Project description:Bacterial transcription networks typically consist of hundreds of transcription factors and thousands of promoters. However, current attempts to map bacterial promoters have failed to report the true complexity of bacterial transcription. The differential RNA-seq (dRNA-seq) approaches only identified a subset of promoters because they involved few growth conditions. Here, we present a simplified approach for global promoter identification in bacteria, based upon the analysis of RNA-seq data from multiple environmental conditions. RNA was extracted from Salmonella enterica serovar Typhimurium (S. Typhimurium) grown in 22 different environmental conditions, which were devised to reflect the pathogenic lifestyle of S. Typhimurium. Individual RNA samples were combined into two pools for sequencing. In just two runs of strand-specific RNA-seq and dRNA-seq of the pooled sample we identified 3701 promoters (Pool sample). In further experiments, we found that individual in vitro conditions stimulate the expression of about 60% of the S. Typhimurium genome, whereas the suite of 22 conditions induced expression of 87% of S. Typhimurium genes. We discovered environmental conditions that induce many genes within Salmonella pathogenicity islands and identified 78 new sRNAs. In S. Typhimurium there is now experimental evidence for 280 sRNAs, and we classified them in terms of location and Hfq-binding.
Project description:Bacterial transcription networks typically consist of hundreds of transcription factors and thousands of promoters. However, current attempts to map bacterial promoters have failed to report the true complexity of bacterial transcription. The differential RNA-seq (dRNA-seq) approaches only identified a subset of promoters because they involved few growth conditions. Here, we present a simplified approach for global promoter identification in bacteria, based upon the analysis of RNA-seq data from multiple environmental conditions. RNA was extracted from Salmonella enterica serovar Typhimurium (S. Typhimurium) grown in 22 different environmental conditions, which were devised to reflect the pathogenic lifestyle of S. Typhimurium. Individual RNA samples were combined into two pools for sequencing. In just two runs of strand-specific RNA-seq and dRNA-seq of the pooled sample we identified 3701 promoters (Pool sample). In further experiments, we found that individual in vitro conditions stimulate the expression of about 60% of the S. Typhimurium genome, whereas the suite of 22 conditions induced expression of 87% of S. Typhimurium genes. We discovered environmental conditions that induce many genes within Salmonella pathogenicity islands and identified 78 new sRNAs. In S. Typhimurium there is now experimental evidence for 280 sRNAs, and we classified them in terms of location and Hfq-binding. Transcriptome analysis of S. Typhimurium 4/74 using RNA from 22 different conditions using RNA-seq. Also, RNA from each condition was pooled into one sample (RNA Pool). Differential RNA-seq (dRNA-seq) was performed for 5 of the samples from the 22 environmental conditions.
Project description:Cell to cell communication in bacteria to regulate various cellular processes with respect to their population density is termed quorum sensing and is achieved using signaling molecules called autoinducers. LuxS, which is involved in the synthesis of the autoinducer molecule-2 (AI-2), is conserved in several Gram-positive and Gram-negative bacteria including the enteric pathogen Salmonella Typhimurium. Genes that are regulated by luxS in S. Typhimurium were identified using microarrays and RNA samples from wild type S. Typhimurium and its isogenic luxS mutant, in two growth conditions (presence and absence of glucose), and at two different time points (mid-log and early-stationary phases). Minimal differential gene expression was observed in the presence of glucose. In the absence of both luxS and glucose, a total of 1560 genes were differentially expressed and 1361 genes were identified as luxS/AI-2-regulated at the mid-log phase and 199 genes at the early-stationary phase. Quantitative real-time PCR was performed on selected genes to validate the microarray results. These results suggest that although the expression of the luxS gene in S. Typhimurium is independent of the growth condition, its role in the production of AI-2 depends on the growth condition. It was found that luxS/AI-2 plays a vital role in a variety of processes such as metabolism, virulence gene expression, motility, transcription and translation. Keywords: Salmonella Typhimurium, quorum sensing, luxS mutant, autoinducer-2
Project description:Investigation of whole genome gene expression level changes in a Salmonella enterica serovar Typhimurium UK1 delta-iacP mutant, compared to the wild-type strain. IacP is resoponsible for the secretion of virulence effector proteins via the type III secretion system, thereby contributing the virulence of S. Typhimurium. The mutants analyzed in this study are further described in Kim et al. 2011. Role of Salmonella Pathogenicity Island 1 Protein IacP in Salmonella enterica Serovar Typhimurium Pathogenesis. Infection and Immunity 79(4):1440-1450 (PMID 21263021).
Project description:FabR ChIP-chip on Salmonella enterica subsp. enterica serovar Typhimurium SL1344 using anti-Myc antibody against strain with chromosomally 9Myc-tagged FabR (IP samples) and wildtype strain (mock IP samples)
Project description:New tools for studying bacterial transcripts at the single nucleotide level offer an unparalleled opportunity to understand the bacterial transcriptome. For the model pathogen Salmonella enterica serovar Typhimurium, it is necessary to identify the regulatory inputs for all RNA transcripts, including small RNAs (sRNAs) and coding genes. Here, we use RNA-seq to define the transcriptomes of mutants lacking 18 global regulatory systems that, among other functions, modulate the expression of the SPI1 and SPI2 Type Three secretion systems in S. Typhimurium strain 4/74. We directly compared the roles of the major regulators of transcription, and reported the effects of the regulatory mutations on expression of sRNAs. We also use this method to describe the impact of the RNA chaperone Hfq upon the steady state levels of 280 sRNA transcripts.