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See detailStrengthen the European collaborative environmental research to meet European policy goals for achieving a sustainable, non-toxic environment
Brack, Werner; Ait-Aissa, Selim; Backhaus, Thomas et al

in Environmental Sciences Europe (2019), 31(1), 1--9

To meet the United Nations (UN) sustainable development goals and the European Union (EU) strategy for a non-toxic environment, water resources and ecosystems management require cost-efficient solutions ... [more ▼]

To meet the United Nations (UN) sustainable development goals and the European Union (EU) strategy for a non-toxic environment, water resources and ecosystems management require cost-efficient solutions for prevailing complex contamination and multiple stressor exposures. For the protection of water resources under global change conditions, specific research needs for prediction, monitoring, assessment and abatement of multiple stressors emerge with respect to maintaining human needs, biodiversity, and ecosystem services. Collaborative European research seems an ideal instrument to mobilize the required transdisciplinary scientific support and tackle the large-scale dimension and develop options required for implementation of European policies. Calls for research on minimizing society’s chemical footprints in the water–food–energy–security nexus are required. European research should be complemented with targeted national scientific funding to address specific transformation pathways and support the evaluation, demonstration and implementation of novel approaches on regional scales. The foreseeable pressure developments due to demographic, economic and climate changes require solution-oriented thinking, focusing on the assessment of sustainable abatement options and transformation pathways rather than on status evaluation. Stakeholder involvement is a key success factor in collaborative projects as it allows capturing added value, to address other levels of complexity, and find smarter solutions by synthesizing scientific evidence, integrating governance issues, and addressing transition pathways. This increases the chances of closing the value chain by implementing novel solutions. For the water quality topic, the interacting European collaborative projects SOLUTIONS, MARS and GLOBAQUA and the NORMAN network provide best practice examples for successful applied collaborative research including multi-stakeholder involvement. They provided innovative conceptual, modelling and instrumental options for future monitoring and management of chemical mixtures and multiple stressors in European water resources. Advancement of EU water framework directive-related policies has therefore become an option. [less ▲]

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See detailThe metaRbolomics Toolbox in Bioconductor and beyond
Stanstrup, Jan; Broeckling, Corey D.; Helmus, Rick et al

in Metabolites (2019), 9(10), 200

Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and ... [more ▼]

Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of high-dimensional and complex experimental data. Open source processing and analysis tools are of major interest in light of innovative, open and reproducible science. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The programming and statistics environment R has emerged as one of the most popular environments to process and analyse Metabolomics datasets. A major benefit of such an environment is the possibility of connecting different tools into more complex workflows. Combining reusable data processing R scripts with the experimental data thus allows for open, reproducible research. This review provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation and identification, and biochemical network and pathway analysis. Multifunctional workflows, possible user interfaces and integration into workflow management systems are also reviewed. In total, this review summarises more than two hundred metabolomics specific packages primarily available on CRAN, Bioconductor and GitHub. [less ▲]

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See detailOntology-based metabolomics data integration with quality control
Buendia, Patricia; Bradley, Ray M.; Taylor, Thomas J. et al

in Bioanalysis (2019), 11(12), 1139-1154

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See detailSupporting non-target identification by adding hydrogen deuterium exchange MS/MS capabilities to MetFrag
Ruttkies, Christoph; Schymanski, Emma UL; Strehmel, Nadine et al

in Analytical and bioanalytical chemistry (2019), 411(19), 4683-4700

Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) is increasingly popular for the non-targeted exploration of complex samples, where tandem mass spectrometry (MS/MS) is used ... [more ▼]

Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) is increasingly popular for the non-targeted exploration of complex samples, where tandem mass spectrometry (MS/MS) is used to characterize the structure of unknown compounds. However, mass spectra do not always contain sufficient information to unequivocally identify the correct structure. This study investigated how much additional information can be gained using hydrogen deuterium exchange (HDX) experiments. The exchange of “easily exchangeable” hydrogen atoms (connected to heteroatoms), with predominantly [M+D]+ ions in positive mode and [M-D]− in negative mode was observed. To enable high-throughput processing, new scoring terms were incorporated into the in silico fragmenter MetFrag. These were initially developed on small datasets and then tested on 762 compounds of environmental interest. Pairs of spectra (normal and deuterated) were found for 593 of these substances (506 positive mode, 155 negative mode spectra). The new scoring terms resulted in 29 additional correct identifications (78 vs 49) for positive mode and an increase in top 10 rankings from 80 to 106 in negative mode. Compounds with dual functionality (polar head group, long apolar tail) exhibited dramatic retention time (RT) shifts of up to several minutes, compared with an average 0.04 min RT shift. For a smaller dataset of 80 metabolites, top 10 rankings improved from 13 to 24 (positive mode, 57 spectra) and from 14 to 31 (negative mode, 63 spectra) when including HDX information. The results of standard measurements were confirmed using targets and tentatively identified surfactant species in an environmental sample collected from the river Danube near Novi Sad (Serbia). The changes to MetFrag have been integrated into the command line version available at http://c-ruttkies.github.io/MetFrag and all resulting spectra and compounds are available in online resources and in the Electronic Supplementary Material (ESM). [less ▲]

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See detailFuture water quality monitoring: improving the balance between exposure and toxicity assessments of real-world pollutant mixtures
Altenburger, Rolf; Brack, Werner; Burgess, Robert M. et al

in Environmental Sciences Europe (2019), 31(1), 12

Environmental water quality monitoring aims to provide the data required for safeguarding the environment against adverse biological effects from multiple chemical contamination arising from anthropogenic ... [more ▼]

Environmental water quality monitoring aims to provide the data required for safeguarding the environment against adverse biological effects from multiple chemical contamination arising from anthropogenic diffuse emissions and point sources. Here, we integrate the experience of the international EU-funded project SOLUTIONS to shift the focus of water monitoring from a few legacy chemicals to complex chemical mixtures, and to identify relevant drivers of toxic effects. Monitoring serves a range of purposes, from control of chemical and ecological status compliance to safeguarding specific water uses, such as drinking water abstraction. Various water sampling techniques, chemical target, suspect and non-target analyses as well as an array of in vitro, in vivo and in situ bioanalytical methods were advanced to improve monitoring of water contamination. Major improvements for broader applicability include tailored sampling techniques, screening and identification techniques for a broader and more diverse set of chemicals, higher detection sensitivity, standardized protocols for chemical, toxicological, and ecological assessments combined with systematic evidence evaluation techniques. No single method or combination of methods is able to meet all divergent monitoring purposes. Current monitoring approaches tend to emphasize either targeted exposure or effect detection. Here, we argue that, irrespective of the specific purpose, assessment of monitoring results would benefit substantially from obtaining and linking information on the occurrence of both chemicals and potentially adverse biological effects. In this paper, we specify the information required to: (1) identify relevant contaminants, (2) assess the impact of contamination in aquatic ecosystems, or (3) quantify cause--effect relationships between contaminants and adverse effects. Specific strategies to link chemical and bioanalytical information are outlined for each of these distinct goals. These strategies have been developed and explored using case studies in the Danube and Rhine river basins as well as for rivers of the Iberian Peninsula. Current water quality assessment suffers from biases resulting from differences in approaches and associated uncertainty analyses. While exposure approaches tend to ignore data gaps (i.e., missing contaminants), effect-based approaches penalize data gaps with increased uncertainty factors. This integrated work suggests systematic ways to deal with mixture exposures and combined effects in a more balanced way, and thus provides guidance for future tailored environmental monitoring. [less ▲]

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See detailThe role of analytical chemistry in exposure science: Focus on the aquatic environment
Hernández, F.; Bakker, J.; Bijlsma, L. et al

in Chemosphere (2019), 222

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 ... [more ▼]

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. [less ▲]

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See detailNon-target screening reveals time trends of polar micropollutants in a riverbank filtration system
Albergamo, Vittorio; Schollée, Jennifer E.; Schymanski, Emma UL et al

in Environmental Science and Technology (2019), 53(13), 7584-7594

The historic emissions of polar micropollutants in a natural drinking water source were investigated by nontarget screening with high-resolution mass spectrometry and open cheminformatics tools. The study ... [more ▼]

