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Identification of mRNA as biomarker of Bacillus weihenstephanensis acid resistance : toward the integration of Omic data into predictive microbiology

  • Desriac, Noémie
Publication Date
Jul 04, 2013
Kaleidoscope Open Archive
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Predictive microbiology is a tool to assess food microbiological risks and optimise food processes. However predictive microbiology which predicts the bacterial behaviour does not take bacterial physiological state into consideration. The aim ofthis work is to identify molecular biomarkers to assess the impact of bacterial adaptation on the subsequent acid resistance. In this study, the acid resistance of Bacillus weihenstephanensis wasinvestigated and mRNAs were identified as acid resistance biomarkers.(i) The bacterial acid resistance of different mildstress adapted cells was quantified using cultural methods. Mild salt-adapted cells were less resistant than cells grown in optimal conditions;and the latter less resistant than acid-adaptedcells. However, the bacterial resistance of B.weihenstephanensis followed the same patternwhen facing acidic changes of the environment and that, whatever the environmental condition previously encountered.(ii) For RT-qPCR gene expression quantifications a specific rotative PCR device based on the PallGeneDisc® Technology was developed.(iii) Omic data and bacterial acid resistances correlation allows the selection of biomarkers to track the more resistant and the more sensitive cells present within the bacterial population.(iv) Both linear and non linear correlations allowed to define two types of biomarkers: ‘Directbiomarker’ for which expression patterns uponmild stress treatment were linearly correlated to the subsequent acid resistance and ‘long-actingbiomarkers’ which were transiently up-regulatedduring mild stress exposure and correlated to increased acid resistance over time.(v) A multivariate analysis was performed to correlate the acid bacterial resistance and the gene expression of vegetative cells. This mathematical method provides the advantage to take gene expressions and their interactions into account and allowed the selection of 9 genes as acid resistance biomarkers of B. weihenstephanensis. Finally, some promising results were also obtained. There by, it would be feasible to use gene expression at a given time to predict the bacterialsurvival behaviour in lethal acid conditions.

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