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1 Department of Clinical Microbiology, University Hospital, SE-751 85 Uppsala, Sweden
2 Department of Molecular Evolution, EBC, Uppsala University, Norbyvägen 18C, SE-19530 Uppsala, Sweden
3 Department of Cell and Molecular Biology, Box 596, Biomedical Centre, SE-75124 Uppsala, Sweden
Correspondence
Björn Herrmann
bjorn.herrmann{at}medsci.uu.se
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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Published online ahead of print on 27 May 2005 as DOI 10.1099/ijs.0.63656-0.
The GenBank/EMBL/DDBJ accession numbers for the rnpB sequences of 55 Legionella strains are AJ781429–AJ781483.
Tables showing the alignment of Legionella rnpB gene sequences included in this study are available as supplementary material in IJSEM Online.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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) and new species are frequently described (http://www.dsmz.de/bactnom/bactname.htm). Some Legionella species cause human disease, while others have been detected only in the environment (Fields et al., 2002). The diseases caused by Legionella include the pneumonic form, Legionnaires' disease, and the extrapulmonary flu-like form, Pontiac fever. Legionella pneumophila serogroup (sg) 1 is the causative agent in up to 84 % of disease cases that are due to Legionella infection (Yu et al., 2002). There may, however, be a bias towards detecting L. pneumophila sg 1, since commonly used urinary antigen tests mainly detect this serogroup (Helbig et al., 2003). Other L. pneumophila serogroups, as well as Legionella longbeachae, Legionella micdadei, Legionella dumoffii and Legionella feeleii, are also often associated with human disease (O'Connell et al., 1996). In Australia, L. longbeachae is the leading cause of Legionnaires' disease (Alli et al., 2003). Immunocompromised individuals are especially susceptible to infection and may be colonized by species not normally associated with disease. Therefore, it is important for epidemiological investigations to identify species within the genus accurately.
In clinical diagnostics, Legionella bacteria are commonly identified by culture since they have very specific growth requirements. If bacteria grow on cysteine-enriched buffered charcoal-yeast extract (BCYE) agar, but not on BCYE agar without cysteine, the bacteria presumably belong to the genus Legionella (Murray et al., 2002). To discriminate between species, phenotypic tests such as growth characteristics, auto-fluorescence and serological methods targeting membrane proteins are often used. These methods provide low resolution and antigen cross-reactivity limits the specificity of antibody tests (Verissimo et al., 1996).
Several DNA-based classification systems have been described for Legionella, some of which target the sequence variation of specific genes such as mip (Ratcliff et al., 1998), 16S rRNA (Fry et al., 1991), rpoB (Ko et al., 2002) and gyrA (Feddersen et al., 2000). Analysis of transfer DNA intergenic spacer length polymorphism has been shown to be highly discriminatory in the identification of Legionella species (De Gheldre et al., 2001). Amplified fragment length polymorphism (AFLP) and multilocus sequence typing (MLST) are very discriminatory techniques for subtyping within the species L. pneumophila (Gaia et al., 2003), where they also distinguish within serogroups (Jonas et al., 2000; Valsangiacomo et al., 1995). Thus, DNA-based analyses have greatly improved Legionella phylogenetics and the ability to discriminate between bacteria within the Legionella genus.
The rnpB gene encodes the catalytic RNA moiety of endoribonuclease P (RNase P), the enzyme that removes the 5'-leader of precursor tRNAs. In Bacteria and some Archaea, the RNA component alone exhibits catalytic activity in vitro; however, the protein subunit C5 is essential for activity in vivo and is encoded by the rnpA gene (Altman & Kirsebom, 1999; Pannucci et al., 1999). Based on the secondary structure of RNase P RNA, two types of bacterial RNase P RNA have been identified, type A and type B. RNase P RNA derived from Legionella belongs to type A, which is suggested to be the ancestral form of RNase P RNA found in bacteria. Type B RNase P RNA may have emerged later within the low G+C Gram-positive lineage (Haas & Brown, 1998).
In bacteria, rnpB comprises about 400 nt (Pace & Brown, 1995) and several conserved regions essential for the functioning of RNase P RNA have been identified. Certain regions with high variability have also been identified, for example, P3, P12 and P17 (see Fig. 1). The sequence variation of rnpB has been used previously to differentiate closely related species of Chlamydiaceae (Herrmann et al., 2000) and Streptococcus (Tapp et al., 2003).
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METHODS |
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. Furthermore, 12 clinical and three environmental isolates (1777/97, 1780/97 and 1829/00) are detailed (see Fig. 5).
