
- Thomas Sheffield
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, USA
| | - Jason Brown
- US Environmental Protection Agency, RTP NC USA
| | | | | | | |
Collapse
|
21
|
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.
Collapse
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
| |
Collapse
|
22
|
Serra A, Fratello M, Federico A, Ojha R, Provenzani R, Tasnadi E, Cattelani L, Del Giudice G, Kinaret PAS, Saarimäki LA, Pavel A, Kuivanen S, Cerullo V, Vapalahti O, Horvath P, Lieto AD, Yli-Kauhaluoma J, Balistreri G, Greco D. Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation. Brief Bioinform 2021; 23:6484515. [PMID: 34962256 PMCID: PMC8769897 DOI: 10.1093/bib/bbab507] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 11/03/2021] [Accepted: 11/04/2021] [Indexed: 12/12/2022] Open
Abstract
The pharmacological arsenal against the COVID-19 pandemic is largely based on generic anti-inflammatory strategies or poorly scalable solutions. Moreover, as the ongoing vaccination campaign is rolling slower than wished, affordable and effective therapeutics are needed. To this end, there is increasing attention toward computational methods for drug repositioning and de novo drug design. Here, multiple data-driven computational approaches are systematically integrated to perform a virtual screening and prioritize candidate drugs for the treatment of COVID-19. From the list of prioritized drugs, a subset of representative candidates to test in human cells is selected. Two compounds, 7-hydroxystaurosporine and bafetinib, show synergistic antiviral effects in vitro and strongly inhibit viral-induced syncytia formation. Moreover, since existing drug repositioning methods provide limited usable information for de novo drug design, the relevant chemical substructures of the identified drugs are extracted to provide a chemical vocabulary that may help to design new effective drugs.
Collapse
Affiliation(s)
- Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,BioMediTech Institute, Tampere University, Tampere, Finland.,Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Michele Fratello
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,BioMediTech Institute, Tampere University, Tampere, Finland.,Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Antonio Federico
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,BioMediTech Institute, Tampere University, Tampere, Finland.,Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Ravi Ojha
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Riccardo Provenzani
- Drug Research Program, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Ervin Tasnadi
- Synthetic and Systems Biology Unit, Biological Research Centre, Eotvos Lorand Research Network, Szeged, Hungary
| | - Luca Cattelani
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,BioMediTech Institute, Tampere University, Tampere, Finland.,Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Giusy Del Giudice
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,BioMediTech Institute, Tampere University, Tampere, Finland.,Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Pia A S Kinaret
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,BioMediTech Institute, Tampere University, Tampere, Finland.,Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland.,Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Laura A Saarimäki
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,BioMediTech Institute, Tampere University, Tampere, Finland.,Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Alisa Pavel
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,BioMediTech Institute, Tampere University, Tampere, Finland.,Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Suvi Kuivanen
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Vincenzo Cerullo
- Drug Research Program, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Olli Vapalahti
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland.,Department of Virology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Peter Horvath
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.,Synthetic and Systems Biology Unit, Biological Research Centre, Eotvos Lorand Research Network, Szeged, Hungary
| | - Antonio Di Lieto
- Department of Forensic Psychiatry, Aarhus University, Aarhus, Denmark
| | - Jari Yli-Kauhaluoma
- Drug Research Program, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Giuseppe Balistreri
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,BioMediTech Institute, Tampere University, Tampere, Finland.,Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland.,Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| |
Collapse
|
23
|
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.
Collapse
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
| |
Collapse
|
24
|
Buick JK, Williams A, Meier MJ, Swartz CD, Recio L, Gagné R, Ferguson SS, Engelward BP, Yauk CL. A Modern Genotoxicity Testing Paradigm: Integration of the High-Throughput CometChip® and the TGx-DDI Transcriptomic Biomarker in Human HepaRG™ Cell Cultures. Front Public Health 2021; 9:694834. [PMID: 34485225 PMCID: PMC8416458 DOI: 10.3389/fpubh.2021.694834] [Citation(s) in RCA: 147] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 07/14/2021] [Indexed: 12/14/2022] Open
Abstract
Higher-throughput, mode-of-action-based assays provide a valuable approach to expedite chemical evaluation for human health risk assessment. In this study, we combined the high-throughput alkaline DNA damage-sensing CometChip® assay with the TGx-DDI transcriptomic biomarker (DDI = DNA damage-inducing) using high-throughput TempO-Seq®, as an integrated genotoxicity testing approach. We used metabolically competent differentiated human HepaRG™ cell cultures to enable the identification of chemicals that require bioactivation to cause genotoxicity. We studied 12 chemicals (nine DDI, three non-DDI) in increasing concentrations to measure and classify chemicals based on their ability to damage DNA. The CometChip® classified 10/12 test chemicals correctly, missing a positive DDI call for aflatoxin B1 and propyl gallate. The poor detection of aflatoxin B1 adducts is consistent with the insensitivity of the standard alkaline comet assay to bulky lesions (a shortcoming that can be overcome by trapping repair intermediates). The TGx-DDI biomarker accurately classified 10/12 agents. TGx-DDI correctly identified aflatoxin B1 as DDI, demonstrating efficacy for combined used of these complementary methodologies. Zidovudine, a known DDI chemical, was misclassified as it inhibits transcription, which prevents measurable changes in gene expression. Eugenol, a non-DDI chemical known to render misleading positive results at high concentrations, was classified as DDI at the highest concentration tested. When combined, the CometChip® assay and the TGx-DDI biomarker were 100% accurate in identifying chemicals that induce DNA damage. Quantitative benchmark concentration (BMC) modeling was applied to evaluate chemical potencies for both assays. The BMCs for the CometChip® assay and the TGx-DDI biomarker were highly concordant (within 4-fold) and resulted in identical potency rankings. These results demonstrate that these two assays can be integrated for efficient identification and potency ranking of DNA damaging agents in HepaRG™ cell cultures.
Collapse
Affiliation(s)
- Julie K Buick
- Environmental Health Science and Research 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
| | - Carol D Swartz
- Integrated Laboratory Systems Inc. (ILS), Research Triangle Park, Durham, NC, United States
| | - Leslie Recio
- Integrated Laboratory Systems Inc. (ILS), Research Triangle Park, Durham, NC, United States
| | - Rémi Gagné
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Stephen S Ferguson
- National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC, United States
| | - Bevin P Engelward
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada.,Department of Biology, University of Ottawa, Ottawa, ON, Canada
| |
Collapse
|
25
|
Lee F, Shah I, Soong YT, Xing J, Ng IC, Tasnim F, Yu H. Reproducibility and robustness of high-throughput S1500+ transcriptomics on primary rat hepatocytes for chemical-induced hepatotoxicity assessment. Curr Res Toxicol 2021; 2:282-295. [PMID: 34467220 PMCID: PMC8384775 DOI: 10.1016/j.crtox.2021.07.003] [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: 03/22/2021] [Revised: 07/15/2021] [Accepted: 07/31/2021] [Indexed: 11/06/2022] Open
Abstract
TempO-Seq assays of rat hepatocytes in collagen sandwich are highly reproducible. Gene expression analysis shows S1500+ is representative of the whole transcriptome. Connectivity mapping shows consistency between TempO-Seq and Affymetrix data. Gene set enrichment shows consistency between S1500+ and the whole transcriptome. Gene set enrichment using hallmark gene sets informs hepatotoxicity.
