13C-based metabolic flux modelling in Leishmania parasites
AffiliationDepartment of Biochemistry and Molecular Biology, Faculty of Medicine, Dentistry & Health Sciences
MetadataShow full item record
Document TypePhD thesis
CitationNg, M. (2012). 13C-based metabolic flux modelling in Leishmania parasites. PhD thesis, Department of Biochemistry and Molecular Biology, Faculty of Medicine, Dentistry & Health Sciences, The University of Melbourne.
Access StatusNo attached file available
© 2012 Dr. Milica Ng
Until recently, 13C-based flux analyses have almost exclusively relied on analysis of labelled amino acids in proteins. This approach is not directly applicable to Leishmania, as these parasites scavenge most of their amino acids from the media. Leishmania are also unusual in that they i) share little genomic similarity with other organisms ii) constitutively express their metabolic genes and iii) display minimal changes in the enzyme levels throughout their life cycle stages. The three factors have contributed to an early development of comprehensive and reproducible 13C-based metabolomics approaches in these parasites. The work presented here contributes to i) the rapid processing of data files generated by the novel 13C-based metabolomics approaches and ii) the creation of new 13C-based metabolic flux approaches based on the isotopologue analysis of free metabolite pools in Leishmania. In particular a new algorithm was developed to semi-automatically quantify metabolite isotopic distribution from metabolically labelled gas chromatographymass spectrometry (GC-MS) data files. Up to now this has often been performed manually, which is both time consuming and prone to error. In addition, although the problem of correcting the measurements for naturally occurring isotopes has been solved for some time, there is a general lack of open source tools available to researchers. The newly developed algorithm automatically quantifies the isotopic distribution of metabolite fragments from the raw GC-MS data files (exported in standard netCDF format) and corrects them for natural isotopic abundance. This work lays the foundation for 13C-metabolic flux analysis (13C-MFA) in Leishmania. In particular, it is demonstrated that the quality of current GC-MS 13C-metabolomics measurements of free metabolic intermediates is sufficient for 13CMFA. However, the lack of knowledge about network topology and/or metabolite compartmentation prevents the method’s full application. The calculation of flux ratios (or relative fluxes) of converging metabolic pathways, is in many ways complementary to 13C-MFA. 13C-metabolic flux ratio analysis (13C-MFRA) has the advantage of being a ‘divide and conquer’ strategy with respect to the network topology, as it is centered around individual metabolite pools. Specifically, 13C-MFRA has the potential to reveal which enzymes are active, which are inactive, and if there are any unknown reactions taking place. A new approach is presented for simultaneous calculation of in vivo fractional fluxes (or flux ratios) into two or more nodes with carbon dioxide condensation, based on isotopologue analysis of free metabolite pools. This method is used to perform the first quantitative in vivo fractional flux calculation of central carbon metabolism in any human parasite. The method is directly applicable to different Leishmania life cycle stages, mutants, nutritional environments, and to studying the effects of drugs.
Keywordsmetabolic flux analysis; metabolic flux ratios; metabolism; Leishmania; 13C-based metabolomics; high-throughput GC-MS; mass isotopic distribution; metabolic systems biology
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