Literature DB >> 19411407

Pyrosequencing of tagged 16S rRNA gene amplicons for rapid deciphering of the microbiomes of fermented foods such as pearl millet slurries.

Christèle Humblot1, Jean-Pierre Guyot.   

Abstract

Pearl millet slurries, mixed with groundnuts or not, were chosen as a model to investigate the feasibility of obtaining a rapid overview of community structure and population dynamics of fermented foods using pyrosequencing of tagged 16S rRNA gene amplicons. From 14 fermented samples collected either in a traditional small-scale processing unit in Burkina Faso or at laboratory scale, 137,469 sequences of bacterial 16S rRNA gene amplicons were characterized. Except for a few Proteobacteria, almost all the bacterial sequences were attributed to cultivable bacteria. This approach enabled 80.7% of the sequences to be attributed to a family and 70% to a genus but did not enable identification to the species level. The bacterial sequences were assigned to four phyla, with Firmicutes representing the highest diversity, followed by Proteobacteria, Actinobacteria, and Bacteroidetes, which were found only in the slurries prepared in traditional production units. Most of the Firmicutes were lactic acid bacteria, mainly represented by members of the Lactobacillus, Pediococcus, Leuconostoc, and Weissella genera, whose ratio varied from the onset to the end of the fermentation. The other bacteria present at the beginning of fermentation were generally no longer detected at the end, which is consistent with already-known patterns in the microbial ecology of fermented foods. In conclusion, this method seems very promising for rapid and preliminary microbial characterization in many samples of an unknown food sample, by determining numerous nucleic sequences simultaneously without the need for cloning and cultivation-dependent methods.

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Year:  2009        PMID: 19411407      PMCID: PMC2704832          DOI: 10.1128/AEM.00451-09

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


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