Abstract
The current culture-based approach for the diagnosis of bloodstreams infection is incommensurate with timely treatment and curbing the prevalence of multi-drug resistant organisms (MDROs) due to its long time-to-result. Bloodstream infections typically involve extremely low (e.g., <10 colony-forming unit (CFU)/mL) bacterial concentrations that require a labor-intensive process and as much as 72 hours to yield a diagnosis. Here, we demonstrate a culture-free approach to achieve rapid diagnosis of bloodstream infections. An immuno-detection platform with intrinsic signal current amplification was developed for the ultrasensitive, rapid detection, identification (ID) and antibiotic susceptibility testing (AST) of infections. With its capability of monitoring short-term (1–2 hours) bacterial growth in blood, the platform is able to provide 84-minute simultaneous detection and ID in blood samples below the 10 CFU/mL level and 204-minute AST. The susceptible-intermediate-resistant AST capacity was demonstrated.
Highlights
The current standard for diagnosis of bloodstream infections, including device associated infections, requires sequential bacterial detection, identification (ID), and antibiotic susceptibility testing (AST) via traditional blood cultures
When the bacterial concentration is less than 10 CFU/mL, without applying VG, the cyclic voltammogram (CV) is similar to that of negative controls (NC), which are blood samples without bacteria
The field effect enzymatic detection (FEED)-based immuno-assay platform is capable of detecting bacterial concentrations below 10 CFU/mL in whole unprocessed blood in 84 min and monitoring bacterial growth at this level with selectivity
Summary
The current standard for diagnosis of bloodstream infections, including device associated infections (e.g., central line-associated bloodstream infections, prosthetic valve endocarditis), requires sequential bacterial detection, identification (ID), and antibiotic susceptibility testing (AST) via traditional blood cultures. This culture-based three-step diagnostic approach is not optimal with profound clinical implications. The ultrasensitive detection capability of the platform facilitates the monitoring of bacterial growth in response to antibiotics over short time frames This capability was leveraged to demonstrate rapid (204 min sample-to-result) AST by exposing susceptible and resistant strains of E. coli to ampicillin. The AST results provide quantitative information on the response of bacteria to antibiotics, differentiating bacteriostatic from bactericidal responses
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