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Abstract: In this study, the chemopreventive effects of rosmarinic acid (RA), a major phenolic acid of the plant Rosmarinus officinalis L., against the carcinogenic naturally occurring mycotoxin aflatoxin B1 (AFB1) were investigated using both in silico and in vitro approaches. The in silico investigation of the chemical reactions between rosmarinic acid and the carcinogenic metabolite of AFB1, aflatoxin B1 exo-8,9-epoxide (AFBO), was conducted by activation free energies calculations with DFT functionals M11-L and MN12-L, in conjunction with the 6-311++G(d,p) flexible basis set and implicit solvation model density (SMD), according to a newly developed quantum mechanics-based protocol for the evaluation of carcinogen scavenging activity (QM-CSA). Following the computational analyses, the chemoprotective effects of RA were further studied in vitro in human hepatocellular carcinoma HepG2 cells by analyzing its influence on AFB1-induced genotoxicity using a comet assay, γH2AX, and p-H3, while its impact on cell proliferation and cell cycle modulation was assessed using flow cytometry. Our computational results revealed that the activation free energy required for the reaction of RA with AFBO (14.86 kcal/mol) is significantly lower than the activation free energy for the competing reaction of AFBO with guanine (16.88 kcal/mol), which indicates that RA acts as an efficient natural scavenger of AFBO, potentially preventing AFB1-specific DNA adduct formation. The chemoprotective activity of RA was confirmed through in vitro experiments, which demonstrated a statistically significant (p < 0.05) reduction in AFB1-induced single- and double-strand breaks in HepG2 cells exposed to a mixture of AFB1 and RA at non-cytotoxic concentrations. In addition, RA reversed the AFB1-induced reduction in cell proliferation.
Keywords: rosmarinic acid, aflatoxin B1, chemopreventive effects, antigenotoxic effects, density functional theory, chemical carcinogen scavenger, toxicology
Published in DiRROS: 03.07.2025; Views: 675; Downloads: 520
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Abstract: Anatoxins (ATX) are globally occurring toxins produced by some species of cyanobacteria in aquatic habitats. They can cause acute poisoning in animals, leading to muscle paralysis and respiratory failure, and might also pose a long-term health risk to humans. Thanks to advances in molecular methods and genomic knowledge, it is now possible to rapidly detect and quantify the genes associated with cyanotoxin production for most major groups of cyanotoxins except ATX. The aim of this study was to develop and validate a new quantitative PCR (qPCR) assay for general detection of all potential ATX producers in the environment. After specificity testing in silico and in vitro with 16 cyanobacterial strains (endpoint PCR, amplicon sequencing and qPCR), two assays targeting the anaC gene were thoroughly validated for linearity, amplification efficiency, sensitivity, dynamic range, inter-assay and intra-assay variability, and the influence of background DNA. The assays were then applied to 144 environmental samples of plankton and biofilm from lakes and rivers whose ATX content had previously been measured by liquid chromatography with tandem mass spectrometry (LC-MS/MS). Amplification efficiency of the two designed assays was between 94% and 103%, and the limits of quantification and detection were up to, but mostly below, 322 and 32 cells/mL, respectively. Both assays showed better or equal specificity in cyanobacterial cultures than currently available PCR assays and were able to predict the presence of ATX detected by LC-MS/MS in most environmental samples (83 % in plankton and 52–62% in biofilm). A higher number of discrepancies between qPCR and LC-MS/MS results in biofilm than in plankton samples indicates limited knowledge and sparse genomic data on benthic cyanobacteria. These assays are the first published general qPCR assays targeting all ATX producers and could provide water managers with a rapid and cost-effective risk assessment to better protect human and animal health.
Keywords: anatoxins (ATX), cyanobacteria, qPCR assay, anaC gene, LC-MS/MS, environmental microbiology, environmental science, toxicology, molecular biology
Published in DiRROS: 17.12.2024; Views: 1040; Downloads: 507
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Abstract: An important goal in toxicology is the development of new ways to increase the speed, accuracy, and applicability of chemical hazard and risk assessment approaches. A promising route is the integration of in vitro assays with biological pathway information. We examined how the adverse outcome pathway (AOP) framework can be used to develop pathway-based quantitative models useful for regulatory chemical safety assessment. By using AOPs as initial conceptual models and the AOP knowledge base as a source of data on key event relationships, different methods can be applied to develop computational quantitative AOP models (qAOPs) relevant for decision making. A qAOP model may not necessarily have the same structure as the AOP it is based on. Useful AOP modeling methods range from statistical, Bayesian networks, regression, and ordinary differential equations to individual-based models and should be chosen according to the questions being asked and the data available. We discuss the need for toxicokinetic models to provide linkages between exposure and qAOPs, to extrapolate from in vitro to in vivo, and to extrapolate across species. Finally, we identify best practices for modeling and model building and the necessity for transparent and comprehensive documentation to gain confidence in the use of qAOP models and ultimately their use in regulatory applications. Environ Toxicol Chem 2019;38:1850–1865. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.
Keywords: Quantitative Adverse Outcome pathways, TKTD modelling, alternatives to animal testing, predictive toxicology, species extrapolation, prioritization of chemicals
Published in DiRROS: 06.08.2024; Views: 1011; Downloads: 625
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Abstract: Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology, and medicine. With the rise of synthetic and new engineered materials, alongside ongoing prioritisation needs in chemical risk assessment for existing chemicals, early predictive evaluations are becoming of utmost importance to both scientific and regulatory purposes. ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. To coordinate the linkage of various life science efforts around modern predictive toxicology, the establishment of a new ELIXIR Community is seen as instrumental. In the past few years, joint efforts, building on incidental overlap, have been piloted in the context of ELIXIR. For example, the EU-ToxRisk, diXa, HeCaToS, transQST, and the nanotoxicology community have worked with the ELIXIR TeSS, Bioschemas, and Compute Platforms and activities. In 2018, a core group of interested parties wrote a proposal, outlining a sketch of what this new ELIXIR Toxicology Community would look like. A recent workshop (held September 30th to October 1st, 2020) extended this into an ELIXIR Toxicology roadmap and a shortlist of limited investment-high gain collaborations to give body to this new community. This Whitepaper outlines the results of these efforts and defines our vision of the ELIXIR Toxicology Community and how it complements other ELIXIR activities.
Keywords: toxicology, ELIXIR, interoperability, FAIR
Published in DiRROS: 05.08.2024; Views: 1043; Downloads: 599
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Abstract: The last decade has seen the adverse outcome pathways (AOP) framework become one of the most powerful tools in chemical risk assessment, but the development of new AOPs remains a slow and manually intensive process. Here, we present a faster approach for AOP generation, based on manually curated causal toxicological networks. As a case study, we took a recently published zebrafish developmental neurotoxicity network, which contains causally connected molecular events leading to neuropathologies, and developed two new adverse outcome pathways: Inhibition of Fyna (Src family tyrosine kinase A) leading to increased mortality via decreased eye size (AOP 399 on AOP-Wiki) and GSK3beta (Glycogen synthase kinase 3 beta) inactivation leading to increased mortality via defects in developing inner ear (AOP 410). The approach consists of an automatic separation of the toxicological network into candidate AOPs, filtering the AOPs according to available evidence and length as well as manual development of new AOPs and weight-of-evidence evaluation. The semiautomatic approach described here provides a new opportunity for fast and straightforward AOP development based on large network resources.
Keywords: systems toxicology, adverse outcome pathway, casual network, toxicological network, neurotoxicity
Published in DiRROS: 16.07.2024; Views: 1210; Downloads: 593
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