Unravelling metabolism of Leishmania by metabolomics

The leishmaniases are neglected tropical diseases with an urgent need for effective drugs. Better understanding of the metabolism of the causative parasites will hopefully lead to development of new compounds targeted at critical points of the parasite’s biochemical pathways. In my work I focused on the pentose phosphate pathway of Leishmania, specifically on transketolase, sugar utilisation, and comparison between insect and mammalian infective stages of the parasites. The pentose phosphate pathway (PPP) is the major cellular source of NADPH, an agent critical for oxidative stress defence. The PPP uses glucose, reduces the NADP+ cofactor and produces various sugar phosphates by mutual interconversions. One of the enzymes involved in this latter part is transketolase (TKT). A Leishmania mexicana cell line deleted in transketolase (Δtkt) was assessed regarding viability, sensitivity to a range of drugs, changes in metabolism, and infectivity. The Δtkt cell line had no obvious growth defect in the promastigote stage, but it was more sensitive to an oxidative stress inducing agent and most of the drugs tested. Most importantly, the Δtkt cells were not infective to mice, establishing TKT as a new potential drug target. Metabolomic analyses revealed multiple changes as a consequence of TKT deletion. Levels of the PPP intermediates upstream of TKT increased substantially, and were diverted into additional reactions. The perturbation triggered further changes in metabolism, resembling the ‘stringent metabolic response’ of amastigotes. The Δtkt cells consumed less glucose and glycolytic intermediates were decreased indicating a decrease in flux, and metabolic end products were diminished in production. The decrease in glycolysis was possibly caused by inhibition of fructose-1,6-bisphosphate aldolase by accumulation of the PPP intermediates 6-phosphogluconate and ribose 5-phosphate. The TCA cycle was fuelled by alternative carbon sources, most likely amino acids, instead of glucose. It remains unclear why deletion of TKT is lethal for amastigotes, increased sensitivity to oxidative stress or drop in mannogen levels may contribute, but no definite conclusions can be made. TKT localisation indicated interesting trends too. The WT enzyme is present in the cytosol and glycosomes, whereas a mutant version, truncated by ten amino acids, but retaining a C-terminal targeting sequence, localised solely to glycosomes. Surprisingly, cells expressing purely cytosolic or glycosomal TKT did not have different phenotypes regarding growth, oxidative stress sensitivity or any detected changes in metabolism. Hence, control of the subcellular localisation remains unclear as well as its function. However, these data are in agreement with the presumed semipermeable nature of the glycosome. Further, L. mexicana promastigote cultures were grown in media with different combinations of labelled glucose and ribose and their incorporation into metabolism was followed. Glucose was the preferred carbon source, but when not available, it could be fully replaced with ribose. I also compared metabolic profiles from splenic amastigotes, axenic amastigotes and promastigotes of L. donovani. Metabolomic analysis revealed a substantial drop in amino acids and other indications coherent with a stringent metabolic response in amastigotes. Despite some notable differences, axenic and splenic amastigotes demonstrated fairly similar results both regarding the total metabolic profile and specific metabolites of interest.

Optimal static and sequential design : a critical review

The aim of this thesis is to review and augment the theory and methods of optimal experimental design. In Chapter I the scene is set by considering the possible aims of an experimenter prior to an experiment, the statistical methods one might use to achieve those aims and how experimental design might aid this procedure. It is indicated that, given a criterion for design, a priori optimal design will only be possible in certain instances and, otherwise, some form of sequential procedure would seem to be indicated. In Chapter 2 an exact experimental design problem is formulated mathematically and is compared with its continuous analogue. Motivation is provided for the solution of this continuous problem, and the remainder of the chapter concerns this problem. A necessary and sufficient condition for optimality of a design measure is given. Problems which might arise in testing this condition are discussed, in particular with respect to possible non-differentiability of the criterion function at the design being tested. Several examples are given of optimal designs which may be found analytically and which illustrate the points discussed earlier in the chapter. In Chapter 3 numerical methods of solution of the continuous optimal design problem are reviewed. A new algorithm is presented with illustrations of how it should be used in practice. It is shown that, for reasonably large sample size, continuously optimal designs may be approximated to well by an exact design. In situations where this is not satisfactory algorithms for improvement of this design are reviewed. Chapter 4 consists of a discussion of sequentially designed experiments, with regard to both the philosophies underlying, and the application of the methods of, statistical inference. In Chapter 5 we criticise constructively previous suggestions for fully sequential design procedures. Alternative suggestions are made along with conjectures as to how these might improve performance. Chapter 6 presents a simulation study, the aim of which is to investigate the conjectures of Chapter 5. The results of this study provide empirical support for these conjectures. In Chapter 7 examples are analysed. These suggest aids to sequential experimentation by means of reduction of the dimension of the design space and the possibility of experimenting semi-sequentially. Further examples are considered which stress the importance of the use of prior information in situations of this type. Finally we consider the design of experiments when semi-sequential experimentation is mandatory because of the necessity of taking batches of observations at the same time. In Chapter 8 we look at some of the assumptions which have been made and indicate what may go wrong where these assumptions no longer hold.