1
|
DeLeo PC. Can next generation ecological risk assessment decisions be made today?-A case study of regulatory risk assessment in the United States. Regul Toxicol Pharmacol 2024; 151:105674. [PMID: 38968966 DOI: 10.1016/j.yrtph.2024.105674] [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: 02/19/2024] [Revised: 06/04/2024] [Accepted: 07/03/2024] [Indexed: 07/07/2024]
Abstract
We examined the need for new in vivo avian toxicity testing for three common industrial chemicals (1,2 dichloropropane, 1,1,2-trichloroethane and triphenyl phosphate) based on estimated avian exposures using fugacity and multimedia fate models for current conditions of use compared to hazard information including existing in vivo test data for the chemicals and analogs, interspecies correlation estimates and results from hundreds of acute avian dietary toxicity studies. The data indicated that acute avian toxicity is not likely to be observed below 10 ppm in the diet for any chemical with the exception of those with a specific mode of toxic action. Modeling indicated low exposure potential for terrestrial birds to any of the three chemicals, with estimated dietary concentration of less than 0.001 ppm. Despite uncertainty associated with the underlying data sources, the four order of magnitude gap between potential exposure and a minimum hazard threshold suggests that additional avian in vivo testing would not generate valuable data. However, a weight of evidence approach for integrating data is necessary to engender greater confidence among government decision-makers in cases where data from a particular in vivo study is not expected to improve risk decision-making and an existing data gap can remain unfilled.
Collapse
Affiliation(s)
- Paul C DeLeo
- Department of Regulatory and Scientific Affairs, American Chemistry Council, 700 Second Street, N.E, Washington, DC, 20002, USA.
| |
Collapse
|
2
|
Anand G, Koniusz P, Kumar A, Golding LA, Morgan MJ, Moghadam P. Graph neural networks-enhanced relation prediction for ecotoxicology (GRAPE). JOURNAL OF HAZARDOUS MATERIALS 2024; 472:134456. [PMID: 38703678 DOI: 10.1016/j.jhazmat.2024.134456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 04/25/2024] [Accepted: 04/25/2024] [Indexed: 05/06/2024]
Abstract
Exposure to toxic chemicals threatens species and ecosystems. This study introduces a novel approach using Graph Neural Networks (GNNs) to integrate aquatic toxicity data, providing an alternative to complement traditional in vivo ecotoxicity testing. This study pioneers the application of GNN in ecotoxicology by formulating the problem as a relation prediction task. GRAPE's key innovation lies in simultaneously modelling 444 aquatic species and 2826 chemicals within a graph, leveraging relations from existing datasets where informative species and chemical features are augmented to make informed predictions. Extensive evaluations demonstrate the superiority of GRAPE over Logistic Regression (LR) and Multi-Layer Perceptron (MLP) models, achieving remarkable improvements of up to a 30% increase in recall values. GRAPE consistently outperforms LR and MLP in predicting novel chemicals and new species. In particular, GRAPE showcases substantial enhancements in recall values, with improvements of ≥ 100% for novel chemicals and up to 13% for new species. Specifically, GRAPE correctly predicts the effects of novel chemicals (104 out of 126) and effects on new species (7 out of 8). Moreover, the study highlights the effectiveness of the proposed chemical features and induced network topology through GNN for accurately predicting metallic (74 out of 86) and organic (612 out of 674) chemicals, showcasing the broad applicability and robustness of the GRAPE model in ecotoxicological investigations. The code/data are provided at https://github.com/csiro-robotics/GRAPE.
Collapse
Affiliation(s)
- Gaurangi Anand
- Environment, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Dutton Park 4102, QLD, Australia
| | - Piotr Koniusz
- Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Black Mountain 2601, ACT, Australia.
| | - Anupama Kumar
- Environment, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Waite Campus 5064, SA, Australia
| | - Lisa A Golding
- Environment, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Dutton Park 4102, QLD, Australia
| | - Matthew J Morgan
- Environment, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Black Mountain 2601, ACT, Australia
| | - Peyman Moghadam
- Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Pullenvale 4069, QLD, Australia
| |
Collapse
|
3
|
Noventa S, Pace E, Esposito D, Libralato G, Manfra L. Handling concentration data below the analytical limit in environmental mixture risk assessment: A case-study on pesticide river monitoring. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:167670. [PMID: 37852501 DOI: 10.1016/j.scitotenv.2023.167670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 09/17/2023] [Accepted: 10/06/2023] [Indexed: 10/20/2023]
Abstract
Aquatic organisms are exposed to ever-changing complex mixtures of chemicals throughout their lifetime. Component-Based Mixture Risk Assessment (CBMRA) is a well-established methodology for water contaminant-mixture management, the use of which is growing due to improved access to reference ecotoxicity data and extensive monitoring datasets. It enables the translation of measured exposure concentrations of chemicals into biological effect values, and thus to quantitatively estimate the risk of the whole water sample (i.e., as a mixture). However, many factors can bias the final risk decision by impacting the risk metric components; thus, a careful design of the CBMRA is needed, taking into primary consideration the specific features of the dataset and mixture risk assessment assignments. This study systematically addressed the effects of the most common approaches used for handling the concentrations of chemicals below the limit of detection/quantification (LOD/LOQ) in CBMRA. The main results included: i) an informed CBMRA procedure that enables the tracking of the risk decisions triggered by substances below LOD/LOQ, ii) a conceptual map and guidance criteria to support the selection of the most suitable approach for specific scenarios and related interpretation; iii) a guided implementation of the informed CBMRA on dataset of pesticide concentrations in Italian rivers in 2020 (702,097 records).
Collapse
Affiliation(s)
- Seta Noventa
- Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), 30015 Chioggia, Italy.
| | - Emanuela Pace
- Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), via Vitaliano Brancati 48, 00144 Roma, Italy
| | - Dania Esposito
- Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), via Vitaliano Brancati 48, 00144 Roma, Italy
| | - Giovanni Libralato
- Department of Biology, University of Naples Federico II, Via Vicinale Cupa Cintia 26, 80126 Napoli, Italy; Department of Marine Biotechnology, Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Napoli, Italy
| | - Loredana Manfra
- Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), via Vitaliano Brancati 48, 00144 Roma, Italy; Department of Marine Biotechnology, Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Napoli, Italy
| |
Collapse
|
4
|
Kramer L, Schulze T, Klüver N, Altenburger R, Hackermüller J, Krauss M, Busch W. Curated mode-of-action data and effect concentrations for chemicals relevant for the aquatic environment. Sci Data 2024; 11:60. [PMID: 38200014 PMCID: PMC10781676 DOI: 10.1038/s41597-023-02904-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 12/29/2023] [Indexed: 01/12/2024] Open
Abstract
Chemicals in the aquatic environment can be harmful to organisms and ecosystems. Knowledge on effect concentrations as well as on mechanisms and modes of interaction with biological molecules and signaling pathways is necessary to perform chemical risk assessment and identify toxic compounds. To this end, we developed criteria and a pipeline for harvesting and summarizing effect concentrations from the US ECOTOX database for the three aquatic species groups algae, crustaceans, and fish and researched the modes of action of more than 3,300 environmentally relevant chemicals in literature and databases. We provide a curated dataset ready to be used for risk assessment based on monitoring data and the first comprehensive collection and categorization of modes of action of environmental chemicals. Authorities, regulators, and scientists can use this data for the grouping of chemicals, the establishment of meaningful assessment groups, and the development of in vitro and in silico approaches for chemical testing and assessment.
Collapse
Affiliation(s)
- Lena Kramer
- Helmholtz Centre for Environmental Research - UFZ, Permoserstr. 15, 04318, Leipzig, Germany
| | - Tobias Schulze
- Helmholtz Centre for Environmental Research - UFZ, Permoserstr. 15, 04318, Leipzig, Germany.
| | - Nils Klüver
- Helmholtz Centre for Environmental Research - UFZ, Permoserstr. 15, 04318, Leipzig, Germany
| | - Rolf Altenburger
- Helmholtz Centre for Environmental Research - UFZ, Permoserstr. 15, 04318, Leipzig, Germany
- RWTH Aachen University, Institute for Environmental Research, 52074, Aachen, Germany
| | - Jörg Hackermüller
- Helmholtz Centre for Environmental Research - UFZ, Permoserstr. 15, 04318, Leipzig, Germany
- University of Leipzig, Faculty of Mathematics and Computer Science, Ritterstr. 26, 04109, Leipzig, Germany
| | - Martin Krauss
- Helmholtz Centre for Environmental Research - UFZ, Permoserstr. 15, 04318, Leipzig, Germany
| | - Wibke Busch
- Helmholtz Centre for Environmental Research - UFZ, Permoserstr. 15, 04318, Leipzig, Germany.
| |
Collapse
|
5
|
Li JJ, Yue YX, Shi SJ, Xue JZ. Investigation on toxicity mechanism of halogenated aromatic disinfection by-products to zebrafish based on molecular docking and QSAR model. CHEMOSPHERE 2023; 341:139916. [PMID: 37633607 DOI: 10.1016/j.chemosphere.2023.139916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/18/2023] [Accepted: 08/19/2023] [Indexed: 08/28/2023]
Abstract
Halogenated aromatic disinfection by-products (DBPs) are a new type of DBPs that have been detected in various water bodies. Previous studies have shown that most of them can induce in vivo toxicity in aquatic organisms. In this study, in order to further investigate the toxic effects and mechanisms of aromatic DBPs, the toxicity and ecological risks of 10 halogenated aromatic DBPs were assessed using the model organism zebrafish. It was found that the toxicity of DBPs was related to the number, type, and position of halogen and the type of substituent, and the 24 h-toxicity value of DBPs in this experiment could replace their 96 h-toxicity value to reduce the test time and save the test cost. Halogenated phenol and halogenated nitrophenol were more toxic, but the current ecological risks of DBPs were relatively low. In addition, the toxicity mechanism of DBPs was analyzed based on molecular docking and quantitative structure-activity relationship (QSAR) models. The molecular docking results showed that all 10 DBPs could bind to zebrafish's catalase (CAT), cytochrome P450 (CYP450), p53, and acetylcholinesterase (AChE), thereby affecting their normal life activities. QSAR models indicated that the toxicity of halogenated aromatic DBPs to zebrafish mainly depended on their hydrophobicity (log D), the interaction with CAT (ECAT), and hydrogen bonding acidity (A).
Collapse
Affiliation(s)
- Jin Jie Li
- College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai, 201306, PR China
| | - Ya Xin Yue
- College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai, 201306, PR China
| | - Sheng Jie Shi
- College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai, 201306, PR China
| | - Jun Zeng Xue
- College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai, 201306, PR China.
| |
Collapse
|
6
|
Höss S, Sanders D, van Egmond R. Determining the toxicity of organic compounds to the nematode Caenorhabditis elegans based on aqueous concentrations. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:96290-96300. [PMID: 37567994 DOI: 10.1007/s11356-023-29193-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 07/28/2023] [Indexed: 08/13/2023]
Abstract
Caenorhabditis elegans is used for assessing the toxicity of chemicals in aqueous medium. However, chemicals can absorb to the bacterial food, which reduces the freely dissolved concentrations of the tested compounds. Thus, based on total or nominal concentrations, toxicity is underestimated, resulting in misleading assumptions on toxicity mechanisms or comparisons to other test organisms. As the verification of freely dissolved exposure concentrations (Cfree) is challenging in small test systems, simple partitioning models might by a good option for estimating Cfree. Therefore, C. elegans was exposed to seven differently acting organic chemicals with varying hydrophobicities, thus also different affinities to bind to the food of C. elegans. Measured concentrations of the dissolved aqueous and the bacterial-bound fraction allowed the calculation of binding constants (Kb). Experimental Kb were comparable to literature data of hydrophobic chemicals and correlated well with their hydrophobicity, expressed as log KOW. The chronic toxicity of the various compounds on C. elegans' reproduction, based on their aqueous concentration, was weakly related to their log KOW. Toxicity expressed based on chemical activity and comparisons with a baseline toxicity model, nevertheless, suggested a narcotic mode of action for most hydrophobic compounds (except methylisothiazolinone and trichlorocarbanilide). Although revealing a similar toxicity ranking than Daphnia magna, C. elegans was less sensitive, probably due to its ability to reduce its internal concentrations by means of its very impermeable cuticle or by efficient detoxification mechanisms. It could be shown that measured aqueous concentrations in the nematode test system corresponded well with freely dissolved concentrations that were modeled using simple mass-balance models from nominal concentrations. This offers the possibility to estimate freely dissolved concentrations of chemicals from nominal concentrations, making routine testing of chemicals and their comparison to other species more accurate.
