Assignment of Staphylococcus aureus isolates ... - Wiley Online Library

RESEARCH ARTICLE

Assignment of Staphylococcus aureus isolates to clonal complexes based on microarray analysis and pattern recognition Stefan Monecke1, Peter Slickers2 & Ralf Ehricht2 1

Institute for Medical Microbiology and Hygiene, Faculty of Medicine ‘Carl Gustav Carus’, Technical University of Dresden, Dresden, Germany; and CLONDIAG GmbH, Jena, Germany

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Correspondence: Stefan Monecke, Institute for Medical Microbiology and Hygiene, Faculty of Medicine ‘Carl Gustav Carus’, Technical University of Dresden, Fetscherstrasse 74, D-01307 Dresden, Germany. Tel.: 149 351 458 6585; fax: 149 351 458 6311; e-mail: [email protected] Received 22 August 2007; revised 3 April 2008; accepted 4 April 2008. First published online 27 May 2008. DOI:10.1111/j.1574-695X.2008.00426.x Editor: Ewa Sadowy Keywords Staphylococcus aureus ; genomics; diagnostic DNA microarray; virulence factors; molecular typing.

Abstract A DNA microarray was designed for the rapid genotyping of Staphylococcus aureus. It covers 185 distinct genes and about 300 alleles thereof, including species-specific controls, accessory gene regulator (agr) alleles, genes encoding virulence factors, and microbial surface components recognizing adhesive matrix molecules, capsule type-specific genes, as well as resistance determinants. It was used to examine 100 clinical isolates and reference strains. Relationships of leukocidin and ssl/set (staphylococcal superantigen-like or exotoxin-like) genes were reviewed considering these experimental results as well as published sequences. A good correlation of overall hybridization pattern and multilocus sequence typing was found. Analysis of hybridization profiles thus allowed not only to assess virulence and drug resistance, but also to assign isolates to strains and to clonal complexes. Hybridization data were used to construct a split network tree and to analyse relationships between strains. Allelic variations of a number of genes indicate a division of S. aureus into three major branches that are not in accordance to agr group or capsule-type affiliations. Additionally, there are some isolated lineages, such as ST75, ST93, or ST152. These strains produce aberrant hybridization profiles, indicating that only a part of the gene pool of S. aureus has been investigated yet.

Introduction DNA microarray technology allows the simultaneous detection of a high number of molecular targets. This approach facilitates a genotype-based assessment of the virulence as well as of the antibiotic resistance of a given isolate. The overall hybridization profile could also be used as a fingerprint, or a dataset, which might allow elucidating relatedness between different isolates and allocating them to strains. For Staphylococcus aureus, the definition of strains based on its possession of genetic elements encoding pathogenic potential and antibiotic resistance or ‘genomic-island allotyping’ has already been proposed by Baba et al. (2002). Because of the high costs of array experiments, this approach has been used for research projects rather than in clinical routine laboratories, and sequence-based typing methods [multilocus sequence typing (MLST) or sequencing of repeating units within the protein A gene, spa] have widely been preferred. FEMS Immunol Med Microbiol 53 (2008) 237–251

In this study, we used a microarray-based assay for the simultaneous detection of clinically relevant virulence factors, resistance determinants, and typing markers of S. aureus. The technology used was based on multiplex linear DNA amplification. Biotin-labelled amplicons were hybridized to probes on the microarray. Hybridization was visualized by a streptavidin-horse raddish-peroxidase-catalysed dye precipitation, followed by recording and analysis. This technology has been shown to be suitable for highthroughput characterization of clinical isolates (Monecke & Ehricht, 2005; Monecke et al., 2007a) at an overall cost that is comparable to a multiplex PCR. For this study, the following major groups of genes and gene clusters have been targeted (for a complete list, see Supplementary Fig. S1). A set of probes for the discrimination of allelic variants of the agr cluster has been designed. These genes encode autoinducing peptides of a signalling pathway, which also inhibit the agr expression of other alleles, resulting in bacterial interference (Ji et al., 1997). There are four distinct 2008 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved

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groups possibly reflecting an ancient division in the evolution of S. aureus (Jarraud et al., 2002). Staphylococcal exotoxin-like or superantigen-like genes (ssl/set genes) and their gene products resemble superantigenic exotoxins in sequence homology (Williams et al., 2000) and protein structure (Al-Shangiti et al., 2004). A role in complement evasion (Rooijakkers & van Strijp, 2007) and an influence on vascular permeability (Taylor et al., 2006) have been proposed. Analysis of ssl/set genes has been obstructed by a confusing and contradictory nomenclature despite proposals for standardization (Fitzgerald et al., 2003; Lina et al., 2004). In order to use them for genomic island allotyping, it became necessary to reevaluate relationships between these genes as well as their nomenclature. Exotoxins of S. aureus have been reviewed exhaustively (Dinges et al., 2000). These virulence factors include socalled enterotoxins. Some of them are a common cause of food poisoning. For others, functional or clinical data are not yet available. Additional toxins which can cause potentially life-threatening toxicoses are the toxin shock syndrome toxin tst1 (Schlievert et al., 1981) and exfoliative toxins etA, etB, and etD (Ladhani et al., 1999). Staphylococcus aureus also produces several haemolysins and proteases as well as two-component toxins that assemble to form pores in host cells (Kaneko & Kamio, 2004). The most important factor from that class is Panton–Valentine leukocidin (PVL), which is associated with severe or chronic skin and soft tissue infections (Panton & Valentine, 1932; Kaneko & Kamio, 2004). A pandemic of PVL-positive, community-associated methicillin-resistant S. aureus (caMRSA) has been recently unfolding (Vandenesch et al., 2003), and several epidemic strains can be distinguished (Baba et al., 2002; Holmes et al., 2005; Diep et al., 2006; Monecke et al., 2007a). The proteins encoded by genes of the cap operon are involved in biosynthesis of capsular polysaccharides. Probes were designed to distinguish types 1, 5 and 8 of this operon. Staphylococcus aureus also possesses several adhesion proteins that have been referred to as MSCRAMMs (Clarke & Foster, 2006). Genes for penicillinase (blaZ), modified penicillin-binding protein (mecA, defining methicillin-resistant S. aureus or MRSA) as well as genes encoding resistance towards aminoglycosides, chloramphenicol, disinfectants, fusidic acid, lincosamides, macrolides, mercury, streptothricin, tetracyclines, trimethoprim and vancomycin were also covered by the array. The mec operon and, variably, some other resistance genes are situated on staphylococcal cassette chromosomes (SCC). These units are large mobile elements also comprising recombinase genes. Different types of SCCmec elements have been described (Ito et al., 2001, 2004; Daum et al., 2002), and probes were designed that allow the identification of SCCmec types I–VI. 2008 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved

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We reviewed published sequences of these target genes in order to facilitate probe design, and applied the resulting microarray on clinical and veterinary isolates from various countries as well as on reference strains in order to prove practically the concept of genomic island allotyping and to assign isolates to clonal complexes.

