Precise spatial structure impacts antimicrobial susceptibility of S. aureus in polymicrobial wound infections.

A hallmark of microbial ecology is that interactions between members of a community shape community function. This includes microbial communities in human infections, such as chronic wounds, where interactions can result in more severe diseases. Staphylococcus aureus is the most common organism isolated from human chronic wound infections and has been shown to have both cooperative and competitive interactions with Pseudomonas aeruginosa. Still, despite considerable study, most interactions between these microbes have been characterized using in vitro well-mixed systems, which do not recapitulate the infection environment. Here, we characterized interactions between S. aureus and P. aeruginosa in chronic murine wounds, focusing on the role that both macro- and micro-scale spatial structures play in disease. We discovered that S. aureus and P. aeruginosa coexist at high cell densities in murine wounds. High-resolution imaging revealed that these microbes establish a patchy distribution, only occupying 5 to 25% of the wound volume. Using a quantitative framework, we identified a precise spatial structure at both the macro (mm)- and micro (µm)-scales, which was largely mediated by P. aeruginosa production of the antimicrobial 2-heptyl-4-hydroxyquinoline N-oxide, while the antimicrobial pyocyanin had no impact. Finally, we discovered that this precise spatial structure enhances S. aureus tolerance to aminoglycoside antibiotics but not vancomycin. Our results provide mechanistic insights into the biogeography of S. aureus and P. aeruginosa coinfected wounds and implicate spatial structure as a key determinant of antimicrobial tolerance in wound infections.

Spatial mapping of polymicrobial communities reveals a precise biogeography associated with human dental caries.

Tooth decay (dental caries) is a widespread human disease caused by microbial biofilms. Streptococcus mutans, a biofilm-former, has been consistently associated with severe childhood caries; however, how this bacterium is spatially organized with other microorganisms in the oral cavity to promote disease remains unknown. Using intact biofilms formed on teeth of toddlers affected by caries, we discovered a unique 3D rotund-shaped architecture composed of multiple species precisely arranged in a corona-like structure with an inner core of S. mutans encompassed by outer layers of other bacteria. This architecture creates localized regions of acidic pH and acute enamel demineralization (caries) in a mixed-species biofilm model on human teeth, suggesting this highly ordered community as the causative agent. Notably, the construction of this architecture was found to be an active process initiated by production of an extracellular scaffold by S. mutans that assembles the corona cell arrangement, encapsulating the pathogen core. In addition, this spatial patterning creates a protective barrier against antimicrobials while increasing bacterial acid fitness associated with the disease-causing state. Our data reveal a precise biogeography in a polymicrobial community associated with human caries that can modulate the pathogen positioning and virulence potential in situ, indicating that micron-scale spatial structure of the microbiome may mediate the function and outcome of host-pathogen interactions.

Spatial determinants of quorum signaling in a Pseudomonas aeruginosa infection model.

Quorum sensing (QS) is a bacterial communication system that involves production and sensing of extracellular signals. In laboratory models, QS allows bacteria to monitor and respond to their own cell density and is critical for fitness. However, how QS proceeds in natural, spatially structured bacterial communities is not well understood, which significantly hampers our understanding of the emergent properties of natural communities. To address this gap, we assessed QS signaling in the opportunistic pathogen Pseudomonas aeruginosa in a cystic fibrosis (CF) lung infection model that recapitulates the biogeographical aspects of the natural human infection. In this model, P. aeruginosa grows as spatially organized, highly dense aggregates similar to those observed in the human CF lung. By combining this natural aggregate system with a micro-3D-printing platform that allows for confinement and precise spatial positioning of P. aeruginosa aggregates, we assessed the impact of aggregate size and spatial positioning on both intra- and interaggregate signaling. We discovered that aggregates containing ∼2,000 signal-producing P. aeruginosa were unable to signal neighboring aggregates, while those containing ≥5,000 cells signaled aggregates as far away as 176 µm. Not all aggregates within this "calling distance" responded, indicating that aggregates have differential sensitivities to signal. Overexpression of the signal receptor increased aggregate sensitivity to signal, suggesting that the ability of aggregates to respond is defined in part by receptor levels. These studies provide quantitative benchmark data for the impact of spatial arrangement and phenotypic heterogeneity on P. aeruginosa signaling in vivo.

A Pseudomonas aeruginosa Antimicrobial Affects the Biogeography but Not Fitness of Staphylococcus aureus during Coculture.

Pseudomonas aeruginosa and Staphylococcus aureus are two of the most common coinfecting bacteria in human infections, including the cystic fibrosis (CF) lung. There is emerging evidence that coinfection with these microbes enhances disease severity and antimicrobial tolerance through direct interactions. However, one of the challenges to studying microbial interactions relevant to human infection is the lack of experimental models with the versatility to investigate complex interaction dynamics while maintaining biological relevance. Here, we developed a model based on an in vitro medium that mimics human CF lung secretions (synthetic CF sputum medium [SCFM2]) and allows time-resolved assessment of fitness and community spatial structure at the micrometer scale. Our results reveal that P. aeruginosa and S. aureus coexist as spatially structured communities in SCFM2 under static growth conditions, with S. aureus enriched at a distance of 3.5 µm from P. aeruginosa Multispecies aggregates were rare, and aggregate (biofilm) sizes resembled those in human CF sputum. Elimination of P. aeruginosa's ability to produce the antistaphylococcal small molecule HQNO (2-heptyl-4-hydroxyquinoline N-oxide) had no effect on bacterial fitness but altered the spatial structure of the community by increasing the distance of S. aureus from P. aeruginosa to 7.6 µm. Lastly, we show that coculture with P. aeruginosa sensitizes S. aureus to killing by the antibiotic tobramycin compared to monoculture growth despite HQNO enhancing tolerance during coculture. Our findings reveal that SCFM2 is a powerful model for studying P. aeruginosa and S. aureus and that HQNO alters S. aureus biogeography and antibiotic susceptibility without affecting fitness.IMPORTANCE Many human infections result from the action of multispecies bacterial communities. Within these communities, bacteria have been proposed to directly interact via physical and chemical means, resulting in increased disease and antimicrobial tolerance. One of the challenges to studying multispecies infections is the lack of robust, infection-relevant model systems with the ability to study these interactions through time with micrometer-scale precision. Here, we developed a versatile in vitro model for studying the interactions between Pseudomonas aeruginosa and Staphylococcus aureus, two bacteria that commonly coexist in human infections. Using this model along with high-resolution, single-cell microscopy, we showed that P. aeruginosa and S. aureus form communities that are spatially structured at the micrometer scale, controlled in part by the production of an antimicrobial by P. aeruginosa In addition, we provide evidence that this antimicrobial enhances S. aureus tolerance to an aminoglycoside antibiotic only during coculture.