An advanced bioinformatics approach for analyzing RNA-seq data reveals sigma H-dependent regulation of competence genes in Listeria monocytogenes

Abstract

Background: Alternative ρ factors are important transcriptional regulators in bacteria. While ρB has been shown to control a large regulon and play important roles in stress response and virulence in the pathogen Listeria monocytogenes, the function of ρH has not yet been well defined in Listeria, even though ρH controls a large regulon in the closely related non-pathogenic Bacillus subtilis. Results: Using RNA-seq characterization of a L. monocytogenes strain with deletions of all 4 genes encoding alternative ρ factors (δBCHL), which was further modified to overexpress sigH (δBCHL::P rha -sigH), we identified 6 transcription units (TUs) that are transcribed from ρH-dependent promoters. Five of these TUs had not been previously identified. Identification of these promoters was facilitated by use of a bio-informatics approach that compared normalized RNA-seq coverage (NRC), between δBCHL::P rha -sigH and a δBCHL control, using sliding windows of 51nt along the whole genome rather than comparing NRC calculated only for whole genes. Interestingly, we found that three operons that encode competence genes (comGABCDEFG, comEABC, coiA) are transcribed from ρH-dependent promoters. While these promoters were highly conserved in L. monocytogenes, none of them were found in all Listeria spp. and coiA and its ρH-dependent promoter were only found in L. monocytogenes. Conclusions: Our data indicate that a number of L. monocytogenes competence genes are regulated by ρH. This ρH-dependent regulation of competence related genes is conserved in the pathogen L. monocytogenes, but not in other non-pathogenic Listeria strains. Combined with prior data that indicated a role of ρH in virulence in a mouse model, this suggests a possible novel role of ρH-dependent competence genes in L. monocytogenes virulence. Development and implementation of a sliding window approach to identify differential transcription using RNA-seq data, not only allowed for identification of ρH-dependent promoters, but also provides a general approach for sensitive identification of differentially transcribed promoters and genes, particularly for genes that are transcribed from multiple promoter elements only some of which show differential transcription.