LC-high resolution MS in environmental analysis: from target screening to the identification of unknowns

Continuous high-frequency pesticide monitoring to observe the unexpected and the overlooked

Synthetic Plant Protection Products (PPPs) are a key element for a large part of today's global food systems. However, the transport of PPPs and their transformation products (TPs) to water bodies has serious negative effects on aquatic ecosystems. Small streams in agricultural catchments may experience pronounced concentration peaks given the proximity to fields and poor dilution capacity. Traditional sampling approaches often prevent a comprehensive understanding of PPPs and TPs concentration patterns being limited by trade-offs between temporal resolution and duration of the observation period. These limitations result in a knowledge gap for accurate ecotoxicological risk assessment and the achievement of optimal monitoring strategies for risk mitigation. We present here high-frequency PPPs and TPs concentration time-series measured with the autonomous MS²Field platform that combines continuous sampling and on-site measurements with a high-resolution mass spectrometer, which allows for overcoming temporal trade-offs. In a small agricultural catchment, we continuously measured 60 compounds at 20 minutes resolution for 41 days during the growing season. This observation period included 8 large and 15 small rain events and provided 2560 concentration values per compound. To identify similarities and differences among the compound-specific concentration time-series, we analysed the entire dataset with positive matrix factorisation. Six factors sufficiently captured the overall complexity in concentration dynamics. While one factor reflected dilution during rainfall, five factors identified PPPs groups that seemed to share a common history of recent applications. The investigation per event of the concentration time-series revealed a surprising complexity of dynamic patterns; physico-chemical properties of the compounds did not influence the (dis)similarity of chemographs. Some PPPs concentration peaks led while others lagged by several hours the water level peaks during large events. During small events, water level peaks always preceded concentration peaks, which were generally only observed when the water levels had almost receded to pre-event levels. Thus, monitoring schemes relying on rainfall or water level as proxies for triggering sampling may lead to systematic biases. The high temporal resolution revealed that the Swiss national monitoring integrating over 3.5 days underestimated critical concentration peaks by a factor of eight to more than 32, captured 3 out of 11 exceedances of legal acute quality standards (the relevant values in the Swiss Water Protection Law) and recorded 1 out of 9 exceedances of regulatory acceptable concentrations (the relevant values for the PPPs registration process). MS²Field allowed for observing unexpected and overlooked pesticide dynamics with consequences for further research but also for monitoring. The large variability in timing of concentration peaks relative to water level calls for more in-depth analyses regarding the respective transport mechanisms. To perform these analyses, spatially distributed sampling and time-series of geo-referenced PPPs application data are needed.

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.

Coupling Suspect and Nontarget Screening with Mass Balance Modeling to Characterize Organic Micropollutants in the Onondaga Lake-Three Rivers System

Characterizing the occurrence, sources, and fate of organic micropollutants (OMPs) in lake-river systems serves as an important foundation for constraining the potential impacts of OMPs on the ecosystem functions of these critical landscape features. In this work, we combined suspect and nontarget screening with mass balance modeling to investigate OMP contamination in the Onondaga Lake-Three Rivers system of New York. Suspect and nontarget screening enabled by liquid chromatography-high-resolution mass spectrometry led to the confirmation and quantification of 105 OMPs in water samples collected throughout the lake-river system, which were grouped by their concentration patterns into wastewater-derived and mixed-source clusters via hierarchical cluster analysis. Four of these OMPs (i.e., galaxolidone, diphenylphosphinic acid, N-butylbenzenesulfonamide, and triisopropanolamine) were prioritized and identified by nontarget screening based on their characteristic vertical distribution patterns during thermal stratification in Onondaga Lake. Mass balance modeling performed using the concentration and discharge data highlighted the export of OMPs from Onondaga Lake to the Three Rivers as a major contributor to the OMP budget in this lake-river system. Overall, this work demonstrated the utility of an integrated screening and modeling framework that can be adapted for OMP characterization, fate assessment, and load apportionment in similar surface water systems.

Suspect and non-target screening of chemicals in clothing textiles by reversed-phase liquid chromatography/hybrid quadrupole-Orbitrap mass spectrometry

The global manufacturing of clothing is usually composed of multistep processes, which include a large number of chemicals. However, there is generally no information regarding the chemical content remaining in the finished clothes. Clothes in close and prolonged skin contact may thus be a significant source of daily human exposure to hazardous compounds depending on their ability to migrate from the textiles and be absorbed by the skin. In the present study, twenty-four imported garments on the Swedish market were investigated with respect to their content of organic compounds, using a screening workflow. Reversed-phase liquid chromatography coupled to electrospray ionization/high-resolution mass spectrometry was used for both suspect and non-target screening. The most frequently detected compound was benzothiazole followed by quinoline. Nitroanilines with suspected mutagenic and possible skin sensitization properties, and quinoline, a carcinogenic compound, were among the compounds occurring at the highest concentrations. In some garments, the level of quinoline was estimated to be close to or higher than 50,000 ng/g, the limit set by the REACH regulation. Other detected compounds were acridine, benzotriazoles, benzothiazoles, phthalates, nitrophenols, and organophosphates. Several of the identified compounds have logP and molecular weight values enabling skin uptake. This pilot study indicates which chemicals and compound classes should be prioritized for future quantitative surveys and control of the chemical content in clothing as well as research on skin transfer, skin absorption, and systemic exposure. The results also show that the current control and prevention from chemicals in imported garments on the Swedish market is insufficient.

Techniques for the detection and quantification of emerging contaminants

In recent years, the diverse industrial practices and human inputs widely disseminated emerging contaminants (ECs) throughout environmental matrices, which is of great concern. Even at low concentrations, ECs pose major ecological problems and threaten human health and the environment’s biota. Consequently, people’s interest and concerns on the widespread dissemination of environmentally connected ECs of great concern as developed due to their scientific understanding, technical innovation, and socioeconomic awareness. Increased detection of contaminants may occur from climatic, socioeconomic, and demographic changes and the growing sensitivity of analytical techniques. Hence, this article reviews the determination of ECs in ecological specimens, from aquatic setup (river water, marine water, and wastewater), sludge, soil, sediment, and air. Sample collection and the quality measures are summarized. The preparation of samples, including extraction and cleanup and the subsequent instrumental analysis of ECs, are all covered. Traditional and recent extraction and cleanup applications to analyze ECs in samples are reviewed here in this paper. The detection and quantification of ECs using gas chromatography (GC) and liquid chromatography (LC) linked with various detectors, particularly mass spectrometry (MS), is also summarized and explored, as are other possible techniques. This study aims to give readers a more excellent knowledge of how new and improved approaches are being developed and serve as a resource for researchers looking for the best method for detecting ECs in their studies.

Data analysis strategies for the characterization of chemical contaminant mixtures. Fish as a case study

Thousands of chemicals are potentially contaminating the environment and food resources, covering a wide spectrum of molecular structures, physico-chemical properties, sources, environmental behavior and toxic profiles. Beyond the description of the individual chemicals, characterizing contaminant mixtures in related matrices has become a major challenge in ecological and human health risk assessments. Continuous analytical developments, in the fields of targeted (TA) and non-targeted analysis (NTA), have resulted in ever larger sets of data on associated chemical profiles. More than ever, the implementation of advanced data analysis strategies is essential to elucidate profiles and extract new knowledge from these large data sets. Specifically focusing on the data analysis step, this review summarizes the recent progress in integrating data analysis tools into TA and NTA workflows to address the challenging characterization of chemical mixtures in environmental and food matrices. As fish matrices are relevant in both aquatic pollution and consumer exposure perspectives, fish was chosen as the main theme to illustrate this review, although the present document is equally relevant to other food and environmental matrices. The key features of TA and NTA data sets were reviewed to illustrate the challenges associated with their analysis. Advanced filtering strategies to mine NTA data sets are presented, with a particular focus on chemical filters and discriminant analysis. Further, the applications of supervised and unsupervised multivariate analysis methods to characterize exposure to chemical mixtures, and their associated challenges, is discussed.