The historic emissions of polar micropollutants in a natural drinking water source were investigated by nontarget screening with high-resolution mass spectrometry and open cheminformatics tools. The study area consisted of a riverbank filtration transect fed by the river Lek, a branch of the lower Rhine, and exhibiting up to 60-year travel time. More than 18,000 profiles were detected. Hierarchical clustering revealed that 43% of the 15 most populated clusters were characterized by intensity trends with maxima in the 1990s, reflecting intensified human activities, wastewater treatment plant upgrades and regulation in the Rhine riparian countries. Tentative structure annotation was performed using automated in silico fragmentation. Candidate structures retrieved from ChemSpider were scored based on the fit of the in silico fragments to the experimental tandem mass spectra, similarity to openly accessible accurate mass spectra, associated metadata, and presence in a suspect list. Sixty-seven unique structures (72 over both ionization modes) were tentatively identified, 25 of which were confirmed and included contaminants so far unknown to occur in bank filtrate or in natural waters at all, such as tetramethylsulfamide. This study demonstrates that many classes of hydrophilic organics enter riverbank filtration systems, persisting and migrating for decades if biogeochemical conditions are stable. [less ▲]

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See detailIdentifying Small Molecules in Untargeted Exposomics Data: A case study of Thirdhand Smoke
Schymanski, Emma UL; Torres, Sonia; Ramirez, Noelia

Scientific Conference (2019)

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See detailEnvironmental Cheminformatics to Identify Unknown Chemicals and their Effects
Schymanski, Emma UL

Scientific Conference (2019)

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See detailChemInChIformatics: IUPAC's Role in the Environmental Monitoring Revolution
Schymanski, Emma UL

Scientific Conference (2019)

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See detailMt Sinai Special Seminar: Finding Small Molecules in Big Data
Schymanski, Emma UL

Presentation (2019)

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See detailSWEMSA 2019: Finding Small Molecules in Big Data
Schymanski, Emma UL

Presentation (2019)

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See detailEstablish data infrastructure to compile and exchange environmental screening data on a European scale
Slobodnik, Jaroslav; Hollender, Juliane; Schulze, Tobias et al

in Environmental Sciences Europe (2019), 31(1), 65

Robust techniques based on liquid (LC) and gas chromatography (GC) coupled with high-resolution mass spectrometry (HR-MS) enable sensitive screening, identification, and (semi)quantification of thousands ... [more ▼]

Robust techniques based on liquid (LC) and gas chromatography (GC) coupled with high-resolution mass spectrometry (HR-MS) enable sensitive screening, identification, and (semi)quantification of thousands of substances in a single sample. Recent progress in computational sciences has enabled archiving and processing of HR-MS ‘big data’ at the routine level. As a result, community-based databases containing thousands of environmental pollutants are rapidly growing and large databases of substances with unique identifiers allowing for inter-comparison at the global scale have become available. A data-archiving infrastructure is proposed, allowing for retrospective screening of HR-MS data, which will help define the ‘chemical universe’ of organic substances and enable prioritisation of toxicants causing adverse environmental effects at the local, river basin, and national and European scale in support of the European water and chemicals management policy. [less ▲]

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See detail"MS-Ready" structures for non-targeted high-resolution mass spectrometry screening studies.
McEachran, Andrew D.; Mansouri, Kamel; Grulke, Chris et al

in Journal of cheminformatics (2018), 10(1), 45

Chemical database searching has become a fixture in many non-targeted identification workflows based on high-resolution mass spectrometry (HRMS). However, the form of a chemical structure observed in HRMS ... [more ▼]

Chemical database searching has become a fixture in many non-targeted identification workflows based on high-resolution mass spectrometry (HRMS). However, the form of a chemical structure observed in HRMS does not always match the form stored in a database (e.g., the neutral form versus a salt; one component of a mixture rather than the mixture form used in a consumer product). Linking the form of a structure observed via HRMS to its related form(s) within a database will enable the return of all relevant variants of a structure, as well as the related metadata, in a single query. A Konstanz Information Miner (KNIME) workflow has been developed to produce structural representations observed using HRMS ("MS-Ready structures") and links them to those stored in a database. These MS-Ready structures, and associated mappings to the full chemical representations, are surfaced via the US EPA's Chemistry Dashboard ( https://comptox.epa.gov/dashboard/ ). This article describes the workflow for the generation and linking of ~ 700,000 MS-Ready structures (derived from ~ 760,000 original structures) as well as download, search and export capabilities to serve structure identification using HRMS. The importance of this form of structural representation for HRMS is demonstrated with several examples, including integration with the in silico fragmentation software application MetFrag. The structures, search, download and export functionality are all available through the CompTox Chemistry Dashboard, while the MetFrag implementation can be viewed at https://msbi.ipb-halle.de/MetFragBeta/ . [less ▲]

