Development and validation of a generic nontarget method based on liquid chromatography - high resolution mass spectrometry analysis for the evaluation of different wastewater treatment options

A stochastic approach for parameter optimization of feature detection algorithms for non-target screening in mass spectrometry

Feature detection plays a crucial role in non-target screening (NTS), requiring careful selection of algorithm parameters to minimize false positive (FP) features. In this study, a stochastic approach was employed to optimize the parameter settings of feature detection algorithms used in processing high-resolution mass spectrometry data. This approach was demonstrated using four open-source algorithms (OpenMS, SAFD, XCMS, and KPIC2) within the patRoon software platform for processing extracts from drinking water samples spiked with 46 per- and polyfluoroalkyl substances (PFAS). The designed method is based on a stochastic strategy involving random sampling from variable space and the use of Pearson correlation to assess the impact of each parameter on the number of detected suspect analytes. Using our approach, the optimized parameters led to improvement in the algorithm performance by increasing suspect hits in case of SAFD and XCMS, and reducing the total number of detected features (i.e., minimizing FP) for OpenMS. These improvements were further validated on three different drinking water samples as test dataset. The optimized parameters resulted in a lower false discovery rate (FDR%) compared to the default parameters, effectively increasing the detection of true positive features. This work also highlights the necessity of algorithm parameter optimization prior to starting the NTS to reduce the complexity of such datasets.

Instrumental and theoretical advancements in pulsed elution-LC × LC: Investigation of pulse parameters and application to wastewater effluent

Due to the decoupling of the first (1D) and second (2D) dimension in pulsed elution-LC × LC (PE-LC × LC), method development is more flexible and straightforward compared to fast comprehensive LC × LC where the dependencies of key parameters between the two dimensions limits its flexibility. In this study we present a method for pulse generation, which is based on a switching valve alternating between one pump that delivers the gradient and a second pump that delivers low eluotrophic strength for the pause state. Consequently, the dwell volume of the system was circumvented and 7.5, and 3.75 times shorter pulse widths could be generated at flow rates of 0.2, and 0.4 mL/min with satisfactory accuracies between programmed and observed mobile phase composition (relative deviation of 6.0 %). We investigated how key parameters including pulse width and step height, 2D gradient time and flow rate affected the peak capacity in PE-LC × LC. The conditions yielding the highest peak capacity for the PE-LC × LC- high-resolution mass spectrometry (HRMS) system were applied to a wastewater effluent sample. The results were compared to a one dimensional (1D)-LC-HRMS chromatogram. The peak capacity increased with a factor 34 from 112 for the 1D-LC run to 3770 for PE-LC × LC-HRMS after correction for undersampling. The analysis time for PE-LC × LC-HRMS was 12.1 h compared to 67.5 min for the 1D-LC-HRMS run. The purity of the mass spectra improved for PE-LC × LC-HRMS by a factor 2.6 (p-value 3.3 × 10-6) and 2.0 (p-value 2.5 × 10-3) for the low and high collision energy trace compared to the 1D-LC-HRMS analysis. Furthermore, the signal-to-noise ratio (S/N) was 4.2 times higher (range: 0.06-56.7, p-value 3.8 × 10-2) compared to the 1D-LC-HRMS separation based on 42 identified compounds. The improvements in S/N were explained by the lower peak volume obtained in the PE-LC × LC-HRMS.

Metabolites are overlooked in environmental risk assessments and monitoring of pharmaceuticals: The case study of pantoprazole

The proton-pump inhibitor pantoprazole (PPZ) is one of the most consumed pharmaceuticals worldwide. Despite its high usage, reported PPZ concentrations in environmental water samples are comparatively low, which can be explained by the extensive metabolism of PPZ in the human body. Since most previous studies did not consider human PPZ metabolites it can be assumed that the current environmental exposure associated with the application of PPZ is substantially underestimated. In our study, 4'-O-demethyl-PPZ sulfide (M1) was identified as the predominant PPZ metabolite by analyzing urine of a PPZ consumer as well as the influent and effluent of a wastewater treatment plant (WWTP) using liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS). M1 was found to be ubiquitously present in WWTP effluents (max. concentration: 3 000 ng/L) and surface waters in Germany. On average, the surface water concentrations of M1 were approximately 30 times higher than those of the parent compound PPZ. Laboratory scale experiments demonstrated that activated carbon can considerably adsorb M1 und thus improve its removal during wastewater and drinking water treatment. Laboratory ozonation experiments showed a fast oxidation of M1, accompanied by the formation of several ozonation products. Certain ozonation products (identities confirmed via synthesized reference standards) were also detected in water samples collected after ozonation in a full-scale WWTP. Overall lower signal intensities were observed in the effluents of a sand filter and biologically active granular activated carbon filter, suggesting that the compounds were significantly removed during these post-ozonation treatment stages.

Development of an analytical method to quantify N-acyl-homoserine lactones in bacterial cultures, river water, and treated wastewater

N-Acyl-homoserine lactones (AHL) play a major role in the communication of Gram-negative bacteria. They influence processes such as biofilm formation, swarming motility, and bioluminescence in the aquatic environment. A comprehensive analytical method was developed to elucidate the "chemical communication" in pure bacterial cultures as well as in the aquatic environment and engineered environments with biofilms. Due to the high diversity of AHLs and their low concentrations in water, a sensitive and selective LC-ESI-MS/MS method combined with solid-phase extraction was developed for 34 AHLs, optimized and validated to quantify AHLs in bacterial conditioned medium, river water, and treated wastewater. Furthermore, the developed method was optimized in terms of enrichment volume, internal standards, limits of detection, and limits of quantification in several matrices. An unanticipated variety of AHLs was detected in the culture media of Pseudomonas aeruginosa (in total 8 AHLs), Phaeobacter gallaeciensis (in total 6 AHLs), and Methylobacterium mesophilicum (in total 15 AHLs), which to our knowledge have not been described for these bacterial cultures so far. Furthermore, AHLs were detected in river water (in total 5 AHLs) and treated wastewater (in total 3 AHLs). Several detected AHLs were quantified (in total 24) using a standard addition method up to 7.3±1.0 µg/L 3-Oxo-C12-AHL (culture media of P. aeruginosa).

Non-target analysis for water characterization: wastewater treatment impact and selection of relevant features

Non-target analyses were conducted to characterize and compare the molecular profiles (UHPLC-HRMS fingerprint) of water samples from a wastewater treatment plant (WWTP). Inlet and outlet samples were collected from three campaigns spaced 6 months apart in order to highlight common trends. A significant impact of the treatment on the sample fingerprints was shown, with a 65-70% abatement of the number of features detected in the effluent, and more polar, smaller and less intense molecules found overall compared to those in WWTP influent waters. Multivariate analysis (PCA) associated with variations of the features between inlets and outlets showed that features appearing or increasing were correlated with effluents while those disappearing or decreasing were correlated with influents. Finally, effluent features considered as relevant to a potentially adverse effect on aqueous media (i.e. those which appeared or increased or slightly varied from the influent) were highlighted. Three hundred seventy-five features common with the 3 campaigns were thus selected and further characterized. For most of them, elementary composition was found to be C, H, N, O (42%) and C, H, N, O, P (18%). Considering the MS2 spectra and several reference MS2 databases, annotations were proposed for 35 of these relevant features. They include synthetic products, pharmaceuticals and metabolites.

Is Nontarget Analysis Ready for Regulatory Application? Influence of Peak-Picking Algorithms on Data Analysis

The use of peak-picking algorithms is an essential step in all nontarget analysis (NTA) workflows. However, algorithm choice may influence reliability and reproducibility of results. Using a real-world data set, the aim of this study was to investigate how different peak-picking algorithms influence NTA results when exploring temporal and/or spatial trends. For this, drinking water catchment monitoring data, using passive samplers collected twice per year across Southeast Queensland, Australia (n = 18 sites) between 2014 and 2019, was investigated. Data were acquired using liquid chromatography coupled to high-resolution mass spectrometry. Peak picking was performed using five different programs/algorithms (SCIEX OS, MSDial, self-adjusting-feature-detection, two algorithms within MarkerView), keeping parameters identical whenever possible. The resulting feature lists revealed low overlap: 7.2% of features were picked by >3 algorithms, while 74% of features were only picked by a single algorithm. Trend evaluation of the data, using principal component analysis, showed significant variability between the approaches, with only one temporal and no spatial trend being identified by all algorithms. Manual evaluation of features of interest (p-value <0.01, log fold change >2) for one sampling site revealed high rates of incorrectly picked peaks (>70%) for three algorithms. Lower rates (<30%) were observed for the other algorithms, but with the caveat of not successfully picking all internal standards used as quality control. The choice is therefore currently between comprehensive and strict peak picking, either resulting in increased noise or missed peaks, respectively. Reproducibility of NTA results remains challenging when applied for regulatory frameworks.

