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Structure Elucidation and Identification of Known and Unknown Structure Elucidation and Identification of Known and Unknown Metabolites by Nuclear Magnetic Resonance Spectroscopy Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Cheng Wang Graduate Program in Chemistry The Ohio State University 2019 Dissertation Committee Rafael Brüschweiler, Advisor James Coe Marcos Sotomayor 1 Copyrighted by Cheng Wang 2019 2 Abstract Identification of metabolites is one of the main challenges in metabolomics. Since metabolite identities and their concentrations are often directly linked to the phenotype, such information can be used to map biochemical pathways and understand their role in health and disease. A very large number of metabolites are still unknown, i.e. their spectroscopic signatures do not match those in existing databases, suggesting unknown molecule identification is both imperative and challenging. This dissertation describes new methods that combine nuclear magnetic resonance (NMR), mass spectrometry (MS) and combinatorial chemoinformatics tools to identify the structures of known and unknown metabolites and development of 2D NMR hydrophobic metabolite database to identify lipids in lipidomics mixtures. Chapter 1 presents a general introduction to metabolomics in systems biology and an overview of current NMR and MS-based metabolite identification. Chapter 2 focuses on the development of the SUMMIT MS/NMR approach for the identification of metabolites in a model mixture and E. coli cell extract. It combines 2D and 3D NMR experiments with Fourier transform ion cyclotron resonance MS and MS/MS data to yield the complete structures or fragments that match those in the complex mixture, independent of any spectroscopic database information. SUMMIT MS/NMR greatly assists the targeted or untargeted analysis of unknown compounds in complex mixtures. Chapter 3 describes an efficient motif-based identification method to identify molecular motif from NMR spectra followed by identification of the complete structure of unknown metabolites. Two databases are assembled, namely COLMAR MSMMDB and pNMR MSMMDB. The motif- ii based identification method was applied to the hydrophilic extract of mouse bile fluid and two unknown metabolites were successfully identified. The final chapter illustrates the development of 2D NMR database of hydrophobic compounds and application of high- resolution non-uniform sampling 2D real-time pure shift HSQC spectra to metabolomics mixtures for accurate lipid identification. The methods and databases introduced here permit applications to a wide range of metabolomics mixtures for accurate identification of both known and unknown metabolites. iii Dedication To my parents. iv Acknowledgments I would like to express my great gratitude to my advisor, Prof. Rafael Brüschweiler, for his invaluable supervision and guidance along my PhD journey. His dedication to science with superior wisdom deeply motivated and helped me overcome numerous problems in research. Particularly, his intelligent ideas and advice inspired me to discover new directions in multiple research projects. I would like to thank my dissertation committee members, Profs. James Coe and Marcos Sotomayor for their continuous support and guidance. They gave me valuable advice for my candidacy proposal, research progress and dissertation. I also thank Profs. Mark Foster, Philip Grandinetti for their help at various stages during my PhD. I greatly appreciate the Campus Chemical Instrument Center, not only the state- of-the-art high-field NMR and mass spectrometers, but more importantly the excellent expertise and helpfulness of its staff scientists. Drs. Alexandar Hansen and Chunhua Yuan mentored me to be familiar with setting up NMR experiments. Dr. Lei Bruschweiler-Li expertly guided me the preparation of high-quality NMR samples. Dr. Da-Wei Li helped me boosting the analysis of multiple research projects with intelligent computational methods. Dr. Árpád Somogyi helped me collecting high-quality ultra-high resolution MS data. I also express sincere thanks to the Brüschweiler Lab members. Particularly, I am grateful to Drs. Bo Zhang and István Timári for their help and discussions in the motif- based unknown metabolite identification, Drs. Mouzh Xie and Jiaqi Yuan for their tutorial and discussion in fundamental NMR tools and experiments, Drs. Yina Gu, Helena v Zacharias, and Gilson C. Santos Jr. for their useful advice how to enhances the daily PhD research efficiency. vi Vita 1991 Born in Heze, Shandong, China, P.R. 2013 B.S. in Applied Chemistry, China University of Petroleum 2014 - Graduate Teaching and Research Associate, The Ohio State University Publications First authored: 1. Wang, C., Zhang, B., Timári, I., Somogyi, A., Li, D. W., Adcox, H. E., Gunn, J. S., Bruschweiler-Li, L., & Brüschweiler, R. (2019). Accurate and Efficient Determination of Unknown Metabolites in Metabolomics by NMR-Based Molecular Motif Identification. Analytical chemistry. (Accepted) 2. Leggett, A.,* Wang, C.,* Li, D. W., Somogyi, A., Bruschweiler-Li, L., & Brüschweiler, R. (2019). Identification of Unknown Metabolomics Mixture Compounds by Combining NMR, MS, and Cheminformatics. Methods in enzymology, 615, 407-422. 