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. 2013 Sep 2;14:597.
doi: 10.1186/1471-2164-14-597.

Comparative Genomics of Metabolic Capacities of Regulons Controlled by Cis-Regulatory RNA Motifs in Bacteria

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Free PMC article

Comparative Genomics of Metabolic Capacities of Regulons Controlled by Cis-Regulatory RNA Motifs in Bacteria

Eric I Sun et al. BMC Genomics. .
Free PMC article

Abstract

Background: In silico comparative genomics approaches have been efficiently used for functional prediction and reconstruction of metabolic and regulatory networks. Riboswitches are metabolite-sensing structures often found in bacterial mRNA leaders controlling gene expression on transcriptional or translational levels.An increasing number of riboswitches and other cis-regulatory RNAs have been recently classified into numerous RNA families in the Rfam database. High conservation of these RNA motifs provides a unique advantage for their genomic identification and comparative analysis.

Results: A comparative genomics approach implemented in the RegPredict tool was used for reconstruction and functional annotation of regulons controlled by RNAs from 43 Rfam families in diverse taxonomic groups of Bacteria. The inferred regulons include ~5200 cis-regulatory RNAs and more than 12000 target genes in 255 microbial genomes. All predicted RNA-regulated genes were classified into specific and overall functional categories. Analysis of taxonomic distribution of these categories allowed us to establish major functional preferences for each analyzed cis-regulatory RNA motif family. Overall, most RNA motif regulons showed predictable functional content in accordance with their experimentally established effector ligands. Our results suggest that some RNA motifs (including thiamin pyrophosphate and cobalamin riboswitches that control the cofactor metabolism) are widespread and likely originated from the last common ancestor of all bacteria. However, many more analyzed RNA motifs are restricted to a narrow taxonomic group of bacteria and likely represent more recent evolutionary innovations.

Conclusions: The reconstructed regulatory networks for major known RNA motifs substantially expand the existing knowledge of transcriptional regulation in bacteria. The inferred regulons can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. The obtained genome-wide collection of reference RNA motif regulons is available in the RegPrecise database (http://regprecise.lbl.gov/).

Figures

Figure 1
Figure 1
Distribution of RNA motifs in 24 taxonomic groups of bacteria. Each bar shows the number of microbial lineages studied that possess at least one predicted RNA motif regulon. Ribosomal and amino acid biosynthesis operon leaders and T-boxes are not shown. The classification codes: (A), widely distributed RNA motifs; (B) moderately distributed RNA motifs; (C) RNA motifs with restricted taxonomic distribution.
Figure 2
Figure 2
Scatter plot of all identified RNA motif-regulated genes versus total number of genes in an individual taxon. Each dot in the figure represents the average value of all the genomes in that taxon.
Figure 3
Figure 3
Functional composition of cobalamin riboswitch regulons across different lineages. Average number of riboswitch regulated genes per genome denotes the overall height of each bar. Colored bar parts show functional regulon composition using SFC categories indicated in the legend. For each taxonomic group, a number in parenthesis represents the number of studied genomes. Phylum / subdivision names are indicated by braces beneath the taxon names.
Figure 4
Figure 4
Functional composition of TPP riboswitch regulons across different lineages. See Figure 3 for figure descriptions.
Figure 5
Figure 5
Functional composition of FMN riboswitch regulons across different lineages. See Figure 3 for figure descriptions
Figure 6
Figure 6
Functional composition of glycine riboswitch regulons across different lineages. See Figure 3 for figure descriptions.
Figure 7
Figure 7
Proportion of overall functional categories in all reconstructed RNA regulons for individual taxonomic groups. For each taxonomic group, the relative contribution of ten overall functional categories (OFCs) to the RNA-regulated genes with assigned functions is shown. The proportions are calculated based on cumulative OFC statistics for all studied RNA families provided in Additional file 6 and exclude functionally unknown genes. The colored bar in each cell is proportional to the total number of OFC in each taxon, with different colors used for each row. Under the first column, the number following the name of each taxon represents the number of genomes examined in this study. The taxonomic groups are arranged according to their phylogeny.
Figure 8
Figure 8
Proportion of overall functional categories for individual RNA motifs. For each RNA motif, the relative contribution of ten overall functional categories (OFCs) to the riboswitch-regulated genes with assigned functions is shown. The proportions are calculated based on cumulative OFC statistics for all studied taxonomic groups provided in Additional file 6 and exclude functionally unknown genes. The colored bar in each cell is proportional to the total number of OFC for each RNA motif family with different colors used for each row. RNA motifs controlling genes without assigned OFCs have their rows labeled as ‘N/A’.

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