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Phylogenetic relationships and genotyping of the genus Streptococcus by sequence determination of the RNase P RNA gene, rnpB

¹ Department of Clinical Microbiology, University Hospital, SE-751 85 Uppsala, Sweden
² Department of Molecular Evolution, EBC, Uppsala University, Norbyvägen 18C, SE-195 30 Uppsala, Sweden

Correspondence
Björn Herrmann
bjorn.herrmann{at}medsci.uu.se

	ABSTRACT

TOP ABSTRACT INTRODUCTION METHODS RESULTS AND DISCUSSION REFERENCES

 
The rnpB gene is universally present in bacterial species and encodes the RNA subunit of endoribonuclease P. In this study, rnpB was sequenced in 50 type strains and 29 additional strains of the genus Streptococcus. Putative secondary-structure models and possible interactions in RNase P RNA molecules are discussed. Phylogenetic relationships were studied and Bayesian, maximum-parsimony and minimum-evolution analyses supported six main clades that comprised 22 of the 50 species analysed. Phylogenetic inference was also studied for the 16S rRNA gene; it indicated a similar tree topology, but with weaker support values than for rnpB. Combined analysis of rnpB and 16S resulted in a phylogeny with significantly better support. Variability in the rnpB and 16S genes among all type strains, calculated as Shannon–Wiener information index values, was 0·45 for rnpB and 0·15 for 16S. Intraspecies proximity was assessed by principal coordinate analysis of rnpB for 32 strains of six closely related species (two clades) and showed species-specific clusters, but heterogeneity occurred in two species. It can be concluded that the rnpB gene is suitable for phylogenetic analysis of closely related taxa and has potential as a tool for species discrimination.

Published online ahead of print on 16 May 2003 as DOI 10.1099/ijs.0.02639-0.

The GenBank/EMBL/DDBJ accession numbers for rnpB are listed in Table 1.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION METHODS RESULTS AND DISCUSSION REFERENCES

 
Identification of Streptococcus species has traditionally been based on the serological grouping by Lancefield and haemolytic reactions. However, Lancefield groups are not species-specific (Farrow & Collins, 1984; Lawrence et al., 1985) and haemolytic activity differs within species and depends on incubation procedures, as well as origin of blood in the substrate. In clinical laboratories, current means of identification of streptococci rely on phenotypic tests. These largely provide adequate species differentiation, but up to 13 % of analysed strains may be identified incorrectly (Kikuchi et al., 1995). Furthermore, strains within a given species may differ for a common trait (Kilian et al., 1989; Beighton et al., 1991) and the same strain may exhibit biochemical variability (Hillmann et al., 1989; Tardif et al., 1989). Moreover, small alterations in realization of a phenotypic test may give false results.

Although no single classification system is perfect, the development of genetic analysis has improved the identification of streptococci. DNA hybridization (Schmidhuber et al., 1988; Adnan et al., 1993; Bentley & Leigh, 1995; Jacobs et al., 1996), rDNA restriction analysis (Jayarao et al., 1992; Rudney & Larson, 1994; Gillespie et al., 1997), amplification of selected targets [interspace 16S–23S (Saruta et al., 1995; Whiley et al., 1995), ddl gene (Garnier et al., 1997), tDNA PCR fragment length (De Gheldre et al., 1999; Baele et al., 2001)] and sequence analysis (Bentley et al., 1991; Poyart et al., 1998) are alternative techniques that provide differentiation between species, often with high resolution.

Differentiation of closely related chlamydial species has recently been shown to be possible by using the RNase P RNA gene rnpB as a marker (Herrmann et al., 1996, 2000). Endoribonuclease P (RNase P) is a ribonucleoprotein complex that removes 5' leader sequences from tRNA precursors during tRNA biosynthesis. RNase P is present in all cells and subcellular compartments that synthesize tRNA, but catalytic activity by RNA alone has only been demonstrated for bacterial and some archaeal RNase P RNAs (Pannucci et al., 1999). The endoribonuclease has been characterized best in the division Bacteria, where it is composed of an RNA molecule of approximately 400 nt and a protein of about 120 aa (Altman & Kirsebom, 1999). Bacterial RNase P RNAs have been separated into two main classes based on secondary structure: type A is the most common class, whereas type B is found exclusively in the low G+C Gram-positive Bacteria (Haas et al., 1996). Secondary structure of RNase P RNA has been characterized for many bacterial lineages and variation among the helices provides useful phylogenetic information (Haas & Brown, 1998).

