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.

Electrospray Ionization Efficiency Predictions and Analytical Standard Free Quantification for SFC/ESI/HRMS.

Supercritical fluid chromatography (SFC) is a promising, sustainable, and complementary alternative to liquid chromatography (LC) and has often been coupled with high resolution mass spectrometry (HRMS) for nontarget screening (NTS). Recent developments in predicting the ionization efficiency for LC/ESI/HRMS have enabled quantification of chemicals detected in NTS even if the analytical standards of the detected and tentatively identified chemicals are unavailable. This poses the question of whether analytical standard free quantification can also be applied in SFC/ES/HRMS. We evaluate both the possibility to transfer an ionization efficiency predictions model, previously trained on LC/ESI/HRMS data, to SFC/ESI/HRMS as well as training a new predictive model on SFC/ESI/HRMS data for 127 chemicals. The response factors of these chemicals ranged over 4 orders of magnitude in spite of a postcolumn makeup flow, expectedly enhancing the ionization of the analytes. The ionization efficiency values were predicted based on a random forest regression model from PaDEL descriptors and predicted values showed statistically significant correlation with the measured response factors (p < 0.05) with Spearman's rho of 0.584 and 0.669 for SFC and LC data, respectively. Moreover, the most significant descriptors showed similarities independent of the chromatography used for collecting the training data. We also investigated the possibility to quantify the detected chemicals based on predicted ionization efficiency values. The model trained on SFC data showed very high prediction accuracy with median prediction error of 2.20×, while the model pretrained on LC/ESI/HRMS data yielded median prediction error of 5.11×. This is expected, as the training and test data for SFC/ESI/HRMS have been collected on the same instrument with the same chromatography. Still, the correlation observed between response factors measured with SFC/ESI/HRMS and predicted with a model trained on LC data hints that more abundant LC/ESI/HRMS data prove useful in understanding and predicting the ionization behavior in SFC/ESI/HRMS.

The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry.

Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA's CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101). Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the "one substance, one assessment" approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/). Supplementary Information: The online version contains supplementary material available at 10.1186/s12302-022-00680-6.

Characterizing Powdered Activated Carbon Treatment of Surface Water Samples Using Polarity-Extended Non-Target Screening Analysis.

Advanced wastewater treatment such as powdered activated carbon (PAC) reduces the load of organic micropollutants entering the aquatic environment. Since mobile and persistent compounds accumulate in water cycles, treatment strategies need to be evaluated for the removal of (very) polar compounds. Thereby, non-targeted analysis gives a global picture of the molecular fingerprint (including these very polar molecules) of water samples. Target and non-target screening were conducted using polarity-extended chromatography hyphenated with mass spectrometry. Samples treated with different types and concentrations of PAC were compared to untreated samples. Molecular features were extracted from the analytical data to determine fold changes, perform a principal component analysis and for significance testing. The results suggest that a part of the polar target analytes was adsorbed but also some byproducts might be formed or desorbed from the PAC.

A Novel Analytical Approach to Assessing Sorption of Trace Organic Compounds into Micro- and Nanoplastic Particles.

Assessing the sorption of trace organic compounds (TOrCs) into micro- and nanoplastic particles has traditionally been performed using an aqueous phase analysis or solvent extractions from the particle. Using thermal extraction/desorption-gas chromatography/mass spectrometry (TD-Pyr-GC/MS) offers a possibility to analyze the TOrCs directly from the particle without a long sample preparation. In this study, a combination of two analytical methods is demonstrated. First, the aqueous phase is quantified for TOrC concentrations using Gerstel Twister® and TD-GC/MS. Subsequently, the TOrCs on the particles are analyzed. Different polymer types and sizes (polymethyl methacrylate (PMMA), 48 µm; polyethylene (PE), 48 µm; polystyrene (PS), 41 µm; and PS, 78 nm) were analyzed for three selected TOrCs (phenanthrene, triclosan, and α-cypermethrin). The results revealed that, over a period of 48 h, the highest and fastest sorption occurred for PS 78 nm particles. This was confirmed with a theoretical calculation of the particle surface area. It was also shown for the first time that direct quantification of TOrCs from PS 78 nm nanoparticles is possible. Furthermore, in a mixed solute solution, the three selected TOrCs were sorbed onto the particles simultaneously.

