Bacteria can be harmless commensals, beneficial probiotics, or harmful pathogens. Therefore, mankind is challenged to detect and identify bacteria in order to prevent or treat bacterial infections. Examples are identification of species for treatment of infection in clinics and E. coli cell counting for water quality monitoring. Finally, in some instances, the pathogenicity of a species is of interest. The main strategies to investigate pathogenicity are detection of target genes which encode virulence factors. Another strategy could be based on phenotypic identification. Raman spectroscopy is a promising phenotypic method, which offers high sensitivities and specificities for the identification of bacteria species. In this study, we evaluated whether Raman microspectroscopy could be used to determine the pathogenicity of E. coli strains. We used Raman spectra of seven non-pathogenic and seven pathogenic E. coli strains to train a PCA-SVM model. Then, the obtained model was tested by identifying the pathogenicity of three additional E. coli strains. The pathogenicity of these three strains could be correctly identified with a mean sensitivity of 77%, which is suitable for a fast screening of pathogenicity of single bacterial cells.

细菌可以是无害的食品，有益的益生菌或有害的病原体。因此，人类面临着检测和鉴定细菌以预防或治疗细菌感染的挑战。例如在诊所和大肠杆菌中鉴定用于治疗感染的物种细胞计数以监测水质。最后，在某些情况下，物种的致病性令人关注。研究致病性的主要策略是检测编码毒力因子的靶基因。另一种策略可以基于表型鉴定。拉曼光谱法是一种有前途的表型方法，它为细菌种类的鉴定提供了高灵敏度和特异性。在这项研究中，我们评估了拉曼光谱是否可用于确定大肠杆菌菌株的致病性。我们使用了七个非病原性和七个致病性大肠杆菌菌株的拉曼光谱来训练PCA-SVM模型。然后，通过识别另外三种大肠杆菌的致病性来测试获得的模型株。这三种菌株的致病性可以正确识别，平均灵敏度为77％，适合快速筛选单个细菌细胞的致病性。