Development of a New Oligonucleotide Array To Identify Staphylococcal Strains at Species Level
http://www.100md.com
微生物临床杂志 2005年第8期
INRA—Centre de Clermont-Ferrand-Theix, UR 370, Microbiologie, 63122 Saint-Genes Champanelle
Centre Hospitalo-Universitaire, Laboratoire de Bacteriologie, 28 place Henri Dunant, 63001 Clermont-Ferrand, France
ABSTRACT
The genus Staphylococcus is made up of 36 validated species which contain strains that are pathogenic, saprophytic, or used as starter cultures for the food industry. An oligonucleotide array targeting the manganese-dependent superoxide dismutase (sodA) gene was developed to overcome the drawbacks of the conventional methods of identification. Divergences of the sodA gene were used to design oligonucleotide probes, and we showed that each of the 36 species had a characteristic pattern of hybridization. To evaluate the array, we analyzed 38 clinical and 38 food or food plant Staphylococcus isolates identified by the phenotype-based system VITEK 2 (bioMerieux). This commercial kit failed to identify 8 (21%) of the clinical isolates and 32 (84%) of the food and food plant isolates. In contrast, the oligonucleotide array we designed provided an accurate and rapid method for the identification of staphylococcal strains, isolated from clinical, environmental, or food samples, at species level.
INTRODUCTION
Staphylococci are widely spread in various niches such as clinical environments and food plants. Thirty-six validated described species, including 21 subspecies, belong to the Staphylococcus genus according to the List of Bacterial Names with Standing in Nomenclature, updated 3 December 2004 (16). Some staphylococcal strains are used for their technological abilities, and others are associated with diseases in humans or animals. Staphylococcus xylosus and S. carnosus strains are used as starter cultures in fermented meat products, because they contribute to their color and flavor (47). In these products, other staphylococci, such as S. simulans, S. succinus, S. equorum, S. warneri, S. epidermidis, S. saprophyticus, and S. aureus, may be found (8), but the last three are also known to be pathogens or opportunistic pathogens. S. saprophyticus is the predominant staphylococcal species involved in acute urinary tract infections of young adult women (32). S. epidermidis is involved in many infections such as bacteremia and prosthetic and natural valvular endocarditis (50). S. aureus is one of the leading causes of food-borne diseases and of nosocomial infections (28, 34).
Because of these yin/yang aspects, much effort has been expended in recent years to identify staphylococci. Several manual and automated methods based on phenotypic characteristics have been developed for identification of the Staphylococcus species that are most often isolated from clinical samples (21, 25, 35, 37). Unfortunately, these systems have their limitations, mostly due to phenotypic differences between strains from the same species (33, 37-39). For this reason, methods based on molecular techniques have been developed.
Genus- and species-specific primers have been designed for the identification of bacteria belonging to the genus Staphylococcus and for the species-specific detection of S. aureus, S. epidermidis, S. saprophyticus, and S. xylosus (2, 18, 31, 33). Some authors associated several genus- and species-specific primer pairs in the same amplification reaction and were able to identify strains at genus level and up to four species (13). These PCR methods are quick and reliable, but they are limited in the number of species that can be identified. Alternative approaches include denaturating gradient gel electrophoresis (8) and sequence determination of the 16S rRNA-encoding gene (rrs) (5, 45). However, closely related species may have nearly identical rrs sequences, impairing the discriminatory power of these techniques (46). To solve this problem, it is possible to use alternative target genes which exhibit more-divergent sequences than rrs. So far the cpn60 (19), gla (53), femA (49), rpoB (14), and sodA (36) genes have been used.
In previous studies, our laboratory reported the sequencing of the sodA genes, encoding a manganese-dependent surperoxide dismutase, of S. xylosus and S. carnosus (3, 4). At the same time, Poyart et al. published the sequences of the sodA genes of nearly all known species of staphylococci (36). Pairwise comparison of these sequences revealed a mean identity (81.5%) lower than that calculated for the rrs sequences of staphylococci (98%). Therefore, the sodA gene will be a more discriminatory target sequence than rrs for differentiation of closely related staphylococci. However, the sodA sequences of pairs of type strains of subspecies shared more than 99.3% identity and did not allow discrimination at the subspecies level, except for the sodA genes of Staphylococcus cohnii subsp. cohnii and Staphylococcus cohnii subsp. urealyticus, which display 4% sequence divergence. Furthermore, Poyart et al. demonstrated that the sodA sequences of strains of the same species isolated from food or clinical samples displayed less than 1.5% divergence from the sequence of the corresponding type strain (36). In conclusion, they proposed that the sequence polymorphism of the sodA gene could allow the development of assays based on DNA chip technologies.