Cell-based in vitro models coupled with high-throughput transcriptomics (HTTr) are increasingly utilized as alternative methods to animal-based toxicity testing. Here, using a panel of 14 chemicals with different risks of human drug-induced liver injury (DILI) and two dosing concentrations, we evaluated an HTTr platform comprised of collagen sandwich primary rat hepatocyte culture and the TempO-Seq surrogate S1500+ (ST) assay. First, the HTTr platform was found to exhibit high reproducibility between technical and biological replicates (r greater than 0.85). Connectivity mapping analysis further demonstrated a high level of inter-platform reproducibility between TempO-Seq data and Affymetrix GeneChip data from the Open TG-GATES project. Second, the TempO-Seq ST assay was shown to be a robust surrogate to the whole transcriptome (WT) assay in capturing chemical-induced changes in gene expression, as evident from correlation analysis, PCA and unsupervised hierarchical clustering. Gene set enrichment analysis (GSEA) using the Hallmark gene set collection also demonstrated consistency in enrichment scores between ST and WT assays. Lastly, unsupervised hierarchical clustering of hallmark enrichment scores broadly divided the samples into hepatotoxic, intermediate, and non-hepatotoxic groups. Xenobiotic metabolism, bile acid metabolism, apoptosis, p53 pathway, and coagulation were found to be the key hallmarks driving the clustering. Taken together, our results established the reproducibility and performance of collagen sandwich culture in combination with TempO-Seq S1500+ assay, and demonstrated the utility of GSEA using the hallmark gene set collection to identify potential hepatotoxicants for further validation.
Collapse
Affiliation(s)
- Fan Lee
- Innovations in Food & Chemical Safety Program (IFCS), Institute of Bioengineering and Bioimaging (IBB), Agency for Science Technology and Research, Singapore
| | - Imran Shah
- Center for Computational Toxicology & Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, United States
| | - Yun Ting Soong
- Innovations in Food & Chemical Safety Program (IFCS), Institute of Bioengineering and Bioimaging (IBB), Agency for Science Technology and Research, Singapore
| | - Jiangwa Xing
- Innovations in Food & Chemical Safety Program (IFCS), Institute of Bioengineering and Bioimaging (IBB), Agency for Science Technology and Research, Singapore
| | - Inn Chuan Ng
- Department of Physiology and Mechanobiology Institute, National University of Singapore, Singapore
| | - Farah Tasnim
- Innovations in Food & Chemical Safety Program (IFCS), Institute of Bioengineering and Bioimaging (IBB), Agency for Science Technology and Research, Singapore
| | - Hanry Yu
- Innovations in Food & Chemical Safety Program (IFCS), Institute of Bioengineering and Bioimaging (IBB), Agency for Science Technology and Research, Singapore.,Department of Physiology and Mechanobiology Institute, National University of Singapore, Singapore.,Critical Analytics for Manufacturing Personalized-Medicine, Singapore-MIT Alliance for Research and Technology, Singapore
| |
Collapse
|
26
|
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.
Collapse
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.
| |
Collapse
|
27
|
Thompson CM, Gentry R, Fitch S, Lu K, Clewell HJ. An updated mode of action and human relevance framework evaluation for Formaldehyde-Related nasal tumors. Crit Rev Toxicol 2021; 50:919-952. [PMID: 33599198 DOI: 10.1080/10408444.2020.1854679] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Formaldehyde is a reactive aldehyde naturally present in all plant and animal tissues and a critical component of the one-carbon metabolism pathway. It is also a high production volume chemical used in the manufacture of numerous products. Formaldehyde is also one of the most well-studied chemicals with respect to environmental fate, biology, and toxicology-including carcinogenic potential, and mode of action (MOA). In 2006, a published MOA for formaldehyde-induced nasal tumors in rats concluded that nasal tumors were most likely driven by cytotoxicity and regenerative cell proliferation, with possible contributions from direct genotoxicity. In the past 15 years, new research has better informed the MOA with the publication of in vivo genotoxicity assays, toxicogenomic analyses, and development of ultra-sensitive methods to measure endogenous and exogenous formaldehyde-induced DNA adducts. Herein, we review and update the MOA for nasal tumors, with particular emphasis on the numerous studies published since 2006. These new studies further underscore the involvement of cytotoxicity and regenerative cell proliferation, and further inform the genotoxic potential of inhaled formaldehyde. The data lend additional support for the use of mechanistic data for the derivation of toxicity criteria and/or scientifically supported approaches for low-dose extrapolation for the risk assessment of formaldehyde.
Collapse
Affiliation(s)
| | | | | | - Kun Lu
- Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, NC, USA
| | | |
Collapse
|
28
|
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.
Collapse
Affiliation(s)
- Joshua A Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Logan J Everett
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Derik E Haggard
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA.,Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee, USA
| | - Thomas Sheffield
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA.,Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, Tennessee, USA
| | - Joseph L Bundy
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Clinton M Willis
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA.,Oak Ridge Associated Universities (ORAU), Oak Ridge, Tennessee, USA
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Imran Shah
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| | - Richard S Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, USA
| |
Collapse
|
29
|
Schüttler A, Jakobs G, Fix J, Krauss M, Krüger J, Leuthold D, Altenburger R, Busch W. Transcriptome-Wide Prediction and Measurement of Combined Effects Induced by Chemical Mixture Exposure in Zebrafish Embryos. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:47006. [PMID: 33826412 PMCID: PMC8041271 DOI: 10.1289/ehp7773] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
BACKGROUND Humans and environmental organisms are constantly exposed to complex mixtures of chemicals. Extending our knowledge about the combined effects of chemicals is thus essential for assessing the potential consequences of these exposures. In this context, comprehensive molecular readouts as retrieved by omics techniques are advancing our understanding of the diversity of effects upon chemical exposure. This is especially true for effects induced by chemical concentrations that do not instantaneously lead to mortality, as is commonly the case for environmental exposures. However, omics profiles induced by chemical exposures have rarely been systematically considered in mixture contexts. OBJECTIVES In this study, we aimed to investigate the predictability of chemical mixture effects on the whole-transcriptome scale. METHODS We predicted and measured the toxicogenomic effects of a synthetic mixture on zebrafish embryos. The mixture contained the compounds diuron, diclofenac, and naproxen. To predict concentration- and time-resolved whole-transcriptome responses to the mixture exposure, we adopted the mixture concept of concentration addition. Predictions were based on the transcriptome profiles obtained for the individual mixture components in a previous study. Finally, concentration- and time-resolved mixture exposures and subsequent toxicogenomic measurements were performed and the results were compared with the predictions. RESULTS This comparison of the predictions with the observations showed that the concept of concentration addition provided reasonable estimates for the effects induced by the mixture exposure on the whole transcriptome. Although nonadditive effects were observed only occasionally, combined, that is, multicomponent-driven, effects were found for mixture components with anticipated similar, as well as dissimilar, modes of action. DISCUSSION Overall, this study demonstrates that using a concentration- and time-resolved approach, the occurrence and size of combined effects of chemicals may be predicted at the whole-transcriptome scale. This allows improving effect assessment of mixture exposures on the molecular scale that might not only be of relevance in terms of risk assessment but also for pharmacological applications. https://doi.org/10.1289/EHP7773.
