Enhanced database creation with in silico workflows for suspect screening of unknown tebuconazole transformation products in environmental samples by UHPLC-HRMS

Screening and identification of unknown chemical contaminants in food based on liquid chromatography-high-resolution mass spectrometry and machine learning

Unknown or unexpected chemical contaminants and/or their transformation products in food that may be harmful to humans need to be discovered for comprehensive safety evaluation. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is a powerful tool for detecting chemical contaminants in food samples. However, identifying all of peaks in LC-HRMS is not possible, but if class information is known in advance, further identification will become easier. In this work, a novel MS2 spectra classification-driven screening strategy was constructed based on LC-HRMS and machine learning. First, the classification model was developed based on machine learning algorithm using class information and experimental MS2 data of chemical contaminants and other non-contaminants. By using the developed artificial neural network classification model, in total 32 classes of pesticides, veterinary drugs and mycotoxins were classified with good prediction accuracy and low false-positive rate. Based on the classification model, a screening procedure was developed in which the classes of unknown features in LC-HRMS were first predicted through the classification model, and then their structures were identified under the guidance of class information. Finally, the developed strategy was tentatively applied to the analysis of pork and aquatic products, and 8 chemical contaminants and 11 transformation products belonging to 8 classes were found. This strategy enables screening of unknown chemical contaminants and transformation products in complex food matrices.

A comprehensive review on toxicological mechanisms and transformation products of tebuconazole: Insights on pesticide management

Tebuconazole has been widely applied over three decades because of its high efficiency, low toxicity, and broad spectrum, and it is still one of the most popular fungicides worldwide. Tebuconazole residues have been frequently detected in environmental samples and food, posing potential hazards for humans. Understanding the toxicity of pesticides is crucial to ensuring human and ecosystem health, but the toxic mechanisms and toxicity of tebuconazole are still unclear. Moreover, pesticides could transform into transformation products (TPs) that may be more persistent and toxic than their parents. Herein, the toxicities of tebuconazole to humans, mammals, aquatic organisms, soil animals, amphibians, soil microorganisms, birds, honeybees, and plants were summarized, and its TPs were reviewed. In addition, the toxicity of tebuconazole TPs to aquatic organisms and mammals was predicted. Tebuconazole posed potential developmental toxicity, genotoxicity, reproductive toxicity, mutagenicity, hepatotoxicity, neurotoxicity, cardiotoxicity, and nephrotoxicity, which were induced via reactive oxygen species-mediated apoptosis, metabolism and hormone perturbation, DNA damage, and transcriptional abnormalities. In addition, tebuconazole exhibited apparent endocrine-disrupting effects by modulating hormone levels and gene transcription. The toxicity of some TPs was equivalent to and higher than tebuconazole. Therefore, further investigation is necessary into the toxicological mechanisms of tebuconazole and the combined toxicity of a mixture of tebuconazole and its TPs.

Non-target analysis for water characterization: wastewater treatment impact and selection of relevant features

Non-target analyses were conducted to characterize and compare the molecular profiles (UHPLC-HRMS fingerprint) of water samples from a wastewater treatment plant (WWTP). Inlet and outlet samples were collected from three campaigns spaced 6 months apart in order to highlight common trends. A significant impact of the treatment on the sample fingerprints was shown, with a 65-70% abatement of the number of features detected in the effluent, and more polar, smaller and less intense molecules found overall compared to those in WWTP influent waters. Multivariate analysis (PCA) associated with variations of the features between inlets and outlets showed that features appearing or increasing were correlated with effluents while those disappearing or decreasing were correlated with influents. Finally, effluent features considered as relevant to a potentially adverse effect on aqueous media (i.e. those which appeared or increased or slightly varied from the influent) were highlighted. Three hundred seventy-five features common with the 3 campaigns were thus selected and further characterized. For most of them, elementary composition was found to be C, H, N, O (42%) and C, H, N, O, P (18%). Considering the MS2 spectra and several reference MS2 databases, annotations were proposed for 35 of these relevant features. They include synthetic products, pharmaceuticals and metabolites.

Combining predictive and analytical methods to elucidate pharmaceutical biotransformation in activated sludge

While man-made chemicals in the environment are ubiquitous and a potential threat to human health and ecosystem integrity, the environmental fate of chemical contaminants such as pharmaceuticals is often poorly understood. Biodegradation processes driven by microbial communities convert chemicals into transformation products (TPs) that may themselves have adverse ecological effects. The detection of TPs formed during biodegradation has been continuously improved thanks to the development of TP prediction algorithms and analytical workflows. Here, we contribute to this advance by (i) reviewing past applications of TP identification workflows, (ii) applying an updated workflow for TP prediction to 42 pharmaceuticals in biodegradation experiments with activated sludge, and (iii) benchmarking 5 different pathway prediction models, comprising 4 prediction models trained on different datasets provided by enviPath, and the state-of-the-art EAWAG pathway prediction system. Using the updated workflow, we could tentatively identify 79 transformation products for 31 pharmaceutical compounds. Compared to previous works, we have further automatized several steps that were previously performed by hand. By benchmarking the enviPath prediction system on experimental data, we demonstrate the usefulness of the pathway prediction tool to generate suspect lists for screening, and we propose new avenues to improve their accuracy. Moreover, we provide a well-documented workflow that can be (i) readily applied to detect transformation products in activated sludge and (ii) potentially extended to other environmental studies.

Does climbazole instigate a threat in the environment as persistent, mobile and toxic compound? Unveiling the occurrence and potential ecological risks of its phototransformation products in the water cycle

Persistent, mobile, and toxic chemicals (PMT), such as the antimycotic climbazole-(CBZ), proliferate in water cycle and imperil drinking water quality, sparking off research about their environmental fate. Unlike the parent compound, its transformation products-(TPs) are scarcely investigated, much less as PMTs. To this end, phototransformation of CBZ was investigated. A novel suspect-screening workflow was developed and optimized by cross-comparing the results of the identified photo-TPs against literature data to create an enhanced HRMS-database for environmental investigations of CBZ/TPs in the water cycle. In total, 24 TPs were identified, 14 of which are reported for the first time. Isomerism, dechlorination, hydroxylation, and cleavage of the ether or C-N bond are suggested as the main transformation routes. A screening of CBZ/TPs was conducted in wastewater, leachates, surface, and groundwater, revealing a maximum concentration of 464.8 ng/L in groundwater. In silico and in vitro methods were used for toxicity assessment, indicating toxicity for CBZ and some TPs. Seemingly, CBZ is rightly considered as PMT, and a higher potential to occur in surface or groundwater than non-PM chemicals appears. Likewise, the occurrence of TPs due to PMT properties or emission patterns was evaluated.