Materials and methods Bacterial isolates One hundred strains of S. aureus of all major clonal complexes were characterized (see Figs 2–6, and Supplementary Fig. S4). These included laboratory strains of S. aureus obtained from the American Type Culture Collection (ATCC, distributed by LGC Promochem, Wesel, Germany), the German Collection of Microorganisms and Cell Cultures (DSMZ, Braunschweig, Germany), the Institut Pasteur (Paris, France), and the Network on Antimicrobial Resistance in S. aureus (NARSA, Herndon, Virginia) as well as a collection of clinical and veterinary isolates from several countries (including Australia, Germany, Switzerland and the United Kingdom; see Acknowledgements). Some PVLpositive isolates and isolates of bovine origin have been described previously (Monecke et al., 2006, 2007a, b, c), but they have been included here for characterization with an expanded set of probes as well as for identification of clonal complexes and for tree construction. Sequenced strains COL, USA300-FPR3757, NCTC8325, N315, Mu50, MW2, Sanger MSSA476 and Sanger MRSA252 were also included. RF122, which is the only sequenced veterinary isolate yet, was not available for testing. Cattle isolates related to RF122 (t529 and similar spa types, Monecke et al., 2007b) were characterized instead. Staphylococcus aureus were cultured on Columbia blood agar and incubated overnight at 37 1C. Single colonies were selected and subcultured.

Preparation of genomic DNA Culture material was subjected to enzymatic lysis using lysostaphin (Sigma, Steinheim, Germany), lysozyme and RNAse A, followed by digestion with proteinase K. The detailed protocol was published previously (Monecke et al., 2007a). Subsequently, the DNA was purified using the QIAgen device EZ1 according to the manufacturer’s tissue lysis protocol.

Microarray design For each target, all relevant entries (as of January 2007) were retrieved from GenBank. One entry was selected as a reference, and its coding sequence was excised. It was blasted against the ‘NR’ database using the NCBI web service FEMS Immunol Med Microbiol 53 (2008) 237–251

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(http://www.ncbi.nlm.nih.gov/blast/Blast.cgi). BLAST hits of S. aureus were downloaded, and a local database was constructed. All coding sequences related to each target gene were excised and aligned. The program EINSI (Katoh et al., 2005) from the MAFFT software package was used to generate multisequence alignments. These alignments were inspected visually using CLUSTAL-X (Thompson et al., 1997). Split network graphs were generated from the multisequence alignments using the program SPLITSTREE 4 (Huson & Bryant, 2006) in order to reveal sequence similarities. An example is shown in Fig. 1. Based on sequence similarities, sequences were classified into paralogues and allelic variants. A symbolic name was assigned to each gene or paralogue. Allelic variants were distinguished by adding the designation of the strain harbouring that variant. The ssl genes were named with respect to their topological position on the staphylococcal chromosome as suggested previously (Lina et al., 2004). Multisequence alignments were used to identify regions with the highest possible sequence identity. Wherever possible, probes and primers were located in regions closely adjacent to each other. Probe and primer sequences were blasted against the local BLAST database in order to reveal potential cross reactions using a stand-alone version of the NCBI BLAST program (Altschul et al., 1990). To rule out hybridization between any two primers or between a labelling primer and a probe on the array, the oligonucleotide sequences were checked for their potential of pair-wise hybridizations using the program NTDPAL from the PRIMER3 software package (Rozen & Skaletsky, 2000). Probe as well as primer sequences were designed to show similar binding efficiencies. Melting temperatures were estimated using the nearest-neighbour algorithm proposed by SantaLucia (1998).

A complete list of probes and primers is provided in Supplementary Fig. S1.

Microarray-based genotyping Diagnostic DNA microarrays based on the ArrayTube platform (CLONDIAG, Jena, Germany) were utilized as described previously (Monecke et al., 2003, 2006, 2007a; Monecke & Ehricht, 2005). Probes on the array are synthetic, aminomodified oligonucleotides with an average length of 28 bases. They, as well as the primers, have been synthesized and purified by Metabion (Martinsried, Germany). An iterated linear primer elongation was used to amplify and to label all targets simultaneously (protocol 1). The primer elongation was performed using 0.27 fmol of each individual primer, 2 nmol of each, dATP, dCTP, and dGTP, 1.3 nmol dTTP, 0.7 nmol biotin-16-dUTP (Roche, Penzberg, Germany), 0.4 U Therminator polymerase (New England Biolabs, Frankfurt, Germany), c. 1.5 mg of S. aureus DNA (altogether 14.9 mL) plus 2 mL Therminator polymerase buffer (New England Biolabs). Reaction conditions comprised an initial denaturation (5 min at 96 1C), followed by 45 cycles of 60 s at 96 1C, 20 s at 62 1C, and 40 s at 72 1C. For at least one representative strain from each clonal group an additional protocol was used (protocol 2). It was a random-primed whole genome-labelling reaction (Monecke et al., 2003, 2006). It allowed detection of deviant allelic variants or truncated genes as it relied only on one conserved site within the target gene for the probe to bind. Arbitrary extension products were generated from genomic DNA over its complete length in a sequenase driven primer extension. Primers used in this step comprised a randomized 3 0 octamer and an invariant part with a defined

Fig. 1. Phylogenetic network tree showing sequence similarities of DNA sequences encoding set/ssl genes. Enterotoxins (seB, seH, seI) and toxic shock syndrome toxin (tst1) are included for comparison. GenBank accession numbers, sequences, as well as distance and similarity matrices are provided as supplementary files.

