Primary transcriptome analysis reveals importance of IS elements for the shaping of the transcriptional landscape of Bordetella pertussis

Abstract

Bordetella pertussis is the causative agent of whooping cough, a respiratory disease still considered as a major public health threat and for which recent re-emergence has been observed. Constant reshuffling of Bordetella pertussis genome organization was observed during evolution. These rearrangements are essentially mediated by Insertion Sequences (IS), a mobile genetic elements present in more than 230 copies in the genome, which are supposed to be one of the driving forces enabling the pathogen to escape from vaccine-induced immunity. Here we use high-throughput sequencing approaches (RNA-seq and differential RNA-seq), to decipher Bordetella pertussis transcriptome characteristics and to evaluate the impact of IS elements on transcriptome architecture. Transcriptional organization was determined by identification of transcription start sites and revealed also a large variety of non-coding RNAs including sRNAs, leaderless mRNAs or long 3' and 5'UTR including seven riboswitches. Unusual topological organizations, such as overlapping 5'- or 3'-extremities between oppositely orientated mRNA were also unveiled. The pivotal role of IS elements in the transcriptome architecture and their effect on the transcription of neighboring genes was examined. This effect is mediated by the introduction of IS harbored promoters or by emergence of hybrid promoters. This study revealed that in addition to their impact on genome rearrangements, most of the IS also impact on the expression of their flanking genes. Furthermore, the transcripts produced by IS are strain-specific due to the strain to strain variation in IS copy number and genomic context.

Keywords: bordetella pertussis; insertion sequence; transcriptome.

Figure 1.

Genome-wide RNA-seq and dRNA-seq data representation and deduced transcriptome organization, focus on a selected region. (A) Visualization of RNA-seq normalized dataset (blue: positive strand depth sequencing graph and grey: negative strand depth sequencing graph). Visualization of dRNA-seq normalized dataset (brown: positive strand depth sequencing graph and red: negative strand depth sequencing graph. The color intensity levels depict the different replicates). (B) Deduced transcriptome annotation in regard to published annotation file (NC_002929). Genes annotation are in green and dark green arrows. Pseudogenes are in firebrick red arrows. Repeated regions are in cyan arrows. Predicted transcripts annotation is indicated with orange and purple arrows. TSS positions are in red and dark red. (C) Detailed view on a few annotated genes.

Figure 2.

bvgR and bvgAS transcription organization. Detailed view of genome browser for the bvgAS and bvgR sequence region. Prediction of transcripts organization is indicated.

Figure 3.

Candidate transcripts classification. Venn diagrams of candidate transcripts numbers deduced from dRNA-seq and RNA-seq. Number of antisens and orphan candidate transcripts are counted as the function of the detection methods.

Figure 4.

Promoters and transcription in insertion sequences. Gene ORF are indicated as plain blue arrows. IS and inverted repeat left and right (IRL and IRR) are indicated as plain brown arrows. The sequencing depth graphs are shown underneath in green for positive (: same orientation as published sequence) orientated reads and in red for negatively orientated reads. Promoter positions and orientation are indicated as black arrows. (A) General organization of transcription in IS region. (B) Representative example of flanking gene transcription activation due to P_out activity. (C) Representative example of antisense transcription in regard to flanking gene due to P_out activity. (D) P_in polar transcription activity in the gene downstream of the transposase.