Raman spectroscopic identification of single bacterial cells at different stages of their lifecycle

Early, rapid, and reliable bacterial identification is of great importance in natural environments and in medical situations. Numerous studies have shown that Raman spectroscopy can be used to differentiate between different bacteria under controlled laboratory conditions. However, individual bacteria within a population exhibit macromolecular and metabolic heterogeneity over their lifetime. Therefore it is important to be able to identify and classify specific bacteria at different time points of the growth cycle. In this study, four species of bacteria were used to explore the capability of confocal Raman spectroscopy as a tool for the identification of (and discrimination between) diverse bacterial species at various growth time points. The results show that bacterial cells from different growth time points (as well as from a random growth phase) can be discriminated among the four species using principal component analysis (PCA). The results also show that bacteria selected from different growth phases can be classified with the help of a prediction model based on principal component and linear discriminant analysis (PC-LDA). These findings demonstrate that Raman spectroscopy with the application of a PC-LDA model rooted in chemotaxonomic analysis has potential for rapid sensing of microbial cells in environmental and clinical studies.