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sequence at the 5 0 end. In a subsequent reaction, these extension products were reamplified by PCR using a 5 0 biotinylated primer matching the invariant part of the primers from the first phase. Labelled amplicons from this reaction were used afterwards for hybridization. Hybridization procedures were identical for both approaches, and have been described previously (Monecke et al., 2007a). In short, the labelled sample was denatured, chilled on ice and hybridized to the array. This was followed by washing steps, and by the addition of a blocking reagent. Afterwards, 100 pg horseradish peroxidase–streptavidin conjugate (Pierce, Rockford) was added to the ArrayTube. This was followed by incubation and washing. Then, the ArrayTube was placed in the ATR01 reading device (CLONDI˙AG) and Seramun Green precipitating dye (Seramun, Heidesee, Germany) was added. After 5 min, a picture of the array was recorded and analysed.

Data interpretation Local precipitation of dye results in clearly visible spots, which can be read by superimposing a coordinate grid over a digital picture of the processed array. The presence of spots is regarded as positive and absence as negative. In order to facilitate computerized data interpretation, the following algorithm was developed and tested using sequenced strains for validation. Dye precipitation results in a local decrease of light transmission. The average signal intensities of the spots and their local backgrounds were determined using the ATR01 reading device, ICONOCLUST software (CLONDI˙AG) and an adapted script for the actual assay and array layout. Normalized intensities of the spots were calculated according to the following equation: NI ¼ 1 ðM=BGÞ with NI being the normalized intensity, M the average intensity of the spot, and BG the intensity of the local background. Results may range between 0 (no signal) and 1 (maximal signal). A breakpoint was defined based on 33% of the average value for staining controls (biotin-labelled DNA immobilized on the array) and positive species markers (ribosomal probes, femA, gapA, katA, coa, spa, sbi, eno, nuc, fnbA, sarA, and vraS). This definition was based on the visibility of spots on the array. If this value was above a predefined threshold, the complete assay was considered to be valid; otherwise, it was to be repeated. If a given probe yielded a signal intensity higher than the breakpoint, the corresponding target was regarded as present; otherwise, it was considered to be absent. Results were regarded as ambiguous if the measured intensity was between 25% and 33% of the controls and if visual inspection of the scanned array confirmed the presence of a spot. 2008 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved

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For some genes, allelic variants differing only by single nucleotides are known, and analysis of all fully sequenced genomes showed that there is only one allelic variant of any of these genes present in a given genome. If such a gene was present, probes for all its allelic variants would yield positive signals of varying intensity. For these genes (some MSCRAMM and ssl genes), that allelic variant was regarded as present for which the corresponding probe yielded the strongest signal. For ssl1, four probes recognizing two distinct binding sites were designed, and determination of ssl1 alleles resulted from the combination of positive results (see Supplementary Fig. S1).

Typing methods Allelic variants of agr were determined by microarray hybridization using the probes listed in Supplementary Fig. S1. Typing based on spa sequences was performed according to published protocols (Harmsen et al., 2003) using the software SPATYPEMAPPER (freeware, download at http://www.clondiag.com/technologies/download.php?file= spa). MLST was performed as described previously (Enright et al., 2000).

Split network tree construction A split network tree was used to visualize similarities between hybridization patterns. The results of all array hybridization experiments were arranged in a matrix where the columns represent the target genes and the rows represent the experiments. The hybridization results only from primer-directed protocol 1 were converted into ‘sequences’ using ‘A’ for positive and ‘T’ for negative results. Ambiguous results were treated as negative, in order to avoid arbitrary interpretations. Protocol 2 data were not considered as this protocol was used for representatives of all clonal complexes, but not for every single isolate. Thus, the matrix was converted into a series of ‘sequences’. These were used for tree construction using SPLITSTREE 4 (Huson & Bryant, 2006) software (characters transformation, uncorrected P; distance transformation, Neighbour-Net; and variance, ordinary least squares).

Results For the design of the assay, it was necessary to review nomenclature as well as allelic variation especially of enterotoxin and leukocidin genes and of ssl/set genes. The bioinformatic analyses and data from the literature were then compared with experimental data obtained from microarray experiments with reference strains and clinical isolates. Complete hybridization profiles are given in Supplementary Fig. S4. A concise overview is given in Figs 2–5. For the sake of conciseness, isolates were merged into FEMS Immunol Med Microbiol 53 (2008) 237–251

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Fig. 2. Presence of agr, ssl/set and hsdS genes in the studied strains. Black circles indicate positive results and divided circles indicate variable results in different isolates of one strain. White circles indicate ambiguous results, and grey circles indicate genes for which the presence of deviant alleles has been proved by alternative methods (protocol 2 or PCR).

strains. Genes, which were either positive or negative in all strains tested, were omitted. Finally, the phylogeny of the studied strains and isolates was analysed based on hybridization profiles. A split network tree was constructed based on these data in order to verify whether similarity of hybridization profiles translated into phylogenetic relatedness as determined by MLST (Fig. 6).

Analysis of the agr genes Ninety-nine S. aureus strains or isolates were assigned to the four agr groups (Jarraud et al., 2002). The agr group of one single strain, a ST75-MRSA IV from Australia, was not determined as it yielded no signal with any of the agr probes (Fig. 2). A cluster of different clonal complexes (ST7, CC8, CC20, CC25, CC97, ST101, and ST239) with rather similar hybridization profiles belonged to agr group I. ST22 and ST45 also belonged to that group. However, they gave distinct hybridization profiles, and they appeared to be more similar to CC30 (agr group III) than to other agr group I strains (Fig. 6). Other agr group I lineages included CC59 (includFEMS Immunol Med Microbiol 53 (2008) 237–251

ing some caMRSA), CC133, ST152 (a caMRSA from the Balkans), ST398 (Cuny et al., 2006; Huijsdens et al., 2006; de Neeling et al., 2007) and ST426. Four distinct lineages belonged to agr group II. One lineage comprised CC5, including N315, Mu50, South German EMRSA and Rhine–Hesse EMRSA (EMRSA-3). A second one consisted of a group of cattle isolates related to sequenced strain RF122 (ST151). Isolates of CC12, CC15 and ST913 formed a third lineage. A fourth one comprised CC10. It showed a higher similarity of its hybridization profiles to CC30 than to other agr group II strains. Strains of agr group III clustered into three distinct groups. The first cluster was represented by ST1, ST80, and CC78, whose overall profiles were related to MSSA467 and MW2. Their relatedness was also confirmed by the similarity of their spa types (Monecke et al., 2006, 2007a). The second cluster consisted of CC30. A third lineage comprised only the Queensland Clone (ST93), an unique caMRSA from Australia. ST121 was the only representative of agr group IV. Hybridization profiles from this group appeared to be similar to the bovine ST151 complex, which belonged to agr group II. 2008 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved

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Fig. 3. Presence of genes encoding superantigens, leukocidins as well as of miscellaneous virulence factors and extracellular enzymes in the studied strains. Coding of results as in Fig. 2.

