Kloss Sandra, Kampe Bernd, Sachse Svea, Rösch Petra, Straube Eberhard, Pfister Wolfgang, Kiehntopf Michael, Popp Jürgen
Institute of Physical Chemistry and Abbe Center of Photonics, University of Jena , Helmholtzweg 4, D-07743 Jena, Germany.
Anal Chem. 2013 Oct 15;85(20):9610-6. doi: 10.1021/ac401806f. Epub 2013 Sep 24.
Urinary tract infection (UTI) is a very common infection. Up to every second woman will experience at least one UTI episode during her lifetime. The gold standard for identifying the infectious microorganisms is the urine culture. However, culture methods are time-consuming and need at least 24 h until the results are available. Here, we report about a culture independent identification procedure by using Raman microspectroscopy in combination with innovative chemometrics. We investigated, for the first time directly, urine samples by Raman microspectroscopy on a single-cell level. In a first step, a database of eleven important UTI bacterial species, which were grown in sterile filtered urine, was built up. A support vector machine (SVM) was used to generate a statistical model, which allows a classification of this data set with an accuracy of 92% on a species level. This model was afterward used to identify infected urine samples of ten patients directly without a preceding culture step. Thereby, we were able to determine the predominant bacterial species (seven Escherichia coli and three Enterococcus faecalis ) for all ten patient samples. These results demonstrate that Raman microspectroscopy in combination with support vector machines allow an identification of important UTI bacteria within two hours without the need of a culture step.
尿路感染（UTI）是一种非常常见的感染。高达每两名女性中就有一人在其一生中至少会经历一次尿路感染发作。鉴定感染性微生物的金标准是尿液培养。然而，培养方法耗时，至少需要24小时才能获得结果。在此，我们报告一种通过将拉曼光谱与创新的化学计量学相结合的非培养鉴定程序。我们首次在单细胞水平上通过拉曼光谱直接研究尿液样本。第一步，建立了在无菌过滤尿液中培养的11种重要尿路感染细菌种类的数据库。使用支持向量机（SVM）生成一个统计模型，该模型能够在物种水平上以92%的准确率对该数据集进行分类。随后，该模型被用于直接识别10名患者的感染尿液样本，而无需事先进行培养步骤。由此，我们能够确定所有10名患者样本中的主要细菌种类（7株大肠杆菌和3株粪肠球菌）。这些结果表明，拉曼光谱与支持向量机相结合能够在两小时内鉴定出重要的尿路感染细菌，而无需培养步骤。
