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Tian M, Ding X, Pang Y, Xu D, Sun Y, Xia P. Transcriptomic dose-response by UVC and heavy ion radiation reveal pathways to immune impairment. Toxicol In Vitro 2025; 108:106086. [PMID: 40419229 DOI: 10.1016/j.tiv.2025.106086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2024] [Revised: 04/27/2025] [Accepted: 05/22/2025] [Indexed: 05/28/2025]
Abstract
Irradiation-induced immune impairment has been linked to human immune diseases, such as myelodysplastic syndromes (MDS) and leukemia. Global molecular responses to genome instability in immune cells can be identified by using transcriptomics. However, it is hard to link the molecular mechanism to the disease outcomes in the previous mechanistic studies. Here, transcriptomic dose-responses in human CD4+ T lymphocytes exposed to ultraviolet and heavy ion radiation were revealed by identification of the gene expression patterns of differential expression genes (DEGs) and calculating the point of departure (POD) of each DEG and molecular pathway, which provided an opportunity for quantitively illustrating the biological process of irradiation-induced immune impairments. Two potential adverse outcome pathways (AOPs) to irradiation-related leukemia were identified by mapping the molecular pathways into the biological event cascades, which provided phenotypic anchoring for the toxicological mechanisms. In addition, this study also revealed that NOP14/ NOP14-AS1 could be potential biomarkers of irradiation-induced immune impairment. Our works strengthen the use of AOP network in the next-generation risk assessment of irradiation-related diseases.
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Affiliation(s)
- Mingming Tian
- Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning 116026, Linghai Road 1, PR China; State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China
| | - Xiaolin Ding
- Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning 116026, Linghai Road 1, PR China
| | - Yue Pang
- Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning 116026, Linghai Road 1, PR China
| | - Dan Xu
- Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning 116026, Linghai Road 1, PR China.
| | - Yeqing Sun
- Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian, Liaoning 116026, Linghai Road 1, PR China
| | - Pu Xia
- State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, PR China; Environmental Genomics Group, School of Biosciences, the University of Birmingham, Birmingham B15 2TT, UK
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2
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Fan T, Han T, Gu A, Jin J, Cui Q, Guo J, Zhang X, Yu H, Shi W. Novel Approach to Screen Endocrine-Disrupting Chemicals via Endocrine-Enhanced Reduced Human Transcriptome. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2025; 59:4845-4856. [PMID: 40042996 DOI: 10.1021/acs.est.4c13159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2025]
Abstract
Endocrine-disrupting chemicals (EDCs) can interfere with multiple pathways and trigger different modes of action. Thus, the traditional EDC in vitro screening processes often require a battery of bioassays to cover multiple target pathways. Here we developed an endocrine-enhanced reduced human transcriptome (ERHT) focused on hormone receptor signaling induced by the EDCs regulating specific genes. ERHT was developed based on 1200 prioritized genes covering 110 endocrine-related biological pathways across eight potential adverse outcomes. The ability of this approach to identify EDCs was derived from machine learning of 1068 dose-dependent transcriptome profiles and enhanced by quantifying chemical-induced critical pathway responses, and thus, it demonstrated excellent classification performance (AUC = 0.84 ± 0.03) in internal cross-validation. We ultimately applied this approach to known EDCs and inactive substances to validate the reliability of this approach. Through external validation on 210 chemicals, the extrapolation accuracy exceeded 80%, demonstrating the outstanding practical performance of this approach. Meanwhile, the pathway responses induced by the same chemical were consistent with the experimental results reported by multiple sequencing platforms, highlighting the robustness of this approach. The above results demonstrate that this approach can provide novel insights for EDCs' high-throughput screening and comprehensive toxic mechanisms through biological pathways.
