Identifying Functional Groups that Determine Rates of Micropollutant Biotransformations Performed by Wastewater Microbial Communities

Recovery mechanism of a microalgal species, Chlorella sp. from toxicity of doxylamine: Physiological and biochemical changes, and transcriptomics

Ubiquitous distribution of pharmaceutical contaminants in environment has caused unexpected adverse effects on ecological organisms; however, how microorganisms recover from their toxicities remains largely unknown. In this study, we comprehensively investigated the effect of a representative pollutant, doxylamine (DOX) on a freshwater microalgal species, Chlorella sp. by analyzing the growth patterns, biochemical changes (total chlorophyll, carotenoid, carbohydrate, protein, and antioxidant enzymes), and transcriptomics. We found toxicity of DOX on Chlorella sp. was mainly caused by disrupting synthesis of ribosomes in nucleolus, and r/t RNA binding and processing. Intriguingly, additional bicarbonate enhanced the toxicity of DOX with decreasing the half-maximum effective concentrations from 15.34 mg L-1 to 4.63 mg L-1, which can be caused by inhibiting fatty acid oxidation and amino acid metabolism. Microalgal cells can recover from this stress via upregulating antioxidant enzymatic activities to neutralize oxidative stresses, and photosynthetic pathways and nitrogen metabolism to supply more energies and cellular signaling molecules. This study extended our understanding on how microalgae can recover from chemical toxicity, and also emphasized the effect of environmental factors on the toxicity of these contaminants on aquatic microorganisms.

Loss of micropollutants on syringe filters during sample filtration: Machine learning approach for selecting appropriate filters

Prefiltration before chromatographic analysis is critical in the monitoring of environmental micropollutants (MPs). However, in an aqueous matrix, such monitoring often leads to out-of-specification results owing to the loss of MPs on syringe filters. Therefore, this study investigated the loss of seventy MPs on eight different syringe filters by employing Random Forest, a machine learning algorithm. The results indicate that the loss of MPs during filtration is filter specific, with glass microfiber and polytetrafluoroethylene filters being the most effective (<20%) compared with nylon (>90%) and others (regenerated-cellulose, polyethersulfone, polyvinylidene difluoride, cellulose acetate, and polypropylene). The Random Forest classifier showed outstanding performance (accuracy range 0.81-0.95) for determining whether the loss of MPs on filters exceeded 20%. Important factors in this classification were analyzed using the SHapley Additive exPlanation value and Kruskal-Wallis test. The results show that the physicochemical properties (LogKow/LogD, pKa, functional groups, and charges) of MPs are more important than the operational parameters (sample volume, filter pore size, diameter, and flow rate) in determining the loss of most MPs on syringe filters. However, other important factors such as the implications of the roles of pH for nylon and pre-rinsing for PTFE syringe filters should not be ignored. Overall, this study provides a systematic framework for understanding the behavior of various MP classes and their potential losses on syringe filters.

Deciphering the role of extracellular polymeric substances in the adsorption and biotransformation of organic micropollutants during anaerobic wastewater treatment

Extracellular polymeric substances (EPS) participate in the removal of organic micropollutants (OMPs), but the primary pathways of removal and detailed mechanisms remain elusive. We evaluated the effect of EPS on removal for 16 distinct chemical classes of OMPs during anaerobic digestion (AD). The results showed that hydrophobic OMPs (HBOMPs) could not be removed by EPS, while hydrophilic OMPs (HLOMPs) were amenable to removal via adsorption and biotransformation of EPS. The adsorption and biotransformation of HLOMPs by EPS accounted up to 19.4 ± 0.9 % and 6.0 ± 0.8 % of total removal, respectively. Further investigations into the adsorption and biotransformation mechanisms of HLOMPs by EPS were conducted utilizing spectral, molecular dynamics simulation, and electrochemical analysis. The results suggested that EPS provided abundant binding sites for the adsorption of HLOMPs. The binding of HLOMPs to tryptophan-like proteins in EPS formed nonfluorescent complexes. Hydrogen bonds, hydrophobic interactions and water bridges were key to the binding processes and helped stabilize the complexes. The biotransformation of HLOMPs by EPS may be attributed to the presence of extracellular redox active components (c-type cytochromes (c-Cyts), c-Cyts-bound flavins). This study enhanced the comprehension for the role of EPS on the OMPs removal in anaerobic wastewater treatment.

