Transcription profiling of butanol producer Clostridium beijerinckii NRRL B-598 using RNA-Seq

Karel Sedlar, Pavlina Koscova, Maryna Vasylkivska, Barbora Branska, Jan Kolek, Kristyna Kupkova, Petra Patakova, Ivo Provaznik

Thinning supplies of natural resources increase attention to sustainable microbial production of bio-based fuels. The strain Clostridium beijerinckii NRRL B-598 is a relatively well-described butanol producer regarding its genotype and phenotype under various conditions. However, a link between these two levels, lying in the description of the gene regulation mechanisms, is missing for this strain, due to the lack of transcriptomic data. In this paper, we present a transcription profile of the strain over the whole fermentation using an RNA-Seq dataset covering six time-points with the current highest dynamic range among solventogenic clostridia. We investigated the accuracy of the genome sequence and particular genome elements, including pseudogenes and prophages. While some pseudogenes were highly expressed, all three identified prophages remained silent. Furthermore, we identified major changes in the transcriptional activity of genes using differential expression analysis between adjacent time-points. We identified functional groups of these significantly regulated genes and together with fermentation and cultivation kinetics captured using liquid chromatography and flow cytometry, we identified basic changes in the metabolism of the strain during fermentation. Interestingly, C. beijerinckii NRRL B-598 demonstrated different behavior in comparison with the closely related strain C. beijerinckii NCIMB 8052 in the latter phases of cultivation. We provided a complex analysis of the C. beijerinckii NRRL B-598 fermentation profile using several technologies, including RNA-Seq. We described the changes in the global metabolism of the strain and confirmed the uniqueness of its behavior. The whole experiment demonstrated a good reproducibility. Therefore, we will be able to repeat the experiment under selected conditions in order to investigate particular metabolic changes and signaling pathways suitable for following targeted engineering.