Coupling pathway prediction and fluorescence spectroscopy to assess the impact of auxiliary substrates on micropollutant biodegradation.

Some bacteria can degrade organic micropollutants (OMPs) as primary carbon sources. Due to typically low OMP concentrations, these bacteria may benefit from supplemental assimilation of natural substrates present in the pool of dissolved organic matter (DOM). The biodegradability of such auxiliary substrates and the impacts on OMP removal are tightly linked to biotransformation pathways. Here, we aimed to elucidate the biodegradability and effect of different DOM constituents for the carbofuran degrader Novosphingobium sp. KN65.2, using a novel approach that combines pathway prediction, laboratory experiments, and fluorescence spectroscopy. Pathway prediction suggested that ring hydroxylation reactions catalysed by Rieske-type dioxygenases and flavin-dependent monooxygenases determine the transformability of the 11 aromatic compounds used as model DOM constituents. Our approach further identified two groups with distinct transformation mechanisms amongst the four growth-supporting compounds selected for mixed substrate biodegradation experiments with the pesticide carbofuran (Group 1: 4-hydroxybenzoic acid, 4-hydroxybenzaldehyde; Group 2: p-coumaric acid, ferulic acid). Carbofuran biodegradation kinetics were stable in the presence of both Group 1 and Group 2 auxiliary substrates. However, Group 2 substrates would be preferable for bioremediation processes, as they showed constant biodegradation kinetics under different experimental conditions (pre-growing KN65.2 on carbofuran vs. DOM constituent). Furthermore, Group 2 substrates were utilisable by KN65.2 in the presence of a competitor (Pseudomonas fluorescens sp. P17). Our study thus presents a simple and cost-efficient approach that reveals mechanistic insights into OMP-DOM biodegradation.

enviRule: an end-to-end system for automatic extraction of reaction patterns from environmental contaminant biotransformation pathways.

MOTIVATION: Transformation products (TPs) of man-made chemicals, formed through microbially mediated transformation in the environment, can have serious adverse environmental effects, yet the analytical identification of TPs is challenging. Rule-based prediction tools are successful in predicting TPs, especially in environmental chemistry applications that typically have to rely on small datasets, by imparting the existing knowledge on enzyme-mediated biotransformation reactions. However, the rules extracted from biotransformation reaction databases usually face the issue of being over/under-generalized and are not flexible to be updated with new reactions. RESULTS: We developed an automatic rule extraction tool called enviRule. It clusters biotransformation reactions into different groups based on the similarities of reaction fingerprints, and then automatically extracts and generalizes rules for each reaction group in SMARTS format. It optimizes the genericity of automatic rules against the downstream TP prediction task. Models trained with automatic rules outperformed the models trained with manually curated rules by 30% in the area under curve (AUC) scores. Moreover, automatic rules can be easily updated with new reactions, highlighting enviRule's strengths for both automatic extraction of optimized reactions rules and automated updating thereof. AVAILABILITY AND IMPLEMENTATION: enviRule code is freely available at https://github.com/zhangky12/enviRule.

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.

Should Transformation Products Change the Way We Manage Chemicals?

When chemical pollutants enter the environment, they can undergo diverse transformation processes, forming a wide range of transformation products (TPs), some of them benign and others more harmful than their precursors. To date, the majority of TPs remain largely unrecognized and unregulated, particularly as TPs are generally not part of routine chemical risk or hazard assessment. Since many TPs formed from oxidative processes are more polar than their precursors, they may be especially relevant in the context of persistent, mobile, and toxic (PMT) and very persistent and very mobile (vPvM) substances, which are two new hazard classes that have recently been established on a European level. We highlight herein that as a result, TPs deserve more attention in research, chemicals regulation, and chemicals management. This perspective summarizes the main challenges preventing a better integration of TPs in these areas: (1) the lack of reliable high-throughput TP identification methods, (2) uncertainties in TP prediction, (3) inadequately considered TP formation during (advanced) water treatment, and (4) insufficient integration and harmonization of TPs in most regulatory frameworks. A way forward to tackle these challenges and integrate TPs into chemical management is proposed.