The potential for microbial diagnostics of DNA microarrays, originally developed for whole-genome gene expression analyses (42, 48), is very high, since they allow simultaneous product interrogation with a large number of probe sequences (10, 11). Recent studies showed the accurateness of such tools at detecting and identifying a great number of bacteria at the genus or species level in a single assay (15, 51, 52). Despite their very interesting abilities, microarrays are not yet common in microbial diagnostic laboratories. Part of the reason is the considerable initial financial investment. A recent survey conducted by the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group estimated the mean cost for setting up a microarray facility at $286,000 (22). Similar but less expensive techniques can be used. Oligonucleotide probe sets spotted onto nylon or nitrocellulose membranes have been used for bacterial identification for 10 years. In 1994, Kaufhold et al. used allele-specific oligonucleotide probes fixed to a membrane to rapidly identify strains of group A streptococci (27). Since that preliminary work, other authors have used closely related techniques to identify bacteria at the genus or species level (6, 40, 41).
In this study, we demonstrated the accurateness of such a tool for identification of staphylococcal strains at species level. This system, which we called "Staph. Array," couples PCR amplification of the sodA gene with an oligonucleotide-based array to efficiently discriminate all the 36 validated Staphylococcus species and the two subspecies of S. cohnii.
MATERIALS AND METHODS
Bacterial strains and culture conditions. The Staphylococcus type strains used are listed in Table 1. Strains were grown at 30°C in brain heart infusion broth or on brain heart infusion agar (Difco, Detroit, Mich.), with the notable exception of S. saccharolyticus, which was grown anaerobically in a medium containing the following (in grams per liter): casein peptone, 10; meat peptone, 5; yeast extract, 5; L-cysteine HCl, 0.4; glucose, 10; NaCl, 5; thioglycolate, 2 (pH 7.2).
Oligonucleotide probe design. A database of sodA gene sequences was constructed, and local BLAST comparisons were done with tools embedded in BioEdit software (23). Alignments were done using the ClustalW (12) service at the public website of the European Bioinformatics Institute (http://www.ebi.ac.uk/clustalw/). To facilitate the probe design, the alignments were reorganized with the "Multialignment Cleaner" tool of the Annhyb package (http://bioinformatics.org/annhyb/). The hairpin and dimer formation abilities of oligonucleotides were tested with the "Oligo" tools of the same package. Melting temperatures of perfect-match duplexes and those of mismatched nucleotides were predicted by the nearest-neighbor method using MELTING (29). All oligonucleotide probes were synthesized with a 5'-terminal amino group by Operon Biotechnologies (Germany) to allow covalent coupling of probes to the membrane. Probes used in this study are reported in Table 2.
Array preparation. Procedures for covalent coupling of probes followed the protocol described previously, with a Cross-Blot dot blot apparatus (Sebia, France) used instead of a Miniblotter (26). Briefly, a charged nylon membrane (Biodyne C; Pall Biosupport, United Kingdom) was activated for 10 min with freshly prepared 16% (wt/vol) 1-(3-dimethylaminopropyl)-3-ethylcarbodiimide hydrochloride (Across Organics, France). The oligonucleotide probes were applied to the membrane in parallel by using the grid with 34 vertical spacers. After 1 min at room temperature, the membrane was inactivated for 8 min with 100 mM NaOH and then washed with 2x SSPE (1x SSPE is 0.18 M NaCl, 10 mM NaH2PO4, and 1 mM EDTA, pH 7.7) (Promega, France) supplemented with 0.1% sodium dodecyl sulfate (SDS; Eurobio Biotechnology, France) for 5 min at 60°C.
Target preparation and hybridization procedures. Primers D1 and D2, used to amplify the internal part of the sodA gene (sodAint), have been described previously (36). D2 was synthesized with a 5'-terminal digoxigenin group (DIG). Amplifications were done with a GenAmp PCR system 9700 PE thermal cycler (Perkin-Elmer, France) and 25-μl volumes containing 0.8 μM of each primer, 50 μM of each deoxyribonucleoside triphosphate, 1.5 mM MgCl2, and 1 U of Taq DNA polymerase in 1x buffer according to the manufacturer's instructions (Promega, France). For efficient amplification from one colony picked up from the agar plate, the following conditions were used: 15 min at 4°C; 5 min at 95°C; 40 cycles of 30 s at 94°C, 1 min at 35°C, and 30 s at 72°C; and a final 2-min hold at 72°C. Relative quantification of the 480-bp amplified fragments was performed by comparison with SmartLadder (Eurogentec, France) after electrophoresis through a 1.5% agarose gel and ethidium bromide staining.