Chemical contaminants in canned food and can-packaged food: a review

Canning, as a preservation technique, is widely used to extend the shelf life as well as to maintain the quality of perishable foods. During the canning process, most of the microorganisms are killed, reducing their impact on food quality and safety. However, the presence of a range of undesirable chemical contaminants has been reported in canned foods and in relation to the canning process. The present review provides an overview of these chemical contaminants, including metals, polymeric contaminants and biogenic amine contaminants. They have various origins, including migration from the can materials, formation during the canning process, or contamination during steps required prior to canning (e.g. the disinfection step). Some other can-packaged foods (e.g. beverages or milk powder), which are not canned foods by definition, were also discussed in this review, as they have been frequently studied simultaneously with canned foods in terms of contamination. The occurrence of these contaminants, the analytical techniques involved, and the factors influencing the presence of these contaminants in canned food and can-packaged food are summarized and discussed.

Non-Targeted Screening Approaches for Profiling of Volatile Organic Compounds Based on Gas Chromatography-Ion Mobility Spectroscopy (GC-IMS) and Machine Learning

Due to its high sensitivity and resolving power, gas chromatography-ion mobility spectrometry (GC-IMS) is a powerful technique for the separation and sensitive detection of volatile organic compounds. It is a robust and easy-to-handle technique, which has recently gained attention for non-targeted screening (NTS) approaches. In this article, the general working principles of GC-IMS are presented. Next, the workflow for NTS using GC-IMS is described, including data acquisition, data processing and model building, model interpretation and complementary data analysis. A detailed overview of recent studies for NTS using GC-IMS is included, including several examples which have demonstrated GC-IMS to be an effective technique for various classification and quantification tasks. Lastly, a comparison of targeted and non-targeted strategies using GC-IMS are provided, highlighting the potential of GC-IMS in combination with NTS.

Large-Scale Implementation and Flaw Investigation of Human Serum Suspect Screening Analysis for Industrial Chemicals

Non-targeted analysis (NTA), including both suspect screening analysis (SSA) and unknown compound analysis, has gained increasing popularity in various fields for its capability in identifying new compounds of interests. Current major challenges for NTA SSA are that (1) tremendous effort and resources are needed for large-scale identification and confirmation of suspect chemicals and (2) suspect chemicals generally show low matching rates during identification and confirmation processes. To narrow the gap between these challenges and smooth implementation of NTA SSA methodology in the biomonitoring field, we present a thorough SSA workflow for the large-scale screen, identification, and confirmation of industrial chemicals that may pose adverse health effects in pregnant women and newborns. The workflow was established in a study of 30 paired maternal and umbilical cord serum samples collected at delivery in the San Francisco Bay area. By analyzing LC-HRMS and MS/MS data, together with the assistance of a combination of resources including online MS/MS spectra libraries, online in silico fragmentation tools, and the EPA CompTox Chemicals Dashboard, we confirmed the identities of 17 chemicals, among which monoethylhexyl phthalate, 4-nitrophenol, tridecanedioic acid, and octadecanedioic acid are especially interesting due to possible toxicities and their high-volume use in industrial manufacturing. Similar to other previous studies in the SSA field, the suspect compounds show relatively low MS/MS identification (16%) and standard confirmation (8%) rates. Therefore, we also investigated origins of false positive features and unidentifiable suspected features, as well as technical obstacles encountered during the confirmation process, which would promote a better understanding of the flaw of low confirmation rate and encourage gaining more effective tools for tackling this issue in NTA SSA.

A data independent acquisition all ion fragmentation mode tool for the suspect screening of natural toxins in surface water

Among natural freshwater pollutants, cyanotoxins, mycotoxins, and phytotoxins are the most important and less studied. Their identification in surface water is challenging especially cause of the lack of standards and established analytical parameters. Most target methods focus one or a single group of compounds with similar characteristics. Here we present an AIF fast method for the tentative identification of natural toxins in water. Respect to the previous method [1], it offers higher performances for the acquisition of unknown compounds at low levels for higher number of analytes.

The key aspects of the method are:

• The qualitative screening DIA-AIF workflow using Q Exactive Orbitrap. Both targeted and suspect screening bases have been combined with online databases and suspect list to retrieve candidates as suspect natural toxins and their metabolites or degradation products.

• The in-silico analysis of mass spectrums allowed a fast structural characterization.

• The workflow has been finally applied to real samples coming from the Czech Republic, Italy, and Spain allowing the determination of 17 suspect natural toxins, 4 of them confirmed. None toxin passed the limit of 1 µg/L taken from the legislation applied for microcystin LR and arbitrarily extended to all toxins.

Analytical methods for organosulfate detection in aerosol particles: Current status and future perspectives

Organosulfates (OSs) are well-known water-soluble constituents of atmospheric aerosol particles. They are formed from multiphase reactions between volatile organic compounds (VOCs) and their photooxidation products, and acidic sulfate originating from biogenic and anthropogenic sources in the atmosphere. Although the analytical procedures used to measure OSs, including sampling, pre-treatment, and instrumental detection, have advanced substantially in the last decade, there is still a need for accurate and standardized analysis procedures for the identification, quantification, and comparison of OSs in different regions. Additionally, there has no study focused on the health effects of OSs. This review outlines the analytical methods developed for OS detection during the last decade, highlighting both improvements and drawbacks. It also considers the future development of analytical methods for OS detection, and proposes the establishment of OSs screening method from the perspective of health effects to solve the problem of unknown health related OSs identification.

Suspect screening of pharmaceuticals in fish livers based on QuEChERS extraction coupled with high resolution mass spectrometry

The presence of pharmaceuticals and personal care products (PPCPs) in aquatic environments is of increasing concern due to the presence of residues in fish and aquatic organisms, and emerging antibiotic resistance. Wastewater release is an important contributor to the presence of these compounds in aquatic ecosystems, where they may accumulate in food webs. The traditional environmental surveillance approach relies on the targeted analysis of specific compounds, but more suspect screening methods have been developed recently to allow for the identification of a variety of contaminants. In this study, a method based on QuEChERS extraction - using acetonitrile/water mixture as solvent and PSA/C₁₈ for sample clean-up - was applied to identify pharmaceuticals and their metabolites in fish livers. Both target and suspect screening workflows were used and fish were sampled upstream and downstream of wastewater treatment plants from the Scioto River, Ohio (USA). The method performed well in terms of extraction of some target PPCPs, with recoveries generally above 90%, good repeatability (<20%), and linearity. Based on target analysis, lincomycin and sulfamethoxazole were two antibiotics identified in fish livers at average concentrations of 30.3 and 25.6 ng g^-1 fresh weight, respectively. Using suspect screening, another antibiotic, azithromycin and an antidepressant metabolite, erythrohydrobupropion were identified (average concentrations: 27.8 and 13.8 ng g^-1, respectively). The latter, reported, to the best of our knowledge, for the first time in fish livers, was also found at higher concentrations in fish livers sampled downstream vs. upstream. The higher frequency of detection for azithromycin in benthic feeding fish species (63%) as well as clusters identified between different foraging groups suggest that foraging behavior may be an important mechanism in the bioaccumulation of PPCPs. This study shows how suspect screening is effective in identifying new contaminants in fish livers, notably using differential analysis among different spatially distributed samples.