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Affiliation(s)
- Tianle Fan
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Tianhao Han
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Aoran Gu
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Jinsha Jin
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Qian Cui
- Nanjing Yangtze River Delta Green Development Institute, Nanjing 210093, China
| | - Jing Guo
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Hongxia Yu
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Wei Shi
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
- Jiangsu Province Ecology and Environment Protection Key Laboratory of Chemical Safety and Health Risk, Nanjing 210023, China
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3
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Lislien M, Kuchovska E, Kapr J, Duale N, Andersen JM, Dirven H, Myhre O, Fritsche E, Koch K, Wojewodzic MW. Transcriptomic characterization of 2D and 3D human induced pluripotent stem cell-based in vitro models as New Approach Methodologies for developmental neurotoxicity testing. Toxicology 2025; 510:154000. [PMID: 39551125 DOI: 10.1016/j.tox.2024.154000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2024] [Revised: 10/30/2024] [Accepted: 11/13/2024] [Indexed: 11/19/2024]
Abstract
The safety and developmental neurotoxicity (DNT) potential of chemicals remain critically understudied due to limitations of current in vivo testing guidelines, which are low throughput, resource-intensive, and hindered by species differences that limit their relevance to human health. To address these issues, robust New Approach Methodologies (NAMs) using deeply characterized cell models are essential. This study presents the comprehensive transcriptomic characterization of two advanced human-induced pluripotent stem cell (hiPSC)-derived models: a 2D adherent and a 3D neurosphere model of human neural progenitor cells (hiNPCs) differentiated up to 21 days. Using high-throughput RNA sequencing, we compared gene expression profiles of 2D and 3D models at three developmental stages (3, 14, and 21 days of differentiation). Both models exhibit maturation towards post-mitotic neurons, with the 3D model maturing faster and showing a higher prevalence of GABAergic neurons, while the 2D model is enriched with glutamatergic neurons. Both models demonstrate broad applicability domains, including excitatory and inhibitory neurons, astrocytes, and key endocrine and especially the understudied cholinergic receptors. Comparison with human fetal brain samples confirms their physiological relevance. This study provides novel in-depth applicability insights into the temporal and dimensional aspects of hiPSC-derived neural models for DNT testing. The complementary use of these two models is highlighted: the 2D model excels in synaptogenesis assessment, while the 3D model is particularly suited for neural network formation as observed as well in previous functional studies with these models. This research marks a significant advancement in developing human-relevant, high-throughput DNT assays for regulatory purposes.
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Affiliation(s)
- Malene Lislien
- Department of Chemical Toxicology, Norwegian Institute of Public Health, Oslo, Norway
| | - Eliska Kuchovska
- IUF-Leibniz-Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Julia Kapr
- IUF-Leibniz-Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Nur Duale
- Department of Chemical Toxicology, Norwegian Institute of Public Health, Oslo, Norway
| | - Jill Mari Andersen
- Department of Chemical Toxicology, Norwegian Institute of Public Health, Oslo, Norway
| | - Hubert Dirven
- Department of Chemical Toxicology, Norwegian Institute of Public Health, Oslo, Norway
| | - Oddvar Myhre
- Department of Chemical Toxicology, Norwegian Institute of Public Health, Oslo, Norway
| | - Ellen Fritsche
- IUF-Leibniz-Research Institute for Environmental Medicine, Düsseldorf, Germany; DNTOX GmbH, Düsseldorf, Germany; Swiss Centre for Applied Human Toxicology, Basel, Switzerland
| | - Katharina Koch
- IUF-Leibniz-Research Institute for Environmental Medicine, Düsseldorf, Germany; DNTOX GmbH, Düsseldorf, Germany
| | - Marcin W Wojewodzic
- Department of Chemical Toxicology, Norwegian Institute of Public Health, Oslo, Norway; Department of Research, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway.
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4
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Zhou Z, Pennings JLA, Sahlin U. Causal, predictive or observational? Different understandings of key event relationships for adverse outcome pathways and their implications on practice. ENVIRONMENTAL TOXICOLOGY AND PHARMACOLOGY 2025; 113:104597. [PMID: 39622398 DOI: 10.1016/j.etap.2024.104597] [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: 08/28/2024] [Revised: 11/22/2024] [Accepted: 11/26/2024] [Indexed: 12/06/2024]
Abstract
The Adverse Outcome Pathways (AOPs) framework is pivotal in toxicology, but the, terminology describing Key Event Relationships (KERs) varies within AOP guidelines.This study examined the usage of causal, observational and predictive terms in AOP, documentation and their adaptation in AOP development. A literature search and text, analysis of key AOP guidance documents revealed nuanced usage of these terms, with KERs often described as both causal and predictive. The adaptation of, terminology varies across AOP development stages. Evaluation of KER causality often, relies targeted blocking experiments and weight-of-evidence assessments in the, putative and qualitative stages. Our findings highlight a potential mismatch between,terminology in guidelines and methodologies in practice, particularly in inferring,causality from predictive models. We argue for careful consideration of terms like, causal and essential to facilitate interdisciplinary communication. Furthermore, integrating known causality into quantitative AOP models remains a challenge.