Collapse
Affiliation(s)
- A. Schüttler
- Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
- Institute for Environmental Research, Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany
| | - G. Jakobs
- Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
| | - J.M. Fix
- Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
| | - M. Krauss
- Department Effect-Directed Analysis, UFZ, Leipzig, Germany
| | - J. Krüger
- Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
| | - D. Leuthold
- Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
| | - R. Altenburger
- Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
- Institute for Environmental Research, Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany
| | - W. Busch
- Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
| |
Collapse
|
30
|
Olesti E, González-Ruiz V, Wilks MF, Boccard J, Rudaz S. Approaches in metabolomics for regulatory toxicology applications. Analyst 2021; 146:1820-1834. [PMID: 33605958 DOI: 10.1039/d0an02212h] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Innovative methodological approaches are needed to conduct human health and environmental risk assessments on a growing number of marketed chemicals. Metabolomics is progressively proving its value as an efficient strategy to perform toxicological evaluations of new and existing substances, and it will likely become a key tool to accelerate chemical risk assessments. However, additional guidance with widely accepted and harmonized procedures is needed before metabolomics can be routinely incorporated in decision-making for regulatory purposes. The aim of this review is to provide an overview of metabolomic strategies that have been successfully employed in toxicity assessment as well as the most promising workflows in a regulatory context. First, we provide a general view of the different steps of regulatory toxicology-oriented metabolomics. Emphasis is put on three key elements: robustness of experimental design, choice of analytical platform, and use of adapted data treatment tools. Then, examples in which metabolomics supported regulatory toxicology outputs in different scenarios are reviewed, including chemical grouping, elucidation of mechanisms of toxicity, and determination of points of departure. The overall intention is to provide insights into why and how to plan and conduct metabolomic studies for regulatory toxicology purposes.
Collapse
Affiliation(s)
- Eulalia Olesti
- School of Pharmaceutical Sciences, University of Geneva, Switzerland.
| | | | | | | | | |
Collapse
|
31
|
Martínez R, Codina AE, Barata C, Tauler R, Piña B, Navarro-Martín L. Transcriptomic effects of tributyltin (TBT) in zebrafish eleutheroembryos. A functional benchmark dose analysis. JOURNAL OF HAZARDOUS MATERIALS 2020; 398:122881. [PMID: 32474318 DOI: 10.1016/j.jhazmat.2020.122881] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 04/03/2020] [Accepted: 05/04/2020] [Indexed: 06/11/2023]
Abstract
Exposure to the antifouling tributyltin (TBT) has been related to imposex in mollusks and to obesogenicity, adipogenesis and masculinization in fish. To understand the underlying molecular mechanisms, we evaluated dose-response effects of TBT (1.7-56 nM) in zebrafish eleutheroembryos transcriptome exposed from 2 to 5 days post-fertilization. RNA-sequencing analysis identified 3238 differentially expressed transcripts in eleutheroembryos exposed to TBT. Benchmark dose analyses (BMD) showed that the point of departure (PoD) for transcriptomic effects (9.28 nM) was similar to the metabolomic PoD (11.5 nM) and about one order of magnitude lower than the morphometric PoD (67.9 nM) or the median lethal concentration (LC50: 93.6 nM). Functional analysis of BMD transcriptomic data identified steroid metabolism and cholesterol and vitamin D3 biosynthesis as the most sensitive pathways to TBT (<50% PoD). Conversely, transcripts related to general stress and DNA damage became affected only at doses above the PoD. Therefore, our results indicate that transcriptomes can act as early molecular indicators of pollutant exposure, and illustrates their usefulness for the mechanistic identification of the initial toxic events. As the estimated molecular PoDs are close to environmental levels, we concluded that TBT may represent a substantial risk in some natural environments.
Collapse
Affiliation(s)
- Rubén Martínez
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain; Universitat de Barcelona (UB), Barcelona, Catalunya 08007, Spain.
| | - Anna E Codina
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain; Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.
| | - Carlos Barata
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
| | - Romà Tauler
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
| | - Benjamin Piña
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
| | - Laia Navarro-Martín
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
| |
Collapse
|
32
|
Shockley KR, Cora MC, Malarkey DE, Jackson-Humbles D, Vallant M, Collins BJ, Mutlu E, Robinson VG, Waidyanatha S, Zmarowski A, Machesky N, Richey J, Harbo S, Cheng E, Patton K, Sparrow B, Dunnick JK. Comparative toxicity and liver transcriptomics of legacy and emerging brominated flame retardants following 5-day exposure in the rat. Toxicol Lett 2020; 332:222-234. [PMID: 32679240 PMCID: PMC7903589 DOI: 10.1016/j.toxlet.2020.07.016] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 07/06/2020] [Accepted: 07/11/2020] [Indexed: 12/13/2022]
Abstract
The relative toxicity of three legacy and six emerging brominated flame retardants* was studied in the male Harlan Sprague Dawley rat. The hepatocellular and thyroid toxicity of each flame retardant was evaluated following five-day exposure to each of the nine flame retardants (oral gavage in corn oil) at 0.1-1000 μmol/kg body weight per day. Histopathology and transcriptomic analysis were performed on the left liver lobe. Centrilobular hypertrophy of hepatocytes and increases in liver weight were seen following exposure to two legacy (PBDE-47, HBCD) and to one emerging flame retardant (HCDBCO). Total thyroxine (TT4) concentrations were reduced to the greatest extent after PBDE-47 exposure. The PBDE-47, decaBDE, and HBCD liver transcriptomes were characterized by upregulation of liver disease-related and/or metabolic transcripts. Fewer liver disease or metabolic transcript changes were detected for the other flame retardants studied (TBB, TBPH, TBBPA-DBPE, BTBPE, DBDPE, or HCDBCO). PBDE-47 exhibited the most disruption of hepatocellular toxic endpoints, with the Nrf2 antioxidant pathway transcripts upregulated to the greatest extent, although some activation of this pathway also occurred after decaBDE, HBCD, TBB, and HCBCO exposure. These studies provide information that can be used for prioritizing the need for more in-depth brominated flame retardant toxicity studies.
Collapse
Affiliation(s)
- Keith R Shockley
- Biostatistics & Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
| | - Michelle C Cora
- Cellular & Molecular Pathology Branch, National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
| | - David E Malarkey
- Cellular & Molecular Pathology Branch, National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
| | - Daven Jackson-Humbles
- Cellular & Molecular Pathology Branch, National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
| | - Molly Vallant
- Program Operations Branch, National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
| | - Brad J Collins
- Program Operations Branch, National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
| | - Esra Mutlu
- Program Operations Branch, National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
| | - Veronica G Robinson
- Program Operations Branch, National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
| | - Surayma Waidyanatha
- Program Operations Branch, National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States
| | | | | | | | - Sam Harbo
- Battelle, Columbus, Ohio, 43210, United States
| | - Emily Cheng
- Battelle, Columbus, Ohio, 43210, United States
| | | | | | - June K Dunnick
- Toxicology Branch, National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, United States.
