Quantitative structure activity relationships (QSAR) for binary mixtures at non-equitoxic ratios based on toxic ratios-effects curves

Acute toxicity of binary mixtures for quorum sensing inhibitors and sulfonamides against Aliivibrio fischeri: QSAR investigations and joint toxic actions

Quorum sensing inhibitors (QSIs), as a kind of ideal antibiotic substitutes, have been recommended to be used in combination with traditional antibiotics in medical and aquaculture fields. Due to the co-existence of QSIs and antibiotics in environmental media, it is necessary to evaluate their joint risk. However, there is little information about the acute toxicity of mixtures for QSIs and antibiotics. In this study, 10 QSIs and 3 sulfonamides (SAs, as the representatives for traditional antibiotics) were selected as the test chemicals, and their acute toxic effects were determined using the bioluminescence of Aliivibrio fischeri (A. fischeri) as the endpoint. The results indicated that SAs and QSIs all induced S-shaped dose-responses in A. fischeri bioluminescence. Furthermore, SAs possessed greater acute toxicity than QSIs, and luciferase (Luc) might be the target protein of test chemicals. Based on the median effective concentration (EC50) for each test chemical, QSI-SA mixtures were designed according to equitoxic (EC50(QSI):EC50(SA) = 1:1) and non-equitoxic ratios (EC50(QSI):EC50(SA) = 1:10, 1:5, 1:0.2, and 1:0.1). It could be observed that with the increase of QSI proportion, the acute toxicity of QSI-SA mixtures enhanced while the corresponding TU values decreased. Furthermore, QSIs contributed more to the acute toxicity of test binary mixtures. The joint toxic actions of QSIs and SAs were synergism for 23 mixtures, antagonism for 12 mixtures, and addition for 1 mixture. Quantitative structure-activity relationship (QSAR) models for the acute toxicity QSIs, SAs, and their binary mixtures were then constructed based on the lowest CDOCKER interaction energy (Ebind-Luc) between Luc and each chemical and the component proportion in the mixture. These models exhibited good robustness and predictive ability in evaluating the toxicity data and joint toxic actions of QSIs and SAs. This study provides reference data and applicable QSAR models for the environmental risk assessment of QSIs, and gives a new perspective for exploring the joint effects of QSI-antibiotic mixtures.

Potentiation of methylmercury toxicity by combined metal exposure: In vitro and in vivo models of a restricted metal exposome

Methylmercury (MeHg) is a prevalent toxic metal that readily modifies protein thiols. Reactive persulfides that play a role in redox homeostasis are able to inactivate this metal through sulfur adduct formation. Although humans are exposed to other metals that could consume reactive persulfides on a daily basis, the health effects of combined exposure to MeHg and other metals remain unexplored. This study aimed to examine potential MeHg toxicity during exposure to MeHg with other metals capable of consuming reactive persulfides. We designed a simple system to assess the risk of combined exposure to metals based on reactivity to reactive persulfides and mercury accumulation. Among the metals examined in a cell-free system, copper, cadmium, nickel, and MeHg consumed Na₂S₂, used as a model of reactive persulfides, whereas zinc, iron, lithium, strontium, tin, and aluminum did not. In HepG2 cells, binary exposure to MeHg and copper, but not aluminum, increased the consumption of extracellular reactive persulfides. Binary exposure exacerbated MeHg-induced cytotoxicity by promoting the modification of intracellular proteins by MeHg. In a mouse model, binary exposure to MeHg and copper resulted in elevated mercury accumulation in the fetuses and placenta of pregnant mice, as well as the brain and liver of non-pregnant mice. Our study suggests that MeHg sensitivity can be increased by combined exposure with other electrophilic metals. In particular, binary exposure to MeHg and copper during pregnancy exacerbated mercury accumulation in offspring.