Mobile phase and column chemistry selection for high sensitivity non-targeted LC/ESI/HRMS screening of water

Systematic selection of mobile phase and column chemistry type can be critical for achieving optimal chromatographic separation, high sensitivity, and low detection limits in liquid chromatography electrospray high resolution mass spectrometry (LC/MS). However, the selection process is challenging for non-targeted screening where the compounds of interest are not preselected nor available for method optimization. To provide general guidance, twenty different mobile phase compositions and four columns were compared for the analysis of 78 compounds with a wide range of physicochemical properties (logP range from -1.46 to 5.48), and analyte sensitivity was compared between methods. The pH, additive type, column, and organic modifier had significant effects on the analyte response factors, and acidic mobile phases (e.g. 0.1% formic acid) yielded highest sensitivity. In some cases, the effect was attributable to the difference in organic modifier content at the time of elution, depending on the mobile phase and column chemistry. Based on these findings, 0.1% formic acid, 0.1% ammonia and 5.0 mM ammonium fluoride were further evaluated for their performance in non-targeted LC/ESI/HRMS analysis of wastewater treatment plan influent and effluent, using a data dependent MS² acquisition and two different data processing workflows (MS-DIAL, patRoon 2.1) to compare number of detected features and sensitivity. Both data-processing workflows indicated that 0.1% formic acid yielded the highest number of features in full scan spectrum (MS¹)^, as well as the highest number of features that triggered fragmentation spectra (MS²) when dynamic exclusion was used.

Novel nontarget LC-HRMS-based approaches for evaluation of drinking water treatment

A conventional evaluation methodology for drinking water pollution focuses on analysing hundreds of compounds, usually by liquid chromatography-tandem mass spectrometry. High-resolution mass spectrometry allows comprehensive evaluation of all detected signals (compounds) based on their elemental composition, intensity, and numbers. We combined target analysis of 192 emerging micropollutants with nontarget (NT) full-scan/MS/MS methods to describe the impact of treatment steps in detail and assess drinking water treatment efficiency without compound identification. The removal efficiency based on target analytes ranged from - 143 to 97%, depending on the treatment section, technologies, and season. The same effect calculated for all signals detected in raw water by the NT method ranged between 19 and 65%. Ozonation increased the removal of micropollutants from the raw water but simultaneously caused the formation of new compounds. Moreover, ozonation byproducts showed higher persistence than products formed during other types of treatment. We evaluated chlorinated and brominated organics detected by specific isotopic patterns within the developed workflow. These compounds indicated anthropogenic raw water pollution but also potential treatment byproducts. We could match some of these compounds with libraries available in the software. We can conclude that passive sampling combined with nontargeted analysis shows to be a promising approach for water treatment control, especially for long-term monitoring of changes in technology lines because passive sampling dramatically reduces the number of samples and provides time-weighted average information for 2 to 4 weeks.

Quantification and characterization of PFASs in suspended particulate matter (SPM) of German rivers using EOF, dTOPA, (non-)target HRMS

In this study, we compare analytical methods for PFAS determination-target analysis, non-target screening (NTS), direct total oxidizable precursor assay (dTOPA) and extractable organically bound fluorine (EOF). Therefore, suspended particulate matter (SPM) samples from German rivers at different locations in time series from 2005 to 2020 were analyzed to investigate temporal and spatially resolved trends. In this study 3 PFAS mass balances approaches were utilized: (i) PFAA target vs. PFAS dTOPA, (ii) PFAS target vs. EOF and (iii) PFAS target vs. PFAS dTOPA vs. organofluorines NTS vs. EOF. Mass balance approach (i) revealed high proportions of precursor substances in SPM samples. For the time resolved analysis an increase from 94% (2005) to 97% in 2019 was observable. Also for the spatial resolved analysis precursor proportions were high with >84% at all sampling sites. Mass balance approach (ii) showed that the unidentified EOF (uEOF) fraction increased over time from 82% (2005) to 99% (2019). Furthermore, along the river courses the uEOF increased. In the combined mass balance approach (iii) using 4 different analytical approaches EOF fractions were further unraveled. The EOF pattern was fully explainable at the sampling sites at Saar and Elbe rivers. For the time resolved analysis, an increased proportion of the EOF was now explainable. However, still 27% of the EOF for the time resolved analysis and 25% of the EOF for the spatial resolved analysis remained unknown. Therefore, in a complementary approach, both the EOF and dTOPA reveal unknown gaps in the PFAS mass balance and are valuable contributions to PFAS risk assessment. Further research is needed to identify organofluorines summarized in the EOF parameter.

Importance of hydraulic travel time for the evaluation of organic compounds removal in bank filtration

The growing global demand for drinking water is driving both the diversification of water supply sources and their sustainability. River bank filtration (RBF) is an excellent option since it strongly reduces the extent of treatment steps compared to direct usage of surface water. Organic micropollutants (e.g. pharmaceuticals) are widely recognized as a hazard in drinking water production from surface water. Due to their potentially high mobility, stability, bioaccumulation and persistency, these substances can pass through RBF-systems. Scientific studies on compound removal and attenuation efficiency of RBF rely on the knowledge of travel time to compare concentrations in the river to the ones in the bank filtrate since water quality in rivers can change rapidly. However, bank filtrate samples represent a mixture of water with different travel times as the flow paths vary. This has not yet been considered in studies of bank filtration removal efficiency for organic micro pollutants. Here we present a method that considers the residence-time distribution of the bank filtrate sample obtained by groundwater modelling to evaluate the removal efficiency of RBF for organic micropollutants. The method was tested in a comprehensive study with 50 samples taken over a one-year-period at a river bank filtration site in Vienna (Austria). Our findings revealed that better coverage of varying river water quality (higher sampling frequency during the period of infiltration) resulted not only in a higher number of compounds considered as removed but also significantly reduced the number of compounds considered to have formed during the RBF process. The application of the presented method indicated that RBF is very effective in removing organic micropollutants. Considering different travel times will provide better models and a better understanding of the potential of RBF for pollutant removal and thus supports its safe application as a solution to the growing demand for drinking water.

Communication Breakdown: Into the Molecular Mechanism of Biofilm Inhibition by CeO2 Nanocrystal Enzyme Mimics and How It Can Be Exploited

Bacterial biofilm formation is a huge problem in industry and medicine. Therefore, the discovery of anti-biofilm agents may hold great promise. Biofilm formation is usually a consequence of bacterial cell-cell communication, a process called quorum sensing (QS). CeO₂ nanocrystals (NCs) have been established as haloperoxidase (HPO) mimics and ecologically beneficial biofilm inhibitors. They were suggested to interfere with QS, a mechanism termed quorum quenching (QQ), but their molecular mechanism remained elusive. We show that CeO₂ NCs are effective QQ agents, inactivating QS signals by bromination. Catalytic bromination of 3-oxo-C₁₂-AHL a QS signaling compound used by Pseudomonas aeruginosa, was detected in the presence of CeO₂ NCs, bromide ions, and hydrogen peroxide. Brominated acyl-homoserine lactones (AHLs) no longer act as QS signals but were not detected in the bacterial cultures. Externally added brominated AHLs also disappeared in P. aeruginosa cultures within minutes of their addition, indicating that they are rapidly degraded by the bacteria. Moreover, we detected the catalytic bromination of 2-heptyl-1-hydroxyquinolin-4(1H)-one (HQNO), a multifunctional non-AHL QS signal from P. aeruginosa with antibacterial and algicidal properties controlling the expression of many virulence genes. Brominated HQNO was not degraded by the bacteria in vivo. The repression of the Pseudomonas quinolone signal (PQS) production and biofilm formation in P. aeruginosa through the catalytic formation of Br-HQNO on surfaces with coatings containing CeO₂ enzyme mimics validates the non-toxic strategy for the development of anti-infectives.