Development and Application of Liquid Chromatographic Retention Time Indices in HRMS-Based Suspect and Nontarget Screening

There is an increasing need for comparable and harmonized retention times (t_R) in liquid chromatography (LC) among different laboratories, to provide supplementary evidence for the identity of compounds in high-resolution mass spectrometry (HRMS)-based suspect and nontarget screening investigations. In this study, a rigorously tested, flexible, and less system-dependent unified retention time index (RTI) approach for LC is presented, based on the calibration of the elution pattern. Two sets of 18 calibrants were selected for each of ESI+ and ESI-based on the maximum overlap with the retention times and chemical similarity indices from a total set of 2123 compounds. The resulting calibration set, with RTI set to range between 1 and 1000, was proposed as the most appropriate RTI system after rigorous evaluation, coordinated by the NORMAN network. The validation of the proposed RTI system was done externally on different instrumentation and LC conditions. The RTI can also be used to check the reproducibility and quality of LC conditions. Two quantitative structure-retention relationship (QSRR)-based models were built based on the developed RTI systems, which assist in the removal of false-positive annotations. The applicability domains of the QSRR models allowed completing the identification process with higher confidence for substances within the domain, while indicating those substances for which results should be treated with caution. The proposed RTI system was used to improve confidence in suspect and nontarget screening and increase the comparability between laboratories as demonstrated for two examples. All RTI-related calculations can be performed online at http://rti.chem.uoa.gr/.

Influence of Electrolyte Concentration on Single-Molecule Sensing of Perfluorocarboxylic Acids

Perfluorocarboxylic acids (PFCAs) are an emerging class of persistent organic pollutants. During the fabrication process, it is unavoidable to form PFCA homologs or isomers which exhibit distinct occurrence, bioaccumulation, and toxicity. The precision measurement of PFCAs is therefore of significant importance. However, the existing characterization techniques, such as LC-MS/MS, cannot fully meet the requirement of isomer-specific analysis, largely due to the lack of authentic standards. Single-molecule sensors (SMSs) based on nanopore electrochemistry may be a feasible solution for PFCAs determination, thanks to their ultra-high spatiotemporal resolutions. Hence, as a first step, this work was to elucidate the influence of electrolyte concentration on the four most critical indicators of nanopore measurements, and furthermore, performance of nanopore SMSs. More specifically, three of the most representative short-chain PFCAs, perfluoropentanoic acid (PFPeA), perfluorohexanoic acid (PFHxA) and perfluoroheptanoic acid (PFHpA), were adopted as the target analytes, aerolysin nanopore was employed as the sensing interface, and 2, 3 and 4 M KCl solutions were used as electrolytes. It was found that, when the concentration of KCl solution increased from 2 to 4 M, the conductance of aerolysin nanopore increased almost linearly at a rate of 0.5 nS per molar KCl within the whole voltage range, the current blockade of PFPeA at -50 mV increased from 61.74 to 66.57% owing to the enhanced steric exclusion effect, the maximum dwell time was more than doubled from 14.5 to 31.5 ms, and the barrier limited capture rate increased by 8.3 times from 0.46 to 3.85 Hz. As a result, when using 4 M KCl as the electrolyte, over 90% of the PFPeA, PFHxA and PFHpA were accurately identified from a mixed sample, and the calculated limit of detection of PFPeA reached 320 nM, more than 24 times lower than in 2 M KCl. It was thus clear that tuning the electrolyte concentration was a simple but very effective approach to improve the performance of nanopore SMSs for PFCAs determination.

Formation of transformation products during ozonation of secondary wastewater effluent and their fate in post-treatment: From laboratory- to full-scale

Ozonation is increasingly applied in water and wastewater treatment for the abatement of micropollutants (MPs). However, the transformation products formed during ozonation (OTPs) and their fate in biological or sorptive post-treatments is largely unknown. In this project, a high-throughput approach, combining laboratory ozonation experiments and detection by liquid chromatography high-resolution mass spectrometry (LC-HR-MS/MS), was developed and applied to identify OTPs formed during ozonation of wastewater effluent for a large number of relevant MPs (total 87). For the laboratory ozonation experiments, a simplified experimental solution, consisting of surrogate organic matter (methanol and acetate), was created, which produced ozonation conditions similar to realistic conditions in terms of ozone and hydroxyl radical exposures. The 87 selected parent MPs were divided into 19 mixtures, which enabled the identification of OTPs with an optimized number of experiments. The following two approaches were considered to identify OTPs. (1) A screening of LC-HR-MS signal formation in these experiments was performed and revealed a list of 1749 potential OTP candidate signals associated to 70 parent MPs. This list can be used in future suspect screening studies. (2) A screening was performed for signals that were formed in both batch experiments and in samples of wastewater treatment plants (WWTPs). This second approach was ultimately more time-efficient and was applied to four different WWTPs with ozonation (specific ozone doses in the range 0.23-0.55 gO₃/gDOC), leading to the identification of 84 relevant OTPs of 40 parent MPs in wastewater effluent. Chemical structures could be proposed for 83 OTPs through the interpretation of MS/MS spectra and expert knowledge in ozone chemistry. Forty-eight OTPs (58%) have not been reported previously. The fate of the verified OTPs was studied in different post-treatment steps. During sand filtration, 87-89% of the OTPs were stable. In granular activated carbon (GAC) filters, OTPs were abated with decreasing efficiency with increasing run times of the filters. For example, in a GAC filter with 16,000 bed volumes, 53% of the OTPs were abated, while in a GAC filter with 35,000 bed volumes, 40% of the OTPs were abated. The highest abatement (87% of OTPs) was observed when 13 mg/L powdered activated carbon (PAC) was dosed onto a sand filter.

Characterization of advanced wastewater treatment with ozone and activated carbon using LC-HRMS based non-target screening with automated trend assignment

Advanced treatment is increasingly being applied to improve abatement of micropollutants in wastewater effluent and reduce their load to surface waters. In this study, non-target screening of high-resolution mass spectrometry (HRMS) data, collected at three Swiss wastewater treatment plants (WWTPs), was used to evaluate different advanced wastewater treatment setups, including (1) granular activated carbon (GAC) filtration alone, (2) pre-ozonation followed by GAC filtration, and (3) pre-ozonation followed by powdered activated carbon (PAC) dosed onto a sand filter. Samples were collected at each treatment step of the WWTP and analyzed with reverse-phase liquid chromatography coupled to HRMS. Each WWTP received a portion of industrial wastewater and a prioritization method was applied to select non-target features potentially resulting from industrial activities. Approximately 37,000 non-target features were found in the influents of the WWTPs. A number of non-target features (1207) were prioritized as likely of industrial origin and 54 were identified through database spectral matching. The fates of all detected non-target features were assessed through a novel automated trend assignment method. A trend was assigned to each non-target feature based on the normalized intensity profile for each sampling date. Results showed that 73±4% of influent non-target features and the majority of industrial features (89%) were well-removed (i.e., >80% intensity reduction) during biological treatment in all three WWTPs. Advanced treatment removed, on average, an additional 11% of influent non-target features, with no significant differences observed among the different advanced treatment settings. In contrast, when considering a subset of 66 known micropollutants, advanced treatment was necessary to adequately abate these compounds and higher abatement was observed in fresh GAC (7,000-8,000 bed volumes (BVs)) compared to older GAC (18,000-48,000 BVs) (80% vs 56% of micropollutants were well-removed, respectively). Approximately half of the features detected in the WWTP effluents were features newly formed during the various treatment steps. In ozonation, between 1108-3579 features were classified as potential non-target ozonation transformation products (OTPs). No difference could be observed for their removal in GAC filters at the BVs investigated (70% of OTPs were well-removed on average). Similar amounts (67%) was observed with PAC (7.7-13.6 mg/L) dosed onto a sand filter, demonstrating that a post-treatment with activated carbon is efficient for the removal of OTPs.