In this study, we sequenced the rnpB gene in 50 Streptococcus species, performed phylogenetic analysis and evaluated the possibility of using rnpB for genotyping.

	METHODS

TOP ABSTRACT INTRODUCTION METHODS RESULTS AND DISCUSSION REFERENCES

 
Bacterial strains.
The 79 streptococcal strains (50 type strains and 29 other strains) used in this study and their sources are listed in Table 1.

PCR amplification and sequencing.
The rnpB gene from Streptococcus species was amplified by PCR with the primer pair strF (5'-YGTGCAATTTTTGGATAAT-3') and strR (5'-TTCTATAAGCCATGTTTTGT-3'); the design was based on the Streptococcus pyogenes sequence (Brown, 1999). The reaction mixture contained 0·2 µM each primer, 200 µM dNTPs, 2·5 mM MgCl₂ and 1·5 U HotStarTaq DNA polymerase (Qiagen). Amplification conditions consisted of 15 min enzyme activation at 95 °C, followed by five cycles of 40 s at 94 °C, 40 s at 58 °C and 40 s at 72 °C. An additional five cycles were added with an annealing temperature of 54 °C, followed by 30 cycles with an annealing temperature of 50 °C. To generate a PCR product from Streptococcus pleomorphus, primers from conserved rnpB regions were used: BAC1 [5'-(GCT)NRG(GCT)NGAGGAAAGTCC-3'] and BM1-2 (5'-TGTAAAACGGCCAGTRTAAGCCGGGTTCTGT-3'). Amplification conditions were as above, except that the primer concentration was 0·4 µM and the annealing temperature was 43 °C for all 40 cycles.

PCR products were sequenced by using BigDye Terminator labelled cycle sequencing chemistry (Applied Biosystems) and sequence reactions from complementary strands were analysed on a 310 Genetic Analyser (Applied Biosystems). Consensus sequences were submitted to GenBank/EMBL and all accession numbers of rnpB sequences from the present study are listed in Table 1.

Phylogenetic analysis.
Sequence alignment required secondary-structure modelling of RNase P RNA, which was performed manually by using comparative sequence analysis. Sequences of 16S rRNA were obtained from the Ribosomal Database Project (Maidak et al., 2001) and GenBank. Obtained alignments were used for phylogenetic inference by using a Bayesian approach, as implemented in MRBAYES 2.01 (Huelsenbeck & Ronquist, 2001). MRBAYES uses Metropolis-coupled Markov chain Monte Carlo methods to calculate posterior probabilities for parameters of interest. Each analysis was run for 5x10⁵ generations and the first 5x10⁴ were discarded as burn-in; four differently heated chains were employed. Convergence was tested by rerunning the analyses with different initial parameter values.

To select an adequate model for the Bayesian analysis (as well as pairwise distances), we used a hierarchical likelihood ratio test (LRT) approach (Huelsenbeck & Crandall, 1997). To do this, we used PAUP* (4.0b8–10, Linux and Macintosh versions; Swofford, 2000) and the same test hierarchy (and thus model selection) as implemented in the program MODELTEST (Posada & Crandall, 1998) at P<0·01. Neighbour-joining trees under the Jukes–Cantor model were produced for each of the datasets/partitions, separately as well as combined, and parameters for each model were estimated by using these trees. The same model was used for pairwise distances (e.g. -shape and proportion of invariant sites) and the parameters assigned were based on the maximum-likelihood estimate.

In addition to the Bayesian analysis, we performed bootstrap analyses by using maximum-parsimony (MP) and minimum-evolution (ME) as optimality criteria, with PAUP* 4·0b8–10. For the optimality criterion methods, 1000 bootstrap replicates were performed and heuristic search algorithms were used, namely simple stepwise addition and TBR (tree bisection–reconnection) branch-swapping.

To map the hosts of the various species on the phylogenetic hypothesis, we used MacClade 3.08 on the combined dataset of 16S and rnpB.

To compare variation in the different genes, we used the Shannon–Wiener information index, H, defined as:

where p_i is the proportion of A, T, C and G (Shannon & Weaver, 1949; Wiener, 1949). The mean value for all sites in the same set of taxa was calculated for each dataset.

To show similarity and distinctiveness of closely related species, we did principal coordinate analysis (Gower, 1966) on uncorrected pairwise distances (p-distances) by using the software DISTPCOA (Legendre & Anderson, 1998, 1999).