Obtaining clean and informative mass spectra from complex chromatographic and high-resolution all-ions-fragmentation data by nonnegative parallel factor analysis 2

A major challenge in processing of complex data obtained from chromatography hyphenated to mass spectrometry is to resolve chromatographically co-eluting compounds. In this study, we present a workflow for the resolution of ultra-high pressure liquid chromatography high-resolution mass spectrometry data obtained by the broadband data-independent acquisition MS^E operation (UHPLCHRMS^E). The workflow is based on a recently introduced algorithm for Parallel Factor Analysis 2 (PARAFAC2) that allows to enforce non-negativity on all the model coefficients. The workflow was tested on three sets of UHPLC-HRMS^E measurements from a Lupinus angustifolius L. crop field study, which included plant tissue samples, soil samples and samples from drainage water as well as stream water close to the field. The three datasets included 93, 59, and 75 chromatographic runs in total for the plant, soil and water batches, respectively. Nonnegative-PARAFAC2 models were fitted on the summed high and low energy (HE and LE) traces on chromatographic intervals corresponding to spiked standard for the three sample sets independently. In soil and plant samples, 13 out of 14 spiked standards were resolved by NN-PARAFAC2 even in presence of chromatographic co-elution, and their mass spectral loadings could be matched to a reference spectrum. In contrast, only seven spiked standards were correctly resolved and matched for the water samples because a higher chromatographic baseline rendered the data noisier. The results show that the workflow we present can provide improved mass spectral selectivity for data-independent acquisition compared to using the raw mass spectra and can be used to match fragment ions from the HE trace, and precursor and adduct ions from the LE trace even in presence of co-eluting compounds.

Non-targeted analysis with high-resolution mass spectrometry for investigation of riverbank filtration processes

A fully non-targeted analytical workflow for the investigation of a riverbank filtration site located at the river Danube has been developed and applied. Variations of compound intensities at different sampling locations of the riverbank filtration site and, for a single production well, over a monitoring period of one year have been investigated using liquid chromatography combined with time-of-flight-mass spectrometry followed by evaluation via non-targeted data analysis. Internal standardization and appropriate quality control strategies have been implemented into the workflow for reduction of possible methodological biases influencing data interpretation. Emphasis was placed on the assessment of different blank elimination steps and the final blank elimination strategy is reported. The spatial study of the selected riverbank filtration site revealed a homogenous composition of the filtered water sampled at 11 different locations across the 32,000 m2 site, except for one sampling location in a zone of the aquifer, which was only weakly connected to the well field in terms of hydrogeological conditions. The examination of time-dependent changes of the composition of surface and groundwater obtained at the riverbank filtration system revealed that the non-targeted workflow is fit-for-purpose regarding the assessment the stability of filtration efficiency and compound residence time in the riverbank filtration compartment. In total, 677 compounds were selected for the investigation of the time-dependent variations of the filtration process. Analysis of the signal intensities of these compounds revealed that the riverbank filtration is significantly reducing the intensity and number of compounds present in surface water over a wide polarity range. In addition, the method enabled the determination of compound residence times in the riverbank filtration system ranging from 5 to 7 days.

From data to reliable conclusions: Identification and comparison of persistent micropollutants and transformation products in 37 wastewater samples by non-target screening prioritization

In this study, micropollutants in wastewater effluents were prioritized by monitoring the composition of influent and effluent wastewater by liquid chromatography - high-resolution mass spectrometry (LCHRMS) non-target screening (NTS) analysis. The study shows how important data pre-processing and filtering of raw data is to produce reliable NTS data for comparison of compounds between many samples (37 wastewater samples) analyzed at different times. Triplicate injections were critical for reducing the number of false-positive detections. Intensity drift corrections within and between batches analyzed months apart made peak intensities comparable across samples. Adjustment of the feature detection threshold was shown to be important, due to large intensity variations for low abundance compounds across batches. When the threshold correction cut-offs, or the filtering of relevant compounds by the occurrence frequency, were too stringent, a high number of false positive transformation products (TPs) were reported. We also showed that matrix effect correction by internal standards can over- or under-correct the intensity for unknown compounds, thus the TIC matrix effect correction was shown as an additional tool for a retention time dependent matrix effect correction. After these preprocessing and filtering steps, we identified 78 prioritized compounds, of which 36 were persistent compounds, defined as compounds with a reduction in peak intensity between influent and effluent wastewater <50%, and 13 compounds were defined as TPs because they occurred solely in the effluent samples. Some examples of persistent compounds are 1,3-diphenylguanidine, amisulpride and the human metabolites from losartan, verapamil and methadone. To our knowledge, nine of the identified TPs have not been previously described in effluent wastewater. The TPs were derived from metoprolol, fexofenadine, DEET and losartan. The screening of all identified compounds in effluent samples from eight wastewater treatment plants (WWTPs) showed that potential drugs of abuse, anti-psychotic and anti-depressant drugs were predominant in the capital city region, whereas the anti-epileptic agents and agricultural pesticides were dominant in more rural areas.

Chemical Characterization and Non-targeted Analysis of Medical Device Extracts: A Review of Current Approaches, Gaps, and Emerging Practices

The developers of medical devices evaluate the biocompatibility of their device prior to FDA's review and subsequent introduction to the market. Chemical characterization, described in ISO 10993-18:2020, can generate information for toxicological risk assessment and is an alternative approach for addressing some biocompatibility end points (e.g., systemic toxicity, genotoxicity, carcinogenicity, reproductive/developmental toxicity) that can reduce the time and cost of testing and the need for animal testing. Additionally, chemical characterization can be used to determine whether modifications to the materials and manufacturing processes alter the chemistry of a patient-contacting device to an extent that could impact device safety. Extractables testing is one approach to chemical characterization that employs combinations of non-targeted analysis, non-targeted screening, and/or targeted analysis to establish the identities and quantities of the various chemical constituents that can be released from a device. Due to the difficulty in obtaining a priori information on all the constituents in finished devices, information generation strategies in the form of analytical chemistry testing are often used. Identified and quantified extractables are then assessed using toxicological risk assessment approaches to determine if reported quantities are sufficiently low to overcome the need for further chemical analysis, biological evaluation of select end points, or risk control. For extractables studies to be useful as a screening tool, comprehensive and reliable non-targeted methods are needed. Although non-targeted methods have been adopted by many laboratories, they are laboratory-specific and require expensive analytical instruments and advanced technical expertise to perform. In this Perspective, we describe the elements of extractables studies and provide an overview of the current practices, identified gaps, and emerging practices that may be adopted on a wider scale in the future. This Perspective is outlined according to the steps of an extractables study: information gathering, extraction, extract sample processing, system selection, qualification, quantification, and identification.

Open-source feature detection for non-target LC-MS analytics

RATIONALE

Non-target screening techniques using high-resolution mass spectrometers become more and more important for environmental sciences. Highly reliable and sophisticated software solutions are required to deal with the large amount of data obtained from such analyses.

METHODS

Processing of high-resolution LC-HRMS data was performed upon conversion into an open, XML-based data format followed by an automated assignment of chromatographic peaks using the open-source programming language R. Raw data from three different LC-HRMS systems were processed as a proof of principle.

RESULTS

We present a simple and straightforward algorithm to extract chromatographic peaks from previously m/z-centroided data based on the open-source programming language R and C++. The working principle and processing parameters are explained in detail. A ready-to-use script is provided in the supporting information.

CONCLUSIONS

The developed algorithm enables a comprehensible automated peak picking of non-target LC-MS data. Application to three completely different HRMS raw data files showed reasonable False Positives and False Negatives detection and moderate calculation times.

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.

What is in Nigerian waters? Target and non-target screening analysis for organic chemicals

Emerging organic contaminants (e.g., active pharmaceutical ingredients and personal care products ingredients) are ubiquitous in the environment and potentially harmful to ecosystems, have gained increasing public attention worldwide. Nevertheless, there is a scarcity of data on these contaminants in Africa. In this study, various types of water samples (wastewater, surface water and tap water) collected from Lagos, Nigeria were analyzed for these chemicals by both target and non-target analysis on an UHPLC-Orbitrap-MS/MS. In total, 109 compounds were identified by non-target screening using the online database mzCloud. Level 1 identification confidence was achieved for 13 compounds for which reference standards were available and level 2 was achieved for the rest. In the quantitative analysis, 18 of 38 target compounds were detected, including the parent compounds and their metabolites. Acetaminophen, sulfamethoxazole, acesulfame, and caffeine were detected in all samples with their highest concentrations at 8000, 5300, 16, and 7700 μg/L in wastewater, 140000, 3300, 7.7, and 12000 μg/L in surface water, and 66, 62, 0.17 and 1000 μg/L in tap water, respectively. The occurrence of psychoactive substances, anticancer treatments, antiretrovirals, antihypertensives, antidiabetics and their metabolites were reported in Nigeria for the first time. These results indicate poor wastewater treatment and management in Nigeria, and provide a preliminary profile of organic contaminants occurring in Nigerian waters. The findings from this study urge more future research on chemical pollution in the aquatic environments in Nigeria.

