Applying mixture toxicity modelling to predict bacterial bioluminescence inhibition by non-specifically acting pharmaceuticals and specifically acting antibiotics

Key Component Analysis of the Time Toxicity Interaction of Five Antibiotics to Q67

Antibiotics are considered as persistent emerging contaminants. The phenomenon of mixed exposure to the environment is a common occurrence causing serious harm to human health and the environment. Therefore, we employed enrofloxacin (ENR), chlortetracycline (CTC), methotrexate (TMP), chloramphenicol (CMP), and erythromycin (ETM) in this study. Nine treatments were designed using the uniform design concentration ratio (UDCR) method to systematically determine the toxicity of individual contaminants and their mixtures on Vibrio qinghaiensis sp.-Q67 through the time-dependent microplate toxicity assay. The combinatorial index (CI) method and the dose reduction index (DRI) were used to analyze the toxic interactions of the mixtures and the magnitude of the contribution of each component to the toxic interactions. The results showed that the toxicities of ENR, CTC, TMR, CMP, and ETM and their mixtures were time-dependent, with toxic effects being enhanced except when exposure time was prolonged. The types of toxic interactions in the ENR-CTC-TMR-CMP-ETM mixtures were found to be correlated with the proportion of each component's concentration, where the proportion of the components exerted the most significant influence. Through DRI extrapolation, it was determined that the primary components of the mixture exhibited a pronounced dependency on time. Specifically, at the 4 h mark, TMP emerged as the predominant component, gradually giving way to ENR as time advanced. Upon analyzing the frequency of mixture interactions under specified effects, the additive effect appeared most frequently (66.6%), while the antagonist effect appeared the least frequently (15.9%) among the nine rays.

Application of in vitro bioassays to monitor pharmaceuticals in water: A synthesis of chronological analysis, mode of action, and practical insights

Pharmaceutical compounds in wastewater have emerged as a significant concern for the aquatic environment. The use of in vitro bioassays represents a sustainable and cost-effective approach for assessing the potential toxicological risks of these biologically active compounds in wastewater and aligns with ethical considerations in research. It facilitates high-throughput analysis, captures mixture effects, integrates impacts of both known and unknown chemicals, and reduces reliance on animal testing. The core aim of the current review was to explore the practical application of in vitro bioassays in evaluating the environmental impacts of pharmaceuticals in wastewater. This comprehensive review strives to achieve several key objectives. First, it provides a summary categorisation of pharmaceuticals based on their mode of action, providing a structured framework for understanding their ecological significance. Second, a chronological analysis of pharmaceutical research aims to document their prevalence and trends over time, shedding light on evolving environmental challenges. Third, the review critically analyses existing bioassay applications in wastewater, while also examining bioassay coverage of representative compounds within major pharmaceutical classes. Finally, it explores the potential for developing innovative bioassays tailored for water quality monitoring of pharmaceuticals, paving the way for more robust environmental monitoring and risk assessment. Overall, adopting effect-based methods for pharmaceutical monitoring in water holds significant promise. It encompasses a broad spectrum of biological impacts, promotes standardized protocols, and supports a bioassay test battery approach indicative of different endpoints, thereby enhancing the effectiveness of environmental risk assessment.

Modeling mixtures interactions in environmental toxicology

In the environment, organisms are exposed to mixtures of different toxicants, which may interact in ways that are difficult to predict when only considering each component individually. Adapting and expanding tools from pharmacology, the toxicology field uses analytical, graphical, and computational methods to identify and quantify interactions in multi-component mixtures. The two general frameworks are concentration addition, where components have similar modes of action and their effects sum together, or independent action, where components have dissimilar modes of action and do not interact. Other interaction behaviors include synergism and antagonism, where the combined effects are more or less than the additive sum of individual effects. This review covers foundational theory, methods, an in-depth survey of original research from the past 20 years, current trends, and future directions. As humans and ecosystems are exposed to increasingly complex mixtures of environmental contaminants, analyzing mixtures interactions will continue to become a more critical aspect of toxicological research.

