Optimization of SPME coating characteristics for metabolomics and targeted analysis with LC/MS
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Metabolomics data provides complementary information to proteomics, genomics, and transcriptomics, in addition to enabling the tracking of the dynamic reactions in living systems. Metabolomics is widely used in various areas of study such as human diseases, drug discovery, plant analysis, and human nutrition. In metabolomics, the workflow for quantitative and comprehensive metabolic mapping of cellular metabolites can be a very challenging undertaking. Sampling and sample preparation play an important role in untargeted analysis as they influence the final composition of the analyzed extract, which can consequently influence the obtained metabolome. The choice of sample preparation method for metabolomics is based on factors such as non-selectivity, high reproducibility, integration of metabolism quenching, and extraction of a wide range of metabolite polarities. It should provide a good representation of the sample under study and obtain high sample clean-up so as to reduce matrix effects, especially when liquid chromatography coupled mass spectrometry (LC-MS) instrumentation is used for analysis. Solid phase microextraction (SPME) has already been demonstrated as a suitable technique for metabolic profiling of various biological matrices. This noninvasive and solventless extraction technique eliminates the need for metabolism quenching steps, as the coating selectively extracts metabolites, eliminating the co-extraction of interfering biomacromolecules such as proteins or enzymes. One of the main objectives of the currently presented research was the development of a new extraction phase that is compatible with complex food matrices and that provides high extraction recovery for a wide range of metabolites. For this purpose, initial research involved the preparation of a silica-based ionic liquid coating as a stationary phase for a 96-blade SPME system for the extraction of polar metabolites from grape juice without any further sample pretreatment. The lab-made polymer demonstrated high physical and chemical stability, and results indicated that the properties of the coating could be changed by changing the functional groups during the synthesis procedure. Chapter 3 presents different SPME coating chemistries that were developed and applied to provide simultaneous extraction of a wide range of both hydrophobic and hydrophilic cellular metabolites produced by a model organism, Escherichia coli (E.coli). This research reports the first successful application of the developed 96-blade SPME method coupled to LC-MS for bacteria and plant metabolomics. Three different LC-MS methods were also evaluated for the analysis of extracted metabolites. The Orbitrap system provided a powerful platform for metabolomics due its high resolution and mass accuracy. Among different coating chemistries applied for analysis, polystyrene–divinylbenzene–weak anion exchange (PS-DVB-WAX), hydrophilic–lipophilic balance particles (HLB), and their mixtures demonstrated the highest extraction recovery and a wide range of metabolite coverage. A mixture of PS-DVB-WAX and HLB particles with 50:50 weight ratio (PS-DVB-WAX: HLB 50:50 [w/w]) was applied successfully for extraction of a wide range of metabolites, while the pentafluorophenyl Kinetex column coupled to an Orbitrap mass spectrometer method provided the widest metabolomics coverage for the investigated system. The method separated and detected over 200 cellular metabolites with widely varying hydrophobicities, ranging from -7 < log P < 17, including amino acids, peptides, nucleotides, carbohydrates, polycarboxylic acids, vitamins, phosphorylated compounds, and lipids such as hydrophobic phospholipids, as well as glycerolipids, and fatty acids at the stationary phase of the E.coli life cycle. Moreover, the 96-blade SPME system provided a high throughput platform, which surpassed sample throughput requirements for a typical metabolomics study whereby ~100 samples/day are processed. Chapters 4, 5, and 6 present the obtained results of applications of the optimized method towards evaluations of environmental stresses on biological systems. Essential oils, as natural plant products with a complex mixture of constituents, are comprised of multiple antimicrobial properties related to oxygenated terpenoids, particularly phenolic terpenes, phenylpropanoids, and alcohols. This thesis presents an investigation into the mechanisms of bactericidal action of cinnamaldehyde and clove oil against E.coli during bacterial growth, applying 96-blade SPME in direct immersion mode coupled to ultra performance liquid chromatography-mass spectrometry (UPLC-MS). Statistical analysis demonstrated alteration in the metabolic pathway during different time points of the E.coli growth curve, via the up-regulation of saturated fatty acids and amino acids, as well as the down-regulation of unsaturated fatty acids, glycolysis, and TCA cycle metabolites for E.coli treated by cinnamaldehyde, below and above the minimum inhibitory concentration. The presented 96-blade SPME-LC/MS method was developed using multivariate design, and applied to evaluate the synergistic effect of major components of clove oil as an antibacterial agent to E.coli. SPME provided clear separation between different sample treatments, and valuable information regarding the mechanisms of antibacterial action of the two naturally occurring compounds, suggesting different metabolic pathways for samples treated with the active agents. As opposed to the utilization of traditional univariate optimization methods, the current study employs the application of multivariate experimental designs for optimization of extraction-influencing parameters. Based on the obtained results, eugenol, as the major component of clove oil, produced the characteristic features of an antimicrobial agent. There is no synergistic effect between the components of clove bud oil in the actual weight percent of its constituents. Evaluation of discriminating metabolites in treated samples indicated eugenol as a lead compound for the development of an active agent through the control of glycolysis in anticancer cells, as this compound demonstrated glycolysis inhibition of E.coli as a model organism. The optimized SPME-LC-MS method was applied for high-throughput analysis of complex apple matrices without a sample pretreatment step. Untargeted metabolic profiling coupled with multivariate statistical analysis indicated metabolic alterations happening prior to scald development. The obtained results could be applied towards an improvement in the nutritional stability of foodstuffs as well as allow for shelf-life expansion, in addition to increasing their potential market value. The developed 96-blade SPME-LC-MS method is promising for global metabolomics applications, in particular in terms of extraction of unstable and short-lived metabolites in comparison to traditional techniques. SPME has also demonstrated high reproducibility and sample clean-up, which is a top requirement in metabolomics investigations.