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Silva AC, Loizou GD, McNally K, Osborne O, Potter C, Gott D, Colbourne JK, Viant MR. A novel method to derive a human safety limit for PFOA by gene expression profiling and modelling. FRONTIERS IN TOXICOLOGY 2024; 6:1368320. [PMID: 38577564 PMCID: PMC10991825 DOI: 10.3389/ftox.2024.1368320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 03/01/2024] [Indexed: 04/06/2024] Open
Abstract
Perfluorooctanoic acid (PFOA) is a persistent environmental contaminant that can accumulate in the human body due to its long half-life. This substance has been associated with liver, pancreatic, testicular and breast cancers, liver steatosis and endocrine disruption. PFOA is a member of a large group of substances also known as "forever chemicals" and the vast majority of substances of this group lack toxicological data that would enable their effective risk assessment in terms of human health hazards. This study aimed to derive a health-based guidance value for PFOA intake (ng/kg BW/day) from in vitro transcriptomics data. To this end, we developed an in silico workflow comprising five components: (i) sourcing in vitro hepatic transcriptomics concentration-response data; (ii) deriving molecular points of departure using BMDExpress3 and performing pathway analysis using gene set enrichment analysis (GSEA) to identify the most sensitive molecular pathways to PFOA exposure; (iii) estimating freely-dissolved PFOA concentrations in vitro using a mass balance model; (iv) estimating in vivo doses by reverse dosimetry using a PBK model for PFOA as part of a quantitative in vitro to in vivo extrapolation (QIVIVE) algorithm; and (v) calculating a tolerable daily intake (TDI) for PFOA. Fourteen percent of interrogated genes exhibited in vitro concentration-response relationships. GSEA pathway enrichment analysis revealed that "fatty acid metabolism" was the most sensitive pathway to PFOA exposure. In vitro free PFOA concentrations were calculated to be 2.9% of the nominal applied concentrations, and these free concentrations were input into the QIVIVE workflow. Exposure doses for a virtual population of 3,000 individuals were estimated, from which a TDI of 0.15 ng/kg BW/day for PFOA was calculated using the benchmark dose modelling software, PROAST. This TDI is comparable to previously published values of 1.16, 0.69, and 0.86 ng/kg BW/day by the European Food Safety Authority. In conclusion, this study demonstrates the combined utility of an "omics"-derived molecular point of departure and in silico QIVIVE workflow for setting health-based guidance values in anticipation of the acceptance of in vitro concentration-response molecular measurements in chemical risk assessment.
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Affiliation(s)
- Arthur de Carvalho e Silva
- School of Biosciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Environmental Research and Justice (CERJ), University of Birmingham, Birmingham, United Kingdom
| | | | | | - Olivia Osborne
- Science Evidence and Research Division, Food Standards Agency, London, United Kingdom
| | - Claire Potter
- Science Evidence and Research Division, Food Standards Agency, London, United Kingdom
| | - David Gott
- Science Evidence and Research Division, Food Standards Agency, London, United Kingdom
| | - John K. Colbourne
- School of Biosciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Environmental Research and Justice (CERJ), University of Birmingham, Birmingham, United Kingdom
| | - Mark R. Viant
- School of Biosciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Environmental Research and Justice (CERJ), University of Birmingham, Birmingham, United Kingdom
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2
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Loizou G, McNally K, Paini A, Hogg A. Derivation of a Human In Vivo Benchmark Dose for Bisphenol A from ToxCast In Vitro Concentration Response Data Using a Computational Workflow for Probabilistic Quantitative In Vitro to In Vivo Extrapolation. Front Pharmacol 2022; 12:754408. [PMID: 35222005 PMCID: PMC8874249 DOI: 10.3389/fphar.2021.754408] [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: 08/06/2021] [Accepted: 11/15/2021] [Indexed: 11/23/2022] Open
Abstract
A computational workflow which integrates physiologically based kinetic (PBK) modelling; global sensitivity analysis (GSA), Approximate Bayesian Computation (ABC), Markov Chain Monte Carlo (MCMC) simulation and the Virtual Cell Based Assay (VCBA) for the estimation of the active, free in vitro concentration of chemical in the reaction medium was developed to facilitate quantitative in vitro to in vivo extrapolation (QIVIVE). The workflow was designed to estimate parameter and model uncertainty within a computationally efficient framework. The workflow was tested using a human PBK model for bisphenol A (BPA) and high throughput screening (HTS) in vitro concentration-response data, for estrogen and pregnane X receptor activation determined in human liver and kidney cell lines, from the ToxCast/Tox21 database. In vivo benchmark dose 10% lower confidence limits (BMDL10) for oral uptake of BPA (ng/kg BW/day) were calculated from the in vivo dose-responses and compared to the human equivalent dose (HED) BMDL10 for relative kidney weight change in the mouse derived by European Food Safety Authority (EFSA). Three from four in vivo BMDL10 values calculated in this study were similar to the EFSA values whereas the fourth was much smaller. The derivation of an uncertainty factor (UF) to accommodate the uncertainties associated with measurements using human cell lines in vitro, extrapolated to in vivo, could be useful for the derivation of Health Based Guidance Values (HBGV).