Toxicity of binary mixtures of pesticides and pharmaceuticals toward Vibrio fischeri: Assessment by quantitative structure-activity relationships

Pollutants in real aquatic systems commonly occur as chemical mixtures. Yet, the corresponding risk assessment is still mostly based on information on single-pollutant toxicity, accepting the assumption that pollutant mixtures exhibit additive toxicity effect which is often not the case. Therefore, it is still better to use the experimental approach. Unfortunately, experimental determination of toxicity for each mixture is practically unfeasible. In this study, quantitative structure-activity relationship (QSAR) models for the prediction of toxicity of binary mixtures towards bioluminescent bacteria Vibrio fischeri were developed at three toxicity levels (EC₁₀, EC₃₀ and EC₅₀). For model development, experimentally determined toxicity values of 14 pollutants (pharmaceuticals and pesticides) were correlated with their structural features, applying multiple linear regression together with genetic algorithm. Statistical analysis, internal validation and external validation of the models were carried out. The toxicity is accurately predicted by all three models. EC₃₀ and EC₅₀ values are mostly influenced by geometrical distances between nitrogen and sulfur atoms. Furthermore, the simultaneous presence of oxygen and chlorine atoms in mixture can induce the increase in toxicity. At lower effect levels (EC₁₀), nitrogen atom bonded to different groups has the highest impact on mixture toxicity. Thus, the analysis of the descriptors involved in the developed models can give insight into toxic mechanisms of the binary systems.

Effect of combined exposure to environmental aliphatic electrophiles from plants on Keap1/Nrf2 activation and cytotoxicity in HepG2 cells: A model of an electrophile exposome

Electrophiles, ubiquitously found in the environment, modify thiol groups of sensor proteins, leading to activation of redox signaling pathways such as the Kelch-like ECH-associated protein 1 (Keap1)/nuclear factor E2 related factor 2 (Nrf2) pathway. Nrf2 activation by exposure to single electrophiles has been established. However, the effect of exposure to a combination of electrophiles on Nrf2 activation has not been well evaluated. The current study examined whether combined exposure to electrophiles enhances the modification of thiol groups and Keap1/Nrf2 activation in HepG2 cells. Six electrophiles [1,2-naphthoquinone (1,2-NQ), 1,4-NQ, 1,4-benzoquinone, (E)-2-hexenal (hexenal), (E)-2-decenal, and (E)-2-butenal] were tested for S-modification of albumin in vitro and for cytotoxicity to HepG2 cells. Interestingly, a mixture of the electrophiles enhanced S-modification of albumin and cytotoxicity compared with exposure to each electrophile separately. Herein, we focused on 1,2-NQ, 1,4-NQ, and hexenal to clarify the combined effect of electrophiles on Keap1/Nrf2 activation in HepG2 cells. A concentration addition model revealed that 1,2-NQ and/or 1,4-NQ additively enhanced hexenal-mediated S-modification of GSH in vitro, whereas the cytotoxicity of hexenal was synergistically increased by simultaneous exposure of HepG2 cells to the NQs. Furthermore, an NQ cocktail (2.5 μM each) that does not activate Nrf2 enhanced hexenal-mediated Nrf2 activation. These results suggest that combined exposure to electrophiles at low concentrations induces stronger activation of redox signaling compared with exposure to each electrophile alone and worsens their cytotoxicity.

Ten years of research on synergisms and antagonisms in chemical mixtures: A systematic review and quantitative reappraisal of mixture studies

BACKGROUND

Several reviews of synergisms and antagonisms in chemical mixtures have concluded that synergisms are relatively rare. However, these reviews focused on mixtures composed of specific groups of chemicals, such as pesticides or metals and on toxicity endpoints mostly relevant to ecotoxicology. Doubts remain whether these findings can be generalised. A systematic review not restricted to specific chemical mixtures and including mammalian and human toxicity endpoints is missing.

