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Elucidation of sigma factor-associated networks in Pseudomonas aeruginosa reveals a modular architecture with limited and function-specific crosstalk.

Schulz S, Eckweiler D, Bielecka A, Nicolai T, Franke R, Dötsch A, Hornischer K, Bruchmann S, Düvel J, Häussler S - PLoS Pathog. (2015)

Bottom Line: They provide effective mechanisms for simultaneously regulating expression of large numbers of genes in response to challenging conditions, and their presence has been linked to bacterial virulence and pathogenicity.We furthermore elucidated the de novo binding motif of each sigma factor, and validated the RNA- and ChIP-seq results by global motif searches in the proximity of transcriptional start sites (TSS).Our data indicate that the modular structure of sigma factor networks enables P. aeruginosa to function adequately in its environment and at the same time is exploited to build up higher-level functions by specific interconnections that are dominated by a participation of RpoN.

View Article: PubMed Central - PubMed

Affiliation: Institute for Molecular Bacteriology, TWINCORE GmbH, Center for Clinical and Experimental Infection Research, a joint venture of the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany; Department of Molecular Bacteriology, Helmholtz Centre for Infection Research, Braunschweig, Germany.

ABSTRACT
Sigma factors are essential global regulators of transcription initiation in bacteria which confer promoter recognition specificity to the RNA polymerase core enzyme. They provide effective mechanisms for simultaneously regulating expression of large numbers of genes in response to challenging conditions, and their presence has been linked to bacterial virulence and pathogenicity. In this study, we constructed nine his-tagged sigma factor expressing and/or deletion mutant strains in the opportunistic pathogen Pseudomonas aeruginosa. To uncover the direct and indirect sigma factor regulons, we performed mRNA profiling, as well as chromatin immunoprecipitation coupled to high-throughput sequencing. We furthermore elucidated the de novo binding motif of each sigma factor, and validated the RNA- and ChIP-seq results by global motif searches in the proximity of transcriptional start sites (TSS). Our integrated approach revealed a highly modular network architecture which is composed of insulated functional sigma factor modules. Analysis of the interconnectivity of the various sigma factor networks uncovered a limited, but highly function-specific, crosstalk which orchestrates complex cellular processes. Our data indicate that the modular structure of sigma factor networks enables P. aeruginosa to function adequately in its environment and at the same time is exploited to build up higher-level functions by specific interconnections that are dominated by a participation of RpoN.

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Conserved and diverged co-expression patterns of differentially regulated genes upon (hyper-) presence and/or absence of sigma factors.(A) Hierarchical clustering based on Pearson correlation coefficients. 1504 genes (67.8%, vertically colored) were differentially regulated due to in trans expression and/or inactivation of a single sigma factor. Genes regulated by more than one sigma factor are shown in white. (B) The expression levels of 471 genes (21.2%) were influenced by two sigma factors (indicated by the two colored bars). (C) White balls highlight the (the number of) genes that are affected by the five most frequent sigma factor combinations.
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ppat.1004744.g001: Conserved and diverged co-expression patterns of differentially regulated genes upon (hyper-) presence and/or absence of sigma factors.(A) Hierarchical clustering based on Pearson correlation coefficients. 1504 genes (67.8%, vertically colored) were differentially regulated due to in trans expression and/or inactivation of a single sigma factor. Genes regulated by more than one sigma factor are shown in white. (B) The expression levels of 471 genes (21.2%) were influenced by two sigma factors (indicated by the two colored bars). (C) White balls highlight the (the number of) genes that are affected by the five most frequent sigma factor combinations.

Mentions: Overall, 491 genes were up-regulated in response to (hyper-) presence and down-regulated in the absence of at least one alternative sigma factor (Fig. 1A). Additional 1195 genes were up-regulated in response to (hyper-) presence and 532 were down-regulated in the absence of at least one alternative sigma factor. Interestingly, the majority of 1504 out of the overall 2218 genes (67.8%) were differentially regulated due to in trans expression and/or inactivation of only one single sigma factor (colored bars in Fig. 1A). The finding that many genes are exclusively affected by only one alternative sigma factor indicates that the alternative sigma factor regulons are distinct functional modules and that they have only a limited overlap at the level of transcription. Nevertheless, there was also shared regulation: the expression level of 471/2218 genes (21.2%) was influenced by two sigma factors (white bars in Fig. 1A, colored bars in Fig. 1B) and 243/2218 genes (11%) were influenced by more than two sigma factors (S2 and S3 Table). Thus, in addition to the detection of largely isolated regulons (Fig. 1A), transcriptional profiling also uncovered a co-ordinated gene expression pattern in which many genes were affected by distinct sets of alternative sigma factors (Fig. 1B and C and Table 1).