The changes in Lemna minor metabolomic profile: A response to diclofenac incubation.

Metabolomics is an emerging approach that investigates the changes in the metabolome profile. In the present study, Lemna minor -considered as an experimental aquatic plant model- was incubated with 10 and 100 µM diclofenac (DCF) for 96 h, respectively. Knowing that DCF is internationally often problematic in wastewater effluents and that it might affect particularly the metabolic profiles in aquatic plants, mainly the oxidoreductase, dehydrogenase, peroxidase, and glutathione reductase activities, here it was hypothesized (H) that in the common duckweed, DCF might increase the phenolic and flavonoids pathways, as an antioxidant response to this stress (H1). Also, it was expected DCF to alternate the physiological characteristics, especially the molecular interaction and biochemical properties, of Lemna (H2). Metabolic changes were investigated with target and untargeted screening analysis using RPLC-HILIC-ESI-TOF-MS. Twelve amino acids were identified in all treatments, together with three organic acids (p-coumaric, cinnamic, and sinapic acids). In untargeted screening, the important metabolites to discriminate between different treatments were assigned to Lemna such as organic acids, lignin, sugars, amino acids, dipeptides, flavonoids, biflavonoids, fatty acids, among others. In resume, Lemna responded to both DCF concentrations, showing different stress patterns. A similar metabolic response had already been identified in other studies in exposing Lemna to other anthropogenic stressors (like pesticides).

Spotlight on mass spectrometric non-target screening analysis: Advanced data processing methods recently communicated for extracting, prioritizing and quantifying features.

Non-target screening of trace organic compounds complements routine monitoring of water bodies. So-called features need to be extracted from the raw data that preferably represent a chemical compound. Relevant features need to be prioritized and further be interpreted, for instance by identifying them. Finally, quantitative data is required to assess the risks of a detected compound. This review presents recent and noteworthy contributions to the processing of non-target screening (NTS) data, prioritization of features as well as (semi-) quantitative methods that do not require analytical standards. The focus lies on environmental water samples measured by liquid chromatography, electrospray ionization and high-resolution mass spectrometry. Examples for fully-integrated data processing workflows are given with options for parameter optimization and choosing between different feature extraction algorithms to increase feature coverage. The regions of interest-multivariate curve resolution method is reviewed which combines a data compression alternative with chemometric feature extraction. Furthermore, prioritization strategies based on a confined chemical space for annotation, guidance by targeted analysis and signal intensity are presented. Exploiting the retention time (RT) as diagnostic evidence for NTS investigations is highlighted by discussing RT indexing and prediction using quantitative structure-retention relationship models. Finally, a seminal technology for quantitative NTS is discussed without the need for analytical standards based on predicting ionization efficiencies.

Untargeted Analysis of Lemna minor Metabolites: Workflow and Prioritization Strategy Comparing Highly Confident Features between Different Mass Spectrometers.

