Institute of Physical Chemistry and Abbe Center of Photonics , Friedrich Schiller University Jena , Helmholtzweg 4 , 07745 Jena , Germany.
Research Campus Infectognostic , Philosophenweg 7 , 07743 Jena , Germany.
Anal Chem. 2018 Aug 7;90(15):8912-8918. doi: 10.1021/acs.analchem.8b01038. Epub 2018 Jul 16.
Fungal spores are one of several environmental factors responsible for causing respiratory diseases like asthma, chronic obstructive pulmonary disease (COPD), and aspergillosis. These spores also are able to trigger exacerbations during chronic forms of disease. Different fungal spores may contain different allergens and mycotoxins, therefore the health hazards are varying between the species. Thus, it is highly important quickly to identify the composition of fungal spores in the air. In this study, UV-Raman spectroscopy with an excitation wavelength of 244 nm was applied to investigate eight different fungal species implicated in respiratory diseases worldwide. Here, we demonstrate that darkly colored spores can be directly examined, and UV-Raman spectroscopy provides the information sufficient for classifying fungal spores. Classification models on the genus, species, and strain levels were built using a combination of principal component analysis and linear discriminant analysis followed by evaluation with leave-one-batch-out-cross-validation. At the genus level an accuracy of 97.5% was achieved, whereas on the species level four different Aspergillus species were classified with 100% accuracy. Finally, classifying three strains of Aspergillus fumigatus an accuracy of 89.4% was reached. These results demonstrate that UV-Raman spectroscopy in combination with innovative chemometrics allows for fast identification of fungal spores and can be a potential alternative to currently used time-consuming cultivation.
真菌孢子是导致哮喘、慢性阻塞性肺疾病(COPD)和曲霉菌病等呼吸道疾病的几个环境因素之一。这些孢子也能够在慢性疾病中引发恶化。不同的真菌孢子可能含有不同的过敏原和霉菌毒素,因此不同物种的健康危害也不同。因此,快速识别空气中真菌孢子的组成非常重要。在这项研究中,我们应用激发波长为 244nm 的紫外拉曼光谱法来研究全球范围内与呼吸道疾病有关的八种不同的真菌物种。在这里,我们证明可以直接检查深色孢子,并且紫外拉曼光谱法提供了足够的信息来对真菌孢子进行分类。使用主成分分析和线性判别分析的组合,并通过留一一批外验证进行评估,构建了属、种和菌株水平的分类模型。在属水平上,达到了 97.5%的准确率,而在种水平上,四种不同的曲霉菌种的分类准确率达到了 100%。最后,对三个烟曲霉菌株的分类准确率达到了 89.4%。这些结果表明,紫外拉曼光谱法结合创新的化学计量学方法可以快速识别真菌孢子,并且可能成为目前耗时的培养方法的潜在替代方法。