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Transcriptional profiling of Klebsiella pneumoniae defines signatures for planktonic, sessile and biofilm-dispersed cells

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Guilhen, Cyril | Charbonnel, Nicolas | Parisot, Nicolas | Gueguen, Nathalie | Iltis, Agnès | Forestier, Christiane | Balestrino, Damien

Edité par CCSD ; BioMed Central -

International audience. BackgroundSurface-associated communities of bacteria, known as biofilms, play a critical role in the persistence and dissemination of bacteria in various environments. Biofilm development is a sequential dynamic process from an initial bacterial adhesion to a three-dimensional structure formation, and a subsequent bacterial dispersion. Transitions between these different modes of growth are governed by complex and partially known molecular pathways.ResultsUsing RNA-seq technology, our work provided an exhaustive overview of the transcriptomic behavior of the opportunistic pathogen Klebsiella pneumoniae derived from free-living, biofilm and biofilm-dispersed states. For each of these conditions, the combined use of Z-scores and principal component analysis provided a clear illustration of distinct expression profiles. In particular, biofilm-dispersed cells appeared as a unique stage in the bacteria lifecycle, different from both planktonic and sessile states. The K-means cluster analysis showed clusters of Coding DNA Sequences (CDS) and non-coding RNA (ncRNA) genes differentially transcribed between conditions. Most of them included dominant functional classes, emphasizing the transcriptional changes occurring in the course of K. pneumoniae lifestyle transitions. Furthermore, analysis of the whole transcriptome allowed the selection of an overall of 40 transcriptional signature genes for the five bacterial physiological states.ConclusionsThis transcriptional study provides additional clues to understand the key molecular mechanisms involved in the transition between biofilm and the free-living lifestyles, which represents an important challenge to control both beneficial and harmful biofilm. Moreover, this exhaustive study identified physiological state specific transcriptomic reference dataset useful for the research community.

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