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GC-IMS 顶空分析可在标准血培养中尽早识别细菌生长并快速区分病原体。

GC-IMS headspace analyses allow early recognition of bacterial growth and rapid pathogen differentiation in standard blood cultures.

机构信息

Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Bunsen-Kirchhoff-Str. 11, 44139, Dortmund, Germany.

ION-GAS GmbH, Konrad-Adenauer-Allee 11, 44263, Dortmund, Germany.

出版信息

Appl Microbiol Biotechnol. 2019 Nov;103(21-22):9091-9101. doi: 10.1007/s00253-019-10181-x. Epub 2019 Oct 30.

DOI:10.1007/s00253-019-10181-x
PMID:31664484
Abstract

Outcome of patients with blood stream infections (BSI) depends on the rapid initiation of adequate antibiotic therapy, which relies on the fast and reliable identification of the underlying pathogen. Blood cultures (BC) using CO-sensitive colorimetric indicators and subsequent microbiological culturing are the diagnostic gold standard but turnaround times range between 24 and 48 h. The detection of volatile organic compounds of microbial origin (mVOC) has been described as a feasible method for identifying microbial growth and to differentiate between several microbial species. In this study, we aimed to investigate the ability of mVOC analyses using a gas chromatograph coupled to an ion mobility spectrometer (GC-IMS) for the recognition of bacterial growth and bacterial differentiation in BCs. Therefore, samples of whole blood and diluted bacterial suspension were injected into aerobic and anaerobic BC bottles and incubated for 8 h. Headspace samples from cultures of Escherichia coli (DSM 25944), Staphylococcus aureus (DSM 13661), and Pseudomonas aeruginosa (DSM 1117) were investigated hourly and we determined at which point of time a differentiation between the bacteria was possible. We found specific mVOC signals in the headspace over growing BCs of all three bacterial species. GC-IMS headspace analyses allowed faster recognition of bacterial growth than the colorimetric indicator of the BCs. A differentiation between the three investigated species was possible after 6 h of incubation with a high reliability in the principal component analysis. We concluded that GC-IMS headspace analyses could be a helpful method for the rapid detection and identification of bacteria in BSI.

摘要

血流感染(BSI)患者的预后取决于是否能迅速开始适当的抗生素治疗,而这又依赖于快速、可靠地确定潜在病原体。使用 CO 敏感比色指示剂的血培养(BC)和随后的微生物培养是诊断的金标准,但周转时间在 24 至 48 小时之间。已经有研究描述了微生物源挥发性有机化合物(mVOC)的检测作为一种可行的方法,可以识别微生物生长并区分几种微生物物种。在这项研究中,我们旨在调查使用气相色谱仪-离子迁移谱仪(GC-IMS)分析 mVOC 来识别 BC 中细菌生长和细菌分化的能力。因此,将全血和稀释细菌悬浮液样本注入需氧和厌氧 BC 瓶中并孵育 8 小时。每隔一小时对大肠杆菌(DSM 25944)、金黄色葡萄球菌(DSM 13661)和铜绿假单胞菌(DSM 1117)的培养物的顶空样本进行调查,并确定何时可以区分细菌。我们发现所有三种细菌的生长 BC 顶空中都有特定的 mVOC 信号。GC-IMS 顶空分析比 BC 的比色指示剂能更快地识别细菌生长。孵育 6 小时后,通过主成分分析可以可靠地区分三种被研究的细菌。我们得出结论,GC-IMS 顶空分析可能是一种有助于快速检测和鉴定 BSI 中细菌的方法。

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