Influence of Season on Biodegradation Rates in Rivers

Biodegradation plays a key role in the fate of chemicals in the environment. The variability of biodegradation in time can cause uncertainty in evaluating the environmental persistence and risk of chemicals. However, the seasonality of biodegradation in rivers has not yet been the subject of environmentally relevant testing and systematic investigation for large numbers of chemicals. In this work, we studied the biodegradation of 96 compounds during four seasons at four locations (up- and downstream of WWTPs located on two Swedish rivers). Significant seasonality (ANOVA, p < 0.05) of the first-order rate constant for primary biodegradation was observed for most compounds. Variations in pH and total bacterial cell count were not the major factors explaining the seasonality of biodegradation. Deviation from the classical Arrhenius-type behavior was observed for most of the studied compounds, which calls into question the application of this relationship to correct biodegradation rate constants for differences in environmental temperature. Similarities in magnitude and seasonality of biodegradation rate constants were observed for some groups of chemicals possessing the same functional groups. Moreover, reduced seasonality of biodegradation was observed downstream of WWTPs, while biodegradation rates of most compounds were not significantly different between up- and downstream.

Quantitative identification of the co-exposure effects of e-waste pollutants on human oxidative stress by explainable machine learning

Global electronic waste (e-waste) generation continues to grow. The various pollutants released during precarious e-waste disposal activities can contribute to human oxidative stress. This study encompassed 129 individuals residing near e-waste dismantling sites in China, with elevated urinary concentrations of e-waste-related pollutants including heavy metals, polycyclic aromatic hydrocarbons (PAHs), organophosphorus flame retardants (OPFRs), bisphenols (BPs), and phthalate esters (PAEs). Utilizing an explainable machine learning framework, the study quantified the co-exposure effects of these pollutants, finding that approximately 23% and 18% of the variance in oxidative DNA damage and lipid peroxidation, respectively, was attributable to these substances. Heavy metals emerged as the most critical factor in inducing oxidative stress, followed by PAHs and PAEs for oxidative DNA damage, and BPs, OPFRs, and PAEs for lipid peroxidation. The interactions between different pollutant classes were found to be weak, attributable to their disparate biological pathways. In contrast, the interactions among congeneric pollutants were strong, stemming from their shared pathways and resultant synergistic or additive effects on oxidative stress. An intelligent analysis system for e-waste pollutants was also developed, which enables more efficient processing of large-scale and dynamic datasets in evolving environments. This study offered an enticing peek into the intricacies of co-exposure effect of e-waste pollutants.

Hydrolysis of Antimicrobial Peptides by Extracellular Peptidases in Wastewater

Several antimicrobial peptides (AMPs) are emerging as promising novel antibiotics. When released into wastewater streams after use, AMPs might be hydrolyzed and inactivated by wastewater peptidases─resulting in a reduced release of active antimicrobials into wastewater-receiving environments. A key step towards a better understanding of the fate of AMPs in wastewater systems is to investigate the activity and specificity of wastewater peptidases. Here, we quantified peptidase activity in extracellular extracts from different stages throughout the wastewater treatment process. For all four tested municipal wastewater treatment plants, we detected highest activity in raw wastewater. Complementarily, we assessed the potential of enzymes in raw wastewater extracts to biotransform 10 selected AMPs. We found large variations in the susceptibility of AMPs to enzymatic transformation, indicating substantial substrate specificity of extracted enzymes. To obtain insights into peptidase specificities, we searched for hydrolysis products of rapidly biotransformed AMPs and quantified selected products using synthetic standards. We found that hydrolysis occurred at specific sites and that these sites were remarkably conserved across the four tested wastewaters. Together, these findings provide insights into the fate of AMPs in wastewater systems and can inform the selection and design of peptide-based antibiotics that are hydrolyzable by wastewater peptidases.

Suspect and Nontarget Screening Reveal the Underestimated Risks of Antibiotic Transformation Products in Wastewater Treatment Plant Effluents

Antibiotics are anthropogenic contaminants with a global presence and of deep concern in aquatic environments, while less is known about the occurrence and risks of their transformation products (TPs). Herein, we developed a comprehensive suspect and nontarget screening workflow based on high-resolution mass spectrometry to identify unknown antibiotic TPs in wastewater treatment plant effluents. We identified 211 compounds (35 parent antibiotics and 176 TPs) at confidence levels of ≥3 and 107 TPs originated from macrolides. TPs were quantified by 17 TPs standards and semiquantified by the predicted response factors and accounted for 55.6-95.1% (76.7% on average) of the total concentrations of parents and TPs. 22.2%, 63.1%, and 18.8% of the identified TPs were estimated to be more persistent, mobile, and toxic than their parent antibiotics, respectively. Further ecological risk assessment based on concentrations and toxicity to aquatic organisms revealed that the cumulative risks of TPs were generally higher than those of parents. Despite the newly formed N-oxide TPs, the tertiary treatment process (mainly ozonation) could decrease the averaged 20.3% of concentrations and 36.2% of the risks of antibiotic-related compounds. This study highlights the necessity to include antibiotic TPs in environmental scrutiny and risk assessment of antibiotics in different aquatic environments.