Identification and determination of emerging pollutants in sewage sludge driven by UPLC-QTOF-MS data mining

Sludge from sewage treatment plants (STPs) is recognized as a sink of moderate to high lipophilic compounds resistant to biodegradation. Herein, we investigate the presence of emerging pollutants in sewage sludge combining the information provided by mass spectrometry detection, following ultra-performance liquid chromatography (UPLC), with the use of an accurate spectral database of pesticides and pharmaceuticals. In a first step, the performance of matrix solid-phase dispersion, as sample preparation technique, and two non-target data acquisition strategies (data dependent, DDA, and data independent analysis modes, DIA), used in combination with a UPLC quadrupole time-of-flight system, are assessed using a selection of deuterated compounds added either to freeze-dried sludge samples, or to sludge extracts. Possibilities and limitations of both modes are discussed. Following the DDA approach, a group of 68 micropollutants was identified in sludge from different STPs. Some of them are reported in this compartment for the first time. Finally, semi-quantitative concentration data are reported for a group of 37 pollutants in samples obtained from 16 STPs. Out of them, 10 pharmaceuticals, showing detection frequencies and median sludge residues above 50% and 100 ng g^-1, respectively; are highlighted as pollutants to be monitored in sludge in order to understand their behaviour during the wastewater treatment.

Improving the Screening Analysis of Pesticide Metabolites in Human Biomonitoring by Combining High-Throughput In Vitro Incubation and Automated LC-HRMS Data Processing

There is a current need to monitor human exposure to a large number of pesticides and other chemicals of emerging concern (CECs). This requires screening analysis with high confidence for these compounds and their metabolites in complex matrices, which is hampered by the fact that no reference standards are available for most metabolites. We address this challenge by a high-throughput workflow based on incubation of pesticides (or other CECs) with human liver S9, followed by solid-phase extraction, liquid chromatography-high-resolution mass spectrometry (LC-HRMS) analysis, and automated data processing to generate a database (retention time, precursor m/z, and MS² spectral library) for the annotation in human samples. The metabolite prioritization consists of statistical comparisons and mass defect and m/z range filtering to obtain a subset of probable phase I metabolites, for which molecular formulas and likely metabolic transformation are retrieved. We tested the workflow on 22 pesticides, for which we could determine 91 metabolite molecular formulas which are only partly covered by the literature and/or predicted by in silico metabolization. Our workflow allows for an efficient generation of metabolite reference information, which can be used directly for annotating LC-HRMS data from human samples. A full structure elucidation of individual metabolites can be limited to those being actually present in human samples.

An asymmetric Schiff base-functionalized gold nanoparticle-based colorimetric sensor for Hg2+ ion determination: experimental and DFT studies

We report a colorimetric sensor for the detection of Hg²⁺ ions utilizing surface-modified gold nanoparticles. Gold nanoparticles (GNPs) were synthesized by direct reduction and were subsequently functionalized using Schiff base ligands. Schiff base ligands as electron transfer agents have been frequently used for the determination of heavy metal ions. From the spectroscopic analysis, it was found that the mechanism could be defined as coordination between azomethine nitrogen and the carbonyl oxygen of the ligand with Hg²⁺ ions. The affinity of Hg²⁺ ions towards the bidentate Schiff base on the GNPs result from their self-aggregation and investigated to be a powerful asset for the development of Hg²⁺ ion-selective sensors, which is accompanied by a visible color change from pink to purple or can be detect by UV-Vis spectroscopy. The optimized structures and binding mechanisms were supported with a high correlation and agreement via spectroscopy and DFT calculations. These simple colorimetric tests can be extended for the rapid pre-screening of a wide variety of heavy metal ions for onsite detection and mitigation.

MolDiscovery: learning mass spectrometry fragmentation of small molecules

Identification of small molecules is a critical task in various areas of life science. Recent advances in mass spectrometry have enabled the collection of tandem mass spectra of small molecules from hundreds of thousands of environments. To identify which molecules are present in a sample, one can search mass spectra collected from the sample against millions of molecular structures in small molecule databases. The existing approaches are based on chemistry domain knowledge, and they fail to explain many of the peaks in mass spectra of small molecules. Here, we present molDiscovery, a mass spectral database search method that improves both efficiency and accuracy of small molecule identification by learning a probabilistic model to match small molecules with their mass spectra. A search of over 8 million spectra from the Global Natural Product Social molecular networking infrastructure shows that molDiscovery correctly identify six times more unique small molecules than previous methods.

Identification of LC-HRMS nontarget signals in groundwater after source related prioritization

Groundwater is a major drinking water resource but its quality with regard to organic micropollutants (MPs) is insufficiently assessed. Therefore, we aimed to investigate Swiss groundwater more comprehensively using liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS). First, samples from 60 sites were classified as having high or low urban or agricultural influence based on 498 target compounds associated with either urban or agricultural sources. Second, all LC-HRMS signals were related to their potential origin (urban, urban and agricultural, agricultural, or not classifiable) based on their occurrence and intensity in the classified samples. A considerable fraction of estimated concentrations associated with urban and/or agricultural sources could not be explained by the 139 detected targets. The most intense nontarget signals were automatically annotated with structure proposals using MetFrag and SIRIUS4/CSI:FingerID with a list of >988,000 compounds. Additionally, suspect screening was performed for 1162 compounds with predicted high groundwater mobility from primarily urban sources. Finally, 12 nontargets and 11 suspects were identified unequivocally (Level 1), while 17 further compounds were tentatively identified (Level 2a/3). amongst these were 13 pollutants thus far not reported in groundwater, such as: the industrial chemicals 2,5-dichlorobenzenesulfonic acid (19 detections, up to 100 ng L^-1), phenylphosponic acid (10 detections, up to 50 ng L^-1), triisopropanolamine borate (2 detections, up to 40 ng L^-1), O-des[2-aminoethyl]-O-carboxymethyl dehydroamlodipine, a transformation product (TP) of the blood pressure regulator amlodipine (17 detections), and the TP SYN542490 of the herbicide metolachlor (Level 3, 33 detections, estimated concentrations up to 100-500 ng L^-1). One monitoring site was far more contaminated than other sites based on estimated total concentrations of potential MPs, which was supported by the elucidation of site-specific nontarget signals such as the carcinogen chlorendic acid, and various naphthalenedisulfonic acids. Many compounds remained unknown, but overall, source related prioritisation proved an effective approach to support identification of compounds in groundwater.