Towards comprehensive non-target screening using heart-cut two-dimensional liquid chromatography for the analysis of organic atmospheric tracers in ice cores

Non-target screening of secondary organic aerosol compounds in ice cores is used to reconstruct atmospheric conditions and sources and is a valuable tool to elucidate the chemical profiles of samples with the aim to obtain as much information as possible from one mass spectrometric measurement. The coupling of mass spectrometry to chromatography limits the results of a non-target screening to signals of compounds within a certain polarity range based on the utilized stationary phases of the columns. Comprehensive two-dimensional liquid chromatography (LCxLC) introduces a second column of different functionality to enable the analysis of a broader range of analytes. Conventional LCxLC requires complex instrumental setups and is difficult to implement for most laboratories. In this work we demonstrate an approach to approximate a comprehensive non-target screening using a simple instrumental setup employing two columns of orthogonal functionalities (HILIC and reversed-phase), an additional pump, and an additional six-port valve. The void volume of the first dimension is transferred to the reversed-phase column to analyze low-polarity compounds during the re-equilibration of the HILIC. Method validation showed adequate repeatability and detection limits for two selected void volume markers and application to snow samples collected at the high-alpine research station Jungfraujoch yielded a total of 270 signals. Comparison to the one-dimensional HILIC approach revealed 175 signals exclusively detected in the two-dimensional method, of which 23 were detected in the second dimension. Detailed analysis of the chemical composition showed consistency with expected compounds in snow samples like lignin or cellulose combustion products from biomass burning or secondary organic aerosol constituents. The results confirmed that one-dimensional chromatography was not sufficient to cover the entire range of compounds and the developed two-dimensional approach will improve the information content from non-target screening while maintaining time of analysis and a simple instrumental setup.

Evaluation of Sample Preparation Methods for Non-Target Screening of Organic Micropollutants in Urban Waters Using High-Resolution Mass Spectrometry

Non-target screening (NTS) has gained interest in recent years for environmental monitoring purposes because it enables the analysis of a large number of pollutants without predefined lists of molecules. However, sample preparation methods are diverse, and few have been systematically compared in terms of the amount and relevance of the information obtained by subsequent NTS analysis. The goal of this work was to compare a large number of sample extraction methods for the unknown screening of urban waters. Various phases were tested for the solid-phase extraction of micropollutants from these waters. The evaluation of the different phases was assessed by statistical analysis based on the number of detected molecules, their range, and physicochemical properties (molecular weight, standard recoveries, polarity, and optical properties). Though each cartridge provided its own advantages, a multilayer cartridge combining several phases gathered more information in one single extraction by benefiting from the specificity of each one of its layers.

Screening priority indicator pollutants in full-scale wastewater treatment plants by non-target analysis

Wastewater treatment plants (WWTPs) are the main sources of emerging contaminants (ECs) in aquatic environment. However, the standards for limiting emerging pollutants in effluent are extremely lacking. We investigated the occurrence and removal of emerging pollutants in 16 WWTPs in China using non-target analysis. 568 substances screened out were divided into 9 kinds including 167 pharmaceuticals, 113 natural substances, 85 pesticides, 86 endogenous substances, 64 chemical raw materials, 14 personal care products, 17 food additives, 6 hormones and 16 others. And they were divided into 5 fates. Pesticides and pharmaceutical compounds seemed to be the most notable categories, the kinds detected in each sample is the largest compared with other compounds. Besides, the average removal rate of pesticides and pharmaceuticals in all WWTPs were the lowest, at 9.54% and 23.77%, respectively. Priority pollutants were screened by considering distribution of pollutants with different fates. Pollutants with the same fate especially "consistent" in different WWTPs had attracted attention. 4 potential priority pollutants including metoprolol, carbamazepine, 10, 11-dihydro-10, 11-dihydroxycarbamazepine and irbesartan were proposed. And it was found that the 4 compounds, "consistent suspects" and "consistent non-targets" had similar rankings of removal rate in 16 WWTPs, which can reflect the performance of different WWTPs.

Enhanced in vitro toxicity of plastic leachates after UV irradiation

Plastics can release numerous chemicals and thereby, contribute to the chemical pollution in aquatic systems. To which extent environmental degradation processes influence the release of plastic chemicals, is currently unknown and subject of research. We therefore evaluated aqueous leachates of 12 differently formulated plastics (e.g., pre-production, post-industrial and recycled pellets as well as final products) using in vitro bioassays and chemical analysis via LC-HRMS nontarget approach. We weathered these plastics by UV irradiation (UV-C and UV-A/B) under laboratory conditions in dryness and a subsequent leaching period in ultrapure water ('atmospheric' weathering) or directly in water ('aquatic' weathering, UV-A/B_aq). A dark control (DC) without UV light served as a reference treatment. Some plastics triggered several toxicological endpoints (low-density polyethylene recyclate (LDPE-R), starch blend (SB), bio-based polybutylene succinate (Bio-PBS) and polyvinyl chloride (PVC)), whereas others caused little to no effects (polyethylene terephthalate (PET), polystyrene (PS), polypropylene (PP) and LDPE). UV irradiation enhanced the plastics' toxicity, even for samples initially evaluated as toxicologically inconspicuous. The plastic samples caused oxidative stress (85%), baseline toxicity (42%), antiestrogenicity (40%) and antiandrogenicity (27%). Positive findings were measured after UV-C (63%) and UV-A/B_aq (50%) treatments, followed by UV-A/B (48%) and DC (33%). Overall, we detected between 42 (DC) and 2896 (UV-A/B_aq) chemical compounds. Our study demonstrates that differently formulated plastics leach toxic chemicals. UV exacerbates the plastics' toxicity by either generating active compounds and/or by facilitating their release. UV light even leads to the release of bioactive compounds from plastics of low chemical complexity. To prevent the exposure to plastic-associated chemicals, the application of chemicals could be reduced to a minimum, while on a regulatory level the evaluation of plastic eluates could be another focal point next to singular compounds.

Suspect screening workflow comparison for the analysis of organic xenobiotics in environmental water samples

Suspect screening techniques are able to determine a broader range of compounds than traditional target analysis. However, the performance of the suspect techniques relies on the procedures implemented for peak annotation and for this, the list of potential candidates is clearly a limiting factor. In order to study this effect on the number of compounds annotated in environmental water samples, a method was validated in terms of absolute recoveries, limits of quantification and identification, as well as the peak picking capability of the software (Compound Discoverer 2.1) using a target list of 178 xenobiotics. Four suspect screening workflows using different suspect lists were compared: (i) the Stoffident list, (ii) all the NORMAN lists, (iii) suspects containing C, H, O, N, S, P, F or Cl in their molecular formula with more than 10 references in Chemspider and (iv) the mzCloud library. The results were compared in terms of the number of annotated compounds at each confidence level. The same 8 compounds (atenolol, caffeine, caprolactam, carbendazim, cotinine, diclofenac, propyphenazone and trimetoprim) were annotated at the highest confidence level using the four workflows. Remarkable differences were observed for lower confidence levels but only 4 features were annotated at different levels by the four workflows. While the third approach provided the highest number of annotated features, the workflow based on the mzCloud library rendered satisfactory results with a simpler approach. Finally, this latter approach was extended to the analysis of organic xenobiotics in different environmental water samples.

Correction of Matrix Effects for Reliable Non-target Screening LC-ESI-MS Analysis of Wastewater

Matrix effects are well-known challenges for accurate and comparable measurements with liquid chromatography (LC) electrospray ionization mass spectrometry (ESI-MS). This study describes a three-step method to evaluate and compensate for matrix effects in enriched wastewater extracts using LC ESI-high-resolution MS (HRMS). As a first step, the "dilute and shoot" approach was used to determine the optimal relative enrichment factor (REF) for a direct comparison between wastewater influent (REF 10) and effluent (REF 50) extracts. However, the rapid decrease in the number of non-target compounds detected with increasing dilution leads to the need for a correction of the matrix effect for analyzing samples with higher REFs. As a second step, the observed matrix effect at higher REFs was corrected by the retention time-dependent matrix effect. A new scaling (TiChri scale) of the matrix effect was introduced, which demonstrates that the total ion chromatogram (TIC) predicts the matrix effect as effectively as post-column infusion (PCI) approaches; thus, the average median matrix effect was improved from -65 to 1% for influent (REF 100) and from -46 to -2% for effluent extracts (REF 250). The TIC traces for concentrated (REF 250) influent and effluent samples were successfully used to correct the matrix effects and allowed the extent of micropollutant degradation in three WWTPs to be quantified. As a final step, the residual structure-specific matrix effect was predicted and corrected by quantitative structure-property relationships (QSPR), which led to a further correction of the matrix effect to 0 ± 7% for 65 compounds.