Fig. 4. Presence of capsule- and biofilm-associated genes, and of MSCRAMM genes. Coding of results as in Fig. 2.


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Fig. 5. Presence of resistance genes and of genes associated with SCCmec elements. Black circles indicate positive results and divided circles indicate variable results in different isolates of one strain.

Analysis of the ssl/set gene clusters An overview of the topological ordering, of the proposed nomenclature and of hybridization probes is given in Supplementary Fig. S3 and hybridization results are shown in Fig. 2. The main ssl/set cluster comprises up to 11 genes. It is part of a highly variable region called RD13 (Williams et al., 2000; Fitzgerald et al., 2003), genomic island nSaa (in sequenced strain MW2), SaPIn2 (N315), or SaPIm2 (Mu50). This cluster is present in all strains sequenced so far, but individual genes are variable, resulting in a complex pattern of strain-specific deletions and allelic variants (Fitzgerald et al., 2003). Sequences from MW2 and N315 are basically identical to each other, as are sequences of MW2 and MRSA476. Sequences of COL, USA300, and NCTC8325 were also very similar, although ssl5 to ssl8 are deleted in COL. These similarities allowed to design consensus probes for ssl2, ssl3, ssl4, ssl5, ssl6, ssl8, ssl9 and ssl10. For ssl1 and ssl11, probes were designed that distinguish allelic variants of ST1, CC5, and CC8. An additional allele of ssl7 has been sequenced previously in strain FRI326 (GenBank AF188836). The ssl/set genes of MRSA252 can be differentiated clearly from those of other sequenced strains. While being distinct, they are occupying the same positions in the ssl/set cluster, MRSA252-like ssl/set genes can be regarded as allelic variants. For example, SAR0423 corresponds to ‘set7’ from Mu50 as well as to ‘set17’ from MW2. An exception is ssl4MRSA252, which is more closely related to ssl3 than to ssl4 FEMS Immunol Med Microbiol 53 (2008) 237–251

(see Fig. 1 and Supplementary Fig. S2). Generally, analysis of ssl/set genes and of their surroundings set MRSA252 apart from other S. aureus genome sequences. With regard to ssl/ set genes, all CC30 isolates gave hybridization patterns identical to MRSA252 and clearly discernible from other clonal complexes (Fig. 2). We also focused on a locus comprising three paralogues (SACOL1178–1180) that are located adjacent to each other, presumably forming a transcription unit. The cluster is located approximately at position 1 100 000 of an S. aureus chromosome. Properties and function have not yet been studied. These genes are basically identical in all sequenced strains but MRSA252. In that strain, there are similar genes, SAR1139–1141, which could be regarded as allelic variants. Probes for SACOL1180 and SAR1141 proved to be crossreactive because they differed in single nucleotide polymorphisms only. The sequence similarity tree (Fig. 1) shows a common origin of the three setB genes, setting them apart from ssl genes. For this reason, we propose to name them in the direction of transcription setB3, setB2, and setB1, and to discern allelic variants from MRSA252. These genes are located in a pathogenicity island nSag (Gill et al., 2005), which also comprises hla and two genes encoding phenol-soluble modulins (SACOL1186, SACOL1187). The topological order of these genes is conserved in all chromosomes, but MRSA252 carries a transposase gene, which is inserted between hla and setB3. Another gene (MW0345) was found to be similar to tst1 and to ssl/set genes. We propose to name it setC. The setC 2008 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved

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Fig. 6. A split network tree constructed from the hybridization results of 100 reference strains, clinical and veterinary isolates. Multilocus sequence types and agr groups are indicated. Strains are numbered as follows (sequenced strains in bold): 1, Sanger MSSA 476; 2, ST1-MSSA; 3, MW2; 4–6, clinical ST1-MRSA IV isolates; 7, ST1-MRSA V; 8 and 9, CC5-MSSA; 10 and 11, CC5/ST228-MRSA I; 12, Mu50; 13, N315; 14–17, ST5-MRSA II; 17, CC5MRSA IV; 18, ST7-MSSA; 19, NCTC8325; 20–27, CC8-MSSA; 28, COL; 29–33, various CC8-MRSA IV; 33 and 34, ST254-MRSA IV (Hannover EMRSA); 35, USA300-FPR3757; 36 and 37, PVL-positive ST8-MRSA IV (USA300) isolates; 38, CC8-MRSA V; 39 and 40, ST239-MRSA III; 41 and 42, CC10-MSSA; 43, CC12-MSSA; 44, CC15-MSSA; 45 and 46, CC20-MSSA; 47, ST22-MSSA; 48 to 50, ST22-MRSA IV (Barnim EMRSA/ERMSA-15); 51, PVL-positive ST22-MRSA IV; 52 and 53, CC25-MSSA; 54–56, PVL-negative CC30-MSSA; 57, ATCC 25923; 58, PVL-positive CC30-MSSA; 59, Sanger MRSA 252; 60, ATCC 43300; 61 and 62, ST36-MRSA II (EMRSA-16); 63 and 64, PVL-positive ST30-MRSA IV; 65, ST45-MSSA; 66–68, ST45-MRSA IV; 69, CC59MSSA; 70 and 71, PVL-positive CC59-MRSA V; 72, ST75-MRSA IV; 73, PVL-positive CC78/ST88-MRSAIV; 74 to 76, PVL-positive ST80-MRSA IV; 77, PVLpositive ST93-MRSA IV; 78 and 79, CC97-MSSA; 80, ST101-MSSA; 81–84, PVL-negative ST121-MSSA; 85 and 86, PVL-positive ST121-MSSA; 87, CC133-MSSA; 88–93, bovine ST151-MSSA; 94, PVL-positive ST152-MRSA V; 95, ST398-MSSA; 96 and 97, ST398-MRSA V; 98 and 99, ST426-MSSA; 100, ST913-MRSA IV.

locus is flanked by highly conserved genes. The rpsF, ssb, and rpsR genes, encoding ribosomal proteins, and a singlestranded DNA-binding protein are preceding on the upstream side, while SACOL0443 and SACOL0444 are found downstream. The function of the latter has not yet been elucidated. The gene setC was present in most clonal complexes, but it was not detectable in CC30 and ST152 (Fig. 2). In MRSA252, the setC gene and adjacent genes are replaced by a mobile element, SaPI4 (Holden et al., 2004). This 15 153 bp island comprises a stretch of 6400 bp that is also present in phage phiPT1028, AY954948.1 (Kwan et al., 2005).