The PCR products at a final concentration of 150 ng/ml in 0.5x SSPE-0.1% SDS were heat denatured and cooled on ice immediately. After 5 min of incubation at room temperature in 50 ml of 0.5x SSPE-0.1% SDS, the membrane was placed in the Cross-Blot dot blot apparatus. The 14 horizontal slots of the grid were filled with the denatured target, and hybridization occurred for 1 h at 50°C on a plane surface. The samples were removed carefully, and slots were filled with a prewarmed (60°C) 2x SSPE-0.5% SDS solution. After aspiration, the membrane was taken from the Cross-Blot dot blot apparatus and washed twice in 70 ml 2x SSPE-0.5% SDS for 15 min at 60°C in a rolling bottle. An additional wash with 70 ml 0.1x SSPE-0.5% SDS occurred for 7 min at room temperature. The hybridized targets were detected with the DIG color detection kit (Roche, France).
Other methods of identification. The ID-GPC card of the VITEK 2 system was used for biochemical identification as recommended by the manufacturer (bioMerieux). Analysis of the results was based on the report provided by the VITEK 2 (version 3.01) computer software. Results with low levels of confidence are indicated.
Multiplex PCRs were performed to check the identification at the genus level and the identification of S. aureus, S. epidermidis, S. saprophyticus, and S. xylosus strains (13).
The internal base compositions of the sodA genes were determined using primers D1 and D2 as previously described (36). Sequences were compared against a local database of sodAint gene sequences. Identification to the species level was based on 97% sequence identity with the type strain sequence and a 5% sequence difference from the next closest species.
Nucleotide sequence accession numbers. All partial staphylococcal sequences determined in this study were deposited in GenBank. The accession numbers of the sodA sequences of Staphylococcus succinus subsp. succinus, Staphylococcus succinus subsp. casei, Staphylococcus equorum subsp. linens, S. fleurettii, and S. nepalensis are AY845222, AY842858, AY878697, AY845223, and AY878698, respectively.
RESULTS
Determination of the sodA internal gene sequences from type strains of coagulase-negative staphylococci. The sodAint sequences of type strains of S. equorum subsp. linens, S. succinus subsp. succinus, S. succinus subsp. casei, S. fleurettii, and S. nepalensis were amplified. These fragments were sequenced, and sequence comparisons were done using BLAST (1). The base composition of S. equorum subsp. linens sodAint was completely identical to that previously published for the S. equorum subsp. equorum type strain. The sodAint sequences of S. succinus subsp. succinus and S. succinus subsp. casei differed in only one base pair. The highest sequence similarity values were (i) 93% for S. succinus compared to S. gallinarum, (ii) 95% for S. fleurettii compared to S. vitulinus, and (iii) 92% for S. nepalensis compared to S. cohnii subsp. urealyticus.
Design of probes. The available partial sequences of sodA and those we determined were used to create characteristic probes for the 36 species. Oligonucleotides of 21 to 38 bases, with predicted melting temperatures from 61°C to 68°C, were chosen from dissimilar parts noted in aligned sodA sequences. We rejected sequences with predicted stable hairpins and dimers or with unsatisfactory specificities. A central mismatch was introduced into probes PGcondi1 and PGnep1. These G/T artificial mismatches were created to increase the specificity of these probes. Candidate probes were tested on the array under different conditions, and those that were adopted are reported in Table 2. Probe concentrations were empirically modified to allow better discrimination.
Validation with type strains. Our array was first tested with type strains of each validated Staphylococcus species (Table 1). As expected, not only unique spots but unique patterns of spots were obtained (Fig. 1). This was due to the conditions of hybridization, which allowed some mismatched probe-target pairs to hybridize, i.e., some probes hybridized not only with the targets for which they were designed but also with targets from closely related species. However, comparisons of the patterns of hybridization showed that a unique pattern was found for each species (Table 3). The probes that we designed discriminated targets with differences in their base composition as low as 3%, since we distinguished S. condimenti from S. carnosus or S. piscifermentans and we obtained distinct patterns for the two subspecies of S. cohnii. We also discriminated species that are difficult to differentiate on the basis of their rrs sequences, such as the S. intermedius and S. delphini species and the S. nepalensis and S. cohnii subsp. urealyticus species (5, 44). We could not distinguish between the two subspecies of S. succinus or the two subspecies of S. equorum because their sodAint sequences were identical.