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Affiliation(s)
- Zheng Zhou
- Center for Environmental and Climate Science, Lund University, Sweden.
| | | | - Ullrika Sahlin
- Center for Environmental and Climate Science, Lund University, Sweden
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5
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Lai W, Song Y, Tollefsen KE, Hvidsten TR. SOLA: dissecting dose-response patterns in multi-omics data using a semi-supervised workflow. Front Genet 2024; 15:1508521. [PMID: 39687738 PMCID: PMC11647027 DOI: 10.3389/fgene.2024.1508521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2024] [Accepted: 11/12/2024] [Indexed: 12/18/2024] Open
Abstract
An increasing number of ecotoxicological studies have used omics-data to understand the dose-response patterns of environmental stressors. However, very few have investigated complex non-monotonic dose-response patterns with multi-omics data. In the present study, we developed a novel semi-supervised network analysis workflow as an alternative to benchmark dose (BMD) modelling. We utilised a previously published multi-omics dataset generated from Daphnia magna after chronic gamma radiation exposure to obtain novel knowledge on the dose-dependent effects of radiation. Our approach combines 1) unsupervised co-expression network analysis to group genes with similar dose responses into modules; 2) supervised classification of these modules by relevant response patterns; 3) reconstruction of regulatory networks based on transcription factor binding motifs to reveal the mechanistic underpinning of the modules; 4) differential co-expression network analysis to compare the discovered modules across two datasets with different exposure periods; and 5) pathway enrichment analysis to integrate transcriptomics and metabolomics data. Our method unveiled both known and novel effects of gamma radiation, provide insight into shifts in responses from low to high dose rates, and can be used as an alternative approach for multi-omics dose-response analysis in future. The workflow SOLA (Semi-supervised Omics Landscape Analysis) is available at https://gitlab.com/wanxin.lai/SOLA.git.
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Affiliation(s)
- Wanxin Lai
- Bioinformatics and Applied Statistics (BIAS), Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences (NMBU), Akershus, Norway
| | - You Song
- Norwegian Institute for Water Research (NIVA), Oslo, Norway
- Norwegian University of Life Sciences (NMBU), Akershus, Norway
| | - Knut Erik Tollefsen
- Norwegian Institute for Water Research (NIVA), Oslo, Norway
- Norwegian University of Life Sciences (NMBU), Akershus, Norway
- Centre for Environmental Radioactivity (CERAD), Faculty of Environmental Sciences and Natural Resource Management (MINA), Norwegian University of Life Sciences (NMBU), Akershus, Norway
| | - Torgeir R. Hvidsten
- Bioinformatics and Applied Statistics (BIAS), Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences (NMBU), Akershus, Norway
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Shi C, Cheng L, Yu Y, Chen S, Dai Y, Yang J, Zhang H, Chen J, Geng N. Multi-omics integration analysis: Tools and applications in environmental toxicology. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 360:124675. [PMID: 39103035 DOI: 10.1016/j.envpol.2024.124675] [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: 05/16/2024] [Revised: 07/08/2024] [Accepted: 08/03/2024] [Indexed: 08/07/2024]
Abstract
Nowadays, traditional single-omics study is not enough to explain the causality between molecular alterations and toxicity endpoints for environmental pollutants. With the development of high-throughput sequencing technology and high-resolution mass spectrometry technology, the integrative analysis of multi-omics has become an efficient strategy to understand holistic biological mechanisms and to uncover the regulation network in specific biological processes. This review summarized sample preparation methods, integration analysis tools and the application of multi-omics integration analyses in environmental toxicology field. Currently, omics methods have been widely applied being as the sensitivity of early biological response, especially for low-dose and long-term exposure to environmental pollutants. Integrative omics can reveal the overall changes of genes, proteins, and/or metabolites in the cells, tissues or organisms, which provide new insights into revealing the overall toxicity effects, screening the toxic targets, and exploring the underlying molecular mechanism of pollutants.