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Affiliation(s)
- George Loizou
- Health and Safety Executive, Harpur Hill, Buxton, United Kingdom
- *Correspondence: George Loizou,
| | - Kevin McNally
- Health and Safety Executive, Harpur Hill, Buxton, United Kingdom
| | - Alicia Paini
- European Commission Joint Research Centre, Ispra, Italy
| | - Alex Hogg
- Health and Safety Executive, Harpur Hill, Buxton, United Kingdom
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3
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Loizou G, McNally K, Dorne JLCM, Hogg A. Derivation of a Human In Vivo Benchmark Dose for Perfluorooctanoic Acid From ToxCast In Vitro Concentration-Response Data Using a Computational Workflow for Probabilistic Quantitative In Vitro to In Vivo Extrapolation. Front Pharmacol 2021; 12:630457. [PMID: 34045957 PMCID: PMC8144460 DOI: 10.3389/fphar.2021.630457] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 03/01/2021] [Indexed: 01/11/2023] Open
Abstract
A computational workflow which integrates physiologically based kinetic (PBK) modeling, global sensitivity analysis (GSA), approximate Bayesian computation (ABC), and Markov Chain Monte Carlo (MCMC) simulation was developed to facilitate quantitative in vitro to in vivo extrapolation (QIVIVE). The workflow accounts for parameter and model uncertainty within a computationally efficient framework. The workflow was tested using a human PBK model for perfluorooctanoic acid (PFOA) and high throughput screening (HTS) in vitro concentration–response data, determined in a human liver cell line, from the ToxCast/Tox21 database. In vivo benchmark doses (BMDs) for PFOA intake (ng/kg BW/day) and drinking water exposure concentrations (µg/L) were calculated from the in vivo dose responses and compared to intake values derived by the European Food Safety Authority (EFSA). The intake benchmark dose lower confidence limit (BMDL5) of 0.82 was similar to 0.86 ng/kg BW/day for altered serum cholesterol levels derived by EFSA, whereas the intake BMDL5 of 6.88 was six-fold higher than the value of 1.14 ng/kg BW/day for altered antibody titer also derived by the EFSA. Application of a chemical-specific adjustment factor (CSAF) of 1.4, allowing for inter-individual variability in kinetics, based on biological half-life, gave an intake BMDL5 of 0.59 for serum cholesterol and 4.91 (ng/kg BW/day), for decreased antibody titer, which were 0.69 and 4.31 the EFSA-derived values, respectively. The corresponding BMDL5 for drinking water concentrations, for estrogen receptor binding activation associated with breast cancer, pregnane X receptor binding associated with altered serum cholesterol levels, thyroid hormone receptor α binding leading to thyroid disease, and decreased antibody titer (pro-inflammation from cytokines) were 0.883, 0.139, 0.086, and 0.295 ng/ml, respectively, with application of no uncertainty factors. These concentrations are 5.7-, 36-, 58.5-, and 16.9-fold lower than the median measured drinking water level for the general US population which is approximately, 5 ng/ml.
