Co-occurring microflora and mucin drive Pseudomonas aeruginosa diversification and pathoadaptation.

While several environmental factors contribute to the evolutionary diversification of the pathogenic bacterium Pseudomonas aeruginosa during cystic fibrosis lung infections, relatively little is known about the impact of the surrounding microbiota. By using in vitro experimental evolution, we show that the presence of Stenotrophomonas maltophilia, Staphylococcus aureus, or them both, prevent the evolution of loss of virulence, which repeatedly occurs in the absence of these species due to mutations in regulators of the Pseudomonas Quinolone Signal quorum sensing system, vqsM and pqsR. Moreover, the strength of the effect of co-occurring species is attenuated through changes in the physical environment by the addition of mucin, resulting in selection for phenotypes resembling those evolved in the absence of the co-occurring species. Together, our findings show that variation in mucosal environment and the surrounding polymicrobial environment can determine the evolutionary trajectory of P. aeruginosa, partly explaining its diversification and pathoadaptation from acute to chronic phenotype during cystic fibrosis lung infections.

Inter-species interactions alter antibiotic efficacy in bacterial communities.

The efficacy of antibiotic treatments targeting polymicrobial communities is not well predicted by conventional in vitro susceptibility testing based on determining minimum inhibitory concentration (MIC) in monocultures. One reason for this is that inter-species interactions can alter the community members' susceptibility to antibiotics. Here we quantify, and identify mechanisms for, community-modulated changes of efficacy for clinically relevant antibiotics against the pathogen Pseudomonas aeruginosa in model cystic fibrosis (CF) lung communities derived from clinical samples. We demonstrate that multi-drug resistant Stenotrophomonas maltophilia can provide high levels of antibiotic protection to otherwise sensitive P. aeruginosa. Exposure protection to imipenem was provided by chromosomally encoded metallo-ß-lactamase that detoxified the environment; protection was dependent upon S. maltophilia cell density and was provided by S. maltophilia strains isolated from CF sputum, increasing the MIC of P. aeruginosa by up to 16-fold. In contrast, the presence of S. maltophilia provided no protection against meropenem, another routinely used carbapenem. Mathematical ordinary differential equation modelling shows that the level of exposure protection provided against different carbapenems can be explained by differences in antibiotic efficacy and inactivation rate. Together, these findings reveal that exploitation of pre-occurring antimicrobial resistance, and inter-specific competition, can have large impacts on pathogen antibiotic susceptibility, highlighting the importance of microbial ecology for designing successful antibiotic treatments for multispecies communities.

Spatial Point Pattern Analysis Identifies Mechanisms Shaping the Skin Parasite Landscape in Leishmania donovani Infection.

Increasing evidence suggests that in hosts infected with parasites of the Leishmania donovani complex, transmission of infection to the sand fly vector is linked to parasite repositories in the host skin. However, a detailed understanding of the dispersal (the mechanism of spread) and dispersion (the observed state of spread) of these obligatory-intracellular parasites and their host phagocytes in the skin is lacking. Using endogenously fluorescent parasites as a proxy, we apply image analysis combined with spatial point pattern models borrowed from ecology to characterize dispersion of parasitized myeloid cells (including ManR+ and CD11c+ cells) and predict dispersal mechanisms in a previously described immunodeficient model of L. donovani infection. Our results suggest that after initial seeding of infection in the skin, heavily parasite-infected myeloid cells are found in patches that resemble innate granulomas. Spread of parasites from these initial patches subsequently occurs through infection of recruited myeloid cells, ultimately leading to self-propagating networks of patch clusters. This combination of imaging and ecological pattern analysis to identify mechanisms driving the skin parasite landscape offers new perspectives on myeloid cell behavior following parasitism by L. donovani and may also be applicable to elucidating the behavior of other intracellular tissue-resident pathogens and their host cells.