Biology subjects

Mahmud, A. K. M. F.

Publications and source records attributed to Mahmud, A. K. M. F..

4 recordsLinked to original sources

bioRxiv2022

A core transcriptional response for biofilm formation by Y. pseudotuberculosis

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 upreg-ulated 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 up-regulated 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.

microbiology↗

bioRxiv2022

RpoN is required for a functional type III secretion system in Yersinia pseudotuberculosis

Pathogenic bacteria use a broad range of virulence factors to thrive within their host. Yersinia pseudotuberculosis, a gram-negative enteropathogen in humans, utilises a Type III secretion system to overcome the hosts innate immune response. A global regulator previously shown to be essential for virulence in Y. pseudotuberculosis is RpoN. We show here that a strain lacking RpoN has a severely reduced capacity to secrete Yop effectors. This strain has a substantially reduced expression of genes encoding structural components of the secretion apparatus, the ysc operons, while expression of genes encoding effectors and translocators is less affected. We show that RpoN regulates a complex network, where one part is suggested to contribute to inducing Type III secretion via the enhancer-binding protein GlrR/RpoN regulon. By analogy, during inducement of Type III secretion, RpoN has a positive effect on expression of the sigma factor RpoE, which also is known to act downstream of GlrR. Interestingly, we found putative RpoE binding sites upstream of the ysc operons, and also a partial rescue of Yop secretion in the rpoN mutant strain by overexpression of RpoE. Our findings suggest that the RpoN-mediated effect on expression of type III genes involves a sigma factor hierarchy, where RpoN via RpoE contributes to inducing Type III secretion.

molecular biology↗

bioRxiv2020

Genome-scale mapping reveals complex regulatory activities of RpoN in Yersinia pseudotuberculosis

RpoN, an alternative sigma factor commonly known as sigma 54, 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 anti-sense strands. Deletion of rpoN had a large impact on gene expression, including down-regulation 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 anti-sense strand commonly reduced expression of genes encoded by the corresponding sense strand. IMPORTANCEThe alternative sigma factor, RpoN ({sigma} 54), which is widely distributed in eubacteria have been implicated to control gene expression of importance for numerous functions including virulence. Proper responses to host environments are crucial for bacteria to establish infection and regulatory mechanisms involved are therefore of high interest for development of future therapeutics. Little is known about the function of RpoN in the intestinal pathogen Y. pseudotuberculosis and we therefore investigated its regulatory role in this pathogen. This regulator was indeed found to be critical for establishment of infection in mice, likely involving its requirement for motility and biofilm formation. The RpoN regulon involved both activating and suppressive effects on gene expression which could be confirmed with mutagenesis of identified binding sites. This is the first of its kind study of RpoN in Y. pseudotuberculosis revealing complex regulation of gene expression involving both productive and silent effects of its binding to DNA providing important information about RpoN regulation in enterobacteria.

microbiology↗

bioRxiv2020

ProkSeq for complete analysis of RNA-seq data from prokaryotes

SummarySince 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, the current tools for assessing gene expression have been designed around the structures of eukaryotic genes. There are a few stand-alone tools designed for prokaryotes, and they require improvement. A well-defined pipeline for prokaryotes that includes all the necessary tools for quality control, 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, and it produces publication-quality figures. Availability and implementationProkSeq is implemented in Python and is published under the ISC open source license. The tool and a detailed user manual are hosted at Docker: https://hub.docker.com/repository/docker/snandids/prokseq-v2.1, Anaconda: https://anaconda.org/snandiDS/prokseq; Github: https://github.com/snandiDS/prokseq.

bioinformatics↗