Classification of some lactic acid bacteria from vacuum‐packed meats by direct probe mass spectrometry

Abstract

The technique of direct probe mass spectrometry (DPMS) has been applied to the classification of 40 strains of lactic acid bacteria from refrigerated vacuum-packed beef, pork, lamb and bacon. Relationships between strains were examined by multi-variate statistical techniques using sets of ions selected for reproducibility and sample discrimination. Five groups were distinguished which corresponded closely to those detected in a previous numerical taxonomic study. Two groups contained all 12 representatives of a cluster of unidentifiable non-aciduric streptobacteria whose sub-division is supported by other taxonomic evidence. All twenty-one strains from a cluster of aciduric streptobacteria provisionally identified with Lactobacillus sake were contained in two further groups. The sub-division of these aciduric strains revealed by DPMS has not been verified by other techniques and requires further investigation. The fifth group contained Leuconostoc strains. The study demonstrates the value of DPMS in confirming and clarifying classification schemes obtained by conventional methods.

Review on microbial metabolomics of probiotics and pathogens: Methodologies and applications

“…In recent years, microbial metabolomics has made great progress and breakthroughs in the field of LAB research, such as strain screening and identification, metabolic pathway analysis, fermentation engineering, and beneficial effects (Kim et al, 2017;Zhao et al, 2016). The traditional classification of LAB is mainly based on morphological observation and biochemical experiments (Cai et al, 1999;Makela et al, 1992;Shaw et al, 1985). With the development of molecular biology techniques, genotyping methods such as microbial genome sequencing, 16S rDNA sequence analysis, polymerase chain reaction (PCR) fingerprinting, and DNA hybridization technology have been widely used (Domingos-Lopes et al, 2017;Ghodhbane et al, 2016;Ramos et al, 2018;Zhao et al, 2015).…”

Comparison of pattern recognition techniques for the identification of lactic acid bacteria

“…Patterns that are close together (short vector length) are considered more similar than those that are further apart. In addition to Euclidean distance, Pythagorean distance (Euclidean distance squared) and Mahalanobis distance (which takes into account correlation as well as distance) have occasionally been used as the similarity measures (MacFie et al 1978; Shaw et al 1985; Shaw and Harding 1984; Borch and Molin 1988). The SIMCA pattern recognition procedure (Ståhl et al .…”

“…The SIMCA pattern recognition procedure (Ståhl et al . 1990) and non‐linear mapping (Shaw et al . 1985) have also been used.…”

“…In addition to Euclidean distance, Pythagorean distance (Euclidean distance squared) and Mahalanobis distance (which takes into account correlation as well as distance) have occasionally been used as the similarity measures (MacFie et al 1978;Shaw et al 1985;Shaw and Harding 1984;Borch and Molin 1988). The SIMCA pattern recognition procedure (Sta Êhl et al 1990) and non-linear mapping (Shaw et al 1985) have also been used. With the multivariate methods, unlike the case for similarity coef®cients, it is readily possible to employ not only binary scored data, but also semiquantitative or continuous property results.…”

Computer-based linear regression analysis of desorption mass spectra of microorganisms

“…Windig et al (7) have applied discriminant analysis to the extracted factors, and their results, presented in the form of discriminant score plots, provide a quantitative measure of the differences between spectra. Similar techniques have been used successfully to distinguish taxonomic groupings of bacteria and yeasts (8,15,16). However, the component spectra themselves cannot be extracted from pyrolysis spectra by simple mathematical techniques because the structures of the mixture components and their origins cannot be fully assigned.…”