3. Wang, C.,* He, L.,* Li, D. W.,* Bruschweiler-Li, L., Marshall, A. G., & Brüschweiler, R. (2017). Accurate identification of unknown and known metabolic mixture components by combining 3D NMR with fourier transform ion cyclotron resonance tandem mass spectrometry. Journal of proteome research, 16(10), 3774-3786. (*co-first author) Co-authored: vii 4. Knobloch, T. J., Ryan, N. M., Bruschweiler-Li, L., Wang. C., Bernier, M. C., Somogyi, A., Yan, P. S., Cooperstone, J. L., Mo, X., Brüschweiler, R., Weghorst, C. M., & Oghumu, S. (2019). Metabolic Regulation of Glycolysis and AMP Activated Protein Kinase Pathways during Black Raspberry-Mediated Oral Cancer Chemoprevention. Metabolites, 9(7), 140. 5. Timári, I., Wang, C., Hansen, A. L., Costa dos Santos, G., Yoon, S. O., Bruschweiler-Li, L., & Brüschweiler, R. (2019). Real-Time Pure Shift HSQC NMR for Untargeted Metabolomics. Analytical chemistry, 91(3), 2304-2311 6. Yuan, J., Zhang, B., Wang, C., & Brüschweiler, R. (2018). Carbohydrate background removal in metabolomics samples. Analytical chemistry, 90(24), 14100-14104. 7. Hansen, A. L., Li, D.W., Wang, C., & Brüschweiler, R. (2017). Absolute Minimal Sampling of Homonuclear 2D NMR TOCSY Spectra for High-Throughput Applications of Complex Mixtures. Angewandte Chemie (International ed. in English), 129(28), 8261-8264. 8. Li, D. W., Wang, C., & Brüschweiler, R. (2017). Maximal clique method for the automated analysis of NMR TOCSY spectra of complex mixtures. Journal of biomolecular NMR, 68(3), 195-202. Fields of Study Major Field: Chemistry viii Table of Contents Abstract .......................................................................................................................................... ii Dedication .................................................................................................................................... iv Acknowledgments ........................................................................................................................v Vita ............................................................................................................................................... vii Table of Contents ........................................................................................................................ ix List of Tables ............................................................................................................................. xiii List of Figures ..............................................................................................................................xv Introduction................................................................................................................ 1 1.1 Metabolomics in Systems Biology .................................................................................... 2 1.2 NMR-Based Metabolomics ................................................................................................ 3 1.2.1 Basics of NMR ............................................................................................................................. 3 1.2.2 One-dimensional and Multidimensional NMR ..................................................................... 5 1.2.3 NMR Metabolomics Database .................................................................................................. 7 1.3 Overview of Identification of Metabolites ....................................................................... 8 1.3.1 Identification of Metabolites by Mass Spectrometry ............................................................ 9 1.3.2 Identification of Metabolites by NMR ................................................................................... 10 1.3.3 MS and NMR Hybrid Approaches for Identification of Metabolites ............................... 12 ix Accurate Identification of Unknown and Known Metabolic Mixture Components by Combining 3D NMR with Fourier Transform Ion Cyclotron Resonance Tandem Mass Spectrometry ..................................................................................................... 19 2.1 Introduction........................................................................................................................ 20 2.2 Materials and
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