Analysis of hsdS genes These genes encode a type I site-specific DNAse subunit. Sequenced S. aureus genomes contain one, two, or three 2008 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved

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copies at different positions in the genome. One locus (SAB0265) is known from the bovine sequence strain RF122. It was detectable only in some, but not all, veterinary ST151 isolates (Fig. 2). Sequence-type specific allelic variants of hsdS genes corresponding to a second locus (e.g. SACOL0477) within the main ssl/set gene cluster and to a third locus (e.g. SACOL1861), usually accompanying leukocidin genes lukD/E, were more widespread. ST45 strains yielded no hybridization signals for alleles of the third hsdS locus and leukocidin genes lukD/E. CC30 strains harbored a distinct allelic variant (SAR1898) and lacked lukD/E. ST80 and ST398 harboured deviant sequences (corresponding to AB057421 and DQ309450, respectively), yielding no hybridizations to probes based on hsdS sequences from sequenced strains. Thus, the positions of hsdS genes in their genomes are not yet known. FEMS Immunol Med Microbiol 53 (2008) 237–251

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Analysis of enterotoxin genes Known clusters or pathogenicity islands (seb1sek1seq, sek1seq, sed1sej1ser, tst11sec1sel, sec1sel and the egccluster: seg1sei1sem1sen1seo1seu/y) have been detected in several unrelated clonal complexes (Fig. 3). Significant sequence variations of enterotoxin genes were noted mainly in the sea gene. BLAST search revealed three allelic variants. One was present in two sequenced strains: Mu50 and MW2. It also occurs in a variety of isolates from different clonal complexes including ST1, CC5, CC8, CC30 and ST426. A second variant is defined by sequence AY196686.1 from strain 320E. It has not been found in any studied isolate. A third allele, also known as enterotoxin P (Kuroda et al., 2001), is carried by sequenced strain N315. It was found in clinical isolates of the related Rhine–Hesse EMRSA (EMRSA-3, ST5MRSA II), as well as in ST7 and CC12 (Fig. 3). For sen as well as for tst1, divergent sequences have been detected from cattle isolates using random amplification (protocol 2), PCR, and subsequent sequencing (Monecke et al., 2007b). The genome sequence of the bovine strain RF122 shows similar allelic variants of these genes. ORF CM14 from U10927.2 was regarded as an enterotoxin-like protein because of sequence similarity. It is present in sequenced strain RF122 (SAB0026), and it was found in CC12, ST93, ST121, ST151 and ST426 isolates. A putative enterotoxin homologue (SACOL1657) was present in all sequenced strains, and experimentally it was detected in all clonal complexes, except ST75 and ST93.

Analysis of leukocidin genes and of other virulence factors Several bicomponent leukocidins are known to occur in S. aureus. Studied genes from this group are lukD/E, lukFPV83/lukM, lukF/S-PVL and lukF/S (1hlgA). Two other genes are annotated as leukocidin homologues (SAV2004/ 05, SA1812/13, MW1941/42, SAS1924/25, SACOL2004/05, SAR2107/08). They will be designated as lukX/Y. Leukocidin genes lukD/E are always located at the same position, forming a pathogenicity island with hsdS, hsdM, splD, splA, epiG, epiA and variable enterotoxin genes. They are present in all sequenced strains, except in MRSA252. This is mirrored by our experimental data (Fig. 3). Indeed, lukD/E were not found in any CC30 isolates. In a number of other strains, hybridization experiments indicate the presence of yet unsequenced alleles showing positive results only in protocol 2 experiments (ST93) or for one component only (ST121). The sequence of lukF-PV83/lukM is slightly more closely related to lukD/E than to lukF/S-PV. Leukocidin genes lukFPV83/lukM were found only in isolates from cows. Most isolates harbouring these genes were related to sequenced strain RF122 (agr group II/ST151). RF122 and related FEMS Immunol Med Microbiol 53 (2008) 237–251

isolates additionally contain lukD/E. This allows the assumption that lukF-PV83/lukM is not a mere host-specific (bovine) variant of lukD/E. Both lukF-PV83/lukM as well as lukF/S-PV are flanked by prophage sequences being accompanied by genes encoding holin and amidase. In MW2 and USA300, the complete structure of a prophage including an attachment site within gene Q1Y416 is recognizable. In RF122, a cluster of genes for holin, amidase, and lukF-PV83/lukM is present; other genes from the phage are absent. PVL genes lukF/S-PV have been detected in highly diverse lines of S. aureus (Baba et al., 2002; Holmes et al., 2005; Diep et al., 2006; Monecke et al., 2007a). In contrast to lukD/E and lukF/S (1hlgA), no evidence for significant sequence variation was found. Leukocidin/haemolysin gamma genes lukF/S and hlgA (hlg genes) were found in all sequenced strains. In ST22, hlg genes were detectable under low stringency conditions only, indicating a possible presence of an unsequenced allele. ST45 did not yield hybridization signals for lukS. PCR (using primers 5 0 -AGTTGATAATGGTCAATTGTTAATGA3 0 and 5 0 -GCAGTACCAGAAAGTAATAATAATGC-3 0 ) and sequencing revealed the presence of deviant variants in ST45 (GenBank EF672356). Thus, a new probe (5 0 -CACTGCATC AGGTCAAAAGTCAGC-3 0 ) and new primers (5 0 -CCTACG AATAAATCGCTATCA-3 0 and 5 0 -TCCTACGAATAAATCA CTATCA-30 ) were designed, allowing the detection of lukS in ST22 and ST45. In ST152, lukF and hlgA were detectable by protocol 2 only. The hlg locus was not found in ST75 and ST93. Leukocidin homologues lukX/Y cluster together with hlb, but whether these genes form a functional unit still needs to be clarified. Known sequences for lukY allowed to distinguish between two allelic variants. One variant originated from the MRSA252 genome sequence, and experimentally it was found in CC30 as well as in ST45. The other one was present in nearly all the remaining strains. In ST75, neither lukX/Y nor hlb was detected. In the genome of COL, lukX/Y and hlb are adjacent because in that strain hlb is not interrupted by a phage insertion. In strains carrying such an insertion, the distance between primer- and probe-binding sites would increase from 17 or 18 bp to more than 40 000 bp (phage phi13 provirus, GenBank NC_004617), rendering hlb detectable only by protocol 2. Intact hlb and sak usually were mutually exclusive. This also applied to genes scn (staphylococcal complement inhibitor), enterotoxin A (sea) and chp (encoding chemotaxis inhibitory protein, CHIPS), which, in different combinations (van Wamel et al., 2006), are also encoded by prophages.

