Rapid antimicrobial susceptibility testing of clinical isolates by digital time-lapse microscopy

Rapid antimicrobial susceptibility testing (AST) is essential for early and appropriate therapy. Methods with short detection time enabling same-day treatment optimisation are highly favourable. In this study, we evaluated the potential of a digital time-lapse microscope system, the oCelloScope system, to perform rapid AST. The oCelloScope system demonstrated a very high accuracy (96 % overall agreement) when determining the resistance profiles of four reference strains, nine clinical isolates, including multi-drug-resistant isolates, and three positive blood cultures. AST of clinical isolates (168 antimicrobial agent–organism combinations) demonstrated 3.6 % minor, no major and 1.2 % very major errors of the oCelloScope system compared to conventional susceptibility testing, as well as a rapid and correct phenotypic detection of strains with methicillin-resistant Staphylococcus aureus (MRSA) and extended-spectrum β-lactamase (ESBL) profiles. The net average time-to-result was 108 min, with 95 % of the results being available within 180 min. In conclusion, this study strongly indicates that the oCelloScope system holds considerable potential as an accurate and sensitive AST method with short time-to-result, enabling same-day targeted antimicrobial therapy, facilitating antibiotic stewardship and better patient management. A full-scale validation of the oCelloScope system including more isolates is necessary to assess the impact of using it for AST

Additional file 1: of Automated image analysis for quantification of filamentous bacteria

Piperacillin-induced filamentation in E. coli . The time-lapse movies show E. coli treated with piperacillin (PIP, 64 mg/L) and without (Positive control), respectively; as well as graphs showing growth and average length of the bacteria. (MOV 4671 kb

Automated image analysis for quantification of filamentous bacteria

Abstract Background Antibiotics of the β-lactam group are able to alter the shape of the bacterial cell wall, e.g. filamentation or a spheroplast formation. Early determination of antimicrobial susceptibility may be complicated by filamentation of bacteria as this can be falsely interpreted as growth in systems relying on colorimetry or turbidometry (such as Vitek-2, Phoenix, MicroScan WalkAway). The objective was to examine an automated image analysis algorithm for quantification of filamentous bacteria using the 3D digital microscopy imaging system, oCelloScope. Results Three E. coli strains displaying different resistant profiles and differences in filamentation kinetics were used to study a novel image analysis algorithm to quantify length of bacteria and bacterial filamentation. A total of 12 β-lactam antibiotics or β-lactam–β-lactamase inhibitor combinations were analyzed for their ability to induce filamentation. Filamentation peaked at approximately 120 min with an average cell length of 30 μm. Conclusion The automated image analysis algorithm showed a clear ability to rapidly detect and quantify β-lactam-induced filamentation in E. coli. This rapid determination of β-lactam-mediated morphological alterations may facilitate future development of fast and accurate AST systems, which in turn will enable early targeted antimicrobial therapy. Therefore, rapid detection of β-lactam-mediated morphological changes may have important clinical implications

Automated image analysis for quantification of filamentous bacteria

Abstract Background Antibiotics of the β-lactam group are able to alter the shape of the bacterial cell wall, e.g. filamentation or a spheroplast formation. Early determination of antimicrobial susceptibility may be complicated by filamentation of bacteria as this can be falsely interpreted as growth in systems relying on colorimetry or turbidometry (such as Vitek-2, Phoenix, MicroScan WalkAway). The objective was to examine an automated image analysis algorithm for quantification of filamentous bacteria using the 3D digital microscopy imaging system, oCelloScope. Results Three E. coli strains displaying different resistant profiles and differences in filamentation kinetics were used to study a novel image analysis algorithm to quantify length of bacteria and bacterial filamentation. A total of 12 β-lactam antibiotics or β-lactam–β-lactamase inhibitor combinations were analyzed for their ability to induce filamentation. Filamentation peaked at approximately 120 min with an average cell length of 30 μm. Conclusion The automated image analysis algorithm showed a clear ability to rapidly detect and quantify β-lactam-induced filamentation in E. coli. This rapid determination of β-lactam-mediated morphological alterations may facilitate future development of fast and accurate AST systems, which in turn will enable early targeted antimicrobial therapy. Therefore, rapid detection of β-lactam-mediated morphological changes may have important clinical implications