Benchmarking the Persistence of Active Pharmaceutical Ingredients in River Systems.

Assessing the persistence of organic micropollutants from field data has been notoriously laborious, requiring extensive data including emissions and chemical properties, and the application of detailed mass-balance models, which often contain parameters that are impossible to measure. To overcome some of these obstacles, we developed the concept of persistence benchmarking for large rivers that receive numerous emissions and provide enough residence time to observe the dissipation of compounds. We estimated the dissipation rate constants of 41 compounds (mostly active pharmaceutical ingredients) from five measurement campaigns in the Rhine and Danube rivers using concentration rate profiles with respect to carbamazepine. Dissipation rates clearly distinguished between known fast- and slow-degrading compounds, and campaign-specific boundary conditions had an influence on a minor subset of compounds only. Benchmarking provided reasonable estimates on summer total system half-lives in the Rhine compared to previous laboratory experiments and a mass-balance modeling study. Consequently, benchmarking can be a straightforward persistence assessment method of continuously emitted organic micropollutants in large river systems, especially when it is supported by field monitoring campaigns of proper analytical quality and spatial resolution.

Modernizing persistence-bioaccumulation-toxicity (PBT) assessment with high throughput animal-free methods.

The assessment of persistence (P), bioaccumulation (B), and toxicity (T) of a chemical is a crucial first step at ensuring chemical safety and is a cornerstone of the European Union's chemicals regulation REACH (Registration, Evaluation, Authorization, and Restriction of Chemicals). Existing methods for PBT assessment are overly complex and cumbersome, have produced incorrect conclusions, and rely heavily on animal-intensive testing. We explore how new-approach methodologies (NAMs) can overcome the limitations of current PBT assessment. We propose two innovative hazard indicators, termed cumulative toxicity equivalents (CTE) and persistent toxicity equivalents (PTE). Together they are intended to replace existing PBT indicators and can also accommodate the emerging concept of PMT (where M stands for mobility). The proposed "toxicity equivalents" can be measured with high throughput in vitro bioassays. CTE refers to the toxic effects measured directly in any given sample, including single chemicals, substitution products, or mixtures. PTE is the equivalent measure of cumulative toxicity equivalents measured after simulated environmental degradation of the sample. With an appropriate panel of animal-free or alternative in vitro bioassays, CTE and PTE comprise key environmental and human health hazard indicators. CTE and PTE do not require analytical identification of transformation products and mixture components but instead prompt two key questions: is the chemical or mixture toxic, and is this toxicity persistent or can it be attenuated by environmental degradation? Taken together, the proposed hazard indicators CTE and PTE have the potential to integrate P, B/M and T assessment into one high-throughput experimental workflow that sidesteps the need for analytical measurements and will support the Chemicals Strategy for Sustainability of the European Union.

Early Assessment of Biodegradability of Small Molecules to Support the Chemical Design in Agro & Pharma R&D.

The use of agrochemical and pharmaceutical active ingredients is essential in our modern society. Given the increased concern and awareness of the potential risks of some chemicals, there is a growing need to align with 'green chemistry' and 'safe and sustainable by design' principles and thus to evaluate the hazards of agrochemical and pharmaceutical active ingredients in early stages of R&D. We give an overview of the current challenges and opportunities to assess the principle of biodegradability in the environment. Development of new medium/high-throughput methodologies, combining predictive tools and wet-lab experimentation are essential to design biodegradable chemicals early in the active ingredient discovery and selection process.

Can AI Help Improve Water Quality? Towards the Prediction of Degradation of Micropollutants in Wastewater.

Micropollutants have become a serious environmental problem by threatening ecosystems and the quality of drinking water. This account investigates if advanced AI can be used to find solutions for this problem. We review background, the challenges involved, and the current state-of-the-art of quantitative structure-biodegradation relationships (QSBR). We report on recent progress combining experiment, quantum chemistry (QC) and chemoinformatics, and provide a perspective on potential future uses of AI technology to help improve water quality.

