Giordano Cesira, Barnini Simona
SD Ospedaliera di Microbiologia, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy.
SD Ospedaliera di Microbiologia, Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy.
J Microbiol Methods. 2018 Dec;155:27-33. doi: 10.1016/j.mimet.2018.11.008. Epub 2018 Nov 12.
Carbapenemase-producing Klebsiella pneumoniae has become a worldwide recognized cause of nosocomial infections and requires urgent public health attention. The main reason of this concern is the increasing resistance to all the last-resort antibiotics, including colistin. The ideal methodology for colistin susceptibility testing still remains undefined. However, the emergence of colistin as one of the last-option treatments requires a reliable method to determine the susceptibility profile of resistant isolates. The aim of the present study was to evaluate the impact of detecting colistin resistance in Klebsiella pneumoniae isolates using MALDI-TOF MS in clinical routine practice. For this reason, 139 isolates of K. pneumoniae were collected during 2015-2017 from patients hospitalized at Pisa University Hospital. Colonies suspected to be colistin resistant were identified using MALDI-TOF MS (Bruker Daltonik GmbH, Bremen, Germany) following a protein extraction protocol. Strains were previously wholly genome sequenced. To create a customized database entry and to generate classifying algorithm models, 1.112 mass spectra were collected. In relation to their mass signals and intensities, a two dimensional peak distribution was created. The recognition capability of the algorithm based on two manually selected mass peaks was 91,8%, while cross validation was 87,6%. The proportion of correctly classified colistin-resistant K. pneumoniae was 91% and colistin-susceptible was 73%. The emergence of colistin-resistant Gram-negative organisms has a dramatic impact on patient outcomes. Our study, based on MALDI-TOF MS technology, offers rapid preliminary results on colistin resistance profile coupled with bacteria identification.
产碳青霉烯酶肺炎克雷伯菌已成为全球公认的医院感染病因，亟需引起公共卫生关注。这种担忧的主要原因是对包括黏菌素在内的所有最后手段抗生素的耐药性不断增加。黏菌素药敏试验的理想方法仍未明确。然而，黏菌素作为最后选择的治疗方法之一的出现，需要一种可靠的方法来确定耐药菌株的药敏谱。本研究的目的是评估在临床常规实践中使用基质辅助激光解吸电离飞行时间质谱（MALDI-TOF MS）检测肺炎克雷伯菌分离株中黏菌素耐药性的影响。因此，2015年至2017年期间，从比萨大学医院住院患者中收集了139株肺炎克雷伯菌分离株。按照蛋白质提取方案，使用MALDI-TOF MS（德国不来梅的布鲁克道尔顿公司）鉴定疑似对黏菌素耐药的菌落。这些菌株之前已进行全基因组测序。为创建定制的数据库条目并生成分类算法模型，收集了1112个质谱图。根据它们的质量信号和强度，创建了二维峰分布。基于两个手动选择的质量峰的算法识别能力为91.8%，交叉验证为87.6%。正确分类的耐黏菌素肺炎克雷伯菌比例为91%，对黏菌素敏感的比例为73%。耐黏菌素革兰氏阴性菌的出现对患者预后有巨大影响。我们基于MALDI-TOF MS技术的研究提供了关于黏菌素耐药谱以及细菌鉴定的快速初步结果。