Suspect and non-target screening: the last frontier in environmental analysis

Suspect and non-target screening (SNTS) techniques are arising as new analytical strategies useful to disentangle the environmental occurrence of the thousands of exogenous chemicals present in our ecosystems. The unbiased discovery of the wide number of substances present over environmental analysis needs to find a consensus with powerful technical and computational requirements, as well as with the time-consuming unequivocal identification of discovered analytes. Within these boundaries, the potential applications of SNTS include the studies of environmental pollution in aquatic, atmospheric, solid and biological samples, the assessment of new compounds, transformation products and metabolites, contaminant prioritization, bioremediation or soil/water treatment evaluation, and retrospective data analysis, among many others. In this review, we evaluate the state of the art of SNTS techniques going over the normalized workflow from sampling and sample treatment to instrumental analysis, data processing and a brief review of the more recent applications of SNTS in environmental occurrence and exposure to xenobiotics. The main issues related to harmonization and knowledge gaps are critically evaluated and the challenges of their implementation are assessed in order to ensure a proper use of these promising techniques in the near future.

Target, suspect and non-target screening analysis from wastewater treatment plant effluents to drinking water using collision cross section values as additional identification criterion

The anthropogenic entry of organic micropollutants into the aquatic environment leads to a potential risk for drinking water resources and the drinking water itself. Therefore, sensitive screening analysis methods are needed to monitor the raw and drinking water quality continuously. Non-target screening analysis has been shown to allow for a more comprehensive investigation of drinking water processes compared to target analysis alone. However, non-target screening is challenging due to the many features that can be detected. Thus, data processing techniques to reduce the high number of features are necessary, and prioritization techniques are important to find the features of interest for identification, as identification of unknown substances is challenging as well. In this study, a drinking water production process, where drinking water is supplied by a water reservoir, was investigated. Since the water reservoir provides surface water, which is anthropogenically influenced by wastewater treatment plant (WWTP) effluents, substances originating from WWTP effluents and reaching the drinking water were investigated, because this indicates that they cannot be removed by the drinking water production process. For this purpose, ultra-performance liquid chromatography coupled with an ion-mobility high-resolution mass spectrometer (UPLC-IM-HRMS) was used in a combined approach including target, suspect and non-target screening analysis to identify known and unknown substances. Additionally, the role of ion-mobility-derived collision cross sections (CCS) in identification is discussed. To that end, six samples (two WWTP effluent samples, a surface water sample that received the effluents, a raw water sample from a downstream water reservoir, a process sample and the drinking water) were analyzed. Positive findings for a total of 60 substances in at least one sample were obtained through quantitative screening. Sixty-five percent (15 out of 23) of the identified substances in the drinking water sample were pharmaceuticals and transformation products of pharmaceuticals. Using suspect screening, further 33 substances were tentatively identified in one or more samples, where for 19 of these substances, CCS values could be compared with CCS values from the literature, which supported the tentative identification. Eight substances were identified by reference standards. In the non-target screening, a total of ten features detected in all six samples were prioritized, whereby metoprolol acid/atenolol acid (a transformation product of the two β-blockers metoprolol and atenolol) and 1,3-benzothiazol-2-sulfonic acid (a transformation product of the vulcanization accelerator 2-mercaptobenzothiazole) were identified with reference standards. Overall, this study demonstrates the added value of a comprehensive water monitoring approach based on UPLC-IM-HRMS analysis.

Suspect and non-target screening of reuse water by large-volume injection liquid chromatography and quadrupole time-of-flight mass spectrometry

Eight samples were obtained to characterize the chemical loads in water recycled for reuse applications. The sources included stormwater, rooftop runoff, wastewater, mixed water, and drinking water as a comparison. The water was reused for irrigation, cleaning, toilet flushing, and cooling purposes. Large-volume injection (650 μL) high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry were employed to separate and detect features by suspect and non-target screening. The instrumental method had the advantage that no sample extractions were required prior to analysis. Two chromatographic methods were developed to separate positive- and negative-ionizing compounds and retention time models were developed for both. Retention time models provide an additional measure of confidence for probable and tentative identifications. The two models had predictive R²-which indicates how well the models predicts new observations-of 0.87. After data-reduction, the number of features detected in the samples ranged from 304 to 1513. Feature metrics such as the average response-per-feature provided a simple method to characterize similarities and differences between samples. Additionally, a statistical comparison was performed by principal component analysis. Of the 97 suspect-screening compounds, 20 were positively identified. Benzotriazole/benzothiazole-derivatives and per- and poly-fluoroalkyl substances were the most frequently detectedcompounds during suspect screening. Other compounds detected included pharmaceuticals, drug metabolites, and sucralose. Features were prioritized for non-target analysis based on in-house library matches, magnitude of response, and frequency of occurrence. Fifty-five unique compounds were positively identified via non-target analysis. The identified compounds included 17 pharmaceuticals, 17 pesticides, 13 industrial compounds, four personal-use compounds, and four biological compounds.

Seasonal performance assessment of four riverbank filtration sites by combined non-target and effect-directed analysis

Targeting the most relevant organic micropollutants (OMP) in routine analysis appears difficult due to formation of transformation products of unknown concentration or toxicity. Performance assessment of water purification processes is still based upon limited target data. Therefore, we broadened the assessment of the removal efficiencies with combined non-target and effect-directed analysis at four riverbank filtration (RBF) sites in Germany. To assess micropollutant elimination, constancy and formation during different seasons, considering local redox conditions, travel distances and total component number in the river, non-target analysis features were grouped into categories. Furthermore, RBF sites were investigated with four endpoints (baseline toxicity, acetylcholinesterase inhibition, antibiotic effects and estrogenic effects) for thin-layer chromatography - effect-directed analysis for the first time. Results showed elimination or reduction of many features and effects, but also constancy and formation of varying proportions. Fall river samples showed precipitation-caused dilution in both tests. Spring samples showed increased effects only in acetylcholinesterase inhibition and estrogenic effects, probably due to phytoestrogens or algae bloom during vegetation period. Sites were ranked considering the total number of features, group proportions, seasonal variations and intensity and number of effects in abstraction wells. Oxic conditions and low initial component numbers in the river (Ruhr sites) resulted in less effects and fewer formations. Longer travel distances were important for a more efficient reduction of effects and features. Combination of non-target and effect-directed analysis proved to be valuable for a more comprehensive assessment of process performance beyond target analysis as also unknown OMP are observed with both methods.

High-throughput multi-residue quantification of contaminants of emerging concern in wastewaters enabled using direct injection liquid chromatography-tandem mass spectrometry

A rapid quantitative method for 135 contaminants of emerging concern (CECs) in untreated wastewater enabled with direct injection liquid chromatography-tandem mass spectrometry is presented. All compounds were analysed within 5 min on a short biphenyl cartridge using only 10 μL of filtered sample per injection. Up to 76 compounds were monitored simultaneously during the gradient (including mostly two transitions per compound and stable isotope-labelled analogues) while yielding >10 data points per peak. Evaluation of seven solid phase extraction sorbents showed no advantage for wastewater matrix removal. Excellent linearity, range, accuracy and precision was achieved for most compounds. Matrix effects were <11 % and detection limits were <30 ng L^-1 on average. Application to untreated wastewater samples from three wastewater treatment works in the UK, USA and Mexico, enabled quantification of 56 compounds. Banned and EU 'watch-list' substances are critically discussed, including pesticides, macrolide antibiotics, diclofenac, illicit drugs as well as multiple pharmaceuticals and biocides. This high-throughput method sets a new standard for the speedy and confident determination of over a hundred CECs in wastewater at the part-per-trillion level, as demonstrated by performing over 260 injections per day.

High-throughput wastewater analysis for substance use assessment in central New York during the COVID-19 pandemic

Wastewater entering sewer networks represents a unique source of pooled epidemiological information. In this study, we coupled online solid-phase extraction with liquid chromatography-high resolution mass spectrometry to achieve high-throughput analysis of health and lifestyle-related substances in untreated municipal wastewater during the coronavirus disease 2019 (COVID-19) pandemic. Twenty-six substances were identified and quantified in influent samples collected from six wastewater treatment plants during the COVID-19 pandemic in central New York. Over a 12 week sampling period, the mean summed consumption rate of six major substance groups (i.e., antidepressants, antiepileptics, antihistamines, antihypertensives, synthetic opioids, and central nervous system stimulants) correlated with disparities in household income, marital status, and age of the contributing populations as well as the detection frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater and the COVID-19 test positivity in the studied sewersheds. Nontarget screening revealed the covariation of piperine, a nontarget substance, with SARS-CoV-2 RNA in wastewater collected from one of the sewersheds. Overall, this proof-of-the-concept study demonstrated the utility of high-throughput wastewater analysis for assessing the population-level substance use patterns during a public health crisis such as COVID-19.