Application to strains isolated from clinical samples. A total of 38 strains (Table 4) from clinical samples were identified first by a phenotypic approach using the VITEK 2 system (bioMerieux), and these results were compared to the array identification. Results were identical for 30 strains of S. aureus, S. capitis, S. epidermidis, S. haemolyticus, S. hominis, and S. warneri. Six strains (16%) were misidentified by the VITEK 2. Three strains identified as S. epidermidis by VITEK 2 were identified as strains of S. aureus, S. warneri, and S. capitis by the array. Two strains identified as S. epidermidis by the array were misidentified as S. warneri and S. hominis by VITEK 2. One strain identified as S. simulans by VITEK 2 did not give any hybridization result on the array. Multiplex PCR confirmed that this strain was not a staphylococcus. Two strains (5%) could not be identified by VITEK 2. They were identified as S. epidermidis and S. hominis.
Application to strains isolated from food or food plant samples. A total of 38 strains (Table 5) from food or food plant samples were also identified by the VITEK 2 system, and the results of the identification were compared to the results from the array. Some species commonly isolated from food or food plants, such as S. equorum and S. succinus (9), are not included in the VITEK card database; thus, the strains belonging to these species could not be identified by the VITEK 2 system. But even for species included in the ID-GPC database, some misidentification or lack of identification occurred. None of eight S. xylosus strains were correctly identified. Five strains were misidentified as S. saprophyticus, two were misidentified as S. cohnii subsp. urealyticus, and one was not identified. Only one of four S. saprophyticus strains was correctly identified; the others were either misidentified as S. chromogenes or S. auricularis or not identified. Of the two strains of S. epidermidis, one was correctly identified, while the other was identified as Kocuria varians. The S. warneri strain was also misidentified as K. varians. Strains of S. hominis, S. capitis, and S. sciuri were correctly identified. All the identifications done via the array were confirmed by multiplex PCR when suitable and by sequencing of the sodAint fragments of these strains.
Stability of patterns obtained with wild-type strains. The stability of the patterns of hybridization obtained for wild-type strains was investigated. As an example, Fig. 2 shows the patterns obtained for strains of S. xylosus and S. equorum isolated from food or food plant samples. Only slight variations in the intensity of hybridization spots occurred. The same stability of hybridization patterns was obtained whatever the origin of the strain (data not shown).
DISCUSSION
In this study, we present a new oligonucleotide array tool, called "Staph. Array," for the identification of the 36 species of staphylococci described and validated and for the discrimination of the two S. cohnii subspecies. For this method, universal primers amplifying an internal part of the sodA gene were used, followed by hybridization of the denatured PCR products onto an oligonucleotide array.
Because a large amount of rrs sequence data is available in a public database, it is not surprising that this gene has been an obvious choice when molecular diagnostic tests based on DNA arrays have been developed. One important drawback of using rrs genes is their conservative nature. Takahashi et al. pointed out that closely related species of staphylococci could have nearly identical rrs base composition (46), decreasing the discriminatory potential of that gene for staphylococci. To bypass this problem, some authors have used more-divergent genes to identify staphylococcal strains. The femA (24, 49), rpoB (14), gla (53), cpn60 (19), and sodA (36) genes have been used. Array techniques have been used with the femA and cpn60 genes. With femA a microarray was developed allowing discrimination of only five Staphylococcus species (S. aureus, S. epidermidis, S. haemolyticus, S. hominis, and S. saprophyticus) (24). The use of amplification products of the HSP60-encoding gene (cpn60) as probes produced better results; Goh et al. identified strains belonging to 30 species (20). However, their system failed to distinguish S. intermedius from S. delphini strains and did not identify some other strains, probably because they belonged to species not included in their 30-species panel. We choose sodA to develop our tool because sequences of that gene were available for 33 out of the 36 species of staphylococci as opposed to 15 for femA, 27 for rpoB, and 30 for cpn60. In the present work, the available sequence data were completed with the sodA partial base composition of the five type strains of S. equorum subsp. linens, S. fleurettii, S. nepalensis, S. succinus subsp. succinus, and S. succinus subsp. casei. This gene proved to be discriminatory at species level, since the sequences obtained were more than 5% divergent from the other sodA sequences present in GenBank. However, the sodAint sequences of the two subspecies of S. succinus showed an identical base pair composition, like the sodAint sequences of the two subspecies of S. equorum. These results confirmed the lack of discriminatory power of the sodAint sequences at the subspecies level (36).