Elucidation of sigma factor-associated networks in Pseudomonas aeruginosa reveals a modular architecture with limited and function-specific crosstalk.

Schulz S, Eckweiler D, Bielecka A, Nicolai T, Franke R, Dötsch A, Hornischer K, Bruchmann S, Düvel J, Häussler S - PLoS Pathog. (2015)

Conserved and diverged co-expression patterns of differentially regulated genes upon (hyper-) presence and/or absence of sigma factors.(A) Hierarchical clustering based on Pearson correlation coefficients. 1504 genes (67.8%, vertically colored) were differentially regulated due to in trans expression and/or inactivation of a single sigma factor. Genes regulated by more than one sigma factor are shown in white. (B) The expression levels of 471 genes (21.2%) were influenced by two sigma factors (indicated by the two colored bars). (C) White balls highlight the (the number of) genes that are affected by the five most frequent sigma factor combinations.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4362757&req=5

ppat.1004744.g001: Conserved and diverged co-expression patterns of differentially regulated genes upon (hyper-) presence and/or absence of sigma factors.(A) Hierarchical clustering based on Pearson correlation coefficients. 1504 genes (67.8%, vertically colored) were differentially regulated due to in trans expression and/or inactivation of a single sigma factor. Genes regulated by more than one sigma factor are shown in white. (B) The expression levels of 471 genes (21.2%) were influenced by two sigma factors (indicated by the two colored bars). (C) White balls highlight the (the number of) genes that are affected by the five most frequent sigma factor combinations.
Mentions: Overall, 491 genes were up-regulated in response to (hyper-) presence and down-regulated in the absence of at least one alternative sigma factor (Fig. 1A). Additional 1195 genes were up-regulated in response to (hyper-) presence and 532 were down-regulated in the absence of at least one alternative sigma factor. Interestingly, the majority of 1504 out of the overall 2218 genes (67.8%) were differentially regulated due to in trans expression and/or inactivation of only one single sigma factor (colored bars in Fig. 1A). The finding that many genes are exclusively affected by only one alternative sigma factor indicates that the alternative sigma factor regulons are distinct functional modules and that they have only a limited overlap at the level of transcription. Nevertheless, there was also shared regulation: the expression level of 471/2218 genes (21.2%) was influenced by two sigma factors (white bars in Fig. 1A, colored bars in Fig. 1B) and 243/2218 genes (11%) were influenced by more than two sigma factors (S2 and S3 Table). Thus, in addition to the detection of largely isolated regulons (Fig. 1A), transcriptional profiling also uncovered a co-ordinated gene expression pattern in which many genes were affected by distinct sets of alternative sigma factors (Fig. 1B and C and Table 1).

Bottom Line: They provide effective mechanisms for simultaneously regulating expression of large numbers of genes in response to challenging conditions, and their presence has been linked to bacterial virulence and pathogenicity.We furthermore elucidated the de novo binding motif of each sigma factor, and validated the RNA- and ChIP-seq results by global motif searches in the proximity of transcriptional start sites (TSS).Our data indicate that the modular structure of sigma factor networks enables P. aeruginosa to function adequately in its environment and at the same time is exploited to build up higher-level functions by specific interconnections that are dominated by a participation of RpoN.

View Article: PubMed Central - PubMed

Affiliation: Institute for Molecular Bacteriology, TWINCORE GmbH, Center for Clinical and Experimental Infection Research, a joint venture of the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany; Department of Molecular Bacteriology, Helmholtz Centre for Infection Research, Braunschweig, Germany.

ABSTRACT
Sigma factors are essential global regulators of transcription initiation in bacteria which confer promoter recognition specificity to the RNA polymerase core enzyme. They provide effective mechanisms for simultaneously regulating expression of large numbers of genes in response to challenging conditions, and their presence has been linked to bacterial virulence and pathogenicity. In this study, we constructed nine his-tagged sigma factor expressing and/or deletion mutant strains in the opportunistic pathogen Pseudomonas aeruginosa. To uncover the direct and indirect sigma factor regulons, we performed mRNA profiling, as well as chromatin immunoprecipitation coupled to high-throughput sequencing. We furthermore elucidated the de novo binding motif of each sigma factor, and validated the RNA- and ChIP-seq results by global motif searches in the proximity of transcriptional start sites (TSS). Our integrated approach revealed a highly modular network architecture which is composed of insulated functional sigma factor modules. Analysis of the interconnectivity of the various sigma factor networks uncovered a limited, but highly function-specific, crosstalk which orchestrates complex cellular processes. Our data indicate that the modular structure of sigma factor networks enables P. aeruginosa to function adequately in its environment and at the same time is exploited to build up higher-level functions by specific interconnections that are dominated by a participation of RpoN.

Show MeSH
Related in: MedlinePlus