Focused ultrasound-based extraction for target analysis and suspect screening of organic xenobiotics in fish muscle

The development of multitarget and/or suspect screening methods for the analysis of xenobiotics in fish samples is compulsory due to the lack of works in the literature where a deep evaluation of the variables affecting extraction and clean-up steps is performed. The aim of the present work was to optimize and validate a multitarget (180 compounds) method for the analysis of priority and emerging xenobiotics in fish muscle using focused ultrasound-assisted solid-liquid extraction. From the different extraction solvents studied, a single extraction in cold acetonitrile rendered the best consensus results in terms of absolute recoveries and the number of target compounds extracted. Matrix effect was minimized using commercially available Captiva ND-Lipid filters, which provided clean extracts and satisfactory repeatability compared to other approaches. Absolute recoveries were corrected using matrix-matched calibration and apparent recoveries in the 43%-105%, 73%-131% and 78%-128% ranges were obtained at low (20 ng g^-1), medium (100 ng g^-1), and high (200 ng g^-1) spiking levels, respectively. A 60% of the xenobiotics showed limits of identification lower than 20 ng g^-1. The developed method was successfully applied to the quantification and suspect screening of samples bought in a local market (hake, gilt-head bream, sea bass and prawn) and fished (thicklip grey mullet) at the Urdaibai estuary (north of Spain). Food additives, antiparasitic drugs and PFOS were quantified at ng g^-1 level. Moreover, the targeted method was extended to the suspect screening, revealing the presence of plastic related products (caprolactam, phthalates, polyethylenglycols), pharmaceutical products (albendazole, mebendazole, valpromide) and pesticides or insect repellents (icaridin, myristyl sulfate, nootkatone). Therefore, FUSLE in cold acetonitrile combined with Captiva ND-Lipid filters and liquid chromatography tandem high-resolution mass spectrometry (LC-q-Orbitrap) were successfully applied to both multitarget quantitative analysis and suspect screening of approx. 17,800 compounds.

Evaluation of Nontarget Long-Term LC-HRMS Time Series Data Using Multivariate Statistical Approaches

The use of liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has steadily increased in many application fields ranging from metabolomics to environmental science. HRMS data are frequently used for nontarget screening (NTS), i.e., the search for compounds that are not previously known and where no reference substances are available. However, the large quantity of data produced by NTS analytical workflows makes data interpretation and time-dependent monitoring of samples very sophisticated and necessitates exploiting chemometric data processing techniques. Consequently, in this study, a prioritization method to handle time series in nontarget data was established. As proof of concept, industrial wastewater was investigated. As routine industrial wastewater analyses monitor the occurrence of a limited number of targeted water contaminants, NTS provides the opportunity to detect also unknown trace organic compounds (TrOCs) that are not in the focus of routine target analysis. The developed prioritization method enables reducing raw data and including identification of prioritized unknown contaminants. To that end, a five-month time series for industrial wastewaters was utilized, analyzed by liquid chromatography-time-of-flight mass spectrometry (LC-qTOF-MS), and evaluated by NTS. Following peak detection, alignment, grouping, and blank subtraction, 3303 features were obtained of wastewater treatment plant (WWTP) influent samples. Subsequently, two complementary ways for exploratory time trend detection and feature prioritization are proposed. Therefore, following a prefiltering step, featurewise principal component analysis (PCA) and groupwise PCA (GPCA) of the matrix (temporal wise) were used to annotate trends of relevant wastewater contaminants. With sparse factorization of data matrices using GPCA, groups of correlated features/mass fragments or adducts were detected, recovered, and prioritized. Similarities and differences in the chemical composition of wastewater samples were observed over time to reveal hidden factors accounting for the structure of the data. The detected features were reduced to 130 relevant time trends related to TrOCs for identification. Exemplarily, as proof of concept, one nontarget pollutant was identified as N-methylpyrrolidone. The developed chemometric strategies of this study are not only suitable for industrial wastewater but also could be efficiently employed for time trend exploration in other scientific fields.

Unraveling longitudinal pollution patterns of organic micropollutants in a river by non-target screening and cluster analysis

The pollution of aquatic ecosystems with complex and largely unknown mixtures of organic micropollutants is not sufficiently addressed with current monitoring strategies based on target screening methods. In this study, we implemented an open-source workflow based on non-target screening to unravel longitudinal pollution patterns of organic micropollutants along a river course. The 47 km long Holtemme River, a tributary of the Bode River (both Saxony-Anhalt, Germany), was used as a case study. Sixteen grab samples were taken along the river and analyzed by liquid chromatography coupled to high-resolution mass spectrometry. We applied a cluster analysis specifically designed for longitudinal data sets to identify spatial pollutant patterns and prioritize peaks for compound identification. Three main pollution patterns were identified representing pollutants entering a) from wastewater treatment plants, b) at the confluence with the Bode River and c) from diffuse and random inputs via small point sources and groundwater input. By further sub-clustering of the main patterns, source-related fingerprints were revealed. The main patterns were characterized by specific isotopologue signatures and the abundance of peaks in homologue series representing the major (pollution) sources. Furthermore, we identified 25 out of 38 representative compounds for the patterns by structure elucidation. The workflow represents an important contribution to the ongoing attempts to understand, monitor, prioritize and manage complex environmental mixtures and may be applied to other settings.

Application of a non-target workflow for the identification of specific contaminants using the example of the Nidda river basin

Non-target screening of water samples from the Nidda river basin in central Germany was conducted with the goal to identify previously unknown chemical contaminants and their emission sources. The focus was on organic, water-borne contaminants which were not typical to municipal wastewater. Grab samples of river water from 13 locations on the Nidda and 15 of its tributaries, in sum 112 samples, were analysed with high resolution LC-QToF-MS/MS. To facilitate the identification of substances, features originating from the same compound such as adducts and isotopologues as well as in-source fragments and species with multiple charge states were registered and grouped by a componentization step utilizing both retention times and peak shapes of the features to combine them in a single component. This led to a reduction of the number of features by an average of 1235 per sample (46%). These grouped features were prioritized if these were detected only in specific tributaries or specific river sections, reducing the number of components by an average of 913 per sample (78%). In addition, grouped features were labelled as typically found in municipal wastewater by combining data from 16 wastewater treatment plants located across Germany and Switzerland and comparing this to components detected in the Nidda basin. These were removed, leading to a further reduction of components by an average of 72 per sample (30%) for an average total reduction of 2536 per sample (93%). Finally, nine compounds, with emission sources in three specific tributaries, were identified, including the textile additive Nylostab S-EED®, which was previously not known to be an environmental contaminant, as well as naturally occurring compounds such as highly toxic microcystins.

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.

Suspect and non-target screening of acutely toxic Prymnesium parvum

Harmful algal blooms (HABs) are increasing in frequency, magnitude, and duration around the world. Prymnesium parvum is a HAB species known to cause massive fish kills, but the toxin(s) it produces contributing to this acute toxicity to fish have not been confirmed. In the present study, a 2 × 2 factorial design was employed to examine influences of salinity (2.4 or 5 ppt) and nutrient limitation (f/2 or f/8) on P. parvum acute toxicity to fish and produced molecules. Acute toxicity (LC50) of these cultures, following a 48-h mortality assay, ranged from 10,213 to 96,816 cells mL-1. Non-targeted analysis was performed using liquid chromatography high-resolution mass spectrometry (LC-HRMS) to investigate compounds contributing to the differential toxicological responses. When P. parvum elicited toxicity to fish, suspect screening confirmed the presence of several prymnesins, and the peak area of PRM-A (3 Cl; prymnesin2aglycone) was significantly (p < 0.05) and positively related to acute toxicity. In addition, a non-targeted approach to highlighting peaks that differ between two chemical fingerprints was developed, termed a relative difference plot, and used to search for peaks co-varying with P. parvum induced acute toxicity to fish. Several peaks were highlighted along with the prymnesins identified through suspect screening when acute toxicity to fish was observed.

