Metabolomic systems biology of trypanosomes

Metabolomics analysis, which aims at the systematic identification and quantification of all metabolites in biological systems, is emerging as a powerful new tool to identify biomarkers of disease, report on cellular responses to environmental perturbation, and to identify the targets of drugs. Here we discuss recent developments in metabolomic analysis, from the perspective of trypanosome research, highlighting remaining challenges and the most promising areas for future research

Use of reconstituted metabolic networks to assist in metabolomic data visualization and mining

Metabolomics experiments seldom achieve their aim of comprehensively covering the entire metabolome. However, important information can be gleaned even from sparse datasets, which can be facilitated by placing the results within the context of known metabolic networks. Here we present a method that allows the automatic assignment of identified metabolites to positions within known metabolic networks, and, furthermore, allows automated extraction of sub-networks of biological significance. This latter feature is possible by use of a gap-filling algorithm. The utility of the algorithm in reconstructing and mining of metabolomics data is shown on two independent datasets generated with LC–MS LTQ-Orbitrap mass spectrometry. Biologically relevant metabolic sub-networks were extracted from both datasets. Moreover, a number of metabolites, whose presence eluded automatic selection within mass spectra, could be identified retrospectively by virtue of their inferred presence through gap filling

Systems analysis of host-parasite interactions.

Parasitic diseases caused by protozoan pathogens lead to hundreds of thousands of deaths per year in addition to substantial suffering and socioeconomic decline for millions of people worldwide. The lack of effective vaccines coupled with the widespread emergence of drug-resistant parasites necessitates that the research community take an active role in understanding host-parasite infection biology in order to develop improved therapeutics. Recent advances in next-generation sequencing and the rapid development of publicly accessible genomic databases for many human pathogens have facilitated the application of systems biology to the study of host-parasite interactions. Over the past decade, these technologies have led to the discovery of many important biological processes governing parasitic disease. The integration and interpretation of high-throughput -omic data will undoubtedly generate extraordinary insight into host-parasite interaction networks essential to navigate the intricacies of these complex systems. As systems analysis continues to build the foundation for our understanding of host-parasite biology, this will provide the framework necessary to drive drug discovery research forward and accelerate the development of new antiparasitic therapies

The silicon trypanosome

African trypanosomes have emerged as promising unicellular model organisms for the next generation of systems biology. They offer unique advantages, due to their relative simplicity, the availability of all standard genomics techniques and a long history of quantitative research. Reproducible cultivation methods exist for morphologically and physiologically distinct life-cycle stages. The genome has been sequenced, and microarrays, RNA-interference and high-accuracy metabolomics are available. Furthermore, the availability of extensive kinetic data on all glycolytic enzymes has led to the early development of a complete, experiment-based dynamic model of an important biochemical pathway. Here we describe the achievements of trypanosome systems biology so far and outline the necessary steps towards the ambitious aim of creating a , a comprehensive, experiment-based, multi-scale mathematical model of trypanosome physiology. We expect that, in the long run, the quantitative modelling enabled by the Silicon Trypanosome will play a key role in selecting the most suitable targets for developing new anti-parasite drugs

Exploring the Role of AMPK in Nutrient Sensing and Signaling in the Human Parasite Trypanosoma brucei

African trypanosomes are protozoan parasites that cause the diseases African sleeping sickness and nagana, in humans and cattle respectively. These parasites have complex life cycles with infection of a mammalian host, ~5mM glucose, following transmission by an insect vector, essentially zero glucose. With these pathogens being exposed to rapidly changing glucose abundance in a host-dependent manner, the ability to sense and rapidly respond to changes in the availability of the hexose are critical. First, I provide a review of glucose metabolism in Trypanosoma brucei. Then, we explore the role of the catalytic α subunit of AMPK, a eukaryotic master regulator of energy, in procyclic form T. brucei. We found that the larger species of AMPKα1, coined AMPKα1+, was more abundant in the presence of glucose, and other metabolizable sugars. Subcellular location of AMPKα1 was similar regardless of glucose abundance. Phosphorylated AMPKα1 had an association with membranes, hypothesized to connect nutrient sensing and signaling pathways. Lastly, we describe how pleomorphic parasites respond to glucose depletion with a focus on parasite changes in energy metabolism and growth. Long slender bloodstream form parasites were rapidly killed as glucose concentrations fell, while short stumpy bloodstream form parasites persisted to differentiate into the insect stage procyclic form parasite. Both differentiation and growth of resulting procyclic form parasites were inhibited by glucose and non-metabolizable glucose analogs and these parasites were found to have upregulated amino acid metabolic pathway component gene expression. In summary, glucose transitions from the primary metabolite of the blood stage infection to a negative regulator of cell development and growth in the insect vector. These data suggest that glucose is not only a key metabolic agent but is also an important signaling molecule and may be signaling through TbAMPK