Biodiversity and identification of sourdough lactic acid bacteria
- PMID: 17008154
- DOI: 10.1016/j.fm.2006.07.005
Biodiversity and identification of sourdough lactic acid bacteria
Abstract
This review deals with recent developments on the biodiversity of sourdough lactic acid bacteria (LAB) and the recent description of new sourdough LAB species. One of the outcomes of biodiversity studies of particular sourdough ecosystems throughout Europe is the description of new taxa of LAB. During the last 3 years, several new LAB species have been isolated from traditional sourdoughs: Lactobacillus mindensis, Lactobacillus spicheri, Lactobacillus rossiae, Lactobacillus zymae, Lactobacillus acidifarinae, Lactobacillus hammesii, and Lactobacillus nantensis. Some of these species have been described on one single isolate only. Isolation of novel taxa mainly depends on the cultivation approach used, i.e. (selective) incubation media and conditions. The distribution of the taxa of LAB is highly variable from one sourdough ecosystem to another. Therefore, it is difficult to define correlations between population composition and both the type of sourdough or the geographic location. Identification of isolated strains needs a polyphasic approach, including a combination of phenotypic and genotypic methods, the latter often based on the polymerase chain reaction (PCR) and encompassing 16S rRNA sequencing and DNA-DNA hybridizations. A main obstacle in current identification approaches of LAB strains is the lack of a robust and exchangeable identification system for all LAB species. Recent studies based on complete genomes have provided the basis for establishing sets of genes useful for multi-locus sequence analysis (MLSA). Monitoring the population dynamics of sourdough ecosystems can be performed by both culture-dependent (plating and incubation) and culture-independent (e.g. PCR-Denaturing Gradient Gel Electrophoresis) methods. Although highly valuable for community fingerprinting, culture-independent methods do not always yield precise quantitative information.
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