Literature DB >> 30663905

Developing adverse outcome pathways on silver nanoparticle-induced reproductive toxicity via oxidative stress in the nematode Caenorhabditis elegans using a Bayesian network model.

Jaeseong Jeong1, Taejun Song1, Nivedita Chatterjee1, Inhee Choi2, Yoon Kyung Cha1, Jinhee Choi1.   

Abstract

An adverse outcome pathway (AOP) is a framework that organizes the mechanistic or predictive relationships between molecular initiating events (MIEs), key events (KEs), and adverse outcomes (AOs). Previously, we intensively investigated the molecular mechanism that underlies toxicity caused by AgNPs in the nematode Caenorhabditis elegans. Using transcriptomics, functional genetics, and various molecular/biochemical tools, we identified oxidative stress as the major mechanism underlying toxicity and reproduction failure as the outcome. With this information, here we conducted a case study of building an AOP to link oxidative stress with reproductive toxicity. To validate this AOP, we filled the gaps by conducting further experiments on its elements, such as NADPH oxidase, ROS formation, PMK-1 P38 MAPK activation, HIF-1 activation, mitochondrial damage, DNA damage, and apoptosis. The establishment of a causal link between the MIE and AO is critical for the construction of an AOP. Therefore, causal relationships between each KE and AO were verified by using functional genetic mutants of each KE. By combining these experimental data with our previously published results, we established causal relationships between the MIE, KEs, and AO using a Bayesian network (BN) model, culminating in an AOP entitled 'NADPH oxidase and P38 MAPK activation leading to reproductive failure in C. elegans ( https://aopwiki.org/aops/207)' . Overall, our approach shows that an AOP can be developed using existing data and further experiments can be conducted to fill the gaps between the MIE, KEs, and the AO. This study also shows that BN modeling has the potential to identify causal relationships in an AOP.

Entities:  

Keywords:  Adverse Outcome Pathway; Bayesian network; ; nanotoxicity; silver nanoparticles

Mesh:

Substances:

Year:  2019        PMID: 30663905     DOI: 10.1080/17435390.2018.1529835

Source DB:  PubMed          Journal:  Nanotoxicology        ISSN: 1743-5390            Impact factor:   5.913


  6 in total

Review 1.  Nanotechnology and artificial intelligence to enable sustainable and precision agriculture.

Authors:  Peng Zhang; Zhiling Guo; Sami Ullah; Georgia Melagraki; Antreas Afantitis; Iseult Lynch
Journal:  Nat Plants       Date:  2021-06-24       Impact factor: 15.793

Review 2.  Overview of Adverse Outcome Pathways and Current Applications on Nanomaterials.

Authors:  Dora Rolo; Ana Tavares; Nádia Vital; Maria João Silva; Henriqueta Louro
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

3.  In Vivo Effects of Silver Nanoparticles on Development, Behavior, and Mitochondrial Function are Altered by Genetic Defects in Mitochondrial Dynamics.

Authors:  Danielle F Mello; Laura L Maurer; Ian T Ryde; Dong Hoon Songr; Stella M Marinakos; Chuanjia Jiang; Mark R Wiesner; Heileen Hsu-Kim; Joel N Meyer
Journal:  Environ Sci Technol       Date:  2022-01-04       Impact factor: 9.028

4.  La2O3 Nanoparticles Induce Reproductive Toxicity Mediated by the Nrf-2/ARE Signaling Pathway in Kunming Mice.

Authors:  Lu Yuan; Qingzhao Li; Disi Bai; Xueliang Shang; Fen Hu; Zhenfei Chen; Tianyang An; Yajing Chen; Xiujun Zhang
Journal:  Int J Nanomedicine       Date:  2020-05-14

Review 5.  Quantitative adverse outcome pathway (qAOP) models for toxicity prediction.

Authors:  Nicoleta Spinu; Mark T D Cronin; Steven J Enoch; Judith C Madden; Andrew P Worth
Journal:  Arch Toxicol       Date:  2020-05-18       Impact factor: 5.153

6.  From Qualitative to Quantitative AOP: A Case Study of Neurodegeneration.

Authors:  Dennis Sinitsyn; Natàlia Garcia-Reyero; Karen H Watanabe
Journal:  Front Toxicol       Date:  2022-03-30
  6 in total

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