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Affiliation(s)
- George Loizou
- Health and Safety Executive, Harpur Hill, Buxton, United Kingdom
| | - Kevin McNally
- Health and Safety Executive, Harpur Hill, Buxton, United Kingdom
| | - Jean-Lou C M Dorne
- Scientific Committee and Emerging Risks Unit, European Food Safety Authority, Parma, Italy
| | - Alex Hogg
- Health and Safety Executive, Harpur Hill, Buxton, United Kingdom
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4
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Linakis MW, Sayre RR, Pearce RG, Sfeir MA, Sipes NS, Pangburn HA, Gearhart JM, Wambaugh JF. Development and evaluation of a high throughput inhalation model for organic chemicals. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2020; 30:866-877. [PMID: 32546826 PMCID: PMC7483974 DOI: 10.1038/s41370-020-0238-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 04/27/2020] [Accepted: 06/03/2020] [Indexed: 05/12/2023]
Abstract
Currently it is difficult to prospectively estimate human toxicokinetics (particularly for novel chemicals) in a high-throughput manner. The R software package httk has been developed, in part, to address this deficiency, and the aim of this investigation was to develop a generalized inhalation model for httk. The structure of the inhalation model was developed from two previously published physiologically based models from Jongeneelen and Berge (Ann Occup Hyg 55:841-864, 2011) and Clewell et al. (Toxicol Sci 63:160-172, 2001), while calculated physicochemical data was obtained from EPA's CompTox Chemicals Dashboard. In total, 142 exposure scenarios across 41 volatile organic chemicals were modeled and compared to published data. The slope of the regression line of best fit between log-transformed simulated and observed blood and exhaled breath concentrations was 0.46 with an r2 = 0.45 and a root mean square error (RMSE) of direct comparison between the log-transformed simulated and observed values of 1.11. Approximately 5.1% (n = 108) of the data points analyzed were >2 orders of magnitude different than expected. The volatile organic chemicals examined in this investigation represent small, generally lipophilic molecules. Ultimately this paper details a generalized inhalation component that integrates with the httk physiologically based toxicokinetic model to provide high-throughput estimates of inhalation chemical exposures.
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Affiliation(s)
- Matthew W Linakis
- United States Air Force, 711th Human Performance Wing, Airman Readiness Optimization, Wright-Patterson AFB, Wright-Patterson AFB, OH, 45433, USA
- UES, Inc., Dayton, OH, 45432, USA
| | - Risa R Sayre
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, 37831, USA
- National Center for Computational Toxicology, United States Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Robert G Pearce
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, 37831, USA
- National Center for Computational Toxicology, United States Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Mark A Sfeir
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, 37831, USA
- National Center for Computational Toxicology, United States Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Nisha S Sipes
- National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27711, USA
| | - Heather A Pangburn
- United States Air Force, 711th Human Performance Wing, Molecular Bioeffects, Wright-Patterson AFB, Wright-Patterson AFB, OH, 45433, USA
| | - Jeffery M Gearhart
- United States Air Force, 711th Human Performance Wing, Airman Readiness Optimization, Wright-Patterson AFB, Wright-Patterson AFB, OH, 45433, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Wright-Patterson AFB, Wright-Patterson AFB, OH, 45433, USA
| | - John F Wambaugh
- National Center for Computational Toxicology, United States Environmental Protection Agency, Research Triangle Park, NC, 27711, USA.
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5
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The Role of Reactive Oxygen Species in Arsenic Toxicity. Biomolecules 2020; 10:biom10020240. [PMID: 32033297 PMCID: PMC7072296 DOI: 10.3390/biom10020240] [Citation(s) in RCA: 174] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 01/28/2020] [Accepted: 01/29/2020] [Indexed: 12/13/2022] Open
Abstract
Arsenic poisoning is a global health problem. Chronic exposure to arsenic has been associated with the development of a wide range of diseases and health problems in humans. Arsenic exposure induces the generation of intracellular reactive oxygen species (ROS), which mediate multiple changes to cell behavior by altering signaling pathways and epigenetic modifications, or cause direct oxidative damage to molecules. Antioxidants with the potential to reduce ROS levels have been shown to ameliorate arsenic-induced lesions. However, emerging evidence suggests that constructive activation of antioxidative pathways and decreased ROS levels contribute to chronic arsenic toxicity in some cases. This review details the pathways involved in arsenic-induced redox imbalance, as well as current studies on prophylaxis and treatment strategies using antioxidants.
