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Mass spectrometry (MS) is a powerful tool for analyzing complex mixtures, offering valuable information regarding identification and quantification for laboratory research, both fundamental and applied. Manipulating ions using electrostatic and electrodynamic fields in a vacuum environment, MS is inherently fast and capable of generating diverse structural information. However, the potential speed of MS analysis is often hindered due to the necessity of separating complex mixtures prior to injection into the mass spectrometer. In this dissertation, we demonstrate methods to improve the speed of mass spectrometric mixture analysis at every stage, from ionization to ion trapping, and eventually to data analysis.One solution to the challenge of increasing speed is ambient ionization using nESI coupled with microdroplet-based reaction acceleration. During the travel of the microdroplet from the ionization source to the inlet of the mass spectrometer, a derivatization reaction was shown to increases the signal of compounds with a targeted functional group from the mixture within milliseconds. This eliminated the need for time-consuming chromatographical separation, allowing for class-based mixture analysis (e.g. phenolic compounds, chapter 2). This accelerated chemical reaction mechanism was studied using the Katritzky reaction and a large surface-to-volume ratio (chapter 3). It is suggested that acceleration is associated with an electric double layer, which creates a strong electric field near the air-liquid interface.The second part of the discussion on speeding up mixture component identification uses a modified ion trap and a new scan type: two-dimensional tandem mass spectrometry (2D MS/MS). In this experiment, MS/MS data of all precursors is recorded without isolation, thereby allowing characterization of each molecule in the mixture using a single ion injection. The generated data is stored in an image format where one dimension represents the precursor domain while the other dimension represents the product m/z values. This allows for the structural interpretation of all mixture components from a single spectrum. Applications of this technology include developing point-of-care assays to analyze patient blood HIV drug levels in less than five minutes (chapter 5 and 6) and the in-situ analysis of sulfonamides in milk in less than one minute (chapter 7) using portable mass spectrometers.The third improvement is focused on novel data analysis techniques. In one case, the effects of an accelerated reaction on a complex mixture were visualized using subtracted 2D MS/MS spectra, which provided an additional layer of information, speeding up the processing and interpretation of an unknown mixture (chapter 8). In another case, raw 2D MS/MS spectra were formatted and processed for machine learning analysis, which was used to classify and identify eight different bacteria based on lipid region profiles within seconds. |