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Affiliation(s)
- Chengcheng Shi
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, China
| | - Lin Cheng
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Ying Yu
- College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, China
| | - Shuangshuang Chen
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, China
| | - Yubing Dai
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Jiajia Yang
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; College of Materials Science and Engineering, Hebei University of Engineering, Handan, 056038, China
| | - Haijun Zhang
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Jiping Chen
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Ningbo Geng
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
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7
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Silva AC, Loizou GD, McNally K, Osborne O, Potter C, Gott D, Colbourne JK, Viant MR. A novel method to derive a human safety limit for PFOA by gene expression profiling and modelling. FRONTIERS IN TOXICOLOGY 2024; 6:1368320. [PMID: 38577564 PMCID: PMC10991825 DOI: 10.3389/ftox.2024.1368320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 03/01/2024] [Indexed: 04/06/2024] Open
Abstract
Perfluorooctanoic acid (PFOA) is a persistent environmental contaminant that can accumulate in the human body due to its long half-life. This substance has been associated with liver, pancreatic, testicular and breast cancers, liver steatosis and endocrine disruption. PFOA is a member of a large group of substances also known as "forever chemicals" and the vast majority of substances of this group lack toxicological data that would enable their effective risk assessment in terms of human health hazards. This study aimed to derive a health-based guidance value for PFOA intake (ng/kg BW/day) from in vitro transcriptomics data. To this end, we developed an in silico workflow comprising five components: (i) sourcing in vitro hepatic transcriptomics concentration-response data; (ii) deriving molecular points of departure using BMDExpress3 and performing pathway analysis using gene set enrichment analysis (GSEA) to identify the most sensitive molecular pathways to PFOA exposure; (iii) estimating freely-dissolved PFOA concentrations in vitro using a mass balance model; (iv) estimating in vivo doses by reverse dosimetry using a PBK model for PFOA as part of a quantitative in vitro to in vivo extrapolation (QIVIVE) algorithm; and (v) calculating a tolerable daily intake (TDI) for PFOA. Fourteen percent of interrogated genes exhibited in vitro concentration-response relationships. GSEA pathway enrichment analysis revealed that "fatty acid metabolism" was the most sensitive pathway to PFOA exposure. In vitro free PFOA concentrations were calculated to be 2.9% of the nominal applied concentrations, and these free concentrations were input into the QIVIVE workflow. Exposure doses for a virtual population of 3,000 individuals were estimated, from which a TDI of 0.15 ng/kg BW/day for PFOA was calculated using the benchmark dose modelling software, PROAST. This TDI is comparable to previously published values of 1.16, 0.69, and 0.86 ng/kg BW/day by the European Food Safety Authority. In conclusion, this study demonstrates the combined utility of an "omics"-derived molecular point of departure and in silico QIVIVE workflow for setting health-based guidance values in anticipation of the acceptance of in vitro concentration-response molecular measurements in chemical risk assessment.