Enantioselectivity in ecotoxicity of pharmaceuticals, illicit drugs, and industrial persistent pollutants in aquatic and terrestrial environments: A review

At present, there is a serious concern about the alarming number of recalcitrant contaminants that can negatively affect biodiversity threatening the ecological status of marine, estuarine, freshwater, and terrestrial ecosystems (e.g., agricultural soils and forests). Contaminants of emerging concern (CEC) such as pharmaceuticals (PHAR), illicit drugs (ID), industrial persistent pollutants, such as polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) and chiral ionic solvents are globally spread and potentially toxic to non-target organisms. More than half of these contaminants are chiral and have been measured at different enantiomeric proportions in diverse ecosystems. Enantiomers can exhibit different toxicodynamics and toxicokinetics, and thus, can cause different toxic effects. Therefore, the enantiomeric distribution in occurrence cannot be neglected as the toxicity and other adverse biological effects are expected to be enantioselective. Hence, this review aims to reinforce the recognition of the stereochemistry in environmental risk assessment (ERA) of chiral CEC and gather up-to-date information about the current knowledge regarding the enantioselectivity in ecotoxicity of PHAR, ID, persistent pollutants (PCBs and PBDEs) and chiral ionic solvents present in freshwater and agricultural soil ecosystems. We performed an online literature search to obtain state-of-the-art research about enantioselective studies available for assessing the impact of these classes of CEC. Ecotoxicity assays have been carried out using organisms belonging to different trophic levels such as microorganisms, plants, invertebrates, and vertebrates, and considering ecologically relevant aquatic and terrestrial species or models organisms recommended by regulatory entities. A battery of ecotoxicity assays was also reported encompassing standard acute toxicity to sub-chronic and chronic assays and different endpoints as biomarkers of toxicity (e.g., biochemical, morphological alterations, reproduction, behavior, etc.). Nevertheless, we call attention to the lack of knowledge about the potential enantioselective toxicity of many PHAR, ID, and several classes of industrial compounds. Additionally, several questions regarding key species, selection of most appropriate toxicological assays and ERA of chiral CEC are addressed and critically discussed.

Using membrane-water partition coefficients in a critical membrane burden approach to aid the identification of neutral and ionizable chemicals that induce acute toxicity below narcosis levels

The risk assessment of thousands of chemicals used in our society benefits from adequate grouping of chemicals based on the mode and mechanism of toxic action (MoA). We measure the phospholipid membrane-water distribution ratio (D_MLW) using a chromatographic assay (IAM-HPLC) for 121 neutral and ionized organic chemicals and screen other methods to derive D_MLW. We use IAM-HPLC based D_MLW as a chemical property to distinguish between baseline narcosis and specific MoA, for reported acute toxicity endpoints on two separate sets of chemicals. The first set comprised 94 chemicals of US EPA's acute fish toxicity database: 47 categorized as narcosis MoA, 27 with specific MoA, and 20 predominantly ionic chemicals with mostly unknown MoA. The narcosis MoA chemicals clustered around the median narcosis critical membrane burden (CMB_narc) of 140 mmol kg^-1 lipid, with a lower limit of 14 mmol kg^-1 lipid, including all chemicals labelled Narcosis_I and Narcosis_II. This maximum 'toxic ratio' (TR) between CMB_narc and the lower limit narcosis endpoint is thus 10. For 23/28 specific MoA chemicals a TR >10 was derived, indicative of a specific adverse effect pathway related to acute toxicity. For 10/12 cations categorized as "unsure amines", the TR <10 suggests that these affect fish via narcosis MoA. The second set comprised 29 herbicides, including 17 dissociated acids, and evaluated the TR for acute toxic effect concentrations to likely sensitive aquatic plant species (green algae and macrophytes Lemna and Myriophyllum), and non-target animal species (invertebrates and fish). For 21/29 herbicides, a TR >10 indicated a specific toxic mode of action other than narcosis for at least one of these aquatic primary producers. Fish and invertebrate TRs were mostly <10, particularly for neutral herbicides, but for acidic herbicides a TR >10 indicated specific adverse effects in non-target animals. The established critical membrane approach to derive the TR provides for useful contribution to the weight of evidence to bin a chemical as having a narcosis MoA or less likely to have acute toxicity caused by a more specific adverse effect pathway. After proper calibration, the chromatographic assay provides consistent and efficient experimental input for both neutral and ionizable chemicals to this approach.

