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分析挥发性指纹图谱,以监测抗真菌药物对原发性和机会性病原体烟曲霉的疗效。

Analysis of volatile fingerprints for monitoring anti-fungal efficacy against the primary and opportunistic pathogen Aspergillus fumigatus.

机构信息

Applied Mycology Group, Cranfield Health, Cranfield University, Bedfordshire, UK.

出版信息

Mycopathologia. 2012 Mar;173(2-3):93-101. doi: 10.1007/s11046-011-9490-y. Epub 2011 Oct 14.

DOI:10.1007/s11046-011-9490-y
PMID:21997859
Abstract

The aims of this study were to use qualitative volatile fingerprints obtained using a hybrid sensor array system to screen anti-fungals for controlling the important lung infecting fungus, Aspergillus fumigatus, especially in immunocompromised patients. SIFT-MS was also used to try and identify key volatiles produced by A. fumigatus. Initial studies were carried out to identify the ED(50) and ED(90) (effective dose) for inhibiting growth of A. fumigatus using three anti-fungal compounds, benomyl, tebuconazole and fluconazole. Subsequent studies involved inoculation of malt extract agar plates with spores of A. fumigatus (25 and 37°C) over periods of 24-72 h to examine the headspace volatile fingerprints generated from the sample treatments using the hybrid sensor array system to compare controls and ED(50)/ED(90) concentrations. The sensor responses showed discrimination between treatments after 48-h incubation when benomyl and tebuconazole were used against A. fumigatus at 37°C using Principal Components Analysis and Cluster Analysis. SIFT-MS analysis showed that methyl pentadiene, ethanol, isoprene and methanol were key biomarker volatiles produced by A. fumigatus in the presence of anti-fungal compounds. This may also be a good approach for the development of rapid screening of anti-microbial compounds and potentially useful for monitoring the possible build up of resistance to specific drug types. Volatile fingerprints produced by patient samples could also be used to evaluate whether lung infections are caused by bacteria or specific fungi to facilitate early diagnosis and enable the right drug treatment to be prescribed.

摘要

本研究旨在使用混合传感器阵列系统获得的定性挥发性指纹图谱筛选抗真菌药物,以控制重要的肺部感染真菌烟曲霉,特别是在免疫功能低下的患者中。SIFT-MS 也被用于尝试鉴定烟曲霉产生的关键挥发物。最初的研究旨在确定三种抗真菌化合物苯菌灵、戊唑醇和氟康唑抑制烟曲霉生长的 ED(50)和 ED(90)(有效剂量)。随后的研究涉及在麦芽提取物琼脂平板上接种烟曲霉孢子(25 和 37°C),培养 24-72 小时,使用混合传感器阵列系统检查样品处理产生的顶空挥发性指纹图谱,以比较对照和 ED(50)/ED(90)浓度。在 37°C 下使用苯菌灵和戊唑醇对烟曲霉菌进行处理 48 小时后,传感器响应通过主成分分析和聚类分析显示出对处理的区分。SIFT-MS 分析表明,在存在抗真菌化合物的情况下,甲基戊二烯、乙醇、异戊二烯和甲醇是烟曲霉产生的关键生物标志物挥发物。这也可能是对抗微生物化合物进行快速筛选的一种很好的方法,并且对于监测特定药物类型的耐药性可能有潜在的用处。患者样本产生的挥发性指纹图谱也可用于评估肺部感染是由细菌还是特定真菌引起,以促进早期诊断,并能开出正确的药物治疗。

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