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Affiliation(s)
- Arthur de Carvalho e Silva
- School of Biosciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Environmental Research and Justice (CERJ), University of Birmingham, Birmingham, United Kingdom
| | | | | | - Olivia Osborne
- Science Evidence and Research Division, Food Standards Agency, London, United Kingdom
| | - Claire Potter
- Science Evidence and Research Division, Food Standards Agency, London, United Kingdom
| | - David Gott
- Science Evidence and Research Division, Food Standards Agency, London, United Kingdom
| | - John K. Colbourne
- School of Biosciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Environmental Research and Justice (CERJ), University of Birmingham, Birmingham, United Kingdom
| | - Mark R. Viant
- School of Biosciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Environmental Research and Justice (CERJ), University of Birmingham, Birmingham, United Kingdom
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Hansen BH, Tarrant AM, Lenz PH, Roncalli V, Almeda R, Broch OJ, Altin D, Tollefsen KE. Effects of petrogenic pollutants on North Atlantic and Arctic Calanus copepods: From molecular mechanisms to population impacts. AQUATIC TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2024; 267:106825. [PMID: 38176169 DOI: 10.1016/j.aquatox.2023.106825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 12/19/2023] [Accepted: 12/27/2023] [Indexed: 01/06/2024]
Abstract
Oil and gas industries in the Northern Atlantic Ocean have gradually moved closer to the Arctic areas, a process expected to be further facilitated by sea ice withdrawal caused by global warming. Copepods of the genus Calanus hold a key position in these cold-water food webs, providing an important energetic link between primary production and higher trophic levels. Due to their ecological importance, there is a concern about how accidental oil spills and produced water discharges may impact cold-water copepods. In this review, we summarize the current knowledge of the toxicity of petroleum on North Atlantic and Arctic Calanus copepods. We also review how recent development of high-quality transcriptomes from RNA-sequencing of copepods have identified genes regulating key biological processes, like molting, diapause and reproduction in Calanus copepods, to suggest linkages between exposure, molecular mechanisms and effects on higher levels of biological organization. We found that the available ecotoxicity threshold data for these copepods provide valuable information about their sensitivity to acute petrogenic exposures; however, there is still insufficient knowledge regarding underlying mechanisms of toxicity and the potential for long-term implications of relevance for copepod ecology and phenology. Copepod transcriptomics has expanded our understanding of how key biological processes are regulated in cold-water copepods. These advances can improve our understanding of how pollutants affect biological processes, and thus provide the basis for new knowledge frameworks spanning the effect continuum from molecular initiating events to adverse effects of regulatory relevance. Such efforts, guided by concepts such as adverse outcome pathways (AOPs), enable standardized and transparent characterization and evaluation of knowledge and identifies research gaps and priorities. This review suggests enhancing mechanistic understanding of exposure-effect relationships to better understand and link biomarker responses to adverse effects to improve risk assessments assessing ecological effects of pollutant mixtures, like crude oil, in Arctic areas.
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Affiliation(s)
| | - Ann M Tarrant
- Woods Hole Oceanographic Institution, Woods Hole, MA, 02543, United States
| | - Petra H Lenz
- University of Hawai'i at Mānoa, Honolulu, HI, 96822, United States
| | | | - Rodrigo Almeda
- EOMAR-ECOAQUA, University of Las Palmas de Gran Canaria (ULPGC), Canary Islands, Spain
| | - Ole Jacob Broch
- SINTEF Ocean, Fisheries and New Biomarine Industry, 7465 Trondheim, Norway
| | - Dag Altin
- BioTrix, 7020 Trondheim, Norway; Norwegian University of Science and Technology, Research Infrastructure SeaLab, 7010 Trondheim, Norway
| | - Knut Erik Tollefsen
- Norwegian Institute for Water Research (NIVA), 0579 Oslo, Norway; Norwegian University of Life Sciences (NMBU), N-1433 Ås, Norway
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Wan C, Ma H, Liu J, Liu F, Liu J, Dong G, Zeng X, Li D, Yu Z, Wang X, Li J, Zhang G. Quantitative relationships of FAM50B and PTCHD3 methylation with reduced intelligence quotients in school aged children exposed to lead: Evidence from epidemiological and in vitro studies. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:167976. [PMID: 37866607 DOI: 10.1016/j.scitotenv.2023.167976] [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: 06/26/2023] [Revised: 09/22/2023] [Accepted: 10/18/2023] [Indexed: 10/24/2023]
Abstract
At present, the application of DNA methylation (DNAm) biomarkers in environmental health risk assessment (EHRA) is more challenging due to the unclearly quantitative relationship between them. We aimed to explore the role of FAM50B and PTCHD3 at the level of signaling pathways, and establish the quantitative relationship between them and children's intelligence quotients (IQs). DNAm of target regions was measured in multiple cell models and was compared with the human population data. Then the dose-response relationships of lead exposure with neurotoxicity and DNAm were established by benchmark dose (BMD) model, followed by potential signaling pathway screening. Results showed that there was a quantitative linear relationship between children's IQs and FAM50B/PTCHD3 DNAm (DNAm between 51.40 % - 78.78 % and 31.41 % - 74.19 % for FAM50B and PTCHD3, respectively), and this relationship was more significant when children's IQs > 90. The receiver operating characteristic (ROC) and calibration curves showed that FAM50B/PTCHD3 DNAm had a satisfying accuracy and consistency in predicting children's IQs, which was confirmed by sensitivity analysis of gender and CpG site grouping data. In cell experiments, there was also a quantitative linear relationship between FAM50B DNAm and reactive oxygen species (ROS) production, which was mediated by PI3K-AKT signaling pathway. In addition, the lead BMD of ROS was close to that of FAM50B DNAm, suggesting that FAM50B DNAm was a suitable biomarker for the risk assessments of adverse outcomes induced by lead. Taken collectively, these results suggest that FAM50B/PTCHD3 can be applied to EHRA and the prevention/intervention of adverse effects of lead on children's IQs.