Comprehensive analysis of the fates and risks of veterinary antibiotics in a small ecosystem comprising a pig farm and its surroundings in Northeast China

This study investigated the behavior of veterinary antibiotics (VAs) in a small farm ecosystem. Manure and environmental samples were collected around a large pig farm in northeast China. Thirty-four VAs in six categories were analyzed. Then, a multimedia fugacity model was used to estimate the fates of VAs in the environment. The results showed that VAs were prevalent in manure, soil, water, and sediment, but not in crops. Compared with fresh manure, VA levels were significantly lower in surface manure piles left in the open air for 3-6 months. The main VAs, tetracyclines and quinolones, decreased by 427.12 and 158.45 µg/kg, respectively. VAs from manure piles were transported to the surroundings and migrated vertically into deep soil. The concentrations of ∑VAs detected in agricultural soils were 0.03-4.60 µg/kg; > 94% of the mass inventory of the VAs was retained in soil organic matter (SOM), suggesting that SOM is the main reservoir for antibiotics in soil. Risk assessment and model analysis indicated that the negative impact of mixed antibiotics at low concentrations in farmland on crops may be mediated by indirect effects, rather than direct effects. Our findings highlight the environmental fates and risks of antibiotics from livestock farms.

Experimental validation of stability and applicability of Start Growth Time method for high-throughput bacterial ecotoxicity assessment

Ecotoxicity assessments based on bacteria as model organisms are widely used for routine toxicity screening because it has the advantages of time-saving, high sensitivity, cost-effectiveness, and less ethical responsibility. Determination of ecotoxicity effect via bacterial growth can avoid the restriction of model bacteria selection and unique equipment requirements, but traditional viable cell count methods are relatively labor- and time-intensive. The Start Growth Time method (SGT) is a high-throughput and time-conserving method to determine the amount of viable bacterial cells. However, its usability and stability for ecotoxicity assessment are rarely studied. This study confirmed its applicability in terms of bacterial types (gram-positive and gram-negative), growth phases (middle exponential and early stationary phases), and simultaneous existence of dead cells (adjustment by flow cytometry). Our results verified that the stability of establishing SGT correlation is independent of the bacterial type and dead-cell portion. Moreover, we only observed the effect of growth phases on the slope value of established SGT correlation in Shewanella oneidensis, which suggests that preparing inoculum for the SGT method should be consistent in keeping its stability. Our results also elucidate that the SGT values and the live cell percentages meet the non-linear exponential correlation with high correlation coefficients from 0.97 to 0.99 for all the examined bacteria. The non-linear exponential correlation facilitates the application of the SGT method in the ecotoxicity assessment. Finally, applying the exponential SGT correlation to evaluate the ecotoxicity effect of copper ions on E. coli was experimentally validated. The SGT-based method would require about 6 to 7 h to finish the assessment and obtain an estimated EC₅₀ at 2.27 ± 0.04 mM. This study demonstrates that the exponential SGT correlation can be a high-throughput, time-conversing, and wide-applicable method for bacterial ecotoxicity assessment.

Impacts of the COVID-19 pandemic on pharmaceuticals in wastewater treated for beneficial reuse: Two case studies in central Pennsylvania

During the COVID-19 pandemic, wastewater surveillance was leveraged as a powerful tool for monitoring community-scale health. Further, the well-known persistence of some pharmaceuticals through wastewater treatment plants spurred concerns that increased usage of pharmaceuticals during the pandemic would increase the concentrations in wastewater treatment plant effluent. We collected weekly influent and effluent samples from May 2020 through May 2021 from two wastewater treatment plants in central Pennsylvania, the Penn State Water Reclamation Facility and the University Area Joint Authority, that provide effluent for beneficial reuse, including for irrigation. Samples were analyzed for severe acute respiratory syndrome coronavirus 2 (influent only), two over-the-counter medicines (acetaminophen and naproxen), five antibiotics (ampicillin, doxycycline, ofloxacin, sulfamethoxazole, and trimethoprim), two therapeutic agents (remdesivir and dexamethasone), and hydroxychloroquine. Although there were no correlations between pharmaceutical and virus concentration, remdesivir detection occurred when the number of hospitalized patients with COVID-19 increased, and dexamethasone detection co-occurred with the presence of patients with COVID-19 on ventilators. Additionally, Penn State decision-making regarding instruction modes explained the temporal variation of influent pharmaceutical concentrations, with detection occurring primarily when students were on campus. Risk quotients calculated for pharmaceuticals with known effective and lethal concentrations at which 50% of a population is affected for fish, daphnia, and algae were generally low in the effluent; however, some acute risks from sulfamethoxazole were high when students returned to campus. Remdesivir and dexamethasone persisted through the wastewater treatment plants, thereby introducing novel pharmaceuticals directly to soils and surface water. These results highlight connections between human health and water quality and further demonstrate the broad utility of wastewater surveillance.

