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. 2018 May 30;19(1):415.
doi: 10.1186/s12864-018-4805-8.

Transcription Profiling of Butanol Producer Clostridium Beijerinckii NRRL B-598 Using RNA-Seq

Free PMC article

Transcription Profiling of Butanol Producer Clostridium Beijerinckii NRRL B-598 Using RNA-Seq

Karel Sedlar et al. BMC Genomics. .
Free PMC article


Background: 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.

Results: 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.

Conclusions: 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.

Keywords: ABE fermentation; Clostridium beijerinckii NRRL B-598; RNA-Seq transcriptome.

Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Fig. 1
Fig. 1
Cultivation and fermentation characteristics of Clostridium beijerinckii NRRL B-598. (a) The concentration of glucose, solvents and acids during ABE fermentation. (b) Flow cytometry – the distribution of cells within the population according to their fluorescence pattern for combined staining using PI and CFDA. (c) pH curve for respective cultivation. (d) Cell growth measured as optical density at 600 nm. Values represent the mean of the biological replicates and error bars represent the standard deviations. Time-points (T1–T6) for samples subjected to RNA expression analysis are indicated by red vertical dotted lines and/or by red text labels
Fig. 2
Fig. 2
Quality of RNA-Seq reads. (a) The total number of reads in particular samples. The color of stacked bars distinguishes between non-rRNA and rRNA reads. (b) Mapping statistics of reads – percentages of uniquely mapped, multi-mapped, and unmapped non-rRNA reads
Fig. 3
Fig. 3
Analysis of the transcriptome reproducibility. (a) Transcription profiles of six selected genes visualized on the heatmap using a Z-score related to an average expression of each gene. (b) 2D representation of the normalized expression data after dimensionality reduction by t-SNE to compare the samples collected at the six time-points (T1–T6) coded by different colors. Each point represented a sample with a text label based on the biological replicate (A, B, and C) and the time-point from which it originated (T1–T6)
Fig. 4
Fig. 4
Differential expression analysis. Venn diagrams showing the number of (a) all-regulated, (b) up-regulated, and (c) down-regulated genes between adjacent time-points

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