Collapse
Affiliation(s)
| | - David Sanders
- Unilever, Safety & Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedford, MK44 1LQ, UK
| | - Roger van Egmond
- Unilever, Safety & Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedford, MK44 1LQ, UK
| |
Collapse
|
7
|
Belanger SE, Lillicrap AD, Moe SJ, Wolf R, Connors K, Embry MR. Weight of evidence tools in the prediction of acute fish toxicity. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2023; 19:1220-1234. [PMID: 35049115 DOI: 10.1002/ieam.4581] [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: 09/21/2021] [Revised: 01/10/2022] [Accepted: 01/12/2022] [Indexed: 06/14/2023]
Abstract
Acute fish toxicity (AFT) is a key endpoint in nearly all regulatory implementations of environmental hazard assessments of chemicals globally. Although it is an early tier assay, the AFT assay is complex and uses many juvenile fish each year for the registration and assessment of chemicals. Thus, it is imperative to seek animal alternative approaches to replace or reduce animal use for environmental hazard assessments. A Bayesian Network (BN) model has been developed that brings together a suite of lines of evidence (LoEs) to produce a probabilistic estimate of AFT without the testing of additional juvenile fish. Lines of evidence include chemical descriptors, mode of action (MoA) assignment, knowledge of algal and daphnid acute toxicity, and animal alternative assays such as fish embryo tests and in vitro fish assays (e.g., gill cytotoxicity). The effort also includes retrieval, assessment, and curation of quality acute fish toxicity data because these act as the baseline of comparison with model outputs. An ideal outcome of this effort would be to have global applicability, acceptance and uptake, relevance to predominant fish species used in chemical assessments, be expandable to allow incorporation of future knowledge, and data to be publicly available. The BN model can be conceived as having incorporated principles of tiered assessment and whose outcomes will be directed by the available evidence in combination with prior information. We demonstrate that, as additional evidence is included in the prediction of a given chemical's ecotoxicity profile, both the accuracy and the precision of the predicted AFT can increase. Ultimately an improved environmental hazard assessment will be achieved. Integr Environ Assess Manag 2023;19:1220-1234. © 2022 SETAC.
Collapse
Affiliation(s)
| | | | - S Jannicke Moe
- Norwegian Institute for Water Research (NIVA), Oslo, Norway
| | - Raoul Wolf
- Norwegian Institute for Water Research (NIVA), Oslo, Norway
- Norwegian Geotechnical Institute (NGI), Oslo, Norway
| | | | - Michelle R Embry
- Health and Environmental Sciences Institute, Washington, DC, USA
| |
Collapse
|
8
|
Schäfer RB, Jackson M, Juvigny-Khenafou N, Osakpolor SE, Posthuma L, Schneeweiss A, Spaak J, Vinebrooke R. Chemical Mixtures and Multiple Stressors: Same but Different? ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2023; 42:1915-1936. [PMID: 37036219 DOI: 10.1002/etc.5629] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/01/2023] [Accepted: 04/04/2023] [Indexed: 05/19/2023]
Abstract
Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects of multiple stressors have largely focussed on nonchemical stressors, whereas studies on chemical mixtures have largely ignored other stressors. However, both research areas face similar challenges and require similar tools and methods to predict the joint effects of chemicals or nonchemical stressors, and frameworks to integrate multiple chemical and nonchemical stressors are missing. We provide an overview of the research paradigms, tools, and methods commonly used in multiple stressor and chemical mixture research and discuss potential domains of cross-fertilization and joint challenges. First, we compare the general paradigms of ecotoxicology and (applied) ecology to explain the historical divide. Subsequently, we compare methods and approaches for the identification of interactions, stressor characterization, and designing experiments. We suggest that both multiple stressor and chemical mixture research are too focused on interactions and would benefit from integration regarding null model selection. Stressor characterization is typically more costly for chemical mixtures. While for chemical mixtures comprehensive classification systems at suborganismal level have been developed, recent classification systems for multiple stressors account for environmental context. Both research areas suffer from rather simplified experimental designs that focus on only a limited number of stressors, chemicals, and treatments. We discuss concepts that can guide more realistic designs capturing spatiotemporal stressor dynamics. We suggest that process-based and data-driven models are particularly promising to tackle the challenge of prediction of effects of chemical mixtures and nonchemical stressors on (meta-)communities and (meta-)food webs. We propose a framework to integrate the assessment of effects for multiple stressors and chemical mixtures. Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Collapse
Affiliation(s)
- Ralf B Schäfer
- Institute for Environmental Sciences, Rheinland-Pfälzische Technische Univerität Kaiserslautern-Landau, Landau, Germany
| | | | - Noel Juvigny-Khenafou
- Institute for Environmental Sciences, Rheinland-Pfälzische Technische Univerität Kaiserslautern-Landau, Landau, Germany
| | - Stephen E Osakpolor
- Institute for Environmental Sciences, Rheinland-Pfälzische Technische Univerität Kaiserslautern-Landau, Landau, Germany
| | - Leo Posthuma
- Centre for Sustainability, Environment and Health, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Environmental Science, Radboud University, Nijmegen, The Netherlands
| | - Anke Schneeweiss
- Institute for Environmental Sciences, Rheinland-Pfälzische Technische Univerität Kaiserslautern-Landau, Landau, Germany
| | - Jürg Spaak
- Institute for Environmental Sciences, Rheinland-Pfälzische Technische Univerität Kaiserslautern-Landau, Landau, Germany
| | - Rolf Vinebrooke
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| |
Collapse
|
9
|
Droge STJ, Hodges G, Bonnell M, Gutsell S, Roberts J, Teixeira A, Barrett EL. Using membrane-water partition coefficients in a critical membrane burden approach to aid the identification of neutral and ionizable chemicals that induce acute toxicity below narcosis levels. ENVIRONMENTAL SCIENCE. PROCESSES & IMPACTS 2023; 25:621-647. [PMID: 36779707 DOI: 10.1039/d2em00391k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
The risk assessment of thousands of chemicals used in our society benefits from adequate grouping of chemicals based on the mode and mechanism of toxic action (MoA). We measure the phospholipid membrane-water distribution ratio (DMLW) using a chromatographic assay (IAM-HPLC) for 121 neutral and ionized organic chemicals and screen other methods to derive DMLW. We use IAM-HPLC based DMLW as a chemical property to distinguish between baseline narcosis and specific MoA, for reported acute toxicity endpoints on two separate sets of chemicals. The first set comprised 94 chemicals of US EPA's acute fish toxicity database: 47 categorized as narcosis MoA, 27 with specific MoA, and 20 predominantly ionic chemicals with mostly unknown MoA. The narcosis MoA chemicals clustered around the median narcosis critical membrane burden (CMBnarc) of 140 mmol kg-1 lipid, with a lower limit of 14 mmol kg-1 lipid, including all chemicals labelled Narcosis_I and Narcosis_II. This maximum 'toxic ratio' (TR) between CMBnarc and the lower limit narcosis endpoint is thus 10. For 23/28 specific MoA chemicals a TR >10 was derived, indicative of a specific adverse effect pathway related to acute toxicity. For 10/12 cations categorized as "unsure amines", the TR <10 suggests that these affect fish via narcosis MoA. The second set comprised 29 herbicides, including 17 dissociated acids, and evaluated the TR for acute toxic effect concentrations to likely sensitive aquatic plant species (green algae and macrophytes Lemna and Myriophyllum), and non-target animal species (invertebrates and fish). For 21/29 herbicides, a TR >10 indicated a specific toxic mode of action other than narcosis for at least one of these aquatic primary producers. Fish and invertebrate TRs were mostly <10, particularly for neutral herbicides, but for acidic herbicides a TR >10 indicated specific adverse effects in non-target animals. The established critical membrane approach to derive the TR provides for useful contribution to the weight of evidence to bin a chemical as having a narcosis MoA or less likely to have acute toxicity caused by a more specific adverse effect pathway. After proper calibration, the chromatographic assay provides consistent and efficient experimental input for both neutral and ionizable chemicals to this approach.
Collapse
Affiliation(s)
- Steven T J Droge
- Department of Freshwater and Marine Ecology (FAME), Institute for Biodiversity and Ecosystem Dynamics (IBED), Universiteit van Amsterdam (UvA), Science Park 904, 1098XH Amsterdam, The Netherlands.
| | - Geoff Hodges
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire, UK
| | - Mark Bonnell
- Environment and Climate Change Canada, Ecological Assessment Division, Science and Risk Assessment Directorate, Gatineau, Quebec, Canada
| | - Steve Gutsell
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire, UK
| | - Jayne Roberts
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire, UK
| | - Alexandre Teixeira
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire, UK
| | - Elin L Barrett
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire, UK
| |
Collapse
|
10
|
Souza-Silva G, de Souza CR, Pereira CADJ, Dos Santos Lima W, Mol MPG, Silveira MR. Using freshwater snail Biomphalaria glabrata (Say, 1818) as a biological model for ecotoxicology studies: a systematic review. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:28506-28524. [PMID: 36701061 DOI: 10.1007/s11356-023-25455-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 01/17/2023] [Indexed: 06/17/2023]
Abstract
Over time, a growing increase in human pollutants in the aquatic environment has been observed. The global presence of residues in water bodies reinforces the need to develop improved methods to detect them and evaluate their ecotoxicological effects in aquatic environments. Thus, this study aimed to present the main assays using Biomphalaria glabrata as a biological model for ecotoxicological studies. We performed a systematic literature review with data published up to June 2022 on the Web of Science, SCOPUS, Science Direct, PubMed, and SciELO databases. Thirty studies were selected for this review after screening. Biomphalaria glabrata has been studied as an ecotoxicological model for different substances through toxicity, embryotoxicity, cytotoxicity, genotoxicity, and bioaccumulation assays. Studies evaluating the impact of B. glabrata exposure to several substances have reported effects on their offspring, as well as toxicity and behavioral and reproductive effects. This review presents various assays using B. glabrata as a biological model for ecotoxicological studies. The use of a representative species of ecosystems from tropical regions is a necessary tool for tropical environmental monitoring. It was observed that the freshwater snail B. glabrata was effective for the evaluation of the ecotoxicity of several types of chemical substances, but further studies are needed to standardize the model.
Collapse
Affiliation(s)
- Gabriel Souza-Silva
- Postgraduate Program in Medicines and Pharmaceutical Assistance, Faculty of Pharmacy, Federal University of Minas Gerais-Belo Horizonte/MG, Belo Horizonte, Brazil.
| | - Clessius Ribeiro de Souza
- Postgraduate Program in Medicines and Pharmaceutical Assistance, Faculty of Pharmacy, Federal University of Minas Gerais-Belo Horizonte/MG, Belo Horizonte, Brazil
| | - Cíntia Aparecida de Jesus Pereira
- Department of Parasitology, Institute of Biological Sciences, Federal University of Minas Gerais-Belo Horizonte/MG, Belo Horizonte, Brazil
| | - Walter Dos Santos Lima
- Department of Parasitology, Institute of Biological Sciences, Federal University of Minas Gerais-Belo Horizonte/MG, Belo Horizonte, Brazil
| | - Marcos Paulo Gomes Mol
- Department of Research and Development, Ezequiel Dias Foundation-Belo Horizonte/MG, Belo Horizonte, Brazil
| | - Micheline Rosa Silveira
- Postgraduate Program in Medicines and Pharmaceutical Assistance, Faculty of Pharmacy, Federal University of Minas Gerais-Belo Horizonte/MG, Belo Horizonte, Brazil
| |
Collapse
|
11
|
Ceger P, Allen D, Blankinship A, Choksi N, Daniel A, Eckel WP, Hamm J, Harwood DE, Johnson T, Kleinstreuer N, Sprankle CS, Truax J, Lowit M. Evaluation of the fish acute toxicity test for pesticide registration. Regul Toxicol Pharmacol 2023; 139:105340. [PMID: 36702196 PMCID: PMC11446266 DOI: 10.1016/j.yrtph.2023.105340] [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: 10/03/2022] [Revised: 01/01/2023] [Accepted: 01/21/2023] [Indexed: 01/25/2023]
Abstract
The U.S. Environmental Protection Agency (USEPA) uses the in vivo fish acute toxicity test to assess potential risk of substances to non-target aquatic vertebrates. The test is typically conducted on a cold and a warm freshwater species and a saltwater species for a conventional pesticide registration, potentially requiring upwards of 200 or more fish. A retrospective data evaluation was conducted to explore the potential for using fewer fish species to support conventional pesticide risk assessments. Lethal concentration 50% (LC50) values and experimental details were extracted and curated from 718 studies on fish acute toxicity submitted to USEPA. The LC50 data were analysed to determine, when possible, the relative sensitivity of the tested species to each pesticide. One of the tested freshwater species was most sensitive in 85% of those cases. The tested cold freshwater species was the most sensitive overall among cases with established relative sensitivity and was within 3X of the LC50 value of the most sensitive species tested in 98% of those cases. The results support potentially using fewer than three fish species to conduct ecological risk assessments for the registration of conventional pesticides.
