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Summary: Since its introduction, RNA-Seq technology has been used extensively in studies of pathogenic bacteria to identify and quantify differences in gene expression across multiple samples from bacteria exposed to different conditions. With some exceptions, tools for studying gene expression, determination of differential gene expression, downstream pathway analysis and normalization of data collected in extreme biological conditions is still lacking. Here, we describe ProkSeq, a user-friendly, fully automated RNA-Seq data analysis pipeline designed for prokaryotes. ProkSeq provides a wide variety of options for analysing differential expression, normalizing expression data and visualizing data and results.

Availability and implementation: ProkSeq is implemented in Python and is published under the MIT source license. The pipeline is available as a Docker container https://hub.docker.com/repository/docker/snandids/prokseq-v2.0, or can be used through Anaconda: https://anaconda.org/snandiDS/prokseq. The code is available on Github: https://github.com/snandiDS/prokseq and a detailed user documentation, including a manual and tutorial can be found at https://prokseqV20.readthedocs.io.

Previous transcriptional profiling of the enteropathogen Yersinia pseudotuberculosis during persistent stages of colonisation of mouse cecal lymphoid follicles indicated the possible involvement of biofilm in infection maintenance. Not much is known about the mechanisms responsible for biofilm formation by this pathogen, and most current knowledge is based on results of experiments conducted using the related Y. pestis pathogen that forms biofilm in the flea gut. In this study, we performed transcriptional profiling of Y. pseudotuberculosis in biofilms from different biofilm-inducing conditions, bile exposure, amino acid deprivation and in vivo mimicking conditions with and without oxygen. The comparison of differential expression of genes in biofilm versus planktonic bacteria showed a set of 54 core genes that were similarly regulated, independent of inducing condition. This set included many genes that were previously shown to be associated with biofilms, such as hutG, hsmF, hmsT and cpxP that were upregulated and other genes such as hmsP and rfaH that were downregulated. There were also novel biofilm-associated genes, including genes encoding hypothetical proteins. To identify the genes involved in inducing biofilm formation, the gene expression of bacteria during an early initial phase when biofilm starts to form after induction by bile or amino acid depletion was determined. Comparisons of the resulting gene expression profiles with the profiles of non-induced bacteria incubated for the same period of time showed a set of core genes associated with early biofilm formation. This set included genes involved in quorum sensing, pili biogenesis and genes indicative of a potential metabolic shift involving nitrogen utilisation. Genes encoding components of sugar phosphotransferase systems were also upregulated during biofilm induction. Assays of biofilm formation by bacteria deleted of some of these core genes showed that strains lacking hpr and luxS, which are known to be important for functional sugar phosphotransferase systems and quorum sensing, as well as glnL encoding a sensory histidine kinase were most negatively affected. Most of the deletion mutant strains tested were affected, but the effect was less severe, suggesting high levels of redundancy in the pathways involved in biofilm formation by this pathogen.

RpoN, an alternative sigma factor commonly known as σ⁵⁴, is implicated in persistent stages of Yersinia pseudotuberculosis infections in which genes associated with this regulator are upregulated. We here combined phenotypic and genomic assays to provide insight into its role and function in this pathogen. RpoN was found essential for Y. pseudotuberculosis virulence in mice, and in vitro functional assays showed that it controls biofilm formation and motility. Mapping genome-wide associations of Y. pseudotuberculosis RpoN using chromatin immunoprecipitation coupled with next-generation sequencing identified an RpoN binding motif located at 103 inter- and intragenic sites on both sense and antisense strands. Deletion of rpoN had a large impact on gene expression, including downregulation of genes encoding proteins involved in flagellar assembly, chemotaxis, and quorum sensing. There were also clear indications of cross talk with other sigma factors, together with indirect effects due to altered expression of other regulators. Matching differential gene expression with locations of the binding sites implicated around 130 genes or operons potentially activated or repressed by RpoN. Mutagenesis of selected intergenic binding sites confirmed both positive and negative regulatory effects of RpoN binding. Corresponding mutations of intragenic sense sites had less impact on associated gene expression. Surprisingly, mutating intragenic sites on the antisense strand commonly reduced expression of genes carried by the corresponding sense strand.

Pathogenic bacteria use a broad range of virulence factors to successfully thrive within their host. Yersinia pseudotuberculosis, a gram-negative enteropathogen of humans, utilises a type III secretion system (T3SS) to overcome the host’s innate immune response. T3SS gene expression is influenced by RpoN, a global regulator that has been shown to be essential for virulence in Y. pseudotuberculosis. To gain further insight into the link between RpoN and T3SS gene expression, we employed different approaches, such as time-course transcriptome profiling, sigma factor overexpression, binding site point mutation and protein secretion analyses. Our findings suggest that the RpoN-mediated effect on T3SS gene expression is multifactorial with sigma factor cross-talk involving effects on transcription of the yscNU operon.