In CADET, we have the capabilities and experience to investigate a range of sample types including cells, tissues and biofluids. The sample preparation, data acquisition and data processing methods applied are dependent on the type of study being performed, the level of quantitative data required and the sample type. Quality Control (QC) and Quality Assurance (QA) in targeted and untargeted studies are very important. In CADET, we apply QC samples for all untargeted and targeted studies.
Untargeted methods/metabolic profiling
Sample preparation for biofluids generally involves the removal of high molecular weight chemicals (for instance, proteins and DNA) from the sample through their precipitation with an organic solvent. For example, in the preparation of serum, we apply a 3:1 ratio of methanol:serum to precipitate protein and nucleic acids followed by centrifugation to leave a metabolite-containing extraction solution for analysis . Typical samples volumes required are 50-100μl for each analysis; dual analysis applying gas chromatography-mass spectrometry (GC-MS) and ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS), would require twice this volume.
Sample preparation for cells and tissues is more complex. For tissues, a combined homogenisation and extraction protocol is performed applying a QIAGEN TissueLyser and a two-phase solvent extraction to produce a Folch-type extraction: methanol, water and chloroform are applied as extraction solvents resulting in two immiscible layers; the methanol/water layer contains hydrophilic metabolites and the chloroform layer contains lipophilic metabolites. This provides the maximum level of metabolome coverage through selective extraction of different classes of metabolites followed by analysis of hydrophilic metabolites by GC-MS and lipophilic metabolites by UHPLC-MS. For cells, fracturing of cell membranes and intracellular metabolite extraction is performed by applying multiple freeze/thaw cycles to the cell pellet suspended in either a hydrophilic or combined hydrophilic/lipophilic extraction solvent.
In CADET for our hypothesis-generating studies, we employ chromatography-mass spectrometry for the study of complex sample extracts containing 100-1000s of unique metabolites. Chromatographic separation is optimised for a large range of metabolites that have diverse physicochemical properties by changing instrument parameters including temperature and mobile phase composition among others. The flow from the chromatography column is then introduced into the mass spectrometer where metabolites are ionised (to positively or negatively charged ions) and their mass-to-charge (m/z) ratio is accurately determined. The number of ions detected is proportional to the concentration of metabolite present and relative changes between the peak areas for a metabolite in different samples are calculated to define biological differences. The identification of metabolites is performed using m/z, retention time/index and fragmentation mass spectra and comparison to mass spectral libraries or metabolite/chemical databases [2,3].
Gas chromatography-mass spectrometry (GC-MS) and ultra-high performance liquid chromatography-mass spectrometry (UHPLC-Orbitrap-MS) are applied in untargeted studies. GC-MS is used for the study of primarily hydrophilic metabolites present in central metabolism and we can identify approximately 80 to 100 such metabolites including amino acids, monosaccharides, organic acids and glycolytic intermediates (Figure 1). UPLC-MS is used primarily for the study of lipophilic metabolites, where we can identify approximately 200 to 250 lipids, including phosphocholines, phosphoethanolamines, inositol phosphates, cholesteryl esters, and di- and tri-glycerides, etc. (Figure 2).
Figure 1. GC-MS of human brain, where 80 metabolites were identified and reported.
Figure 2. Lipid coverage using LC-MS; for simplicity, only selected classes are labelled.
Sample preparation of organic metabolites for targeted analysis follows a similar workflow as for untargeted analysis. However, further sample preparation may be applied to the crude extract to reduce the large number of metabolites present in the sample matrix. This can include liquid-liquid extraction and solid phase extraction. Samples are then analysed along with calibration standards to provide absolute quantification data. We employ UPLC-QQQ-MS with selected reaction monitoring (SRM) to provide high specificity and sensitivity. All data are quantitative; metabolite concentrations are determined by comparison of the analyte in biological samples to calibration curves constructed with authentic chemical standards and chemically similar internal standards.
 Dunn WB, Broadhurst D, et al. ‘Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry.’ Nature Protocols 2011 6:1060-83. [http://www.ncbi.nlm.nih.gov/pubmed/?term= 21720319]
 Brown, M., Wedge, D.C., Goodacre, R., Kell, D.B., Baker, P.N., Kenny, L.C., Mamas, M.A., Neyses, L., Dunn, W.B. ‘Automated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets.’ Bioinformatics 2011 27:1108-12. [http://www.ncbi.nlm.nih.gov/pubmed/?term= 21325300]
 Brown, M., Dunn, W.B., Dobson, P., Patel, Y., Winder, C.L., Francis-McIntyre, S., Begley, P., Carroll, K., Broadhurst, D., Tseng, A., Swainston, N., Spasic, I., Goodacre, R., Kell, D.B. ‘Mass spectrometry tools and metabolite-specific databases for molecular identification in metabolomics.’ Analyst 2009 134:1322-1332. [http://www.ncbi.nlm.nih.gov/pubmed/?term= 19562197]