Collapse
Affiliation(s)
- Patricia Ceger
- Inotiv, P.O. Box 13501, Research Triangle Park, NC, 27709, USA.
| | - David Allen
- Inotiv, P.O. Box 13501, Research Triangle Park, NC, 27709, USA.
| | - Amy Blankinship
- U.S. Environmental Protection Agency, Office of Pesticide Programs, MC7507M, 1200 Pennsylvania Ave. NW, Washington, DC, 20460, USA.
| | - Neepa Choksi
- Inotiv, P.O. Box 13501, Research Triangle Park, NC, 27709, USA.
| | - Amber Daniel
- Inotiv, P.O. Box 13501, Research Triangle Park, NC, 27709, USA.
| | - William P Eckel
- U.S. Environmental Protection Agency, Office of Pesticide Programs, MC7507M, 1200 Pennsylvania Ave. NW, Washington, DC, 20460, USA.
| | - Jon Hamm
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC, 27709, USA.
| | - D Ethan Harwood
- U.S. Environmental Protection Agency, Office of Pesticide Programs, MC7507M, 1200 Pennsylvania Ave. NW, Washington, DC, 20460, USA.
| | - Tamara Johnson
- U.S. Environmental Protection Agency, Office of Pesticide Programs, MC7507M, 1200 Pennsylvania Ave. NW, Washington, DC, 20460, USA.
| | - Nicole Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC, 27709, USA.
| | | | - James Truax
- Inotiv, P.O. Box 13501, Research Triangle Park, NC, 27709, USA.
| | - Michael Lowit
- U.S. Environmental Protection Agency, Office of Pesticide Programs, MC7507M, 1200 Pennsylvania Ave. NW, Washington, DC, 20460, USA.
| |
Collapse
|
12
|
Brockmeier EK, Basili D, Herbert J, Rendal C, Boakes L, Grauslys A, Taylor NS, Danby EB, Gutsell S, Kanda R, Cronin M, Barclay J, Antczak P, Viant MR, Hodges G, Falciani F. Data-driven learning of narcosis mode of action identifies a CNS transcriptional signature shared between whole organism Caenorhabditis elegans and a fish gill cell line. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 849:157666. [PMID: 35908689 DOI: 10.1016/j.scitotenv.2022.157666] [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: 02/02/2022] [Revised: 06/27/2022] [Accepted: 07/23/2022] [Indexed: 06/15/2023]
Abstract
With the large numbers of man-made chemicals produced and released in the environment, there is a need to provide assessments on their potential effects on environmental safety and human health. Current regulatory frameworks rely on a mix of both hazard and risk-based approaches to make safety decisions, but the large number of chemicals in commerce combined with an increased need to conduct assessments in the absence of animal testing makes this increasingly challenging. This challenge is catalysing the use of more mechanistic knowledge in safety assessment from both in silico and in vitro approaches in the hope that this will increase confidence in being able to identify modes of action (MoA) for the chemicals in question. Here we approach this challenge by testing whether a functional genomics approach in C. elegans and in a fish cell line can identify molecular mechanisms underlying the effects of narcotics, and the effects of more specific acting toxicants. We show that narcosis affects the expression of neuronal genes associated with CNS function in C. elegans and in a fish cell line. Overall, we believe that our study provides an important step in developing mechanistically relevant biomarkers which can be used to screen for hazards, and which prevent the need for repeated animal or cross-species comparisons for each new chemical.
Collapse
Affiliation(s)
- Erica K Brockmeier
- Department of Biochemistry & System Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Danilo Basili
- Department of Biochemistry & System Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; Safety and Environmental Assurance Centre (SEAC), Unilever, Colworth Park, Sharnbrook, UK
| | - John Herbert
- Department of Biochemistry & System Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Cecilie Rendal
- Safety and Environmental Assurance Centre (SEAC), Unilever, Colworth Park, Sharnbrook, UK
| | - Leigh Boakes
- Department of Biochemistry & System Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; Christeyns Food Hygiene, Warrington, UK
| | - Arturas Grauslys
- Department of Biochemistry & System Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; Computational Biology Facility (CBF), University of Liverpool, Liverpool, UK
| | - Nadine S Taylor
- School of Biosciences, University of Birmingham, Birmingham, UK
| | - Emma Butler Danby
- Safety and Environmental Assurance Centre (SEAC), Unilever, Colworth Park, Sharnbrook, UK
| | - Steve Gutsell
- Safety and Environmental Assurance Centre (SEAC), Unilever, Colworth Park, Sharnbrook, UK
| | - Rakesh Kanda
- Institute of Environment, Health and Societies, Brunel University, London, UK
| | - Mark Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, UK
| | - Jeff Barclay
- Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Philipp Antczak
- Department of Biochemistry & System Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; Computational Biology Facility (CBF), University of Liverpool, Liverpool, UK
| | - Mark R Viant
- School of Biosciences, University of Birmingham, Birmingham, UK
| | - Geoff Hodges
- Safety and Environmental Assurance Centre (SEAC), Unilever, Colworth Park, Sharnbrook, UK
| | - Francesco Falciani
- Department of Biochemistry & System Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; Computational Biology Facility (CBF), University of Liverpool, Liverpool, UK.
| |
Collapse
|
13
|
Lambert FN, Vivian DN, Raimondo S, Tebes-Stevens CT, Barron MG. Relationships Between Aquatic Toxicity, Chemical Hydrophobicity, and Mode of Action: Log Kow Revisited. ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2022; 83:326-338. [PMID: 35864329 PMCID: PMC11375592 DOI: 10.1007/s00244-022-00944-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 06/24/2022] [Indexed: 06/15/2023]
Abstract
Relationships between toxicity and chemical hydrophobicity have been known for nearly 100 years in mammals and fish, typically using the log of the octanol:water partition coefficient (Kow). The current study reassessed the influence of mode of action (MOA) on acute aquatic toxicity-log Kow relationships using a comprehensive database of 617 organic chemicals with curated and standardized acute toxicity data that did not exceed solubility limits, their consensus log Kow values, and weight of evidence-based MOA classifications (including 6 broad and 26 specific MOAs). A total of 166 significant (p < 0.05) log Kow-toxicity models were developed across six taxa groups that included QSARs for 5 of the broad and 13 of the specific MOAs. In this study, we demonstrate that QSARs based on MOAs can significantly increase LC50 prediction accuracy for specific acting chemicals. Prediction accuracy increases when QSARs are built based on highly specific MOAs, rather than broad MOA classifications. Additionally, we demonstrate that building QSAR models with chemicals in specific MOA groupings, rather than broader MOA groups leads to significantly better estimates. We also evaluated the differences between models developed from mass-based (µg/L) and mole-based (µmol/L) toxicity data and demonstrate that both are suitable for QSAR development with no clear trend in greater model accuracy. Overall, the results reveal that, despite high variance in all taxa and MOA groups, specific MOA-based models can improve the accuracy of aquatic toxicity predictions over more general groupings.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.The affiliations are correct.
Collapse
Affiliation(s)
- Faith N Lambert
- Office of Research and Development, U.S. EPA, U.S. EPA, 1 Sabine Island Drive, Gulf Breeze, FL, USA
- Syngenta, Research Triangle Park, NC, 27709, USA
| | - Deborah N Vivian
- Office of Research and Development, U.S. EPA, U.S. EPA, 1 Sabine Island Drive, Gulf Breeze, FL, USA
| | - Sandy Raimondo
- Office of Research and Development, U.S. EPA, U.S. EPA, 1 Sabine Island Drive, Gulf Breeze, FL, USA
| | | | - Mace G Barron
- Office of Research and Development, U.S. EPA, U.S. EPA, 1 Sabine Island Drive, Gulf Breeze, FL, USA.
| |
Collapse
|
14
|
Shavalieva G, Papadokonstantakis S, Peters G. Prior Knowledge for Predictive Modeling: The Case of Acute Aquatic Toxicity. J Chem Inf Model 2022; 62:4018-4031. [PMID: 35998659 PMCID: PMC9472271 DOI: 10.1021/acs.jcim.1c01079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Indexed: 11/30/2022]
Abstract
Early assessment of the potential impact of chemicals on health and the environment requires toxicological properties of the molecules. Predictive modeling is often used to estimate the property values in silico from pre-existing experimental data, which is often scarce and uncertain. One of the ways to advance the predictive modeling procedure might be the use of knowledge existing in the field. Scientific publications contain a vast amount of knowledge. However, the amount of manual work required to process the enormous volumes of information gathered in scientific articles might hinder its utilization. This work explores the opportunity of semiautomated knowledge extraction from scientific papers and investigates a few potential ways of its use for predictive modeling. The knowledge extraction and predictive modeling are applied to the field of acute aquatic toxicity. Acute aquatic toxicity is an important parameter of the safety assessment of chemicals. The extensive amount of diverse information existing in the field makes acute aquatic toxicity an attractive area for investigation of knowledge use for predictive modeling. The work demonstrates that the knowledge collection and classification procedure could be useful in hybrid modeling studies concerning the model and predictor selection, addressing data gaps, and evaluation of models' performance.
Collapse
Affiliation(s)
- Gulnara Shavalieva
- Department
of Space, Earth and Environment, Division of Energy Technology, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden
| | - Stavros Papadokonstantakis
- Department
of Space, Earth and Environment, Division of Energy Technology, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden
- Institute
of Chemical, Environmental and Bioscience Engineering, TU Wien, Getreidemarkt 9, 1060 Vienna, Austria
| | - Gregory Peters
- Department
of Technology Management and Economics, Chalmers University of Technology, SE-411 33 Gothenburg, Sweden
| |
Collapse
|
15
|
Larras F, Charles S, Chaumot A, Pelosi C, Le Gall M, Mamy L, Beaudouin R. A critical review of effect modeling for ecological risk assessment of plant protection products. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:43448-43500. [PMID: 35391640 DOI: 10.1007/s11356-022-19111-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 02/03/2022] [Indexed: 06/14/2023]
Abstract
A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).
Collapse
Affiliation(s)
- Floriane Larras
- INRAE, Directorate for Collective Scientific Assessment, Foresight and Advanced Studies, Paris, 75338, France
| | - Sandrine Charles
- University of Lyon, University Lyon 1, CNRS UMR 5558, Laboratory of Biometry and Evolutionary Biology, Villeurbanne Cedex, 69622, France
| | - Arnaud Chaumot
- INRAE, UR RiverLy, Ecotoxicology laboratory, Villeurbanne, F-69625, France
| | - Céline Pelosi
- Avignon University, INRAE, UMR EMMAH, Avignon, 84000, France
| | - Morgane Le Gall
- Ifremer, Information Scientifique et Technique, Bibliothèque La Pérouse, Plouzané, 29280, France
| | - Laure Mamy
- Université Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, Thiverval-Grignon, 78850, France
| | - Rémy Beaudouin
- Ineris, Experimental Toxicology and Modelling Unit, UMR-I 02 SEBIO, Verneuil en Halatte, 65550, France.
| |
Collapse
|
16
|
Gui B, Wang C, Xu X, Li C, Zhao Y, Su L. Identification of active or inactive agonists of tumor suppressor protein based on Tox21 library. Toxicology 2022; 474:153224. [PMID: 35659517 DOI: 10.1016/j.tox.2022.153224] [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: 02/15/2022] [Revised: 05/15/2022] [Accepted: 05/25/2022] [Indexed: 11/18/2022]
Abstract
Exposure of cells to xenobiotic human-made products can lead to genotoxicity and cause DNA damage. It is an urgent need to quickly identify the chemicals that cause DNA damage, and their toxicity should be predicted. In this study, recursive partitioning (RP), binary logistic regression, and one machine learning approach, namely, random forest (RF) classifier, were used to predict the active and inactive compounds of a total 5036 data based on the assay conducted by a β-lactamase reporter gene under control of the p53 response element (p53RE) from Tox21 library. Results show that the binary logistic regression model with a threshold of 0.5 has a high accuracy rate (83%) to distinguish active and inactive compounds. The RF classifier method has satisfactory results, with an accuracy rate (84.38%) approximately higher than that of binary logistic regression. The models established can identify compounds that induce DNA damage and activate p53, and provide a scientific basis for the risk assessment of organic chemicals in the environment.
Collapse
Affiliation(s)
- Bingxin Gui
- State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, 2555 Jingyue Street, Changchun 130117 Jilin, PR China
| | - Chen Wang
- State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, 2555 Jingyue Street, Changchun 130117 Jilin, PR China
| | - Xiaotian Xu
- State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, 2555 Jingyue Street, Changchun 130117 Jilin, PR China
| | - Chao Li
- State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, 2555 Jingyue Street, Changchun 130117 Jilin, PR China
| | - Yuanhui Zhao
- State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, 2555 Jingyue Street, Changchun 130117 Jilin, PR China
| | - Limin Su
- State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, 2555 Jingyue Street, Changchun 130117 Jilin, PR China.
| |
Collapse
|
17
|
Multi-Strategy Assessment of Different Uses of QSAR under REACH Analysis of Alternatives to Advance Information Transparency. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19074338. [PMID: 35410019 PMCID: PMC8998180 DOI: 10.3390/ijerph19074338] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 03/13/2022] [Accepted: 03/17/2022] [Indexed: 11/16/2022]
Abstract
Under the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) analysis of alternatives (AoA) process, quantitative structure–activity relationship (QSAR) models play an important role in expanding information gathering and organizing frameworks. Increasingly recognized as an alternative to testing under registration. QSARs have become a relevant tool in bridging data gaps and supporting weight of evidence (WoE) when assessing alternative substances. Additionally, QSARs are growing in importance in integrated testing strategies (ITS). For example, the REACH ITS framework for specific endpoints directs registrants to consider non-testing results, including QSAR predictions, when deciding if further animal testing is needed. Despite the raised profile of QSARs in these frameworks, a gap exists in the evaluation of QSAR use and QSAR documentation under authorization. An assessment of the different uses (e.g., WoE and ITS) in which QSAR predictions play a role in evidence gathering and organizing remains unaddressed for AoA. This study approached the disparity in information for QSAR predictions by conducting a substantive review of 24 AoA through May 2017, which contained higher-tier endpoints under REACH. Understanding the manner in which applicants manage QSAR prediction information in AoA and assessing their potential within ITS will be valuable in promoting regulatory use of QSARs and building out future platforms in the face of rapidly evolving technology while advancing information transparency.