Environmental health and risk assessment metrics with special mention to biotransfer, bioaccumulation and biomagnification of environmental pollutants

The environment pollutants, which are landed up in environment because of human activities like urbanization, mining and industrializations, affects human health, plants and animals. The living organisms present in environment are constantly affected by the toxic pollutants through direct contact or bioaccumulation of chemicals from the environment. The toxic and hazardous pollutants are easily transferred to different environmental matrices like land, air and water bodies such as surface and ground waters. This comprehensive review deeply discusses the routes and causes of different environmental pollutants along with their toxicity, impact, occurrences and fate in the environment. Environment health and risk assessment tools that are used to evaluate the harmfulness, exposure of living organisms to pollutants and the amount of pollutant accumulated are explained with help of bio-kinetic models. Biotransfer, toxicity factor, biomagnification and bioaccumulation of different pollutants in the air, water and marine ecosystems are critically addressed. Thus, the presented survey would be collection of correlations those addresses the factors involved in assessing the environmental health and risk impacts of distinct environmental pollutants.

Mixture toxicity of six pharmaceuticals towards Aliivibrio fischeri, Daphnia magna, and Lemna minor

As the knowledge on the joint effects of pharmaceuticals towards different non-target organisms is still limited, the aim of our study was to evaluate the toxicity of mixtures of pharmaceuticals, as well as their baseline toxicity towards three selected organisms, namely the bioluminescent bacteria Aliivibrio fischeri, the crustacean Daphnia magna, and the duckweed Lemna minor. Different mixtures composed of three up to five pharmaceuticals having the same or different mechanisms of action in terms of their therapeutic activity (non-steroidal anti-inflammatory drugs, opioid analgesic, antibacterial and anti-epileptic drugs) were investigated. The observed EC₅₀s were compared with those predicted using the concentration addition (CA) and independent action (IA) models. In general, the EC₅₀ values for mixtures predicted with the CA model were lower than those obtained with the IA model, although, in some cases, test predictions of these two models were almost identical. Most of the experimentally determined EC₅₀ values for the specific mixtures were slightly higher than those predicted with the CA model; hence, a less than additive effect was noted. Based on the obtained results, it might be concluded that the CA model assumes the worst-case scenario and gives overall closer predictions; therefore, it should be recommended also for modeling the mixture toxicity of pharmaceuticals with different modes of action.

Development of a high-throughput bioassay for screening of antibiotics in aquatic environmental samples

The goal of the present study was to select a Gram-positive (Gram+) and Gram-negative (Gram-) strain to measure antimicrobial activity in environmental samples, allowing high-throughput environmental screening. The sensitivity of eight pre-selected bacterial strains were tested to a training set of ten antibiotics, i.e. three Gram+ Bacillus subtilis strains with different read-outs, and five Gram- strains. The latter group consisted of a bioluminescent Allivibrio fischeri strain and four Escherichia coli strains, i.e. a wild type (WT) and three strains with a modified cell envelope to increase their sensitivity. The WT B. subtilis and an E. coli strain newly developed in this study, were most sensitive to the training set. This E. coli strain carries an open variant of an outer membrane protein combined with an inactivated multidrug efflux transport system. The assay conditions of these two strains were optimized and validated by exposure to a validation set of thirteen antibiotics with clinical and environmental relevance. The assay sensitivity ranged from the ng/mL to μg/mL range. The applicability of the assays for toxicological characterization of aquatic environmental samples was demonstrated for hospital effluent extract. A future application includes effect-directed analysis to identify yet unknown antibiotic contaminants or their transformation products.

