Applying Fourier-transform infrared spectroscopy and chemometrics to the characterization and identification of lactic acid bacteria

Abstract

The infrared absorption spectra of 55 lactic acid bacteria belonging to the genera Lactobacillus, Weissella and Carnobacterium were obtained and mathematically analyzed. Sixteen reference strains and 39 food strains isolated from meat and meat products and belonging to the genera Lactobacillus (6 species), Weissella (3 species) and Carnobacterium (2 species) were processed under standardized conditions and their medium infrared spectra obtained using Fourier-transform infrared (FT-IR) spectroscopy. Reproducibility indexes and similarities between FT-IR spectra were calculated using modified correlation coefficients to detect the ranges with the best reproducibility and discrimination properties. Hierarchical cluster analysis and stepwise discriminant analysis (SDA) were subsequently carried out to detect classes and create library groups. Reference strains could be distinguished on the basis of their spectral data and their clustering was in agreement with differences in chemical composition of the cell wall. For the 39 food isolates, the capability of two identification systems was compared. Unknown strains were identified (a) using the linear functions obtained from SDA (canonical variables) of the variables that provide the best discrimination of spectra, and (b) by calculating a differentiation index when a range of the unknown's transformed IR spectrum was compared to all spectra included in a reference library. The system based on the differentiation index obtained a higher rate of identification, allowing for detection of outliers. FT-IR spectroscopy is shown to afford additional information to phenotypic and genotypic data which may help to establish a more robust taxonomic classification.