After initial database screening, oligonucleotide probes were selected on the basis of hybridization results obtained by using reference strains as templates. The conditions of hybridization allowed some mismatched duplexes to form. Consequently, cross-hybridization of several probes with some targets obtained from strains belonging to closely related species was observed. However, a unique pattern of hybridization was obtained for each staphylococcal species, allowing us to identify unknown strains. We used the "Staph. Array" system to identify 76 strains from clinical, food, or environmental food samples, and these identifications were compared with those obtained by the VITEK 2 system. VITEK 2 is one of the laboratories' routine identification systems and has been shown to provide reliable results compared to other systems based on phenotypic identification (17, 30). Nineteen species commonly encountered in clinical isolates are included in the ID-GPC database of the VITEK 2 system. We showed that strains can be misidentified or not identified by the commercial system, even strains of species whose identification is covered by the VITEK 2 database; this is especially true for strains isolated from food or food plants. Strangely, identifications with good or higher levels of confidence were obtained when some strains belonging to species not included in the ID-GPC database were submitted to the VITEK 2 system (Table 5). Therefore, caution should be taken when VITEK 2 is used with unsuitable species. The problem of identification by the VITEK 2 system could be explained by the intraspecies variability of the phenotypic traits. In contrast to their phenotypic traits, the patterns obtained with "Staph. Array" were stable for strains belonging to the same species, whatever their origins. This result confirmed the low intraspecies variation of the sodAint sequences (36, 43).
Recent studies have shown that molecular methods give more-accurate results than kits based on biochemical assays (5, 43). Interestingly, one of these studies used sodA sequencing to identify staphylococcal strains from clinical isolates (43). Identification was based on 97% sequence identity with the type strain sequence and a 5% difference in sequence from the next closest species. However, these criteria did not allow discrimination of S. condimenti and S. carnosus (96.7% nucleotide identity) or of S. condimenti and S. piscifermentans (95.6% nucleotide identity). With "Staph. Array," the hybridization profiles of S. carnosus, S. piscifermentans, and S. condimenti were clearly distinct, so these three species can be identified (Fig. 1).
The specificity of the probes we designed was ensured by comparison with the sequences available in GenBank (7). To date, screening of GenBank revealed that the sodA gene is present in about 30 bacterial genera, but most of the data covered strains of Staphylococcus, Enterococcus, Streptococcus, Pasteurella, and Mycobacterium. We cannot exclude the possibility that yet unknown targets hybridize to our probes, but it is unlikely that targets from nonstaphylococcal strains produce patterns of hybridization that can be confused with staphylococcal patterns.
In conclusion, the tool "Staph. Array" allowed the rapid (less than 24 h) and accurate identification of staphylococcal strains at species level. It is the only tool described to date that distinguishes in one shot the 36 validated staphylococcal species and also discriminates the two subspecies of S. cohnii.
ACKNOWLEDGMENTS
We are grateful to Caroline Michaud, Christine Lamadon, and Laurent Lanore for excellent technical assistance.
This work was financially supported by the European project "Tradisausage" QLK1-CT-2002-02240.
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Centre Hospitalo-Universitaire, Laboratoire de Bacteriologie, 28 place Henri Dunant, 63001 Clermont-Ferrand, France
ABSTRACT
The genus Staphylococcus is made up of 36 validated species which contain strains that are pathogenic, saprophytic, or used as starter cultures for the food industry. An oligonucleotide array targeting the manganese-dependent superoxide dismutase (sodA) gene was developed to overcome the drawbacks of the conventional methods of identification. Divergences of the sodA gene were used to design oligonucleotide probes, and we showed that each of the 36 species had a characteristic pattern of hybridization. To evaluate the array, we analyzed 38 clinical and 38 food or food plant Staphylococcus isolates identified by the phenotype-based system VITEK 2 (bioMerieux). This commercial kit failed to identify 8 (21%) of the clinical isolates and 32 (84%) of the food and food plant isolates. In contrast, the oligonucleotide array we designed provided an accurate and rapid method for the identification of staphylococcal strains, isolated from clinical, environmental, or food samples, at species level.
INTRODUCTION
Staphylococci are widely spread in various niches such as clinical environments and food plants. Thirty-six validated described species, including 21 subspecies, belong to the Staphylococcus genus according to the List of Bacterial Names with Standing in Nomenclature, updated 3 December 2004 (16). Some staphylococcal strains are used for their technological abilities, and others are associated with diseases in humans or animals. Staphylococcus xylosus and S. carnosus strains are used as starter cultures in fermented meat products, because they contribute to their color and flavor (47). In these products, other staphylococci, such as S. simulans, S. succinus, S. equorum, S. warneri, S. epidermidis, S. saprophyticus, and S. aureus, may be found (8), but the last three are also known to be pathogens or opportunistic pathogens. S. saprophyticus is the predominant staphylococcal species involved in acute urinary tract infections of young adult women (32). S. epidermidis is involved in many infections such as bacteremia and prosthetic and natural valvular endocarditis (50). S. aureus is one of the leading causes of food-borne diseases and of nosocomial infections (28, 34).