MOA-based linear and nonlinear QSAR models for predicting the toxicity of organic chemicals to Vibrio fischeri

Risk assessment of pollutants to humans and ecosystems requires much toxicological data. However, experimental testing of compounds expends a large number of animals and is criticized for ethical reasons. The in silico method is playing an important role in filling the data gap. In this paper, the acute toxicity data of 1221 chemicals to Vibrio fischeri were collected. The global models obtained showed that there was a poor relationship between the toxicity data and the descriptors calculated based on linear and nonlinear regression analysis. This is due to the fact that the studied compounds contain not only non-reactive compounds but also reactive and specifically acting compounds with different modes of action (MOAs). MOAs are fundamental for the development of mechanistically based QSAR models and toxicity prediction. To investigate MOAs and develop MOA-based prediction models, the compounds were classified into baseline, less inert, reactive, and specifically acting compounds based on the modified Verhaar's classification scheme. Satisfactory models were established by multivariate linear regression (MLR) and support vector machine (SVM) analysis not only for baseline and less inert chemicals, but also for reactive and specifically acting compounds. Compared with linear models obtained by the MLR method, the nonlinear models obtained by the SVM method had better performance. The cross validation proved that all of the models were robust except for those for reactive chemicals with nN (number of nitrogen atoms) = 0 and n(C=O) (number of carbonyl groups) > 0 (Q²_ext < 0.5). The application domains and outliers are discussed for those MOA-based models. The models developed in this paper are significantly helpful not only because the application domains for baseline and less inert compounds have been expended, but also the toxicity of reactive and specifically acting compounds can be successfully predicted. This work will promote understanding of toxic mechanisms and toxicity prediction for the chemicals with structural diversity, especially for reactive and specifically acting compounds.

Evaluating the enantiospecific differences of non-steroidal anti-inflammatory drugs (NSAIDs) using an ecotoxicity bioassay test battery

Wastewater treatment plants are a major pathway for pharmaceuticals to the aquatic environment. Many pharmaceuticals, including non-steroidal anti-inflammatory drugs (NSAIDs), are chiral chemicals and the biological activity of their enantiomers can differ. Few studies have assessed the effects of different NSAID enantiomers on non-target organisms. However, this information is important for environmental risk assessment to ensure that the effects of more potent enantiomers are not overlooked. In the current study, enantiomers of naproxen, ibuprofen, ketoprofen and flurbiprofen were evaluated in bioassays with bacteria, algae and fish cells. All enantiomers induced bacterial toxicity, with (R)-naproxen more toxic than (S)-naproxen (EC₅₀ 0.75 vs 0.93 mg/L) and (S)-flurbiprofen more toxic than (R)-flurbiprofen (EC₅₀ 1.22 vs 2.13 mg/L). Both (R)-flurbiprofen and (S)-flurbiprofen induced photosystem II inhibition in green algae, with (R)-flurbiprofen having a greater effect in the assay after 24 h (EC₁₀ 5.47 vs 9.07 mg/L). Only the (R)-enantiomers of flurbiprofen and ketoprofen induced ethoxyresorufin-O-deethylase (EROD) activity in fish cells, while (S)-naproxen was 2.5 times more active than (R)-naproxen in the EROD assay. While enantiospecific differences were observed for all assays, the difference was less than an order of magnitude. This indicates that the risk of overlooking the effect of more potent NSAID enantiomers is minor for the studied test systems and supports the use of racemic (or single enantiomer) effect data for environmental risk assessment. However, further investigation of the (R)-enantiomer of commonly used NSAID ketoprofen is recommended as it was at least six times more potent in the EROD assay than the inactive (S)-ketoprofen.

