State of the art in the application of QSAR techniques for predicting mixture toxicity in environmental risk assessment

Environmental Risks of Pharmaceutical Mixtures in Aquatic Ecosystems: Reflections on a Decade of Research

Pharmaceuticals and personal care products (PPCPs) occur as variable mixtures in surface waters receiving discharges of human and animal wastes. A key question identified a decade ago is how to assess the effects of long-term exposures of these PPCP mixtures on nontarget organisms. We review the recent progress made on assessing the aquatic ecotoxicity of PPCP mixtures-with a focus on active pharmaceutical ingredients-and the challenges and research needs that remain. New knowledge has arisen from the use of whole-mixture testing combined with component-based approaches, and these studies show that mixtures often result in responses that meet the concentration addition model. However, such studies have mainly been done on individual species over shorter time periods, and longer-term, multispecies assessments remain limited. The recent use of targeted and nontargeted gene analyses has improved our understanding of the diverse pathways that are impacted, and there are promising new "read-across" methods that use mammalian data to predict toxicity in wildlife. Risk assessments remain challenging given the paucity of ecotoxicological and exposure data on PPCP mixtures. As such, the assessment of PPCP mixtures in aquatic environments should remain a priority given the potential for additive-as well as nontarget-effects in nontarget organisms. In addition, we need to improve our understanding of which species, life stages, and relevant endpoints are most sensitive to which types of PPCP mixtures and to expand our knowledge of environmental PPCP levels in regions of the globe that have been poorly studied to date. We recommend an increased use of new approach methodologies, in particular "omics," to advance our understanding of the molecular mechanics of mixture effects. Finally, we call for systematic research on the role of PPCP mixtures in the development of antimicrobial resistance. Environ Toxicol Chem 2024;43:549-558. © 2023 SETAC.

Conceptual risk assessment of mosquito population modification gene-drive systems to control malaria transmission: preliminary hazards list workshops

The field-testing and eventual adoption of genetically-engineered mosquitoes (GEMs) to control vector-borne pathogen transmission will require them meeting safety criteria specified by regulatory authorities in regions where the technology is being considered for use and other locales that might be impacted. Preliminary risk considerations by researchers and developers may be useful for planning the baseline data collection and field research used to address the anticipated safety concerns. Part of this process is to identify potential hazards (defined as the inherent ability of an entity to cause harm) and their harms, and then chart the pathways to harm and evaluate their probability as part of a risk assessment. The University of California Malaria Initiative (UCMI) participated in a series of workshops held to identify potential hazards specific to mosquito population modification strains carrying gene-drive systems coupled to anti-parasite effector genes and their use in a hypothetical island field trial. The hazards identified were placed within the broader context of previous efforts discussed in the scientific literature. Five risk areas were considered i) pathogens, infections and diseases, and the impacts of GEMs on human and animal health, ii) invasiveness and persistence of GEMs, and interactions of GEMs with target organisms, iii) interactions of GEMs with non-target organisms including horizontal gene transfer, iv) impacts of techniques used for the management of GEMs and v) evolutionary and stability considerations. A preliminary hazards list (PHL) was developed and is made available here. This PHL is useful for internal project risk evaluation and is available to regulators at prospective field sites. UCMI project scientists affirm that the subsequent processes associated with the comprehensive risk assessment for the application of this technology should be driven by the stakeholders at the proposed field site and areas that could be affected by this intervention strategy.

Predicting acute contact toxicity of organic binary mixtures in honey bees (A. mellifera) through innovative QSAR models