Collapse
|
18
|
Barron MG, Otter RR, Connors KA, Kienzler A, Embry MR. Ecological Thresholds of Toxicological Concern: A Review. FRONTIERS IN TOXICOLOGY 2022; 3:640183. [PMID: 35295098 PMCID: PMC8915905 DOI: 10.3389/ftox.2021.640183] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 02/10/2021] [Indexed: 12/22/2022] Open
Abstract
The ecological threshold of toxicological concern (ecoTTC) is analogous to traditional human health-based TTCs but with derivation and application to ecological species. An ecoTTC is computed from the probability distribution of predicted no effect concentrations (PNECs) derived from either chronic or extrapolated acute toxicity data for toxicologically or chemically similar groups of chemicals. There has been increasing interest in using ecoTTCs in screening level environmental risk assessments and a computational platform has been developed for derivation with aquatic species toxicity data (https://envirotoxdatabase.org/). Current research and development areas include assessing mode of action-based chemical groupings, conservatism in estimated PNECs and ecoTTCs compared to existing regulatory values, and the influence of taxa (e.g., algae, invertebrates, and fish) composition in the distribution of PNEC values. The ecoTTC continues to develop as a valuable alternative strategy within the toolbox of traditional and new approach methods for ecological chemical assessment. This brief review article describes the ecoTTC concept and potential applications in ecological risk assessment, provides an overview of the ecoTTC workflow and how the values can be derived, and highlights recent developments and ongoing research. Future applications of ecoTTC concept in different disciplines are discussed along with opportunities for its use.
Collapse
Affiliation(s)
- Mace G Barron
- U.S. EPA, Office of Research & Development, Gulf Breeze, FL, United States
| | - Ryan R Otter
- The Data Science Institute, Middle Tennessee State University, Murfreesboro, TN, United States
| | | | - Aude Kienzler
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Michelle R Embry
- Health and Environmental Sciences Institute, Washington, DC, United States
| |
Collapse
|
19
|
Trinh TX, Seo M, Yoon TH, Kim J. Developing random forest based QSAR models for predicting the mixture toxicity of TiO 2 based nano-mixtures to Daphnia magna. NANOIMPACT 2022; 25:100383. [PMID: 35559889 DOI: 10.1016/j.impact.2022.100383] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 11/20/2021] [Accepted: 01/14/2022] [Indexed: 05/24/2023]
Abstract
During emission, TiO2 nanoparticles (NPs) might meet various chemicals, including metal ions and organic compounds in aquatic environments (e.g., surface water, sediments). At environmentally safe concentrations, combinations of both TiO2 NPs and those chemicals might cause cocktail effects (i.e., mixture toxicity) to aquatic organisms. Previous models such as concentration addition and independent action require dose-response curves of single components in the mixtures to predict the mixture toxicity. Structure-activity relationship (QSAR) models might predict the toxicity of nano-mixtures without dose-response curves of single components in the mixtures. However, current quantitative structure-activity relationship (QSAR) models are mainly focused on predicting cytotoxicity (i.e., cell viability) of heterogeneous metallic TiO2 nanoparticles (NPs) or mixtures of TiO2 NPs and four metal ions (Cu2+, Cd2+, Ni2+, and Zn2+). To minimize the experimental cost of nano-mixture risk assessment, in this study, we developed novel nano-mixture QSAR models to predict i) EC50 of 76 nano-mixtures containing TiO2 NPs and one of eight inorganic/organic compounds (i.e., AgNO3, Cd(NO3)2, Cu(NO3)2, CuSO4, Na2HAsO4, NaAsO2, Benzylparaben and Benzophenone-3), to Daphnia magna(D. magna), and ii) immobilization of D. magna exposed to one of 98 mixtures containing TiO2 NPs and one of eleven inorganic/organic compounds (i.e., AgNO3, Cd(NO3)2, Cu(NO3)2, CuSO4, Na2HAsO4, NaAsO2, Benzylparaben Benzophenone-3, Pirimicarb, Pentabromodiphenyl Ether and Triton X-100). The nano-mixture QSAR models were developed with mixture descriptors (Dmix) combing quantum descriptors of mixture components (e.g., TiO2 NPs and its partners) by using different machine learning techniques (i.e., random forest, neural network, support vector machine, and multiple linear regression). Nano-mixture QSAR models built with the random forest algorithm and proposed mixture descriptors exhibited good performance for predicting logEC50 (Adj.R2test = 0.955 ± 0.003, RMSEtest = 0.016 ± 0.002, and MAEtest = 0.008 ± 0.001) and immobilization (Adj.R2test = 0.888 ± 0.011, RMSEtest = 11.327 ± 0.730, and MAEtest = 5.933 ± 0.442). The models developed in this study were implemented in a user-friendly application for assessing the aquatic toxicity of TiO2 based nano-mixtures.
Collapse
Affiliation(s)
- Tung X Trinh
- Chemical Safety Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Republic of Korea; Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Republic of Korea
| | - Myungwon Seo
- Chemical Safety Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Republic of Korea
| | - Tae Hyun Yoon
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Republic of Korea; Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Republic of Korea
| | - Jongwoon Kim
- Chemical Safety Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon 34114, Republic of Korea.
| |
Collapse
|
20
|
Astuto MC, Di Nicola MR, Tarazona JV, Rortais A, Devos Y, Liem AKD, Kass GEN, Bastaki M, Schoonjans R, Maggiore A, Charles S, Ratier A, Lopes C, Gestin O, Robinson T, Williams A, Kramer N, Carnesecchi E, Dorne JLCM. In Silico Methods for Environmental Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives. Methods Mol Biol 2022; 2425:589-636. [PMID: 35188648 DOI: 10.1007/978-1-0716-1960-5_23] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
This chapter aims to introduce the reader to the basic principles of environmental risk assessment of chemicals and highlights the usefulness of tiered approaches within weight of evidence approaches in relation to problem formulation i.e., data availability, time and resource availability. In silico models are then introduced and include quantitative structure-activity relationship (QSAR) models, which support filling data gaps when no chemical property or ecotoxicological data are available. In addition, biologically-based models can be applied in more data rich situations and these include generic or species-specific models such as toxicokinetic-toxicodynamic models, dynamic energy budget models, physiologically based models, and models for ecosystem hazard assessment i.e. species sensitivity distributions and ultimately for landscape assessment i.e. landscape-based modeling approaches. Throughout this chapter, particular attention is given to provide practical examples supporting the application of such in silico models in real-world settings. Future perspectives are discussed to address environmental risk assessment in a more holistic manner particularly for relevant complex questions, such as the risk assessment of multiple stressors and the development of harmonized approaches to ultimately quantify the relative contribution and impact of single chemicals, multiple chemicals and multiple stressors on living organisms.
Collapse
Affiliation(s)
| | | | | | - A Rortais
- European Food Safety Authority, Parma, Italy
| | - Yann Devos
- European Food Safety Authority, Parma, Italy
| | | | | | | | | | | | | | | | | | | | | | - Antony Williams
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency (U.S. EPA), Research Triangle Park, NC, USA
| | - Nynke Kramer
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands
| | - Edoardo Carnesecchi
- Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands
| | | |
Collapse
|
21
|
Rizzi C, Villa S, Cuzzeri AS, Finizio A. Use of the Species Sensitivity Distribution Approach to Derive Ecological Threshold of Toxicological Concern (eco-TTC) for Pesticides. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:12078. [PMID: 34831835 PMCID: PMC8623465 DOI: 10.3390/ijerph182212078] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 11/11/2021] [Accepted: 11/11/2021] [Indexed: 11/16/2022]
Abstract
The species sensitivity distribution (SSD) calculates the hazardous concentration at which 5% of species (HC5) will be potentially affected. For many compounds, HC5 values are unavailable impeding the derivation of SSD curves. Through a detailed bibliographic survey, we selected HC5 values (from acute toxicity tests) for freshwater aquatic species and 129 pesticides. The statistical distribution and variability of the HC5 values within the chemical classes were evaluated. Insecticides are the most toxic compounds in the aquatic communities (HC5 = 1.4 × 10-3 µmol L-1), followed by herbicides (HC5 = 3.3 × 10-2 µmol L-1) and fungicides (HC5 = 7.8 µmol L-1). Subsequently, the specificity of the mode of action (MoA) of pesticides on freshwater aquatic communities was investigated by calculating the ratio between the estimated baseline toxicity for aquatic communities and the HC5 experimental values gathered from the literature. Moreover, we proposed and validated a scheme to derive the ecological thresholds of toxicological concern (eco-TTC) of pesticides for which data on their effects on aquatic communities are not available. We proposed eco-TTCs for different classes of insecticides, herbicides, and fungicides with a specific MoA, and three eco-TTCs for those chemicals with unavailable MoA. We consider the proposed approach and eco-TTC values useful for risk management purposes.
Collapse
Affiliation(s)
| | - Sara Villa
- Department of Earth and Environmental Sciences DISAT, University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy; (C.R.); (A.S.C.); (A.F.)
| | | | | |
Collapse
|
22
|
Manggara AB, Ohkawa K, Sugimoto M. Classifying Modes of Toxic Action of Molecules with Electronic-structure Informatics. Application to Imbalanced Toxicity Data of Phenol Derivatives to Tetrahymena pyriformis. CHEM LETT 2021. [DOI: 10.1246/cl.210453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Algafari Bakti Manggara
- Graduate School of Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan
| | - Kazufumi Ohkawa
- Graduate School of Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan
| | - Manabu Sugimoto
- Graduate School of Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan
- Faculty of Advanced Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan
- Institute of Industrial Nanomaterials, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan
| |
Collapse
|
23
|
Bai Y, Lian D, Su T, Wang YYL, Zhang D, Wang Z, Gimeno S, You J. Species and Life-Stage Sensitivity of Chinese Rare Minnow (Gobiocypris rarus) to Chemical Exposure: A Critical Review. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2021; 40:2680-2692. [PMID: 34265131 DOI: 10.1002/etc.5165] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 05/03/2021] [Accepted: 07/09/2021] [Indexed: 06/13/2023]
Abstract
Chemical production and consumption in Asia are increasing at an unprecedented rate, calling for regulations on chemical management. Under the New Chemical Substance Notification in China, information on ecotoxicological effects of chemicals is mandatory for the simplified registration of chemicals with the requirement that one ecotoxicological test is conducted locally. It is now mandatory to use the native fish species Chinese rare minnow (Gobiocypris rarus). However, its chemical sensitivity compared to that of fathead minnow (Pimephales promelas) or zebrafish (Danio rerio) is still unclear. We performed a holistic literature review on toxicity data with G. rarus from 1997 to 2020. Species sensitivity among G. rarus, P. promelas, and D. rerio and life-stage sensitivity of G. rarus were systematically investigated for various chemicals using both chemical ratio distribution and probabilistic chemical toxicity distribution approaches. Comparatively, the Chinese native fish species G. rarus was more sensitive than D. rerio, particularly to metals. Juvenile and adult G. rarus were more sensitive than its larvae and embryos. The observed lower sensitivity of G. rarus embryo was likely due to the thick embryonic chorion, discrepant methods of collecting embryos, and the paucity of toxicity data, implying the necessity to standardize G. rarus embryo tests and validate the sensitivity with various types of chemicals. This unique review allows us to conclude that G. rarus studies could be used in worldwide registrations and that further investigations are needed to use G. rarus embryos as alternatives to the fish test. Environ Toxicol Chem 2021;40:2680-2692. © 2021 SETAC.
Collapse
Affiliation(s)
- Yunfei Bai
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
| | - Deru Lian
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
| | - Tenghui Su
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
| | - Yolina Yu Lin Wang
- Institute of Marine Sciences and Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, Shantou, China
| | - Dainan Zhang
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
| | - Zhen Wang
- Institute of Marine Sciences and Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, Shantou, China
| | - Sylvia Gimeno
- Firmenich Belgium, Legal and Compliance, Global Registration Services, Louvain-La-Neuve, Belgium
| | - Jing You
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, China
| |
Collapse
|
24
|
Gajewicz-Skretna A, Furuhama A, Yamamoto H, Suzuki N. Generating accurate in silico predictions of acute aquatic toxicity for a range of organic chemicals: Towards similarity-based machine learning methods. CHEMOSPHERE 2021; 280:130681. [PMID: 34162070 DOI: 10.1016/j.chemosphere.2021.130681] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 04/21/2021] [Accepted: 04/22/2021] [Indexed: 06/13/2023]
Abstract
There has been an increase in the use of non-animal approaches, such as in silico and/or in vitro methods, for assessing the risks of hazardous chemicals. A number of machine learning algorithms link molecular descriptors that interpret chemical structural properties with their biological activity. These computer-aided methods encounter several challenges, the most significant being the heterogeneity of datasets; more efficient and inclusive computational methods that are able to process large and heterogeneous chemical datasets are needed. In this context, this study verifies the utility of similarity-based machine learning methods in predicting the acute aquatic toxicity of diverse organic chemicals on Daphnia magna and Oryzias latipes. Two similarity-based methods were tested that employ a limited training dataset, most similar to a given fitting point, instead of using the entire dataset that encompasses a wide range of chemicals. The kernel-weighted local polynomial approach had a number of advantages over the distance-weighted k-nearest neighbor (k-NN) algorithm. The results highlight the importance of lipophilicity, electrophilic reactivity, molecular polarizability, and size in determining acute toxicity. The rigorous model validation ensures that this approach is an important tool for estimating toxicity in new or untested chemicals.
