Recombination Drives Evolution of the <i>Clostridium difficile</i> 16S-23S rRNA Intergenic Spacer Region

<div><p>PCR-ribotyping, a typing method based on size variation in 16S-23S rRNA intergenic spacer region (ISR), has been used widely for molecular epidemiological investigations of <i>C. difficile</i> infections. In the present study, we describe the sequence diversity of ISRs from 43 <i>C. difficile</i> strains, representing different PCR-ribotypes and suggest homologous recombination as a possible mechanism driving the evolution of 16S-23S rRNA ISRs. ISRs of 45 different lengths (ranging from 185 bp to 564 bp) were found among 458 ISRs. All ISRs could be described with one of the 22 different structural groups defined by the presence or absence of different sequence modules; tRNA^Ala genes and different combinations of spacers of different lengths (33 bp, 53 bp or 20 bp) and 9 bp direct repeats separating the spacers. The ISR structural group, in most cases, coincided with the sequence length. ISRs that were of the same lengths had also very similar nucleotide sequence, suggesting that ISRs were not suitable for discriminating between different strains based only on the ISR sequence. Despite large variations in the length, the alignment of ISR sequences, based on the primary sequence and secondary structure information, revealed many conserved regions which were mainly involved in maturation of pre-rRNA. Phylogenetic analysis of the ISR alignment yielded strong evidence for intra- and inter-homologous recombination which could be one of the mechanisms driving the evolution of <i>C. difficile</i> 16S-23S ISRs. The modular structure of the ISR, the high sequence similarities of ISRs of the same sizes and the presence of homologous recombination also suggest that different copies of <i>C. difficile</i> 16S-23S rRNA ISR are evolving in concert.</p></div

Indication of homologous recombination in <i>C. difficile</i> 16S-23S rRNA intergenic spacer region.

<p>(A) Phylogenetic network constructed for 95 representative ISR sequences from 43 different <i>C. difficile</i> strains. (B) Phylogenetic network of 29 ISR sequences (279–282 bp) from 29 different strains of <i>C. difficile</i>. Only one ISR per strain was included in the analysis. Box-like branches seen on both figures indicate relative support for alternative relationships among ISRs, probably resulting from homologous recombination that was subsequently confirmed by statistical analysis. In groups I, II and III the ISRs without a gene for tRNA^Ala are clustered and in group IV the ISRs with a tRNA gene.</p

Clustering of <i>C. difficile</i> PCR-ribotypes.

<p>(A) Clustering of PRC-ribotypes based on fingerprinting profiles generated by capillary gel electrophoresis-based PCR-ribotyping. Dendrogram is color coded according to MLST type. The exact lengths of the bands, representing the 16S-23S rRNA intergenic spacer regions are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106545#pone.0106545.s004" target="_blank">Table S1</a>. (B) Minimum spanning tree of MLST results showing relatedness of PCR-ribotypes. Each circle represents one sequence type (ST) and is subdivided into sectors corresponding to the number of PCR-ribotypes represented with this ST. The numbers between circles represent number of differing loci between the STs.</p

Schematic representation of the modular structure of <i>C. difficile</i> 16S-23S rRNA intergenic spacer region.

<p>Start (29 bp) – 5' end of the ISR sequence; Ntrna (26 bp) – part of the ISR without a gene for tRNA^Ala; Trna (186 bp) – part of the ISR with a gene for tRNA^Ala; DR – 9 bp long direct repeat; 53 bp, 33 bp, 20 bp – spacers of 53 bp, 33 bp and 20 bp, respectively and End (103–114 bp) is the 3' end of the ISR. The size of each structural group is given on the right. The inverse spacer arrangements can be seen in groups 6 and 7, 10 and 11, 12 and 13 and in groups 15 and 16.</p

Fitting parameters in the duplication-divergence model for all organisms.

<p> and are time-independent and describe the probability that an interaction is retained after a duplication and the probability that an interaction is created de novo, respectively. The fraction of interacting pairs in the ancestral network at time is represented by . There are in total nine ancestral time levels for the organisms investigated: the ancestral primates (prNOG), the ancestral rodents (roNOG), the ancestral mammals (maNOG), the ancestral vertebrates (veNOG), the ancestral insects (inNOG), the ancestral animals (meNOG), the ancestral fungi (fuNOG), the ancestral eukaryotes (KOG/euNOG), and the LUCA (COG/NOG). Existing time levels are specific for every species depending on its lineage.</p

Consensus sequence and number of sequence variants found in ISR building blocks.

<p>Only the representatives (n = 95) of non-redundant sets were used to calculate the consensus sequence and to determine the number of sequence variants.</p><p>Consensus sequence and number of sequence variants found in ISR building blocks.</p

Input data overview.

<p>The numbers of proteins (nodes) and interactions extracted from STRING at each filter step before construction of the protein-protein interaction networks. Numbers are show on log-scale. (A) Number of nodes. (B) Number of interactions. Violet: STRING experimental score , green: conserved on all evolutionary levels, red: after filtering at , orange bars: after filtering at considering only largest (connected) component (LC); the largest component is necessary for the topological analysis.</p

Scaling exponents, growth rates and their relationships.

<p>Scaling exponents (, , ), growth rates (, , ) and their relationships derived from the dynamic analysis (The growth rates of <i>E. coli</i> do not have uncertainties because there are only two time levels). Here we selected the three largest networks (<i>E. coli</i>, <i>S. cerevisiae</i>, and <i>H. sapiens</i>) and one sample (<i>M. musculus</i>) representing the smaller networks.</p

An example of the reconstruction process of the <i>S. cerevisiae</i> ancestral networks.

<p>(A) Illustration of the network reconstruction process. A subset of the empirical PPI network of <i>S. cerevisiae</i> is shown. The phylogenetic trees demonstrate how the proteins are grouped into COGs at different evolutionary levels. This information is used to identify the ancestral nodes. Note C2(COG0515) comprises other proteins which are not shown here. (B) The interaction between each pair of COGs is assigned a probability based on the duplication-divergence model. (C) The fractal dimension versus the cutoff for the ancestral prokaryote network of yeast. By increasing , approaches to the value of the present-day network (dashed line). We choose cutoff so that the ancestral network has the some fractal dimension as the present-day network. For , remains (approximately) as a constant.</p

Summary of the evolutionary mechanism.

<p>Conservative and multiplicative laws determine the static scaling exponents (, , , ) in terms of growth rates (, , , ). The three theoretical predictions (, , and ) have been corroborated by empirical calculations, while the remaining relation is a prediction open for test.</p