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

High-performance thin-layer chromatography-umu combined with nontarget analysis-a sensitive genotoxicity screening tool applicable for potable water analysis

Monitoring of genotoxic chemicals released into the water cycle or formed through transformation processes is critical to prevent harm to human health. The development of the high-performance thin-layer chromatography (HPTLC)-umu bioassay combines sample separation and detection of genotoxic substances in the low ng/L concentration range. In this study, raw, process, and drinking water samples from 11 different waterworks in Germany were analyzed using the HPTLC-umu. A genotoxic response was detected in three out of 42 samples (one raw water sample and two drinking water samples). Genotoxicity testing using the micronucleus and p53-CALUX (chemical activated luciferase gene expression) assays revealed genotoxic effects for the raw water sample and one of the drinking water samples. Fortunately, only minor genotoxic effects could be detected in the two drinking water samples, with estimated 4-nitroquinoline-N-oxide equivalency concentrations of 0.12 ng/L and 0.17 ng/L, respectively. After extraction of the genotoxic zones from HPTLC plates, identification attempts were conducted with nontarget analysis (NTA). A prioritization approach based on chlorine and bromine isotope pattern revealed several halogenated features for both drinking water samples. These tentatively identified substances were previously reported in the literature as possible carcinogens. Although the detected features could not be conclusively identified, the presence of halogenated features in the genotoxic effective zone of the HPTLC-umu assay strongly suggests that the chlorine disinfection process in both waterworks was responsible for the formation of the genotoxic substances in the drinking water samples. These findings emphasize that the HPTLC-umu in combination with additional genotoxicity assays and NTA can be used to evaluate even relatively clean samples, such as drinking water.

Progress, applications, and challenges in high-throughput effect-directed analysis for toxicity driver identification - is it time for HT-EDA?

The rapid increase in the production and global use of chemicals and their mixtures has raised concerns about their potential impact on human and environmental health. With advances in analytical techniques, in particular, high-resolution mass spectrometry (HRMS), thousands of compounds and transformation products with potential adverse effects can now be detected in environmental samples. However, identifying and prioritizing the toxicity drivers among these compounds remain a significant challenge. Effect-directed analysis (EDA) emerged as an important tool to address this challenge, combining biotesting, sample fractionation, and chemical analysis to unravel toxicity drivers in complex mixtures. Traditional EDA workflows are labor-intensive and time-consuming, hindering large-scale applications. The concept of high-throughput (HT) EDA has recently gained traction as a means of accelerating these workflows. Key features of HT-EDA include the combination of microfractionation and downscaled bioassays, automation of sample preparation and biotesting, and efficient data processing workflows supported by novel computational tools. In addition to microplate-based fractionation, high-performance thin-layer chromatography (HPTLC) offers an interesting alternative to HPLC in HT-EDA. This review provides an updated perspective on the state-of-the-art in HT-EDA, and novel methods/tools that can be incorporated into HT-EDA workflows. It also discusses recent studies on HT-EDA, HT bioassays, and computational prioritization tools, along with considerations regarding HPTLC. By identifying current gaps in HT-EDA and proposing new approaches to overcome them, this review aims to bring HT-EDA a step closer to monitoring applications.

Identification of polar bioactive substances in the Upper Rhine using effect-directed analysis

Effect-Directed Analysis (EDA) was used to identify bioactive compounds in surface and well water from the Upper Rhine, and to evaluate their properties against the criteria set for Persistent, Mobile and Toxic (PMT) and very persistent and very mobile (vPvM) substances. A multi-layered solid-phase extraction was implemented to enrich a broad range of polar substances from the collected samples. The extracts were fractionated into 108 fractions and tested in the transthyretin (TTR)-binding assay measuring displacement of fluorescently labeled thyroxine (FITC-T4 TTR-binding assay) and the Aliivibrio fischeri bioluminescence (AFB) bioassay. Bioactive fractions guided the identification strategy using high-resolution mass spectrometry. Chemical features were systematically annotated using library databases and suspect lists, incorporating an automated assessment of the quality of each annotation. Based on this assessment, each chemical feature was assigned a specific identification confidence level. Identification of bioactive compounds was facilitated by using bioassay specific suspect lists that were extracted from an in-house developed database of positive and negative TTR-binding compounds and from a recently published database of active inhibitors of AFB. This resulted in the identification and confirmation of ten bioactive substances, including four evaluated as PMT and vPvM substances (diclofenac, trifloxystrobin acid, 6:2 FTSA and PFOA), and one as a potential PMT substance (4-aminoazobenzene). This study demonstrates the effectiveness of EDA in the identification of PMT/vPvM substances in the aquatic environment, facilitating their prioritization for comprehensive environmental risk assessment and possible regulation.

High-Efficiency Effect-Directed Analysis Leveraging Five High Level Advancements: A Critical Review

Organic contaminants are ubiquitous in the environment, with mounting evidence unequivocally connecting them to aquatic toxicity, illness, and increased mortality, underscoring their substantial impacts on ecological security and environmental health. The intricate composition of sample mixtures and uncertain physicochemical features of potential toxic substances pose challenges to identify key toxicants in environmental samples. Effect-directed analysis (EDA), establishing a connection between key toxicants found in environmental samples and associated hazards, enables the identification of toxicants that can streamline research efforts and inform management action. Nevertheless, the advancement of EDA is constrained by the following factors: inadequate extraction and fractionation of environmental samples, limited bioassay endpoints and unknown linkage to higher order impacts, limited coverage of chemical analysis (i.e., high-resolution mass spectrometry, HRMS), and lacking effective linkage between bioassays and chemical analysis. This review proposes five key advancements to enhance the efficiency of EDA in addressing these challenges: (1) multiple adsorbents for comprehensive coverage of chemical extraction, (2) high-resolution microfractionation and multidimensional fractionation for refined fractionation, (3) robust in vivo/vitro bioassays and omics, (4) high-performance configurations for HRMS analysis, and (5) chemical-, data-, and knowledge-driven approaches for streamlined toxicant identification and validation. We envision that future EDA will integrate big data and artificial intelligence based on the development of quantitative omics, cutting-edge multidimensional microfractionation, and ultraperformance MS to identify environmental hazard factors, serving for broader environmental governance.

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.