Quantification of yeast and bacterial gene transcripts in retail cheeses by reverse transcription-quantitative PCR.

Abstract:

:The cheese microbiota contributes to a large extent to the development of the typical color, flavor, and texture of the final product. Its composition is not well defined in most cases and varies from one cheese to another. The aim of the present study was to establish procedures for gene transcript quantification in cheeses by reverse transcription-quantitative PCR. Total RNA was extracted from five smear-ripened cheeses purchased on the retail market, using a method that does not involve prior separation of microbial cells. 16S rRNA and malate:quinone oxidoreductase gene transcripts of Corynebacterium casei, Brevibacterium aurantiacum, and Arthrobacter arilaitensis and 26S rRNA and beta tubulin gene transcripts of Geotrichum candidum and Debaryomyces hansenii could be detected and quantified in most of the samples. Three types of normalization were applied: against total RNA, against the amount of cheese, and against a reference gene. For the first two types of normalization, differences of reverse transcription efficiencies from one sample to another were taken into account by analysis of exogenous control mRNA. No good correlation was found between the abundances of target mRNA or rRNA transcripts and the viable cell concentration of the corresponding species. However, in most cases, no mRNA transcripts were detected for species that did not belong to the dominant species. The applications of gene expression measurement in cheeses containing an undefined microbiota, as well as issues concerning the strategy of normalization and the assessment of amplification specificity, are discussed.

journal_name

Appl Environ Microbiol

authors

Monnet C,Straub C,Castellote J,Onesime D,Bonnarme P,Irlinger F

doi

10.1128/AEM.02360-12

subject

Has Abstract

pub_date

2013-01-01 00:00:00

pages

469-77

issue

2

eissn

0099-2240

issn

1098-5336

pii

AEM.02360-12

journal_volume

79

pub_type

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