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Due to recent technological advances in the field of HRMS, untargeted, hypothesis-generating metabolomics approaches have become a feasible approach to analysis of complex samples.1 Mass spectrometers capable of 100,000 resolution facilitating routine low part per million (ppm) mass accuracy have become widely available from multiple vendors.2,3 This mass accuracy allows greater specificity and confidence in a preliminary assignment of analyte identity, isotopic pattern recognition, and adduct identification.4 When coupled with an appropriate extraction procedure and high-performance LC or UPLC, complex mixtures can be analyzed with additional specificity derived from retention time data.5 UPLC possesses greater chromatographic efficiency and allows greater sensitivity, resolution and analysis time making a greater coverage of the metabolome possible.6 The resulting large datasets can be integrated into any of multiple differential analysis software and mined for useful patterns or individual analytes of interest.7,8,9,10,11 Putative hits can be initially identified using a combination of peak detection algorithms, accurate mass based chemical formula prediction, fragmentation prediction, and chemical database searching. This approach allows prioritization of targets for time-consuming complete structural identification or for development of more sensitive and more specific stable isotope dilution UPLC/selected or multiple reaction monitoring/MS studies that are the current gold standard methods for quantification.12
The varying nature of biological samples has led to optimization of extraction protocols for urine13, cells14, serum15, or tissue16. This protocol features extractions for cells, serum, and tissue. Where appropriate, comments and additional references have been included for modifications of the procedure to address inclusion of stable isotopes, or for inclusion of especially unstable metabolites.