FB2026_02 , released June 18, 2026
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Citation
Robert, A., Talagrand-Reboul, E., Figueras, M.J., Ruimy, R., Boyer, L., Lamy, B. (2023). Drosophila melanogaster Systemic Infection Model to Study Altered Virulence during Polymicrobial Infection by Aeromonas.  Pathogens 12(3): 405.
FlyBase ID
FBrf0256065
Publication Type
Research paper
Abstract
Polymicrobial infections are complex infections associated with worse outcomes compared to monomicrobial infections. We need simple, fast, and cost-effective animal models to assess their still poorly known pathogenesis. We developed a Drosophila melanogaster polymicrobial infection model for opportunistic pathogens and assessed its capacity to discriminate the effects of bacterial mixtures taken from cases of human polymicrobial infections by Aeromonas strains. A systemic infection was obtained by needle pricking the dorsal thorax of the flies, and the fly survival was monitored over time. Different lineages of the flies were infected by a single strain or paired strains (strain ratio 1:1). Individual strains killed more than 80% of the flies in 20 h. The course of infection could be altered with a microbial mix. The model could distinguish between the diverse effects (synergistic, antagonistic, and no difference) that resulted in a milder, more severe, or similar infection, depending on the paired strain considered. We then investigated the determinants of the effects. The effects were maintained in deficient fly lineages for the main signaling pathways (Toll deficient and IMD deficient), which suggests an active microbe/microbe/host interaction. These results indicate that the D. melanogaster systemic infection model is consistent with the study of polymicrobial infection.
PubMed ID
PubMed Central ID
PMC10055632 (PMC) (EuropePMC)
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Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Pathogens
    Title
    Pathogens
    ISBN/ISSN
    2076-0817
    Data From Reference
    Genes (2)
    Human Disease Models (1)