OBJECTIVES

We conducted a systematic review and quantitative reappraisal of 10 years' of experimental mixture studies to investigate the frequency and reliability of evaluations of mixture effects as synergistic or antagonistic. Unlike previous reviews, we did not limit our efforts to certain groups of chemicals or specific toxicity outcomes and covered mixture studies relevant to ecotoxicology and human/mammalian toxicology published between 2007 and 2017.

DATA SOURCES, ELIGIBILITY CRITERIA

We undertook searches for peer-reviewed articles in PubMed, Web of Science, Scopus, GreenFile, ScienceDirect and Toxline and included studies of controlled exposures of environmental chemical pollutants, defined as unintentional exposures leading to unintended effects. Studies with viruses, prions or therapeutic agents were excluded, as were records with missing details on chemicals' identities, toxicities, doses, or concentrations.

STUDY APPRAISAL AND SYNTHESIS METHODS

To examine the internal validity of studies we developed a risk-of-bias tool tailored to mixture toxicology. For a subset of 388 entries that claimed synergisms or antagonisms, we conducted a quantitative reappraisal of authors' evaluations by deriving ratios of predicted and observed effective mixture doses (concentrations).

RESULTS

Our searches produced an inventory of 1220 mixture experiments which we subjected to subgroup analyses. Approximately two thirds of studies did not incorporate more than 2 components. Most experiments relied on low-cost assays with readily quantifiable endpoints. Important toxicity outcomes of relevance for human risk assessment (e.g. carcinogenicity, genotoxicity, reproductive toxicity, immunotoxicity, neurotoxicity) were rarely addressed. The proportion of studies that declared additivity, synergism or antagonisms was approximately equal (one quarter each); the remaining quarter arrived at different evaluations. About half of the 1220 entries were rated as "definitely" or "probably" low risk of bias. Strikingly, relatively few claims of synergistic or antagonistic effects stood up to scrutiny in terms of deviations from expected additivity that exceed the boundaries of acceptable between-study variability. In most cases, the observed mixture doses were not more than two-fold higher or lower than the predicted additive doses. Twenty percent of the entries (N = 78) reported synergisms in excess of that degree of deviation. Our efforts of pinpointing specific factors that predispose to synergistic interactions confirmed previous concerns about the synergistic potential of combinations of triazine, azole and pyrethroid pesticides at environmentally relevant doses. New evidence of synergisms with endocrine disrupting chemicals and metal compounds such as chromium (VI) and nickel in combination with cadmium has emerged.

CONCLUSIONS, LIMITATIONS AND IMPLICATIONS

These specific cases of synergisms apart, our results confirm the utility of default application of the dose (concentration) addition concept for predictive assessments of simultaneous exposures to multiple chemicals. However, this strategy must be complemented by an awareness of the synergistic potential of specific classes of chemicals. Our conclusions only apply to the chemical space captured in published mixture studies which is biased towards relatively well-researched chemicals.

SYSTEMATIC REVIEW REGISTRATION NUMBER

The final protocol was published on the open-access repository Zenodo and attributed the following digital object identifier, doi: https://doi.org//10.5281/zenodo.1319759 (https://zenodo.org/record/1319759#.XXIzdy7dsqM).

Cytotoxicity of Halogenated Tyrosyl Compounds, an Emerging Class of Disinfection Byproducts

Halogenated amino acids and peptides are an emerging class of disinfection byproducts (DBPs), having been detected in drinking water and in washed food products. However, the toxicological significance of these emerging DBPs remains unclear. In this study, the cytotoxicity of eight halogenated tyrosyl compounds was investigated in Chinese hamster ovary (CHO) cells using real-time cell analysis (RTCA). Dihalogenated tyrosyl compounds are more cytotoxic than their monohalogenated analogues. The cytotoxicity of the dihalogenated compounds is associated with their ability to induce intracellular reactive oxygen species (ROS), suggesting that oxidative stress is an important toxicity pathway of these compounds. Pearson correlation analysis of the cytotoxicity (IC₅₀ values) of these compounds with eight physicochemical parameters showed strong associations with their lipophilicity (logP) and reactivity (polarizability, E_LUMO). Finally, cytotoxicity testing of the concentrated extracts of a chloraminated mixture of eight dipeptides with bromide or iodide showed the cytotoxicity of these mixtures in the order: iodinated peptides > brominated peptides ≥ chlorinated peptides. These results demonstrate that halogenated peptide DBPs are toxicologically relevant, and further research is needed to understand the implications of long-term exposure for human health.