| |
Collapse
|
33
|
Serra A, Saarimäki LA, Fratello M, Marwah VS, Greco D. BMDx: a graphical Shiny application to perform Benchmark Dose analysis for transcriptomics data. Bioinformatics 2020; 36:2932-2933. [PMID: 31950985 DOI: 10.1093/bioinformatics/btaa030] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 12/16/2019] [Accepted: 01/14/2020] [Indexed: 01/21/2023] Open
Abstract
MOTIVATION The analysis of dose-dependent effects on the gene expression is gaining attention in the field of toxicogenomics. Currently available computational methods are usually limited to specific omics platforms or biological annotations and are able to analyse only one experiment at a time. RESULTS We developed the software BMDx with a graphical user interface for the Benchmark Dose (BMD) analysis of transcriptomics data. We implemented an approach based on the fitting of multiple models and the selection of the optimal model based on the Akaike Information Criterion. The BMDx tool takes as an input a gene expression matrix and a phenotype table, computes the BMD, its related values, and IC50/EC50 estimations. It reports interactive tables and plots that the user can investigate for further details of the fitting, dose effects and functional enrichment. BMDx allows a fast and convenient comparison of the BMD values of a transcriptomics experiment at different time points and an effortless way to interpret the results. Furthermore, BMDx allows to analyse and to compare multiple experiments at once. AVAILABILITY AND IMPLEMENTATION BMDx is implemented as an R/Shiny software and is available at https://github.com/Greco-Lab/BMDx/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, Tampere 33100, Finland.,BioMediTech Institute, Tampere University, Tampere 33100, Finland
| | - Laura Aliisa Saarimäki
- Faculty of Medicine and Health Technology, Tampere University, Tampere 33100, Finland.,BioMediTech Institute, Tampere University, Tampere 33100, Finland
| | - Michele Fratello
- Faculty of Medicine and Health Technology, Tampere University, Tampere 33100, Finland.,BioMediTech Institute, Tampere University, Tampere 33100, Finland
| | - Veer Singh Marwah
- Faculty of Medicine and Health Technology, Tampere University, Tampere 33100, Finland.,BioMediTech Institute, Tampere University, Tampere 33100, Finland
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, Tampere 33100, Finland.,BioMediTech Institute, Tampere University, Tampere 33100, Finland.,Institute of Biotechnology, University of Helsinki, Helsinki 00014, Finland
| |
Collapse
|
34
|
Larras F, Billoir E, Scholz S, Tarkka M, Wubet T, Delignette-Muller ML, Schmitt-Jansen M. A multi-omics concentration-response framework uncovers novel understanding of triclosan effects in the chlorophyte Scenedesmus vacuolatus. JOURNAL OF HAZARDOUS MATERIALS 2020; 397:122727. [PMID: 32361673 DOI: 10.1016/j.jhazmat.2020.122727] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 03/28/2020] [Accepted: 04/11/2020] [Indexed: 05/27/2023]
Abstract
In aquatic ecosystems, the biocide triclosan represents a hazard for the non-target microalgae. So far, algal responses were mainly investigated at apical levels hampering the acquisition of a holistic view on primary, adaptive, and compensatory stress responses. We assessed responses of the chlorophyte Scenedesmus vacuolatus to triclosan at apical (growth, photosynthesis) and molecular (transcriptome, metabolome) levels for comparative pathway sensitivity analysis. For each responsive signal (contigs, metabolites), a concentration-response curve was modeled and effect concentrations were calculated leading to the setting of cumulative sensitivity distributions. Molecular responses showed higher sensitivity than apical observations. The functional annotation of contigs and metabolites revealed 118 metabolic pathways putatively impaired by triclosan, highlighting a wide repercussion on the algal metabolism. Metabolites involved in the lipid metabolism showed decreasing trends along the concentration gradient and a globally highest sensitivity, pointing to the primary target of triclosan. The pathways involved in xenobiotic degradation and membrane transporters were mainly regulated in the transcriptome with increasing response trends comprising compensatory responses. The suggested novel approach, combining apical and multi-omics analyses in a concentration-response framework improves mechanistic understanding and mode of action analysis on non-targeted organisms and is suggested to better implement high-throughput multi-omics data in environmental risk assessment.
Collapse
Affiliation(s)
- Floriane Larras
- Helmholtz-Centre for Environmental Research - UFZ, Department of Bioanalytical Ecotoxicology, Permoserstrasse 15, 04318 Leipzig, Germany.
| | - Elise Billoir
- Université de Lorraine, CNRS, LIEC, F-57000 Metz, France
| | - Stefan Scholz
- Helmholtz-Centre for Environmental Research - UFZ, Department of Bioanalytical Ecotoxicology, Permoserstrasse 15, 04318 Leipzig, Germany
| | - Mika Tarkka
- Department of Soil Ecology, Helmholtz-Centre for Environmental Research - UFZ, Theodor-Lieser-Straße 4, 06120 Halle, Germany; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany
| | - Tesfaye Wubet
- Department of Community Ecology, Helmholtz-Centre for Environmental Research - UFZ, Theodor-Lieser-Straße 4, 06120 Halle, Germany; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany
| | - Marie-Laure Delignette-Muller
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, 69622 Villeurbanne, France
| | - Mechthild Schmitt-Jansen
- Helmholtz-Centre for Environmental Research - UFZ, Department of Bioanalytical Ecotoxicology, Permoserstrasse 15, 04318 Leipzig, Germany.
| |
Collapse
|
35
|
Nyffeler J, Haggard DE, Willis C, Setzer RW, Judson R, Paul-Friedman K, Everett LJ, Harrill JA. Comparison of Approaches for Determining Bioactivity Hits from High-Dimensional Profiling Data. SLAS DISCOVERY 2020; 26:292-308. [PMID: 32862757 DOI: 10.1177/2472555220950245] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Phenotypic profiling assays are untargeted screening assays that measure a large number (hundreds to thousands) of cellular features in response to a stimulus and often yield diverse and unanticipated profiles of phenotypic effects, leading to challenges in distinguishing active from inactive treatments. Here, we compare a variety of different strategies for hit identification in imaging-based phenotypic profiling assays using a previously published Cell Painting data set. Hit identification strategies based on multiconcentration analysis involve curve fitting at several levels of data aggregation (e.g., individual feature level, aggregation of similarly derived features into categories, and global modeling of all features) and on computed metrics (e.g., Euclidean and Mahalanobis distance metrics and eigenfeatures). Hit identification strategies based on single-concentration analysis included measurement of signal strength (e.g., total effect magnitude) and correlation of profiles among biological replicates. Modeling parameters for each approach were optimized to retain the ability to detect a reference chemical with subtle phenotypic effects while limiting the false-positive rate to 10%. The percentage of test chemicals identified as hits was highest for feature-level and category-based approaches, followed by global fitting, whereas signal strength and profile correlation approaches detected the fewest number of active hits at the fixed false-positive rate. Approaches involving fitting of distance metrics had the lowest likelihood for identifying high-potency false-positive hits that may be associated with assay noise. Most of the methods achieved a 100% hit rate for the reference chemical and high concordance for 82% of test chemicals, indicating that hit calls are robust across different analysis approaches.
Collapse
Affiliation(s)
- Johanna Nyffeler
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA.,Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, USA
| | - Derik E Haggard
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA.,Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, USA
| | - Clinton Willis
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA.,Oak Ridge Associated Universities (ORAU), Oak Ridge, TN, USA
| | - R Woodrow Setzer
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA
| | - Richard Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA
| | - Katie Paul-Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA
| | - Logan J Everett
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA
| | - Joshua A Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC, USA
| |
Collapse
|
36
|
Johnson KJ, Auerbach SS, Costa E. A Rat Liver Transcriptomic Point of Departure Predicts a Prospective Liver or Non-liver Apical Point of Departure. Toxicol Sci 2020; 176:86-102. [PMID: 32384157 PMCID: PMC7357187 DOI: 10.1093/toxsci/kfaa062] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Identifying a toxicity point of departure (POD) is a required step in human health risk characterization of crop protection molecules, and this POD has historically been derived from apical endpoints across a battery of animal-based toxicology studies. Using rat transcriptome and apical data for 79 molecules obtained from Open TG-GATES (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System) (632 datasets), the hypothesis was tested that a short-term exposure, transcriptome-based liver biological effect POD (BEPOD) could estimate a longer-term exposure "systemic" apical endpoint POD. Apical endpoints considered were body weight, clinical observation, kidney weight and histopathology and liver weight and histopathology. A BMDExpress algorithm using Gene Ontology Biological Process gene sets was optimized to derive a liver BEPOD most predictive of a systemic apical POD. Liver BEPODs were stable from 3 h to 29 days of exposure; the median fold difference of the 29-day BEPOD to BEPODs from earlier time points was approximately 1 (range: 0.7-1.1). Strong positive correlation (Pearson R = 0.86) and predictive accuracy (root mean square difference = 0.41) were observed between a concurrent (29 days) liver BEPOD and the systemic apical POD. Similar Pearson R and root mean square difference values were observed for comparisons between a 29-day systemic apical POD and liver BEPODs derived from 3 h to 15 days of exposure. These data across 79 molecules suggest that a longer-term exposure study apical POD from liver and non-liver compartments can be estimated using a liver BEPOD derived from an acute or subacute exposure study.