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Affiliation(s)
- Cong Wan
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China
| | - Huimin Ma
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China.
| | - Jiahong Liu
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fei Liu
- School of Business Administration, South China University of Technology, Guangzhou 510641, China
| | - Jing Liu
- Guangzhou First People's Hospital, Guangzhou 510180, China
| | - Guanghui Dong
- Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiaowen Zeng
- Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Daochuan Li
- Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Zhiqiang Yu
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China
| | - Jun Li
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China
| | - Gan Zhang
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China
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10
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Baudiffier D, Audouze K, Armant O, Frelon S, Charles S, Beaudouin R, Cosio C, Payrastre L, Siaussat D, Burgeot T, Mauffret A, Degli Esposti D, Mougin C, Delaunay D, Coumoul X. Editorial trend: adverse outcome pathway (AOP) and computational strategy - towards new perspectives in ecotoxicology. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:6587-6596. [PMID: 37966636 DOI: 10.1007/s11356-023-30647-w] [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: 03/15/2023] [Accepted: 10/18/2023] [Indexed: 11/16/2023]
Abstract
The adverse outcome pathway (AOP) has been conceptualized in 2010 as an analytical construct to describe a sequential chain of causal links between key events, from a molecular initiating event leading to an adverse outcome (AO), considering several levels of biological organization. An AOP aims to identify and organize available knowledge about toxic effects of chemicals and drugs, either in ecotoxicology or toxicology, and it can be helpful in both basic and applied research and serve as a decision-making tool in support of regulatory risk assessment. The AOP concept has evolved since its introduction, and recent research in toxicology, based on integrative systems biology and artificial intelligence, gave it a new dimension. This innovative in silico strategy can help to decipher mechanisms of action and AOP and offers new perspectives in AOP development. However, to date, this strategy has not yet been applied to ecotoxicology. In this context, the main objective of this short article is to discuss the relevance and feasibility of transferring this strategy to ecotoxicology. One of the challenges to be discussed is the level of organisation that is relevant to address for the AO (population/community). This strategy also offers many advantages that could be fruitful in ecotoxicology and overcome the lack of time, such as the rapid identification of data available at a time t, or the identification of "data gaps". Finally, this article proposes a step forward with suggested priority topics in ecotoxicology that could benefit from this strategy.