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.

Regular time-dependent cross-phenomena induced by hormesis: A case study of binary antibacterial mixtures to Aliivibrio fischeri

Time-dependent cross-phenomenon in which the cross between the actual concentration-response curve (CRC) for mixture crosses the CRCs for reference model varies with time has been frequently reported in previous studies, expressed as a heterogeneous pattern of joint toxic action. However, the variation tendency of time-dependent cross-phenomenon is rarely addressed. In this study, the joint toxic actions of binary antibacterial mixtures (i.e., two quorum sensing inhibitors, tetracycline hydrochloride, erythromycin, and chloramphenicol with sulfonamides) were judged using independent action (IA) model to find the variation tendency of time-dependent cross-phenomenon. The results show that the time-dependent cross-phenomena of the test binary antibacterial mixtures follow a unified variation tendency and the corresponding joint toxic actions change regularly with an increase of both concentration and time. Through investigating the relationship between the stimulatory and inhibitory modes of action for the single agents and the time-dependent cross-phenomena of binary mixtures, the regular time-dependent cross-phenomena is speculated to be derived from the hormetic effects of the components in the mixtures. This study offers an advance for the variation tendency and mechanistic explanation of time-dependent cross-phenomenon, which will provide a support for the future development in the exploration of time-dependent cross-phenomenon and environmental risk assessment of pollutant mixtures.

New Insight Regarding the Relationship Between Enantioselective Toxicity Difference and Enantiomeric Toxicity Interaction from Chiral Ionic Liquids

Chirality is an important property of molecules. The study of biological activity and toxicity of chiral molecules has important theoretical and practical significance for toxicology, pharmacology, and environmental science. The toxicological significance of chiral ionic liquids (ILs) has not been well revealed. In the present study, the enantiomeric joint toxicities of four pairs of chiral ILs 1-alkyl-3-methylimidazolium lactate to Allivibrio fischeri were systematically investigated by using a comprehensive approach including the co-toxicity coefficient (CTC) integrated with confidence interval (CI) method (CTCICI), concentration-response curve (CRC), and isobole analysis. The direct equipartition ray (EquRay) design was used to design five binary mixtures of enantiomers according to molar ratios of 1:5, 2:4, 3:3, 4:2, and 5:1. The toxicities of chiral ILs and their mixtures were determined using the microplate toxicity analysis (MTA) method. Concentration addition (CA) and independent action (IA) were used as the additive reference models to construct the predicted CRC and isobole of mixtures. On the whole, there was an enantioselective toxicity difference between [BMIM]D-Lac and [BMIM]L-Lac, and [HMIM]D-Lac and [HMIM]L-Lac, while no enantioselective toxicity difference was observed for [EMIM]D-Lac and [EMIM]L-Lac, and [OMIM]D-Lac and [OMIM]L-Lac. Thereinto, the enantiomer mixtures of [BMIM]D-Lac and [BMIM]L-Lac, and [HMIM]D-Lac and [HMIM]L-Lac presented antagonistic action, and the enantiomer mixtures of [EMIM]D-Lac and [EMIM]L-Lac, and [OMIM]D-Lac and [OMIM]L-Lac overall presented additive action. Moreover, the greatest antagonistic toxicity interaction occurred at the equimolar ratio of enantiomers. Based on these results, we proposed two hypotheses, (1) chiral molecules with enantioselective toxicity difference tended to produce toxicity interactions, (2) the highest or lowest toxicity was usually at the equimolar ratio and its adjacent ratio for the enantiomer mixture. These hypotheses will need to be further validated by other enantiomer mixtures.