Identification and Prioritization of Environmental Organic Pollutants: From an Analytical and Toxicological Perspective

Exposure to environmental organic pollutants has triggered significant ecological impacts and adverse health outcomes, which have been received substantial and increasing attention. The contribution of unidentified chemical components is considered as the most significant knowledge gap in understanding the combined effects of pollutant mixtures. To address this issue, remarkable analytical breakthroughs have recently been made. In this review, the basic principles on recognition of environmental organic pollutants are overviewed. Complementary analytical methodologies (i.e., quantitative structure-activity relationship prediction, mass spectrometric nontarget screening, and effect-directed analysis) and experimental platforms are briefly described. The stages of technique development and/or essential parts of the analytical workflow for each of the methodologies are then reviewed. Finally, plausible technique paths and applications of the future nontarget screening methods, interdisciplinary techniques for achieving toxicant identification, and burgeoning strategies on risk assessment of chemical cocktails are discussed.

Combining predictive and analytical methods to elucidate pharmaceutical biotransformation in activated sludge

While man-made chemicals in the environment are ubiquitous and a potential threat to human health and ecosystem integrity, the environmental fate of chemical contaminants such as pharmaceuticals is often poorly understood. Biodegradation processes driven by microbial communities convert chemicals into transformation products (TPs) that may themselves have adverse ecological effects. The detection of TPs formed during biodegradation has been continuously improved thanks to the development of TP prediction algorithms and analytical workflows. Here, we contribute to this advance by (i) reviewing past applications of TP identification workflows, (ii) applying an updated workflow for TP prediction to 42 pharmaceuticals in biodegradation experiments with activated sludge, and (iii) benchmarking 5 different pathway prediction models, comprising 4 prediction models trained on different datasets provided by enviPath, and the state-of-the-art EAWAG pathway prediction system. Using the updated workflow, we could tentatively identify 79 transformation products for 31 pharmaceutical compounds. Compared to previous works, we have further automatized several steps that were previously performed by hand. By benchmarking the enviPath prediction system on experimental data, we demonstrate the usefulness of the pathway prediction tool to generate suspect lists for screening, and we propose new avenues to improve their accuracy. Moreover, we provide a well-documented workflow that can be (i) readily applied to detect transformation products in activated sludge and (ii) potentially extended to other environmental studies.

Experimental and numerical elucidation of the fate and transport of antibiotics in aquatic environment: A review

This review highlights various experimental and mathematical modeling strategies to investigate the fate and transport of antibiotics that elucidate antimicrobial selective pressure in aquatic environments. Globally, the residual antibiotic concentrations in effluents from bulk drug manufacturing industries were 30- and 1500-fold greater than values reported in municipal and hospital effluents, respectively. The antibiotic concentration from different effluents enters the waterbodies that usually get diluted as they go downstream and undergo various abiotic and biotic reactive processes. In aquatic systems, photolysis is the predominant process for antibiotic reduction in the water matrix, while hydrolysis and sorption are frequently reported in the sediment compartment. The rate of antibiotic reduction varies widely with influencing factors such as the chemical properties of the antibiotics and hydrodynamic conditions of river streams. Among all, tetracycline was found to more unstable (log Kow =  - 0.62 to - 1.12) that can readily undergo photolysis and hydrolysis; whereas macrolides were more stable (log Kow = 3.06 to 4.02) that are prone to biodegradation. The processes like photolysis, hydrolysis, and biodegradation followed first-order reaction kinetics while the sorption followed a second-order kinetics for most antibiotic classes with reaction rates occurring in the decreasing order of Fluoroquinolones and Sulphonamides. The reports from various experiments on abiotic and biotic processes serve as input parameters for an integrated mathematical modeling to predict the fate of the antibiotics in the aquatic environment. Various mathematical models viz. Fugacity level IV, RSEMM, OTIS, GREAT-ER, SWAT, QWASI, and STREAM-EU are discussed for their potential capabilities. However, these models do not account for microscale interactions of the antibiotics and microbial community under real-field conditions. Also, the seasonal variations for contaminant concentrations that exert selective pressure for antimicrobial resistance has not been accounted. Addressing these aspects collectively is the key to exploring the emergence of antimicrobial resistance. Therefore, a comprehensive model involving antimicrobial resistance parameters like fitness cost, bacterial population dynamics, conjugation transfer efficiency, etc. is required to predict the fate of antibiotics.

