Carolina Axelsson1,2, Ann-Sofi Rehnstam-Holm1,2, Bo Nilson3,4. 1. Faculty of Natural Science, Kristianstad University, Kristianstad, Sweden. 2. Faculty of Medicine, Lund University, Lund, Sweden. 3. Department of Clinical Microbiology, Labmedicin, Lund, Sweden. 4. Department of Laboratory Medicine Lund, Faculty of Medicine, Division of Medical Microbiology, Lund University, Lund, Sweden.
Abstract
Introduction: For fast and effective antibiotic therapy of serious infections like sepsis, it is crucial with rapid information about antibiotic susceptibility, especially in a time when the number of infections caused by multi resistant bacteria has escalated in the world. Methods: Here, we have used a semi-quantitative MALDI-TOF-MS based method for antibiotic resistance detection, MBT-ASTRA™, which is based on the comparison of growth rate of the bacteria cultivated with and without antibiotics. We demonstrate a new protocol where several parameters have been optimized and automated leading to reduced hands-on time and improved capacity to simultaneously analyse multiple clinical samples and antibiotics. Results: Ninety minutes of incubation at 37 °C with agitation was sufficient to differentiate the susceptible and resistant strains of E. coli and K. pneumoniae, for the antibiotics cefotaxime, meropenem and ciprofloxacin. In total, 841 positive blood culture analyses of 14 reference strains were performed. The overall sensitivity was 99%, specificity 99% and the accuracy 97%. The assay gave no errors for cefotaxime (n = 263) or meropenem (n = 289) for sensitive and resistant strains, whilst ciprofloxacin (n = 289) gave six (0.7%) major errors (false resistance) and four (0.5%) very major errors (false susceptibility). The intermediate strains showed a larger variety compared to the E-test MIC values.Conclusions: The hands-on time and the analysis time to detect antibiotic resistance of clinical blood samples can be substantially reduced and the sample capacity can be increased by using automation and this improved protocol.
Introduction: For fast and effective antibiotic therapy of serious infections like sepsis, it is crucial with rapid information about antibiotic susceptibility, especially in a time when the number of infections caused by multi resistant bacteria has escalated in the world. Methods: Here, we have used a semi-quantitative MALDI-TOF-MS based method for antibiotic resistance detection, MBT-ASTRA™, which is based on the comparison of growth rate of the bacteria cultivated with and without antibiotics. We demonstrate a new protocol where several parameters have been optimized and automated leading to reduced hands-on time and improved capacity to simultaneously analyse multiple clinical samples and antibiotics. Results: Ninety minutes of incubation at 37 °C with agitation was sufficient to differentiate the susceptible and resistant strains of E. coli and K. pneumoniae, for the antibiotics cefotaxime, meropenem and ciprofloxacin. In total, 841 positive blood culture analyses of 14 reference strains were performed. The overall sensitivity was 99%, specificity 99% and the accuracy 97%. The assay gave no errors for cefotaxime (n = 263) or meropenem (n = 289) for sensitive and resistant strains, whilst ciprofloxacin (n = 289) gave six (0.7%) major errors (false resistance) and four (0.5%) very major errors (false susceptibility). The intermediate strains showed a larger variety compared to the E-test MIC values.Conclusions: The hands-on time and the analysis time to detect antibiotic resistance of clinical blood samples can be substantially reduced and the sample capacity can be increased by using automation and this improved protocol.
Authors: Rathina Kumar Shanmugakani; Balaji Srinivasan; Marshall J Glesby; Lars F Westblade; Washington B Cárdenas; Tony Raj; David Erickson; Saurabh Mehta Journal: Lab Chip Date: 2020-07-09 Impact factor: 6.799