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由……产生的挥发性代谢物的气相色谱-质谱联用分析

GC-MS profiling of volatile metabolites produced by .

作者信息

Filipiak Wojciech, Żuchowska Karolina, Marszałek Marta, Depka Dagmara, Bogiel Tomasz, Warmuzińska Natalia, Bojko Barbara

机构信息

Department of Pharmacodynamics and Molecular Pharmacology, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, Bydgoszcz, Poland.

Department of Microbiology, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, Bydgoszcz, Poland.

出版信息

Front Mol Biosci. 2022 Oct 18;9:1019290. doi: 10.3389/fmolb.2022.1019290. eCollection 2022.

Abstract

Currently used methods for diagnosing ventilator-associated pneumonia (VAP) are complex, time-consuming and require invasive procedures while empirical antibacterial therapy applies broad spectrum antibiotics that may promote antimicrobial resistance. Hence, novel and fast methods based on alternative markers are needed for VAP detection and differentiation of causative pathogens. Pathogenic bacteria produce a broad range of volatile organic compounds (VOCs), some of which may potentially serve as biomarkers for microorganism identification. Additionally, monitoring of dynamically changing VOCs concentration profiles may indicate emerging pneumonia and allow timely implementation of appropriate antimicrobial treatment. This study substantially extends the knowledge on bacterial metabolites providing the unambiguous identification of volatile metabolites produced by carbapenem-resistant and susceptible strains of (confirmed with pure standards in addition to mass spectra match) but also revealing their temporary concentration profiles (along the course of pathogen proliferation) and dependence on the addition of antibiotic (imipenem) to bacteria. Furthermore, the clinical strains of isolated from bronchoalveolar lavage specimens collected from mechanically ventilated patients were investigated to reveal, whether bacterial metabolites observed in model experiments with reference strains could be relevant for wild pathogens as well. In all experiments, the headspace samples from bacteria cultures were collected on multibed sorption tubes and analyzed by GC-MS. Sampling was done under strictly controlled conditions at seven time points (up to 24 h after bacteria inoculation) to follow the dynamic changes in VOC concentrations, revealing three profiles: release proportional to bacteria load, temporary maximum and uptake. Altogether 32 VOCs were released by susceptible and 25 VOCs by resistant strain, amongst which 2-pentanone, 2-heptanone, and 2-nonanone were significantly higher for carbapenem-resistant KPN. Considerably more metabolites ( = 64) were produced by clinical isolates and in higher diversity compared to reference KPN strains.

摘要

目前用于诊断呼吸机相关性肺炎(VAP)的方法复杂、耗时且需要侵入性操作,而经验性抗菌治疗使用的广谱抗生素可能会促进抗菌药物耐药性。因此,需要基于替代标志物的新型快速方法来检测VAP并鉴别致病病原体。病原菌会产生多种挥发性有机化合物(VOCs),其中一些可能潜在地用作微生物鉴定的生物标志物。此外,监测动态变化的VOCs浓度曲线可能预示肺炎的发生,并有助于及时实施适当的抗菌治疗。本研究极大地扩展了关于细菌代谢产物的知识,不仅明确鉴定了耐碳青霉烯类和敏感菌株产生的挥发性代谢产物(除质谱匹配外还通过纯标准品进行了确认),还揭示了它们的临时浓度曲线(沿病原体增殖过程)以及对向细菌中添加抗生素(亚胺培南)的依赖性。此外,还对从机械通气患者采集的支气管肺泡灌洗标本中分离出的临床菌株进行了研究,以确定在参考菌株的模型实验中观察到的细菌代谢产物是否也与野生病原体相关。在所有实验中,细菌培养物的顶空样品收集在多床吸附管上,并通过气相色谱 - 质谱联用仪(GC-MS)进行分析。在严格控制的条件下,于七个时间点(细菌接种后长达24小时)进行采样,以跟踪VOC浓度的动态变化,揭示出三种曲线:与细菌载量成比例释放、临时最大值和吸收。敏感菌株共释放32种VOCs,耐药菌株释放25种VOCs,其中耐碳青霉烯类肺炎克雷伯菌的2 - 戊酮、2 - 庚酮和2 - 壬酮显著更高。与参考肺炎克雷伯菌菌株相比,临床分离株产生的代谢产物明显更多(= 64种)且种类更丰富。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/690e/9623108/103c802ed3fe/fmolb-09-1019290-g001.jpg

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