Honey Phenolic Compound Profiling and Authenticity Assessment Using HRMS Targeted and Untargeted Metabolomics

Honey consumption is attributed to potentially advantageous effects on human health due to its antioxidant capacity as well as anti-inflammatory and antimicrobial activity, which are mainly related to phenolic compound content. Phenolic compounds are secondary metabolites of plants, and their content in honey is primarily affected by the botanical and geographical origin. In this study, a high-resolution mass spectrometry (HRMS) method was applied to determine the phenolic profile of various honey matrices and investigate authenticity markers. A fruitful sample set was collected, including honey from 10 different botanical sources (n = 51) originating from Greece and Poland. Generic liquid-liquid extraction using ethyl acetate as the extractant was used to apply targeted and non-targeted workflows simultaneously. The method was fully validated according to the Eurachem guidelines, and it demonstrated high accuracy, precision, and sensitivity resulting in the detection of 11 target analytes in the samples. Suspect screening identified 16 bioactive compounds in at least one sample, with abscisic acid isomers being the most abundant in arbutus honey. Importantly, 10 markers related to honey geographical origin were revealed through non-targeted screening and the application of advanced chemometric tools. In conclusion, authenticity markers and discrimination patterns were emerged using targeted and non-targeted workflows, indicating the impact of this study on food authenticity and metabolomic fields.

(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.

Enhanced Nontarget Screening Algorithm Reveals Highly Abundant Chlorinated Azo Dye Compounds in House Dust

Humans spend 90% of their time indoors, but the majority of indoor pollutants remain unknown. In this study, a nontarget screening algorithm with reduced false discovery rates was developed to screen indoor pollutants using the Toxic Substances Control Act (TSCA) database. First, a putative lock mass algorithm was developed for post-acquisition calibration of Orbitrap mass spectra to sub-ppm mass accuracy. Then, a one-stop screening algorithm was developed by combining MS¹ spectra, isotopic peaks, retention time prediction, and in silico MS² spectra. A sufficient true positive rate (73%) and false discovery rate (5%) were achieved for the screening of halogenated compounds at a score cutoff of 0.28. Above this cutoff, 427 chemicals were detected from 24 house dust samples, including 39 chlorinated compounds. While some identified halogenated compounds (e.g., triclosan) are well known, 18 previously unrecognized chlorinated azo dyes were detected with high abundance as the largest class of chlorinated compounds. Two chlorinated azo dyes were confirmed with authentic standards, but the two most abundant chlorinated azo dyes were missed by the algorithm due to the limited breadth of the TSCA database. These compounds were annotated as chlorinated analogues of Disperse Blue 373 and Disperse Violet 93 using the DIPIC-Frag method. This study revealed the presence of highly abundant chlorinated azo dyes in house dusts, highlighting their potential health risks in the indoor environment.

Retrospective mass spectrometric analysis of wastewater-fed mesocosms to assess the degradation of drugs and their human metabolites

Temporary rivers become dependent on wastewater effluent for base flows, which severely impacts river ecosystems through exposure to elevated levels of nutrients, dissolved organic matter, and organic micropollutants. However, biodegradation processes occurring in these rivers can be enhanced by wastewater bacteria/biofilms. Here, we evaluated the attenuation of pharmaceuticals and their human metabolites performing retrospective analysis of 120 compounds (drugs, their metabolites and transformation products) in mesocosm channels loaded with wastewater effluents twice a week for a period of 31 days. Eighteen human metabolites and seven biotransformation products were identified with high level of confidence. Compounds were classified into five categories. Type-A: recalcitrant drugs and metabolites (diclofenac, carbamazepine and venlafaxine); Type-B: degradable drugs forming transformation products (TPs) (atenolol, sitagliptin, and valsartan); Type-C: drugs for which no known human metabolites or TPs were detected (atorvastatin, azithromycin, citalopram, clarithromycin, diltiazem, eprosartan, fluconazole, ketoprofen, lamotrigine, lormetazepam, metformin, telmisartan, and trimethoprim); Type-D: recalcitrant drug metabolites (4-hydroxy omeprazole sulfide, erythro/threo-hydrobupropion, and zolpidem carboxylic acid); Type-E: unstable metabolites whose parent drug was not detectable (norcocaine, benzolylecgonine, and erythromycin A enol ether). Noteworthy was the valsartan acid formation from valsartan with transient formation of TP-336.

Non-targeted screening of trace organic contaminants in surface waters by a multi-tool approach based on combinatorial analysis of tandem mass spectra and open access databases

Non-targeted screening (NTS) in mass spectrometry (MS) helps alleviate the shortcoming of targeted analysis such as missing the presence of concerning compounds that are not monitored and its lack of retrospective analysis to subsequently look for new contaminants. Most NTS workflows include high resolution tandem mass spectrometry (HRMS²) and structure annotation with libraries which are still limited. However, in silico combinatorial fragmentation tools that simulate MS² spectra are available to help close the gap of missing compounds in empirical libraries. Three NTS tools were combined and used to detect and identify unknown contaminants at ultra-trace levels in surface waters in real samples in this qualitative study. Two of them were based on combinatorial fragmentation databases, MetFrag and the Similar Partition Searching algorithm (SPS), and the third, the Global Natural Products Social Networking (GNPS), was an ensemble of empirical databases. The three NTS tools were applied to the analysis of real samples from a local river. A total of 253 contaminants were identified by combining all three tools: 209 were assigned a probable structure and 44 were confirmed using reference standards. The two major classes of contaminants observed were pharmaceuticals and consumer product additives. Among the confirmed compounds, octylphenol ethoxylates, denatonium, irbesartan and telmisartan are reported for the first time in surface waters in Canada. The workflow presented in this work uses three highly complementary NTS tools and it is a powerful approach to help identify and strategically select contaminants and their transformation products for subsequent targeted analysis and uncover new trends in surface water contamination.

A review on analytical methods for pharmaceutical and personal care products and their transformation products

Pharmaceutical and personal care products (PPCPs) and corresponding transformation products have caused widespread concern due to their persistent emissions and potential toxicity. They have wide octanol-water partition coefficients (K_ow) and different ionization constants (pK_a) resulting in a poor analysis accuracy and efficiency. A suitable analytical method is the first prerequisite for further research on their environmental behavior to prioritize the substances. This study reviewed a full-scale analytical protocol for environmental samples in the recent ten years: from sampling to instrumental methods. Passive sampling techniques were compared and recommended for long-term continuous and scientific observation. A quick and effective sample extraction and clean-up method are highly required. Chromatographic methods coupled to mass spectrometry for determining PPCPs with a wide range of logK_ow (-7.53 to 10.80) were summed up. High-resolution mass spectrometry was confirmed to be a promising strategy for screening unknown transformation products, which would provide a nanogram level of detection limits and more accurate mass resolution. Screening strategies and mass change principles were summarized in detail. The recovery rate was important in multiple contaminants analysis identification and factors affecting the recovery rate of PPCPs were also discussed in this review, including sample matrix, target compounds characteristics, extraction method and solid-phase adsorbent. This review provides useful information for the selection of appropriate analytical methods and future development directions.

LC-MS untargeted metabolomics assesses the delayed response of glufosinate treatment of transgenic glufosinate resistant (GR) buffalo grasses (Stenotaphrum secundatum L.)

