Pharmaceuticals released into the aquatic and soil environments can be absorbed by plants and soil organisms, potentially leading to the formation of unknown metabolites that may negatively affect these organisms or contaminate the food chain. The aim of this study was to identify pharmaceutical metabolites through a triplet approach for metabolite structure prediction (software-based predictions, literature review, and known common metabolic pathways), followed by generating in silico mass spectral libraries and applying various mass spectrometry modes for untargeted LC-qTOF analysis. Therefore, Eisenia fetida and Lactuca sativa were exposed to a pharmaceutical mixture (atenolol, enrofloxacin, erythromycin, ketoprofen, sulfametoxazole, tetracycline) under hydroponic and soil conditions at environmentally relevant concentrations. Samples collected at different time points were extracted using QuEChERS and analyzed with LC-qTOF in data-dependent (DDA) and data-independent (DIA) acquisition modes, applying both positive and negative electrospray ionization. The triplet approach for metabolite structure prediction yielded a total of 3762 pharmaceutical metabolites, and an in silico mass spectral library was created based on these predicted metabolites. This approach resulted in the identification of 26 statistically significant metabolites (p < 0.05), with DDA + and DDA - outperforming DIA modes by successfully detecting 56/67 sample type:metabolite combinations. Lettuce roots had the highest metabolite count (26), followed by leaves (6) and earthworms (2). Despite the lower metabolite count, earthworms showed the highest peak intensities, closely followed by roots, with leaves displaying the lowest intensities. Common metabolic reactions observed included hydroxylation, decarboxylation, acetylation, and glucosidation, with ketoprofen-related metabolites being the most prevalent, totaling 12 distinct metabolites. In conclusion, we developed a high-throughput workflow combining open-source software with LC-HRMS for identifying unknown metabolites across various sample types.

• Keywords
• High-resolution mass spectrometry, In silico spectral library, Liquid chromatography, Metabolite identification in Eisenia fetida and Lactuca sativa, Pharmaceuticals, Software prediction,
• MeSH
• Chromatography, Liquid methods   MeSH
• Mass Spectrometry methods   MeSH
• Soil Pollutants analysis   metabolism   MeSH
• Pharmaceutical Preparations metabolism   chemistry   analysis   MeSH
• Oligochaeta * metabolism   chemistry   MeSH
• Computer Simulation MeSH
• Lactuca * metabolism   chemistry   MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Soil Pollutants MeSH
• Pharmaceutical Preparations MeSH

The accumulation of six pharmaceuticals of different therapeutic uses has been thoroughly investigated and compared between onion, spinach, and radish plants grown in six soil types. While neutral molecules (e.g., carbamazepine (CAR) and some of its metabolites) were efficiently accumulated and easily translocated to the plant leaves (onion > radish > spinach), the same for ionic (both anionic and cationic) molecules seems to be minor to moderate. The maximum accumulation of CAR crosses 38,000 (onion), 42,000 (radish), and 7000 (spinach) ng g-1 (dry weight) respectively, in which the most majority of them happened within the plant leaves. Among the metabolites, the accumulation of carbamazepine 10,11-epoxide (EPC - a primary CAR metabolite) was approximately 19,000 (onion), 7000 (radish), and 6000 (spinach) ng g-1 (dry weight) respectively. This trend was considerably similar even when all these pharmaceuticals applied together. The accumulation of most other molecules (e.g., citalopram, clindamycin, clindamycin sulfoxide, fexofenadine, irbesartan, and sulfamethoxazole) was restricted to plant roots, except for certain cases (e.g., clindamycin and clindamycin sulfoxide in onion leaves). Our results clearly demonstrated the potential role of this accumulation process on the entrance of pharmaceuticals/metabolites into the food chain, which eventually becomes a threat to associated living biota.