Analysis of capsule genes All tested strains except for the ST75-MRSA IV isolate belonged to capsule types 5 or 8 (Fig. 4). ST75-MRSA IV 2008 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved

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yielded no hybridization results with any of the probes for capsule genes. Capsule type 1 was not detected. There was no correlation of agr group and capsule type. While all tested agr group III and IV strains belonged to capsule type 8, agr groups I and II comprised of isolates belonging to either capsule type. All strains and isolates of a given clonal complex belonged to the same capsule type. The only exception was ST239, which belonged to capsule type 8 rather than to type 5 as other CC8 strains. This, as well as MLST, spa type and some other hybridization results suggest the insertion of a large chromosomal fragment from CC30 (Robinson & Enright, 2004).

Analysis of MSCRAMM genes The probes and primers for MSCRAMM genes were designed to bind to the most conserved regions of the coding sequence. The array hybridizations were run under stringent conditions and usually no signals were detectable if probe sequences deviated from their binding sites at more than three positions. Probe-binding sites were selected from multisequence alignments of all sequences available in GenBank. Among the available sequences, there were no universally conserved oligonucleotide-binding sites for bbp, fib, fnbA, fnbB, map and vwb. The alignments revealed that the sequences of the nonrepeating regions of MSCRAMM genes vary slightly, usually allowing discrimination of allelic variants being specific for clonal complexes. Probes and primers were selected to bind within such regions. The array was not designed to discriminate the highly variable sequence stretches or repeating units. This design must be kept in mind when interpreting the results of the hybridization experiments. In this work, we use the symbol bbp for several allelic variants of the bone sialoprotein-binding protein although variants from COL, Mu50 and MW2 have been named sdrE previously because of the presence of a serine–aspartate (SD) repeat. Most MSCRAMM genes were widely distributed and occurred in nearly all clonal groups, but several genes like clfA, icaA/C/D, ebh, ebpS, map and vwb were not detectable in ST75-MRSA IV. Two MSCRAMM genes, cna (encoding collagen adhesin) and sasG (Staphylococcal protein G, with two different alleles), occurred only in some clonal complexes (Fig. 4). Some isolates showed deletions of MSCRAMM genes. For instance, bbp, clfA (clumping factor A) and fnbB (fibronectin-binding protein B) are usually present in clonal group 5 strains. However, both isolates of the South German EMRSA (CC5/ST228-MRSA I) lacked fnbB, one of them lacked bbp, and the other one was negative for clfA. Similarly, NCTC 8325 and the ‘Hannover EMRSA’ (CC8/ST245-MRSA IV) lacked bbp, which otherwise was present in CC8 strains, and 2008 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved

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about half of the tested CC30 strains (including MRSA252) were negative for fnbB.

Antibiotic resistance determinants The only resistance determinant that was specific for certain clonal complexes was chromosomal fosB (metallothiol transferase, fosfomycin resistance), which was present in CC5, CC8, CC12, CC15, CC20, CC25, CC30 and ST75. All other antibiotic resistance determinants have been found to be highly promiscuous (Fig. 5). For instance, mecA was detected in most clonal complexes, notable exceptions being ST121 and ST151. Other resistance genes are similarly widespread. Many resistance determinants regularly occur in fixed combinations, some of which are known to be situated on chromosomal cassettes (Ito et al., 2001), transposons (e.g. aphA31sat, Werner et al., 2001), or plasmids (e.g. blaZ1tetK1far1, Monecke et al., 2006). While none of the genes involved proved to be characteristic for a clonal complex, such sets of resistance genes might differ between otherwise related strains. For instance, the South German EMRSA carried aphA3 and sat, which were absent in the related Rhine–Hesse EMRSA (EMRSA-3). SCCmec typing was performed by detection of recombinase genes (ccrA, B, C) and accessory genes of SCCmec cassettes. SCCmec type I was assumed if crrA1, crrB1, truncated mecR (delta mecR), plsSCC-COL (SACOL0050, plasmin-sensitive surface protein) and the dcs region (Q9XB68, SACOL0029) were detected. SCCmec type I was present in COL and in the South German EMRSA. SCCmec type II was identified based on the detection of crrA2, crrB2, mecI, untruncated mecR, the kdp operon (kdpA to kdpE), xylR and, variably, the dcs region. Resistance genes aadD and ermA were not considered to be necessary for the identification of SCCmec II because of their variable occurrence. SCCmec type II was present in Rhine–Hesse EMRSA (EMRSA-3, including Mu50 and N315) and EMRSA-16. SCCmec type III yielded positive hybridization results with probes for crrA3, crrB3, mecI, xylR and untruncated mecR. Genes tetK and ermA were variable. The mercury resistance operon (merA, merB, merR, merT) was also found in isolates of other SCCmec types. Probes designed for determination of an atypical SCCmec unit originally described as type III from strain 85/2082 (GenBank AB037671) were designated ccrAA because of similarity to ccrA. They proved to cross-react with both SCCmec types III and V. SCCmec III was restricted to ST239. SCCmec type IV was similar to SCCmec type II, but kdp probes did not yield positive signals. This SCCmec type was found in a great diversity of strains, both community and hospital acquired. Identification of SCCmec type V was based on the reactivity of probes for ccrAA (with a probe based on the FEMS Immunol Med Microbiol 53 (2008) 237–251

