The standard laboratory procedure for determining the antibiotic susceptibility of a pathogen (an antimicrobial susceptibility test, AST) measures the inhibition of growth, and requires several days. This can delay effective therapy and lead to antibiotic overuse and misuse. Recent work (Wei Hou et al, Lab on a Chip 2015) has shown that resistant and susceptible pathogens will have very different gene expression profiles shortly following antibiotic exposure, and that these expression biomarkers may be used to accurately identify the pathogen species, strain and antibiotic susceptibility without growth. We therefore developed an ultrasensitive ‘digital microarray’ for performing rapid & quantitative gene expression analysis as part of a rapid AST. The digital microarray uses plasmonic gold nanorods (GNRs) functionalized with DNA to specifically label each target RNA that binds to the microarray. Each GNR on the array is then individually detected based on its light scattering, with an interferometric microscopy technique called SP- IRIS. Our optimized high-throughput version of SP-IRIS is able to scan a typical array of 500 spots in less than 10 minutes. Due to its single molecule readout, the assay has a limit of detection of less than 1 femtomolar following just 2 hours of incubation. Altogether, digital microarrays are about 10,000-fold more sensitive than fluorescence microarrays, yet maintain all of the strengths of the platform including low cost and high multiplexing. The reproducibility and robustness of the multiplexed assay will next be evaluated with clinically relevant pathogenic strains of E. coli as part of a functional rapid AST.
Derin D. Sevenler, Emma A. Briars, George Daaboul, Fulya Ekiz Kanik, Joseph Greene, Ahmad Khalil, and M. Selim Ünlü, "A digital microarray for transcriptional biomarkers of antibiotic resistance utilizing plasmonic nanorods and interferometric imaging (Conference Presentation)," Proc. SPIE 10479, Light-Based Diagnosis and Treatment of Infectious Diseases, 1047908 (Presented at SPIE BiOS: January 29, 2018; Published: 14 March 2018); https://doi.org/10.1117/12.2290068.5751479181001.
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