Project description:Longitudinal analysis of Salmonella typhimurium mRNA from superspeader mouse cecal content and stool compared to in vitro Salmonella typhimurium mRNA.
Project description:OmpR is a DNA binding protein belonging to the OmpR/EnvZ two component system. This system is known to sense changes in osmolarity in Escherichia coli. Recently, OmpR in Salmonella enterica serovar Typhimurium was found to be activated by acidic pH and DNA relaxation. In this study, ChIP-on-chip was employed to ascertain the genome-wide distribution of OmpR in Salmonella Typhimurium and Escherichia coli in acidic and neutral pH. In addition we investigated the affect of DNA relaxation on OmpR binding in Salmonella Typhimurium.
Project description:Antimicrobials have been shown to select for changes in biofilm formation and multidrug susceptibility in common human pathogens. We investigated whether common food preservatives selected for these changes in the food pathogen Salmonella enterica serovar Typhimurium. Bacteria were exposed to four food preservatives in either planktonic cultures or biofilms grown on stainless steel beads. Cultures were passaged into fresh media supplemented with the food preservative every 72 hours. Following approximately 1000 generations of continuous preservative exposure, populations were sequenced to determine the single nucleotide polymorphisms that were selected for over evolutionary time.
Project description:Raghunathan2009 - Genome-scale metabolic
network of Salmonella typhimurium (iRR1083)
This model is described in the article:
Constraint-based analysis of
metabolic capacity of Salmonella typhimurium during
host-pathogen interaction.
Raghunathan A, Reed J, Shin S,
Palsson B, Daefler S.
BMC Syst Biol 2009; 3: 38
Abstract:
BACKGROUND: Infections with Salmonella cause significant
morbidity and mortality worldwide. Replication of Salmonella
typhimurium inside its host cell is a model system for studying
the pathogenesis of intracellular bacterial infections.
Genome-scale modeling of bacterial metabolic networks provides
a powerful tool to identify and analyze pathways required for
successful intracellular replication during host-pathogen
interaction. RESULTS: We have developed and validated a
genome-scale metabolic network of Salmonella typhimurium LT2
(iRR1083). This model accounts for 1,083 genes that encode
proteins catalyzing 1,087 unique metabolic and transport
reactions in the bacterium. We employed flux balance analysis
and in silico gene essentiality analysis to investigate growth
under a wide range of conditions that mimic in vitro and host
cell environments. Gene expression profiling of S. typhimurium
isolated from macrophage cell lines was used to constrain the
model to predict metabolic pathways that are likely to be
operational during infection. CONCLUSION: Our analysis suggests
that there is a robust minimal set of metabolic pathways that
is required for successful replication of Salmonella inside the
host cell. This model also serves as platform for the
integration of high-throughput data. Its computational power
allows identification of networked metabolic pathways and
generation of hypotheses about metabolism during infection,
which might be used for the rational design of novel
antibiotics or vaccine strains.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180058.
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To the extent possible under law, all copyright and related or
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Project description:RNA from in vitro grown Salmonella typhimurium is compared with RNA extracted from Salmonella typhimurium from infected chick caecums using a common DNA reference. Keywords: Disease state analysis, infected versus uninfected, common reference
Project description:HilD is a regulator of Salmonella pathogenicity island 1 (SPI-1) virulence genes in Salmonella enterica serovar Typhimurium. To identify novel HilD-regulated genes, we mapped the genome-wide association of HilD in S. Typhimurium under SPI-1-inducing conditions (high salt, low aeration) using ChIP-seq. HilD was C-terminally tagged with 3 FLAG tags in strain 14028s.
Project description:Purpose: The goals of this study are to compare hnRNP M shRNA knockdown macrophages to scramble shRNA control macrophages in uninfected cells and Salmonella Typhimurium-infecetd cells to unbiasly look at gene expression changes that are regulated by the splicing factor, hnRNP M during resting state and during an innate immune response. Methods: Macrophage mRNA profiles of uninfected and Salmonella Typhimurium-infected hnRNP M knockdown cells lines and SCR shRNA control RAW264.7 macrophages were generated by sequencing, in triplicate, using Illumina 1.9 system. The sequence reads that passed quality filters were analyzed at the gene expression level with CLC Genomics Workbench 8 with Transcriptomeics Analysis followed by statistical analysi with Empiciral Analysis of DGE and (EDGE test) and Baggerly's test. qRT–PCR validation was performed using SYBR Green assays. Results: Using CLC Genomics Workbench 8 transcriptomics workflow, we mapped about 30 million sequence reads per sample to the mouse genome (GRCm38). Approximately 140 transcripts showed differential expression between the scramble control and hnRNP M knockdown macrophages in uninfected cells, with a fold change ≥1.5 and p value <0.05. Additionally, ~150 transcripts showed differential expression between the scramble control and hnRNP M knockdown macrophages in Salmonella-Typhimurium cells, with a fold change ≥1.5 and p value <0.05. Altered expression of genes was confirmed with qRT–PCR, demonstrating the effectiveness of the RNA-seq method. Conclusions: Our study demonstrates hnRNP M-dependent differential gene expression in the context of the innate immune response.
Project description:ChIP-on-chip analysis of RNAP and RpoD binding to the Salmonella enterica serovar Typhimurium chromosome demonstrated a high degree of overlap between RNAP and RpoD binding and provided us with important insights into the global distribution of these factors. Furthermore this data was correlated with information on the location of 1873 transcription start sites identified by RNA-Seq technology, thereby providing a detailed transcriptional map of Salmonella Typhimurium.