(625w) Determining the Effect of Spacing In Protection of Staphylococcus Aureus by Pseudomonas Aeruginosa

Biofilm-causing bacteria such as Pseudomonas aeruginosa and Staphylococcus aureus are associated with adverse clinical outcomes due to several antibiotic resistance mechanisms inherent to biofilms. Both bacterial species are opportunistic pathogens that can be found individually or in co-culture with other organisms on catheters, skin, mucosa, or the respiratory tract. Recent studies have investigated the effect of the aminoglycoside antibiotic Tobramycin and its production of a new S. aureus phenotype, Small Colony Variants (SCV). An exoproduct, 4-hydroxy-2-heptylquinoline-N-oxide (HQNO), secreted from P. aeruginosa suppresses the electron transport inhibiting the growth of wild-type S. aureus and therefore protecting it from antibiotics. However, the effect of the distance between P. aeruginosa and S. aureus and specific fluxes of HQNO needed to produce SCVs are unknown. Studies have used Petri Dish culture methods to determine the concentrations needed, but this does not address the rate of delivery, or flux. Here we employ a microfluidic device designed to deliver spatially and temporally varying concentrations and fluxes to a central field. Using the device, concentration and fluxes of HQNO versus susceptibility to Tobramycin are determined as a function of position and time. We confirm that SCVs are derived from HQNO exposure by comparing the size of the colonies grown with the antistaphylococcal substance against the SCVs grown in co-culture with P. aeruginosa. When introducing .5 ug/ml HQNO and .55 ug/ml Tobramycin into the QUAD the lawn shows to have an increase in SVCs near the HQNO diffusing source and are more resistant than the wildtype S. aureus at above MIC levels.  Pathogenic co-cultures may have different antibiotic susceptibilities versus pure culture infections. Our results demonstrate the use of microfluidic devices and mass transport modeling for more quantitatively understanding the mechanism for antibiotic resistance. Future work may utilize a similar approach for mechanistic studies as well as screening combinatorial therapies.