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Reconstruction of the core and extended regulons of global transcription factors.

Dufour YS, Kiley PJ, Donohue TJ - PLoS Genet. (2010)

Bottom Line: Our results show that this approach correctly predicted many regulon members, provided new insights into the biological functions of the respective regulons for these regulators, and suggested models for the evolution of the corresponding transcriptional networks.In addition, the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species, possibly reflecting species-specific adaptation to environmental and other factors.The comparative genomics approach we developed is readily applicable to other regulatory networks.

View Article: PubMed Central - PubMed

Affiliation: Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

ABSTRACT
The processes underlying the evolution of regulatory networks are unclear. To address this question, we used a comparative genomics approach that takes advantage of the large number of sequenced bacterial genomes to predict conserved and variable members of transcriptional regulatory networks across phylogenetically related organisms. Specifically, we developed a computational method to predict the conserved regulons of transcription factors across alpha-proteobacteria. We focused on the CRP/FNR super-family of transcription factors because it contains several well-characterized members, such as FNR, FixK, and DNR. While FNR, FixK, and DNR are each proposed to regulate different aspects of anaerobic metabolism, they are predicted to recognize very similar DNA target sequences, and they occur in various combinations among individual alpha-proteobacterial species. In this study, the composition of the respective FNR, FixK, or DNR conserved regulons across 87 alpha-proteobacterial species was predicted by comparing the phylogenetic profiles of the regulators with the profiles of putative target genes. The utility of our predictions was evaluated by experimentally characterizing the FnrL regulon (a FNR-type regulator) in the alpha-proteobacterium Rhodobacter sphaeroides. Our results show that this approach correctly predicted many regulon members, provided new insights into the biological functions of the respective regulons for these regulators, and suggested models for the evolution of the corresponding transcriptional networks. Our findings also predict that, at least for the FNR-type regulators, there is a core set of target genes conserved across many species. In addition, the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species, possibly reflecting species-specific adaptation to environmental and other factors. The comparative genomics approach we developed is readily applicable to other regulatory networks.

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Transcription profile heatmap of members of the FnrL regulon across conditions with varying oxygen tension.The colors represent the relative level of mRNA abundance compared to the mean level of expression for each locus (yellow = high expression, red = low expression). Genes are identified by their locus ID and gene names. Vertical lines next to the locus IDs denote predicted transcription units. Asterisks denote transcription units that had no FnrL ChIP–chip peak detected within their promoter regions but had a sequence matching the FnrL binding site consensus. The amount of oxygen or light in the experimental conditions are indicated below the plot (Photo10 and Photo100 represent illumination of the cultures at 10W/m2 and 100W/m2, respectively). Genes were grouped according to their expression profiles. Group A contains genes whose expression levels negatively correlate with oxygen tension. Group B contains genes whose expression levels also negatively correlate with oxygen tension but with the exception that these genes have relatively low expression under low light conditions (Photo10). Group C contains genes whose expression levels positively correlate with oxygen tension.
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pgen-1001027-g006: Transcription profile heatmap of members of the FnrL regulon across conditions with varying oxygen tension.The colors represent the relative level of mRNA abundance compared to the mean level of expression for each locus (yellow = high expression, red = low expression). Genes are identified by their locus ID and gene names. Vertical lines next to the locus IDs denote predicted transcription units. Asterisks denote transcription units that had no FnrL ChIP–chip peak detected within their promoter regions but had a sequence matching the FnrL binding site consensus. The amount of oxygen or light in the experimental conditions are indicated below the plot (Photo10 and Photo100 represent illumination of the cultures at 10W/m2 and 100W/m2, respectively). Genes were grouped according to their expression profiles. Group A contains genes whose expression levels negatively correlate with oxygen tension. Group B contains genes whose expression levels also negatively correlate with oxygen tension but with the exception that these genes have relatively low expression under low light conditions (Photo10). Group C contains genes whose expression levels positively correlate with oxygen tension.

Mentions: To identify FnrL regulated transcription units, genes within 500 bp on either side of the 37 potential FnrL target sites (27 sites identified by ChIP-chip and the 10 putative FnrL binding sites identified by sequence analysis) were collected and analyzed for O2-dependent changes in transcript abundance using publically available global gene expression data from R. sphaeroides [14]–[16], [35]. When the transcript abundance profiles were clustered by similarity (Pearson correlation coefficient), the RNA transcript levels of 68 putative FnrL target genes showed O2-dependent expression patterns (Figure 6).