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sequence of MRSAZH47, GenBank AM292304.1) and ccrC (based on strain 85/2082, AB037671), although the latter also cross-reacted with ccrB3. In SCCmec type V isolates, truncated mecR was absent. SCCmec V elements were found in some, unrelated caMRSA. SCCmec type VI was not found in this study. Three methicillin-susceptible strains also harboured SCC elements without being positive for mecA. These included a CC8 MSSA (ccrA/B-2-positive) as well as the sequenced strain MSSA 476 and a PVL-positive ST1 isolate (ccrA/B-1positive). Both harboured a gene encoding a putative fusidic acid resistance protein (SAS0043), which, according to MSSA476 sequence data, belongs to a mecA-negative SCC element. Interestingly, an ST1-MRSA strain was also found, which obviously carried two SCC elements, ccrA/B-1 and SAS0043 as well as ccrA/B-2 and mecA.

Analysis of phylogenetic relations between isolates strains and clonal complexes Hybridization profiles were used to construct a split network tree to visualize similarities or relationships between strains and isolates. This network tree is presented in Fig. 6 (least square fit 99.25), and a modified version of this figure indicating bootstrapping values is provided in Supplementary Fig. S5. Generally, there is a good correlation of hybridization pattern and MLST/spa type resulting in fairly stable hybridization profiles for all isolates of a given MLST/spa type. It is possible to recognize strains as related even if they differ in mobile genes such as resistance determinants, enterotoxin or PVL genes. For instance, all CC8 isolates cluster together, regardless of whether they carry SCCmec elements or PVL (Fig. 6). Thus, the similarity of hybridization profiles translates into a phylogenetic relationship, and it is possible to assign a given isolate to MLST-based clonal complexes by analysing its hybridization profile. This facilitated to develop a computerized pattern match algorithm for the identification of related strains (Partisan Array LIMS, CLONDIAG). Our data indicate a split of S. aureus into three large clusters. This resembles the results of a phylogenetic analysis based on MLST and additional sequences polymorphisms (Cooper & Feil, 2006). These clusters were not identical to agr groups (‘Analysis of the agr genes’, and Fig. 6) or capsule types (Fig. 4). Within the largest cluster, three lineages could be distinguished. CC5, CC20, CC25, and CC97 appear to be closely related. CC8 including ST239 forms a second lineage. ST1, ST7, CC12, CC15, ST80, CC88, ST101, and ST913 represent a third line. With the exception of ST101, strains of this lineage have related spa types. CC59, ST121, CC133, and ST151 form a second large cluster. ST10, ST22, CC30, ST45, ST398 and ST426 comprise a third one. Additionally, there are a few isolated lineages (ST75, ST93 and ST152), FEMS Immunol Med Microbiol 53 (2008) 237–251

that appear to be associated with this cluster. However, they produce irregular hybridization patterns and harbour deviant alleles of several genes as shown in random-primed protocol 2.

Discussion The definition of strains based on the presence of genetic elements encoding pathogenic potential or antibiotic resistance, i.e. on genomic island allotyping (Baba et al., 2002) has a certain appeal to a clinical microbiologist. These properties are of direct consequence for patient care. However, due to the high number of relevant genes, genomic island allotyping by PCR is impractical, time consuming, and expensive. For these reasons, we developed an array that can be used for high-throughput isolate characterization even in clinical routine laboratories that do not have resources to perform experiments with high-density wholegenome arrays such as described by Lindsay et al. (2006). Genes were selected either to encode clinically relevant information or to be of use for typing purposes. The present array proved to be a suitable tool for assessing the resistance and virulence of isolates as well as for their assignment to clonal complexes and strains by recognition of hybridization patterns. On DNA microarrays as described above, S. aureus produces group-specific hybridization patterns in accordance to clusters or clonal complexes as defined by other methods, such as MLST- or spa typing. These methods are based on the concept that sequence variations monitored at a small number of genomic loci correlate with the overall genotype of the core genome. In contrast, our microarray monitors about 200 loci in parallel, which are scattered all over the genome of S. aureus. The resolution for each probe is rather low, but due to the large number of presumably redundant features, the hybridization profiles correlate well with clonal complex affiliation. Discrimination is not based on nucleotide polymorphisms, but on detection of allelic variants, of group-specific genes or gene clusters, of gene deletions (such as of ssl genes from COL, or fnbB from the South-German EMRSA) and on detection of variable elements. Our data show that these features correlate well with affiliations to clonal complexes as well as to strains within these complexes. Hybridization profiles also include data on virulence and drug resistance determinates. These genes usually cannot be expected to correlate with clonal complex affiliation, but they can be considered to be evolutionary recent variations mediated by mobile elements such as SCC elements, plasmids or phages. Strains are recognized to be related even if they differed in such genes. For instance, clinical ST1 isolates as well as MW2 and MRSA476 produced highly similar hybridization profiles, but differ in carriage of SCC elements, PVL or enterotoxins C and L. 2008 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved

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Variations affecting such variable elements occur on a strain or even on an isolate level rather than on a level of MLST types, and the high number of such genes enables a high resolution of strains within clonal complexes. This is especially valuable for epidemiological purposes. While the array did not discriminate single locus variants of MLST or spa types (such as t007, t012 or t018 within EMRSA-16), a comparatively high resolution of strains and variants can be achieved by the detection of random deletions (such as of bbp or clfA from the South German EMRSA), or of variability affecting accessory resistance determinants (e.g. blaZ1tetK1far1 and linA in ST80-MRSA IV, or ermC in EMRSA-15) or enterotoxins (e.g. sec1sel in EMRSA-15). Thus, another significant potential of the array lies in the ability to compare related strains in order to detect newly emerging variants resulting from the acquisition of new resistance or virulence determinants. In some cases, hybridization patterns indicated deviations from known sequences, pinpointing targets for further sequence analysis. For instance, the apparent lack of lukS in ST45 isolates was interpreted as indication for an aberrant lukS sequence. This was proved by PCR and sequencing (GenBank EF672356). Similarly, divergent tst1, sen, lukE, and splA have been found in bovine isolates (Monecke et al., 2007b). Among ssl/set genes, several new sequences can be expected. Examples are ST22 (cross-reactivity between alleles of ssl2 and ssl5) or ST93 and ST152 (protocol 2 detected more ssl/set genes than protocol 1). All these data show that previously sequenced strains do not fully reflect the genetic diversity of S. aureus. While strains such as Mu50 and N315, or MW2 and MSSA476, are closely related to each other, the presence of clonal complexes such as ST22, ST45 and especially of ‘aberrant’ strains ST75, ST93 and ST152 proves that the gene pool of S. aureus has only partially been investigated. Therefore, it would be interesting to sequence such strains, and the technique described in the present study can be used to pinpoint rewarding target strains for further sequencing projects. An abundant germ, such as S. aureus, probably features a genetic diversity that no assay and no sequence database realistically can be expected to cover completely. Contrary to other nucleic acid-based assays, diagnostic DNA arrays can be designed to allow proof-reading by generating enough information to check results for genes missed from known clusters, and it can be used to actively screen isolates for conspicuous variations. The use of genome-wide random amplification and labelling (protocol 2) and lowstringency conditions for hybridization are further options to detect the presence of as yet unknown allelic variants of a given gene. In order to analyse similarities of hybridization patterns, they were used for network tree construction. Because strains or isolates belonging to one MLST-defined clonal 2008 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved

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complex and/or to related spa-types were observed to be situated on neighbouring branches of such a tree (Fig. 6), it was inferred that similarity indeed meant phylogenetic relatedness. The clustering of clonal complexes resembles the topology of trees constructed by Cooper and Feil using sequences of seven or 37 genes scattered all around the chromosome (Feil et al., 2003; Cooper & Feil, 2006). Cooper and Feil also clustered ST10, ST22, CC30 and ST45 (‘Group 1a’) as well as ST59 and ST121 (‘Group 1b’) apart from the others, e.g., ST1, CC5 and CC8 (‘Group 2’). This similarity of the proposed phylogenetic trees is especially remarkable, because they result from entirely different approaches. In conclusion, the overall profile of the genes (many of them being highly mobile) targeted by our study comprises basically the same phylogenetic information as a set of housekeeping genes and the polymorphisms therein. The position and origin of apparently aberrant strains (ST75, ST93, ST152) deserves further study. An interesting issue in the phylogeny of S. aureus is the relationship between agr groups and genomic cluster allotypes (Fig. 6). Originally (Jarraud et al., 2002), it was proposed that S. aureus is split along the lines of agr groups, giving them some kind of subspecies status. Similar to as MLST data (Robinson et al., 2005), our results do not support this concept. The agr groups I–III encompass very diverse strains, and the only agr group that appears to be really homogenous was group IV. These findings allow at least two interpretations. One possibility (as discussed in Robinson et al., 2005) is that the split into agr groups I–III was indeed an ancient event occurring earlier than another split into two distinct groups. One of them comprised basically of ST22, CC30 and ST45, and the other one of the remaining strains. The agr group IV later might have evolved from the latter group. Another possibility is that an ancient diversification of S. aureus also included a diversification of agr groups. The mutual incompatibility of strains with different agr loci (Ji et al., 1997) might have led to an extinction of some agr alleles and in other cases to the acquisition of similar agr sequences by unrelated strains by means of convergent evolution and/or recombination. The agr groups I–III might have evolved in this way from a variety of unrelated ancestors, while only agr group IV could represent a truly monophyletic group. The lack of a correlation between agr group affiliation, sequence type and capsule type might indicate the ‘shuffling’ of genomic DNA by recombination events affecting large portions of chromosomal DNA. Indeed, recombination events of such a scale can occur in S. aureus. Robinson & Enright (2004) described ST239 to be derived from CC8 and CC30. Two studied isolates belonged to ST239. They had hybridization profiles similar to typical CC8 strains, but displayed a CC30-like spa type (t037) as well as the presence of other genes from that clonal complex (aur-MRSA252, FEMS Immunol Med Microbiol 53 (2008) 237–251

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cna, capsule type 8). Microarray technology might help to find further evidence for such recombination events, for instance, if hybridization profile and MLST/spa types of an isolate did not match together. The observation that unrelated strains on all major branches of the phylogenetic tree contain genes such as, e.g., lukS/F-PVL or mecA, and that even large gene clusters such as egc appear in unrelated strains highlights the practical relevance of a variety of mobile elements in S. aureus. As genes that are localized on mobile elements can either be acquired or lost within a short time, genomic island allotyping can only work reliably if a high number of genes are scrutinized. This practically demands a DNA microarray approach that can be used under routine conditions not only to obtain clinically relevant information, but also to assign a given isolate to clonal complexes.

Acknowledgements We acknowledge Antje Ruppelt, Ines Engelmann, Hanna Kanig, Susann Kolewa, Elke Müller and Jana Sachtschal for excellent help and technical assistance. Vico Baier developed software used for this work. We thank Prof. Enno Jacobs and the Vice-Rectorate for Research of the Medical Faculty Dresden for supporting this work. We also thank Karsten Becker (Muenster, Germany), Brigitte Berger-Bächi (Zürich, Switzerland), Geoffrey Coombs (Perth, Australia), Matthew Ellington (London, UK), Anne Holmes (London, UK), Helmut Hotzel (Jena, Germany), Angela Kearns (London, UK), Peter Kuhnert (Bern, Switzerland), Hans-Jörg Linde (Regensburg, Germany), Francis O’Brien (Perth, Australia), Wolfgang Witte (Wernigerode, Germany), the Institut Pasteur, Paris, and the Network on Antimicrobial Resistance in Staphylococcus aureus (NARSA) for supplying strains and typing data.

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Supplementary material The following supplementary material for this article is available online: Fig. S1. Targets, primers and probes. Fig. S2. Accession numbers, sequences, distance and similarity matrices used for Fig. 1.


Fig. S3. Nomenclature, synonyms and topological order of sequenced ssl/set genes. Fig. S4. Full hybridisation data for all isolates. Fig. S5. Bootstrap values (1.000 iterations) for the network tree from Fig. 6. This material is available as part of the online article from: http://www.blackwell-synergy.com/doi/abs/10.1111/ j.1574-695X.2008.00426.x (This link will take you to the article abstract). Please note: Blackwell Publishing is not responsible for the content or functionality of any supplementary materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.


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