Metabolomics approaches provide a vast array of analytical datasets, which require a comprehensive analytical, statistical, and biochemical workflow to reveal changes in metabolic profiles. The biological interpretation of mass spectrometric metabolomics results is still obstructed by the reliable identification of the metabolites as well as annotation and/or classification. In this work, the whole Lemna minor (common duckweed) was extracted using various solvents and analyzed utilizing polarity-extended liquid chromatography (reversed-phase liquid chromatography (RPLC)-hydrophilic interaction liquid chromatography (HILIC)) connected to two time-of-flight (TOF) mass spectrometer types, individually. This study (introduces and) discusses three relevant topics for the untargeted workflow: (1) A comparison study of metabolome samples was performed with an untargeted data handling workflow in two different labs with two different mass spectrometers using the same plant material type. (2) A statistical procedure was observed prioritizing significant detected features (dependent and independent of the mass spectrometer using the predictive methodology Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA). (3) Relevant features were transferred to a prioritization tool (the FOR-IDENT platform (FI)) and were compared with the implemented compound database PLANT-IDENT (PI). This compound database is filled with relevant compounds of the Lemnaceae, Poaceae, Brassicaceae, and Nymphaceae families according to analytical criteria such as retention time (polarity and LogD (pH 7)) and accurate mass (empirical formula). Thus, an untargeted analysis was performed using the new tool as a prioritization and identification source for a hidden-target screening strategy. Consequently, forty-two compounds (amino acids, vitamins, flavonoids) could be recognized and subsequently validated in Lemna metabolic profile using reference standards. The class of flavonoids includes free aglycons and their glycosides. Further, according to our knowledge, the validated flavonoids robinetin and norwogonin were for the first time identified in the Lemna minor extracts.

(Very) polar organic compounds in the Danube river basin: a non-target screening workflow and prioritization strategy for extracting highly confident features.

Recently, more and more research has been focused on the analysis of polar organic compounds as they tend to be persistent and mobile in the aquatic environment. The serial coupling of reversed-phase and hydrophilic interaction liquid chromatography allows the separation of analytes of an extended polarity range within a single run. The non-target screening approach was driven by high-resolution mass spectrometry and is able to detect unexpected compounds. It is therefore capable of complementing regular monitoring of surface water. Non-target screening, however, can produce massive data sets. Here, a data processing method is presented focusing on unravelling tentative polar compounds from the full scan data of 51 samples of the Danube river and its tributaries. The feature extraction method was optimized to 34 reference compounds at two concentration levels and was then applied to real samples. Features were matched by accurate mass with anthropogenic substances stored in the compound database STOFF-IDENT located on the FOR-IDENT platform. In order to extract polar candidates, the retention time interval corresponding to the HILIC separation was connected to compounds with a negative log D value. As a result, 67 candidates were detected which were found to be plausible. Finally, features were prioritized based on an identification certainty classification system as well as their frequency of occurrence. Therefore, several feature-candidate compound pairs could be suggested for confirmation via reference materials. The presented non-target screening strategy followed by a database query is transferrable to other sample sets and other data evaluation tools.

Organic Contaminants and Interactions with Micro- and Nano-Plastics in the Aqueous Environment: Review of Analytical Methods.

Micro- and nanoplastic particles are increasingly seen not only as contaminants themselves, but also as potential vectors for trace organic chemicals (TOrCs) that might sorb onto these particles. An analysis of the sorbed TOrCs can either be performed directly from the particle or TOrCs can be extracted from the particle with a solvent. Another possibility is to analyze the remaining concentration in the aqueous phase by a differential approach. In this review, the focus is on analytical methods that are suitable for identifying and quantifying sorbed TOrCs on micro- and nano-plastics. Specific gas chromatography (GC), liquid chromatography (LC) and ultraviolet-visible spectroscopy (UV-VIS) methods are considered. The respective advantages of each method are explained in detail. In addition, influencing factors for sorption in the first place are being discussed including particle size and shape (especially micro and nanoparticles) and the type of polymer, as well as methods for determining sorption kinetics. Since the particles are not present in the environment in a virgin state, the influence of aging on sorption is also considered.

Untargeted Metabolomics Studies on Drug-Incubated Phragmites australis Profiles.