Exploration of Computational Approaches to Predict the Toxicity of Chemical Mixtures

Industrial advances have led to generation of multi-component chemicals, materials and pharmaceuticals which are directly or indirectly affecting the environment. Although toxicity data are available for individual chemicals, generally there is no toxicity data of chemical mixtures. Most importantly, the nature of toxicity of these studied mixtures is completely different to the single components, which makes the toxicity evaluation of mixtures more critical and challenging. Interactions of individual chemicals in a mixture can result in multifaceted and considerable deviations in the apparent properties of its ingredients. It results in synergistic or antagonistic effects as opposed to the ideal case of additive behavior i.e., concentration addition (CA) and independent action (IA). The CA and IA are leading models for the assessment of joint activity supported by pharmacology literature. Animal models for toxicity testing are time- and money-consuming as well as unethical. Thus, computational approaches are already proven efficient alternatives for assessing the toxicity of chemicals by regulatory authorities followed by industries. In silico methods are capable of predicting toxicity, prioritizing chemicals, identifying risk and assessing, followed by managing, the risk. In many cases, the mechanism behind the toxicity from species to species can be understood by in silico methods. Until today most of the computational approaches have been employed for single chemical's toxicity. Thus, only a handful of works in the literature and methods are available for a mixture's toxicity prediction employing computational or in silico approaches. Therefore, the present review explains the importance of evaluation of a mixture's toxicity, the role of computational approaches to assess the toxicity, followed by types of in silico methods. Additionally, successful application of in silico tools in a mixture's toxicity predictions is explained in detail. Finally, future avenues towards the role and application of computational approaches in a mixture's toxicity are discussed.

Mechanistic explanation of time-dependent cross-phenomenon based on quorum sensing: A case study of the mixture of sulfonamide and quorum sensing inhibitor to bioluminescence of Aliivibrio fischeri

Cross-phenomenon in which the concentration-response curve (CRC) for a mixture crosses the CRC for the reference model has been identified in many studies, expressed as a heterogeneous pattern of joint toxic action. However, a mechanistic explanation of the cross-phenomenon has thus far been extremely insufficient. In this study, a time-dependent cross-phenomenon was observed, in which the cross-concentration range between the CRC for the mixture of sulfamethoxypyridazine (SMP) and (Z-)-4-Bromo-5-(bromomethylene)-2(5H)-furanone (C30) to the bioluminescence of Aliivibrio fischeri (A. fischeri) and the CRC for independent action model with 95% confidence bands varied from low-concentration to higher-concentration regions in a timely manner expressed the joint toxic action of the mixture changing with an increase of both concentration and time. Through investigating the time-dependent hormetic effects of SMP and C30 (by measuring the expression of protein mRNA, simulating the bioluminescent reaction and analyzing the toxic action), the underlying mechanism was as follows: SMP and C30 acted on the quorum sensing (QS) system of A. fischeri, which induced low-concentration stimulatory effects and high-concentration inhibitory effects; in the low-concentration region, the stimulatory effects of SMP and C30 made the mixture produce a synergistic stimulation on the bioluminescence; thus, the joint toxic action exhibited antagonism. In the high-concentration region, the inhibitory effects of SMP and C30 in the mixture caused a double block in the loop circuit of the QS system; thus, the joint toxic action exhibited synergism. With the increase of time, these stimulatory and inhibitory effects of SMP and C30 were changed by the variation of the QS system at different growth phases, resulting in the time-dependent cross-phenomenon. This study proposes an induced mechanism for time-dependent cross-phenomenon based on QS, which may provide new insight into the mechanistic investigation of time-dependent cross-phenomenon, benefitting the environmental risk assessment of mixtures.