Because of these yin/yang aspects, much effort has been expended in recent years to identify staphylococci. Several manual and automated methods based on phenotypic characteristics have been developed for identification of the Staphylococcus species that are most often isolated from clinical samples (21, 25, 35, 37). Unfortunately, these systems have their limitations, mostly due to phenotypic differences between strains from the same species (33, 37-39). For this reason, methods based on molecular techniques have been developed.
Genus- and species-specific primers have been designed for the identification of bacteria belonging to the genus Staphylococcus and for the species-specific detection of S. aureus, S. epidermidis, S. saprophyticus, and S. xylosus (2, 18, 31, 33). Some authors associated several genus- and species-specific primer pairs in the same amplification reaction and were able to identify strains at genus level and up to four species (13). These PCR methods are quick and reliable, but they are limited in the number of species that can be identified. Alternative approaches include denaturating gradient gel electrophoresis (8) and sequence determination of the 16S rRNA-encoding gene (rrs) (5, 45). However, closely related species may have nearly identical rrs sequences, impairing the discriminatory power of these techniques (46). To solve this problem, it is possible to use alternative target genes which exhibit more-divergent sequences than rrs. So far the cpn60 (19), gla (53), femA (49), rpoB (14), and sodA (36) genes have been used.
In previous studies, our laboratory reported the sequencing of the sodA genes, encoding a manganese-dependent surperoxide dismutase, of S. xylosus and S. carnosus (3, 4). At the same time, Poyart et al. published the sequences of the sodA genes of nearly all known species of staphylococci (36). Pairwise comparison of these sequences revealed a mean identity (81.5%) lower than that calculated for the rrs sequences of staphylococci (98%). Therefore, the sodA gene will be a more discriminatory target sequence than rrs for differentiation of closely related staphylococci. However, the sodA sequences of pairs of type strains of subspecies shared more than 99.3% identity and did not allow discrimination at the subspecies level, except for the sodA genes of Staphylococcus cohnii subsp. cohnii and Staphylococcus cohnii subsp. urealyticus, which display 4% sequence divergence. Furthermore, Poyart et al. demonstrated that the sodA sequences of strains of the same species isolated from food or clinical samples displayed less than 1.5% divergence from the sequence of the corresponding type strain (36). In conclusion, they proposed that the sequence polymorphism of the sodA gene could allow the development of assays based on DNA chip technologies.
The potential for microbial diagnostics of DNA microarrays, originally developed for whole-genome gene expression analyses (42, 48), is very high, since they allow simultaneous product interrogation with a large number of probe sequences (10, 11). Recent studies showed the accurateness of such tools at detecting and identifying a great number of bacteria at the genus or species level in a single assay (15, 51, 52). Despite their very interesting abilities, microarrays are not yet common in microbial diagnostic laboratories. Part of the reason is the considerable initial financial investment. A recent survey conducted by the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group estimated the mean cost for setting up a microarray facility at $286,000 (22). Similar but less expensive techniques can be used. Oligonucleotide probe sets spotted onto nylon or nitrocellulose membranes have been used for bacterial identification for 10 years. In 1994, Kaufhold et al. used allele-specific oligonucleotide probes fixed to a membrane to rapidly identify strains of group A streptococci (27). Since that preliminary work, other authors have used closely related techniques to identify bacteria at the genus or species level (6, 40, 41).
In this study, we demonstrated the accurateness of such a tool for identification of staphylococcal strains at species level. This system, which we called "Staph. Array," couples PCR amplification of the sodA gene with an oligonucleotide-based array to efficiently discriminate all the 36 validated Staphylococcus species and the two subspecies of S. cohnii.
MATERIALS AND METHODS
Bacterial strains and culture conditions. The Staphylococcus type strains used are listed in Table 1. Strains were grown at 30°C in brain heart infusion broth or on brain heart infusion agar (Difco, Detroit, Mich.), with the notable exception of S. saccharolyticus, which was grown anaerobically in a medium containing the following (in grams per liter): casein peptone, 10; meat peptone, 5; yeast extract, 5; L-cysteine HCl, 0.4; glucose, 10; NaCl, 5; thioglycolate, 2 (pH 7.2).
Oligonucleotide probe design. A database of sodA gene sequences was constructed, and local BLAST comparisons were done with tools embedded in BioEdit software (23). Alignments were done using the ClustalW (12) service at the public website of the European Bioinformatics Institute (http://www.ebi.ac.uk/clustalw/). To facilitate the probe design, the alignments were reorganized with the "Multialignment Cleaner" tool of the Annhyb package (http://bioinformatics.org/annhyb/). The hairpin and dimer formation abilities of oligonucleotides were tested with the "Oligo" tools of the same package. Melting temperatures of perfect-match duplexes and those of mismatched nucleotides were predicted by the nearest-neighbor method using MELTING (29). All oligonucleotide probes were synthesized with a 5'-terminal amino group by Operon Biotechnologies (Germany) to allow covalent coupling of probes to the membrane. Probes used in this study are reported in Table 2.