Collapse
Affiliation(s)
- Agnieszka Gajewicz-Skretna
- Laboratory of Environmental Chemometrics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308, Gdansk, Poland.
| | - Ayako Furuhama
- Center for Health and Environmental Risk Research, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba, 305-8506, Japan; Division of Genetics and Mutagenesis, National Institute of Health Sciences (NIHS), 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki City, Kanagawa, 210-9501, Japan
| | - Hiroshi Yamamoto
- Center for Health and Environmental Risk Research, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba, 305-8506, Japan
| | - Noriyuki Suzuki
- Center for Health and Environmental Risk Research, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba, 305-8506, Japan
| |
Collapse
|
25
|
Embry MR, Belanger SE, Connors KA, Otter R. Comment on Plugge et al. 2021 "Toward a Universal Acute Fish Threshold of Toxicological Concern". ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2021; 40:2379-2381. [PMID: 34437737 DOI: 10.1002/etc.5124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 04/14/2021] [Indexed: 06/13/2023]
Affiliation(s)
- Michelle R Embry
- Health and Environmental Sciences Institute, Washington, DC, USA
| | | | | | - Ryan Otter
- Middle Tennessee State University, Murfreesboro, Tennessee, USA
| |
Collapse
|
26
|
Huang H, Jin Y, Chen C, Feng M, Wang Q, Li D, Chen W, Xing X, Yu D, Xiao Y. A toxicity pathway-based approach for modeling the mode of action framework of lead-induced neurotoxicity. ENVIRONMENTAL RESEARCH 2021; 199:111328. [PMID: 34004169 DOI: 10.1016/j.envres.2021.111328] [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: 12/08/2020] [Revised: 04/16/2021] [Accepted: 05/11/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND The underlying mechanisms of lead (Pb) toxicity are not fully understood, which makes challenges to the traditional risk assessment. There is growing use of the mode of action (MOA) for risk assessment by integration of experimental data and system biology. The current study aims to develop a new pathway-based MOA for assessing Pb-induced neurotoxicity. METHODS The available Comparative Toxicogenomic Database (CTD) was used to search genes associated with Pb-induced neurotoxicity followed by developing toxicity pathways using Ingenuity Pathway Analysis (IPA). The spatiotemporal sequence of disturbing toxicity pathways and key events (KEs) were identified by upstream regulator analysis. The MOA framework was constructed by KEs in biological and chronological order. RESULTS There were a total of 71 references showing the relationship between lead exposure and neurotoxicity, which contained 2331 genes. IPA analysis showed that the neuroinflammation signaling pathway was the core toxicity pathway in the enriched pathways relevant to Pb-induced neurotoxicity. The upstream regulator analysis demonstrated that the aryl hydrocarbon receptor (AHR) signaling pathway was the upstream regulator of the neuroinflammation signaling pathway (11.76% overlap with upstream regulators, |Z-score|=1.451). Therefore, AHR activation was recognized as the first key event (KE1) in the MOA framework. The following downstream molecular and cellular key events were also identified. The pathway-based MOA framework of Pb-induced neurotoxicity was built starting with AHR activation, followed by an inflammatory response and neuron apoptosis. CONCLUSION Our toxicity pathway-based approach not only advances the development of risk assessment for Pb-induced neurotoxicity but also brings new insights into constructing MOA frameworks of risk assessment for new chemicals.
Collapse
Affiliation(s)
- Hehai Huang
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuan Jin
- Department of Toxicology, School of Public Health, Qingdao University, Qingdao, 266071, China
| | - Chuanying Chen
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Meiyao Feng
- Department of Toxicology, School of Public Health, Qingdao University, Qingdao, 266071, China
| | - Qing Wang
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Daochuan Li
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Wen Chen
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Xiumei Xing
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Dianke Yu
- Department of Toxicology, School of Public Health, Qingdao University, Qingdao, 266071, China.
| | - Yongmei Xiao
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
| |
Collapse
|
27
|
Belanger SE, Beasley A, Brill JL, Krailler J, Connors KA, Carr GJ, Embry M, Barron MG, Otter R, Kienzler A. Comparisons of PNEC derivation logic flows under example regulatory schemes and implications for ecoTTC. Regul Toxicol Pharmacol 2021; 123:104933. [PMID: 33891999 PMCID: PMC10461128 DOI: 10.1016/j.yrtph.2021.104933] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 04/07/2021] [Accepted: 04/12/2021] [Indexed: 11/18/2022]
Abstract
Derivation of Predicted No Effect Concentrations (PNECs) for aquatic systems is the primary deterministic form of hazard extrapolation used in environmental risk assessment. Depending on the data availability, different regulatory jurisdictions apply application factors (AFs) to the most sensitive measured endpoint to derive the PNEC for a chemical. To assess differences in estimated PNEC values, two PNEC determination methodologies were applied to a curated public database using the EnviroTox Platform (www.EnviroToxdatabase.org). PNECs were derived for 3647 compounds using derivation procedures based on example US EPA and a modified European Union chemical registration procedure to allow for comparisons. Ranked probability distributions of PNEC values were developed and 5th percentile values were calculated for the entire dataset and scenarios where full acute or full chronic data sets were available. The lowest PNEC values indicated categorization based on chemical attributes and modes of action would lead to improved extrapolations. Full acute or chronic datasets gave measurably higher 5th percentile PNEC values. Algae were under-represented in available ecotoxicity data but drove PNECs disproportionately. Including algal inhibition studies will be important in understanding chemical hazards. The PNEC derivation logic flows are embedded in the EnviroTox Platform providing transparent and consistent PNEC derivations and PNEC distribution calculations.
Collapse
Affiliation(s)
- S E Belanger
- The Procter & Gamble Company, Cincinnati, OH, USA.
| | - A Beasley
- The Dow Chemical Company, Midland, MI, USA.
| | - J L Brill
- The Procter & Gamble Company, Cincinnati, OH, USA.
| | - J Krailler
- The Procter & Gamble Company, Cincinnati, OH, USA.
| | - K A Connors
- The Procter & Gamble Company, Cincinnati, OH, USA.
| | - G J Carr
- The Procter & Gamble Company, Cincinnati, OH, USA.
| | - M Embry
- Health and Environmental Sciences Institute, Washington, DC, USA.
| | - M G Barron
- U.S. EPA, Office of Research & Development, Gulf Breeze, FL, USA.
| | - R Otter
- The Data Science Institute, Middle Tennessee State University, Murfreesboro, TN, USA.
| | - A Kienzler
- European Commission, Joint Research Centre, Ispra, Italy.
| |
Collapse
|
28
|
Toth GP, Bencic DC, Martinson JW, Flick RW, Lattier DL, Kostich MS, Huang W, Biales AD. Development of omics biomarkers for estrogen exposure using mRNA, miRNA and piRNAs. AQUATIC TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2021; 235:105807. [PMID: 33838496 DOI: 10.1016/j.aquatox.2021.105807] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 03/03/2021] [Accepted: 03/05/2021] [Indexed: 06/12/2023]
Abstract
The number of chemicals requiring risk evaluation exceeds our capacity to provide the underlying data using traditional methodology. This has led to an increased focus on the development of novel approach methodologies. This work aimed to expand the panel of gene expression-based biomarkers to include responses to estrogens, to identify training strategies that maximize the range of applicable concentrations, and to evaluate the potential for two classes of small non-coding RNAs (sncRNAs), microRNA (miRNA) and piwi-interacting RNA (piRNA), as biomarkers. To this end larval Pimephales promelas (96 hpf +/- 1h) were exposed to 5 concentrations of 17α- ethinylestradiol (0.12, 1.25, 2.5, 5.0, 10.0 ng/L) for 48 h. For mRNA-based biomarker development, RNA-seq was conducted across all concentrations. For sncRNA biomarkers, small RNA libraries were prepared only for the control and 10.0 ng/L EE2 treatment. In order to develop an mRNA classifier that remained accurate over the range of exposure concentrations, three different training strategies were employed that focused on 10 ng/L, 2.5 ng/L or a combination of both. Classifiers were tested against an independent test set of individuals exposed to the same concentrations used in training and subsequently against concentrations not included in model training. Both random forest (RF) and logistic regression with elastic net regularizations (glmnet) models trained on 10 ng/L EE2 performed poorly when applied to lower concentrations. RF models trained with either the 2.5 ng/L or combination (2.5 + 10 ng/L) treatments were able to accurately discriminate exposed vs. non-exposed across all but the lowest concentrations. glmnet models were unable to accurately classify below 5 ng/L. With the exception of the 10 ng/L treatment, few mRNA differentially expressed genes (DEG) were observed, however, there was marked overlap of DEGs across treatments. Overlapping DEGs have well established linkages to estrogen and several of the 81 DEGs identified in the 10 ng/L treatment have been previously utilized as estrogenic biomarkers (vitellogenin, estrogen receptor-β). Following multiple test correction, no sncRNAs were found to be differentially expressed, however, both miRNA and piRNA classifiers were able to accurately discriminate control and 10 ng/L exposed organisms with AUCs of 0.83 and 1.0 respectively. We have developed a highly discriminative estrogenic mRNA biomarker that is accurate over a range of concentrations likely to be found in real-world exposures. We have demonstrated that both miRNA and piRNA are responsive to estrogenic exposure, suggesting the need to further investigate their regulatory roles in the estrogenic response.
Collapse
Affiliation(s)
- Gregory P Toth
- US Environmental Protection Agency, Office of Research and Development, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, United States
| | - David C Bencic
- US Environmental Protection Agency, Office of Research and Development, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, United States
| | - John W Martinson
- US Environmental Protection Agency, Office of Research and Development, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, United States
| | - Robert W Flick
- US Environmental Protection Agency, Office of Research and Development, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, United States
| | - David L Lattier
- US Environmental Protection Agency, Office of Research and Development, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, United States
| | - Mitchell S Kostich
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Dr, Farmington, CT 06032, United States
| | - Weichun Huang
- US Environmental Protection Agency, Office of Research and Development, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Adam D Biales
- US Environmental Protection Agency, Office of Research and Development, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, United States.
| |
Collapse
|
29
|
Hernandez‐Jerez A, Adriaanse P, Aldrich A, Berny P, Coja T, Duquesne S, Focks A, Marina M, Millet M, Pelkonen O, Tiktak A, Topping C, Widenfalk A, Wilks M, Wolterink G, Conrad A, Pieper S. Statement of the PPR Panel on a framework for conducting the environmental exposure and risk assessment for transition metals when used as active substances in plant protection products (PPP). EFSA J 2021; 19:e06498. [PMID: 33815619 PMCID: PMC8006092 DOI: 10.2903/j.efsa.2021.6498] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
The European Commission asked the European Food Safety Authority (EFSA) to prepare a statement on a framework for the environmental risk assessment (ERA) of transition metals (e.g. iron and copper) used as active substances in plant protection products (PPPs). Non-degradability, essentiality and specific conditions affecting fate and behaviour as well as their toxicity are distinctive characteristics possibly not covered in current guidance for PPPs. The proposed risk assessment framework starts with a preliminary phase, in which monitoring data on transition metals in relevant environmental compartments are provided. They deliver the metal natural background and anthropogenic residue levels to be considered in the exposure calculations. A first assessment step is then performed assuming fully bioavailable residues. Should the first step fail, refined ERA can, in principle, consider bioavailability issues; however, non-equilibrium conditions need to be taken into account. Simple models that are fit for purpose should be employed in order to avoid unnecessary complexity. Exposure models and scenarios would need to be adapted to address environmental processes and parameters relevant to the fate and behaviour of transition metals in water, sediment and soils (e.g. speciation). All developments should follow current EFSA guidance documents. If refined approaches have been used in the risk assessment of PPPs containing metals, post-registration monitoring and controlled long-term studies should be conducted and assessed. Utilisation of the same transition metal in other PPPs or for other uses will lead to accumulation in environmental compartments acting as sinks. In general, it has to be considered that the prospective risk assessment of metal-containing PPPs can only cover a defined period as there are limitations in the long-term hazard assessment due to issues of non-degradability. It is therefore recommended to consider these aspects in any risk management decisions and to align the ERA with the goals of other overarching legislative frameworks.
Collapse
|
30
|
Sapounidou M, Ebbrell DJ, Bonnell MA, Campos B, Firman JW, Gutsell S, Hodges G, Roberts J, Cronin MTD. Development of an Enhanced Mechanistically Driven Mode of Action Classification Scheme for Adverse Effects on Environmental Species. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:1897-1907. [PMID: 33478211 DOI: 10.1021/acs.est.0c06551] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
This study developed a novel classification scheme to assign chemicals to a verifiable mechanism of (eco-)toxicological action to allow for grouping, read-across, and in silico model generation. The new classification scheme unifies and extends existing schemes and has, at its heart, direct reference to molecular initiating events (MIEs) promoting adverse outcomes. The scheme is based on three broad domains of toxic action representing nonspecific toxicity (e.g., narcosis), reactive mechanisms (e.g., electrophilicity and free radical action), and specific mechanisms (e.g., associated with enzyme inhibition). The scheme is organized at three further levels of detail beyond broad domains to separate out the mechanistic group, specific mechanism, and the MIEs responsible. The novelty of this approach comes from the reference to taxonomic diversity within the classification, transparency, quality of supporting evidence relating to MIEs, and that it can be updated readily.
