Evolutionary, metabolic, and immunoinformatics analysis of surface proteins of importance in the pathogen-host relationship in organisms of the phylum Euglenozoa

• Grant number: 22/01262-8
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date: December 01, 2022
• End date: December 31, 2025
• Field of knowledge: Biological Sciences - Parasitology - Protozoology of Parasites
• Principal Investigator: João Marcelo Pereira Alves
• Grantee: Davi Salles Xavier
• Host Institution: Instituto de Ciências Biomédicas (ICB). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

Among eukaryotes, the cell surface protein composition is highly specialized to support different lifestyles, participating in immune evasion, cell invasion, migration and environmental interaction. This notorious mutability and variation can be explored through comparative analyzes in a monophyletic group that presents great diversity, correlating these proteins with different lifestyles. The phylum Euglenozoa has a range of different lifestyles and fits as a potential object of study for such evolutionary inferences, being composed of unicellular organisms from photosynthetic and heterotrophic clades and numerous examples of parasitism. Considering the importance of surface proteins and their interaction with the microenvironment, the project aims to identify, analyze and compare different surface proteins in Euglenozoa and their distribution in organisms with different lifestyles, allowing to make functional inferences and their correlation with different habitats and behaviors. To this end, genomes and transcriptomes representative of the phylum Euglenozoa were strategically selected to cover a wide diversity and will be assembled, predicted and annotated when necessary. The metabolic annotations will be performed by the ASGARD program, which will have its functionalities improved in this project and will be useful to select the metabolic pathways associated with the query proteins. Phylogenetic analyzes will be performed using maximum likelihood and Bayesian inferences for the protein sequences that were predicted and annotated as surface. Additionally, proteomes from organisms of human and veterinary medical interest in Euglenozoa will be carefully selected for the application of immunoinformatics strategies, using surface proteins for in silico prediction of potentially immunogenic sequences. (AU)