Array preparation. Procedures for covalent coupling of probes followed the protocol described previously, with a Cross-Blot dot blot apparatus (Sebia, France) used instead of a Miniblotter (26). Briefly, a charged nylon membrane (Biodyne C; Pall Biosupport, United Kingdom) was activated for 10 min with freshly prepared 16% (wt/vol) 1-(3-dimethylaminopropyl)-3-ethylcarbodiimide hydrochloride (Across Organics, France). The oligonucleotide probes were applied to the membrane in parallel by using the grid with 34 vertical spacers. After 1 min at room temperature, the membrane was inactivated for 8 min with 100 mM NaOH and then washed with 2x SSPE (1x SSPE is 0.18 M NaCl, 10 mM NaH2PO4, and 1 mM EDTA, pH 7.7) (Promega, France) supplemented with 0.1% sodium dodecyl sulfate (SDS; Eurobio Biotechnology, France) for 5 min at 60°C.
Target preparation and hybridization procedures. Primers D1 and D2, used to amplify the internal part of the sodA gene (sodAint), have been described previously (36). D2 was synthesized with a 5'-terminal digoxigenin group (DIG). Amplifications were done with a GenAmp PCR system 9700 PE thermal cycler (Perkin-Elmer, France) and 25-μl volumes containing 0.8 μM of each primer, 50 μM of each deoxyribonucleoside triphosphate, 1.5 mM MgCl2, and 1 U of Taq DNA polymerase in 1x buffer according to the manufacturer's instructions (Promega, France). For efficient amplification from one colony picked up from the agar plate, the following conditions were used: 15 min at 4°C; 5 min at 95°C; 40 cycles of 30 s at 94°C, 1 min at 35°C, and 30 s at 72°C; and a final 2-min hold at 72°C. Relative quantification of the 480-bp amplified fragments was performed by comparison with SmartLadder (Eurogentec, France) after electrophoresis through a 1.5% agarose gel and ethidium bromide staining.
The PCR products at a final concentration of 150 ng/ml in 0.5x SSPE-0.1% SDS were heat denatured and cooled on ice immediately. After 5 min of incubation at room temperature in 50 ml of 0.5x SSPE-0.1% SDS, the membrane was placed in the Cross-Blot dot blot apparatus. The 14 horizontal slots of the grid were filled with the denatured target, and hybridization occurred for 1 h at 50°C on a plane surface. The samples were removed carefully, and slots were filled with a prewarmed (60°C) 2x SSPE-0.5% SDS solution. After aspiration, the membrane was taken from the Cross-Blot dot blot apparatus and washed twice in 70 ml 2x SSPE-0.5% SDS for 15 min at 60°C in a rolling bottle. An additional wash with 70 ml 0.1x SSPE-0.5% SDS occurred for 7 min at room temperature. The hybridized targets were detected with the DIG color detection kit (Roche, France).
Other methods of identification. The ID-GPC card of the VITEK 2 system was used for biochemical identification as recommended by the manufacturer (bioMerieux). Analysis of the results was based on the report provided by the VITEK 2 (version 3.01) computer software. Results with low levels of confidence are indicated.
Multiplex PCRs were performed to check the identification at the genus level and the identification of S. aureus, S. epidermidis, S. saprophyticus, and S. xylosus strains (13).
The internal base compositions of the sodA genes were determined using primers D1 and D2 as previously described (36). Sequences were compared against a local database of sodAint gene sequences. Identification to the species level was based on 97% sequence identity with the type strain sequence and a 5% sequence difference from the next closest species.
Nucleotide sequence accession numbers. All partial staphylococcal sequences determined in this study were deposited in GenBank. The accession numbers of the sodA sequences of Staphylococcus succinus subsp. succinus, Staphylococcus succinus subsp. casei, Staphylococcus equorum subsp. linens, S. fleurettii, and S. nepalensis are AY845222, AY842858, AY878697, AY845223, and AY878698, respectively.
RESULTS
Determination of the sodA internal gene sequences from type strains of coagulase-negative staphylococci. The sodAint sequences of type strains of S. equorum subsp. linens, S. succinus subsp. succinus, S. succinus subsp. casei, S. fleurettii, and S. nepalensis were amplified. These fragments were sequenced, and sequence comparisons were done using BLAST (1). The base composition of S. equorum subsp. linens sodAint was completely identical to that previously published for the S. equorum subsp. equorum type strain. The sodAint sequences of S. succinus subsp. succinus and S. succinus subsp. casei differed in only one base pair. The highest sequence similarity values were (i) 93% for S. succinus compared to S. gallinarum, (ii) 95% for S. fleurettii compared to S. vitulinus, and (iii) 92% for S. nepalensis compared to S. cohnii subsp. urealyticus.
