Rapid phenotypic identification of microorganisms with Raman

Importance of Rapid Phenotypic Microbial Identification

Microorganisms underpin ecological cycles, food production, and biotechnology. Rapid and non-destructive identification of bacterial strains enhances quality control, ecological monitoring, and bioprocess optimization. Raman spectroscopy offers a label-free approach to capture biochemical fingerprints directly from colonies, avoiding time-consuming genetic sequencing.

Study Objectives and Overview

This study evaluated the feasibility of using 785 nm and 1064 nm Raman excitation to differentiate bacterial colonies grown on LB agar. The aim was to demonstrate a simple workflow for direct phenotypic identification and metabolite monitoring.

Methodology and Instrumentation

Bacterial colonies were cultivated on lysogeny broth (LB) agar prepared by standard protocols and transferred via fingertip stamping. After room-temperature incubation, colonies were probed using:

• Metrohm i-Raman Prime 785 Raman spectrometer (785 nm excitation)
• Metrohm i-Raman EX Raman spectrometer (1064 nm excitation)
• BAC150B probe holder and BAC151C video microscope with 50× objective
• BWSpec software for data acquisition and preprocessing

Key acquisition parameters included laser power from 30 % to 100 %, integration times of 3–60 s, and 3–5 accumulations per measurement.

Main Results and Discussion

Raman spectra of colonies revealed characteristic peaks corresponding to amino acids (e.g., 1001, 1156, 1654 cm⁻¹) and nucleic acids (e.g., 723, 1337 cm⁻¹). Excitation at 785 nm produced sharper and stronger peaks due to higher scattering efficiency and CCD detector performance, while 1064 nm minimized fluorescence from complex media.
Two morphologically distinct colonies (white and yellow) exhibited unique spectral profiles. Yellow colonies showed pigment-related bands. Principal Component Analysis effectively separated these phenotypes, suggesting simple chemometric models can discriminate strains in small communities.

Benefits and Practical Applications of the Method

• Direct, label-free analysis of solid media without extensive sample preparation
• Rapid discrimination of bacterial phenotypes for QC and environmental screening
• Non-destructive monitoring of metabolite storage compounds (e.g., glycogen, polyphosphate)
• Potential integration with automated workflows and portable instrumentation

Future Trends and Applications

Emerging directions include machine learning algorithms for subtle spectral differences, expansion of Raman databases for high-throughput identification, and in situ monitoring of microbial dynamics in bioreactors or environmental samples. Integration with advanced chemometric tools will enhance sensitivity and specificity.

Conclusion

Raman spectroscopy with both 785 nm and 1064 nm excitation offers a versatile platform for rapid phenotypic identification of bacteria on agar. The approach is simple, nondestructive, and adaptable for real-time microbiological analysis. Chemometric methods like PCA and advanced machine-learning pipelines further improve discrimination of microbial communities.

References

Paret ML, Sharma SK, Green LM, et al. Biochemical Characterization of Gram-Positive and Gram-Negative Plant-Associated Bacteria with Micro-Raman Spectroscopy. Applied Spectroscopy 2010;64(4):433–441. DOI:10.1366/000370210791114293