Collapse
Affiliation(s)
- Kamin J Johnson
- Predictive Safety Center, Corteva Agriscience, Indianapolis, Indiana
| | - Scott S Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina
| | - Eduardo Costa
- Data Science and Informatics, Corteva Agriscience, Mogi Mirim, Sao Paulo, Brazil
| |
Collapse
|
37
|
Early microRNA indicators of PPARα pathway activation in the liver. Toxicol Rep 2020; 7:805-815. [PMID: 32642447 PMCID: PMC7334544 DOI: 10.1016/j.toxrep.2020.06.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 06/01/2020] [Accepted: 06/19/2020] [Indexed: 12/29/2022] Open
Abstract
MicroRNAs (miRNAs) are short non-coding RNA species that play key roles in post-transcriptional regulation of gene expression. MiRNAs also serve as a promising source of early biomarkers for different environmental exposures and health effects, although there is limited information linking miRNA changes to specific target pathways. In this study, we measured liver miRNAs in male B6C3F1 mice exposed to a known chemical activator of the peroxisome proliferator-activated receptor alpha (PPARα) pathway, di(2-ethylhexyl) phthalate (DEHP), for 7 and 28 days at concentrations of 0, 750, 1500, 3000, or 6000 ppm in feed. At the highest dose tested, DEHP altered 61 miRNAs after 7 days and 171 miRNAs after 28 days of exposure, with 48 overlapping miRNAs between timepoints. Analysis of these 48 common miRNAs indicated enrichment in PPARα–related targets and other pathways related to liver injury and cancer. Four of the 10 miRNAs exhibiting a clear dose trend were linked to the PPARα pathway: mmu-miRs-125a-5p, -182−5p, -20a−5p, and -378a−3p. mmu-miRs-182−5p and -378a−3p were subsequently measured using digital drop PCR across a dose range for DEHP and two related phthalates with weaker PPARα activity, di-n-octyl phthalate and n-butyl benzyl phthalate, following 7-day exposures. Analysis of mmu-miRs-182−5p and -378a−3p by transcriptional benchmark dose analysis correctly identified DEHP as having the greatest potency. However, benchmark dose estimates for DEHP based on these miRNAs (average 163; range 126−202 mg/kg-day) were higher on average than values for PPARα target genes (average 74; range 29−183 mg/kg-day). These findings identify putative miRNA biomarkers of PPARα pathway activity and suggest that early miRNA changes may be used to stratify chemical potency.
Collapse
Key Words
- AIC, Akaike Information Criterion
- ALT, alanine aminotransferase
- AOP, adverse outcome pathway
- AST, aspartate aminotransferase
- Acox1, acyl-Coenzyme A oxidase 1
- Adverse outcome pathway (AOP)
- AhR, aryl hydrocarbon receptor
- BBP, n-butyl benzyl phthalate
- BMD, benchmark dose
- BMDA, apical-based benchmark dose
- BMDL, BMD lower confidence interval
- BMDT, transcriptional-based benchmark dose
- BMR, benchmark response
- BROD, benzyloxyresorufin O-debenzylation
- Benchmark dose (BMD)
- Biomarkers
- CAR, constitutive androstane receptor
- DEGs, differentially expressed genes
- DEHP, di (2-thylhexyl) phthalate
- DEmiRs, differentially expressed miRNAs
- DNOP, di-n-octyl phthalate
- EPA, U.S. Environmental Protection Agency
- EROD, ethoxyresorufin O-dealkylation
- GEO, Gene Expression Omnibus
- HCA, hepatocellular adenoma
- HCC, hepatocellular carcinoma
- Hepatocellular carcinoma
- IPA, Ingenuity Pathway Analysis
- Liver toxicity
- MOA, mode of action
- MicroRNAs
- Mode of action (MOA)
- Nrf2, nuclear receptor erythroid 2-like 2
- POD, point-of-departure
- PPARα, peroxisome proliferator-activated receptor alpha
- PROD, pentoxyresorufin O-depentylation
- PXR, pregnane X receptor
- Peroxisome proliferator-activated receptor alpha (PPARα)
- Phthalate
- SDH, sorbitol dehydrogenase
- TMM, trimmed mean of M-values
- ddPCR, droplet digital polymerase chain reaction
- mRNA, messenger RNA
- miRNAs, microRNAs
- mtDNA, mitochondrial
- rRNA, ribosomal RNA
- smallRNA-seq, small RNA sequencing
- tRNA, transfer RNA
Collapse
|
38
|
Fang W, Peng Y, Yan L, Xia P, Zhang X. A Tiered Approach for Screening and Assessment of Environmental Mixtures by Omics and In Vitro Assays. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:7430-7439. [PMID: 32401503 DOI: 10.1021/acs.est.0c00662] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
New methodology approaches with a broad coverage of the biological effects are urgently needed to evaluate the safety of the universe of environmentally relevant chemicals. Here, we propose a tiered approach incorporating transcriptomics and in vitro bioassays to assess environmental mixtures. The mixture samples and the perturbed biological pathways are prioritized by concentration-dependent transcriptome (CDT) and then used to guide the selection of in vitro bioassays for toxicant identification. To evaluate omics' screening capability, we first applied a CDT technique to test mixture samples by HepG2 and MCF7 cells. The effect recoveries of large-volume solid-phase extraction on the overall bioactivity of the mixture were 48.9% in HepG2 and 58.3% in MCF7. The overall bioactivity potencies obtained by transcriptomics were positively correlated with the panel of 8 bioassays among 14 mixture samples combined with the previous data. Transcriptomics could predict their activation status (AUC = 0.783) and the relative potency (p < 0.05) of bioassays for four of the eight receptors (AhR, ER, AR, and Nrf2). Furthermore, the CDT identified other biological pathways perturbated by mixture samples, such as the pathway related to TP53, CAR, FXR, HIF, THRA, etc. Overall, this study demonstrates the potential of concentration-dependent omics for effect-based water quality assessment.
Collapse
Affiliation(s)
- Wendi Fang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China, 210023
| | - Ying Peng
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China, 210023
| | - Lu Yan
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China, 210023
| | - Pu Xia
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China, 210023
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China, 210023
| |
Collapse
|
39
|
Mezencev R, Auerbach SS. The sensitivity of transcriptomics BMD modeling to the methods used for microarray data normalization. PLoS One 2020; 15:e0232955. [PMID: 32413060 PMCID: PMC7228135 DOI: 10.1371/journal.pone.0232955] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 04/25/2020] [Indexed: 11/25/2022] Open
Abstract
Whole-genome expression data generated by microarray studies have shown promise for quantitative human health risk assessment. While numerous approaches have been developed to determine benchmark doses (BMDs) from probeset-level dose responses, sensitivity of the results to methods used for normalization of the data has not yet been systematically investigated. Normalization of microarray data converts raw hybridization signals to expression estimates that are expected to be proportional to the amounts of transcripts in the profiled specimens. Different approaches to normalization have been shown to greatly influence the results of some downstream analyses, including biological interpretation. In this study we evaluate the influence of microarray normalization methods on the transcriptomic BMDs. We demonstrate using in vivo data that the use of alternative pipelines for normalization of Affymetrix microarray data can have a considerable impact on the number of detected differentially expressed genes and pathways (processes) determined to be treatment responsive, which may lead to alternative interpretations of the data. In addition, we found that normalization can have a considerable effect (as much as ~30-fold in this study) on estimation of the minimum biological potency (transcriptomic point of departure). We argue for consideration of alternative normalization methods and their data-informed selection to most effectively interpret microarray data for use in human health risk assessment.