Toward Characterizing the Genetic Basis of Trace Organic Contaminant Biotransformation in Activated Sludge: The Role of Multicopper Oxidases as a Case Study.

Activated sludge treatment leverages the ability of microbes to uptake and (co)-metabolize chemicals and has shown promise in eliminating trace organic contaminants (TrOCs) during wastewater treatment. However, targeted interventions to optimize the process are limited as the fundamental drivers of the observed reactions remain elusive. In this work, we present a comprehensive workflow for the identification and characterization of key enzymes involved in TrOCs biotransformation pathways in complex microbial communities. To demonstrate the applicability of the workflow, we investigated the role of the enzymatic group of multicopper oxidases (MCOs) as one putatively relevant driver of TrOCs biotransformation. To this end, we analyzed activated sludge metatranscriptomic data and selected, synthesized, and heterologously expressed three phylogenetically distinct MCO-encoding genes expressed in communities with different TrOCs oxidation potentials. Following the purification of the encoded enzymes, we screened their activities against different substrates. We saw that MCOs exhibit significant activities against selected TrOCs in the presence of the mediator compound 2,2'-azino-bis-3-ethylbenzthiazoline-6-sulfonic acid and, in some cases, also in the presence of the wastewater contaminant 4'-hydroxy-benzotriazole. In the first case, we identified oxidation products previously reported from activated sludge communities and concluded that in the presence of appropriate mediators, bacterial MCOs could contribute to the biological removal of TrOCs. Similar investigations of other key enzyme systems may significantly advance our understanding of TrOCs biodegradation and assist the rational design of biology-based water treatment strategies in the future.

Concerted Evaluation of Pesticides in Soils of Extensive Grassland Sites and Organic and Conventional Vegetable Fields Facilitates the Identification of Major Input Processes.

The intensive use of pesticides and their subsequent distribution to the environment and non-target organisms is of increasing concern. So far, little is known about the occurrence of pesticides in soils of untreated areas─such as ecological refuges─as well as the processes contributing to this unwanted pesticide contamination. In this study, we analyzed the presence and abundance of 46 different pesticides in soils from extensively managed grassland sites, as well as organically and conventionally managed vegetable fields (60 fields in total). Pesticides were found in all soils, including the extensive grassland sites, demonstrating a widespread background contamination of soils with pesticides. The results suggest that after conversion from conventional to organic farming, the organic fields reach pesticide levels as low as those of grassland sites not until 20 years later. Furthermore, the different pesticide composition patterns in grassland sites and organically managed fields facilitated differentiation between long-term persistence of residues and diffuse contamination processes, that is, short-scale redistribution (spray drift) and long-scale dispersion (atmospheric deposition), to offsite contamination.

Towards more Sustainable Peptide- based Antibiotics: Stable in Human Blood, Enzymatically Hydrolyzed in Wastewater?

The emergence and spread of antibiotic resistance is a major societal challenge and new antibiotics are needed to successfully fight bacterial infections. Because the release of antibiotics into wastewater and downstream environments is expected to contribute to the problem of antibiotic resistance, it would be beneficial to consider the environmental fate of antibiotics in the development of novel antibiotics. In this article, we discuss the possibility of designing peptide-based antibiotics that are stable during treatment (e.g. in human blood), but rapidly inactivated through hydrolysis by peptidases after their secretion into wastewater. In the first part, we review studies on the biotransformation of peptide-based antibiotics during biological wastewater treatment and on the specificity of dissolved extracellular peptidases derived from wastewater. In the second part, we present first results of our endeavour to identify peptide bonds that are stable in human blood plasma and susceptible to hydrolysis by the industrially produced peptidase Subtilisin A.

Understanding the Dependence of Micropollutant Biotransformation Rates on Short-Term Temperature Shifts.

