Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, Jena, Germany.
Appl Environ Microbiol. 2010 May;76(9):2895-907. doi: 10.1128/AEM.02481-09. Epub 2010 Mar 5.
Micro-Raman spectroscopy is a fast and sensitive tool for the detection, classification, and identification of biological organisms. The vibrational spectrum inherently serves as a fingerprint of the biochemical composition of each bacterium and thus makes identification at the species level, or even the subspecies level, possible. Therefore, microorganisms in areas susceptible to bacterial contamination, e.g., clinical environments or food-processing technology, can be sensed. Within the scope of point-of-care-testing also, detection of intentionally released biosafety level 3 (BSL-3) agents, such as Bacillus anthracis endospores, or their products is attainable. However, no Raman spectroscopy-compatible inactivation method for the notoriously resistant Bacillus endospores has been elaborated so far. In this work we present an inactivation protocol for endospores that permits, on the one hand, sufficient microbial inactivation and, on the other hand, the recording of Raman spectroscopic signatures of single endospores, making species-specific identification by means of highly sophisticated chemometrical methods possible. Several physical and chemical inactivation methods were assessed, and eventually treatment with 20% formaldehyde proved to be superior to the other methods in terms of sporicidal capacity and information conservation in the Raman spectra. The latter fact has been verified by successfully using self-learning machines (such as support vector machines or artificial neural networks) to identify inactivated B. anthracis-related endospores with adequate accuracies within the range of the limited model database employed.
微拉曼光谱学是一种快速而灵敏的工具,可用于检测、分类和识别生物有机体。振动光谱本质上是每个细菌生化组成的指纹,因此可以进行物种甚至亚种级别的鉴定。因此,可以检测到易受细菌污染的区域中的微生物,例如临床环境或食品加工技术。在即时检测的范围内,也可以检测到故意释放的生物安全 3 级(BSL-3)制剂,如炭疽芽孢杆菌芽孢或其产物。然而,迄今为止,还没有针对臭名昭著的芽孢杆菌芽孢的耐拉曼光谱兼容的失活动力学方法。在这项工作中,我们提出了一种用于芽孢的失活动力学方法,一方面可以充分失活微生物,另一方面可以记录单个芽孢的拉曼光谱特征,从而可以通过高度复杂的化学计量学方法进行种特异性鉴定。评估了几种物理和化学失活方法,最终 20%甲醛处理在杀菌能力和拉曼光谱中信息保存方面优于其他方法。这一事实已通过成功使用自学习机器(如支持向量机或人工神经网络)在使用有限模型数据库范围内以足够的准确性识别灭活的炭疽芽孢杆菌相关芽孢得到了验证。