	RESULTS AND DISCUSSION

TOP ABSTRACT INTRODUCTION METHODS RESULTS AND DISCUSSION REFERENCES

 
Comparison of rnpB sequences and characterization of secondary-structure models
PCR products that included 97·5 % of the full-length rnpB gene were obtained from 79 streptococcal strains, representing 49 different species. Products varied in length from 367 to 388 bp and similarities were 77·7–100 %. Additionally, a 304 bp product was obtained from S. pleomorphus, making a total of 50 species examined. The only species with identical sequences were Streptococcus waius and Streptococcus macedonicus, both isolated originally from dairy products and proposed recently to comprise a single species (Manachini et al., 2002; Poyart et al., 2002). Alignment of rnpB sequences indicated seven hypervariable regions located in distinct stem–loops, denoted P3, P9, P10.1, P12, P15.1 and P19 in the suggested secondary structure (Fig. 1). This is in keeping with previous reports (Haas et al., 1996; Massire et al., 1998); it is thought that these hypervariable domains of the RNA subunit of RNase P RNA are important in the formation of a mature ribozyme and its interaction with tRNA precursors.

View larger version (30K): [in this window] [in a new window]   Fig. 1. Deduced secondary structure of RNase P RNA in Streptococcus oralis. Nucleotides in primer sequences are in lower case. Abbreviations: y, cytosine/thymidine mixture; N, tentative nucleotides in flanking regions of primer, based on minimum consensus bacterial RNase P RNA (Brown, 1999). Suggested long-distance interactions for P4 are denoted by lines.

The P15.2 helix varies in length among the species examined. In five species that belong to the mitis group, this helix was 29 nt long, whereas in all other species it was 12–16 nt long. This is in keeping with the tertiary model of RNase P RNA, in which this helix can exhibit variable length in type B sequences without affecting the interaction of the P15.1/P15.2 helix with the loop of the P5 helix (Massire et al., 1998).

The P15.1 loop has been suggested to interact with the P5.1 loop to stabilize the catalytic site of RNase P RNA. Conserved motifs of RAA-NNNAA in P15.1 and UGNRAU in P5.1 would participate in this interaction. Sequences from streptococci fitted into this model and the corresponding sequence variation in the motifs was GAA-N(C/A/U)GAA and UG(T/A/C)GAU, respectively.

Another tertiary interaction has been proposed for the distal part of P10.1 and a highly conserved GAAA tetraloop of P12 (Tanner & Cech, 1995; Haas et al., 1996). Among streptococci, the GAAA loop was found in all sequences except for that of Streptococcus bovis, which had AAAA in this loop. This observation in the type strain was confirmed in sequence analysis of two other S. bovis strains (CCUG 34832 and CCUG 4214). A corresponding shift in the motif of the P10.1 stem was not detected. RNase P RNA of type B typically forms an internal loop in P10.1 (nt 136–140 and 162–167 in Fig. 1, Streptococcus oralis) with the consensus motif RAA...RAGUA (Fig. 3 of Massire et al., 1998). Of 49 streptococcal type strains, the RAAA motif was not found in nine strains. These strains differed by 1 or 2 nt. The RAGUA motif was found only in 19 species and of the 30 species with alterations, three species had three nucleotide changes (two with two gaps) and one species had changes in all five positions. Variation noted in the internal P10.1 loop shows the complexity of the helix and the difficulty in interpreting structure patterns.

View larger version (32K): [in this window] [in a new window]   Fig. 3. Majority-rule consensus tree summarizing the result from Bayesian analysis of the combined (16S and rnpB) dataset. Branches with a posterior probability of <0·5 have been collapsed. Numbers above branches are posterior probabilities; numbers below branches are bootstrap percentages for the MP and ME analyses, respectively. Bars indicate currently used taxonomic groups within Streptococcus (Kawamura et al., 1995); solid bars indicate taxa present in the original classification, dashed bars indicate taxa added in subsequent analyses.

Analysis of a 304 bp rnpB fragment of S. pleomorphus, a species suggested to be removed from the Streptococcus genus (Ludwig et al., 1988), showed some distinctive features compared to those of classical streptococcal species. The P10.1 loop formed a closed stem of 13 bp without the internal loop that is typical of type B RNase P RNA. Furthermore S. pleomorphus completely lacks the P19 stem–loop structure, which is found in all other streptococcal species. Our findings are compatible with the proposed removal of S. pleomorphus from the genus Streptococcus.

