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Parsing and analysis of mass spectrometry data of complex biological and environmental mixtures

University of British Columbia

The chemical characterization of biological and environmental samples are areas of research which involve the analysis of highly complex chemical mixtures. While the samples from these two fields differ greatly in composition, they present similar challenges. Complex mixtures provide a challenge to the analytical chemist as compounds in the mixture can have matrix effects which interfere with the analysis. Indeed, these interfering compounds may even be analytes themselves. High resolution mass spectrometry, which separates and detects ions based on their mass-to-charge ratio, is a powerful tool in the analysis of such mixtures. The amount of data resulting from such analyses, however, can be intractable to manual analysis, necessitating the use of computational tools. Furthermore, for the data to be reliable it is important that the performance of the mass spectrometer is optimal and consistent, but the complexity of the data again makes manual interpretation of the quality difficult. Thus, there is a need for computational assistance in analysis as well as method optimization and quality control. In Chapter 2:, we present a review of considerations toward the design of a standard mass spectrometry-based method for the quantification of naphthenic acids. The study provides recommendations for how these considerations can be addressed. In Chapter 3:, we describe a computational method of resolving dicarboxylic acids in high resolution mass spectrometry data of mixtures of derivatized naphthenic acid fraction compounds. The study is a proof-of-concept and demonstrates that derivatization-based methods of analyzing these diacid components is feasible but requires further investigation. In Chapter 4: and Chapter 5:, we present two computational tools which assist in method optimization and quality control of Thermo Orbitrap mass spectrometer systems. Chapter 4: presents RawQuant, a software tool which extracts scan quantification and meta data from data-dependent analysis data files from Orbitrap mass spectrometer systems. The tool is designed to inform the user toward method optimization. Chapter 5: presents RawTools, which builds upon RawQuant by adding the ability to track important measures of mass spectrometer performance longitudinally across a multi-run experiment. The tool is demonstrated using a 140-file dataset and provides easy visual monitoring of instrument performance.

Text

2019-08-15

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/71302

Chemistry

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/