Soil contamination with antibiotics in a typical peri-urban area in eastern China: Seasonal variation, risk assessment, and microbial responses

The prevalence and persistence of antibiotics in soils has become an emerging environmental issue and an increasing threat to soil security and global public health. The problem is more severe in areas undergoing rapid urbanization; however, the ecological risks of antibiotics, seasonal variability, and associated soil microbial responses in peri-urban soils have not been well-explored. The seasonal soil sampling campaigns were conducted in a typical peri-urban watershed in eastern China to investigate distribution of antibiotics. The results demonstrated higher mean concentrations of most antibiotic compounds in winter than in summer in peri-urban soils. The seasonal variations of norfloxacin, enrofloxacin, and ciprofloxacin were more significant than those of other antibiotics, due to their higher migration ability and bioavailability. An ecological risk assessment demonstrated that chlortetracycline, ciprofloxacin, doxycycline, and ofloxacin can pose high risks to soil microorganisms. Furthermore, the coexistence of multiple antibiotics obviously poses higher risks than individual compounds. A redundancy analysis demonstrated that tetracyclines mainly showed negative correlations with Firmicutes and Chloroflexi, and quinolones showed obviously negative correlations with Acidobacteria, Gemmatimonadetes, and Nitrospirae, suggesting potential inhibition from antibiotics on biological activities or biodegradation processes. However, the persistence of antibiotics in soil results in a significant decrease in bacterial diversity and a change in dominant species. Our results provide an overview of the seasonal variability of antibiotics and the associated effects on bacterial communities in peri-urban soils. The results can provide scientific guidance on decreasing soil contamination with antibiotics to enhance soil security in similar areas.

Polyethylene glycol 400 significantly enhances the stimulation of 2-phenoxyethanol on Vibrio qinghaiensis sp.-Q67 bioluminescence

Previous studies demonstrated long-term stimulation of some commercial personal care products (PCPs) on freshwater luminescent bacteria Vibrio qinghaiensis sp.-Q67 (Q67). However, whether a certain component can affect mixture's hormetic effect is still unknown. In this paper, two of ingredients in PCPs, 2-phenoxyethanol (PhE) and polyethylene glycol 400 (PEG400), were selected as object compounds to explore the relationship between concentration-response (CR) of mixtures and that of a single component. It was found that PEG400 has monotonic CR (MCR) on Q67 both at the short-term (0.25 h) and long-term (12 h) exposures while PhE has MCR at 0.25 h and hormetic CR (HCR) at 12 h. Here, the concentration-response curves (CRCs) of PEG400 at 0.25 and 12 h are overlapped each other and the CRCs of PEG400 are on the right of PhE. If the pEC₅₀ is taken as a toxic index, the toxicities of PEG400 at two times are basically the same, and those of PhE are the same, too, but PhE is twice as toxic as PEG400. For the mixtures of PEG400 and PhE, all rays except R1 have MCRs at 0.25 h while all rays have HCRs at 12 h where the higher the mixture ratio of PhE is, the more negative the maximum stimulation effect is. More importantly, the E_min values of all rays are more negative (1.79-3.17-fold) than that of PhE worked alone, which implies that the introduction of PEG400 significantly enhances stimulative effect of PhE. At 0.25 h, all binary mixture rays but R1 produce a low-concentration additive action and high-concentration synergism. At 12 h, all rays display additive action, antagonism, additive action, and synergism in turn when the concentration changes from low to high. The overall findings suggested toxicological interactions should be considered in the risk assessment of PCPs and their potential impacts on ecological balances.

Toxicological interaction of multi-component mixtures to Vibrio qinghaiensis sp.-Q67 induced by at least three components

It has been stated by researchers that the antibiotic polymyxin B sulfate (POL) is a key component inducing time-dependent antagonism in freshwater luminescent bacteria, Vibrio qinghaiensis sp.-Q67, exposed in the ternary mixture system of the ionic liquids, pesticide and antibiotics. However, the previous statement is limited to ternary and quaternary mixtures without considering situations such as the binary system. In order to prove the direct inducing of antagonism by POL in a more complete and systematic way, two categories of experiments (adding POL in non-antagonistic ternary system and decomposing antagonistic ternary system with POL into the binary system) have been conducted in this paper. The results showed that quaternary mixture systems (adding POL to non-antagonism ternary mixture, up verification) exhibit antagonistic action in a majority of rays, at some point in the experiment. However, by decomposing the antagonistic ternary mixtures with POL into binary mixtures (down verification), the combined toxicities of binary mixtures at all time points in the experiment are additive. Obviously, the POL has a significant contribution to antagonism only in the ternary and quaternary mixtures, but not in the binary mixtures. We can draw a new conclusion that the antagonism of the multi-component mixtures is induced by at least three components (including POL), with complex chemical interactions. Therefore, considering POL's influence of antagonism as an example, future environmental protection practitioners and academic researchers should construct more scenarios of mixtures when assessing the influences and reactions of certain chemicals causing pollutions.