Reconstruction of the core and extended regulons of global transcription factors.

Dufour YS, Kiley PJ, Donohue TJ - PLoS Genet. (2010)

Transcription profile heatmap of members of the FnrL regulon across conditions with varying oxygen tension.The colors represent the relative level of mRNA abundance compared to the mean level of expression for each locus (yellow = high expression, red = low expression). Genes are identified by their locus ID and gene names. Vertical lines next to the locus IDs denote predicted transcription units. Asterisks denote transcription units that had no FnrL ChIP–chip peak detected within their promoter regions but had a sequence matching the FnrL binding site consensus. The amount of oxygen or light in the experimental conditions are indicated below the plot (Photo10 and Photo100 represent illumination of the cultures at 10W/m2 and 100W/m2, respectively). Genes were grouped according to their expression profiles. Group A contains genes whose expression levels negatively correlate with oxygen tension. Group B contains genes whose expression levels also negatively correlate with oxygen tension but with the exception that these genes have relatively low expression under low light conditions (Photo10). Group C contains genes whose expression levels positively correlate with oxygen tension.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2908626&req=5

pgen-1001027-g006: Transcription profile heatmap of members of the FnrL regulon across conditions with varying oxygen tension.The colors represent the relative level of mRNA abundance compared to the mean level of expression for each locus (yellow = high expression, red = low expression). Genes are identified by their locus ID and gene names. Vertical lines next to the locus IDs denote predicted transcription units. Asterisks denote transcription units that had no FnrL ChIP–chip peak detected within their promoter regions but had a sequence matching the FnrL binding site consensus. The amount of oxygen or light in the experimental conditions are indicated below the plot (Photo10 and Photo100 represent illumination of the cultures at 10W/m2 and 100W/m2, respectively). Genes were grouped according to their expression profiles. Group A contains genes whose expression levels negatively correlate with oxygen tension. Group B contains genes whose expression levels also negatively correlate with oxygen tension but with the exception that these genes have relatively low expression under low light conditions (Photo10). Group C contains genes whose expression levels positively correlate with oxygen tension.
Mentions: To identify FnrL regulated transcription units, genes within 500 bp on either side of the 37 potential FnrL target sites (27 sites identified by ChIP-chip and the 10 putative FnrL binding sites identified by sequence analysis) were collected and analyzed for O2-dependent changes in transcript abundance using publically available global gene expression data from R. sphaeroides [14]–[16], [35]. When the transcript abundance profiles were clustered by similarity (Pearson correlation coefficient), the RNA transcript levels of 68 putative FnrL target genes showed O2-dependent expression patterns (Figure 6).

Bottom Line: Our results show that this approach correctly predicted many regulon members, provided new insights into the biological functions of the respective regulons for these regulators, and suggested models for the evolution of the corresponding transcriptional networks.In addition, the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species, possibly reflecting species-specific adaptation to environmental and other factors.The comparative genomics approach we developed is readily applicable to other regulatory networks.

View Article: PubMed Central - PubMed

Affiliation: Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

ABSTRACT
The processes underlying the evolution of regulatory networks are unclear. To address this question, we used a comparative genomics approach that takes advantage of the large number of sequenced bacterial genomes to predict conserved and variable members of transcriptional regulatory networks across phylogenetically related organisms. Specifically, we developed a computational method to predict the conserved regulons of transcription factors across alpha-proteobacteria. We focused on the CRP/FNR super-family of transcription factors because it contains several well-characterized members, such as FNR, FixK, and DNR. While FNR, FixK, and DNR are each proposed to regulate different aspects of anaerobic metabolism, they are predicted to recognize very similar DNA target sequences, and they occur in various combinations among individual alpha-proteobacterial species. In this study, the composition of the respective FNR, FixK, or DNR conserved regulons across 87 alpha-proteobacterial species was predicted by comparing the phylogenetic profiles of the regulators with the profiles of putative target genes. The utility of our predictions was evaluated by experimentally characterizing the FnrL regulon (a FNR-type regulator) in the alpha-proteobacterium Rhodobacter sphaeroides. Our results show that this approach correctly predicted many regulon members, provided new insights into the biological functions of the respective regulons for these regulators, and suggested models for the evolution of the corresponding transcriptional networks. Our findings also predict that, at least for the FNR-type regulators, there is a core set of target genes conserved across many species. In addition, the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species, possibly reflecting species-specific adaptation to environmental and other factors. The comparative genomics approach we developed is readily applicable to other regulatory networks.

Show MeSH
Related in: MedlinePlus