Temperature is a key factor that influences chemical biotransformation potential and rates, on which exposure and fate models rely to predict the environmental (micro)pollutant fate. Arrhenius-based models are currently implemented in environmental exposure assessment to adapt biotransformation rates to actual temperatures, assuming validity in the 0-30 °C range. However, evidence on how temperature shifts affect the physicochemical and microbial features in biological systems is scarce, questioning the validity of the existing modeling approaches. In this work, laboratory-scale batch assays were designed to investigate how a mixed microbial community responds to short-term temperature shifts, and how this impacts its ability to biotransform a range of structurally diverse micropollutants. Our results revealed three distinct kinetic responses at temperatures above 20 °C, mostly deviating from the classic Arrhenius-type behavior. Micropollutants with similar temperature responses appeared to undergo mostly similar initial biotransformation reactions, with substitution-type reactions maintaining Arrhenius-type behavior up to higher temperatures than oxidation-type reactions. Above 20 °C, the microbial community also showed marked shifts in both composition and activity, which mostly correlated with the observed deviations from Arrhenius-type behavior, with compositional changes becoming a more relevant factor in biotransformations catalyzed by more specific enzymes (e.g., oxidation reactions). Our findings underline the need to re-examine and further develop current environmental fate models by integrating biological aspects, to improve accuracy in predicting the environmental fate of micropollutants.

Quantification of Active Ingredient Losses from Formulating Pharmaceutical Industries and Contribution to Wastewater Treatment Plant Emissions.

In this work, emissions of active pharmaceutical ingredients (APIs) from formulating pharmaceutical industries (FPIs) were investigated for the first time based on detailed production information and compared to overall API emissions in wastewater treatment plant (WWTP) effluents. At two municipal WWTPs, both receiving wastewater from several FPIs, two months' daily effluent samples were collected and measured using liquid chromatography high-resolution mass spectrometry (LC-HRMS). Thirty-three APIs formulated during the sampling period as well as >120 organic contaminants commonly present in WWTP effluents were quantified. On the basis of their time patterns and manufacturing data, industrial contributions were found for 22 of 26 APIs (85%) detected in the samples and processed by the FPIs. API emissions from FPIs led to daily concentration increases of up to 300-fold, despite pretreatment of the industrial wastewater. However, emissions from FPIs seemed to depend on the type of formulating activity, with granulation and mixing being most prone to API losses. Losses from FPIs were responsible for the highest concentrations and for up to 60% of the daily total API emissions measured. Furthermore, screening for suspects in LC-HRMS data resulted in the detection of unexpected emissions from FPIs, demonstrating the value of these data to comprehensively assess industrial API losses. Overall, this study showed that FPIs were relevant contributors of APIs emitted in the WWTP effluents, although only a minor fraction (<1%) of the total processed API quantity was lost to the wastewater, and despite the small percentage (<5%) of FPI wastewater compared to the total wastewater flow.

Comparison of Small Molecule Biotransformation Half-Lives between Activated Sludge and Soil: Opportunities for Read-Across?

Compartment-specific degradation half-lives are essential pieces of information in the regulatory risk assessment of synthetic chemicals. However, their measurement according to regulatory testing guidelines is laborious and costly. Despite the obvious ecological and economic benefits of knowing environmental degradability as early as possible, its consideration in the early phases of rational chemical design is therefore challenging. Here, we explore the possibility to use half-lives determined in highly time- and work-efficient biotransformation experiments with activated sludge and mixtures of chemicals to predict soil half-lives from regulatory simulation studies. We experimentally determined half-lives for 52 structurally diverse agrochemical active ingredients in batch reactors with three concentrations of the same activated sludge. We then developed bi- and multivariate models for predicting half-lives in soil by regressing the experimentally determined half-lives in activated sludge against average soil half-lives of the same chemicals extracted from regulatory data. The models differed in how we accounted for sorption-related bioavailability differences in soil and activated sludge. The best-performing models exhibited good coefficients of determination (R2 of around 0.8) and low average errors (

Assessing Emissions from Pharmaceutical Manufacturing Based on Temporal High-Resolution Mass Spectrometry Data.