INTRODUCTION

Glufosinate resistant (GR) buffalo grasses were genetically modified to resist the broad-spectrum herbicide, glufosinate by inserting a novel pat gene into its genome. This modification results in a production of additional phosphinothricin acetyltransferase (PAT) to detoxify the deleterious effects of glufosinate. The GR grasses and its associated herbicide form a modern, weeding program, to eradicate obnoxious weeds in turf lawn without damaging the grasses at relatively low costs and labor. As with several principal crops which are genetically modified to improve agricultural traits, biosafety of the GR buffalo grasses is inevitably expected to become a public concern. For the first time, we had previously examined the metabolome of glufosinate-resistant buffalo grasses, using a GC-MS untargeted approach to assess the risk of GR as well as identify any pleotropic effects arising from the genetically modification process. In this paper, an untargeted high-resolution LC-MS (LC-HRMS) untargeted metabolomics approach was carried out to complement our previous findings with respect to GR and wild type (WT) buffalo grasses.

OBJECTIVE

One of the major aims of this present work was to compare GR to WT buffalo grasses by including the detection of the secondary metabolome and determine any unprecedented metabolic changes.

METHODS

Eight-week old plants of 4 GR buffalo grasses, (93-1A, 93-2B, 93-3 C and 93-5A) and 3 wild type varieties (WT 8-4A, WT 9-1B and WT 9-1B) were submerged in either 5 % v/v of glufosinate or distilled water 3 days prior to a LC-HRMS based untargeted metabolomics analysis (glufosinate-treated or control, samples, respectively). An Ultra-High-Performance Liquid Chromatography (UHPLC) system coupled to a Velos Pro Orbitrap mass spectrometer system was employed to holistically measure the primary and secondary metabolome of both GR and WT buffalo grasses either treated with or without glufosinate and subsequently apply several bioinformatic tools including the automated pathway analysis algorithm, mummichog.

RESULTS

LC-HRMS untargeted based metabolomics clearly identified that the global metabolite pools of both GR and WT cultivars were highly similar, providing strong, supporting evidence of substantial equivalence between the GR and WT varieties. These findings indicate that if any associated risks to these GR grasses were somehow present, the risk would be within those acceptable ranges present in the WT. Additionally, mummichog-based pathway analysis indicated that phenylalanine metabolism and the TCA cycle were significantly impacted by glufosinate treatment in the WT cultivar. It was possible that alterations in the relative concentrations of several intermediates in these pathways were likely due to glufosinate-induced production of secondary metabolites to enhance plant defense mechanisms against herbicidal stress at the expense of primary metabolism.

CONCLUSIONS

GR buffalo grasses were found to be near identical to its WT comparator based on this complementary LC-HRMS based untargeted metabolomics. Therefore, these results further support the safe use of these GR buffalo grasses with substantial evidence. Interestingly, despite protected by PAT, GR buffalo grasses still demonstrated the response to glufosinate treatment by up-regulating some secondary metabolite-related pathways.

Target and Nontarget Analysis of Per- and Polyfluoralkyl Substances in Wastewater from Electronics Fabrication Facilities

The goals of this study were to improve our understanding of the types of per- and polyfluoroalkyl substances (PFASs) that occur in wastewater from electronics fabrication facilities (fabs) and to assess the relative concentrations of PFAS species. We collected wastewater samples from three fabs in the United States, analyzed the samples by means of high-resolution mass spectrometry, and implemented complementary target and nontarget analyses. Twelve of 25 target PFASs were quantified in at least one sample, and five perfluorocarboxylates and perfluorobutane sulfonate (PFBS) were quantified in all samples. PFBS was quantified at the highest concentration among the samples (8040 ng L^-1) and we expect that its presence is related to the use of photoacid generators during photolithography. The sum concentrations of the target PFASs in the diluted discharge samples from each fab were 623, 394, and 376 ng L^-1. Nontarget analysis revealed the presence of 41 homologous series of PFASs comprising 133 homologues. We proposed structures for 15 homologous series of nontarget PFASs, six of which are reported here for the first time. Using an approach for semiquantification of nontarget PFASs, we estimated that the sum concentrations of target and nontarget PFASs in the diluted discharge samples from each fab were 1490, 78 700, and 2170 ng L^-1. Our findings are essential for developing alternative photolithography chemicals or informing the implementation of advanced wastewater treatment technologies at fabs.

Rapid determination of pharmaceuticals in wastewater by direct infusion HRMS using target and suspect screening analysis

A wide-scope screening of active pharmaceutical ingredients (APIs) and their transformation products (TPs) in wastewater can yield valuable insights and pinpoint emerging contaminants that have not been previously reported. Such information is relevant to investigate their occurrence and fate in various environmental compartments. In this study, we explored the applicability of direct infusion high resolution mass spectrometry (DI-HRMS) for comprehensive and rapid detection of APIs and their TPs in wastewater samples. The method was developed using a Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) system and incorporated both wide-scope suspect screening and semi-quantitative determination of selected analytes. The identification strategy was based on the following criteria: narrow accurate mass window (±1.25 ppm) for two most abundant full-MS signals, isotopic pattern fit and additional confirmation on the basis of MS² spectra at three fragmentation levels. The tentative identification of suspects and target compounds relied on an in-house database containing more than 500 different APIs and TPs. The measured fragment spectra were matched against experimental MS² patterns obtained from a publicly available spectral library (MassBank of North America) and in-silico generated fragmentation features (from the CFM-ID algorithm). In total, 79 suspects were identified and 24 target compounds were semi-quantified in 72 wastewater samples. The highest detection frequencies in treated wastewater effluents were observed for diclofenac, metoprolol and telmisartan, while hydroxydiclofenac, dextrorphan, and carbamazepine metabolites were the most frequently detected TPs. The obtained API profiles were in accordance with the national consumption statistics and the origin of wastewater samples. The developed method is suitable for rapid screening of APIs in wastewater and can be used as a complementary tool to characterize API emissions from wastewater treatment facilities and to identify problematic compounds that require more rigorous monitoring.

Suspect screening based on market data of polar halogenated micropollutants in river water affected by wastewater

Wastewater treatment plants (WWTPs) are known point sources of contaminants of emerging concern (CECs) to the aquatic environment, but current knowledge is mostly limited to well-known chemical structures. In this study, we sought to identify unknown CECs polluting the aquatic environment through a novel suspect screening approach for organohalogens, i.e. organic halogenated molecules often toxic and resistant to transformation and characterised as persistent organic pollutants (POPs). Surface water samples were collected with passive samplers in the Fyris River catchment (Uppsala, Sweden), analysed using liquid chromatography high-resolution mass spectrometry (LC-HRMS) and screened for organohalogens using a suspect screening approach based on market data obtained from a regulatory authority. Thirteen suspects from very different application areas were confirmed or tentatively identified with high confidence, including seven previously unknown structures (diflufenican, chlorzoxazone, 3-(3,4-dichlorophenyl)-1,1-dimethylurea, 2,4-disulfamyl-5-trifluoromethylaniline, 5-amino-2-chlorotoluene-4-sulfonic acid, perfluoropentane-1-sufonic acid, (2-chlorophenyl)(hydroxy)methanesulfonic acid). Spatiotemporal occurrence patterns were detected, which helped to understand the usage pattern of the chemicals and pinpoint potential pollution sources, e.g. specific WWTPs in the catchment. Several of the newly identified structures had virtually no information publicly available and were detected years after their last registered use, which highlights the knowledge gaps and concerns about POPs.

