Europe PMC

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Abstract 


Pseudomonas aeruginosa is the most important opportunistic pathogen leading to serious and life-threatening infections, especially in immunocompromised patients. Because of its remarkable capacity to resist antibiotics, the selection of the right antibiotics with the exact dose for the appropriate duration is critical to effectively treat the infections and prevent antibiotic resistance. Although conventional genotypic and phenotypic antibiotic susceptibility testing (AST) methods have been dramatically advanced, they have suffered from many technical and operational issues as a generalized antibiotic stewardship program. Furthermore, given that most microbial infections are caused by their biofilms, the existing AST methods do not provide evidence-based antibiotic prescribing guidance for biofilm-based infections because the results are based on individual bacteria traditionally grown in their planktonic form. In this work, we create an innovative susceptibility testing technique for P. aeruginosa that offers clinically relevant guidelines and widely adaptable stewardship to effectively treat the infections and minimize antibiotic resistance. Our approach evaluates the antibiotic efficacy by continuously monitoring the accumulated electrical outputs from the bacterial extracellular electron transfer (EET) process in the presence of antibiotics. Our innovative paper-based culturing 3-D scaffold promotes surface-associated growth of bacterial colonies and biofilms. The platform replicates a natural habitat for P. aeruginosa where it can grow similarly to sites it infects. Our technique enables an all-electrical, real-time, easy-to-use, portable AST that can be easily translatable to clinical settings. The entire procedure takes 96 min to provide evidence-based antimicrobial prescribing guidance for biofilm-based infections.

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Funding 


Funders who supported this work.

Division of Chemical, Bioengineering, Environmental, and Transport Systems (1)

Division of Electrical, Communications and Cyber Systems (2)

NSF

    National Science Foundation