Assessing accuracy, precision and selectivity using quality controls for non-targeted analysis

The benchmarks to assess reproducibility are not well defined for non-target analysis. Parameters to evaluate analytical performance, such as accuracy, precision and selectivity, are well defined for target analysis, but remain elusive for non-target screening analysis. In this study, quality control (QC) guidelines are proposed to assure reliable data in non-target screening methodologies using a simple set of standards. Workflow reproducibility was assessed using an in-house QC mixture containing selected compounds with a wide range of polarity that can be detected either by electrospray ionization (ESI) in positive or negative mode. The analysis was performed by online solid phase extraction (SPE) liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS). Data processing was done by a commercially available software, Compound Discoverer v. 3.0 using an environmental working template, which searched a multitude of databases, including Chemspider, EPA Toxcast, MzCloud among others. We have specifically evaluated method specificity, precision, accuracy and reproducibility in terms of peak area and retention time variability, true positive identification rate, intraday (within days) and interday (consecutive days) variations and the use of QC samples to reduce false positives. The method showed a satisfactory accuracy with an identification rate of ≥70% for most of the QC compounds. Precision estimated based on peak area relative standard deviation (RSD) ranged between 30 and 50% for most of the compounds. Data normalization to a single internal standard did not improve peak area variability. Retention time precision showed great repeatability and reproducibility (RSD ≤ 5%). In addition, a simple model of RT vs log K_ow was designed based on our QC mixtures to efficiently reduced false positives by an average of 49.1%.

Comparing mass, retention time and tandem mass spectra as criteria for the automated screening of small molecules in aqueous environmental samples analyzed by liquid chromatography/quadrupole time-of-flight tandem mass spectrometry

RATIONALE

The adoption of database screening using high-resolution liquid chromatography/mass spectrometry data is promising as a river water monitoring and surveillance tool but depends on the ability to perform reliable data processing on a large number of samples in a unified workflow. Strategies to minimize errors have been proposed but automated procedures are rare.

METHODS

High-resolution LC/ESI-QTOFMS/MS in data-dependent MS² acquisition mode was performed for the analysis of surface water samples by direct injection. Data processing was achieved with software tools written in R. A database containing MS² spectra of 693 compounds formed the basis of the workflow. Standard mixes and a time series of 361 samples of river water were analyzed and processed with the optimized workflow.

RESULTS

Using the database and a mix of 70 standards for testing, it was found that an identification strategy including (i) mass, (ii) retention time, and (iii) MS² spectral matching achieved a two- to three-fold improvement in the fraction of false positives compared with using only two criteria, while the number of false negatives remained low. The optimized workflow was applied to the sample series of river water. In total, 135 compounds were identified by a library match.

CONCLUSIONS

The developed automated database screening approach minimizes the proportion of false positives, while still allowing for the screening of hundreds of water samples for hundreds of compounds in a single run.

Developing Unique Nontarget High-Resolution Mass Spectrometry Signatures to Track Contaminant Sources in Urban Waters

Diffuse pollution in urban receiving waters often adversely impacts both humans and ecosystems. Identifying such pollution sources is challenging and limits the effectiveness of management actions intended to reduce risk. Here, we evaluated the use of nontarget analysis via high-resolution mass spectrometry (HRMS) to develop chemical fingerprints/signatures for source tracking. Specifically, we applied nontarget HRMS to characterize and differentiate two urban chemical sources: roadway runoff and wastewater influent. We isolated 112 and 598 nontarget compounds (both known and unidentified chemicals) that co-occurred in all roadway runoff and wastewater influent samples, respectively, and were unique relative to other sampled sources. For example, methamphetamine, often considered wastewater derived, was detected in all samples, implying that individual wastewater indicators may lack sufficient specificity in urban receiving waters impacted by multiple sources. Hierarchical cluster analysis differentiated source types, and normalized abundance profiling prioritized nontarget compounds with consistent relative abundance patterns across field sites for a given source. Hexa(methoxymethyl)melamine, 1,3-diphenylguanidine, and polyethylene glycols co-occurred in roadway runoff across geographic areas and traffic intensities, supporting continued development of a universal roadway runoff fingerprint based on ubiquitous compounds. This study provides a proof-of-concept for isolating nontarget source fingerprints to track diffuse contamination in urban receiving waters.

Suspect screening and prioritization of chemicals of concern (COCs) in a forest-water reuse system watershed

Much research has assessed organic chemicals of concern (COCs) in municipal wastewater and receiving waters, but few studies have examined COCs in land treatment systems. Many prior studies have implemented targeted methods that quantify a relatively small fraction of COCs present in wastewater and receiving waters. This study used suspect screening to assess chemical features in ground- and surface waters from a watershed where secondary-treated wastewater is irrigated onto 900 ha of temperate forest, offering a more holistic view of chemicals that contribute to the exposome. Chemical features were prioritized by abundance and ToxPi scoring across seasonal sampling events to determine if the forest-water reuse system contributed to the chemical exposome of ground- and surface waters. The number of chemical features detected in wastewater was usually higher than on- and off-site ground- and surface waters; in wastewater, chemical features trended with precipitation in which greater numbers of features were detected in months with low precipitation. The number of chemical features detected in off- and on-site waters was similar. The lower overlap between chemical features found in wastewater and downstream surface waters, along with the similar numbers of features being detected in upstream and downstream surface waters, suggests that though wastewater may be a source of chemicals to ground and surface waters on-site, dissipation of wastewater-derived features (in number and peak area abundance) likely occurs with limited off-site surface water export by the forested land treatment system. Further, the numbers of features detected on site and the overlap between wastewater and surface waters did not increase during periods of low rainfall, counter to our initial expectations. The chemical features tentatively identified in this watershed appear common to features identified in other studies, warranting further examination on the potential for resulting impacts of these on humans and the environment.

Nontarget analysis: A new tool for the evaluation of wastewater processes

Strategies to determine the removal efficiency of micropollutants in wastewater treatment plants (WWTPs) are widely discussed. Especially the evaluation of the potential benefit of further advanced treatment steps such as an additional tertiary treatment based on ozonation or activated carbon have come into focus. Such evaluation strategies are often based on the removal behavior of known micropollutants via target or suspected analysis. The utilization of nontarget analysis is considered to lead to a more comprehensive picture as also unknown or not expected micropollutants are analyzed. Here, the results of an evaluation via target and nontarget analysis were compared for biological treatment (BT) processes of eleven full-scale WWTPs and three different post-treatments (PTs): one sand filter (SF) and two granular activated carbon (GAC) filters. The similarity of the determined removals from target and nontarget analysis of the BTs increased significantly by excluding easily degradable "features" from the nontarget evaluation. A similar ranking of the removal trends for the BTs could also be achieved by comparing this new subset of nontarget features with a set of nine readily to moderately biodegradable micropollutants. This observation suggests that a performance ranking of BTs based either on target or nontarget analysis is plausible. In contrast to the BTs, the evaluation of the three PTs revealed that the difference of feature removal between SF and the two GACs was small, but large for the target analytes with substantially higher removal effciencies for the GACs compared to the SF. In addition to the removal behavior, the nontarget analysis provided further information about the number and quantity of transformation products (TPs) in the effluent from the BTs. For all BTs more than half (55-67%) of the features detected in the effluent were not found in the influent. A comparable proportion of TPs was also detected after GAC and sand filtration due to their microbial activities.

Prioritizing potential endocrine active high resolution mass spectrometry (HRMS) features in Minnesota lakewater

Liquid chromatography high-resolution mass spectrometry (LC-HRMS) shows great potential for expanding our understanding of relevant unknown chemical components present within complex environmental mixtures. This study identified potentially endocrine active components within Minnesota lakewater by prioritizing LC-HRMS features uniquely present at sunfish spawning habitats where male fish showed signs of estrogen agonism. Porewater samples from four locations within the same lake were analyzed using liquid chromatography quadrupole time of flight mass spectrometry (LC-QToF/MS) with positive (ESI+) and negative (ESI-) electrospray ionization. Plasma vitellogenin concentrations of captured male sunfish was used to designate sites as either endocrine active (ACT; 2 sites) or reference (REF; 2 sites). Assuming unique chemical presence at active sites contributed to endocrine activity, features at significantly higher intensities (p-value < 0.05, t-value > t-critical, log-fold change > 0.1; equal variance t-test of log2 transformed data) in ACT sites were then compiled into a suspect search list for feature identification. Adducts and isotopes of prioritized features were deprioritized using pattern recognizing algorithms using mass, retention time, and intensity. Feature identities were reported according to established confidence metrics using spectral libraries and elemental composition algorithms. This LC-HRMS approach identified a number of features omitted by targeted analysis with higher relative abundances in ACT sites, including plant essential oils, fatty acids, and mycotoxins. Multivariate analysis determined whether features were either present at both sites (AB) or unique to individual ACT sites (A or B). Detection frequency across datasets indicated bias in feature prioritization influenced by the chosen sampling method and sample acquisition mode. The majority of features prioritized by this workflow remain tentatively identified or unidentified masses of interest, reflective of current limitations in shared spectral libraries for soft ionization analyses. Strategies similar to this workflow have the potential to reduce bias in database-driven toxicological prioritization frameworks.

