Feature-based molecular networking for identification of organic micropollutants including metabolites by non-target analysis applied to riverbank filtration.

Due to growing concern about organic micropollutants and their transformation products (TP) in surface and drinking water, reliable identification of unknowns is required. Here, we demonstrate how non-target liquid chromatography (LC)-high-resolution tandem mass spectrometry (MS/MS) and the feature-based molecular networking (FBMN) workflow provide insight into water samples from four riverbank filtration sites with different redox conditions. First, FBMN prioritized and connected drinking water relevant and seasonally dependent compounds based on a modification-aware MS/MS cosine similarity. Within the resulting molecular networks, forty-three compounds were annotated. Here, carbamazepine, sartans, and their respective TP were investigated exemplarily. With chromatographic information and spectral similarity, four additional TP (dealkylated valsartan, dealkylated irbesartan, two oxygenated irbesartan isomers) and olmesartan were identified and partly verified with an authentic standard. In this study, sartans and TP were investigated and grouped regarding their removal behavior under different redox conditions and seasons for the first time. Antihypertensives were grouped into compounds being well removed during riverbank filtration, those primarily removed under anoxic conditions, and rather persistent compounds. Observed seasonal variations were mainly limited to varying river water concentrations. FBMN is a powerful tool for identifying previously unknown or unexpected compounds and their TP in water samples by non-target analysis.

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

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

Impact of seasonality, redox conditions, travel distances and initial concentrations on micropollutant removal during riverbank filtration at four sites.

Riverbank filtration (RBF) is a reliable water purification technique that has proven to be suitable for the removal of organic micropollutants. Its removal efficiency and dependency on a variety of factors such as redox conditions, temperatures, geology, travel times, level of initial micropollutant concentrations and seasonality were investigated during three seasonal sampling campaigns. Two anoxic (silty sand, Ems river) and two oxic (gravel, Ruhr river) RBF sites in Germany with different travel distances (42-633 m) were studied. Micropollutant concentrations were examined using a large-volume direct injection liquid chromatography method coupled to high-resolution mass spectrometry. Seasonal differences in micropollutant concentrations in the rivers were observed for chlorotolurone, diclofenac, terbuthylazine, mecoprop-P, MCPA (2-methyl-4-chlorophenoxyacetic acid) and propyphenazone. Redox dependencies in RBF were only found for sulfamethoxazole, propyphenazone, terbuthylazine and carbamazepine. Data for oxazepam, tramadol, N-desmethyl-tramadol, tilidin-desmethyl, carbamazepine and carbendazim indicate a required minimum travel distance of e.g. 100-200 m for the complete removal. Notably, travel time did not seem to be a substantial factor for their removal. High conductivity aquifers are also well suited for micropollutant removal. Seasonal initial concentration level variations showed no impact on the resulting abstraction well concentrations. Although the calculated removal efficiencies varied, they proved to be improper for seasonal raw water quality comparison. Knowledge of micropollutant behavior in riverbank filtration was broadened and RBF proved to be well suited for effective micropollutant reduction throughout the year, yet for a complete removal long travel distances or further technical purification steps are required.

Determination of food allergens by LC-MS: Impacts of sample preparation, food matrix, and thermal processing on peptide detectability and quantification.

Food allergies are a growing worldwide concern and the contamination of products with food allergens represents a significant health risk to allergic consumers. With the introduction of reference doses, quantitative methods are needed for the monitoring of allergen levels, and the potential of LC-MS/MS is of hugely growing interest. In this study, we demonstrate that relevant food matrices (bakery products and chocolates) and thermal food processing substantially influence the quantification of 18 marker peptides from various nut and peanut allergens via targeted proteomics. In addition, we characterize the individual release kinetics of marker peptides and provide examples for metastable marker peptide candidates. Matrix recovery rates overall ranged between 15 and 250% with the observed variation being linked to the individual peptide structure as well as to specific matrix interferences. In contrast, thermal processing considerably influences the detectability of allergens on the protein level as different marker peptides from the identical parent allergen are similarly affected, leading to a loss in signal of up to 83% in extreme cases after a 45-min simulated baking. Provided data are finally used for evaluation of different calibrators as well as the overall potential and challenges of LC-MS for the absolute quantification of food allergens. SIGNIFICANCE: With the scientific discussion moving towards a risk-based management of food allergens, including the establishment of threshold doses, robust methods for the absolute quantification of allergens in food samples are urgently needed. Because the currently used antibody- and DNA-based technologies show severe limitations in terms of specificity and reproducibility, LC-MS has emerged as a promising alternative. Its application to absolute quantification, however, first requires an understanding of the various impacts that affect quantification results, including different food matrices, sample preparation, and thermal processing of foodstuffs. Knowledge of these factors, which are assessed as part of a comprehensive survey in this study, is also an important prerequisite to evaluate means of calibration for an LC-MS-based quantification of food allergens.