Collapse
Affiliation(s)
- Roman Mezencev
- Center for Public Health and Environmental Assessment, Office of Research and Development, US EPA, Washington DC, United States of America
| | - Scott S. Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, Durham, NC, United States of America
| |
Collapse
|
40
|
Serra A, Fratello M, del Giudice G, Saarimäki LA, Paci M, Federico A, Greco D. TinderMIX: Time-dose integrated modelling of toxicogenomics data. Gigascience 2020; 9:giaa055. [PMID: 32449777 PMCID: PMC7247400 DOI: 10.1093/gigascience/giaa055] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 04/22/2020] [Accepted: 05/05/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Omics technologies have been widely applied in toxicology studies to investigate the effects of different substances on exposed biological systems. A classical toxicogenomic study consists in testing the effects of a compound at different dose levels and different time points. The main challenge consists in identifying the gene alteration patterns that are correlated to doses and time points. The majority of existing methods for toxicogenomics data analysis allow the study of the molecular alteration after the exposure (or treatment) at each time point individually. However, this kind of analysis cannot identify dynamic (time-dependent) events of dose responsiveness. RESULTS We propose TinderMIX, an approach that simultaneously models the effects of time and dose on the transcriptome to investigate the course of molecular alterations exerted in response to the exposure. Starting from gene log fold-change, TinderMIX fits different integrated time and dose models to each gene, selects the optimal one, and computes its time and dose effect map; then a user-selected threshold is applied to identify the responsive area on each map and verify whether the gene shows a dynamic (time-dependent) and dose-dependent response; eventually, responsive genes are labelled according to the integrated time and dose point of departure. CONCLUSIONS To showcase the TinderMIX method, we analysed 2 drugs from the Open TG-GATEs dataset, namely, cyclosporin A and thioacetamide. We first identified the dynamic dose-dependent mechanism of action of each drug and compared them. Our analysis highlights that different time- and dose-integrated point of departure recapitulates the toxicity potential of the compounds as well as their dynamic dose-dependent mechanism of action.
Collapse
Affiliation(s)
- Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
- BioMediTech Institute, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
| | - Michele Fratello
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
- BioMediTech Institute, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
| | - Giusy del Giudice
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
- BioMediTech Institute, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
| | - Laura Aliisa Saarimäki
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
- BioMediTech Institute, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
| | - Michelangelo Paci
- BioMediTech Institute, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
| | - Antonio Federico
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
- BioMediTech Institute, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
- BioMediTech Institute, Tampere University, Arvo Ylpön katu 34, 33520, Tampere, Finland
- Institute of Biotechnology, University of Helsinki, Viikinkaari 5, 00014, Helsinki, Finland
| |
Collapse
|
41
|
Wei F, Wang D, Li H, Xia P, Ran Y, You J. Toxicogenomics provides insights to toxicity pathways of neonicotinoids to aquatic insect, Chironomus dilutus. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 260:114011. [PMID: 31991362 DOI: 10.1016/j.envpol.2020.114011] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Revised: 01/03/2020] [Accepted: 01/16/2020] [Indexed: 06/10/2023]
Abstract
Neonicotinoid insecticides have posed a great threat to non-target organisms, yet the mechanisms underlying their toxicity are not well characterized. Major modes of action (MoAs) of imidacloprid were analyzed in an aquatic insect Chironomus dilutus. Lethal and sublethal outcomes were assessed in the midges after 96-h exposure to imidacloprid. Global transcriptomic profiles were determined using de novo RNA-sequencing to more holistically identify toxicity pathways. Transcriptional 10% biological potency values derived from ranked KEGG pathways and GO terms were 0.02 (0.01-0.08) (mean (95% confidence interval) and 0.05 (0.04-0.06) μg L-1, respectively, which were more sensitive than those from phenotypic traits (10% lethal concentration: 0.44 (0.23-0.79) μg L-1; 10% burrowing behavior concentration: 0.30 (0.22-0.43) μg L-1). Major MoAs of imidacloprid in aquatic species were identified as follows: the activation of nicotinic acetylcholine receptors (nAChRs) induced by imidacloprid impaired organisms' nerve system through calcium ion homeostasis imbalance and mitochondrial dysfunction, which posed oxidative stress and DNA damage and eventually caused death of organisms. The current investigation highlighted that imidacloprid affected C. dilutus at environmentally relevant concentrations, and elucidated toxicity pathways derived from gene alteration to individual outcomes, calling for more attention to toxicity of neonicotinoids to aquatic organisms.
Collapse
Affiliation(s)
- Fenghua Wei
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China; Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Dali Wang
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China
| | - Huizhen Li
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China
| | - Pu Xia
- Department of Biology, University of Ottawa, Ontario, K1N 6N5, Canada
| | - Yong Ran
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China
| | - Jing You
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China.
| |
Collapse
|
42
|
Serra A, Fratello M, Cattelani L, Liampa I, Melagraki G, Kohonen P, Nymark P, Federico A, Kinaret PAS, Jagiello K, Ha MK, Choi JS, Sanabria N, Gulumian M, Puzyn T, Yoon TH, Sarimveis H, Grafström R, Afantitis A, Greco D. Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment. NANOMATERIALS (BASEL, SWITZERLAND) 2020; 10:E708. [PMID: 32276469 PMCID: PMC7221955 DOI: 10.3390/nano10040708] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 12/30/2022]
Abstract
Transcriptomics data are relevant to address a number of challenges in Toxicogenomics (TGx). After careful planning of exposure conditions and data preprocessing, the TGx data can be used in predictive toxicology, where more advanced modelling techniques are applied. The large volume of molecular profiles produced by omics-based technologies allows the development and application of artificial intelligence (AI) methods in TGx. Indeed, the publicly available omics datasets are constantly increasing together with a plethora of different methods that are made available to facilitate their analysis, interpretation and the generation of accurate and stable predictive models. In this review, we present the state-of-the-art of data modelling applied to transcriptomics data in TGx. We show how the benchmark dose (BMD) analysis can be applied to TGx data. We review read across and adverse outcome pathways (AOP) modelling methodologies. We discuss how network-based approaches can be successfully employed to clarify the mechanism of action (MOA) or specific biomarkers of exposure. We also describe the main AI methodologies applied to TGx data to create predictive classification and regression models and we address current challenges. Finally, we present a short description of deep learning (DL) and data integration methodologies applied in these contexts. Modelling of TGx data represents a valuable tool for more accurate chemical safety assessment. This review is the third part of a three-article series on Transcriptomics in Toxicogenomics.
Collapse
Affiliation(s)
- Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
| | - Michele Fratello
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
| | - Luca Cattelani
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
| | - Irene Liampa
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece; (I.L.); (H.S.)
| | - Georgia Melagraki
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia 1065, Cyprus; (G.M.); (A.A.)
| | - Pekka Kohonen
- Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden; (P.K.); (P.N.); (R.G.)
- Division of Toxicology, Misvik Biology, 20520 Turku, Finland
| | - Penny Nymark
- Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden; (P.K.); (P.N.); (R.G.)
- Division of Toxicology, Misvik Biology, 20520 Turku, Finland
| | - Antonio Federico
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
| | - Pia Anneli Sofia Kinaret
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
- Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland
| | - Karolina Jagiello
- QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland; (K.J.); (T.P.)
- University of Gdansk, Faculty of Chemistry, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - My Kieu Ha
- Center for Next Generation Cytometry, Hanyang University, Seoul 04763, Korea; (M.K.H.); (J.-S.C.); (T.-H.Y.)
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
- Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Korea
| | - Jang-Sik Choi
- Center for Next Generation Cytometry, Hanyang University, Seoul 04763, Korea; (M.K.H.); (J.-S.C.); (T.-H.Y.)
