In vitro bioanalytical assessment of toxicity of wetland samples from Spanish Mediterranean coastline

Background Fresh water bodies represent less than 1% of overall amount of water on earth and ensuring their quality and sustainability is pivotal. Although several campaigns have been performed to monitor the occurrence of micropollutants by means of chemical analysis, this might not cover the whole set of chemicals present in the sample nor the potential toxic effects of mixtures of natural and anthropogenic chemicals. In this sense, by selecting relevant toxicity endpoints when performing in vitro bioanalysis, effect-based methodologies can be of help to perform a comprehensive assessment of water quality and reveal biological activities relevant to adverse health effects. However, no prior bioanalytical study was performed in wetland water samples from the Spanish Mediterranean coastline. Methods Eleven samples from relevant water bodies from the Spanish Mediterranean coastline were collected to monitor water quality on 8 toxicity endpoints. Aryl hydrocarbon receptor (AhR), androgenicity (AR+ and AR-), estrogenicity (ER+ and ER-), oxidative stress response (Nrf2) and vitamin D receptor (VDR+ and VDR-) reporter gene assays were evaluated. Results AhR was the reporter gene assay showing a more frequent response over the set of samples (activated by 9 out of 11 samples), with TCDD-eq in the range 7.7-22.2 pM. For AR, ER and VDR assays sporadic activations were observed. Moreover, no activity was observed on the Nrf2 reporter gene assay. Wastewater and street runaway streams from Valencia could be responsible for enhanced activities in one of the water inputs in the Natural Park 'L'Albufera'. Conclusions Water quality of relevant wetlands from the Spanish Mediterranean coastline has been evaluated. The utilization of a panel of 5 different bioassays to cover for different toxicity endpoints has demonstrated to be a good tool to assess water quality

Prediction of Retention Time and Collision Cross Section (CCSH plus , CCSH-, and CCSNa plus ) of Emerging Contaminants Using Multiple Adaptive Regression Splines

Ultra-high performance liquid chromatography coupled to ion mobility separation and high-resolution mass spectrometry instruments have proven very valuable for screening of emerging contaminants in the aquatic environment. However, when applying suspect or nontarget approaches (i.e., when no reference standards are available), there is no information on retention time (RT) and collision cross-section (CCS) values to facilitate identification. In silico prediction tools of RT and CCS can therefore be of great utility to decrease the number of candidates to investigate. In this work, Multiple Adaptive Regression Splines (MARS) were evaluated for the prediction of both RT and CCS. MARS prediction models were developed and validated using a database of 477 protonated molecules, 169 deprotonated molecules, and 249 sodium adducts. Multivariate and univariate models were evaluated showing a better fit for univariate models to the experimental data. The RT model (R2 = 0.855) showed a deviation between predicted and experimental data of +/- 2.32 min (95% confidence intervals). The deviation observed for CCS data of protonated molecules using the CCSH model (R2 = 0.966) was +/- 4.05% with 95% confidence intervals. The CCSH model was also tested for the prediction of deprotonated molecules, resulting in deviations below +/- 5.86% for the 95% of the cases. Finally, a third model was developed for sodium adducts (CCSNa, R2 = 0.954) with deviation below +/- 5.25% for 95% of the cases. The developed models have been incorporated in an open-access and user-friendly online platform which represents a great advantage for third-party research laboratories for predicting both RT and CCS data

Are preserved coastal water bodies in Spanish Mediterranean basin impacted by human activity? Water quality evaluation using chemical and biological analyses

The Spanish Mediterranean basin is particularly susceptible to climate change and human activities, making it vulnerable to the influence of anthropogenic contaminants. Therefore, conducting comprehensive and exhaustive water quality assessment in relevant water bodies of this basin is pivotal. In this work, surface water samples from coastal lagoons or estuaries were collected across the Spanish Mediterranean coastline and subjected to target and suspect screening of 1,585 organic micropollutants by liquid chromatography coupled to ion mobility separation and high resolution mass spectrometry. In total, 91 organic micropollutants could be confirmed and 5 were tentatively identified, with pharmaceuticals and pesticides being the most prevalent groups of chemicals. Chemical analysis data was compared with data on bioanalysis of those samples (recurrent aryl hydrocarbon receptor (AhR) activation, and estrogenic receptor (ER) inhibition in wetland samples affected by wastewater streams). The number of identified organic contaminants containing aromatic rings could explain the AhR activation observed. For the ER antagonistic effects, predictions on estrogenic inhibition potency for the detected compounds were used to explain the activities observed. The integration of chemical analysis with bioanalytical observations allowed a comprehensive overview of the quality of the water bodies under study

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

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

New developments to refine target, suspect and non-target screening strategies for comprehensive monitoring of the aquatic environment

Compendi d'articlesThe amount of organic micropollutants (OMP) currently being released to the aquatic environment is incommensurable. Thus, different analytical strategies were developed over the recent years to monitor the occurrence of OMP in environmental samples. In this thesis, different tools have been applied to refine target, suspect and non-target screening strategies for the monitoring of the aquatic environment with special emphasis on the hyphenation of ion mobility separation (IMS) to high resolution mass spectrometry. Additionally, the development of refinement tools for suspect screening strategies such as retention time indexing or in silico prediction of IMS data, as well as the implementation of effect-directed analysis for a comprehensive overview of the quality of water bodies have also been explored. Finally, the monitoring of new psychoactive substances in complex matrices such as influent wastewater and pooled urine samples is evaluated, with special aid of the previously developed tools.La cantidad de microcontaminantes orgánicos (OMP) emitidos al medio ambiente acuático en la actualidad es incalculable. Por ello, se han desarrollado distintas estrategias analíticas para monitorizar la incidencia de OMP en muestras ambientales. En esta tesis se han aplicado diferentes herramientas para refinar estrategias de cribado dirigidas, de sospechosos y no dirigidas para la monitorización del medio ambiente acuático con especial énfasis en el acoplamiento de la separación por movilidad iónica (IMS) con espectrometría de masas de alta resolución. Adicionalmente, se ha explorado el desarrollo de herramientas de mejora para los cribados de sospechosos como, por ejemplo, indexación de tiempo de retención o predicción computacional de datos de IMS, así como la implementación de análisis basados en efecto (EDA) para una visión completa de la calidad de los cuerpos acuáticos. Finalmente, se ha evaluado la monitorización de Nuevas Sustancias Psicoactivas (NPS) en muestras complejas tales como aguas residuales y orina.Programa de Doctorat en Cièncie