Time and dose-dependent impairment of liver metabolism in Gasterosteus aculeatus following exposure to diclofenac (DCF) highlighted by LC-HRMS untargeted metabolomics.

Anthropogenic chemicals as emerging contaminants, such as pharmaceuticals, increased worldwide in the environment. This study aimed to apply metabolomics-based approaches on the fish model species three-spined stickleback (Gasterosteus aculeatus) exposed to diclofenac (DCF) to identify toxicity pathways and potential biomarkers. For this purpose, males and females were exposed to a continuous flow of diclofenac solution in laboratory for 21 days, followed by 3 days of depuration, to nominal concentrations of 1 (low) and 100 µg/L (high) of DCF. A methodology based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) was employed. Uni- and multivariate statistical analyses were combined to evaluate the modulations of the liver metabolome of G. aculeatus after exposure to DCF. The metabolomics data revealed variations both as a function of time and of the DCF concentration. We observed 2487 altered metabolites, with 1460 and 1027 specific to males and females, respectively. Some of them were significantly impaired by the experimental conditions. However, we showed that several metabolites were impacted by other factors as they were already modulated in the control individuals. The results indicated that the energy metabolism was up-modulated in females and down-modulated in males, with the presence of DCF. The antioxidant system was impacted in males, suggesting oxidative stress in the metabolism, while the immunity system was down-regulated in females following exposure. Moreover, our results revealed 1 and 4 metabolites as potential metabolic biomarkers in male and female sticklebacks, respectively. Among them, the glutaryl-carnitine and the adipoyl-carnitine were putatively identified in females, known to be implicated in the energy metabolism. These 5 metabolites showed to be promising biomarkers since they were early modulated during exposure to the stress and showed a notable trend through time.

An optimized LC-HRMS untargeted metabolomics workflow for multi-matrices investigations in the three-spined stickleback.

Environmental metabolomics has become a growing research field to understand biological and biochemical perturbations of organisms in response to various abiotic or biotic stresses. It focuses on the comprehensive and systematic analysis of a biologic system's metabolome. This allows the recognition of biochemical pathways impacted by a stressor, and the identification of some metabolites as biomarkers of potential perturbations occurring in a body. In this work, we describe the development and optimization of a complete reliable methodology based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) for untargeted metabolomics studies within a fish model species, the three-spined stickleback (Gasterosteus aculeatus). We evaluated the differences and also the complementarities between four different matrices (brain, gills, liver and whole fish) to obtain metabolome information. To this end, we optimized and compared sample preparation and the analytical method, since the type and number of metabolites detected in any matrix are closely related to these latter. For the sample preparation, a solid-liquid extraction was performed on a low quantity of whole fish, liver, brain, or gills tissues using combinations of methanol/water/heptane. Based on the numbers of features observed in LC-HRMS and on the responses of analytical standards representative of different metabolites groups (amino acids, sugars…), we discuss the influence of the nature, volume, and ratio of extraction solvents, the sample weight, and the reconstitution solvent. Moreover, the analytical conditions (LC columns, pH and additive of mobile phases and ionization modes) were also optimized so as to ensure the maximum metabolome coverages. Thus, two complementary chromatographic procedures were combined in order to cover a broader range of metabolites: a reversed phase separation (RPLC) on a C18 column followed by detection with positive ionization mode (ESI+) and a hydrophilic interaction chromatography (HILIC) on a zwitterionic column followed by detection with negative ionization mode (ESI-). This work provides information on brain, gills, liver, vs the whole body contribution to the stickleback metabolome. These information would help to guide ecotoxicological and biomonitoring studies.