Date on Master's Thesis/Doctoral Dissertation
Committee Co-Chair (if applicable)
Nantz, Michael H.
Baba, Shahid P.
GC-MS; GC × GC–MS; metabolomics; 2DLC-MS; LC-MS; bioinformatics; retention index calculation; second dimension retention index; surface fitting
Untargeted metabolomics aims to analyze as many metabolites as possible in a biological system. Due to the vast complexity of the metabolome, bioanalytical platforms have been developed for untargeted metabolomics. While comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) has been used in different scientific fields, its use in untargeted metabolomics is limited due to several challenges, such as complicated data analysis and limited accuracy of metabolite identification. Two-dimensional liquid chromatography mass spectrometry (2DLC-MS) has also been employed in untargeted metabolomics, but with limited metabolite coverage. This dissertation describes the efforts in developing new data analysis algorithms to improve the accuracy of metabolite identification in GC×GC-MS as well as integration of multiple analytical techniques for increased metabolite coverage and high confidence of metabolite quantification and pathway assignment. This dissertation is divided into six chapters. Chapter One provides the overview of the current methodologies for untargeted metabolomics. Chapters Two, Three and Four describe the methods developed for the calculation of the second dimension retention index ( ) in GC×GC-MS. Specifically, Chapter Two introduces a surface fitting approach to calculation using n-alkanes as reference compounds and considering the second dimension separation as in pseudo-isothermal mode. Chapter Three describes an improved method for calculation of by considering the second dimension separations in its actuality, i.e., temperature-programmed mode. Chapter Four introduces a universal reference system for calculation to improve retention map coverage that allows the use of any compounds as reference compounds while keeping retention scale in conventional n-alkane scale. Chapter Five introduces a method that integrates the GC×GC-MS and parallel 2DLC-MS platforms for untargeted metabolomics to achieve higher metabolite coverage and accurate metabolite quantification. Chapter Six summarizes the overall scientific contribution of this dissertation.
Prodhan, Md Aminul Islam, "GC×GC-MS and parallel 2DLC-MS based untargeted metabolomics." (2019). Electronic Theses and Dissertations. Paper 3307.