Relationship between operon preference and functional properties of persistent genes in bacterial genomes

Abstract

Background: Genes in bacteria may be organised into operons, leading to strict co-expression of the genes that participate in the same operon. However, comparisons between different bacterial genomes have shown that much of the operon structure is dynamic on an evolutionary time scale. This indicates that there are opposing effects influencing the tendency for operon formation, and these effects may be reflected in properties like evolutionary rate, complex formation, metabolic pathways and gene fusion.

Results: We have used multi-species protein-protein comparisons to generate a high-quality set of genes that are persistent in bacterial genomes (i.e. they have close to universal distribution). We have analysed these genes with respect to operon participation and important functional properties, including evolutionary rate and protein-protein interactions.

Conclusions: Genes for ribosomal proteins show a very slow rate of evolution. This is consistent with a strong tendency for the genes to participate in operons and for their proteins to be involved in essential and well defined complexes. Persistent genes for non-ribosomal proteins can be separated into two classes according to tendency to participate in operons. Those with a strong tendency for operon participation make proteins with fewer interaction partners that seem to participate in relatively static complexes and possibly linear pathways. Genes with a weak tendency for operon participation tend to produce proteins with more interaction partners, but possibly in more dynamic complexes and convergent pathways. Genes that are not regulated through operons are therefore more evolutionary constrained than the corresponding operon-associated genes and will on average evolve more slowly.

Figure 1

Similarity to minimal gene sets. Venn-diagram showing our gene set compared to the gene sets from Gil et al. [13] and Baba et al. [19]

Figure 2

Genomic range of persistent genes. Genomic range of persistent genes expressed as a percentage of genome size. The four linear genomes are marked with black points; the grey points represent circular genomes.

Figure 3

Genomic distribution of persistent genes in E. coli. The genomic distribution of persistent genes shown as a genome atlas map for the reference organism E. coli O157:H7. The genes are colour coded according to COG group.

Figure 4

Gene clusters from gene pair distances. a) Gene clusters with intra-genomic pair-wise distance of at most 500 base pairs. Edges indicate the number of organisms where the distance is within this cut-off (see legend). b) An overview showing the persistent genes in the S10, spc and alpha operons found in E. coli O157:H7. The cluster number and gene type ([Additional file 1: Supplemental Table S2]; red: singletons, blue: duplicates) is also indicated.

Figure 5

Relative order of persistent genes in all genomes. The red line indicates the gene order of the reference organism, E. coli O157:H7. For the other genomes the order of the persistent genes has been sorted according to the reference organism, and the relative genomic position of the genes plotted along the y-axis. Relatively flat horizontal lines in the plot indicate regions with conserved gene clustering compared to the reference organism (i.e. we are moving short genomic distances between genes when they are sorted according to the E. coli gene order). We see several such regions, marked with the same colours as in Figure 4. However, outside these regions the intra-genomic gene distances are highly variable.

Figure 6

Evolutionary distance between genomes. Correlation between evolutionary distance from amino acid sequences for all persistent genes versus genomic gene order (EDE).

Figure 7

Phylogram from persistent genes. Phylogram based on a multiple alignment of protein sequences from the all persistent genes. Bacteria normally classified to the same phyla are marked with identical colour.

Figure 8

Strong and weak operon genes according to COG categories. The graph includes ribosomal genes (Translation, ribosomal structure and biogenesis (J)).

Figure 9

Average protein bit score for strong and weak operon gene clusters. A box plot showing the different gene clusters ranked according to average pair-wise bit score of the protein sequences (BitScore) normalised against alignment length (AliLen). The legend text shows the median score of each group (weak operon 0.79 bits, strong operon 0.65 bits). Ribosomal genes are not included. When they are included the numbers are 0.81 and 0.75, respectively.

Figure 10

Average protein length for strong and weak operon gene clusters. The median protein sequence length over all 113 proteins for each of the 213 gene clusters plotted against median of normalised bit scores (see Figure 9). The legend text shows the median length for each group (weak operon 497.31 residues, strong operon 335.06 residues). This plot and analysis excludes ribosomal proteins; when they are included the corresponding number are 461.93 and 273.51, respectively.