Novel two-tiered approach of ecological risk assessment for pesticide mixtures based on joint effects

Ecological risk assessments for mixtures have attracted considerable attention. In this study, 38 pesticides in the real environment were taken as objects and their toxicities to different organisms from three trophic levels were employed to assess the ecological risk of the mixture. The first tier assessment was based on the CA effect and the obtained sum of risk quotients (SRQ_species-CA) were 3.06-9.22. The second tier assessment was based on non-CA effects and the calculated SRQ_species-TU are 5.37-9.29 using joint effects (TU_sum) as modified coefficients, which is higher than SRQ_species-CA and indicates that ignoring joint effects might run the risk of underestimating the actual impact of pesticide mixtures. Due to the influences of synergistic and antagonistic effects, risk contribution of components to mixture risks based on non-CA effects are different from those based on the CA effect. Moreover, it was found that the top 8 dominating components explained 95.5%-99.8% of mixture risks in this study. The dominating components are similar in the two tiers for a given species. Accordingly, a novel two-tiered approach was proposed to assess the ecological risks of mixtures based on joint effects. This study provides new insights for ecological risk assessments with the consideration of joint effects of components in the pesticide mixtures.

Mechanism Underlying Time-dependent Cross-phenomenon between Concentration-response Curves and Concentration Addition Curves: A Case Study of Sulfonamides-Erythromycin mixtures on Escherichia coli

Previous studies have identified a phenomenon in which the concentration-response curves (CRCs) for mixtures cross the curves for concentration addition model when predicting or judging joint toxic actions. However, mechanistic investigations of this phenomenon are extremely limited. In this study, a similar phenomenon was observed when we determined the joint toxic actions of sulfonamides (SAs) and erythromycin (ERY) on Escherichia coli (E. coli), which we named the "cross-phenomenon", and it was characterized by antagonism in the low-concentration range, addition in the medium-concentration range, and synergism in the high-concentration range. The mechanistic investigation of the cross-phenomenon was as follows: SAs and ERY could form a double block to inhibit the bacterial growth by exhibiting a synergistic effect; however, the hormetic effect of SAs on E. coli led to antagonism in the low-concentration range, resulting from the stimulation of sdiA mRNA expression by SAs, which increased the expression of the efflux pump (AcrAB-TolC) to discharge ERY. Furthermore, this cross-phenomenon was observed to be a time-dependent process induced by the increase of both the concentration and extent of stimulation of sdiA mRNA with exposure time. This work explains the dose-dependent and time-dependent cross-phenomenon and provides evidence regarding the interaction between hormesis and cross-phenomenon.

The mixture toxicity of environmental contaminants containing sulfonamides and other antibiotics in Escherichia coli: Differences in both the special target proteins of individual chemicals and their effective combined concentration

Organisms in the environment are exposed to mixtures of multiple contaminants, leading to serious environmental harm. These mixtures pose an ecological risk and have attracted an increasing amount of attention; however there has been little in-depth research the toxicity of mixtures, such as antibiotics. To determine how different mixtures of antibiotics affect organisms, the individual and mixture toxicity of sulfonamides and several antibiotics were determined using Escherichia coli as a target organism in our study. The results show that additive effects occur between sulfonamides and quinolones or with a portion of β-lactams, synergistic effects appear between sulfonamides and their potentiators or cefotaxime sodium, and antagonistic effects arise between sulfonamides and tetracyclines or penicillin V potassium salt. In addition, the toxicity mechanism of binary mixtures is further discussed and the results reveal that the joint effect differences depend not only the target proteins of individual chemicals but also on their effective combined concentration based on the approach of Quantitative Structure Activity Relationships (QSARs) and molecular docking. This study introduces the concept of the "effective concentration" to provide insight into understanding the mechanism of binary mixtures, which will be beneficial for evaluating the ecological risk of antibiotics.