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6
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Perkins EJ, Ashauer R, Burgoon L, Conolly R, Landesmann B, Mackay C, Murphy CA, Pollesch N, Wheeler JR, Zupanic A, Scholz S. Building and Applying Quantitative Adverse Outcome Pathway Models for Chemical Hazard and Risk Assessment. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2019; 38:1850-1865. [PMID: 31127958 PMCID: PMC6771761 DOI: 10.1002/etc.4505] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 03/26/2019] [Accepted: 05/21/2019] [Indexed: 05/20/2023]
Abstract
An important goal in toxicology is the development of new ways to increase the speed, accuracy, and applicability of chemical hazard and risk assessment approaches. A promising route is the integration of in vitro assays with biological pathway information. We examined how the adverse outcome pathway (AOP) framework can be used to develop pathway-based quantitative models useful for regulatory chemical safety assessment. By using AOPs as initial conceptual models and the AOP knowledge base as a source of data on key event relationships, different methods can be applied to develop computational quantitative AOP models (qAOPs) relevant for decision making. A qAOP model may not necessarily have the same structure as the AOP it is based on. Useful AOP modeling methods range from statistical, Bayesian networks, regression, and ordinary differential equations to individual-based models and should be chosen according to the questions being asked and the data available. We discuss the need for toxicokinetic models to provide linkages between exposure and qAOPs, to extrapolate from in vitro to in vivo, and to extrapolate across species. Finally, we identify best practices for modeling and model building and the necessity for transparent and comprehensive documentation to gain confidence in the use of qAOP models and ultimately their use in regulatory applications. Environ Toxicol Chem 2019;38:1850-1865. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.
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Affiliation(s)
- Edward J. Perkins
- US Army Engineer Research and Development CenterVicksburgMississippiUSA
| | - Roman Ashauer
- Environment DepartmentUniversity of York, HeslingtonYorkUK
- ToxicodynamicsYorkUK
| | - Lyle Burgoon
- US Army Engineer Research and Development CenterVicksburgMississippiUSA
| | - Rory Conolly
- Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory, Office of Research and DevelopmentUS Environmental Protection Agency, Research Triangle ParkNorth CarolinaUSA
| | | | - Cameron Mackay
- Unilever Safety and Environmental Assurance Centre, SharnbrookBedfordUK
| | - Cheryl A. Murphy
- Department of Fisheries and WildlifeMichigan State UniversityEast LansingMichiganUSA
| | - Nathan Pollesch
- Mid‐Continent Ecology Division, National Health and Environmental Effects Laboratory, Office of Research and DevelopmentUS Environmental Protection AgencyDuluthMinnesotaUSA
| | | | - Anze Zupanic
- Department of Environmental ToxicologySwiss Federal Institute for Aquatic Science and TechnologyDübendorfSwitzerland
| | - Stefan Scholz
- Department of Bioanalytical EcotoxicologyHelmholtz Centre for Environmental Research‐UFZLeipzigGermany
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7
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Rowland MA, Wear H, Watanabe KH, Gust KA, Mayo ML. Statistical relationship between metabolic decomposition and chemical uptake predicts bioconcentration factor data for diverse chemical exposures. BMC SYSTEMS BIOLOGY 2018; 12:81. [PMID: 30086736 PMCID: PMC6081876 DOI: 10.1186/s12918-018-0601-y] [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: 02/12/2018] [Accepted: 07/09/2018] [Indexed: 11/10/2022]
Abstract
BACKGROUND A challenge of in vitro to in vivo extrapolation (IVIVE) is to predict the physical state of organisms exposed to chemicals in the environment from in vitro exposure assay data. Although toxicokinetic modeling approaches promise to bridge in vitro screening data with in vivo effects, they are often encumbered by a need for redesign or re-parameterization when applied to different tissues or chemicals. RESULTS We demonstrate a parameterization of reverse toxicokinetic (rTK) models developed for the adult zebrafish (Danio rerio) based upon particle swarm optimizations (PSO) of the chemical uptake and degradation rates that predict bioconcentration factors (BCF) for a broad range of chemicals. PSO reveals a relationship between chemical uptake and decomposition parameter values that predicts chemical-specific BCF values with moderate statistical agreement to a limited yet diverse chemical dataset, and all without a need to retrain the model to new data. CONCLUSIONS The presented model requires only the octanol-water partitioning ratio to predict BCFs to a fidelity consistent with existing QSAR models. This success begs re-evaluation of the modeling assumptions; specifically, it suggests that chemical uptake into arterial blood may be limited by transport across gill membranes (diffusion) rather than by counter-current flow between gill lamellae (convection). Therefore, more detailed molecular modeling of aquatic respiration may further improve predictive accuracy of the rTK approach.