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
- Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Korea
| | - Natasha Sanabria
- National Institute for Occupational Health, Johannesburg 30333, South Africa; (N.S.); (M.G.)
| | - Mary Gulumian
- National Institute for Occupational Health, Johannesburg 30333, South Africa; (N.S.); (M.G.)
- Haematology and Molecular Medicine Department, School of Pathology, University of the Witwatersrand, Johannesburg 2050, South Africa
| | - Tomasz Puzyn
- QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland; (K.J.); (T.P.)
- University of Gdansk, Faculty of Chemistry, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Tae-Hyun Yoon
- Center for Next Generation Cytometry, Hanyang University, Seoul 04763, Korea; (M.K.H.); (J.-S.C.); (T.-H.Y.)
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
- Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Korea
| | - Haralambos Sarimveis
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece; (I.L.); (H.S.)
| | - Roland Grafström
- Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden; (P.K.); (P.N.); (R.G.)
- Division of Toxicology, Misvik Biology, 20520 Turku, Finland
| | - Antreas Afantitis
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia 1065, Cyprus; (G.M.); (A.A.)
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (M.F.); (L.C.); (A.F.); (P.A.S.K.)
- BioMediTech Institute, Tampere University, FI-33014 Tampere, Finland
- Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland
| |
Collapse
|
43
|
Wang P, Wang Z, Xia P, Zhang X. Concentration-dependent transcriptome of zebrafish embryo for environmental chemical assessment. CHEMOSPHERE 2020; 245:125632. [PMID: 31864044 DOI: 10.1016/j.chemosphere.2019.125632] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Revised: 12/07/2019] [Accepted: 12/09/2019] [Indexed: 06/10/2023]
Abstract
Mechanistic information is essential to screen and predict the adverse effects of a large number of chemicals during early-life exposure. Concentration-dependent omics can capture the extent of perturbations of biological pathways or processes and provide information on the mechanism of toxicity. However, the application of concentration-dependent transcriptome to assess the developmental toxicity of environmental chemicals is still limited. Here, twelve chemicals representing five different modes of action (MOAs) were tested by the concentration-dependent reduced zebrafish transcriptome approach (CRZT) in combination with a phenotype-based high content screen (PHCS). The responsiveness, sensitivity and mechanistic differentiation of CRZT were validated in comparison with PHCS. First, PHCS identified 10 chemicals with obvious embryotoxicity (LD50 range: 2.11-70.68 μM), while the potencies of the biological pathways perturbed by 12 chemicals (PODpath20 range: 0.002-2.1 μM) were demonstrated by CRZT. Second, although the potency of the transcriptome perturbations was positively correlated with lethality (LD50) (R2 = 0.64, P-value < 0.05) for most tested chemicals, BbF was non-embryotoxic but was the most potent on the perturbance of biological pathways. Finally, the profiles of the perturbed biological processes and the transcriptome potency (PODpath20) captured by CRZT could effectively classify most chemicals corresponding to their known MOAs. In summary, CRZT could significantly improve testing the developmental toxicity of environmental chemicals.
Collapse
Affiliation(s)
- Pingping Wang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210023, PR China
| | - Zhihao Wang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210023, PR China
| | - Pu Xia
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210023, PR China
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210023, PR China.
| |
Collapse
|
44
|
Xia P, Zhang H, Peng Y, Shi W, Zhang X. Pathway-based assessment of single chemicals and mixtures by a high-throughput transcriptomics approach. ENVIRONMENT INTERNATIONAL 2020; 136:105455. [PMID: 31945694 DOI: 10.1016/j.envint.2019.105455] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 12/12/2019] [Accepted: 12/26/2019] [Indexed: 05/23/2023]
Abstract
The ever-increasing number of chemicals and complex mixtures demands a high-throughput and cost-effective approach for chemical safety assessment. High-throughput transcriptomics (HTT) is promising in investigating genome-scale perturbation of chemical exposure in concentration-dependent manner. However, the application of HTT has been limited due to lack of methodology for single chemicals and mixture assessment. This study aimed to evaluate the ability of a newly-developed human reduced transcriptomics (RHT) approach to assess pathway-based profiles of single chemicals, and to develop a biological pathway-based approach for benchmarking mixture potency using single chemical-based prediction model. First, concentration-dependent RHT were used to qualitatively and quantitatively differentiate pathway-based patterns of different chemicals, using three model toxicants, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), triclosan (TCS) and 5-Chloro-6-hydroxy-2,2',4,4'-tetrabromodiphenyl ether (5-Cl-6-OH-BDE-47). AHR-regulated genes and pathways were most sensitively induced by TCDD, while TCS and 5-Cl-6-OH-BDE-47 were much less potent in AHR-associated activation, which was concordant with known MoA of each single chemical. Second, two artificial mixtures and their components of twelve individual chemicals were performed with concentration-dependent RHT. Concentration addition (CA) and independent action (IA) models were used to predict transcriptional potency of mixtures from transcriptomics of individual chemicals. For overall bioactivity, CA and IA models can both predict potency of observed responses within 95% confidence interval. For specific biological processes, multiple biological processes such as hormone signaling and DNA damage can be predicted using CA models for mixtures. The concentration-dependent RHT can provide a powerful approach for qualitative and quantitative assessment of biological pathway perturbated by environment chemical and mixtures.
Collapse
Affiliation(s)
- Pu Xia
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China
| | - Hanxin Zhang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China
| | - Ying Peng
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China
| | - Wei Shi
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China.
| |
Collapse
|
45
|
Nault R, Bals B, Teymouri F, Black MB, Andersen ME, McMullen PD, Krishnan S, Kuravadi N, Paul N, Kumar S, Kannan K, Jayachandra KC, Alagappan L, Patel BD, Bogen KT, Gollapudi BB, Klaunig JE, Zacharewski TR, Bringi V. A toxicogenomic approach for the risk assessment of the food contaminant acetamide. Toxicol Appl Pharmacol 2020; 388:114872. [PMID: 31881176 PMCID: PMC7014822 DOI: 10.1016/j.taap.2019.114872] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Revised: 12/10/2019] [Accepted: 12/20/2019] [Indexed: 12/26/2022]
Abstract
Acetamide (CAS 60-35-5) is detected in common foods. Chronic rodent bioassays led to its classification as a group 2B possible human carcinogen due to the induction of liver tumors in rats. We used a toxicogenomics approach in Wistar rats gavaged daily for 7 or 28 days at doses of 300 to 1500 mg/kg/day (mkd) to determine a point of departure (POD) and investigate its mode of action (MoA). Ki67 labeling was increased at doses ≥750 mkd up to 3.3-fold representing the most sensitive apical endpoint. Differential gene expression analysis by RNA-Seq identified 1110 and 1814 differentially expressed genes in male and female rats, respectively, following 28 days of treatment. Down-regulated genes were associated with lipid metabolism while up-regulated genes included cell signaling, immune response, and cell cycle functions. Benchmark dose (BMD) modeling of the Ki67 labeling index determined the BMD10 lower confidence limit (BMDL10) as 190 mkd. Transcriptional BMD modeling revealed excellent concordance between transcriptional POD and apical endpoints. Collectively, these results indicate that acetamide is most likely acting through a mitogenic MoA, though specific key initiating molecular events could not be elucidated. A POD value of 190 mkd determined for cell proliferation is suggested for risk assessment purposes.