This study presents a nontarget approach to detect discharges from pharmaceutical production in municipal wastewater treatment plant (WWTP) effluents and to estimate their relevance on the total emissions. Daily composite samples were collected for 3 months at two WWTPs in Switzerland, measured using liquid chromatography high-resolution mass spectrometry, and time series were generated for all features detected. The extent of intensity variation in the time series was used to differentiate relatively constant domestic inputs from highly fluctuating industrial emissions. We show that an intensity variation threshold of 10 correctly classifies compounds of known origin and reveals clear differences between the two WWTPs. At the WWTP receiving wastewater from a pharmaceutical manufacturing site, (i) 10 times as many potential industrial emissions were detected as compared to the WWTP receiving purely domestic wastewater; (ii) for 11 pharmaceuticals peak concentrations, >10 µg/L and up to 214 µg/L were quantified, which are clearly above typical municipal wastewater concentrations; and (iii) a pharmaceutical not authorized in Switzerland was identified. Signatures of potential industrial emissions were even traceable at the downstream Rhine monitoring station at a >4000-fold dilution. Several of them occurred repeatedly, suggesting that they were linked to regular production, not to accidents. Our results demonstrate that small wastewater volumes from a single industry not only left a clear signature in the effluents of the respective WWTP but also influenced the water quality of one of Europe's most important river systems. Overall, these findings indicate that pharmaceutical production is a relevant emission source even in highly developed countries with a strong focus on water quality, such as Switzerland.

Relating Metatranscriptomic Profiles to the Micropollutant Biotransformation Potential of Complex Microbial Communities.

Biotransformation of chemical contaminants is of importance in various natural and engineered systems. However, in complex microbial communities and with chemical contaminants at low concentrations, our current understanding of biotransformation at the level of enzyme-chemical interactions is limited. Here, we explored an approach to identify associations between micropollutant biotransformation and specific gene products in complex microbial communities, using association mining between chemical and metatranscriptomic data obtained from experiments with activated sludge grown at different solid retention times. We successfully demonstrate proportional relationships between the measured rate constants and associated gene transcripts for nitrification as a major community function, but also for the biotransformation of two nitrile-containing micropollutants (bromoxynil and acetamiprid) and transcripts of nitrile hydratases, a class of enzymes that we experimentally confirmed to produce the detected amide transformation products. As these results suggest that metatranscriptomic information can indeed be quantitatively correlated with low abundant community functions such as micropollutant biotransformation in complex microbial communities, we proceeded to explore the potential of association mining to highlight enzymes likely involved in catalyzing less well-understood micropollutant biotransformation reactions. Specifically, we use the cases of nitrile hydration and oxidative biotransformation reactions to show that the consideration of additional experimental evidence (such as information on biotransformation pathways) increases the likelihood of detecting plausible novel enzyme-chemical relationships. Finally, we identify a cluster of mono- and dioxygenase fourth-level enzyme classes that most strongly correlate with oxidative micropollutant biotransformation reactions in activated sludge.

Ion Trapping of Amines in Protozoa: A Novel Removal Mechanism for Micropollutants in Activated Sludge.

To optimize removal of organic micropollutants from the water cycle, understanding the processes during activated sludge treatment is essential. In this study, we hypothesize that aliphatic amines, which are highly abundant among organic micropollutants, are partly removed from the water phase in activated sludge through ion trapping in protozoa. In ion trapping, which has been extensively investigated in medical research, the neutral species of amine-containing compounds diffuse through the cell membrane and further into acidic vesicles present in eukaryotic cells such as protozoa. There they become trapped because diffusion of the positively charged species formed in the acidic vesicles is strongly hindered. We tested our hypothesis with two experiments. First, we studied the distribution of the fluorescent amine acridine orange in activated sludge by confocal fluorescence imaging. We observed intense fluorescence in distinct compartments of the protozoa, but not in the bacterial biomass. Second, we investigated the distribution of 12 amine-containing and eight control micropollutants in both regular activated sludge and sludge where the protozoa had been inactivated. In contrast to most control compounds, the amine-containing micropollutants displayed a distinctly different behavior in the noninhibited sludge compared to the inhibited one: (i) more removal from the liquid phase; (ii) deviation from first-order kinetics for the removal from the liquid phase; and (iii) higher amounts in the solid phase. These results provide strong evidence that ion trapping in protozoa occurs and that it is an important removal mechanism for amine-containing micropollutants in batch experiments with activated sludge that has so far gone unnoticed. We expect that our findings will trigger further investigations on the importance of this process in full-scale wastewater treatment systems, including its relevance for accumulation of ammonium.

