Metabolic Network Analysis of Apicomplexan Parasites to Identify Novel Drug Targets

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Metabolic Network Analysis of Apicomplexan Parasites to Identify Novel Drug Targets Metabolic Network Analysis of Apicomplexan Parasites to Identify Novel Drug Targets by Stacy Susan Hung A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Molecular Genetics University of Toronto © Copyright by Stacy Susan Hung 2014 ii Metabolic Network Analysis of Apicomplexan Parasites to Identify Novel Drug Targets Stacy Susan Hung Doctor of Philosophy Molecular Genetics University of Toronto 2014 Abstract Parasites of the phylum Apicomplexa include many important human and veterinary pathogens such as Plasmodium (malaria), Toxoplasma (a leading opportunistic infection associated with AIDS and congenital neurological birth defects) and Eimeria (an economically significant disease of poultry and cattle). The lack of effective vaccines or treatments and increasing prevalence of drug-resistant strains stresses the urgency to develop novel drug therapies. Research presented within this thesis has provided numerous insights into the metabolic capabilities of apicomplexans and importantly, identifies potential enzyme drug targets offering a plethora of opportunities for further investigation and experimental validation. I first focused on generating a pipeline for accurately reconstructing metabolic networks by integrating enzyme annotations from complementary curated datasets and automated tools. Key to this integration is the Density Estimation Tool for Enzyme ClassificaTion (DETECT), a probabilistic method I developed for improved enzyme prediction accounting for sequence diversity across enzyme families. My comparative analyses across the resulting networks revealed that apicomplexans iii adopt differing strategies for performing similar core metabolic activities. Pantothenate biosynthesis was highlighted as a druggable pathway based on its conserved enzyme complement across the phylum and absence from the host. Using P. falciparum as a model for metabolism, I incorporated gene expression, thermodynamics and evolutionary data to gain insight into the operation of metabolic pathways in the parasite. Finally, the application of my metabolic reconstruction pipeline to other parasites illustrates its utility for establishing a meaningful characterization of metabolism for a newly sequenced organism, and when combined with additional experimental datasets provide a wealth of insights in the biology of these organisms. iv Acknowledgements I express my sincerest gratitude to my supervisor Dr. John Parkinson for giving me the opportunity to pursue my doctoral thesis in his lab. I am truly grateful for his insightful feedback and unwavering support throughout my Ph. D. degree. I would also like to thank all current and previous members of the Parkinson Lab, especially postdoc fellow Dr. James Wasmuth, who was an inspirational project mate and helped me feel grounded in my project. A special thanks to Alexandra Gast, Viviana Pszenny, and other members of Dr. Michael Grigg’s Lab at the NIH who have been instrumental in fast-forwarding my wet-lab expertise and knowledge of working with Toxoplasma parasites in the lab. Finally, I’d like to thank all my friends and family for their love, support, and encouragement. v Table of Contents Acknowledgements ........................................................................................................................ iv Table of Contents ............................................................................................................................ v List of Tables ................................................................................................................................. ix List of Figures ................................................................................................................................. x Chapter 1 Introduction .................................................................................................................... 1 1 Introduction ......................................................................................................................... 1 1.1 The Apicomplexa .......................................................................................................... 1 1.1.1 Taxonomy .............................................................................................................. 1 1.1.1.1 Genomes ............................................................................................................ 3 1.1.2 Epidemiology and Pathology ................................................................................ 5 1.1.2.1 Plasmodium ...................................................................................................... 5 1.1.2.2 Toxoplasma gondii ........................................................................................... 6 1.1.2.3 Cryptosporidium .............................................................................................. 7 1.1.2.4 Other Apicomplexa .......................................................................................... 8 1.1.3 General morphological features ............................................................................ 8 1.1.4 Life Cycle ............................................................................................................ 10 1.1.4.1 General life cycle of apicomplexans .............................................................. 10 1.1.4.2 Plasmodium falciparum life cycle .................................................................. 10 1.1.4.3 Toxoplasma gondii life cycle ......................................................................... 12 1.1.5 Population Genetics and Virulence ..................................................................... 13 1.1.5.1 Plasmodium .................................................................................................... 13 1.1.5.2 Toxoplasma gondii ......................................................................................... 13 1.1.6 Available drugs for the Apicomplexa ................................................................. 14 1.1.7 Metabolism as a source of drug targets ................................................................... 16 1.1.7.1 Enzymes are essential for life .......................................................................... 17 1.1.7.2 Mechanistic basis of enzymes for highly directed drug design ....................... 17 1.2 Experimental manipulations in the Apicomplexa ...................................................... 18 1.2.1 Methods for genetic manipulation ....................................................................... 18 1.2.1.1 Transfection and transformation .................................................................... 18 1.2.1.2 Gene knockouts .............................................................................................. 19 1.3 Metabolic reconstruction and analysis as a route to drug discovery .......................... 20 1.3.1 Metabolic reconstruction for the Apicomplexa ................................................... 21 1.3.2 Importance of enzyme annotation for metabolic reconstruction ......................... 23 vi 1.3.2.1 Enzyme annotation ......................................................................................... 23 1.3.2.2 Automated methods for enzyme prediction ................................................... 25 1.3.2.3 Curated resources for metabolic reconstruction ............................................. 26 1.3.3 Modelling, Network-based methods and FBA: Applications to drug discovery 28 1.4 Project goals ............................................................................................................... 31 Chapter 2 Improving enzyme annotation for accurate metabolic reconstruction ......................... 32 2 Improving enzyme annotation for accurate metabolic reconstruction .............................. 32 2.1 Introduction ................................................................................................................ 32 2.2 Materials and Methods ............................................................................................... 33 2.2.1 Protein sequence and enzyme data ...................................................................... 33 2.2.2 Generation of probability profiles ....................................................................... 34 2.2.3 Probability score calculation ............................................................................... 34 2.2.4 Five-fold cross-validation and ROC analysis ...................................................... 36 2.2.5 Prediction of malarial enzymes ........................................................................... 36 2.3 Results and Discussion ............................................................................................... 37 2.3.1 Assessing enzyme diversity ................................................................................ 37 2.3.2 Density estimation tool for enzyme classification (DETECT) ........................... 41 2.3.3 Comparison to current prediction methods ......................................................... 46 2.3.4 Expanding the metabolome of P. falciparum ...................................................... 52 2.4 Concluding Remarks .................................................................................................. 57 Chapter 3 Reconstructing parasite metabolism: Biological insights ............................................ 58 3 Reconstructing parasite
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