Collapse
Affiliation(s)
- Maria Sapounidou
- School of Pharmacy and Bimolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, U.K
| | - David J Ebbrell
- School of Pharmacy and Bimolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, U.K
| | - Mark A Bonnell
- Science and Risk Assessment Directorate, Environment & Climate Change Canada, 351 St. Joseph Blvd, Gatineau, Quebec K1A 0H3, Canada
| | - Bruno Campos
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - James W Firman
- School of Pharmacy and Bimolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, U.K
| | - Steve Gutsell
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Geoff Hodges
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Jayne Roberts
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K
| | - Mark T D Cronin
- School of Pharmacy and Bimolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, U.K
| |
Collapse
|
31
|
van den Berg SJP, Maltby L, Sinclair T, Liang R, van den Brink PJ. Cross-species extrapolation of chemical sensitivity. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 753:141800. [PMID: 33207462 DOI: 10.1016/j.scitotenv.2020.141800] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 08/15/2020] [Accepted: 08/17/2020] [Indexed: 06/11/2023]
Abstract
Ecosystems are usually populated by many species. Each of these species carries the potential to show a different sensitivity towards all of the numerous chemical compounds that can be present in their environment. Since experimentally testing all possible species-chemical combinations is impossible, the ecological risk assessment of chemicals largely depends on cross-species extrapolation approaches. This review overviews currently existing cross-species extrapolation methodologies, and discusses i) how species sensitivity could be described, ii) which predictors might be useful for explaining differences in species sensitivity, and iii) which statistical considerations are important. We argue that risk assessment can benefit most from modelling approaches when sensitivity is described based on ecologically relevant and robust effects. Additionally, specific attention should be paid to heterogeneity of the training data (e.g. exposure duration, pH, temperature), since this strongly influences the reliability of the resulting models. Regarding which predictors are useful for explaining differences in species sensitivity, we review interspecies-correlation, relatedness-based, traits-based, and genomic-based extrapolation methods, describing the amount of mechanistic information the predictors contain, the amount of input data the models require, and the extent to which the different methods provide protection for ecological entities. We develop a conceptual framework, incorporating the strengths of each of the methods described. Finally, the discussion of statistical considerations reveals that regardless of the method used, statistically significant models can be found, although the usefulness, applicability, and understanding of these models varies considerably. We therefore recommend publication of scientific code along with scientific studies to simultaneously clarify modelling choices and enable elaboration on existing work. In general, this review specifies the data requirements of different cross-species extrapolation methods, aiming to make regulators and publishers more aware that access to raw- and meta-data needs to be improved to make future cross-species extrapolation efforts successful, enabling their integration into the regulatory environment.
Collapse
Affiliation(s)
- Sanne J P van den Berg
- Aquatic Ecology and Water Quality Management group, Wageningen University and Research, P.O. box 47, 6700 AA Wageningen, the Netherlands; Research Unit of Environmental and Evolutionary Biology, Namur Institute of Complex Systems, Institute of Life, Earth, and the Environment, University of Namur, Rue de Bruxelles 61, 5000 Namur, Belgium.
| | - Lorraine Maltby
- Department of Animal and Plant Sciences, The University of Sheffield, Alfred Denny Building, Western Bank, S10 2TN Sheffield, United Kingdom
| | - Tom Sinclair
- Department of Animal and Plant Sciences, The University of Sheffield, Alfred Denny Building, Western Bank, S10 2TN Sheffield, United Kingdom
| | - Ruoyu Liang
- Department of Animal and Plant Sciences, The University of Sheffield, Alfred Denny Building, Western Bank, S10 2TN Sheffield, United Kingdom
| | - Paul J van den Brink
- Aquatic Ecology and Water Quality Management group, Wageningen University and Research, P.O. box 47, 6700 AA Wageningen, the Netherlands; Wageningen Environmental Research, P.O. Box 47, 6700 AA Wageningen, the Netherlands
| |
Collapse
|
32
|
Bouhedjar K, Benfenati E, Nacereddine AK. Modelling quantitative structure activity-activity relationships (QSAARs): auto-pass-pass, a new approach to fill data gaps in environmental risk assessment under the REACH regulation. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2020; 31:785-801. [PMID: 32878491 DOI: 10.1080/1062936x.2020.1810770] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 08/12/2020] [Indexed: 06/11/2023]
Abstract
Reviewing the toxicological literature for over the past decades, the key elements of QSAR modelling have been the mechanisms of toxic action and chemical classes. As a result, it is often hard to design an acceptable single model for a particular endpoint without clustering compounds. The main aim here was to develop a Pass-Pass Quantitative Structure-Activity-Activity Relationship (PP QSAAR) model for direct prediction of the toxicity of a larger set of compounds, combing the application of an already predicted model for another species, and molecular descriptors. We investigated a large acute toxicity data set of five aquatic organisms, fish, Daphnia magna, and algae from the VEGA-Hub, as well as Tetrahymena pyriformis and Vibrio fischeri. The statistical quality of the models encouraged us to consider this alternative for the prediction of toxicity using interspecies extrapolation QSAAR models without regard to the toxicity mechanism or chemical class. In the case of algae, the use of activity values from a second species did not improve the models. This can be attributed to the weak interspecies relationships, due to different aquatic toxicity mechanisms in species.
Collapse
Affiliation(s)
- K Bouhedjar
- Laboratoire de Synthèse et Biocatalyse Organique, Département de Chimie, Faculté des Sciences, Université Badji Mokhtar Annaba , Annaba, Algeria
- Laboratoire Bioinformatique, Centre de Recherche en Biotechnologie (CRBt) , Constantine, Algeria
- Laboratory of Environmental Chemistry and Toxicology, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS , Milano, Italy
| | - E Benfenati
- Laboratory of Environmental Chemistry and Toxicology, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS , Milano, Italy
| | - A K Nacereddine
- Laboratory of Physical Chemistry and Biology of Materials, Department of Physics and Chemistry, Higher Normal School of Technological Education-Skikda , Skikda, Algeria
| |
Collapse
|
33
|
Tinkov OV, Grigorev VY, Razdolsky AN, Grigoryeva LD, Dearden JC. Effect of the structural factors of organic compounds on the acute toxicity toward Daphnia magna. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2020; 31:615-641. [PMID: 32713201 DOI: 10.1080/1062936x.2020.1791250] [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: 05/14/2020] [Accepted: 06/30/2020] [Indexed: 06/11/2023]
Abstract
The acute toxicity of organic compounds towards Daphina magna was subjected to QSAR analysis. The two-dimensional simplex representation of molecular structure (2D SiRMS) and the support vector machine (SVM), gradient boosting (GBM) methods were used to develop QSAR models. Adequate regression QSAR models were developed for incubation of 24 h. Their interpretation allowed us to quantitatively describe and rank the well-known toxicophores, to refine their molecular surroundings, and to distinguish the structural derivatives of the fragments that significantly contribute to the acute toxicity (LC50) of organic compounds towards D. magna. Based on the results of the interpretation of the regression models, a molecular design (modification) of highly toxic compounds was performed in order to reduce their hazard. In addition, acceptable classification QSAR models were developed to reliably predict the following mode of action (MOA): specific and non-specific toxicity of organic compounds towards D. magna. When interpreting these models, we were able to determine the structural fragments and the physicochemical characteristics of molecules that are responsible for the manifestation of one of the modes of action. The on-line version of the OCHEM expert system (https://ochem.eu), HYBOT descriptors, and the random forest and SVM methods were used for a comparative QSAR investigation.
Collapse
Affiliation(s)
- O V Tinkov
- Department of Computer Science, Military Institute of the Ministry of Defense , Tiraspol, Moldova
| | - V Y Grigorev
- Department of Computer-aided Molecular Design, Institute of Physiologically Active Compounds of the Russian Academy of Science , Chernogolovka, Russia
| | - A N Razdolsky
- Department of Computer-aided Molecular Design, Institute of Physiologically Active Compounds of the Russian Academy of Science , Chernogolovka, Russia
| | - L D Grigoryeva
- Department of Fundamental Physicochemical Engineering, Moscow State University , Moscow, Russia
| | - J C Dearden
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University , Liverpool, UK
| |
Collapse
|
34
|
Escher BI, Henneberger L, König M, Schlichting R, Fischer FC. Cytotoxicity Burst? Differentiating Specific from Nonspecific Effects in Tox21 in Vitro Reporter Gene Assays. ENVIRONMENTAL HEALTH PERSPECTIVES 2020; 128:77007. [PMID: 32700975 PMCID: PMC7377237 DOI: 10.1289/ehp6664] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 06/16/2020] [Accepted: 07/02/2020] [Indexed: 05/03/2023]
Abstract
BACKGROUND High-throughput screening of chemicals with in vitro reporter gene assays in Tox21 has produced a large database on cytotoxicity and specific modes of action. However, the validity of some of the reported activities is questionable due to the "cytotoxicity burst," which refers to the supposition that many stress responses are activated in a nonspecific way at concentrations close to cell death. OBJECTIVES We propose a pragmatic method to identify whether reporter gene activation is specific or cytotoxicity-triggered by comparing the measured effects with baseline toxicity. METHODS Baseline toxicity, also termed narcosis, is the minimal toxicity any chemical causes. Quantitative structure-activity relationships (QSARs) developed for baseline toxicity in mammalian reporter gene cell lines served as anchors to define the chemical-specific threshold for the cytotoxicity burst and to evaluate the degree of specificity of the reporter gene activation. Measured 10% effect concentrations were related to measured or QSAR-predicted 10% cytotoxicity concentrations yielding specificity ratios (SR). We applied this approach to our own experimental data and to ∼ 8,000 chemicals that were tested in six of the high-throughput Tox21 reporter gene assays. RESULTS Confirmed baseline toxicants activated reporter gene activity around cytotoxic concentrations triggered by the cytotoxicity burst. In six Tox21 assays, 37%-87% of the active hits were presumably caused by the cytotoxicity burst (SR < 1 ) and only 2%-14% were specific with SR ≥ 10 against experimental cytotoxicity but 75%-97% were specific against baseline toxicity. This difference was caused by a large fraction of chemicals showing excess cytotoxicity. CONCLUSIONS The specificity analysis for measured in vitro effects identified whether a cytotoxicity burst had likely occurred. The SR-analysis not only prevented false positives, but it may also serve as measure for relative effect potency and can be used for quantitative in vitro-in vivo extrapolation and risk assessment of chemicals. https://doi.org/10.1289/EHP6664.
Collapse
Affiliation(s)
- Beate I. Escher
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
- Environmental Toxicology, Center for Applied Geoscience, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Luise Henneberger
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
| | - Maria König
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
| | - Rita Schlichting
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
| | - Fabian C. Fischer
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
| |
Collapse
|
35
|
Wang Z, Berninger JP, You J, Brooks BW. One uncertainty factor does not fit all: Identifying mode of action and species specific acute to chronic ratios for aquatic life. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 262:114262. [PMID: 32120260 DOI: 10.1016/j.envpol.2020.114262] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 02/19/2020] [Accepted: 02/22/2020] [Indexed: 06/10/2023]
Abstract
In ecological risk assessment, acute to chronic ratio (ACR) uncertainty factors are routinely applied to acute mortality benchmarks to estimate chronic toxicity thresholds. To investigate variability of aquatic ACRs, we first compiled and compared 56 and 150 pairs of acute and subchronic/chronic growth/reproductive toxicity data for fishes (Pimephales promelas (53), Danio rerio (2), and Oryzias latipes (1)) and the crustacean Daphnia magna, respectively, for 172 chemicals with different modes of action (MOA). We found that there were only significant relationships between P. promelas acute median lethal concentrations and growth lowest-observed effect concentrations for class 1 (nonpolar narcosis) chemicals, though significant relationships were demonstrated for D. magna to all Verhaar et al. MOA classes (Class 1: nonpolar narcosis, Class 2: polar narcosis, Class 3: reactive chemicals, and Class 4: AChE inhibitors and estrogenics). Probabilistic ecological hazard assessment using chemical toxicity distributions was subsequently employed for each MOA class to estimate acute and chronic thresholds, respectively, to identify MOA and species specific ecological thresholds of toxicological concern. Finally, novel MOA and species specific ACRs using both chemical toxicity distribution comparison and individual ACR probability distribution approaches were identified using representative MOA and chemical categories. Our data-driven approaches and newly identified ACR values represent robust alternatives to application of default ACR values, and can also support future research and risk assessment and management activities for other chemical classes when toxicity information is limited for chemicals with specific MOAs within invertebrates and fish.
Collapse
Affiliation(s)
- Zhen Wang
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, 510632, China; Institute of Marine Sciences and Guangdong Provincial Key Laboratory of Marine Biotechnology, Shantou University, Shantou, 515063, China
| | - Jason P Berninger
- Department of Environmental Science and Institute of Biomedical Studies, Baylor University, Waco, TX, USA
| | - Jing You
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, 510632, China.
| | - Bryan W Brooks
- School of Environment and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, 510632, China; Department of Environmental Science and Institute of Biomedical Studies, Baylor University, Waco, TX, USA
| |
Collapse
|
36
|
Abstract
An increasing number of chemicals such as pharmaceuticals, pesticides and synthetic hormones are in daily use all over the world. In the environment, chemicals can adversely affect populations and communities and in turn related ecosystem functions. To evaluate the risks from chemicals for ecosystems, data on their toxicity, which are typically produced in standardized ecotoxicological laboratory tests, is required. The results from ecotoxicological tests are compiled in (meta-)databases such as the United States Environmental Protection Agency (EPA) ECOTOXicology Knowledgebase (ECOTOX). However, for many chemicals, multiple ecotoxicity data are available for the same test organism. These can vary strongly, thereby causing uncertainty of related analyses. Given that most current databases lack aggregation steps or are confined to specific chemicals, we developed Standartox, a tool and database that continuously incorporates the ever-growing number of test results in an automated process workflow that ultimately leads to a single aggregated data point for a specific chemical-organism test combination, representing the toxicity of a chemical. Standartox can be accessed through a web application and an R package.