Antimicrobial activity of pharmaceutical cocktails in sewage treatment plant effluent - An experimental and predictive approach to mixture risk assessment

Municipal wastewater contains multi-component mixtures of active pharmaceutical ingredients (APIs). This could shape microbial communities in sewage treatment plants (STPs) and the effluent-receiving ecosystems. In this paper we assess the risk of antimicrobial effects in STPs and the aquatic environment for a mixture of 18 APIs that was previously detected in the effluent of a European municipal STP. Effects on microbial consortia (collected from a separate STP) were determined using respirometry, enumeration of culturable microorganisms and community-level physiological profiling. The mixture toxicity against selected bacteria was assessed using assays with Pseudomonas putida and Vibrio fischeri. Additional data on the toxicity to environmental bacteria were compiled from literature in order to assess the individual and expected joint bacterial toxicity of the pharmaceuticals in the mixture. The reported effluent concentration of the mixture was 15.4 nmol/l and the lowest experimentally obtained effect concentrations (EC₁₀) were 242 nmol/l for microbial consortia in STPs, 225 nmol/l for P. putida and 73 nmol/l for V. fischeri. The lowest published effect concentrations (EC₅₀) of the individual antibiotics in the mixture range between 15 and 150 nmol/l, whereas 0.9-190 μmol/l was the range of bacterial EC₅₀ values found for the non-antibiotic mixture components. Pharmaceutical cocktails could shape microbial communities at concentrations relevant to STPs and the effluent receiving aquatic environment. The risk of antimicrobial mixture effects was completely dominated by the presence of antibiotics, whereas other pharmaceutical classes contributed only negligibly to the mixture toxicity. The joint bacterial toxicity can be accurately predicted from the individual toxicity of the mixture components, provided that standardized data on representative bacterial strains becomes available for all relevant compounds. These findings argue for a more sophisticated bacterial toxicity assessment of environmentally relevant pharmaceuticals, especially for those with a mode of action that is known to specifically affect prokaryotic microorganisms.

General baseline toxicity QSAR for nonpolar, polar and ionisable chemicals and their mixtures in the bioluminescence inhibition assay with Aliivibrio fischeri

The Microtox assay, a bioluminescence inhibition assay with the marine bacterium Aliivibrio fischeri, is one of the most popular bioassays for assessing the cytotoxicity of organic chemicals, mixtures and environmental samples. Most environmental chemicals act as baseline toxicants in this short-term screening assay, which is typically run with only 30 min of exposure duration. Numerous Quantitative Structure-Activity Relationships (QSARs) exist for the Microtox assay for nonpolar and polar narcosis. However, typical water pollutants, which have highly diverse structures covering a wide range of hydrophobicity and speciation from neutral to anionic and cationic, are often outside the applicability domain of these QSARs. To include all types of environmentally relevant organic pollutants we developed a general baseline toxicity QSAR using liposome-water distribution ratios as descriptors. Previous limitations in availability of experimental liposome-water partition constants were overcome by reliable prediction models based on polyparameter linear free energy relationships for neutral chemicals and the COSMOmic model for charged chemicals. With this QSAR and targeted mixture experiments we could demonstrate that ionisable chemicals fall in the applicability domain. Most investigated water pollutants acted as baseline toxicants in this bioassay, with the few outliers identified as uncouplers or reactive toxicants. The main limitation of the Microtox assay is that chemicals with a high melting point and/or high hydrophobicity were outside of the applicability domain because of their low water solubility. We quantitatively derived a solubility cut-off but also demonstrated with mixture experiments that chemicals inactive on their own can contribute to mixture toxicity, which is highly relevant for complex environmental mixtures, where these chemicals may be present at concentrations below the solubility cut-off.