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See detailAnnotating Nontargeted LC-HRMS/MS Data with Two Complementary Tandem Mass Spectral Libraries
Oberacher, Herbert; Reinstadler, Vera; Kreidl, Marco et al

in Metabolites (2018), 9(1 3),

Tandem mass spectral databases are indispensable for fast and reliable compound identification in nontargeted analysis with liquid chromatography–high resolution tandem mass spectrometry (LC-HRMS/MS ... [more ▼]

Tandem mass spectral databases are indispensable for fast and reliable compound identification in nontargeted analysis with liquid chromatography–high resolution tandem mass spectrometry (LC-HRMS/MS), which is applied to a wide range of scientific fields. While many articles now review and compare spectral libraries, in this manuscript we investigate two high-quality and specialized collections from our respective institutes, recorded on different instruments (quadrupole time-of-flight or QqTOF vs. Orbitrap). The optimal range of collision energies for spectral comparison was evaluated using 233 overlapping compounds between the two libraries, revealing that spectra in the range of CE 20–50 eV on the QqTOF and 30–60 nominal collision energy units on the Orbitrap provided optimal matching results for these libraries. Applications to complex samples from the respective institutes revealed that the libraries, combined with a simple data mining approach to retrieve all spectra with precursor and fragment information, could confirm many validated target identifications and yield several new Level 2a (spectral match) identifications. While the results presented are not surprising in many ways, this article adds new results to the debate on the comparability of Orbitrap and QqTOF data and the application of spectral libraries to yield rapid and high-confidence tentative identifications in complex human and environmental samples. [less ▲]

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See detailCommunity Resources Connecting Chemistry and Toxicity Knowledge to Environmental Observations
Schymanski, Emma UL; Williams, Antony J.

Scientific Conference (2018)

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See detailFinding Small Molecules in Big Data - Analytica Munich
Schymanski, Emma UL; Williams, Antony J.

Scientific Conference (2018)

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See detailPerformance of combined fragmentation and retention prediction for the identification of organic micropollutants by LC-HRMS.
Hu, Meng; Muller, Erik; Schymanski, Emma UL et al

in Analytical and bioanalytical chemistry (2018), 410(7), 1931-1941

In nontarget screening, structure elucidation of small molecules from high resolution mass spectrometry (HRMS) data is challenging, particularly the selection of the most likely candidate structure among ... [more ▼]

In nontarget screening, structure elucidation of small molecules from high resolution mass spectrometry (HRMS) data is challenging, particularly the selection of the most likely candidate structure among the many retrieved from compound databases. Several fragmentation and retention prediction methods have been developed to improve this candidate selection. In order to evaluate their performance, we compared two in silico fragmenters (MetFrag and CFM-ID) and two retention time prediction models (based on the chromatographic hydrophobicity index (CHI) and on log D). A set of 78 known organic micropollutants was analyzed by liquid chromatography coupled to a LTQ Orbitrap HRMS with electrospray ionization (ESI) in positive and negative mode using two fragmentation techniques with different collision energies. Both fragmenters (MetFrag and CFM-ID) performed well for most compounds, with average ranking the correct candidate structure within the top 25% and 22 to 37% for ESI+ and ESI- mode, respectively. The rank of the correct candidate structure slightly improved when MetFrag and CFM-ID were combined. For unknown compounds detected in both ESI+ and ESI-, generally positive mode mass spectra were better for further structure elucidation. Both retention prediction models performed reasonably well for more hydrophobic compounds but not for early eluting hydrophilic substances. The log D prediction showed a better accuracy than the CHI model. Although the two fragmentation prediction methods are more diagnostic and sensitive for candidate selection, the inclusion of retention prediction by calculating a consensus score with optimized weighting can improve the ranking of correct candidates as compared to the individual methods. Graphical abstract Consensus workflow for combining fragmentation and retention prediction in LC-HRMS-based micropollutant identification. [less ▲]

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