Untargeted metabolomics based on gas chromatography-mass spectrometry and advanced chemometric tools for identifying responsible metabolites in lettuce exposed to emerging contaminants

In a context of climate change and a burgeoning world population, the pressure on water resources will grow. A great number of integrated water resource management schemes are being implemented with focus on the utilization of non-conventional water resources, such as treated wastewater (TWW) [1]. TWW may contain undesirable chemicals such as contaminants of emerging concern (CECs). Plant metabolomics aims to study the plant system at the molecular level to provide a non-biased characterization of the metabolome of a plant’s tissue in response to its environment [2]. In this study, a non-targeted metabolomic analysis was performed on lettuce exposed to nine CECs by irrigation and the subsequent changes have been traced comprehensively by gas chromatography-mass spectrometry (GC-MS) and the huge amount of acquired data was analyzed by advanced chemometric techniques. For this purpose, seedlings of lettuce were planted in experimental units consisted of 4.5 L cylindrical amber glass pots (Ø = 30 cm and 25 cm high) fitted with a tubing outlet at the bottom connected to drainage tubing (Ø = 1.5 cm). Treatments consisted of direct application of 0 (control sample), 100 and 500 μg L-1 of parabens (methyl, ethyl, propyl, and butyl-) and drugs (carbamazepine, mefenamic acid, diclofenac, gemfibrozil, and naproxen) per experimental unit (exposed samples with three replicates). Treatments were distributed among 10 experimental, starting 52 days after planting. After sampling, the leaves were comminuted with liquid nitrogen and stored at −20◦C until analysis. The extraction of metabolites was performed using a solvent extraction procedure as reported elsewhere [2]. For GC-MS analysis, 100 µL of 30 μL of N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA) with 1% trimethylchlorosilane (TMCS) was added to the dry residue and the mixture was injected into GC-MS. Then, two-way GC-MS data of control and exposed samples were arranged in a data matrix and analyzed by Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) to recover the pure elution and mass spectral of the metabolites [3]. The identity of the resolved components was determined from the spectral profiles match with NIST MS library. Then, the peak areas of the identified metabolites were calculated and arranged in a new data matrix to be analyzed by Partial Least Squares-Discriminant Analysis (PLS-DA) to find a boundary between control and exposed samples and also to find responsible metabolites using variable importance in projection (VIP). Finally, the metabolic pathways were determined using KEGG database. The metabolic response indicates that exposure to CECs at environmentally relevant concentrations causes large metabolic alterations in lettuce (carbohydrate metabolism, TCA cycle, pentose phosphate pathway, and glutathione pathway).