Pollinators such as honey bees are of considerable importance, because of the crucial pollination services they provide for food crops and wild plants. Since bees are exposed to a wide range of multiple chemicals "mixtures" both of anthropogenic (e.g. plant protection products) and natural origin (e.g. plant toxins), understanding their combined toxicity is critical. Although honey bees are employed worldwide as surrogate species for Apis and non-Apis bees in toxicity tests, it is practically unfeasible to perform in vivo tests for all mixtures of chemicals. Therefore, Quantitative Structure-Activity Relationships (QSAR) models can be developed using available data and can provide useful tools to predict such combined toxicity. Here, three different QSAR models within the CORAL software have been calibrated and validated for honey bees (A. mellifera) to predict the acute contact mixtures potency (LD_50-mix), in two regression based-models, and the nature of combined toxicity (synergism / non-synergism) in a classification-based model. Experimental data on binary mixtures (n = 123) (LD_50-mix) including dose response data (n = 97) and corresponding Toxic Unit values were retrieved from EFSA databases. The models were built using the principle of extraction of attributes from SMILES (or quasi-SMILES) while calculating so-called correlation weights for these attributes using Monte Carlo techniques. The two regression models were validated for their reliability and robustness (R² = 0.89, CCC = 0.92, Q² = 0.81; R² = 0.87, CCC = 0.89, Q² = 0.75). The classification model was validated using sensitivity (=0.86), specificity (=1), accuracy (=0.96), and Matthews correlation coefficient (MCC = 0.90) as qualitative statistical validation parameters. Results indicate that these QSAR models successfully predict acute contact toxicity of binary mixtures in honey bees and can support prioritisation of multiple chemicals of concerns. Data gaps and further development of QSAR models for honey bees are highlighted particularly for chronic and sub-lethal effects.

QSAR-based investigation on antibiotics facilitating emergence and dissemination of antibiotic resistance genes: A case study of sulfonamides against mutation and conjugative transfer in Escherichia coli

Antibiotic resistance genes (ARGs), which are emerging environmental contaminants, have posed great threats to global public health. Although extensive efforts have been undertaken to investigate ARG pollution, little attention has been paid to the structural information of antibiotics when exploring their impact on the emergence and dissemination of ARGs. In this study, setting Escherichia coli (E. coli) as the test organism, the effects of sulfonamides (SAs) on growth, mutation frequency and conjugative transfer frequency were tested, and quantitative structure-activity relationship (QSAR) was used to quantitatively analyze the promotion of SAs on these biological effects and explore their possible mechanism. The constructed QSAR models reveal that SAs may increase expression of the FtsZ protein and pili in E. coli via binding to the SdiA protein, ultimately leading to SAs facilitation of growth, mutation frequency and conjugative transfer frequency. The results indicate that SAs can produce selective pressure on E. coli to promote the emergence and dissemination of ARGs. This study provides reference data for further investigation of the emergence and dissemination of ARGs under antibiotic exposure and a new perspective for the mechanistic exploration of ARG pollution.

Protein-specific distribution patterns of perfluoroalkyl acids in egg yolk and albumen samples around a fluorochemical facility

In this study, eggs from free-range and barn chickens in farms around a fluorochemical facility were collected to assess the distribution profiles of perfluoroalkyl acids (PFAAs), including isomers of perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonate (PFHxS), in egg yolk and albumen. The results revealed that the concentrations of PFAAs in yolks were significantly higher than those in albumen. All 17 PFAAs examined could be detected in yolks, showing decreasing concentrations with increasing distance from the fluorochemical facility. The three predominant compounds in yolks were perfluorobutanoic acid (PFBA, mean concentration 81.4 ng/g ww), PFOS (28.0 ng/g ww), and PFOA (4.83 ng/g ww), and this result is consistent with the product structure of the facility. Moreover, n-PFOA, n-PFOS, and n-PFHxS were the dominant contaminants in yolk, with mean concentrations of 4.75, 25.7, and 4.29 ng/g ww, respectively. In albumen, PFBA was still the predominant PFAA congener (mean concentration = 3.93 ng/g ww), followed by PFOA. Docking analysis indicated that the PFAAs presented higher binding abilities with the low density lipoprotein, high density lipoprotein, and vitellin proteins in yolk than that with ovalbumin albumen proteins, which might be the main factor influencing the possible difference in distributions of PFAAs in yolk and albumen.