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PCR amplification.
The rnpB gene was amplified using the primer pair LP3 [5'CA(INOSINE)AGTYGGTCAGGCAAT-3'] and BM1-2 (5'-TGTAAAACGACGGCCAGTRTAAGCCGGGTTCTGT-3'). The reaction mixture consisted of 0·8 µM of each primer, 200 µM dNTPs, 2 mM MgCl2, 2 U HotStar Taq DNA polymerase (Qiagen) and 20–100 ng template DNA, as measured from semiquantitative measurement on ethidium bromide-stained agarose gels. The reaction mixture was subjected to enzyme activation for 15 min at 95 °C followed by 37 cycles of amplification. Each amplification cycle consisted of denaturation for 30 s at 95 °C, primer annealing for 40 s at 50 °C and elongation for 40 s at 72 °C. A final step of 7 min at 72 °C was performed to ensure complete extension.
The 16S rRNA and mip genes of the environmental isolate 1829/00 were sequenced as described elsewhere (Johansson et al., 1995; Ratcliff et al., 1998).
Sequence analyses.
Initially, partial rnpB gene sequences were PCR-amplified with primers binding to the conserved regions defined by P4. The products generated by these primers, however, did not include the hypervariable P3 loop.
To facilitate the design of the LP3 primer, the sequence between the promoter region and the P3 loop was determined for ten Legionella species by amplifying the 5'-flanking DNA of the P4 loop in a PCR with biotinylated primers and streptavidin-coated beads, as described elsewhere (Sorensen et al., 1993). Sequencing of PCR products defined by LP3 and BM1-2 was performed on both DNA strands of all strains using polymer POP6 in an ABI 310 Genetic Analyser (Applied Biosystems). BM1-2 and LP3 were also used as primers in the sequencing PCR, in which the BigDye terminator-labelled cycle sequencing chemistry kit version 2.0 (Applied Biosystems) was used.
Phylogenetic analysis.
The rnpB gene sequences were aligned using CLUSTAL W, but required some manual editing to align homologous sites according to the secondary structures of RNase P RNA. The 16S rRNA, mip and rpoB gene sequences were obtained from GenBank and their accession numbers are presented in Table 1
. The 16S rRNA and mip gene sequences varied in size, and sequences from some species were therefore trimmed at the ends to generate sequences with homologous sites in the CLUSTAL W alignments. The rnpB fragments included were 304–354 nt long. 16S rRNA genes were approximately 1350 nt in length. All rpoB fragments were 300 nt long and approximately 650 nt were included from mip sequences, including the hypervariable insert adjacent to the signal sequence. The combined dataset, consisting of rnpB, 16S rRNA, mip and rpoB gene sequences, was constructed by concatenating the alignments for the individual genes and included 39 Legionella species, of which 37 had sequences available for all four genes.
The alignments obtained (individual genes and concatenated alignments) were used for phylogenetic inference using a Bayesian approach as implemented in MrBayes 3.0B4 (Huelsenbeck & Ronquist, 2001). MrBayes uses Metropolis-coupled Markov chain Monte Carlo methods to calculate the posterior probabilities for the parameters of interest. Each analysis was run for 1x107 generations with four differently heated chains; generations before convergence (as monitored on tree likelihood and total tree length) were discarded as burn-in.
To select an adequate model for the Bayesian analysis, as well as pairwise distances, we used a hierarchical likelihood ratio test 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 modeltest program (Posada & Crandall, 1998) at P<0·01. Neighbour-joining (NJ) trees under the Jukes–Cantor model were produced for each of the datasets/partitions separately as well as in combination and the parameters for each model were estimated using these trees. The same model was used for the pairwise distances (e.g. gamma shape, proportion invariant sites) and the parameters assigned were based on the maximum-likelihood estimate.
In addition to the Bayesian analysis, we performed bootstrap analyses as implemented in PAUP* 4.0b8-10, using maximum parsimony (MP) as optimality criterion and also using NJ. For the optimality criterion method, 1000 bootstrap replicates were performed and heuristic search algorithms were used, namely simple stepwise addition and tree bisection reconnection branch swapping.
To compare the variation in the different genes, we used the Shannon–Wiener information index, H, defined as
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; Wiener, 1949). The mean value for all sites in the same set of taxa was calculated for each dataset. |
RESULTS AND DISCUSSION |
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); they are however distinguishable using mip gene sequencing.