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Affiliation(s)
- Michael A Rowland
- Environmental Laboratory, US Army Engineer Research and Development Center, Vicksburg, MS, USA.,Oak Ridge Institute for Science and Education, Oak Ridge, TN, USA
| | - Hannah Wear
- Portland State University, Portland, OR, USA
| | - Karen H Watanabe
- School of Mathematical and Natural Sciences, Arizona State University, Glendale, AZ, USA
| | - Kurt A Gust
- Environmental Laboratory, US Army Engineer Research and Development Center, Vicksburg, MS, USA
| | - Michael L Mayo
- Environmental Laboratory, US Army Engineer Research and Development Center, Vicksburg, MS, USA.
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8
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McNally K, Hogg A, Loizou G. A Computational Workflow for Probabilistic Quantitative in Vitro to in Vivo Extrapolation. Front Pharmacol 2018; 9:508. [PMID: 29867507 PMCID: PMC5968095 DOI: 10.3389/fphar.2018.00508] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Accepted: 04/27/2018] [Indexed: 11/30/2022] Open
Abstract
A computational workflow was developed to facilitate the process of quantitative in vitro to in vivo extrapolation (QIVIVE), specifically the translation of in vitro concentration-response to in vivo dose-response relationships and subsequent derivation of a benchmark dose value (BMD). The workflow integrates physiologically based pharmacokinetic (PBPK) modeling; global sensitivity analysis (GSA), Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo (MCMC) simulation. For a given set of in vitro concentration and response data the algorithm returns the posterior distribution of the corresponding in vivo, population-based dose-response values, for a given route of exposure. The novel aspect of the workflow is a rigorous statistical framework for accommodating uncertainty in both the parameters of the PBPK model (both parameter uncertainty and population variability) and in the structure of the PBPK model itself recognizing that the model is an approximation to reality. Both these sources of uncertainty propagate through the workflow and are quantified within the posterior distribution of in vivo dose for a fixed representative in vitro concentration. To demonstrate this process and for comparative purposes a similar exercise to previously published work describing the kinetics of ethylene glycol monoethyl ether (EGME) and its embryotoxic metabolite methoxyacetic acid (MAA) in rats was undertaken. The computational algorithm can be used to extrapolate from in vitro data to any organism, including human. Ultimately, this process will be incorporated into a user-friendly, freely available modeling platform, currently under development, that will simplify the process of QIVIVE.
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9
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Kirla KT, Groh KJ, Poetzsch M, Banote RK, Stadnicka-Michalak J, Eggen RIL, Schirmer K, Kraemer T. Importance of Toxicokinetics to Assess the Utility of Zebrafish Larvae as Model for Psychoactive Drug Screening Using Meta-Chlorophenylpiperazine (mCPP) as Example. Front Pharmacol 2018; 9:414. [PMID: 29755353 PMCID: PMC5932571 DOI: 10.3389/fphar.2018.00414] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Accepted: 04/10/2018] [Indexed: 01/05/2023] Open
Abstract
The number of new psychoactive substances (NPS) increases rapidly, harming society and fuelling the need for alternative testing strategies. These should allow the ever-increasing number of drugs to be tested more effectively for their toxicity and psychoactive effects. One proposed strategy is to complement rodent models with zebrafish (Danio rerio) larvae. Yet, our understanding of the toxicokinetics in this model, owing to the waterborne drug exposure and the distinct physiology of the fish, is incomplete. We here explore the toxicokinetics and behavioral effects of an NPS, meta-chlorophenylpiperazine (mCPP), in zebrafish larvae. Uptake kinetics of mCPP, supported by toxicokinetic modeling, strongly suggested the existence of active transport processes. Internal distribution showed a dominant accumulation in the eye, implying that in zebrafish, like in mammals, melanin could serve as a binding site for basic drugs. We confirmed this by demonstrating significantly lower drug accumulation in two types of hypo-pigmented fish. Comparison of the elimination kinetics between mCPP and previously characterized cocaine demonstrated that drug affinities to melanin in zebrafish vary depending on the structure of the test compound. As expected from mCPP-elicited responses in rodents and humans, zebrafish larvae displayed hypoactive behavior. However, significant differences were seen between zebrafish and rodents with regard to the concentration-dependency of the behavioral response and the comparability of tissue levels, corroborating the need to consider the organism-internal distribution of the chemical to allow appropriate dose modeling while evaluating effects and concordance between zebrafish and mammals. Our results highlight commonalities and differences of mammalian versus the fish model in need of further exploration.
