Abstract
US military service members experiencing combat-related wounds have higher risk of infection by multidrug-resistant bacteria. The gold standard culture-based antimicrobial susceptibility testing (AST) is not feasible in the battlefield environment. Thus, a rapid deployable system for bacteria identification and AST directly from wound sample is urgently needed. We report the potential of a Rapid, Label-free Pathogen Identification (RAPID) diagnostic system based on ATR-FTIR method to detect and distinguish multi-drug resistant strains for six different species in the ESKAPEE group. Our RAPID system combines sample processing on-broad to isolate and enrich bacteria cells from wound sample, ATR-FTIR measurement to detect antimicrobial-induced bacterial cell spectral changes, and machine learning model for automated, objective, and quantitative spectral analysis and unknown sample classification. Based on experimental results, our RAPID system is a promising technology for label-free, sensitive (104 cfu/mL from mixture), species-specific (> 95% accuracy), rapid (< 10 min for identification, ~ 4 hours for AST) bacteria detection directly from wound samples.