Revealing specific transformation pattern of sulfonamides during wastewater biological treatment processes by molecular networking nontarget screening

Biotransformation of emerging contaminants (ECs) is of importance in various natural and engineered systems to eliminate the adverse effects of ECs toward organisms. In wastewater, structurally similar ECs may transform through similar reactions triggered by common enzymes. However, the transformation pattern for them was scarcely studied. To fill the research gaps, five sulfonamides were chosen as the targeted ECs with similar structure to explore the transformation pattern in wastewater biological treatment experiments at lab scale. Through molecular networking based nontarget screening, 45 transformation products (TPs) of sulfonamides were identified and 14 of them were newly found. On the basis, five specific transformation patterns were summarized for sulfonamides by transformation pathways comparing, reaction frequency analyzing and dominant TPs comparing. Results suggested that pterin-chelation and formylation (dominant transformation pathway) and acetylation, methylation and deamination reactions were commonly occurred for sulfonamides in wastewater. Among them, the role of formylation as the dominant transformation pathway for sulfonamides transformed in wastewater was firstly reported in present study. Subsequent frontier molecular orbital calculation suggested the active site of amino (N₁H₂-) may contribute the specific transformation pattern of sulfonamides. Present study reveals the specific transformation pattern of sulfonamides from the aspect of TPs and transformation pathways. In the future, knowledge on the specific transformation pattern can be used to regulate and enhance the removal of a class of ECs with similar structure rather than just one of ECs.

Understanding the biodegradation pathways of azo dyes by immobilized white-rot fungus, Trametes hirsuta D7, using UPLC-PDA-FTICR MS supported by in silico simulations and toxicity assessment

No biodegradation methods are absolute in the treatment of all textile dyes, which leads to structure-dependent degradation. In this study, biodegradation of three azo dyes, reactive black 5 (RB5), acid blue 113 (AB113), and acid orange 7 (AO7), was investigated using an immobilized fungus, Trametes hirsuta D7. The degraded metabolites were identified using UPLC-PDA-FTICR MS and the biodegradation pathway followed was proposed. RB5 (92%) and AB113 (97%) were effectively degraded, whereas only 30% of AO7 was degraded. Molecular docking simulations were performed to determine the reason behind the poor degradation of AO7. Weak binding affinity, deficiency in H-bonding interactions, and the absence of interactions between the azo (-NN-) group and active residues of the model laccase enzyme were responsible for the low degradation efficiency of AO7. Furthermore, cytotoxicity and genotoxicity assays confirmed that the fungus-treated dye produced non-toxic metabolites. The observations of this study will be useful for understanding and further improving enzymatic dye biodegradation.

Uptake, Metabolism and Accumulation of Tire Wear Particle-Derived Compounds in Lettuce

Tire wear particle (TWP)-derived compounds may be of high concern to consumers when released in the root zone of edible plants. We exposed lettuce plants to the TWP-derived compounds diphenylguanidine (DPG), hexamethoxymethylmelamine (HMMM), benzothiazole (BTZ), N-phenyl-N'-(1,3-dimethylbutyl)-p-phenylenediamine (6PPD), and its quinone transformation product (6PPD-q) at concentrations of 1 mg L-1 in hydroponic solutions over 14 days to analyze if they are taken up and metabolized by the plants. Assuming that TWP may be a long-term source of TWP-derived compounds to plants, we further investigated the effect of leaching from TWP on the concentration of leachate compounds in lettuce leaves by adding constantly leaching TWP to the hydroponic solutions. Concentrations in leaves, roots, and nutrient solution were quantified by triple quadrupole mass spectrometry, and metabolites in the leaves were identified by Orbitrap high resolution mass spectrometry. This study demonstrates that TWP-derived compounds are readily taken up by lettuce with measured maximum leaf concentrations between ∼0.75 (6PPD) and 20 μg g-1 (HMMM). Although these compounds were metabolized in the plant, we identified several transformation products, most of which proved to be more stable in the lettuce leaves than the parent compounds. Furthermore, continuous leaching from TWP led to a resupply and replenishment of the metabolized compounds in the lettuce leaves. The stability of metabolized TWP-derived compounds with largely unknown toxicities is particularly concerning and is an important new aspect for the impact assessment of TWP in the environment.