RNA-seq analysis of glucose fermentation by the natural Isopropanol producer Clostridium beijerinckii DSM6423

  • Hadrien Mate de Gerando (IFP Energies nouvelles) (Creator)
  • Frédérique Bidard (Creator)
  • Etienne Jourdier (Creator)
  • Ana Lopez Contreras (Creator)
  • Nicolas Lopes Ferreira (Creator)



Purpose: C. beijerinckii DSM 6423 is the most cited natural IpOH producer. Improving the natural production of this strain through a targeted approach required a full sequencing and characterization of its genome, together with transcriptomic analyses of its own regulations.The goals of this study are then to evaluate the transcriptional profile (RNA-Seq) of C. beijerinckii DSM6423, a natural isopropanol producer, during a fermentation of glucose in controlled bioreactors.
Methods: A RNA-Seq approach was chosen in order to have a timelapse study of DSM 6423 throughout the fermentation process. Three independent duplicate fermentations of DSM 6423 were carried out in bioreactors on three different weeks, showing good reproducibility. On each cultivation, five biomass samples were collected for RNA-Seq analyses.and DNA was eliminated after DNAse I treatment (AM1906, Invitrogen). The 15 resulting RNA samples were sequenced and analyzed using the previously reconstructed genome of DSM 6423.
Results: Using a data analysis workflow (TAMARA) developed by the Genoscope platform of Evry, we were able to highlight the transcriptional regulation along the fermentation by calculating the transcription profiles of each gene, using the 3h sample as reference. Clustering was performed using CAST algorithm revealed 8 clusters containing 953 genes and corresponding to genes up-regulated at 6, 8, 11 or 24 hours and gene down-regulated at 6, 8, 11 or 24 hours.
Conclusion: Such analyses were carried out in this study and provide useful data to better understand the genetic background and the physiological specificities of C. beijerinckii DSM6423 isopropanol producer. Notably, this work is the first omic study of a natural IBE producer. The data gathered needs time for proper exploitation, but a better understanding of the metabolic pathways and various genes involved opens the door for future targeted approaches.
Date made available5 May 2018


  • Clostridium beijerinckii

Accession numbers

  • GSE100024
  • PRJNA390516

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