Differentiation of Legionella bozemanae and Legionella anisa has been proven difficult by transfer DNA intergenic spacer length polymorphisms (De Gheldre et al., 2001). A close species relationship was found when comparing rnpB gene sequences derived from these two Legionella species. In sequence analysis, L. anisa ATCC 35292T differs in four nucleotide positions compared with L. bozemanae ATCC 35545 sg 2, while the corresponding differences in comparisons between L. anisa ATCC 35292T and L. bozemanae ATCC 33217T sg 1, as well as between the two serogroups of L. bozemanae, were seven nucleotide positions. The finding that rnpB gene sequences from L. bozemanae sg 2 and L. anisa are more similar than those from the two serogroups of L. bozemanae was surprising since sequence data from previous studies examining other genes, such as mip and rpoB, have indicated a more distant relationship between the two species (Ko et al., 2002; Ratcliff et al., 1998).
The L. pneumophila serogroups 4, 5 and 15, together constituting L. pneumophila subsp. fraseri, differed in 14–15 nt from the rnpB gene sequence of L. pneumophila ATCC 33152T sg 1, while the sequence variation within subspecies fraseri was 1 nt. Similarly, the sequence variation within the subspecies of L. pneumophila subsp. pneumophila varied between 0 and 4 nt.
Secondary structures and intermolecular interactions of the RNase P RNA
The RNase P RNA gene has been sequenced and characterized from a large number of different bacteria (Brown, 1999). This information has been incorporated into models of the three-dimensional structures of both types of RNase P RNA, as well as in a complex with the protein subunit (Massire et al., 1998; Tsai et al., 2003). The majority of these previous studies on bacterial RNase P RNA have, however, focused on structural and functional differences between members of different bacterial genera (Haas & Brown, 1998). This study examined 39 species within one genus.
With the guidance of a type A RNase P RNA minimum consensus structure model (Brown, 1999), secondary structures of RNase P RNAs from three Legionella type strains were generated. As shown in Fig. 1, the secondary structures are very similar to those of some 
-Proteobacteria, e.g. Pseudomonas aeruginosa and Escherichia coli. Within the Legionella genus, RNase P RNA showed structural variations, particularly in P3 and P12 but also in the structural element between P16 and P17.
Two P3 variants were observed where the major variant was an 8 bp stem structure with a loop varying in size between three and six residues. In one species, Legionella israelensis ATCC 43119T, the sequence suggested the existence of a P3 helix composed of 20 bp with a U-rich internal bulge and a loop with eight residues (Fig. 1). Moreover, we noted that the first 6 bp of P3 are highly conserved irrespective of Legionella species (boxed residues in Fig. 1; see also sequence alignment data in Supplementary Material in IJSEM Online). Likewise, comparison of RNase P RNA structures derived from closely related bacterial species, e.g. Mycoplasma species (Svard et al., 1994), also reveals that the length of P3 varies and that residues in the boxed region (Fig. 1) in P3 are conserved. In contrast, a comparison of the length and sequence variation of the P3 domain derived from different bacterial branches indicates that the structure of the P3 is highly variable (Haas & Brown, 1998). The three-dimensional structural model of E. coli RNase P RNA (type A) in complex with the RNase P protein (C5) suggests that part of P3 interacts with the C5 protein (Tsai et al., 2003). In this model, the nucleotides in P3 that are suggested to interact with C5 are positioned closer to the P3 loop (the size of P3 in E. coli RNase P RNA is similar to that of L. israelensis ATCC 43119T). However, if P3 serves as a binding region for C5, then the available structural data (i.e. comparison of the P3 structure derived from closely related bacterial species, see above) suggest that the interaction between P3 and C5 should not depend on the length of P3. We therefore argue that it is possible that C5 binds to a specific sequence motif in P3. We suggest that it is likely that the ‘boxed’ residues in Fig. 1 serve as a binding motif for the C5 protein. The extra P3 residues in L. israelensis ATCC 43119T (and in other RNase P RNAs with long P3 helices) might be important for structural stabilization and/or be involved in interactions with other factors in the cell. However, this remains to be investigated.
