Antibiotic resistance is compromising our ability to treat bacterial infections. Clinical microbiology laboratories guide appropriate treatment through antimicrobial susceptibility testing (AST) of patient bacterial isolates. However, increasingly, pathogens are developing resistance to a broad range of antimicrobials, requiring AST of less commonly used or recently introduced agents for which no commercially available or FDA-cleared testing methods exist. Agar and broth dilution are gold standard methods for AST that can be used to test any antimicrobial; however, labor and technical complexity precludes their use in hospital-based clinical laboratories. Therefore, bacterial isolates often must be sent to a reference laboratory with a 4-6 day delay in results. Furthermore, even standard methods require overnight incubation prior to readout. Therefore, there exists a significant AST testing gap in which current methodologies cannot adequately address the need for rapid results in the face of unpredictable susceptibility profiles. Our laboratory has recently verified inkjet printer-based digital dispensing technology as a novel platform to facilely perform reference AST for any antimicrobial at will. In this proposal, we aim to combine this methodology with advanced microscopy to leapfrog traditional AST capabilities through: (1) development of a method for microscopic imaging of bacterial replication on a solid-phase, 384-well microplate AST format, thereby allowing determination of susceptibility for any drug at will in 4 hours and (2) development and application of advanced image analysis for automated susceptibility calls. This new platform is designated MAST for microscopy-based antimicrobial susceptibility testing. The clinical diagnostic performance of the platform will be optimized against an AST reference method for accuracy and precision using a large panel of well-characterized clinical isolates. We anticipate establishing a prototype platform that will address the AST testing gap and thereby help our health system more effectively address the antimicrobial resistance threat.
With the emergence of multi-drug resistant bacteria, it is no longer possible to accurately predict which antimicrobials will be effective against life-threatening bacterial illness. Testing bacteria directly for response available therapies may take several days. Therefore, a new technology platform called MAST is proposed to allow us to determine which antibiotics can treat a bacteria infection in a matter of hours and thereby address our current, clinically unacceptable antimicrobial testing gap.
