Exploring Leishmania-Host Interaction with Reactome, a Database of Biological Pathways and Processes

Abstract

AbstractLeishmaniasis is a parasitic disease with a wide range of clinical manifestations. Multiple aspects of the Leishmania-host interaction, such as genetic factors and modulation of microbicidal functions in host cells, influence pathogenesis, disease severity and treatment outcome. How do scientists contend with this complexity? Here, we work towards representing detailed, contextual knowledge on Leishmania-host interactions in the Reactome pathway database to facilitate the extraction of novel mechanistic insights from existing datasets. The Reactome database uses a hierarchy of abstractions that allows for the incorporation of detailed contextual knowledge on biological processes matched to differentially expressed genes. It also includes tools for enhanced over-representation analysis that exploits this extra information. We conducted a systematic curation of published studies documenting different aspects of the Leishmania-host interaction. The “Leishmania infection pathway” included four sub-pathways: phagocytosis, killing mechanisms, cell recruitment, and Leishmania parasite growth and survival. As proof-of-principle of the usefulness of the released pathway, we used it to analyze two previously released transcriptomic datasets of human and murine macrophages infected with Leishmania. Our results provide insights on the participation of ADORA2B signaling pathway in the modulation of IL10 and IL6 in infected macrophages. This work opens the way for other researchers to contribute to, and make use of, the Reactome database.ImportanceLeishmaniasis is a neglected disease infectious disease which affects more than 1.5 million people annually. Many researchers in the field apply -omic technologies to dissect the basis of clinical and therapeutic outcomes and access drug targetable features in the host-parasite interaction, among others. However, getting mechanistic insights from -omics data to such end is not an easy task. The most common approach is to use the -omics data to inquire pathways databases. The retrieved list of pathways often contains vague names that lack the biological context. In this study, we worked to create the Leishmania infection pathway in the Reactome database. With two practical examples from transcriptomics and microarray data, we demonstrated how this pathway facilitates the analysis of such data. In both datasets, we found a common mechanism of IL10 and IL6 production that the authors did not advert in their previous analysis, providing proof-of-principle of the tool’s enhanced potential for knowledge extraction. Leishmania infection pathway is in its first version, and must be expanded to cover the current knowledge base of the Leishmania-host interaction. We strongly encourage contributions from domain experts for the completion of Leishmania infection pathways.