Joint toxic effects of the type-2 alkene electrophiles

Human populations are exposed to complex environmental mixtures of acrolein, methylvinyl ketone (MVK) and other type-2 alkenes. Many members of this chemical class are electrophiles that possess a common molecular mechanism of toxicity; i.e., protein inactivation via formation of stable cysteine adducts. Therefore, acute or chronic exposure to type-2 alkene mixtures could represent a health risk due to additive or synergistic interactions among component chemicals. Despite this risk, there is little experimental information regarding the joint effects of type-2 alkenes. In the present study we used sum of toxic units (TUsum = ∑TUi) to assess the relative toxicity of different type-2 alkene mixtures. These studies involved well characterized environmental type-2 alkene toxicants and included amide (acrylamide; ACR), ketone (methyl vinyl ketone; MVK), aldehyde (2-ethylacrolein; EA) and ester (methyl acrylate; MA) derivatives. In chemico analyses revealed that both binary and ternary mixtures could deplete thiol groups according to an additive joint effect at equitoxic and non-equitoxic ratios; i.e., TUsum = 1.0 ± 0.20. In contrast, analyses of joint effects in SNB19 cell cultures indicated that different permutations of type-2 alkene mixtures produced mostly synergistic joint effects with respect to cell lethality; i.e., TUsum < 0.80. A mixture of ACR and MA was shown to produce joint toxicity in a rat model. This mixture accelerated the onset and development of neurotoxicity relative to the effects of the individual toxicants. Synergistic effects in biological models might occur when different cellular proteomes are targeted, whereas additive effects develop when the mixtures encompasses a similar proteome.

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

The focus of regulatory chemical risk assessment has been mainly placed on single chemicals rather than mixtures. However, living organisms and the environment might be exposed to mixtures of chemicals. Many scientific studies have revealed that mixture toxicity can arise from the combined effects of components present at levels below their individual no-effect concentrations. Predictive approaches will be essential for estimating mixture toxicity, as the number of possible mixtures is extremely large. Although predictive models are virtually indispensable for estimating mixture toxicity for both scientific and regulatory purposes, risk assessors encounter substantial difficulties in using conventional models, mainly due to the lack of information on the modes of toxic action of the mixture constituents. Alternative models that use different information instead of the modes of action thus need to be developed. The objective of this study is to investigate the state of the art in predictive models based on quantitative structure-activity relationship techniques for estimating the toxicity of mixture components, and to identify future challenges hindering more reliable mixture risk assessment for environmental risk assessment. Alternative models need to be developed not only to overcome the limitations of conventional models, but also to improve their performance.

Balance between herbicidal activity and toxicity effect: a case study of the joint effects of triazine and phenylurea herbicides on Selenastrum capricornutum and Photobacterium phosphoreum

The use of herbicide mixtures has become a cost-effective strategy against the evolution of herbicide resistance to protect global food production. Much research has focused on investigating either the herbicidal activities or the toxicity effects of herbicides; however, few of them have investigated both factors. This study investigates the balance between herbicidal activity for Selenastrum capricornutum and toxicity effect toward Photobacterium phosphoreum by determining the joint effects of triazine (simetryn, atrazine, prometon and prometryn) and phenylurea (fenuron, monuron, monolinuron and diuron) herbicides. The results showed that among the four triazines, only simetryn exhibited a unique effect (formation of a pi-sigma bond with the D1 microalga protein and an H-bond with the Luc photobacterial protein); and among 16 triazine-phenylurea binary mixtures, only the mixtures containing simetryn resulted in TU1 values (herbicidal activities of mixtures on S. capricornutum) >TU2 values (toxicity effects of mixtures on P. phosphoreum). However, the other 12 mixtures, which did not contain simetryn, showed the opposite result (TU1<TU2). A comparison of TU1 with TU2 showed that additive effects occurred more frequently for TU1, whereas antagonism effects occurred more frequently for TU2. Based on these results, a preliminary mechanistic hypothesis of herbicide mixtures was proposed. Meanwhile, some suggestions are provided firstly for herbicide combinations based on the balance between herbicidal activity and toxicity effect, which will encourage thoughtful efforts for how to best combine herbicides in a sustainable way.