| Grant number: | 20/08343-8 |
| Support Opportunities: | Regular Research Grants |
| Start date: | December 01, 2020 |
| End date: | November 30, 2023 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science - Computational Mathematics |
| Agreement: | Université de Lyon (UDL) |
| Principal Investigator: | André Fujita |
| Grantee: | André Fujita |
| Principal researcher abroad: | Marie-France Sagot |
| Institution abroad: | Institut National de Recherche en Informatique et en Automatique (INRIA Rhône-Alpes), France |
| Host Institution: | Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
| Associated researchers: | Ariel Mariano Silber ; Carlos Eduardo Ferreira ; Guilherme Oliveira Mota ; Marcel Kenji de Carli Silva ; Sinai Robins ; Yoshiharu Kohayakawa |
Abstract
Trypanosoma is a genus, which contains two pathogenic species to human beings: Trypanosoma brucei and Trypanosoma cruzi. These two species are relevant in terms of economy, welfare, and health. The metabolism of the different stages of both pathogenic trypanosomatids has been a matter of study not only because of their relevance for the economy and human health, but also because of their intrinsic biological interest. Several works reported how the central metabolic pathways work in these parasites. Also, based on omics analysis, a more general picture has been built in the last decade. However, attempts to approach the complexity of the metabolism of T. cruzi and T. brucei are still scarce. Thus, we propose combining graph theory-based algorithms and statistics to answer two relevant questions of parasitism. (i) Are metabolic networks more complex and interconnected in the insect stages than the mammalian stages? (ii) For each kind of host (insects or mammals), are the metabolic networks of these parasites significantly different in terms of complexity and connectivity among their subnetworks? The answers to these questions will bring invaluable biological information in terms of metabolic adaptations of these parasites to the environments they colonize in their hosts. Also, it will contribute to identifying frequent metabolic bottlenecks essential to propose new metabolic drugs targets for treating the infections they cause. (AU)
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