Collapse
|
37
|
Hou P, Jolliet O, Zhu J, Xu M. Estimate ecotoxicity characterization factors for chemicals in life cycle assessment using machine learning models. ENVIRONMENT INTERNATIONAL 2020; 135:105393. [PMID: 31862642 DOI: 10.1016/j.envint.2019.105393] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 12/03/2019] [Accepted: 12/03/2019] [Indexed: 06/10/2023]
Abstract
In life cycle assessment, characterization factors are used to convert the amount of the chemicals and other pollutants generated in a product's life cycle to the standard unit of an impact category, such as ecotoxicity. However, as a widely used impact assessment method, USEtox (version 2.11) only has ecotoxicity characterization factors for a small portion of chemicals due to the lack of laboratory experiment data. Here we develop machine learning models to estimate ecotoxicity hazardous concentrations 50% (HC50) in USEtox to calculate characterization factors for chemicals based on their physical-chemical properties in EPA's CompTox Chemical Dashborad and the classification of their mode of action. The model is validated by ten randomly selected test sets that are not used for training. The results show that the random forest model has the best predictive performance. The average root mean squared error of the estimated HC50 on the test sets is 0.761. The average coefficient of determination (R2) on the test set is 0.630, meaning 63% of the variability of HC50 in USEtox can be explained by the predicted HC50 from the random forest model. Our model outperforms a traditional quantitative structure-activity relationship (QSAR) model (ECOSAR) and linear regression models. We also provide estimates of missing ecotoxicity characterization factors for 552 chemicals in USEtox using the validated random forest model.
Collapse
Affiliation(s)
- Ping Hou
- School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA; Michigan Institute for Computational Discovery & Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Olivier Jolliet
- Environmental Health Sciences, School of Public Heath, University of Michigan, Ann Arbor, MI, USA
| | - Ji Zhu
- Department of Statistics, University of Michigan, Ann Arbor, MI, USA
| | - Ming Xu
- School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA; Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, USA.
| |
Collapse
|
38
|
Kienzler A, Bopp S, Halder M, Embry M, Worth A. Application of new statistical distribution approaches for environmental mixture risk assessment: A case study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 693:133510. [PMID: 31357034 PMCID: PMC6839615 DOI: 10.1016/j.scitotenv.2019.07.316] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 07/18/2019] [Accepted: 07/19/2019] [Indexed: 06/10/2023]
Abstract
OBJECTIVES There is growing evidence that single substances present below their individual thresholds of effect may still contribute to combined effects. In component-based mixture risk assessment (MRA), the risks can be addressed using information on the mixture components. This is, however, often hampered by limited availability of ecotoxicity data. Here, the possible use of ecotoxicological threshold concentrations of no concern (i.e. 5th percentile of statistical distribution of ecotoxicological values) is investigated to fill data gaps in MRA. METHODS For chemicals without available aquatic toxicity data, ecotoxicological threshold concentrations of no concern have been derived from Predicted No Effect Concentration (PNEC) distributions and from chemical toxicity distributions, using the EnviroTox tool, with and without considering the chemical mode of action. For exposure, chemical monitoring data from European rivers have been used to illustrate four realistic co-exposure scenarios. Based on those monitoring data and available ecotoxicity data or threshold concentrations when no data were available, Risk Quotients for individual chemicals were calculated, to then derive a mixture Risk Quotient (RQmix). RESULTS A risk was identified in two of the four scenarios. Threshold concentrations contribute from 24 to 95% of the whole RQmix; thus they have a large impact on the predicted mixture risk. Therefore they could only be used for data gap filling for a limited number of chemicals in the mixture. The use of mode of action information to derive more specific threshold values could be a helpful refinement in some cases.
Collapse
Affiliation(s)
- Aude Kienzler
- European Commission, Joint Research Centre, Via E. Fermi, 2749, 21027 Ispra, VA, Italy.
| | - Stephanie Bopp
- European Commission, Joint Research Centre, Via E. Fermi, 2749, 21027 Ispra, VA, Italy
| | - Marlies Halder
- European Commission, Joint Research Centre, Via E. Fermi, 2749, 21027 Ispra, VA, Italy
| | - Michelle Embry
- Health and Environmental Science Institute, 740 15th Street NW, Suite 600, Washington, DC 20005, USA
| | - Andrew Worth
- European Commission, Joint Research Centre, Via E. Fermi, 2749, 21027 Ispra, VA, Italy
| |
Collapse
|
39
|
Aurisano N, Albizzati PF, Hauschild M, Fantke P. Extrapolation Factors for Characterizing Freshwater Ecotoxicity Effects. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2019; 38:2568-2582. [PMID: 31393623 DOI: 10.1002/etc.4564] [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: 04/30/2019] [Revised: 05/15/2019] [Accepted: 08/02/2019] [Indexed: 05/21/2023]
Abstract
Various environmental and chemical assessment frameworks including ecological risk assessment and life cycle impact assessment aim at evaluating long-term ecotoxicity effects. Chronic test data are reported under the European Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) regulation for various chemicals. However, chronic data are missing for a large fraction of marketed chemicals, for which acute test results are often available. Utilizing acute data requires robust extrapolation factors across effect endpoints, exposure durations, and species groups. We propose a decision tree based on strict criteria for curating and selecting high-quality aquatic ecotoxicity information available in REACH for organic chemicals, to derive a consistent set of generic and species group-specific extrapolation factors. Where ecotoxicity effect data are not available at all, we alternatively provide extrapolations from octanol-water partitioning coefficients as suitable predictor for chemicals with nonpolar narcosis as mode of action. Extrapolation factors range from 0.2 to 7 and are higher when simultaneously extrapolating across effect endpoints and exposure durations. Our results are consistent with previously reported values, while considering more endpoints, providing species group-specific factors, and characterizing uncertainty. Our proposed decision tree can be adapted to curate information from additional data sources as well as data for other environments, such as sediment ecotoxicity. Our approach and robust extrapolation factors help to increase the substance coverage for characterizing ecotoxicity effects across chemical and environmental assessment frameworks. Environ Toxicol Chem 2019;38:2568-2582. © 2019 SETAC.
Collapse
Affiliation(s)
- Nicolò Aurisano
- Quantitative Sustainability Assessment, Department of Technology, Management and Economics, Technical University of Denmark, Kgs, Lyngby, Denmark
| | | | - Michael Hauschild
- Quantitative Sustainability Assessment, Department of Technology, Management and Economics, Technical University of Denmark, Kgs, Lyngby, Denmark
| | - Peter Fantke
- Quantitative Sustainability Assessment, Department of Technology, Management and Economics, Technical University of Denmark, Kgs, Lyngby, Denmark
| |
Collapse
|
40
|
Kienzler A, Connors KA, Bonnell M, Barron MG, Beasley A, Inglis CG, Norberg‐King TJ, Martin T, Sanderson H, Vallotton N, Wilson P, Embry MR. Mode of Action Classifications in the EnviroTox Database: Development and Implementation of a Consensus MOA Classification. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2019; 38:2294-2304. [PMID: 31269286 PMCID: PMC6851772 DOI: 10.1002/etc.4531] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 04/29/2019] [Accepted: 06/25/2019] [Indexed: 05/24/2023]
Abstract
Multiple mode of action (MOA) frameworks have been developed in aquatic ecotoxicology, mainly based on fish toxicity. These frameworks provide information on a key determinant of chemical toxicity, but the MOA categories and level of specificity remain unique to each of the classification schemes. The present study aimed to develop a consensus MOA assignment within EnviroTox, a curated in vivo aquatic toxicity database, based on the following MOA classification schemes: Verhaar (modified) framework, Assessment Tool for Evaluating Risk, Toxicity Estimation Software Tool, and OASIS. The MOA classifications from each scheme were first collapsed into one of 3 categories: non-specifically acting (i.e., narcosis), specifically acting, or nonclassifiable. Consensus rules were developed based on the degree of concordance among the 4 individual MOA classifications to attribute a consensus MOA to each chemical. A confidence rank was also assigned to the consensus MOA classification based on the degree of consensus. Overall, 40% of the chemicals were classified as narcotics, 17% as specifically acting, and 43% as unclassified. Sixty percent of chemicals had a medium to high consensus MOA assignment. When compared to empirical acute toxicity data, the general trend of specifically acting chemicals being more toxic is clearly observed for both fish and invertebrates but not for algae. EnviroTox is the first approach to establishing a high-level consensus across 4 computationally and structurally distinct MOA classification schemes. This consensus MOA classification provides both a transparent understanding of the variation between MOA classification schemes and an added certainty of the MOA assignment. In terms of regulatory relevance, a reliable understanding of MOA can provide information that can be useful for the prioritization (ranking) and risk assessment of chemicals. Environ Toxicol Chem 2019;38:2294-2304. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.
Collapse
Affiliation(s)
- Aude Kienzler
- European Commission, Joint Research Centre, IspraItaly
| | | | - Mark Bonnell
- Environment and Climate Change Canada, GatineauQuebecCanada
| | - Mace G. Barron
- Gulf Ecology DivisionUS Environmental Protection Agency, Gulf BreezeFlorida
| | | | | | | | - Todd Martin
- US Environmental Protection Agency, CinncinatiOhio
| | | | | | | | | |
Collapse
|
41
|
Van den Berg SJP, Baveco H, Butler E, De Laender F, Focks A, Franco A, Rendal C, Van den Brink PJ. Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:6025-6034. [PMID: 31008596 PMCID: PMC6535724 DOI: 10.1021/acs.est.9b00893] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 04/15/2019] [Accepted: 04/22/2019] [Indexed: 05/31/2023]
Abstract
In this study, a trait-based macroinvertebrate sensitivity modeling tool is presented that provides two main outcomes: (1) it constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for each one of a diverse set of predefined Modes of Action (MOAs) and (2) it reveals data gaps and restrictions, helping with the direction of future research. Besides revealing taxonomic patterns of species sensitivity, we find that there was not one genus, family, or class which was most sensitive to all MOAs and that common test taxa were often not the most sensitive at all. Traits like life cycle duration and feeding mode were identified as important in explaining species sensitivity. For 71% of the species, no or incomplete trait data were available, making the lack of trait data the main obstacle in model construction. Research focus should therefore be on completing trait databases and enhancing them with finer morphological traits, focusing on the toxicodynamics of the chemical (e.g., target site distribution). Further improved sensitivity models can help with the creation of ecological scenarios by predicting the sensitivity of untested species. Through this development, our approach can help reduce animal testing and contribute toward a new predictive ecotoxicology framework.
Collapse
Affiliation(s)
- Sanne J. P. Van den Berg
- Aquatic
Ecology and Water Quality Management Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands
- Department
of Biology, University of Namur, Rue de Bruxelles 61, 5000 Namur, Belgium
| | - Hans Baveco
- Wageningen
Environmental Research, P.O. Box 47, 6700 AA Wageningen, The Netherlands
| | - Emma Butler
- Safety
and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook MK441LQ, United Kingdom
| | - Frederik De Laender
- Department
of Biology, University of Namur, Rue de Bruxelles 61, 5000 Namur, Belgium
| | - Andreas Focks
- Wageningen
Environmental Research, P.O. Box 47, 6700 AA Wageningen, The Netherlands
| | - Antonio Franco
- Safety
and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook MK441LQ, United Kingdom
| | - Cecilie Rendal
- Safety
and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook MK441LQ, United Kingdom
| | - Paul J. Van den Brink
- Aquatic
Ecology and Water Quality Management Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands
- Wageningen
Environmental Research, P.O. Box 47, 6700 AA Wageningen, The Netherlands
| |
Collapse
|
42
|
Connors KA, Beasley A, Barron MG, Belanger SE, Bonnell M, Brill JL, de Zwart D, Kienzler A, Krailler J, Otter R, Phillips JL, Embry MR. Creation of a Curated Aquatic Toxicology Database: EnviroTox. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2019; 38:1062-1073. [PMID: 30714190 PMCID: PMC6850623 DOI: 10.1002/etc.4382] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 01/29/2019] [Accepted: 01/30/2019] [Indexed: 05/20/2023]
Abstract
Flexible, rapid, and predictive approaches that do not require the use of large numbers of vertebrate test animals are needed because the chemical universe remains largely untested for potential hazards. Development of robust new approach methodologies and nontesting approaches requires the use of existing information via curated, integrated data sets. The ecological threshold of toxicological concern (ecoTTC) represents one such new approach methodology that can predict a conservative de minimis toxicity value for chemicals with little or no information available. For the creation of an ecoTTC tool, a large, diverse environmental data set was developed from multiple sources, with harmonization, characterization, and information quality assessment steps to ensure that the information could be effectively organized and mined. The resulting EnviroTox database contains 91 217 aquatic toxicity records representing 1563 species and 4016 unique Chemical Abstracts Service numbers and is a robust, curated database containing high-quality aquatic toxicity studies that are traceable to the original information source. Chemical-specific information is also linked to each record and includes physico-chemical information, chemical descriptors, and mode of action classifications. Toxicity data are associated with the physico-chemical data, mode of action classifications, and curated taxonomic information for the organisms tested. The EnviroTox platform also includes 3 analysis tools: a predicted-no-effect concentration calculator, an ecoTTC distribution tool, and a chemical toxicity distribution tool. Although the EnviroTox database and tools were originally developed to support ecoTTC analysis and development, they have broader applicability to the field of ecological risk assessment. Environ Toxicol Chem 2019;9999:1-12. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.
