Pathogen Host Shift: Meta-analytical and experimental approaches using bacteria and insects interactions

• Grant number: 22/09752-4
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date: April 01, 2023
• End date: December 02, 2026
• Field of knowledge: Biological Sciences - Genetics - Animal Genetics
• Principal Investigator: Rodrigo Cogni
• Grantee: Eduardo Gomes Ragnoni
• Host Institution: Instituto de Biociências (IB). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 21/06874-9 - Ecological genomics of insects' phase 2: climate adaptations and evolution of ecological interactions, AP.JP2
• Associated scholarship(s): 24/13788-0 - Can natural variation in Diptericin explain phylogenetic effects in resistance to bacteria infection?, BE.EP.DD

Abstract

Emerging Infectious Diseases (EIDs) cause enormous negative effects in humanity and are becoming more frequent. One of the main sources of EIDs are host shift events (when the jump of a pathogen to a new host specie increases the genetic differentiation of the parasite, leading to specialization on the new host). The host phylogeny is relevant to the host shift success, because it can influence the virulence and pathogenic load in a new host. However, it is not known if the phylogeny effect occurs only for a specific pathogen or the response to different pathogens is correlated. In this project we will study the phylogenetic effects on host shifts using two approaches, a meta-analysis and an experiment . (1) We will conduct a meta-analysis studying the host shift of bacterias in insect fitness in the literature. (2) We will also conduct a cross infection experiment using the Drosophilidae family and the bacteria Providencia rettgeri and Enterococcus faecalis. Our goal is to find out how host phylogeny influences bacteria and host fitness. We will investigate the virulence and bacterial load variation in 39 species of the Drosophilidae family. The bacterial load will indicate host resistance and virulence will be measured by fly mortality rate after the bacterial infection. We will also measure the expression of immune system genes searching if differential gene expression can explain the possible observed pattern. We will also compare our results with bacteria with previously published data of viral infections.