In Bacillus subtilis, RNase P system chemical cleavage footprinting (Loria et al., 1998) and nucleotide analogue modification interference studies (NAIM; Rox et al., 2002) suggest that P12 and the C5 protein are in close proximity. Given that the RNase P holoenzyme consists of one RNA subunit and one protein subunit, neither of the two three-dimensional models are consistent with an interaction of C5 with both P12 and P3 (Chen et al., 1998; Tsai et al., 2003 and references therein). However, Fang et al. (2001) observed that the B. subtilis RNase P holoenzyme formed tetramers in solution that might rationalize the footprinting and NAIM data. For E. coli RNase P holoenzyme, no tetramers in solution have so far been observed (Fang et al., 2001). Nevertheless, cross-linking between the RNA and the protein subunits in E. coli RNase P holoenzyme has been observed (Sharkady & Nolan, 2001). The residues at positions 144 and 145 in L. pneumophila sg 1 correspond to the nucleotides in E. coli RNase P RNA that cross-linked to the C5 protein. In this study, we observed major structural variation in P12 in RNase P RNA derived from a large number of Legionella species with respect to size (i.e. number of base pairs), loop size and the number of bulges and their position in P12 (Fig. 1). Taken together, if P12 constitutes a binding site for the RNase P protein, it might be reoriented as proposed elsewhere (Sharkady & Nolan, 2001) or perhaps these data might reflect flexibility in the structure of RNase P RNA. Moreover, there is a possibility of identifying C5 amino acid residues that bind to the RNA in P12 by characterizing the rnpA gene from the corresponding Legionella species and looking for co-variation.
Another interesting structural feature is the suggested stem–loop structure between P16 and P17. This structural element has previously been described in RNase P RNA derived from Planctomycetes and 
-Proteobacteria (Brown, 1999), but it has not been observed in RNase P RNA from -Proteobacteria. Although the function of this stem–loop is not known, it is located very close to the domain of RNase P RNA that interacts with the 3' RCCA motif of the precursor substrates (interacting residues at position 284 : G and 285 : G in L. pneumophila ATCC 33152T sg 1 in Fig. 1) (Kirsebom & Svard, 1994). In the structural model of the RNase P holoenzyme, the RNase P protein is positioned close to the P15/16 region and therefore raises the possibility that the stem–loop structure between P16 and P17 functions as an anchoring site for the RNase P protein. However, its position in the three-dimensional structure cannot be such that it interferes with the binding of the substrate.
Phylogenetic analysis
Site-to-site rate variation was modelled separately for each of the genes rnpB, 16S rRNA, rpoB and mip. For the rnpB and rpoB genes, the most adequate model was TrNef+I+
, i.e. a Tamura Nei model (Tamura & Nei, 1993), with equal base frequencies and invariant sites plus a gamma rate distribution. For the mip gene, the GTR+I+ model, i.e. General Time Reversible (Lanave et al., 1984) with invariant sites and a gamma rate distribution (Yang, 1994), was shown to be the most suitable. For the 16S rRNA gene, the most appropriate model was found to be HKY+I+ (Hasegawa et al., 1985). In the Bayesian combined analysis, each gene was assigned its corresponding optimal model with independent parameters and GTR was used in place of TrNef (due to limitation in MrBayes).
The MP, NJ and Bayesian analyses of each gene separately, and for the four genes combined, resulted in similar topologies, although differences were observed. Tree topologies showed that the number of conflicts, above a Bayesian posterior probability of 95, was highest for the comparison between rpoB and mip (eight conflicts), followed by the 16S rRNA gene and rpoB (five conflicts), rnpB and mip (four conflicts) and rpoB and rnpB (three conflicts). There were two conflicts between the 16S rRNA gene sequence and mip and between 16S rRNA and rnpB.
Node support (posterior probabilities for Bayesian analyses and bootstrap proportions for MP and NJ) was used to evaluate the phylogenetic utility of the information embedded in the gene sequences. The majority rule consensus trees from the Bayesian analyses of rnpB and 16S rRNA gene sequences are shown in Fig. 2. Branches with Bayesian posterior probabilities of <0·90 are collapsed and the numbers below the branches indicate the score obtained by bootstrap analysis using NJ and parsimony algorithms.
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The phylogenetic analysis of combined datasets (one comprising rnpB together with mip and the other with all four genes) included 39 Legionella species, of which 37 had sequences available for all four genes. The phylogenetic analysis of the four genes together (Fig. 3) and rnpB together with mip (not presented) revealed very similar branching with 18 and 17 well-supported nodes, respectively, i.e. with posterior probabilities of 
0·95. The numbers of well-supported nodes in the analyses of each gene sequence alone were 13 for mip, 12 for 16S rRNA, 11 for rnpB and five for rpoB. The well-supported nodes together comprised 29 species in the analysis of all four genes, 28 species for rnpB together with mip, 25 species for rnpB, 22 species for mip, 19 species for 16S rRNA and 11 species for rpoB. Interestingly, the well-supported nodes derived from rnpB and mip gene sequences comprised more species than the well-supported nodes from 16S rRNA and rpoB gene sequences and therefore contributed most of the phylogenetic signal in the dataset including all four genes.