Plants produce a huge number of functionally and chemically different natural products that play an important role in linking the plant with the adjacent environment. Plants can also absorb and transform external organic compounds (xenobiotics). Currently there are only a few studies concerning the effects of xenobiotics and their transformation products on plant metabolites using a mass spectrometric untargeted screening strategy. This study was designed to investigate the changes of the Phragmites australis metabolome following/after diclofenac or carbamazepine incubation, using a serial coupling of reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) combined with accurate high-resolution time-of-flight mass spectrometer (TOF-MS). An untargeted screening strategy of metabolic fingerprints was developed to purposefully compare samples from differently treated P. australis plants, revealing that P. australis responded to each drug differently. When solvents with significantly different polarities were used, the metabolic profiles of P. australis were found to change significantly. For instance, the production of polyphenols (such as quercetin) in the plant increased after diclofenac incubation. Moreover, the pathway of unsaturated organic acids became more prominent, eventually as a reaction to protect the cells against reactive oxygen species (ROS). Hence, P. australis exhibited an adaptive mechanism to cope with each drug. Consequently, the untargeted screening approach is essential for understanding the complex response of plants to xenobiotics.

Systematic Development of a Simultaneous Determination of Plastic Particle Identity and Adsorbed Organic Compounds by Thermodesorption-Pyrolysis GC/MS (TD-Pyr-GC/MS).

Micro-, submicro- and nanoplastic particles are increasingly regarded as vectors for trace organic chemicals. In order to determine adsorbed trace organic chemicals on polymers, it has usually been necessary to carry out complex extraction steps. With the help of a newly designed thermal desorption pyrolysis gas chromatography mass spectrometry (TD-Pyr-GC/MS) method, it is possible to identify adsorbed trace organic chemicals on micro-, submicro- and nanoparticles as well as the particle short chain polymers in one analytical setup without any transfers. This ensures a high sample throughput for the qualitative analysis of trace substances and polymer type. Since the measuring time per sample is only 2 h, a high sample throughput is possible. It is one of the few analytical methods which can be used also for the investigation of nanoplastic particles. Initially adsorbed substances are desorbed from the particle by thermal desorption (TD); subsequently, the polymer is fragmented by pyrolysis (PYR). Both particle treatment techniques are directly coupled with the same GC-MS system analyzing desorbed molecules and pyrolysis products, respectively. In this study, we developed a systematic and optimized method for this application. For method development, the trace organic chemicals phenanthrene, α-cypermethrin and triclosan were tested on reference polymers polystyrene (PS), polymethyl methacrylate (PMMA) and polyethylene (PE). Well-defined particle fractions were used, including polystyrene (sub)micro- (41 and 40 µm) and nanoparticles (78 nm) as well as 48-µm sized PE and PMMA particles, respectively. The sorption of phenanthrene (PMMA << PS 40 µm < 41 µm < PE < PS 78 nm) and α-cypermethrin (PS 41 µm < PS 40 µm < PE < PMMA < PS 78 nm) to the particles was strongly polymer-dependent. Triclosan adsorbed only on PE and on the nanoparticles of PS (PE < PS78).

Optimized hidden target screening for very polar molecules in surface waters including a compound database inquiry.

Highly polar trace organic compounds, which are persistent, mobile, and toxic (PMT) or are very persistent and very mobile (vPvM) in the aquatic environment, may pose a risk to surface water, ground water, and drinking water supplies. Despite the advances in liquid chromatography-mass spectrometry, there often exists an analytical blind spot when it comes to very polar chemicals. This study seeks to make a broad polarity range analytically accessible by means of serially coupling reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) to high-resolution mass spectrometry (HRMS). Moreover, a workflow is presented using optimized data processing of nontarget screening (NTS) data and subsequently generating candidate lists for the identification of very polar molecules via an open-access NTS platform and implemented compound database. First, key input parameters and filters of the so-called feature extraction algorithms were identified, and numerical performance indicators were defined to systematically optimize the data processing method. Second, all features from the very polar HILIC elution window were uploaded to the STOFF-IDENT database as part of the FOR-IDENT open-access NTS platform, which contains additional physicochemical information, and the features matched with potential compounds by their accurate mass. The hit list was filtered for compounds with a negative log D value, indicating that they were (very) polar. For instance, 46 features were assigned to 64 candidate compounds originating from a set of 33 samples from the Isar river in Germany. Three PMT candidates (e.g., guanylurea, melamine, and 1,3-dimethylimidazolidin-2-one) were illustratively validated using the respective reference standards. In conclusion, these findings demonstrate that polarity-extended chromatography reproducibly retards and separates (very) polar compounds from surface waters. These findings further indicate that a transparent and robust data processing workflow for nontarget screening data is available for addressing new (very) polar substances in the aqueous environment.

