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

Abstract

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.

Metabolomic‐Based Comparison of Daphnia magna and Japanese Medaka Responses After Exposure to Acetaminophen, Diclofenac, and Ibuprofen

“…Polar metabolite extraction was performed for D. magna according to the method of Jeong & Simpson (2019) and for medaka based on other published methods (Lebeau‐Roche et al, 2021; Yoon et al, 2016). To ensure metabolite preservation, samples were placed on ice.…”

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

“…Depending on the mass available for each pool, 1 to 3 aliquots of 45.0 ± 0.2 mg dry weight (dw) were weighed in a 5 mL tube. Each sample was fortified with a spiking mixture of labeled internal standards (Table S1) prepared in ACN, then a solid-liquid extraction was performed with water, MeOH, and heptane as described in our previous study (Lebeau-Roche et al, 2021). Two aliquots of each final extract were transferred into two 2 mL tubes then dried under a slight nitrogen flow at 35°C.…”

“…HILIC acquisitions were performed with a Nucleodur HILIC-column (100 mm x 2 mm; 3 µm) from Macherey-Nagel (Hoerdt, France) in negative ionization mode and RPLC acquisitions with an Acquity UPLC® HSS T3 C18-column (100 mm x 2.1 mm; 1.8 µm) in positive ionization mode. The analysis conditions are described in Lebeau-Roche et al (2021). QCs were run several times at the beginning of the analytical sequence to equilibrate the column and at regular intervals throughout the sequence to check for instrument drift and to control analytical repeatability and sensitivity.…”