Metabolomics focuses on the characterisation of small-molecule metabolite profiles (Molecular weight < 2000 Da) specific to investigated pathways. Metabolomics studies usually require the preparation of extensive sample sets to allow significant differentiation between sample types in biological matrices. Hence, analytical data quality (i.e. low analytical variability) is essential to highlight true biological variability. Fatty acids are small molecules whose presence and abundance are key to many pathways in metabolic regulation. In this study, lipids were extracted from salmon tissue by an automated Folch extraction (an established manual approach) and the extracts were subjected to direct trans-methylation before injection on the GC-MS system. Automation ensures robustness of sample preparation and leads to improved data quality and reduced analytical variability. This application note compares standard Folch extraction with Folch extraction using bead beating to improve tissue extraction. Samples were analysed using a fully automated workflow on an Agilent 7200B GC/Q-TOF-MS. Very good agreement was achieved between the three replicates (RSD <10%) and when sampler were extracted using the standards approach and using bead beating. Fatty acids were successfully extracted and derivatised with very good reproducibility for both investigated methods, demonstrating the performance of the fully automated procedure. The reduction in analytical variability due to automation and potential to analyse a larger number of samples to increase the data set, gives significant advantage in Metabolomics studies.
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Fully automated on-line Folch Extraction and trans-methylation of fatty acids in salmon tissue