Phylogeny of the genus Streptococcus
Different approaches were used to infer phylogenetic relationships among streptococcal species. Analysis of both the rnpB and 16S rRNA genes required that site-to-site rate variation was modelled; the optimal model for both genes used a discrete -distribution (Yang, 1993, 1994) and treated a fraction of the sites as invariant (Gu et al., 1995; Waddell & Penny, 1996). For rnpB, as well as the combined dataset of rnpB and 16S, the Tamura–Nei model (i.e. unequal base frequencies, transversions and two classes of transitions treated separately; Tamura & Nei, 1993) was indicated to be the most adequate, whereas the 16S dataset required the general time-reversible (GTR) model with six different rate parameters (Rodriguez et al., 1990). Due to limitations in the MRBAYES software, the model actually employed for Bayesian analysis of the combined dataset was the more parameter-rich GTR model, with separate -distributions for the genes.

To compare phylogenetic utility of the two genes, and specifically to explore clade support in each gene and any significant conflicts between them, majority-rule consensus trees that comprise clades with a posterior probability of 0·85 for the two genes when analysed separately, are shown in Fig. 2. Branch support, as assessed by Bayesian posterior probabilities and bootstrap percentages in the MP and ME analyses, are given on the branches. Results from the two genes were generally congruent, i.e. there were only a few cases where clades with substantial support were in conflict (see below) and all remaining differences in the optimal trees (not shown) from the two genes can, at the moment, be treated as being due to limited sampling (i.e. sequence length) and not as real incongruence between the histories of the two genes. Thus, a combined approach (using both genes in the analysis) is beneficial to obtain a better phylogenetic hypothesis of the genus Streptococcus (Fig. 3).

View larger version (44K): [in this window] [in a new window]   Fig. 2. Majority-rule consensus trees summarizing the results from Bayesian analysis of the rnpB (left) and 16S (right) datasets. Branches with a posterior probability of <0·85 have been collapsed and hence relationships with a lower support will appear as polychotomies, even if they are present in the optimal tree. Numbers above branches indicate posterior probabilities of the branches in the Bayesian analysis; numbers below branches are bootstrap percentages for the MP and ME analyses, respectively. No value given (-) indicates a bootstrap proportion of <50 %, i.e. no support. Capital letters designate some clades discussed in the text.

In the pyogenic group, there is support for Streptococcus dysgalactiae, Streptococcus agalactiae and Streptococcus phocae in one clade (G) in the 16S tree, although there is no support for Streptococcus iniae as the closest relative, as stated previously (Skaar et al., 1994). The remaining eight species in this group according to the previous classification (Kawamura et al., 1995) are either found in well-supported pair-clades (Streptococcus canis and S. pyogenes; S. iniae and Streptococcus parauberis) or without any well-supported association with other species (Streptococcus hyointestinalis, Streptococcus porcinus, Streptococcus uberis and Streptococcus equi). In contrast, in the rnpB tree, S. dysgalactiae, S. canis and S. pyogenes form a clade (F), whereas S. agalactiae do not form a well-supported clade with any other streptococcal species. This is the other strong incongruence between the 16S and rnpB datasets, for which additional data will be needed before the issue can be resolved. It is worth noting, however, that analysis of the sodA gene (Poyart et al., 1998; Whatmore & Whiley, 2002) is congruent with rnpB in this matter. The close relationship between the two type strains of S. equi subsp. equi and S. equi subsp. zooepidemicus was supported strongly in both the rnpB and 16S rRNA trees. Other species that were, until recently, considered to belong to the pyogenic group (Streptococcus urinalis and S. hyointestinalis, and the pair Streptococcus pluranimalium and Streptococcus hyovaginalis) did not receive substantial support for inclusion in such a clade (although there was no contradiction).

For the bovis group, rnpB data supported a clade (E) with S. bovis, Streptococcus equinus, Streptococcus infantarius subsp. infantarius and S. infantarius subsp. coli (Streptococcus lutetiensis) together. This is also supported by recent analysis of the sodA gene (Poyart et al., 2002), and, with slightly lower support (p=0·89), by the 16S dataset.

The notable lack of support in the rnpB tree for a clade that consists of the two identical sequences of S. macedonicus and S. waius may seem paradoxical. S. macedonicus and S. waius do form a clade in the optimal phylogeny, regardless of the method used. Support, however, also depends on how distinct taxa in a clade are related to other taxa. In this case, just a few sites differ from other sequences in species that are closely related to S. macedonicus/S. waius in the analysis; the hypothesis that S. macedonicus and S. waius are close relatives due to sequence convergence cannot be ruled out completely (but there is even less support in favour of such a hypothesis).