The Algal Polysaccharide Ulvan Induces Resistance in Wheat Against Zymoseptoria tritici Without Major Alteration of Leaf Metabolome

This study aimed to examine the ability of ulvan, a water-soluble polysaccharide from the green seaweed Ulva fasciata, to provide protection and induce resistance in wheat against the hemibiotrophic fungus Zymoseptoria tritici. Matrix-assisted laser desorption/ionization-time-of-flight-mass spectrometry (MALDI-TOF-MS) analysis indicated that ulvan is mainly composed of unsaturated monosaccharides (rhamnose, rhamnose-3-sulfate, and xylose) and numerous uronic acid residues. In the greenhouse, foliar application of ulvan at 10 mg.ml^-1 2 days before fungal inoculation reduced disease severity and pycnidium density by 45 and 50%, respectively. Ulvan did not exhibit any direct antifungal activity toward Z. tritici, neither in vitro nor in planta. However, ulvan treatment significantly reduced substomatal colonization and pycnidium formation within the mesophyll of treated leaves. Molecular assays revealed that ulvan spraying elicits, but does not prime, the expression of genes involved in several wheat defense pathways, including pathogenesis-related proteins (β-1,3-endoglucanase and chitinase), reactive oxygen species metabolism (oxalate oxidase), and the octadecanoid pathway (lipoxygenase and allene oxide synthase), while no upregulation was recorded for gene markers of the phenylpropanoid pathway (phenylalanine ammonia-lyase and chalcone synthase). Interestingly, the quantification of 83 metabolites from major chemical families using ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) in both non-infectious and infectious conditions showed no substantial changes in wheat metabolome upon ulvan treatment, suggesting a low metabolic cost associated with ulvan-induced resistance. Our findings provide evidence that ulvan confers protection and triggers defense mechanisms in wheat against Z. tritici without major modification of the plant physiology.

Characterizing changes of dissolved organic matter composition with the use of distinct feeds in recirculating aquaculture systems via high-resolution mass spectrometry

Recirculating aquaculture systems (RAS) are a new alternative to traditional aquaculture approaches, allowing full control over the fish production conditions, while reducing the water demand. The reduction of water exchange leads to an accumulation of dissolved organic matter (DOM) that can have potential effects on water quality, fish welfare and system performance. Despite the growing awareness of DOM in aquaculture, scarce scientific information exists for understanding the composition and transformation of DOM in RAS. In this study, a non-targeted approach using ultra-performance liquid chromatography coupled to a hybrid quadrupole-time of flight mass spectrometer (UPLC-QTOF-MS) was used to characterize compositional changes of low molecular weight (LMW) DOM in RAS, when operated under two different feed types. A total of 1823 chemicals were identified and the majority of those contained a CHON chemical group in their structure. Changes in the composition of LMW-DOM in RAS waters were observed when the standard feed was switched to RAS feed. The DOM with the use of standard feed, consisted mainly of lignin/CRAM-like, CHO and CHOS chemical groups, while the DOM that used RAS feed, was mainly composed by unsaturated hydrocarbon, CHNO and CHNOS chemical groups. The Bray-Curtis dissimilarity cluster demonstrated differences in the composition of DOM from RAS and was associated to the type of feed used. When the RAS feed was used, the Kendrick mass defect plots of -CH₂- homologous units in the pump-sump (after the water treatment) showed a high removal capacity for CHNO, CHNOS and halogenated chemicals with high Kendrick mass defect, KMD > 0.7. To our knowledge, this is the first report of LMW-DOM characterization of RAS by high-resolution mass spectrometry (HRMS).

Suspect screening of natural toxins in surface and drinking water by high performance liquid chromatography and high-resolution mass spectrometry

Besides anthropogenic contamination, freshwater environments can also be affected by the presence of natural toxins. Mycotoxins, plant toxins and cyanotoxins are the most relevant groups that can be found in the aquatic system. However, until now, only cyanotoxins have been more carefully studied. In the present work, single workflow for the assessment of natural toxins in waters, based on suspect screening and target screening of a selected group of toxins is presented. The approach is based on a triple-stage solid-phase extraction (SPE) able to isolate a wide range of natural toxins of different polarities, followed by liquid chromatography coupled to high-resolution mass spectrometry (HPLC-ddHRMS²) using a Q-Exactive Orbitrap analyser. The acquisition was performed in full-scan (FS) and data-dependant acquisition (ddMS²) mode, working under positive and negative mode. For the tentative identification, different on-line databases such as ChemSpider and MzCloud and an in-house natural toxins list with 2384 structures, that includes cyanotoxins, plant toxins and mycotoxins, were used. Also, thanks to the MS² data, it was possible to achieve a high level of tentative identification confidence, but confirmation was only possible comparing the standards of the suspected compounds. For those, the analytical parameters of the developed method were also validated, and the quantification was possible by external calibration. Validation showed recoveries in the range between 53 and 95%, and method limits of detection (MDL) between 0.02 and 1.22 μg/L. This approach was applied to study natural toxins in 4 sampling sites along the Ter River in Catalonia (NE Spain). In this preliminary study 23 natural toxins were tentatively identified, and 9 of them confirmed (aflatoxin B1, anatoxin-a, nodularin, microcystin-LR, baicalein, kojic acid, cinchonine, B-asarone and atropine). The results of the quantification of these compounds showed concentrations below 1 μg/L in all cases, that is considered safe according to the actual legislation. This suspect screening approach allows a more comprehensive assessment of natural toxins in natural waters.

Suspect and Target Screening of Natural Toxins in the Ter River Catchment Area in NE Spain and Prioritisation by Their Toxicity

This study presents the application of a suspect screening approach to screen a wide range of natural toxins, including mycotoxins, bacterial toxins, and plant toxins, in surface waters. The method is based on a generic solid-phase extraction procedure, using three sorbent phases in two cartridges that are connected in series, hence covering a wide range of polarities, followed by liquid chromatography coupled to high-resolution mass spectrometry. The acquisition was performed in the full-scan and data-dependent modes while working under positive and negative ionisation conditions. This method was applied in order to assess the natural toxins in the Ter River water reservoirs, which are used to produce drinking water for Barcelona city (Spain). The study was carried out during a period of seven months, covering the expected prior, during, and post-peak blooming periods of the natural toxins. Fifty-three (53) compounds were tentatively identified, and nine of these were confirmed and quantified. Phytotoxins were identified as the most frequent group of natural toxins in the water, particularly the alkaloids group. Finally, the toxins identified to levels 2 and 1 were prioritised according to their bioaccumulation factor, biodegradability, frequency of detection, and toxicity. This screening and prioritisation approach resulted in different natural toxins that should be further assessed for their ecotoxicological effects and considered in future studies.

Characterization of monoaminergic neurochemicals in the different brain regions of adult zebrafish

Monoaminergic neurotransmitters are the main components that regulate of a lot of processes in the vertebrate brain. There is growing interest to monitor the changes produced in these neurochemicals due to the large number of exogenous agents, such as pharmaceuticals and drugs of abuse, targeting and affecting this system. Adult zebrafish (Danio rerio) shares the common neurotransmitter pathways and nervous system organization with mammals. Therefore, a method based on liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) has been developed for the first time to study the profile of ten monoaminergic neurochemicals in the anterior, middle and posterior brain regions of adult zebrafish. Moreover, the applied LC-MS/MS method has been studied in terms of quality such as linearity, sensitivity and intra- and inter-day precision. The analytical method based in LC-MS/MS has become a new source in neurotoxicology using adult zebrafish as research model. Significant differences on the levels of these neurotransmitters have been found between the different brain regions. CAPSULE: The profile of ten monoaminergic neurochemicals in the main three brain areas of adult zebrafish has been reported for the first time in this manuscript.