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Affiliation(s)
- Krishna Tulasi Kirla
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland.,Department of Environmental Toxicology, Swiss Federal Institute of Aquatic Science and Technology, Eawag, Dübendorf, Switzerland
| | - Ksenia J Groh
- Department of Environmental Toxicology, Swiss Federal Institute of Aquatic Science and Technology, Eawag, Dübendorf, Switzerland.,Food Packaging Forum Foundation, Zurich, Switzerland
| | - Michael Poetzsch
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland
| | - Rakesh Kumar Banote
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Julita Stadnicka-Michalak
- Department of Environmental Toxicology, Swiss Federal Institute of Aquatic Science and Technology, Eawag, Dübendorf, Switzerland.,Civil and Environmental Engineering, School of Architecture, EPFL, Lausanne, Switzerland
| | - Rik I L Eggen
- Department of Environmental Toxicology, Swiss Federal Institute of Aquatic Science and Technology, Eawag, Dübendorf, Switzerland.,Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, Zurich, Switzerland
| | - Kristin Schirmer
- Department of Environmental Toxicology, Swiss Federal Institute of Aquatic Science and Technology, Eawag, Dübendorf, Switzerland.,Civil and Environmental Engineering, School of Architecture, EPFL, Lausanne, Switzerland.,Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, Zurich, Switzerland
| | - Thomas Kraemer
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland
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10
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Glover CN. Defence mechanisms: the role of physiology in current and future environmental protection paradigms. CONSERVATION PHYSIOLOGY 2018; 6:coy012. [PMID: 29564135 PMCID: PMC5848810 DOI: 10.1093/conphys/coy012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Revised: 02/09/2018] [Accepted: 02/22/2018] [Indexed: 05/13/2023]
Abstract
Ecological risk assessments principally rely on simplified metrics of organismal sensitivity that do not consider mechanism or biological traits. As such, they are unable to adequately extrapolate from standard laboratory tests to real-world settings, and largely fail to account for the diversity of organisms and environmental variables that occur in natural environments. However, an understanding of how stressors influence organism health can compensate for these limitations. Mechanistic knowledge can be used to account for species differences in basal biological function and variability in environmental factors, including spatial and temporal changes in the chemical, physical and biological milieu. Consequently, physiological understanding of biological function, and how this is altered by stressor exposure, can facilitate proactive, predictive risk assessment. In this perspective article, existing frameworks that utilize physiological knowledge (e.g. biotic ligand models, adverse outcomes pathways and mechanistic effect models), are outlined, and specific examples of how mechanistic understanding has been used to predict risk are highlighted. Future research approaches and data needs for extending the incorporation of physiological information into ecological risk assessments are discussed. Although the review focuses on chemical toxicants in aquatic systems, physical and biological stressors and terrestrial environments are also briefly considered.
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Affiliation(s)
- Chris N Glover
- Faculty of Science and Technology and Athabasca River Basin Research Institute, Athabasca University, Canada
- Department of Biological Sciences, CW 405, Biological Sciences Bldg. University of Alberta Edmonton, Alberta, Canada T6G 2E9
- Corresponding author: 1 University Drive, Athabasca, Alberta, Canada T9S 3A3. Tel: +(587) 985 8007.
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