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In this study, Raman microspectroscopy has been utilized to identify mycobacteria to the species level. Because of the slow growth of mycobacteria, the per se cultivation-independent Raman microspectroscopy emerges as a perfect tool for a rapid on-the-spot mycobacterial diagnostic test. Special focus was laid upon the identification of Mycobacterium tuberculosis complex (MTC) strains, as the main causative agent of pulmonary tuberculosis worldwide, and the differentiation between pathogenic and commensal nontuberculous mycobacteria (NTM). Overall the proposed model considers 26 different mycobacteria species as well as antibiotic susceptible and resistant strains. More than 8800 Raman spectra of single bacterial cells constituted a spectral library, which was the foundation for a two-level classification system including three support vector machines. Our model allowed the discrimination of MTC samples in an independent validation dataset with an accuracy of 94% and could serve as a basis to further improve Raman microscopy as a first-line diagnostic point-of-care tool for the confirmation of tuberculosis disease.

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Lower respiratory tract infections are the fourth leading cause of death worldwide. Here, a timely identification of the causing pathogens is crucial to the success of the treatment. Raman spectroscopy allows for quick identification of bacterial cells without the need for time-consuming cultivation steps, which is the current gold standard to detect pathogens. However, before Raman spectroscopy can be used to identify pathogens, they have to be isolated from the sample matrix, i.e., sputum in case of lower respiratory tract infections. In this study, we report an isolation protocol for single bacterial cells from sputum samples for Raman spectroscopic identification. Prior to the isolation, a liquefaction step using the proteolytic enzyme mixture Pronase E is required in order to deal with the high viscosity of sputum. The extraction of the bacteria was subsequently performed via different filtration and centrifugation steps, whereby isolation ratios between 46 and 57 % were achieved for sputa spiked with 6·10(7) to 6·10(4) CFU/mL of Staphylococcus aureus. The compatibility of such a liquefaction and isolation procedure towards a Raman spectroscopic classification was shown for five different model species, namely S. aureus, Staphylococcus epidermidis, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa. A classification of single-cell Raman spectra of these five species with an accuracy of 98.5 % could be achieved on the basis of a principal component analysis (PCA) followed by a linear discriminant analysis (LDA). These classification results could be validated with an independent test dataset, where 97.4 % of all spectra were identified correctly. Graphical Abstract Development of an isolation protocol of bacterial cells out of sputum samples followed by Raman spectroscopic measurement and species identification using chemometrical models.