Analytical Strategies for Fingerprinting of Antioxidants, Nutritional Substances, and Bioactive Compounds in Foodstuffs Based on High Performance Liquid Chromatography-Mass Spectrometry: An Overview

New technology development and globalisation have led to extreme changes in the agri-food sector in recent years that need an important food supply chain characterisation from plant materials to commercial productions. Many analytical strategies are commonly utilised in the agri-food industry, often using complementary technologies with different purposes. Chromatography on-line coupled to mass spectrometry (MS) is one of the most selective and sensitive analytical methodologies. The purpose of this overview is to present the most recent MS-based techniques applied to food analysis. An entire section is dedicated to the recent applications of high-resolution MS. Covered topics include liquid (LC)– and gas chromatography (GC)–MS analysis of natural bioactive substances, including carbohydrates, flavonoids and related compounds, lipids, phenolic compounds, vitamins, and other different molecules in foodstuffs from the perspectives of food composition, food authenticity and food adulteration. The results represent an important contribution to the utilisation of GC–MS and LC–MS in the field of natural bioactive compound identification and quantification.

Non-targeted screening workflows for gas chromatography-high-resolution mass spectrometry analysis and identification of biomagnifying contaminants in biota samples

The health of key species in the Baltic region has been impaired by exposure to anthropogenic hazardous substances (AHSs), which accumulate in organisms and are transferred through food chains. There is, thus, a need for comprehensive characterization of the occurrence and accumulation of AHSs in the ecosystem. In this study, we use a non-target screening (NTS) approach for this purpose. A major challenge in NTS of biological samples is the removal of matrix components such as lipids that may interfere with the detection and identification of compounds of interest. Here, we combine gel permeation chromatography with Florisil^® column fractionation to achieve sufficient lipid removal for gas chromatography–high-resolution mass spectrometry analysis using electron ionization (EI) and electron capture negative ion chemical ionization (ECNI). In addition, we present new data processing workflows designed to systematically find and identify frequently occurring and biomagnifying AHSs, including known, emerging, and new contaminants. Using these workflows, we discovered a wide range of contaminants in tissue samples from blue mussels, fish, and marine mammals, and calculated their biomagnification factors (BMFs). Compounds with BMFs above 1 for herring and at least one marine mammal included legacy chlorinated pollutants (polychlorinated biphenyls, DDTs, chloro-benzenes/cyclohexanes, chlordanes, toxaphenes, dieldrin), polybrominated diphenyl ethers (PBDEs), and brominated biphenyls. However, there were also several halogenated natural products (halogenated methoxylated brominated diphenyl ethers, 1′-methyl-1,2′-bipyrroles, 1,1′-dimethyl-2,2′-bipyrroles, and the halogenated monoterpene mixed halogenated compound 1) as well as the novel flame retardant Dechlorane 602 and several polycyclic aromatic hydrocarbons, terpenoids, and steroids. The legacy pollutants exhibited the expected biomagnification behavior, demonstrating the utility of the unguided data processing workflow.

Strategies for data reduction in non-targeted screening analysis: The impact of sample variability for food safety applications

While analytical methods targeting specific compounds are critical for food safety, analytes excluded from the targeted list will not be identified. Non-targeted analyses (NTA) using LC/HR-MS complement these approaches by producing information-rich data sets where molecular formula can be generated for each detected compound; however, data mining can be labor intensive. Thus, we examined different NTA approaches to reduce the number of compounds needing further investigation, without relying on a suspect list or MS/MS database, both in single ingredient foods (i.e., oats) and more complex, oat-containing samples. We investigated inherent sample variability and utilized this information to build in-house databases for removing food compounds from sample data. While food databases were useful for data reduction, differential analysis was the most promising approach for single ingredient foods because it substantially reduced the number of features while retaining spiked QC compounds; however, a combination of approaches was necessary with greater sample complexity.

High-Resolution Historical Record of Plant Protection Product Deposition Documented by Target and Nontarget Trend Analysis in a Swiss Lake under Anthropogenic Pressure

A multiproxy workflow was used to assess >60 plant protection products (PPPs) in sediment samples from a Swiss lake under heavy agricultural pressure. The results show the appearance of PPPs for the first time in the early 1960s with an overall detection of 34 PPPs and with herbicides and fungicides found in equal proportions. Paleolimnological data [e.g., chronology, hyperspectral imaging of sedimentary green pigments, and semiquantitative elemental composition (μXRF scans)] suggest that PPP concentrations and fluxes to the sediment over time are not related to land surface processes such as soil erosion or lake biogeochemistry but are attributed mainly to PPP application (inferred from sales) or regulatory measures (bans). Additional compounds with similar sources of contamination as the target PPPs captured by nontarget trend analysis (≥2000 unknown profiles) reveal significant inputs of contaminants to the lake starting in the 1970s, followed by a decrease of contamination at the beginning of the 1990s and a constant increase by ∼28% of the unknown compounds since the year 2000. An ecological risk assessment conducted on detected PPPs indicates that since the 1980s, the sediment quality is insufficient with risk quotient values displaying maximum levels in the most recent sediments (∼2010) despite bans of specific PPPs and environmental regulations.

Characterization of synthetic dyes for environmental and forensic assessments: A chromatography and mass spectrometry approach

Dyes have become common substances since they are employed in mostly all objects surrounding our daily activities such as clothing and upholstery. Based on the usage and disposal of these objects, the transfer of the dyes to other media such as soil and water increases their prevalence in our environment. However, this prevalence could help to solve crimes and pollution problems if detection techniques are proper. For that reason, the detection and characterization of dyes in complex matrices is important to determine the possible events leading to their deposition (natural degradation, attempts of removal, possible match with evidence, among others). Currently, there are several chromatographic and mass spectrometric approaches used for the identification of these organic molecules and their derivatives with high specificity and accuracy. This review presents current chromatographic and mass spectrometric methods that are used for the detection and characterization of disperse, acid, basic, and reactive dyes, and their derivatives.

Simultaneous screening for chemically diverse micropollutants in public water bodies in Japan by high-performance liquid chromatography-Orbitrap mass spectrometry

An improved assessment of environmental risks to public water bodies requires screening a large number of micropollutants. This study reports the development of a novel target screening method based on solid-phase extraction (SPE), HPLC, and high-resolution Orbitrap MS for the analysis of micropollutants with diverse chemical properties. First, target compounds were screened for their detectability by Orbitrap MS. An optimized SPE cartridge and HPLC column maximized recovery and separated most target compounds. The sensitivity and repeatability of the method was validated by determining the detection limits and relative standard deviation (RSD). Eighty-four compounds with highly diverse properties were simultaneously detected with detection limits of 0.1-100 ng/L. Of these compounds, 52 were quantitated, with R2 ≥ 0.99 by linearity analysis and SPE recovery ratios of ≥50%. The remaining 32 compounds were qualitatively detected, with R2 < 0.99 or SPE recovery ratio of <50%. Satisfactory repeatability was obtained (RSD < 13.5%). This method was applied to the surveillance of the Arakawa River in Japan in 2019. Thirty-two compounds, including pesticides, surfactants, plasticizers, adhesives, and industrial solvents, were detected in the river. The measured concentrations of 13 compounds were compared with their predicted no effect concentrations (PNECs). Decanoic acid showed a higher concentration than the corresponding PNEC value, suggesting that its risk to the Arakawa water environment required further evaluation. The concentrations of dicyclohexylamine, 1,3-diphenylguanidine, and 2,4-dichlorophenoxyacetic acid were higher than their corresponding PNEC/10 values, demonstrating that these compounds were of higher priority than other compounds.