Selection for unequal densities of sigma70 promoter-like signals in different regions of large bacterial genomes

Abstract

The evolutionary processes operating in the DNA regions that participate in the regulation of gene expression are poorly understood. In Escherichia coli, we have established a sequence pattern that distinguishes regulatory from nonregulatory regions. The density of promoter-like sequences, that could be recognizable by RNA polymerase and may function as potential promoters, is high within regulatory regions, in contrast to coding regions and regions located between convergently transcribed genes. Moreover, functional promoter sites identified experimentally are often found in the subregions of highest density of promoter-like signals, even when individual sites with higher binding affinity for RNA polymerase exist elsewhere within the regulatory region. In order to see the generality of this pattern, we have analyzed 43 additional genomes belonging to most established bacterial phyla. Differential densities between regulatory and nonregulatory regions are detectable in most of the analyzed genomes, with the exception of those that have evolved toward extreme genome reduction. Thus, presence of this pattern follows that of genes and other genomic features that require weak selection to be effective in order to persist. On this basis, we suggest that the loss of differential densities in the reduced genomes of host-restricted pathogens and symbionts is an outcome of the process of genome degradation resulting from the decreased efficiency of purifying selection in highly structured small populations. This implies that the differential distribution of promoter-like signals between regulatory and nonregulatory regions detected in large bacterial genomes confers a significant, although small, fitness advantage. This study paves the way for further identification of the specific types of selective constraints that affect the organization of regulatory regions and the overall distribution of promoter-like signals through more detailed comparative analyses among closely related bacterial genomes.

Figure 1. Schematic Representation of the Main Interactions of RNAP with Promoter DNA and Alignment of the σ⁷⁰ Motifs for Recognition and Binding of −10 (2.4 Region) and −35 Promoter Sequences (4.2 Region) for Representative Eubacteria

Sequence alignments of several σ⁷⁰ factors from different bacteria reveal four conserved regions that can be further divided into subregions [39]. Only regions 2 and 4 are well conserved in all members of the σ⁷⁰ family [–43] and include subregions involved in binding to the core RNAP complex, promoter melting, and recognition of the −10 and −35 promoter sequences (regions 2.4 and 4.2, respectively) [10,40,44]. CLUSTALW was used to generate the alignment with default parameters (http://www.ebi.ac.uk/clustalw) [45].

Figure 2. Frequency Matrices for the −10 and −35 Motifs of σ⁷⁰ Promoters in E. coli

This matrix pair (Matrix_18_15_13_2_1.5) was selected for searching across bacterial genomes from a collection of optimized matrices defined for E. coli in [1]. Note that in order to compare these matrices with the canonical patterns (TTGACA and TATAAT), the spacers of 13 bp to 19 bp between the two boxes correspond to the 15 bp to 21 bp reported in the literature, as the TGT triplet is considered as part of the −10 box. Before searching for promoter-like signals, these matrices were calibrated using the noncoding base composition of each target genome.

Figure 3. Signal Density in Regulatory versus Nonregulatory Regions of Large and Small Eubacterial Genomes

Regulatory regions correspond to the strictly noncoding regions located upstream of a gene start. For the set of genomes selected in this study, the average size of the strictly noncoding upstream regions is 182 bp. For the sake of the graph, the regions were extended to 500 bases upstream and 500 bases downstream of the start of the gene (position 0). Nonregulatory regions include the coding regions and the noncoding regions between convergently transcribed genes. For coding regions, the middle point of a gene was taken as the position 0 and 500 bases upstream and 500 bases downstream of this position were included. For the set of genomes analyzed here, the average size of the convergent regions is 194.5 bp. For the sake of the graph, the end of the 3′ gene was taken as position 0 and 500 bases upstream and 500 bases downstream of this position were included. The number of signals was averaged within intervals of 10 bp.

Figure 4. Signal Density in Regulatory versus Nonregulatory Regions of M. tuberculosis and M. leprae

M. leprae shows an increase of promoter-like signals in the upstream and downstream regions of pseudogenes relative to the regulatory regions. M. leprae contains over 1,115 recognizable pseudogenes [20]. Both 500 bp upstream and downstream of the start of pseudogenes (position 0) were analyzed for searches of promoter-like signals. All other region definitions and methodology are as in Figure 3.