• Keywords
• Metabolism, Pharmaceutical accumulation, Pharmaceuticals, Plant-dependent transformation of pharmaceuticals, Plants, Root uptake, Soils, Translocation of pharmaceuticals in plant,
• MeSH
• Onions MeSH
• Clindamycin metabolism   MeSH
• Soil Pollutants * analysis   MeSH
• Pharmaceutical Preparations metabolism   MeSH
• Soil chemistry   MeSH
• Raphanus * metabolism   MeSH
• Plants metabolism   MeSH
• Spinacia oleracea metabolism   MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Clindamycin MeSH
• Soil Pollutants * MeSH
• Pharmaceutical Preparations MeSH
• Soil MeSH

Food contamination is a major worldwide risk for human health. Dynamic plant uptake of pollutants from contaminated environments is the preferred pathway into the human and animal food chain. Mechanistic models represent a fundamental tool for risk assessment and the development of mitigation strategies. However, difficulty in obtaining comprehensive observations in the soil-plant continuum hinders their calibration, undermining their generalizability and raising doubts about their widespread applicability. To address these issues, a Bayesian probabilistic framework is used, for the first time, to calibrate and assess the predictive uncertainty of a mechanistic soil-plant model against comprehensive observations from an experiment on the translocation of carbamazepine in green pea plants. Results demonstrate that the model can reproduce the dynamics of water flow and solute reactive transport in the soil-plant domain accurately and with limited uncertainty. The role of different physicochemical processes in bioaccumulation of carbamazepine in fruits is investigated through Global Sensitivity Analysis, which shows how soil hydraulic properties and soil solute sorption regulate transpiration streams and bioavailability of carbamazepine. Overall, the analysis demonstrates the usefulness of mechanistic models and proposes a comprehensive numerical framework for their assessment and use.

• MeSH
• Bayes Theorem MeSH
• Pisum sativum MeSH
• Carbamazepine analysis   MeSH
• Soil Pollutants * analysis   MeSH
• Humans MeSH
• Soil * MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Carbamazepine MeSH
• Soil Pollutants * MeSH
• Soil * MeSH

Soils can be contaminated by pharmaceuticals. The aim of this study was to evaluate the impact of soil conditions (influencing sorption and persistence of pharmaceuticals in soils) and plant type on the root uptake of selected pharmaceuticals and their transformation in plant-soil systems. Four plants (lamb's lettuce, spinach, arugula, radish) planted in 3 soils were irrigated for 20 days (26) with water contaminated by one of 3 pharmaceuticals (carbamazepine, atenolol, sulfamethoxazole) or their mixture. The concentrations of pharmaceuticals and their metabolites in soils and plant tissues were evaluated after the harvest. Sulfamethoxazole and atenolol dissipated rapidly from soils. The larger concentrations of both compounds and an atenolol metabolite were found in roots than in leaves. Sulfamethoxazole metabolites were below the limits of quantifications. Carbamazepine was stable in soils, easily uptaken, accumulated, and metabolized in plant leaves. The efficiency of radish and arugula (both family Brassicaceae) in metabolizing was very low contrary to the high and moderate efficiencies of lamb's lettuce and spinach, respectively. Compounds' transformations mostly masked the soil impact on their accumulation in plant tissues. The negative relationships were found between the carbamazepine sorption coefficients and its concentrations in roots of radish, lamb's lettuce, and spinach.

• Keywords
• Compound’s translocation in plant, Metabolites, Pharmaceuticals, Plant-dependent compound’s transformation, Plants, Root uptake, Soils,
• MeSH
• Atenolol metabolism   MeSH
• Carbamazepine analysis   metabolism   MeSH
• Soil Pollutants analysis   metabolism   MeSH
• Plant Leaves metabolism   MeSH
• Soil MeSH
• Raphanus metabolism   MeSH
• Plants metabolism   MeSH
• Sulfamethoxazole metabolism   MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Atenolol MeSH
• Carbamazepine MeSH
• Soil Pollutants MeSH
• Soil MeSH
• Sulfamethoxazole MeSH