Lemna minor studies under various storage periods using extended-polarity extraction and metabolite non-target screening analysis.

Plant metabolomic studies cover a broad band of compounds, including various functional groups with different polarities and other physiochemical properties. For this reason, specific optimized methods are needed in order to enable efficient and non-destructive extraction of molecules over a large range of LogD values. This study presents a simple and efficient extraction procedure for Lemna minor samples demonstrating polarity extension of the molecular range. The Lemna samples chosen were kept under the following storage conditions: 1) fresh, 2) stored for a few days at -80 °C, and 3) stored for 6 months at -80 °C. The samples were extracted using five specifically chosen solvents: 100 % ethanol, 100 % methanol (MeOH), acidic 90 % MeOH (MeOH-water-formic acid (FAC) (90:9.5:0.5, v/v/v), MeOH-water (50:50, v/v), and 100 % water. The final extraction procedure was conducted subject to three solvent conditions, and the subsequent polarity-extended analysis was applied for Lemna minor samples using RPLC-HILIC-ESI-TOF-MS. The extraction yield is in descending order (acidic 90 % MeOH), 50 % MeOH, 100 % water and 100 % MeOH. The results displayed significant molecular differences, both in the extracts investigated and in the fresh Lemna samples, compared to stored samples, in terms of the extraction yield and reducing contents as well as the number of features. The storage of Lemna minor resulted in changes to the fingerprint of its metabolites as the reducing contents increased. The comparisons enable a direct view of molecule characterizations, in terms of their polarity, molecular mass, and signal intensity. This parametric information would appear ideal for further statistical data analysis. Consequently, the extraction procedure and the analysis/data evaluation are highly suitable for the so-called extended-polarity non-target screening procedure.

The strength in numbers: comprehensive characterization of house dust using complementary mass spectrometric techniques.

Untargeted analysis of a composite house dust sample has been performed as part of a collaborative effort to evaluate the progress in the field of suspect and nontarget screening and build an extensive database of organic indoor environment contaminants. Twenty-one participants reported results that were curated by the organizers of the collaborative trial. In total, nearly 2350 compounds were identified (18%) or tentatively identified (25% at confidence level 2 and 58% at confidence level 3), making the collaborative trial a success. However, a relatively small share (37%) of all compounds were reported by more than one participant, which shows that there is plenty of room for improvement in the field of suspect and nontarget screening. An even a smaller share (5%) of the total number of compounds were detected using both liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). Thus, the two MS techniques are highly complementary. Most of the compounds were detected using LC with electrospray ionization (ESI) MS and comprehensive 2D GC (GC×GC) with atmospheric pressure chemical ionization (APCI) and electron ionization (EI), respectively. Collectively, the three techniques accounted for more than 75% of the reported compounds. Glycols, pharmaceuticals, pesticides, and various biogenic compounds dominated among the compounds reported by LC-MS participants, while hydrocarbons, hydrocarbon derivatives, and chlorinated paraffins and chlorinated biphenyls were primarily reported by GC-MS participants. Plastics additives, flavor and fragrances, and personal care products were reported by both LC-MS and GC-MS participants. It was concluded that the use of multiple analytical techniques was required for a comprehensive characterization of house dust contaminants. Further, several recommendations are given for improved suspect and nontarget screening of house dust and other indoor environment samples, including the use of open-source data processing tools. One of the tools allowed provisional identification of almost 500 compounds that had not been reported by participants.

Comprehensive MS-based screening and identification of pharmaceutical transformation products formed during enzymatic conversion.