Species that constitute the mutans group in the 16S analysis of Kawamura et al. (1995) (S. mutans, S. ratti, S. macacae, Streptococcus downei, Streptococcus sobrinus and Streptococcus criceti) obtained no significant support to form a clade in the 16S tree. However, in the rnpB tree, S. mutans, S. ratti and S. macacae form a well-supported clade. Another clade is formed by S. downei, S. sobrinus and S. criceti, with bootstrap values of 96 and 100 % in MP and ME analyses, respectively, albeit with a posterior probability of only 0·89.

Our phylogenetic analysis of streptococcal 16S genes indicates that for several species there is no strongly supported evolutionary relationship. As the rate of substitution in this gene is slow, this is not surprising. Although certain criteria for using 16S sequences have been adopted in many studies (<97 % sequence similarity enables the 16S rRNA gene to differentiate species; Stackebrandt & Goebel, 1994), taxonomic classification analysis must be based on more than a single gene and, in addition to genetic data, ecological data must be considered. Analysis of separate genes showed nine nodes with at least three terminal branches and significant posterior probabilities of 0·95; three unique nodes for rnpB, two unique nodes for 16S and four nodes common to both genes (Fig. 2). By combining the two genes in one analysis, the number of nodes increased to 12 (Fig. 3), indicating a higher resolution and increased clade support in phylogenetic analysis when available data are combined.

The taxonomically most significant result from the combined analysis (Fig. 3) is that the mitis group, as currently circumscribed, is not monophyletic without inclusion of the anginosus group. The latter formed a subclade within a clade that also comprised the mitis group, which is in contrast to analysis of the sodA gene (Whatmore & Whiley, 2002). Interestingly, all species in this clade (anginosus and mitis groups) have humans as their host organism. Combined analysis also showed weak support for the placement of S. urinalis, S. hyointestinalis, S. hyovaginalis and S. pluranimalium in the pyogenic clade. Furthermore, combined analysis firmly (posterior probability, 1·0) placed Streptococcus ferus in the mutans group (with S. mutans, S. ratti and S. macacae), in which it has been included until recently. Whatmore & Whiley (2002) found no support in the 16S rRNA or sodA genes for inclusion of S. ferus in the mutans (or any other established) group and concluded that it is distantly related to all other Streptococcus species.

To characterize the variability in the 16S rRNA and rnpB genes, we calculated the Shannon–Wiener information index for each site over the same set of taxa. The frequency of positions with low nucleotide variation is much higher for the 16S rRNA gene than for the rnpB gene. On average, the index is three times higher for rnpB (0·45) than for 16S rRNA (0·15) (Fig. 4). A frequently used estimate of the variation in genes is obtained by comparing mean sequence similarity. However, this rough estimate does not take into account the fact that genes may not differentiate species properly if the nucleotide variation is limited to relatively few positions. Nevertheless, our analysis shows that for streptococci, rnpB has higher potential for species discrimination than the 16S rRNA gene. In fact, separate bacterial species have been found to have identical 16S rRNA gene sequences (Fox et al., 1992). Another advantage of rnpB is the single-copy expression of the gene. In contrast, the 16S rRNA gene may have several copy variants in the genome and sequence heterogeneities may result in erroneous genotyping (Nubel et al., 1996).

View larger version (23K): [in this window] [in a new window]   Fig. 4. Analysis of nucleotide variation of the rnpB and 16S genes in 50 type strains of streptococcal species. The Shannon–Wiener (S–W) information index expresses variation as information at each nucleotide position. Percentage of positions with different index values are plotted on the x-axis, with mean values for rnpB and 16S above. A site with the same base in all sequences has a S–W index of 0, whereas a site with all bases having the same frequency (0·25) obtains the maximum S–W value of 2.

View larger version (14K): [in this window] [in a new window]   Fig. 5. First two principal coordinates resulting from principal coordinate analysis of rnpB sequences of (top) five strains of each species in the salivarius group [S. salivarius (, n=5), S. thermophilus (, n=5) and S. vestibularis (, n=5)] and (bottom) 18 strains of species in the anginosus group [S. anginosus (, n=8), S. constellatus (, n=5) and S. intermedius (, n=8)]. Relative difference in sequence similarity between strains is shown for the 33 strains. Arrow indicates all S. constellatus strains and one S. anginosus strain.

	ACKNOWLEDGEMENTS

 
The rnpB sequences presented here were generated by Bioimics AB, Uppsala, Sweden. We thank Leif Kirsebom for reading the manuscript.

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