Identification of antimicrobial and glucocorticoid compounds in wastewater effluents with effect-directed analysis.

Pharmaceuticals, such as glucocorticoids and antibiotics, are inadequately removed from wastewater and may cause unwanted toxic effects in the receiving environment. This study aimed to identify contaminants of emerging concern in wastewater effluent with antimicrobial or glucocorticoid activity by applying effect-directed analysis (EDA). Effluent samples from six wastewater treatment plants (WWTPs) in the Netherlands were collected and analyzed with unfractionated and fractionated bioassay testing. Per sample, 80 fractions were collected and in parallel high-resolution mass spectrometry (HRMS) data were recorded for suspect and nontarget screening. The antimicrobial activity of the effluents was determined with an antibiotics assay and ranged from 298 to 711 ng azithromycin equivalents·L-1. Macrolide antibiotics were identified in each effluent and found to significantly contribute to the antimicrobial activity of each sample. Agonistic glucocorticoid activity determined with the GR-CALUX assay ranged from 98.1 to 286 ng dexamethasone equivalents·L-1. Bioassay testing of several tentatively identified compounds to confirm their activity revealed inactivity in the assay or the incorrect identification of a feature. Effluent concentrations of glucocorticoid active compounds were estimated from the fractionated GR-CALUX bioassay response. Subsequently, the biological and chemical detection limits were compared and a sensitivity gap between the two monitoring approaches was identified. Overall, these results emphasize that combining sensitive effect-based testing with chemical analysis can more accurately reflect environmental exposure and risk than chemical analysis alone.

Identifying antimicrobials and their metabolites in wastewater and surface water with effect-directed analysis.

This study aimed to identify antimicrobial contaminants in the aquatic environment with effect-directed analysis. Wastewater influent, effluent, and surface water (up- and downstream of the discharge location) were sampled at two study sites. The samples were enriched, subjected to high-resolution fractionation, and the resulting 80 fractions were tested in an antibiotics bioassay. The resulting bioactive fractions guided the suspect and nontargeted identification strategy in the high-resolution mass spectrometry data that was recorded in parallel. Chemical features were annotated with reference databases, assessed on annotation quality, and assigned identification confidence levels. To identify antibiotic metabolites, Phase I metabolites were predicted in silico for over 500 antibiotics and included as a suspect list. Predicted retention times and fragmentation patterns reduced the number of annotations to consider for confirmation testing. Overall, the bioactivity of three fractions could be explained by the identified antibiotics (clarithromycin and azithromycin) and an antibiotic metabolite (14-OH(R) clarithromycin), explaining 78% of the bioactivity measured at one study site. The applied identification strategy successfully identified antibiotic metabolites in the aquatic environment, emphasizing the need to include the toxic effects of bioactive metabolites in environmental risk assessments.

High-Performance Data Processing Workflow Incorporating Effect-Directed Analysis for Feature Prioritization in Suspect and Nontarget Screening.

Effect-directed analysis (EDA) aims at the detection of bioactive chemicals of emerging concern (CECs) by combining toxicity testing and high-resolution mass spectrometry (HRMS). However, consolidation of toxicological and chemical analysis techniques to identify bioactive CECs remains challenging and laborious. In this study, we incorporate state-of-the-art identification approaches in EDA and propose a robust workflow for the high-throughput screening of CECs in environmental and human samples. Three different sample types were extracted and chemically analyzed using a single high-performance liquid chromatography HRMS method. Chemical features were annotated by suspect screening with several reference databases. Annotation quality was assessed using an automated scoring system. In parallel, the extracts were fractionated into 80 micro-fractions each covering a couple of seconds from the chromatogram run and tested for bioactivity in two bioassays. The EDA workflow prioritized and identified chemical features related to bioactive fractions with varying levels of confidence. Confidence levels were improved with the in silico software tools MetFrag and the retention time indices platform. The toxicological and chemical data quality was comparable between the use of single and multiple technical replicates. The proposed workflow incorporating EDA for feature prioritization in suspect and nontarget screening paves the way for the routine identification of CECs in a high-throughput manner.

Development of a high-throughput bioassay for screening of antibiotics in aquatic environmental samples.

The goal of the present study was to select a Gram-positive (Gram+) and Gram-negative (Gram-) strain to measure antimicrobial activity in environmental samples, allowing high-throughput environmental screening. The sensitivity of eight pre-selected bacterial strains were tested to a training set of ten antibiotics, i.e. three Gram+ Bacillus subtilis strains with different read-outs, and five Gram- strains. The latter group consisted of a bioluminescent Allivibrio fischeri strain and four Escherichia coli strains, i.e. a wild type (WT) and three strains with a modified cell envelope to increase their sensitivity. The WT B. subtilis and an E. coli strain newly developed in this study, were most sensitive to the training set. This E. coli strain carries an open variant of an outer membrane protein combined with an inactivated multidrug efflux transport system. The assay conditions of these two strains were optimized and validated by exposure to a validation set of thirteen antibiotics with clinical and environmental relevance. The assay sensitivity ranged from the ng/mL to µg/mL range. The applicability of the assays for toxicological characterization of aquatic environmental samples was demonstrated for hospital effluent extract. A future application includes effect-directed analysis to identify yet unknown antibiotic contaminants or their transformation products.