Collapse
Affiliation(s)
- Rance Nault
- Institute for Integrative Toxicology, Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, United States of America
| | - Bryan Bals
- Michigan Biotechnology Institute, Lansing, MI, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Tim R Zacharewski
- Institute for Integrative Toxicology, Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, United States of America
| | - Venkataraman Bringi
- Chemical Engineering & Materials Science, Michigan State University, East Lansing, MI, USA.
| |
Collapse
|
46
|
Peng Y, Fang W, Yan L, Wang Z, Wang P, Yu J, Zhang X. Early Life Stage Bioactivity Assessment of Short-Chain Chlorinated Paraffins at Environmentally Relevant Concentrations by Concentration-Dependent Transcriptomic Analysis of Zebrafish Embryos. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:996-1004. [PMID: 31829571 DOI: 10.1021/acs.est.9b04879] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Short-chain chlorinated paraffins (SCCPs), a class of ubiquitous pollutants, are considered to be embryotoxic and teratogenic. However, little is known regarding the bioactivity and mechanisms at environmentally relevant concentrations at the embryonic period. Here, a concentration-dependent reduced transcriptomic approach was used to evaluate the environmental dose (<100 ppb) effects of nine SCCP congeners and eight commercial mixtures on zebrafish embryos at 8 hpf. After 24 h of exposure, the overall biological potency of all the SCCPs, in terms of interference with 20% of the differentially expressed genes (PODDEG20), in zebrafish embryos ranged from 0.83 to 67.61 ppb. C10H14Cl8 (PODGO20 = 3.80 ppb) and C10-13 51.5% Cl (PODGO20 = 3.31 ppb) exhibited the strongest interference with biological processes compared to other SCCP homologs and mixtures, respectively. The most sensitive early molecular responses induced by SCCPs were associated with pathways of genetic damage, energy metabolite interference, and metal ion binding. Furthermore, the carbon number was positively correlated with the transcriptomic potency (PODGO20) of SCCP congeners (with chlorine content > 60%) (p = 0.038), and the chlorine content of SCCP congeners affected the bioactivity associated with genotoxic pathways. The concentration-dependent reduced transcriptomic approach significantly improved the understanding of the ecological risk of environmental contaminants at early life stages.
Collapse
Affiliation(s)
- Ying Peng
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment , Nanjing University , Nanjing 210023 , China
| | - Wendi Fang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment , Nanjing University , Nanjing 210023 , China
| | - Lu Yan
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment , Nanjing University , Nanjing 210023 , China
| | - Zhihao Wang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment , Nanjing University , Nanjing 210023 , China
| | - Pingping Wang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment , Nanjing University , Nanjing 210023 , China
| | - Jiaxin Yu
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment , Nanjing University , Nanjing 210023 , China
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment , Nanjing University , Nanjing 210023 , China
| |
Collapse
|
47
|
Nyffeler J, Willis C, Lougee R, Richard A, Paul-Friedman K, Harrill JA. Bioactivity screening of environmental chemicals using imaging-based high-throughput phenotypic profiling. Toxicol Appl Pharmacol 2019; 389:114876. [PMID: 31899216 DOI: 10.1016/j.taap.2019.114876] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 12/27/2019] [Accepted: 12/28/2019] [Indexed: 10/25/2022]
Abstract
The present study adapted an existing high content imaging-based high-throughput phenotypic profiling (HTPP) assay known as "Cell Painting" for bioactivity screening of environmental chemicals. This assay uses a combination of fluorescent probes to label a variety of organelles and measures a large number of phenotypic features at the single cell level in order to detect chemical-induced changes in cell morphology. First, a small set of candidate phenotypic reference chemicals (n = 14) known to produce changes in the cellular morphology of U-2 OS cells were identified and screened at multiple time points in concentration-response format. Many of these chemicals produced distinct cellular phenotypes that were qualitatively similar to those previously described in the literature. A novel workflow for phenotypic feature extraction, concentration-response modeling and determination of in vitro thresholds for chemical bioactivity was developed. Subsequently, a set of 462 chemicals from the ToxCast library were screened in concentration-response mode. Bioactivity thresholds were calculated and converted to administered equivalent doses (AEDs) using reverse dosimetry. AEDs were then compared to effect values from mammalian toxicity studies. In many instances (68%), the HTPP-derived AEDs were either more conservative than or comparable to the in vivo effect values. Overall, we conclude that the HTPP assay can be used as an efficient, cost-effective and reproducible screening method for characterizing the biological activity and potency of environmental chemicals for potential use in in vitro-based safety assessments.
Collapse
Affiliation(s)
- Johanna Nyffeler
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America; Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN 37831, United States of America
| | - Clinton Willis
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America; Oak Ridge Associated Universities (ORAU) National Student Services Contractor, Oak Ridge, TN 37831, United States of America
| | - Ryan Lougee
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America; Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN 37831, United States of America
| | - Ann Richard
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America
| | - Katie Paul-Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America
| | - Joshua A Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Durham, NC 27711, United States of America.
| |
Collapse
|
48
|
Christopher Corton J. Integrating gene expression biomarker predictions into networks of adverse outcome pathways. CURRENT OPINION IN TOXICOLOGY 2019. [DOI: 10.1016/j.cotox.2019.05.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
|
49
|
Jensen SM, Kluxen FM, Ritz C. A Review of Recent Advances in Benchmark Dose Methodology. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2019; 39:2295-2315. [PMID: 31046141 DOI: 10.1111/risa.13324] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 02/01/2019] [Accepted: 04/03/2019] [Indexed: 06/09/2023]
Abstract
In this review, recent methodological developments for the benchmark dose (BMD) methodology are summarized. Specifically, we introduce the advances for the main steps in BMD derivation: selecting the procedure for defining a BMD from a predefined benchmark response (BMR), setting a BMR, selecting a dose-response model, and estimating the corresponding BMD lower limit (BMDL). Although the last decade has shown major progress in the development of BMD methodology, there is still room for improvement. Remaining challenges are the implementation of new statistical methods in user-friendly software and the lack of consensus about how to derive the BMDL.
Collapse
Affiliation(s)
- Signe M Jensen
- Department of Plant and Environmental Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Christian Ritz
- Department of Nutrition, Sports and Exercise, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
50
|
Critical assessment and integration of separate lines of evidence for risk assessment of chemical mixtures. Arch Toxicol 2019; 93:2741-2757. [PMID: 31520250 DOI: 10.1007/s00204-019-02547-x] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Accepted: 08/14/2019] [Indexed: 12/17/2022]
Abstract
Humans are exposed to multiple chemicals on a daily basis instead of to just a single chemical, yet the majority of existing toxicity data comes from single-chemical exposure. Multiple factors must be considered such as the route, concentration, duration, and the timing of exposure when determining toxicity to the organism. The need for adequate model systems (in vivo, in vitro, in silico and mathematical) is paramount for better understanding of chemical mixture toxicity. Currently, shortcomings plague each model system as investigators struggle to find the appropriate balance of rigor, reproducibility and appropriateness in mixture toxicity studies. Significant questions exist when comparing single-to mixture-chemical toxicity concerning additivity, synergism, potentiation, or antagonism. Dose/concentration relevance is a major consideration and should be subthreshold for better accuracy in toxicity assessment. Previous work was limited by the technology and methodology of the time, but recent advances have resulted in significant progress in the study of mixture toxicology. Novel technologies have added insight to data obtained from in vivo studies for predictive toxicity testing. These include new in vitro models: omics-related tools, organs-on-a-chip and 3D cell culture, and in silico methods. Taken together, all these modern methodologies improve the understanding of the multiple toxicity pathways associated with adverse outcomes (e.g., adverse outcome pathways), thus allowing investigators to better predict risks linked to exposure to chemical mixtures. As technology and knowledge advance, our ability to harness and integrate separate streams of evidence regarding outcomes associated with chemical mixture exposure improves. As many national and international organizations are currently stressing, studies on chemical mixture toxicity are of primary importance.
Collapse
|