RESUMEN
Investigations into sample preparation procedures usually focus on analyte recovery with no information provided about the fate of other components of the sample (matrix). For many analyses, however, and particularly those using liquid chromatography-mass spectrometry (LC-MS), quantitative measurements are greatly influenced by sample matrix. Using the example of the drug amitriptyline and three of its metabolites in serum, we performed a comprehensive investigation of nine commonly used sample clean-up procedures in terms of their suitability for preparing serum samples. We were monitoring the undesired matrix compounds using a combination of charged aerosol detection (CAD), LC-CAD, and a metabolomics-based LC-MS/MS approach. In this way, we compared analyte recovery of protein precipitation-, liquid-liquid-, solid-phase- and hybrid solid-phase extraction methods. Although all methods provided acceptable recoveries, the highest recovery was obtained by protein precipitation with acetonitrile/formic acid (amitriptyline 113%, nortriptyline 92%, 10-hydroxyamitriptyline 89%, and amitriptyline N-oxide 96%). The quantification of matrix removal by LC-CAD showed that the solid phase extraction method (SPE) provided the lowest remaining matrix load (48-123 µg mL(-1)), which is a 10-40 fold better matrix clean-up than the precipitation- or hybrid solid phase extraction methods. The metabolomics profiles of eleven compound classes, comprising 70 matrix compounds showed the trends of compound class removal for each sample preparation strategy. The collective data set of analyte recovery, matrix removal and matrix compound profile was used to assess the effectiveness of each sample preparation method. The best performance in matrix clean-up and practical handling of small sample volumes was showed by the SPE techniques, particularly HLB SPE. CAD proved to be an effective tool for revealing the considerable differences between the sample preparation methods. This detector can be used to follow matrix compound elution during chromatographic separations, and the facile monitoring of matrix signal can assist in avoiding unfavourable matrix effects on analyte quantification.