The role of analytical chemistry in exposure science: Focus on the aquatic environment

Exposure science, in its broadest sense, studies the interactions between stressors (chemical, biological, and physical agents) and receptors (e.g. humans and other living organisms, and non-living items like buildings), together with the associated pathways and processes potentially leading to negative effects on human health and the environment. The aquatic environment may contain thousands of compounds, many of them still unknown, that can pose a risk to ecosystems and human health. Due to the unquestionable importance of the aquatic environment, one of the main challenges in the field of exposure science is the comprehensive characterization and evaluation of complex environmental mixtures beyond the classical/priority contaminants to new emerging contaminants. The role of advanced analytical chemistry to identify and quantify potential chemical risks, that might cause adverse effects to the aquatic environment, is essential. In this paper, we present the strategies and tools that analytical chemistry has nowadays, focused on chromatography hyphenated to (high-resolution) mass spectrometry because of its relevance in this field. Key issues, such as the application of effect direct analysis to reduce the complexity of the sample, the investigation of the huge number of transformation/degradation products that may be present in the aquatic environment, the analysis of urban wastewater as a source of valuable information on our lifestyle and substances we consumed and/or are exposed to, or the monitoring of drinking water, are discussed in this article. The trends and perspectives for the next few years are also highlighted, when it is expected that new developments and tools will allow a better knowledge of chemical composition in the aquatic environment. This will help regulatory authorities to protect water bodies and to advance towards improved regulations that enable practical and efficient abatements for environmental and public health protection.

Nontargeted Detection Methods for Food Safety and Integrity

Nontargeted workflows for chemical hazard analyses are highly desirable in the food safety and integrity fields to ensure human health. Two different analytical strategies, nontargeted metabolomics and chemical database filtering, can be used to screen unknown contaminants in food matrices. Sufficient mass and chromatographic resolutions are necessary for the detection of compounds and subsequent componentization and interpretation of candidate ions. Analytical chemistry–based technologies, including gas chromatography–mass spectrometry (GC-MS), liquid chromatography–mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and capillary electrophoresis–mass spectrometry (CE-MS), combined with chemometrics analysis are being used to generate molecular formulas of compounds of interest. The construction of a chemical database plays a crucial role in nontargeted detection. This review provides an overview of the current sample preparation, analytical chemistry–based techniques, and data analysis as well as the limitations and challenges of nontargeted detection methods for analyzing complex food matrices. Improvements in sample preparation and analytical platforms may enhance the relevance of food authenticity, quality, and safety.

Evaluating emerging organic contaminant removal in an engineered hyporheic zone using high resolution mass spectrometry

The hyporheic zone (HZ), located at the interface of surface and groundwater, is a natural bioreactor for attenuation of chemical contaminants. Engineered HZs can be incorporated into stream restoration projects to enhance hyporheic exchange, with flowpaths optimized to promote biological habitat, water quantity, and water quality improvements. Designing HZs for in-stream treatment of stormwater, a significant source of flow and contaminant loads to urban creeks, requires assessment of both the hydrology and biogeochemical capacity for water quality improvement. Here, we applied tracer tests and high resolution mass spectrometry (HRMS) to characterize an engineered hyporheic zone unit process, called a hyporheic design element (HDE), in the Thornton Creek Watershed in Seattle, WA. Dye, NaCl, and bromide were used to hydrologically link downwelling and upwelling zones and estimate the hydraulic retention time (HRT) of hyporheic flowpaths. We then compared water quality improvements across hydrologically-linked surface and hyporheic flowpaths (3-5 m length; ∼30 min to >3 h) during baseflow and stormflow conditions. We evaluated fate outcomes for 83 identified contaminants during stormflow, including those correlated with an urban runoff mortality syndrome in coho salmon. Non-target HRMS analysis was used to assess holistic water quality improvements and evaluate attenuation mechanisms. The data indicated substantial water quality improvement in hyporheic flowpaths relative to surface flow and improved contaminant removal with longer hyporheic HRT (for ∼1900 non-target compounds detected during stormflow, <17% were attenuated >50% via surface flow vs. 59% and 78% via short and long hyporheic residence times, respectively), and strong contributions of hydrophobic sorption towards observed contaminant attenuation.

Extended Targeted and Non-Targeted Strategies for the Analysis of Marine Toxins in Mussels and Oysters by (LC-HRMS)

When considering the geographical expansion of marine toxins, the emergence of new toxins and the associated risk for human health, there is urgent need for versatile and efficient analytical methods that are able to detect a range, as wide as possible, of known or emerging toxins. Current detection methods for marine toxins rely on a priori defined target lists of toxins and are generally inappropriate for the detection and identification of emerging compounds. The authors describe the implementation of a recent approach for the non-targeted analysis of marine toxins in shellfish with a focus on a comprehensive workflow for the acquisition and treatment of the data generated after liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) analysis. First, the study was carried out in targeted mode to assess the performance of the method for known toxins with an extended range of polarities, including lipophilic toxins (okadaic acid, dinophysistoxins, azaspiracids, pectenotoxins, yessotoxins, cyclic imines, brevetoxins) and domoic acid. The targeted method, assessed for 14 toxins, shows good performance both in mussel and oyster extracts. The non-target potential of the method was then challenged via suspects and without a priori screening by blind analyzing mussel and oyster samples spiked with marine toxins. The data processing was optimized and successfully identified the toxins that were spiked in the blind samples.

Anaerobic Transformation of the Iodinated X-ray Contrast Medium Iopromide, Its Aerobic Transformation Products, and Transfer to Further Iodinated X-ray Contrast Media

The iodinated X-ray contrast medium (ICM) iopromide and its aerobic transformation products (TPs) are frequently detected in the effluents of wastewater treatment plants and in different compartments of the aquatic environment. In this study, the anaerobic transformation of iopromide and its aerobic TPs was investigated in water-sediment systems. Iopromide, its final aerobic TP didespropanediol iopromide (DDPI), and its primary aniline desmethoxyacetyl iopromide (DAMI) were used as model substances. Five biologically formed anaerobic TPs of iopromide and DAMI and six of DDPI, and the respective transformation pathways, were identified. The TPs were formed by successive deiodination and hydrolysis of amide moieties. Quantification of the iodinated TPs was achieved by further development of a complementary liquid chromatography (LC)-quadrupole time-of-flight mass spectrometry (Q-ToF-MS) and LC-inductively coupled plasma - mass spectrometry (ICP-MS) strategy without needing authentic standards, despite several TPs coeluting with others. A database with predicted anaerobic TPs of ICMs was derived by applying the transformation rules found for the anaerobic transformation pathways of iopromide and diatrizoate to further ICMs (iomeprol and iopamidol) and their aerobic TPs already reported in the literature. The environmental relevance of the identified transformation pathways was confirmed by identifying an experimental TP and two predicted TPs using suspect screening of water taken from anaerobic bank filtration zones.

A non-targeted high-resolution mass spectrometry data analysis of dissolved organic matter in wastewater treatment

The dissolved organic matter (DOM) in wastewater is typically described by a limited number of concentration measurements of select DOM fractions or micro-contaminants, which determine the removal efficiency in a wastewater treatment. Current methods do not necessarily reflect the true performance of the treatment with regard to environmental and public health risk. Herein we describe the development and application of a non-targeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) data analysis for the evaluation of wastewater treatment processes. Our data analysis approach was applied to a real wastewater system with secondary biological treatment and tertiary treatment consisting of sand filtration, UV-treatment, and chlorination. We identified significant changes in DOM during wastewater treatment. The secondary treatment removed 1617 of 2409 (67%) detected molecular features (grouped isotopologues belonging to the same molecule) from the influent while 255 of 1047 (24%) new molecular features appeared in the secondary effluent. A reduction in the number of large molecules (>450 Da) and an increase in unsaturated molecular features of the effluent organic matter was observed. Van Krevelen plots revealed the distribution of unsaturation and heteroatoms and Kendrick mass defect plots uncovered CH₂ homologous series implying a removal of heavy constituents in that fraction. The demonstrated approach is a step towards a more comprehensive monitoring of DOM in wastewater and contributes to the understanding of current treatment technologies.