Trends in Micropollutant Biotransformation along a Solids Retention Time Gradient.

For many polar organic micropollutants, biotransformation by activated sludge microorganisms is a major removal process during wastewater treatment. However, our current understanding of how wastewater treatment operations influence microbial communities and their micropollutant biotransformation potential is limited, leaving major parts of observed variability in biotransformation rates across treatment facilities unexplained. Here, we present biotransformation rate constants for 42 micropollutants belonging to different chemical classes along a gradient of solids retention time (SRT). The geometric mean of biomass-normalized first-order rate constants shows a clear increase between 3 and 15 d SRT by 160% and 87%, respectively, in two experiments. However, individual micropollutants show a variety of trends. Rate constants of oxidative biotransformation reactions mostly increased with SRT. Yet, nitrifying activity could be excluded as primary driver. For substances undergoing other than oxidative reactions, i.e., mostly substitution-type reactions, more diverse dependencies on SRT were observed. Most remarkably, characteristic trends were observed for groups of substances undergoing similar types of initial transformation reaction, suggesting that shared enzymes or enzyme systems that are conjointly regulated catalyze biotransformation reactions within such groups. These findings open up opportunities for correlating rate constants with measures of enzyme abundance such as genes or gene products, which in turn should help to identify enzymes associated with the respective biotransformation reactions.

Biotransformation of Sulfonamide Antibiotics in Activated Sludge: The Formation of Pterin-Conjugates Leads to Sustained Risk.

The presence of antibiotics in treated wastewater and consequently in surface and groundwater resources raises concerns about the formation and spread of antibiotic resistance. Improving the removal of antibiotics during wastewater treatment therefore is a prime objective of environmental engineering. Here we obtained a detailed picture of the fate of sulfonamide antibiotics during activated sludge treatment using a combination of analytical methods. We show that pterin-sulfonamide conjugates, which are formed when sulfonamides interact with their target enzyme to inhibit folic acid synthesis, represent a major biotransformation route for sulfonamides in laboratory batch experiments with activated sludge. The same major conjugates were also present in the effluents of nine Swiss wastewater treatment plants. The demonstration of this biotransformation route, which is related to bacterial growth, helps explain seemingly contradictory views on optimal conditions for sulfonamide removal. More importantly, since pterin-sulfonamide conjugates show retained antibiotic activity, our findings suggest that risk from exposure to sulfonamide antibiotics may be less reduced during wastewater treatment than previously assumed. Our results thus further emphasize the inadequacy of focusing on parent compound removal and the importance of investigating biotransformation pathways and removal of bioactivity to properly assess contaminant removal in both engineered and natural systems.

enviPath--The environmental contaminant biotransformation pathway resource.

The University of Minnesota Biocatalysis/Biodegradation Database and Pathway Prediction System (UM-BBD/PPS) has been a unique resource covering microbial biotransformation pathways of primarily xenobiotic chemicals for over 15 years. This paper introduces the successor system, enviPath (The Environmental Contaminant Biotransformation Pathway Resource), which is a complete redesign and reimplementation of UM-BBD/PPS. enviPath uses the database from the UM-BBD/PPS as a basis, extends the use of this database, and allows users to include their own data to support multiple use cases. Relative reasoning is supported for the refinement of predictions and to allow its extensions in terms of previously published, but not implemented machine learning models. User access is simplified by providing a REST API that simplifies the inclusion of enviPath into existing workflows. An RDF database is used to enable simple integration with other databases. enviPath is publicly available at https://envipath.org with free and open access to its core data.