Newton001: Research and Training in Leishmaniasis, a Neglected Tropical Disease of Public Health Importance in Brazil

Leishmaniasis is a neglected tropical disease with strong and complex links with poverty. The burden of leishmaniasis falls disproportionately on the poorest segments of the global population, including within Brazil, where there are 30,000 cases/year. Leishmaniasis diagnosis and treatment are expensive and many of the drugs used are not fit for purpose; drug resistance is an increasing problem. Public investment in treatment and control would decrease the leishmaniasis disease burden and help to alleviate poverty, yet more research is required to facilitate implementation. This project aims to increase capacity in Brazil for early phase drug discovery by enhancing research links between the UK and Brazil in the molecular, cell and immunobiology of Leishmania parasites.

This proposal aims at combining efforts of the research groups to investigate virulence factors and pathways contributing to pathology and resistance to drug treatment in visceral leishmaniasis using meta-approaches. We will undertake two main approaches to study experimental infections in the mouse model using strains derived from clinical isolates of L. chagasi (Brazil) and L. donovani (Sudan, studied in UK): (i) use in vivo imaging techniques to collect data on parasite dissemination and burden, attraction of immune cells and development of pathology, (ii) collect data using meta-analyses, such as RNA-seq, and apply computational modelling built to simulate drug and immune-mediated interventions in the settings of visceral leishmaniasis. We will also adopt those approaches to investigate the contribution of defined virulence factors to disease pathology. The specific approaches are described below:

1. L. donovani and L. chagasi transgenic lines will be created and evaluated using IVIS whole animal imaging in experimental murine models of infection to track visceralisation, immune response and pathology.

2. Generation of "omics" data. We will evaluate the pattern of gene expression via transcriptome analyses at different stages of infection to generate a database for the search for relevant pathways and drug targets with potential for therapeutic intervention. Profiling of parasite genes expressed at different time-points of infection and intracellular growth in animal models, and of the immune response infections will be evaluated. The genome/transcriptome data will be correlated with data generated by in vivo imaging analyses, regarding cellular recruitment, parasite load at different sites and pathology.

3. Multiscale computation models: We will use novel approaches for the development and implementation of computer models in the context of host pathogen interactions at the level of the individual infected host.

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