In this study, transformation products (TPs) of diclofenac, mefenamic acid, and sotalol derived from peroxidase- and laccase-catalyzed transformations were studied with different mass spectrometry (MS)-based workflows. A straightforward pre-screening of enzymatic degradation rate was performed using a robotic nano-ESI source coupled to single quadrupole MS. Accurate mass data and information on molecular hydrophobicity were obtained from a serial coupling of reversed phase liquid chromatography (RPLC) with hydrophilic interaction liquid chromatography (HILIC) to a time-of-flight-mass spectrometer (ToF-MS). These parameters were combined with fragmentation information from product ion scan operated in enhanced mode (EPI) with precursor selection in Q3 and data from multiple reaction monitoring (MRM) modes using a hybrid triple quadrupole-linear ion trap-mass spectrometer (QqQ/LIT-MS). "Suspect" MRM modes did not provide a significant sensitivity improvement compared to EPI experiments. The complementarity of the data from different MS-based workflows allowed for an increase of identification confidence. Overall, this study demonstrated that dimerization, hydroxylation, and dehydration reactions were the predominant mechanisms found for diclofenac and mefenamic acid during enzyme-catalyzed transformation, whereas a degradation product was observed for the peroxidase-catalyzed conversion of sotalol. Results can contribute to understand enzymatic mechanisms and provide a basis for assessing risks and benefits of enzyme-based remediation. Graphical abstract ᅟ.

Enzymes in removal of pharmaceuticals from wastewater: A critical review of challenges, applications and screening methods for their selection.

At present, the removal of trace organic chemicals such as pharmaceuticals in wastewater treatment plants is often incomplete resulting in a continuous discharge into the aqueous environment. To overcome this issue, bioremediation approaches gained significant importance in recent times, since they might have a lower carbon footprint than chemical or physical treatment methods. In this context, enzyme-based technologies represent a promising alternative since they are able to specifically target certain chemicals. For this purpose, versatile monitoring of enzymatic reactions is of great importance in order to understand underlying transformation mechanisms and estimate the suitability of various enzymes exhibiting different specificities for bioremediation purposes. This study provides a comprehensive review, summarizing research on enzymatic transformation of pharmaceuticals in water treatment applications using traditional and state-of-the-art enzyme screening approaches with a special focus on mass spectrometry (MS)-based and high-throughput tools. MS-based enzyme screening represents an approach that allows a comprehensive mechanistic understanding of enzymatic reactions and, in particular, the identification of transformation products. A critical discussion of these approaches for implementation in wastewater treatment processes is also presented. So far, there are still major gaps between laboratory- and field-scale research that need to be overcome in order to assess the viability for real applications.

Monitoring enzymatic degradation of emerging contaminants using a chip-based robotic nano-ESI-MS tool.

Up to now, knowledge of enzymes capable of degrading various contaminants of emerging concern (CEC) is limited, which is especially due to the lack of rapid screening methods. Thus, a miniaturized high-throughput setup using a chip-based robotic nanoelectrospray ionization system coupled to mass spectrometry has been developed to rapidly screen enzymatic reactions with environmentally relevant CECs. Three laccases, two tyrosinases, and two peroxidases were studied for their ability to transform ten pharmaceuticals and benzotriazole. Acetaminophen was most susceptible to enzymatic conversion by horseradish peroxidase (HRP), laccase from Trametes versicolor (LccTV), and a tyrosinase from Agaricus bisporus (TyrAB). Diclofenac and mefenamic acid were converted by HRP and LccTV, whereas sotalol was solely amenable to HRP conversion. Benzotriazole, carbamazepine, gabapentin, metoprolol, primidone, sulfamethoxazole, and venlafaxine remained persistent in this study. The results obtained here emphasize that enzymes are highly selective catalysts and more effort is required in the use of fast monitoring technologies to find suitable enzyme systems. Despite the methodological limitations discussed in detail, the automated tool provides a routine on-line screening of various enzymatic reactions to identify potential enzymes that degrade CECs. Graphical abstract A chip-based robotic nano-ESI-MS tool to rapidly monitor enzymatic degradation of environmentally relevant emerging contaminants.