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Identification of the regulatory logic controlling Salmonella pathoadaptation by the SsrA-SsrB two-component system.

Tomljenovic-Berube AM, Mulder DT, Whiteside MD, Brinkman FS, Coombes BK - PLoS Genet. (2010)

Bottom Line: To survive in the host environment, Salmonella enterica uses a type III secretion system and effector proteins, which are activated by the SsrA-SsrB two-component system in response to the host environment.Mutational analysis of a representative promoter validated this palindrome as the minimal architecture needed for regulatory input by SsrB.These data provide a high-resolution map of a regulatory network and the underlying logic enabling pathogen adaptation to a host.

View Article: PubMed Central - PubMed

Affiliation: Michael G. DeGroote Institute for Infectious Disease Research and the Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Canada.

ABSTRACT
Sequence data from the past decade has laid bare the significance of horizontal gene transfer in creating genetic diversity in the bacterial world. Regulatory evolution, in which non-coding DNA is mutated to create new regulatory nodes, also contributes to this diversity to allow niche adaptation and the evolution of pathogenesis. To survive in the host environment, Salmonella enterica uses a type III secretion system and effector proteins, which are activated by the SsrA-SsrB two-component system in response to the host environment. To better understand the phenomenon of regulatory evolution in S. enterica, we defined the SsrB regulon and asked how this transcription factor interacts with the cis-regulatory region of target genes. Using ChIP-on-chip, cDNA hybridization, and comparative genomics analyses, we describe the SsrB-dependent regulon of ancestral and horizontally acquired genes. Further, we used a genetic screen and computational analyses integrating experimental data from S. enterica and sequence data from an orthologous regulatory system in the insect endosymbiont, Sodalis glossinidius, to identify the conserved yet flexible palindrome sequence that defines DNA recognition by SsrB. Mutational analysis of a representative promoter validated this palindrome as the minimal architecture needed for regulatory input by SsrB. These data provide a high-resolution map of a regulatory network and the underlying logic enabling pathogen adaptation to a host.

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Genome-wide functional genomics analyses for SsrB.(A) ChIP-on-chip and microarray analysis. Genomic islands are indicated and labelled on track 1 (outermost circle), where prophages are in green, pathogenicity islands are in red and regions of difference (ROD) with S. bongori are in blue. ChIP-on-chip interaction scores (log2) for SsrB-activating conditions are plotted on track 2, where peaks with signals greater than one standard deviation from the mean probe signal are indicated in blue. Transcriptional profiling analysis of SsrB-regulated genes is plotted on track 3. Genes repressed more than 5-fold in an ssrB mutant are indicated in green. G+C content is plotted on track 4, where values greater than 53% (genome mean) are indicated in red and less than 53% are indicated in green. (B) Summary of gene expression data and SsrB binding data for pathogenicity islands, prophage islands, S. bongori ROD and genome sequence not in islands. The number of SsrB binding peaks identified by ChIP-on-chip for each of the individual islands is shown in the outermost track, along with the number of genes down-regulated in the transcriptional profiling analysis (in brackets). The total number of ChIP-on-chip interaction peaks and genes regulated by SsrB are shown in the innermost circles along with the percent of total (in brackets). The total genomic content of each island or conserved regions are shown below each circle, along with the percent of total genome. The remainder of microarray data (not in islands) includes 194 interaction peaks (75.8%) for ChIP-on-chip and 77 genes (58.0%) for transcriptional profiling arrays.
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pgen-1000875-g002: Genome-wide functional genomics analyses for SsrB.(A) ChIP-on-chip and microarray analysis. Genomic islands are indicated and labelled on track 1 (outermost circle), where prophages are in green, pathogenicity islands are in red and regions of difference (ROD) with S. bongori are in blue. ChIP-on-chip interaction scores (log2) for SsrB-activating conditions are plotted on track 2, where peaks with signals greater than one standard deviation from the mean probe signal are indicated in blue. Transcriptional profiling analysis of SsrB-regulated genes is plotted on track 3. Genes repressed more than 5-fold in an ssrB mutant are indicated in green. G+C content is plotted on track 4, where values greater than 53% (genome mean) are indicated in red and less than 53% are indicated in green. (B) Summary of gene expression data and SsrB binding data for pathogenicity islands, prophage islands, S. bongori ROD and genome sequence not in islands. The number of SsrB binding peaks identified by ChIP-on-chip for each of the individual islands is shown in the outermost track, along with the number of genes down-regulated in the transcriptional profiling analysis (in brackets). The total number of ChIP-on-chip interaction peaks and genes regulated by SsrB are shown in the innermost circles along with the percent of total (in brackets). The total genomic content of each island or conserved regions are shown below each circle, along with the percent of total genome. The remainder of microarray data (not in islands) includes 194 interaction peaks (75.8%) for ChIP-on-chip and 77 genes (58.0%) for transcriptional profiling arrays.

Mentions: To examine SsrB allocation on the chromosome in vivo, we isolated functional SsrB-DNA interactions using chromatin immunoprecipitation and examined the bound DNA by chip analysis (ChIP-on-chip) using an S. Typhimurium SL1344 array containing 44,021 probes. With this method, we identified 256 significant interaction peaks distributed throughout the genome that were enriched under SsrB-activating conditions and with interaction scores three standard deviations greater than the mean probe score (Figure 2A and Table 1). Of these 256 peaks, 126 (49%) occurred within coding regions of genes (CDS) and 130 (51%) were in intergenic regions (IGR). Given the strong influence of SsrB on horizontally acquired genes (Table 1), we plotted the ChIP-on-chip data against all genomic islands in S. Typhimurium SL1344. From this analysis, 62 of 256 SsrB binding peaks (24.3%) occurred within genomic islands (Figure 2B).


