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首次使用电子鼻检测挥发性有机化合物进行细菌学诊断

来源: Heers H., Heinig J., Von Stauffenberg F. et al  发布日期: 2019-06-11  访问量: 69


挥发性有机化合物(VOC)可以帮助诊断各种疾病。它们可能是疾病特异性的,并且可以用“电子鼻”从尿液样本中检测到。我们的研究小组以前报道并发表了利用这个快速检测系统检测膀胱肿瘤的有前景的数据。使用尿液培养物或拭子进行细菌学诊断通常需要几天时间来建立可靠的诊断。本研究的目的是研究VOC检测是否有可能成为细菌感染诊断的快速替代方法。...
标签: Cyranose 320、电子鼻、挥发性有机物、细菌、VOCs
 

Bacteriological diagnosis with volatile organic compounds – first experiences with an electronic nose

首次使用电子鼻检测挥发性有机化合物进行细菌学诊断
Eur Urol Suppl 2019; 18(1);e381

Heers H. 1 , Heinig J. 1 , Von Stauffenberg F. 1 , Hegele A. 1 , Hofmann R. 1 , Böselt T. 2 , Koczulla A.R. 2
1Philipps-Universität Marburg, Dept. of Urology and Paediatric Urology, Marburg, Germany, 2Philipps-Universität Marburg, Dept. of Pulmonology,
Marburg, Germany

 

Introduction & Objectives: Volatile organic compounds (VOCs) can help to diagnose a wide range of diseases. They may be disease-specific and can be detected for example from urine samples using “electronic noses”. Our group previously reported and published promising data on the detection of bladder tumours using this rapid testing system. Bacteriological diagnosis using urine cultures or swabs usually requires several days to establish a reliable diagnosis. The aim of this study was to investigate whether VOC detection can potentially represent a speedy alternative in the diagnosis of bacterial infections.

挥发性有机化合物(VOC)可以帮助诊断各种疾病。它们可能是疾病特异性的,并且可以用“电子鼻”从尿液样本中检测到。我们的研究小组以前报道并发表了利用这个快速检测系统检测膀胱肿瘤的有前景的数据。使用尿液培养物或拭子进行细菌学诊断通常需要几天时间来建立可靠的诊断。本研究的目的是研究VOC检测是否有可能成为细菌感染诊断的快速替代方法。


Materials & Methods: VOC measurements were carried out with Cyranose 320, an electronic nose measuring changes in resistance induced by VOCs competitively binding to an array of 32 polymer sensors. Statistical analysis was performed using principal component analysis and linear discriminant analysis. 71 urine samples of patients with confirmed urinary tract infection (UTI) or significant bacteriuria (≥ 104 colony forming units (CFU)/ml) as established by urine culture and 55 samples from healthy controls were collected and measured. Furthermore, broth cultures at 108 CFU/ml from 20 stock samples each of methicillin-resistant staphylococcus aureus (MRSA) and methicillin-sensitive staphylococcus aureus (MSSA) were tested against pure medium (brain heart infusion broth).

 VOC测量采用Cyranose 320进行,这是一种电子鼻,用于测量VOC与32个聚合物传感器阵列的竞争性结合导致的电阻变化。采用主成分分析和线性判别分析进行统计分析。收集经尿培养证实的尿路感染(UTI)或明显细菌尿(菌落形成单位≥104 cfu/ml)患者的71份尿液样本和健康对照者的55份样本,并进行测量。此外,在纯培养基(脑-心输注肉汤)中检测20个储备样品(每个耐甲氧西林金黄色葡萄球菌(MRSA)和甲氧西林敏感金黄色葡萄球菌(MSSA))的108 cfu/ml肉汤培养物。

 

Results: Urine culture of the UTI samples showed solitary bacterial strains in 39 cases, two differenent strains in 22 cases, and three strains in 9 cases. The range of bacterial strains present were representative for UTI. For the separation of UTI versus healthy control, the electronic nose had a sensitivity of 81.7% and a specificity of 77.3%. Due to the small sample size, no significant differences in the measurement pattern of individual strains could be detected. The measurement of broth cultures from stock samples led to more meaningful results. MRSA was separated from medium with a sensitivity of 96% and specificity of 94%; MSSA vs medium sensitivity 81%, specificity 75%; MRSA vs MSSA sensitivity 100%, specificity 91%.

尿培养结果显示,尿路感染者39例为孤立性细菌,22例为两种不同的细菌,9例为三种细菌。存在的细菌菌株范围代表了尿路感染。对于UTI与健康对照的分离,电子鼻的灵敏度为81.7%,特异性为77.3%。由于样本量小,单个菌株的测量模式没有显著差异。对肉汤样品培养基的测定得到了更有意义的结果。MRSA与培养基分离,敏感度96%,特异性94%;MSSA与培养基敏感度81%,特异性75%;MRSA与MSSA敏感度100%,特异性91%。


Conclusions: VOC-based detection of bacterial infections seems feasible. In purified culture, individual strains may show specific recognisable VOC patterns. Preliminary measurements from urine samples show good results in UTI detection. Further sample handling leading to higher bacterial concentrations may be necessary to allow recognition of individual bacteria. Updated data with further and confirmatory measurements including ion mobility spectrometry will be presented.

基于VOC的细菌感染检测似乎是可行的。在纯化培养基中,单个菌株可能表现出特定的可识别的VOC模式。尿液样本的初步测量结果显示,UTI检测结果良好。进一步的样品处理导致更高的细菌浓度可能是必要的,以便识别单个细菌。将提供包括离子迁移率光谱法在内的更新数据和进一步的验证性测量。


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