Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections

Abstract

A number of human infections are characterized by the presence of more than one bacterial species and are defined as polymicrobial diseases. Methods for the analysis of the complex biological interactions in mixed infections with a large number of microorganisms are limited and do not effectively determine the contribution of each bacterial species to the pathogenesis of the polymicrobial community. We have developed a novel Drosophila melanogaster infection model to study microbe–microbe interactions and polymicrobe–host interactions. Using this infection model, we examined the interaction of 40 oropharyngeal isolates with Pseudomonas aeruginosa. We observe three classes of microorganisms, one of which acts synergistically with the principal pathogen, while being avirulent or even beneficial on its own. This synergy involves microbe–microbe interactions that result in the modulation of P. aeruginosa virulence factor gene expression within infected Drosophila. The host innate immune response to these natural-route polymicrobial infections is complex and characterized by additive, suppressive, and synergistic transcriptional activation of antimicrobial peptide genes. The polymicrobial infection model was used to differentiate the bacterial flora in cystic fibrosis (CF) sputum, revealing that a large proportion of the organisms in CF airways has the ability to influence the outcome of an infection when in combination with the principal CF pathogen P. aeruginosa. Bacterial infections often involve more than one species. The lung disease of cystic fibrosis (CF) patients provides examples of polymicrobial infections whereby diverse and dynamic microbial communities are a characteristic of CF airways. The significance of microbe–microbe interactions and the interplay of the communities with the host have not been thoroughly investigated. We describe a novel Drosophila model to discern the biological interactions between microbes within microbial communities, as well as the interactions between the communities and the innate immune system. Using fly survival as a readout of relevant interactions, we show that mixed infections may additively or synergistically enhance the pathogenicity of a microbial community. The polymicrobial infection model was used to differentiate the bacterial flora in CF sputum, revealing that a large proportion of the organisms in CF airways has the ability to influence the outcome of an infection when in combination with the principal CF pathogen Pseudomonas aeruginosa. We show that during the synergistic-type mixed infections, P. aeruginosa virulence gene expression is altered within live Drosophila compared to mono-species infections. The immune response to microbial communities takes many forms and can include synergistic activation of antimicrobial peptide gene expression. We postulate that the biological interactions exposed using this model may contribute to the transition from chronic stable infections to acute pulmonary exacerbation infections in CF.