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Affiliation(s)
| | - Karine Audouze
- Université Paris Cité - INSERM T3S, 45 rue des Saints-Pères, 75006, Paris, France
| | - Olivier Armant
- Institut de Radioprotection et de Sûreté Nucléaire (IRSN), Pôle Santé-Environnement, Lez-Durance, F-13115, Saint-Paul, France
| | - Sandrine Frelon
- Institut de Radioprotection et de Sûreté Nucléaire (IRSN), Pôle Santé-Environnement, Lez-Durance, F-13115, Saint-Paul, France
| | - Sandrine Charles
- University of Lyon 1 - CNRS, UMR 5558, Laboratory of Biometry and Evolutionary Biology, F-69622, Villeurbanne, France
| | - Remy Beaudouin
- UMR-I 02 SEBIO - INERIS - Parc Technologique ALATA, 60550, Verneuil-en-Halatte, France
| | - Claudia Cosio
- Université de Reims Champagne-Ardenne - UMR-I 02 INERIS-URCA-ULHN SEBIO, Campus Moulin de la Housse, 51687, Reims, France
| | - Laurence Payrastre
- UMR 1331 TOXALIM - INRAE, 180 chemin de Tournefeuille, F-31027, Toulouse, France
| | - David Siaussat
- Institut d'écologie et sciences environnementales de Paris - Sorbonne Université - CNRS - INRAE - IRD - UPEC - Université de Paris Cité, 4 Place Jussieu Sorbonne Université - Campus Pierre et Marie Curie Barre 44-45, 3e étage, bureau 310, 75005, Paris, France
| | - Thierry Burgeot
- IFREMER - Unit of Research CCEM Contamination Chimique des Ecosystèmes marins, F-44000, Nantes, France
| | - Aourell Mauffret
- IFREMER - Unit of Research CCEM Contamination Chimique des Ecosystèmes marins, F-44000, Nantes, France
| | | | - Christian Mougin
- Université Paris-Saclay, INRAE, AgroParisTech, UMR EcoSys, 91120, Palaiseau, France
| | | | - Xavier Coumoul
- Université Paris Cité - INSERM T3S, 45 rue des Saints-Pères, 75006, Paris, France
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Cui T, Lan Y, Lu Y, Yu F, Lin S, Fu Y, Qiu J, Niu G. Isoorientin ameliorates H 2O 2-induced apoptosis and oxidative stress in chondrocytes by regulating MAPK and PI3K/Akt pathways. Aging (Albany NY) 2023; 15:204768. [PMID: 37277114 PMCID: PMC10292868 DOI: 10.18632/aging.204768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 04/18/2023] [Indexed: 06/07/2023]
Abstract
Osteoarthritis (OA) is a chronic and complicated degenerative disease for which there is currently no effective treatment. Isoorientin (ISO) is a natural plant extract that has antioxidant activity and could be used to treat OA. However, due to a lack of research, it has not been widely used. In this study, we investigated the protective effects and molecular mechanisms of ISO on H2O2-induced chondrocytes, a widely used cell model for OA. Based on RNA-seq and bioinformatics, we discovered that ISO significantly increased the activity of chondrocytes induced by H2O2, which was associated with apoptosis and oxidative stress. Furthermore, the combination of ISO and H2O2 significantly reduced apoptosis and restored mitochondrial membrane potential (MMP), which may be achieved by inhibiting apoptosis and mitogen-activated protein kinase (MAPK) signaling pathways. Moreover, ISO increased superoxide dismutase (SOD), heme oxygenase 1 (HO-1) and quinone oxidoreductase 1 (NQO-1) and reduced malondialdehyde (MDA) levels. Finally, ISO inhibited H2O2-induced intracellular reactive oxygen species (ROS) in chondrocytes by activating the nuclear factor erythroid 2-related factor 2 (Nrf2) and phosphatidylinositol 3 kinase/protein kinase B (PI3K/Akt) signaling pathways. This study establishes a theoretical framework for ISO's ability to inhibit OA in vitro models.
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Affiliation(s)
- Tiehan Cui
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
- Medical Innovation Center, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Yun Lan
- Department of Stomatology, Beijing Hospital of Integrated Traditional Chinese and Western Medicine, Beijing 100039, China
| | - Yuying Lu
- Department of Stomatology, Beijing Hospital of Integrated Traditional Chinese and Western Medicine, Beijing 100039, China
| | - Fei Yu
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
- Medical Innovation Center, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Suai Lin
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
- Medical Innovation Center, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Yizhe Fu
- Department of Stomatology, Beijing Hospital of Integrated Traditional Chinese and Western Medicine, Beijing 100039, China
| | - Jiaxuan Qiu
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Guangliang Niu
- Department of Stomatology, Beijing Hospital of Integrated Traditional Chinese and Western Medicine, Beijing 100039, China
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