Assessment of river sediment toxicity: Combining empirical zebrafish embryotoxicity testing with in silico toxicity characterization

Quantitative chemical analyses of 428 organic contaminants (OCs) indicated the presence of 313 OCs in the sediment extracts from Sava River, Croatia. Pharmaceuticals were present in higher concentrations than pesticides thus confirming their increasing threat to freshwater ecosystems. Toxicity evaluation of the sediment extracts from four locations (Jesenice, Rugvica, Galdovo and Lukavec) using zebrafish embryotoxicity test (ZET) accompanied with semi-quantitative histopathological analyses exhibited correlation with cumulative number and concentrations of OCs at the investigated sites (10.05, 15.22, 1.25, and 9.13 μg/g respectively). Toxicity of sediment extracts and sediment was predicted using toxic unit (TU) approach and persistence, bioaccumulation and toxicity (PBT) ranking. Additionally, influential OCs and genes were identified by graph mining of the prior knowledge informed, site-specific chemical-gene interaction models. Predicted toxicity of sediment extracts (TU_ext) was similar to the results obtained by ZET and associated histopathology with Rugvica sediment being the most toxic, followed by Jesenice, Lukavec and Galdovo. Sediment TU (TU_sed) favoured OCs with low octanol-water partition coefficients like herbicide glyphosate and antibiotics ciprofloxacin and sulfamethazine thus indicating locations containing higher concentrations of these OCs (Galdovo and Rugvica) as the most toxic. Results suggest that comprehensive in silico sediment toxicity predictions advocate providing equal attention to organic contaminants with either very low or very high log K_ow.

Elevated concentrations of perfluorohexanesulfonate and other per- and polyfluoroalkyl substances in Baiyangdian Lake (China): Source characterization and exposure assessment

Novel 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA) and legacy PFASs, such as perfluorohexane sulfonate (PFHxS), have been used to replace perfluorooctane sulfonate (PFOS), a known persistent organic pollutant. Thus, it is critical to understand these PFOS alternatives regarding their sources and concentrations in the natural environment. In this study, 41 surface water samples as well as edible aquatic organisms were collected from Baiyangdian Lake, the largest freshwater lake in Hebei Province, China. Perfluorooctanoate acid (PFOA) and PFHxS were the predominant PFASs detected in the surface water, reaching concentrations of 8 397.23 ng/L and 1 478.03 ng/L, respectively, with PFHxS accounting for the greatest proportion (∼80.00%) in most water samples. PFHxS (mean: 87.53 ng/g) and PFOS (mean: 35.94 ng/g) were also the most prevalent compounds detected in aquatic organisms. Estimated daily intake (EDI) values of PFOS (16.56 ng/kg bw/d) and PFHxS (16.11 ng/kg bw/d) via aquatic food and drinking water were the highest among PFASs, indicating potential exposure risks to residents. In addition, fish product consumption was the important exposure pathway for residents to PFOA, PFHxS, PFOS, and 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA). This study reports on the highest PFHxS levels ever recorded in surface water, suggesting that further quantification of PFHxS in human serum and assessment of its health risks to local residents are warranted and critical.

A QSAR-based mechanistic study on the combined toxicity of antibiotics and quorum sensing inhibitors against Escherichia coli

Quorum sensing inhibitors (QSIs) have attracted increasing attention due to their potential roles as the antibiotic alternatives. The combination of QSIs and antibiotics in clinical use and their subsequent release into the environment may result in joint effects on the ecology and environment, which has not received enough concerns yet. In this study, eight potential QSIs and three types of commonly used antibiotics, i.e., sulfonamides (SAs), β-lactams and tetracyclines (TCs), were investigated for their combined toxicity on Escherichia coli (E. coli). The QSAR models for the combined toxicity were constructed using the interaction energies between the chemicals and their target proteins as calculated by molecular docking. It was revealed that the SAs and QSIs presented either additive or antagonistic joint effects in the mixture toxicity test, while β-lactams and TCs showed only antagonistic effects with the QSIs. The analysis on the coefficients in the QSAR models suggested that the QSIs in the mixtures were more involved in the interaction with the proteins than the antibiotics. This study will help better understand the risks of joint exposure to the antibiotics and QSIs, and provide a new perspective for the study of the combined toxicity mechanism.