High-Wavenumber Raman Spectroscopy for the Identification and Biochemical Characterization of Microbial Species

Raman spectroscopy is a powerful tool for microbiological and infectious disease research, enabling rapid discrimination of microbial species. While spectral discrimination has typically been performed using the fingerprint region (400-1800 cm^-1), high autofluorescence backgrounds can degrade signal quality and decrease the overall effectiveness. This work investigates the effectiveness of utilizing the low-background high-wavenumber region (2800-3800 cm^-1) to both identify and biochemically characterize microbial species. High-wavenumber spectra of 14 microbial species were collected and used to train and validate a multitiered classification model capable of identifying cell wall type (100%), genus (98.9%), and species (97.4%) with high accuracy. Additionally, utilizing a spectral unmixing approach, the relative Raman contributions from proteins, carbohydrates, nucleic acids, lipids, and cell wall components were determined for each species, with general trends matching reported physiological differences. Utilizing a method of converting high-wavenumber Raman spectral fractions to relative dry mass, a biochemical characterization of each species was obtained, with the Raman dry mass characterization of Escherichia coli (E. coli) closely matching previously reported values. Taken together, these results demonstrate that high-wavenumber Raman spectroscopy is a feature-rich technique capable of performing both accurate discrimination and nondestructive biochemical characterization of microbial species.