Fiber Probe-Based Raman Spectroscopic Identification of Pathogenic Infection Microorganisms on Agar Plates

Rapid identification of microorganisms is clinically meaningful, and it helps to decelerate the spread of drug resistance and improve patient treatment. In this study, we present a rapid fiber probe-based Raman technique with an excitation wavelength of 785 nm, which is applied to classify and identify nine different species of microorganisms. The cost-effective fiber probe compresses the dimension of the system and provides a more reliable and stable database. All microorganisms were simply cultivated on Luria-Bertani (LB) agar, and Raman spectra were obtained directly from the microbial colonies with the fiber probe within 30 s. The classification model consists of principal component analysis (PCA) in combination with linear discriminant analysis (LDA) and was examined by applying leave-one-batch-out cross-validation (LOBOCV). This model achieved an accuracy of 98.9%. In addition, the validation and identification processes based on independent replicates achieved accuracies of 99.8% and 100%, respectively. The results demonstrated that fiber probe Raman spectroscopy in combination with chemometric analysis allowed a rapid classification and identification of microorganisms only with a normal culture. Therefore, it is promising especially for medical applications and could moreover be helpful to investigate and identify microorganisms rapidly in further studies.