Collapse
Affiliation(s)
| | | | | | | | - Mark Bonnell
- Environment and Climate Change CanadaGatineauOntarioCanada
| | | | | | | | | | - Ryan Otter
- Middle Tennessee State UniversityMurfreesboroTennesseeUSA
| | | | | |
Collapse
|
43
|
Rawlings JM, Belanger SE, Connors KA, Carr GJ. Fish embryo tests and acute fish toxicity tests are interchangeable in the application of the threshold approach. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2019; 38:671-681. [PMID: 30615221 DOI: 10.1002/etc.4351] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2018] [Revised: 11/20/2018] [Accepted: 12/21/2018] [Indexed: 05/13/2023]
Abstract
A database was compiled for algal Organisation for Economic Co-operation and Development (OECD) test guideline 201, for Daphnia magna OECD test guideline 202, for the acute fish toxicity (AFT) OECD test guideline 203, and for the fish embryo toxicity (FET) OECD test guideline 236 to assess the suitability and applicability of the FET test in a threshold approach context. In the threshold approach, algal and Daphnia toxicity are assessed first, after which a limit test is conducted at the lower of the 2 toxicity values using fish. If potential fish toxicity is indicated, a full median lethal concentration assay is performed. This tiered testing strategy can significantly reduce the number of fish used in toxicity testing because algae or Daphnia are typically more sensitive than fish. A total of 165 compounds had AFT and FET data available, and of these, 82 had algal and Daphnia acute toxicity data available. Algae and Daphnia were more sensitive 75 to 80% of the time. Fish or FET tests were most sensitive 20 and 16% of the time, respectively, when considered as the sole fish toxicity indicator and 27% of the time when both were considered simultaneously. When fish were the most sensitive trophic level, different compounds were identified as the most toxic in FET and to AFT tests; however, the differences were not so large that they resulted in substantially different outcomes when potencies were binned using the United Nations categories of aquatic toxicity under the Globally Harmonized System for classification and labeling. It is recommended that the FET test could be used to directly replace the AFT test in the threshold approach or could be used as the definitive test if an AFT limit test indicated toxicity potential for a chemical. Environ Toxicol Chem 2019;38:671-681. © 2019 SETAC.
Collapse
Affiliation(s)
- Jane M Rawlings
- Environmental Stewardship, The Procter & Gamble Company, Mason, Ohio, USA
| | - Scott E Belanger
- Environmental Stewardship, The Procter & Gamble Company, Mason, Ohio, USA
| | - Kristin A Connors
- Environmental Stewardship, The Procter & Gamble Company, Mason, Ohio, USA
| | - Gregory J Carr
- Quantitative Sciences, The Procter & Gamble Company, Mason, Ohio, USA
| |
Collapse
|
44
|
Belanger SE, Rawlings JM, Stackhouse R. Advances in understanding the response of fish to linear alcohols in the environment. CHEMOSPHERE 2018; 206:539-548. [PMID: 29778079 DOI: 10.1016/j.chemosphere.2018.04.152] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 04/17/2018] [Accepted: 04/24/2018] [Indexed: 06/08/2023]
Abstract
Short to long chain alcohols have a range of ecotoxicity to aquatic life driven by hydrophobic interactions with biological membranes. Carbon chain length and octanol:water partitioning coefficients are surrogates for hydrophobicity and strongly relate to aquatic toxicity. In these investigations, the toxicity of ethanol to 1-n-dodecanol to juvenile fish in standard acute toxicity tests is reviewed. Toxicity tests employing fish embryos (zebrafish Danio rerio and fathead minnow Pimephales promelas) in the Fish Embryo Test (OECD 236) format were conducted from C2 to C10 to compare against standard juvenile fish toxicity. Quantitative structure activity relationships for FET and fish individually and combined demonstrate that embryos are not different in sensitivity to juvenile fish. A combined QSAR was developed of the form Log 96 h LC50 (mM/L) = -0.925*log Kow + 2.060 (R2 10 = 0.954). Alcohols of 11-12 carbons show a deflection in the QSAR as toxicity approaches the solubility limit. Alcohols with longer chain lengths may only be tested at lower exposures relevant for chronic toxicity. Decanol was evaluated in a 33-d fish early life stage test (OECD 210) and survival was the most sensitive endpoint (EC10 = 0.43 mg/L, 0.0027 mM/L). This study suggests a reasonable acute to chronic ratio of 6.5 in line with historical literature for non-polar narcotic compounds. Fish are not uniquely more sensitive than Daphnia magna which suggests estimations of environmental hazard can be confidently made with either taxon. The overall environmental risk assessments for the longer chain alcohols included in this research remain largely unchanged primarily due to previous research demonstrating a very minimal environmental exposure even for highly toxic members of the category.
Collapse
Affiliation(s)
- Scott E Belanger
- Global Product Stewardship, The Procter & Gamble Company, Mason Business Center, Mason, OH 45040, USA.
| | - Jane M Rawlings
- Global Product Stewardship, The Procter & Gamble Company, Mason Business Center, Mason, OH 45040, USA
| | - Ricky Stackhouse
- Toxicology & Risk Assessment, Performance Chemicals, Sasol (USA) Corporation, 2201 Old Spanish Trail, Westlake, LA 70669, USA
| |
Collapse
|
45
|
Baas J, Augustine S, Marques GM, Dorne JL. Dynamic energy budget models in ecological risk assessment: From principles to applications. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 628-629:249-260. [PMID: 29438934 DOI: 10.1016/j.scitotenv.2018.02.058] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Revised: 02/05/2018] [Accepted: 02/05/2018] [Indexed: 06/08/2023]
Abstract
In ecological risk assessment of chemicals, hazard identification and hazard characterisation are most often based on ecotoxicological tests and expressed as summary statistics such as No Observed Effect Concentrations or Lethal Concentration values and No Effect Concentrations. Considerable research is currently ongoing to further improve methodologies to take into account toxico kinetic aspects in toxicological assessments, extrapolations of toxic effects observed on individuals to population effects and combined effects of multiple chemicals effects. In this context, the principles of the Dynamic Energy Budget (DEB), namely the conserved allocation of energy to different life-supporting processes in a wide variety of different species, have been applied successfully to the development of a number of DEB models. DEB models allow the incorporation of effects on growth, reproduction and survival within one consistent framework. This review aims to discuss the principles of the DEB theory together with available DEB models, databases available and applications in ecological risk assessment of chemicals for a wide range of species and taxa. Future perspectives are also discussed with particular emphasis on ongoing research efforts to develop DEB models as open source tools to further support the research and regulatory community to integrate quantitative biology in ecotoxicological risk assessment.
Collapse
Affiliation(s)
- Jan Baas
- Centre for Ecology and Hydrology, MacLean Building Benson Lane, Wallingford, Oxfordshire, UK.
| | - Starrlight Augustine
- Akvaplan-niva, Fram - High North Research Centre for Climate and the Environment, 9296 Tromsø, Norway
| | | | - Jean-Lou Dorne
- European Food Safety Authority (EFSA), Scientific Committee and emerging Risks Unit, Parma, Italy
| |
Collapse
|
46
|
Fay KA, Villeneuve DL, Swintek J, Edwards SW, Nelms MD, Blackwell BR, Ankley GT. Differentiating Pathway-Specific From Nonspecific Effects in High-Throughput Toxicity Data: A Foundation for Prioritizing Adverse Outcome Pathway Development. Toxicol Sci 2018; 163:500-515. [PMID: 29529260 PMCID: PMC6820004 DOI: 10.1093/toxsci/kfy049] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The U.S. Environmental Protection Agency's ToxCast program has screened thousands of chemicals for biological activity, primarily using high-throughput in vitro bioassays. Adverse outcome pathways (AOPs) offer a means to link pathway-specific biological activities with potential apical effects relevant to risk assessors. Thus, efforts are underway to develop AOPs relevant to pathway-specific perturbations detected in ToxCast assays. Previous work identified a "cytotoxic burst" (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared with the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). The prioritization approaches did not appear to be influenced by inter-assay differences in chemical bioavailability. Furthermore, the outcomes were robust based on a variety of different parameters used to define the CTB.
Collapse
Affiliation(s)
- Kellie A. Fay
- University of Minnesota-Duluth, Biology Department; 1035 Kirby Drive, Swenson Science Building 207, Duluth, MN 55812
- CSRA Inc, Science and Engineering, 6201 Congdon Blvd, Duluth, MN 55804
| | - Daniel L. Villeneuve
- U.S. EPA National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, 6201 Congdon Blvd, Duluth, MN 55804
| | - Joe Swintek
- Badger Technical Services, 6201 Congdon Blvd, Duluth, MN 55804
| | - Stephen W. Edwards
- U.S. EPA National Health and Environmental Effects Research Laboratory, Integrated Systems Toxicology Division, 109 TW Alexander Dr. (MD B105-03), RTP, NC 27711
- RTI International, Research Computing Division, 3040 E Cornwallis Rd, Durham, NC 27709
| | - Mark D. Nelms
- U.S. EPA National Health and Environmental Effects Research Laboratory, Integrated Systems Toxicology Division, 109 TW Alexander Dr. (MD B105-03), RTP, NC 27711
| | - Brett R. Blackwell
- U.S. EPA National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, 6201 Congdon Blvd, Duluth, MN 55804
| | - Gerald T. Ankley
- U.S. EPA National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, 6201 Congdon Blvd, Duluth, MN 55804
| |
Collapse
|
47
|
Ashauer R, Jager T. Physiological modes of action across species and toxicants: the key to predictive ecotoxicology. ENVIRONMENTAL SCIENCE. PROCESSES & IMPACTS 2018; 20:48-57. [PMID: 29090718 DOI: 10.1039/c7em00328e] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
As ecotoxicologists we strive for a better understanding of how chemicals affect our environment. Humanity needs tools to identify those combinations of man-made chemicals and organisms most likely to cause problems. In other words: which of the millions of species are at risk from pollution? And which of the tens of thousands of chemicals contribute most to the risk? We identified our poor knowledge on physiological modes of action (how a chemical affects the energy allocation in an organism), and how they vary across species and toxicants, as a major knowledge gap. We also find that the key to predictive ecotoxicology is the systematic, rigorous characterization of physiological modes of action because that will enable more powerful in vitro to in vivo toxicity extrapolation and in silico ecotoxicology. In the near future, we expect a step change in our ability to study physiological modes of action by improved, and partially automated, experimental methods. Once we have populated the matrix of species and toxicants with sufficient physiological mode of action data we can look for patterns, and from those patterns infer general rules, theory and models.
Collapse
Affiliation(s)
- Roman Ashauer
- Environment Department, University of York, Heslington, York YO10 5NG, UK.
| | | |
Collapse
|
48
|
McCarty LS, Borgert CJ. Comment on "Mode of Action (MOA) Assignment Classifications for Ecotoxicology: An Evaluation of Approaches". ENVIRONMENTAL SCIENCE & TECHNOLOGY 2017; 51:13509-13510. [PMID: 29120618 DOI: 10.1021/acs.est.7b04967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Affiliation(s)
- Lynn S McCarty
- L.S. McCarty Scientific Research & Consulting , Newmarket, ON L3X 3E2, Canada
| | - Christopher J Borgert
- Applied Pharmacology and Toxicology, Inc. , Gainesville, Florida 32605, United States
| |
Collapse
|
49
|
Kienzler A, Barron MG, Belanger SE, Beasley A, Embry MR. Response to "Comment on 'Mode of Action (MOA) Assignment Classifications for Ecotoxicology: An Evaluation of Approaches'". ENVIRONMENTAL SCIENCE & TECHNOLOGY 2017; 51:13511-13512. [PMID: 29120622 DOI: 10.1021/acs.est.7b05413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Affiliation(s)
- A Kienzler
- European Commission, Joint Research Centre, Directorate F-Health, Consumers and Reference Materials; F.3 Chemicals Safety & Alternative Methods, TP 126, Via E. Fermi, 2749, I-21027 Ispra, Italy
| | - M G Barron
- United States Environmental Protection Agency , Gulf Ecology Division, 1 Sabine Island Drive, Gulf Breeze, Florida 32561, United States
| | - S E Belanger
- The Procter & Gamble Company , Global Product Stewardship, Mason Business Center, 8700 Mason Montgomery Road, Cincinnati, Ohio 45050, United States
| | - A Beasley
- The Dow Chemical Company , 1803 Building, Midland, Michigan 48640, United States
| | - M R Embry
- International Life Sciences Institute Health and Environmental Sciences Institute , 1156 15th Street, NW, Suite 200, Washington, D.C. 20005, United States
| |
Collapse
|