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Metabolic Systems Biology of the Malaria Parasite Metabolic Systems Biology of the Malaria Parasite Reconstruction, visualisation and analysis of an experimentally parameterised metabolic model of the human acute malaria parasite Plasmodium falciparum. Thomas Forth Submitted in accordance with the requirements for the degree of Integrated PhD with Masters The University of Leeds The White Rose Doctoral Training Centre within the School of Physics and Astronomy September, 2012 i The candidate confirms that the work submitted is his own, except where work which has formed part of jointly-authored publications has been included. The contribution of the candidate and the other authors to this work has been explicitly indicated below. The candidate confirms that appropriate credit has been given within the thesis where reference has been made to the work of others. Chapter 1 : Introduction. This chapter shares much of its content with the Wikipedia page written by the candidate on flux-balance analysis. The candidate remains the principal author of the page but recognises that the contributions of others — which are fully described in the "history" section of the Wikipedia page — are significant. Chapter 2: MetNetMaker. The software described in this chapter was published as Forth T, McConkey GA, Westhead DR. MetNetMaker: a free and open-source tool for the creation of novel metabolic networks in SBML format. Bioinformatics (Oxford, England). 2010;26(18):2352–3. This paper was written by the candidate with guidance and correction provided principally by D. R Westhead. This copy has been supplied on the understanding that it is copyright material and that no quotation from the thesis may be published without proper acknowledgement. © 2012 The University of Leeds and Thomas Forth. ii Acknowledgements I am extremely grateful to my supervisors Prof. David Westhead and Dr. Glenn McConkey for suggesting this line of study and for giving me the freedom to explore so widely and so independently the rapidly changing field of systems biology. They have always been available to me and provided critical guidance, suggestions, and contacts at key moments. Fewer and fewer doctoral students in the UK can expect to continue to academic careers and the balance of priorities in doctoral study has thus shifted away from purely academic achievement towards the broader acquisition skills, connections and experience for a rapidly changing and globally competitive future. I am well aware that this could present a conflict between the interests of a doctoral supervisor and the long-term interests of a doctoral student and I hugely appreciate that both of my supervisors and the White Rose doctoral training centre have always acted in my best interest. Some of the most significant findings in this thesis come from a collaboration I developed with Prof. Julie Fisher’s NMR metabolomics lab at the University of Leeds and I am greatly indebted to Prof. Fisher, Dr. Hayley Fenton-Saville and especially Dr. Cassey McRae for the time they spent sharing their experience and helping me develop the techniques described in this thesis. Emese O'Donnell (Prandovszky) and Paul Bedingfield have been extremely generous with their time and expertise in the wet-lab and I could not have completed that section of this thesis without their continual support. I am similarly grateful for the hard-work of masters students I have worked with, particularly Jennifer Lake who worked exceptionally hard in the culture room and scoured early NMR spectra for the tiny peaks that led to a more serious metabolomics study of the malaria parasite. Lastly I am grateful to the family, friends and colleagues who have provided inspiration, support and encouragement to continue with my work, especially at extremely difficult times in my first and in my most recent year at Leeds. That some of the greatest sources of my inspiration are no longer alive has not diminished the determination to succeed that they have passed on to me. This research has been carried out by a team which has included Masters Students Cheng Ma, Jennifer Lake and Sara Zakutansky. My own contributions form the majority of the research and work performed in collaboration with others is explicitly and fully indicated in the thesis. iii Abstract Quantitative one-dimensional proton NMR metabolomics is performed on growth medium samples gathered at up to ten time-points during the in vitro culture of P. falciparum in human red blood cells. From this study, exchange fluxes between the parasite-host complex and the growth medium are calculated for glucose, lactate, glycerol, glutamine, hypoxanthine, valine, leucine, isoleucine, alanine, tyrosine and phenylanaine. Carbon-source exchange fluxes are added as constraints to a new model of malaria metabolism — built using my published MetNetMaker software — consisting of 249 reactions, 143 genes and a novel experimentally derived biomass function. Analysis of this network including by flux-balance analysis and flux-variability analysis are projected onto a live map of the network providing the most accessible view of malaria metabolism to date. This model reproduces key phenotypes of the malaria parasite such as the unusual branched TCA cycle, and accurately predicts internal fluxes through the pentose-phosphate cycle and the low oxygen-dependence of the parasite’s metabolism during its erythrocytic life stages. The model is carbon balanced and accurately predicts the parasite’s growth-rate at measured glucose uptake rates. Furthermore, it accurately reproduces measured amino acid and purine-source exchange fluxes at the optimal solution and implies that the parasite digests 30% of its red blood cell host’s haemoglobin but incorporates just 40% of the resulting freed amino acids into its proteome. Lethal single and double gene deletions are predicted and suggest potential drug and vaccine targets. The metabolic model is available in MetNetMaker format for easy editing, SBML format including constraints for metabolic modelling and the independent reproduction of the reported results, and cytoscape format with metadata for visualisation of both the network and the results of simulations performed on it. iv Contents List of acronyms ................................................................................................ xviii Introduction ............................................................................................................ 1 Metabolic networks ......................................................................................................................... 1 The malaria parasite ....................................................................................................................... 23 Network analysis ............................................................................................................................ 31 MetNetMaker .......................................................................................................46 Building MetNetMaker .................................................................................................................. 50 Application structure ................................................................................................................................... 51 User interface................................................................................................................................................ 61 Application outputs for further analysis .................................................................................... 68 Visualisation and Network Reconstruction ......................................................71 KEGG projector and Cytoscape: one problem, two approaches ...................................... 73 Four elements of my P. falciparum reconstruction ................................................................. 76 Example reconstruction: nucleotide metabolism .................................................................... 82 The size of the task ........................................................................................................................ 87 The final model ............................................................................................................................... 89 Encouraging model re-use ............................................................................................................ 95 Experimental Methods ........................................................................................99 Malaria culture ................................................................................................................................. 99 Observing cultures...................................................................................................................................... 102 Synchronisation of cultures ...................................................................................................................... 106 Saponin lysis and parasite biomass isolation ...................................................................................... 111 Problems working with large culture volumes..................................................................................... 112 Measurements techniques .......................................................................................................... 113 Used growth medium assays .................................................................................................................. 113 Biomass analysis ........................................................................................................................................
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