Rapid detection of antibiotic resistance in positive blood cultures by MALDI-TOF MS and an automated and optimized MBT-ASTRA protocol for Escherichia coli and Klebsiella pneumoniae
Rapid detection of antibiotic resistance in positive blood cultures by MALDI-TOF MS and an automated and optimized MBT-ASTRA protocol for Escherichia coli and Klebsiella pneumoniae
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DOI：
10.1080/23744235.2019.1682658
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发表时间：
2019-10-26
影响因子：
5.8
通讯作者：
Nilson, Bo
中科院分区：
文献类型：
--
作者：
Axelsson, Carolina;Rehnstam-Holm, Ann-Sofi;Nilson, Bo
简介：对于败血症等严重感染的快速有效的抗生素治疗，快速获得抗生素敏感性信息至关重要，特别是在世界上由多重耐药细菌引起的感染数量不断增加的情况下。研究方法：在这里，我们使用了基于半定量MALDI-TOF-MS的方法进行抗生素耐药性检测，MBT-ASTRA（TM），该方法基于比较在有和没有抗生素的情况下培养的细菌的生长速率。我们展示了一种新的方案，其中几个参数已经优化和自动化，从而减少了动手时间，提高了同时分析多个临床样品和抗生素的能力。结果：在37 ℃下搅拌孵育90分钟足以区分敏感和耐药的E。埃希菌和肺炎，用于抗生素头孢噻肟，美罗培南和环丙沙星。总共对14种参考菌株进行了841次阳性血培养分析。总的敏感性为99%，特异性为99%，准确性为97%。对于敏感和耐药菌株，该检测方法对头孢噻肟（n = 263）或美罗培南（n = 289）没有给出任何错误，而环丙沙星（n = 289）给出了6个（0.7%）重大错误（假耐药）和4个（0.5%）非常重大错误（假敏感性）。与E-试验MIC值相比，中间菌株显示出更大的多样性。结论：通过使用自动化和这种改进的方案，可以大大减少检测临床血液样品的抗生素耐药性的操作时间和分析时间，并且可以增加样品容量。
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 (TM), 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 degrees 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.