Identification Analysis of Lactobacillus Species/Strains Using IRXross

Significance of the Topic

This article addresses the need for rapid and reliable identification of bacterial species and strains in clinical diagnostics, food quality control and pharmaceutical processes. Fourier Transform Infrared (FTIR) spectroscopy offers a simpler and faster alternative to conventional methods such as PCR and PFGE by exploiting molecular vibrational fingerprints.

Objectives and Overview of the Study

The study demonstrates the application of an IRXross FTIR spectrophotometer equipped with a diffuse reflectance accessory and a microfocus plate to identify seven Lactobacillus strains. The goal is to achieve species- and subspecies-level discrimination within a short measurement time.

Methodology

Sample Preparation:

• Seven Lactobacillus strains cultured on MRS medium at 30 °C for 24 h.
• Cell suspensions prepared by mixing 50 μL water, 50 μL ethanol, and three 1 μL inoculation loops of bacterial culture.
• Cell disruption using zirconia beads and a disintegration device (30 s×4).
• Suspension centrifuged, 2 μL of supernatant applied to a 64-well microfocus plate and air-dried.

Data Analysis:

• Infrared spectra collected in diffuse reflectance mode (4 cm⁻¹ resolution, 20 accumulations, DLATGS detector) under nitrogen purge.
• Spectral preprocessing in LabSolutions IR and Aspen Unscrambler: 2nd derivative (Savitzky-Golay, 31 points, 2nd order), wavelength range 1300–800 cm⁻¹, unit vector normalization and mean centering.
• Multivariate analysis: principal component analysis (PCA) and hierarchical cluster analysis (Ward’s method, squared Euclidean distance).

Instrumentation Used

• Shimadzu IRXross/IRTracer-100 FTIR Spectrophotometer
• Diffuse Reflectance Measurement Accessory (special order)
• 64-well Microfocus Plate
• DLATGS Detector
• Cell Disintegration Device with zirconia beads
• LabSolutions IR Software
• Aspen Unscrambler Multivariate Analysis Program

Main Results and Discussion

The raw infrared spectra of the seven strains show highly similar profiles, making direct spectral comparison insufficient for identification. Second-derivative processing enhances subtle differences. PCA score plots and hierarchical clustering distinctly separate L. rhamnosus from other species, and further resolve L. paracasei subspecies, L. zeae, L. chiayiensis, and L. casei at the strain level. The observed clustering aligns with established taxonomic relationships.

Benefits and Practical Applications

• Rapid measurement (about 30 s per sample) supports high-throughput workflows.
• Minimal and straightforward sample preparation without complex reagents.
• Applicability to diverse biological and non-biological samples.
• Potential integration into quality assurance, clinical research, and industrial monitoring.

Future Trends and Potential Applications

Advancements may include automated spectral classification using machine learning, expansion of spectral libraries for broader microbial identification, integration with online process control, and development of portable FTIR platforms for on-site analysis.

Conclusion

The combination of IRXross FTIR spectroscopy and diffuse reflectance measurement provides a fast, reliable, and user-friendly method for discriminating Lactobacillus species and strains. This approach overcomes limitations of traditional molecular techniques and offers significant utility in research and industrial settings.

References

1. Lasch P, Naumann D. Infrared Spectroscopy in Microbiology. Encyclopedia of Analytical Chemistry, 3: 1–32, 2015.
2. Liu DD, Gu CT. Proposal to reclassify Lactobacillus zhaodongensis, Lactobacillus zeae, Lactobacillus argentoratensis and Lactobacillus buchneri subsp. silagei as Lacticaseibacillus zhaodongensis comb. nov., Lacticaseibacillus zeae comb. nov., Lactiplantibacillus argentoratensis comb. nov. and Lentilactobacillus buchneri subsp. silagei comb. nov., respectively and Apilactobacillus kosoi as a later heterotypic synonym of Apilactobacillus micheneri. Int J Syst Evol Microbiol, 70: 6414–6417, 2020.