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; data not shown). In their presented NJ trees, there were several nodes that were in conflict compared with an analysis of mip gene sequences. In contrast, such conflicts were almost absent in our comparison between rpoB and the other gene sequences. Thus rpoB did not improve the resolution of the phylogenetic tree regarding species, but showed six nodes with significant support within the L. pneumophila species. This is more than was found for the rnpB and mip phylogeny, where only four nodes were observed. However, the rpoB tree is in conflict with current taxonomy in which serogroups 4, 5 and 15 comprise one subspecies: L. pneumophila subsp. fraseri (Brenner et al., 1988).
The results from the Shannon–Wiener analysis are presented in Fig. 4(a) as the SW index for each nucleotide position along the genes. The protein coding genes mip and rpoB have a regular high variation, mainly in nucleotides corresponding to the third position of codons, while the rnpB and 16S rRNA genes have conserved domains interspersed with variable and hypervariable regions. The proportions of nucleotide positions with certain information content are shown in Fig. 4(b) and the histograms show that the 16S rRNA gene has a lower fraction of nucleotide positions with high information content compared with rnpB.
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). In 12 cases, rnpB-based identification was in agreement with previous phenotypic determinations in a reference laboratory. Two isolates originally identified as L. micdadei had rnpB genes identical to those from L. micdadei ATCC 33218T and L. maceachernii ATCC 35300T and could not be further typed by using rnpB. For the three isolates with discrepant results, two showed rnpB sequences that were identical to type strains other than those indicated by phenotypic identification. The third isolate, 1829/00, was identified as Legionella gormanii at the reference laboratory from which it was obtained. However, here we show that the rnpB of this isolate had ten discrepant nucleotide positions compared with the rnpB of L. gormanii ATCC 33297T. The 16S rRNA gene sequence was 98·8 % similar to that of L. gormanii ATCC 33297T and sequencing of mip generated a sequence identical to that of the type strain, indicating that the correct identity of the isolate was L. gormanii.
These data suggest that the rnpB gene may be useful for the identification of most Legionella species. However, further investigation on intraspecies sequence heterogeneity is required. The 16S rRNA gene sequence is commonly used for the differentiation of closely related species. It is well-characterized for a wide variety of organisms and displays enough variable and conserved regions in order to be useful. However, 16S rRNA genes can occur as multiple heterogeneous copies in the genome (Clayton et al., 1995; Nubel et al., 1996; Ueda et al., 1999; Wang & Wang, 1997) and this can lead to misidentification, due to chimerical sequences, if this heterogeneity is not considered in the design of the assay for genotypic identification. Furthermore, recombination in 16S rRNA genes has been reported as a potential cause of erroneous species identification (Schouls et al., 2003). The 16S rRNA gene is quite large and consists of approximately 1500 bp and may therefore be laborious to sequence when full-length sequencing is necessary. The mip and rpoB genes are protein-encoding and thus the nucleotide at the third position of each codon is often variable (Fig. 4b). This results in the absence of highly conserved regions and therefore hampers the design of primers in assays for genotypic identification.
For the Legionella genus, sequencing of rnpB in combination with other genes can contribute to improved species identification and could be used in MLST. Characterization of rnpB from type strains of all known members of the genus Legionella will further determine the potential of rnpB for species identification. When compared with other genes commonly used for the discrimination of bacteria, the advantages of rnpB lie in the combination of conserved and highly variable sequence regions. Furthermore, rnpB is a single copy gene which has been shown to be useful in the differentiation of closely related bacteria (Herrmann et al., 2000; Svard et al., 1994; Tapp et al., 2003).
To conclude, the sequence variation of rnpB separated 37 of 39 Legionella species included in this study. The variation in putative secondary structures provides the possibility of understanding the interaction between RNase P RNA and the C5 protein. Phylogenetic analysis showed that rnpB clustered more species in nodes with strong branch support than did any of the other three genes, and when combined with mip the phylogenetic utility was further enhanced. Thus, the combination of strictly conserved and hypervariable elements suggests rnpB as useful for species identification and for the phylogenetic analysis of closely related species.
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) received a different assignment using rnpB gene sequences. The identification of LD170/98 and LD164/98 as L. micdadei or L. maceachernii does not receive significant posterior probability (only 0·82), despite having the identical sequence.
