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

Determining the toxicity of organic compounds to the nematode Caenorhabditis elegans based on aqueous concentrations

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.

Deciphering the toxicity mechanism of haloquinolines on Chlorella pyrenoidosa using QSAR and metabolomics approaches

The hazardous potential of haloquinolines (HQLs) is becoming an issue of great concern due to its wide and long-term usage in many personal care products. We examined the growth inhibition, structure-activity relationship, and toxicity mechanism of 33 HQLs on Chlorella pyrenoidosa using the 72-h algal growth inhibition assay, three-dimensional quantitative structure-activity relationship (3D-QSAR), and metabolomics. We found that the IC₅₀ (half maximal inhibitory concentration) values for 33 compounds ranged from 4.52 to > 150 mg·L^-1, most tested compounds were toxic (1 mg·L^-1 < IC₅₀ < 10 mg·L^-1) or harmful (10 mg·L^-1 < IC₅₀ < 100 mg·L^-1) for the aquatic ecosystem. Hydrophobic properties of HQLs dominate their toxicity. Halogen atoms with large volume appear at the 2, 3, 4, 5, 6, and 7-positions of the quinoline ring to significantly increase the toxicity. In algal cells, HQLs can block diverse carbohydrates, lipids, and amino acid metabolism pathways, thereby resulting in energy usage, osmotic pressure regulation, membrane integrity, oxidative stress disorder, thus fatally damaging algal cells. Therefore, our results provide insight into the toxicity mechanism and ecological risk of HQLs.

Genes-to-Pathways Species Conservation Analysis: Enabling the Exploration of Conservation of Biological Pathways and Processes Across Species

The last two decades have witnessed a strong momentum toward integration of cell-based and computational approaches in safety assessments. This is fueling a global regulatory paradigm shift toward reduction and replacement of the use of animals in toxicity tests while promoting the use of new approach methodologies. The understanding of conservation of molecular targets and pathways provides an opportunity to extrapolate effects across species and ultimately to determine the taxonomic applicability domain of assays and biological effects. Despite the wealth of genome-linked data available, there is a compelling need for improved accessibility, while ensuring that it reflects the underpinning biology. We present the novel pipeline Genes-to-Pathways Species Conservation Analysis (G2P-SCAN) to further support understanding on cross-species extrapolation of biological processes. This R package extracts, synthetizes, and structures the data available from different databases, that is, gene orthologs, protein families, entities, and reactions, linked to human genes and respective pathways across six relevant model species. The use of G2P-SCAN enables the overall analysis of orthology and functional families to substantiate the identification of conservation and susceptibility at the pathway level. In the present study we discuss five case studies, demonstrating the validity of the developed pipeline and its potential use as species extrapolation support. We foresee this pipeline will provide valuable biological insights and create space for the use of mechanistically based data to inform potential species susceptibility for research and safety decision purposes. Environ Toxicol Chem 2023;42:1152-1166. © 2023 UNILEVER GLOBAL IP LTD. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Construction of an In Silico Structural Profiling Tool Facilitating Mechanistically Grounded Classification of Aquatic Toxicants

The performance of chemical safety assessment within the domain of environmental toxicology is often impeded by a shortfall of appropriate experimental data describing potential hazards across the many compounds in regular industrial use. In silico schemes for assigning aquatic-relevant modes or mechanisms of toxic action to substances, based solely on consideration of chemical structure, have seen widespread employment─including those of Verhaar, Russom, and later Bauer (MechoA). Recently, development of a further system was reported by Sapounidou, which, in common with MechoA, seeks to ground its classifications in understanding and appreciation of molecular initiating events. Until now, this Sapounidou scheme has not seen implementation as a tool for practical screening use. Accordingly, the primary purpose of this study was to create such a resource─in the form of a computational workflow. This exercise was facilitated through the formulation of 183 structural alerts/rules describing molecular features associated with narcosis, chemical reactivity, and specific mechanisms of action. Output was subsequently compared relative to that of the three aforementioned alternative systems to identify strengths and shortcomings as regards coverage of chemical space.