Identification of the regulatory logic controlling Salmonella pathoadaptation by the SsrA-SsrB two-component system.

Tomljenovic-Berube AM, Mulder DT, Whiteside MD, Brinkman FS, Coombes BK - PLoS Genet. (2010)

Genome-wide functional genomics analyses for SsrB.(A) ChIP-on-chip and microarray analysis. Genomic islands are indicated and labelled on track 1 (outermost circle), where prophages are in green, pathogenicity islands are in red and regions of difference (ROD) with S. bongori are in blue. ChIP-on-chip interaction scores (log2) for SsrB-activating conditions are plotted on track 2, where peaks with signals greater than one standard deviation from the mean probe signal are indicated in blue. Transcriptional profiling analysis of SsrB-regulated genes is plotted on track 3. Genes repressed more than 5-fold in an ssrB mutant are indicated in green. G+C content is plotted on track 4, where values greater than 53% (genome mean) are indicated in red and less than 53% are indicated in green. (B) Summary of gene expression data and SsrB binding data for pathogenicity islands, prophage islands, S. bongori ROD and genome sequence not in islands. The number of SsrB binding peaks identified by ChIP-on-chip for each of the individual islands is shown in the outermost track, along with the number of genes down-regulated in the transcriptional profiling analysis (in brackets). The total number of ChIP-on-chip interaction peaks and genes regulated by SsrB are shown in the innermost circles along with the percent of total (in brackets). The total genomic content of each island or conserved regions are shown below each circle, along with the percent of total genome. The remainder of microarray data (not in islands) includes 194 interaction peaks (75.8%) for ChIP-on-chip and 77 genes (58.0%) for transcriptional profiling arrays.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2837388&req=5

pgen-1000875-g002: Genome-wide functional genomics analyses for SsrB.(A) ChIP-on-chip and microarray analysis. Genomic islands are indicated and labelled on track 1 (outermost circle), where prophages are in green, pathogenicity islands are in red and regions of difference (ROD) with S. bongori are in blue. ChIP-on-chip interaction scores (log2) for SsrB-activating conditions are plotted on track 2, where peaks with signals greater than one standard deviation from the mean probe signal are indicated in blue. Transcriptional profiling analysis of SsrB-regulated genes is plotted on track 3. Genes repressed more than 5-fold in an ssrB mutant are indicated in green. G+C content is plotted on track 4, where values greater than 53% (genome mean) are indicated in red and less than 53% are indicated in green. (B) Summary of gene expression data and SsrB binding data for pathogenicity islands, prophage islands, S. bongori ROD and genome sequence not in islands. The number of SsrB binding peaks identified by ChIP-on-chip for each of the individual islands is shown in the outermost track, along with the number of genes down-regulated in the transcriptional profiling analysis (in brackets). The total number of ChIP-on-chip interaction peaks and genes regulated by SsrB are shown in the innermost circles along with the percent of total (in brackets). The total genomic content of each island or conserved regions are shown below each circle, along with the percent of total genome. The remainder of microarray data (not in islands) includes 194 interaction peaks (75.8%) for ChIP-on-chip and 77 genes (58.0%) for transcriptional profiling arrays.
Mentions: To examine SsrB allocation on the chromosome in vivo, we isolated functional SsrB-DNA interactions using chromatin immunoprecipitation and examined the bound DNA by chip analysis (ChIP-on-chip) using an S. Typhimurium SL1344 array containing 44,021 probes. With this method, we identified 256 significant interaction peaks distributed throughout the genome that were enriched under SsrB-activating conditions and with interaction scores three standard deviations greater than the mean probe score (Figure 2A and Table 1). Of these 256 peaks, 126 (49%) occurred within coding regions of genes (CDS) and 130 (51%) were in intergenic regions (IGR). Given the strong influence of SsrB on horizontally acquired genes (Table 1), we plotted the ChIP-on-chip data against all genomic islands in S. Typhimurium SL1344. From this analysis, 62 of 256 SsrB binding peaks (24.3%) occurred within genomic islands (Figure 2B).

Bottom Line: To survive in the host environment, Salmonella enterica uses a type III secretion system and effector proteins, which are activated by the SsrA-SsrB two-component system in response to the host environment.Mutational analysis of a representative promoter validated this palindrome as the minimal architecture needed for regulatory input by SsrB.These data provide a high-resolution map of a regulatory network and the underlying logic enabling pathogen adaptation to a host.

View Article: PubMed Central - PubMed

Affiliation: Michael G. DeGroote Institute for Infectious Disease Research and the Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Canada.

ABSTRACT
Sequence data from the past decade has laid bare the significance of horizontal gene transfer in creating genetic diversity in the bacterial world. Regulatory evolution, in which non-coding DNA is mutated to create new regulatory nodes, also contributes to this diversity to allow niche adaptation and the evolution of pathogenesis. To survive in the host environment, Salmonella enterica uses a type III secretion system and effector proteins, which are activated by the SsrA-SsrB two-component system in response to the host environment. To better understand the phenomenon of regulatory evolution in S. enterica, we defined the SsrB regulon and asked how this transcription factor interacts with the cis-regulatory region of target genes. Using ChIP-on-chip, cDNA hybridization, and comparative genomics analyses, we describe the SsrB-dependent regulon of ancestral and horizontally acquired genes. Further, we used a genetic screen and computational analyses integrating experimental data from S. enterica and sequence data from an orthologous regulatory system in the insect endosymbiont, Sodalis glossinidius, to identify the conserved yet flexible palindrome sequence that defines DNA recognition by SsrB. Mutational analysis of a representative promoter validated this palindrome as the minimal architecture needed for regulatory input by SsrB. These data provide a high-resolution map of a regulatory network and the underlying logic enabling pathogen adaptation to a host.

Show MeSH
Related in: MedlinePlus