Design of probes. The available partial sequences of sodA and those we determined were used to create characteristic probes for the 36 species. Oligonucleotides of 21 to 38 bases, with predicted melting temperatures from 61°C to 68°C, were chosen from dissimilar parts noted in aligned sodA sequences. We rejected sequences with predicted stable hairpins and dimers or with unsatisfactory specificities. A central mismatch was introduced into probes PGcondi1 and PGnep1. These G/T artificial mismatches were created to increase the specificity of these probes. Candidate probes were tested on the array under different conditions, and those that were adopted are reported in Table 2. Probe concentrations were empirically modified to allow better discrimination.
Validation with type strains. Our array was first tested with type strains of each validated Staphylococcus species (Table 1). As expected, not only unique spots but unique patterns of spots were obtained (Fig. 1). This was due to the conditions of hybridization, which allowed some mismatched probe-target pairs to hybridize, i.e., some probes hybridized not only with the targets for which they were designed but also with targets from closely related species. However, comparisons of the patterns of hybridization showed that a unique pattern was found for each species (Table 3). The probes that we designed discriminated targets with differences in their base composition as low as 3%, since we distinguished S. condimenti from S. carnosus or S. piscifermentans and we obtained distinct patterns for the two subspecies of S. cohnii. We also discriminated species that are difficult to differentiate on the basis of their rrs sequences, such as the S. intermedius and S. delphini species and the S. nepalensis and S. cohnii subsp. urealyticus species (5, 44). We could not distinguish between the two subspecies of S. succinus or the two subspecies of S. equorum because their sodAint sequences were identical.
Application to strains isolated from clinical samples. A total of 38 strains (Table 4) from clinical samples were identified first by a phenotypic approach using the VITEK 2 system (bioMerieux), and these results were compared to the array identification. Results were identical for 30 strains of S. aureus, S. capitis, S. epidermidis, S. haemolyticus, S. hominis, and S. warneri. Six strains (16%) were misidentified by the VITEK 2. Three strains identified as S. epidermidis by VITEK 2 were identified as strains of S. aureus, S. warneri, and S. capitis by the array. Two strains identified as S. epidermidis by the array were misidentified as S. warneri and S. hominis by VITEK 2. One strain identified as S. simulans by VITEK 2 did not give any hybridization result on the array. Multiplex PCR confirmed that this strain was not a staphylococcus. Two strains (5%) could not be identified by VITEK 2. They were identified as S. epidermidis and S. hominis.
Application to strains isolated from food or food plant samples. A total of 38 strains (Table 5) from food or food plant samples were also identified by the VITEK 2 system, and the results of the identification were compared to the results from the array. Some species commonly isolated from food or food plants, such as S. equorum and S. succinus (9), are not included in the VITEK card database; thus, the strains belonging to these species could not be identified by the VITEK 2 system. But even for species included in the ID-GPC database, some misidentification or lack of identification occurred. None of eight S. xylosus strains were correctly identified. Five strains were misidentified as S. saprophyticus, two were misidentified as S. cohnii subsp. urealyticus, and one was not identified. Only one of four S. saprophyticus strains was correctly identified; the others were either misidentified as S. chromogenes or S. auricularis or not identified. Of the two strains of S. epidermidis, one was correctly identified, while the other was identified as Kocuria varians. The S. warneri strain was also misidentified as K. varians. Strains of S. hominis, S. capitis, and S. sciuri were correctly identified. All the identifications done via the array were confirmed by multiplex PCR when suitable and by sequencing of the sodAint fragments of these strains.
Stability of patterns obtained with wild-type strains. The stability of the patterns of hybridization obtained for wild-type strains was investigated. As an example, Fig. 2 shows the patterns obtained for strains of S. xylosus and S. equorum isolated from food or food plant samples. Only slight variations in the intensity of hybridization spots occurred. The same stability of hybridization patterns was obtained whatever the origin of the strain (data not shown).
DISCUSSION
In this study, we present a new oligonucleotide array tool, called "Staph. Array," for the identification of the 36 species of staphylococci described and validated and for the discrimination of the two S. cohnii subspecies. For this method, universal primers amplifying an internal part of the sodA gene were used, followed by hybridization of the denatured PCR products onto an oligonucleotide array.
Because a large amount of rrs sequence data is available in a public database, it is not surprising that this gene has been an obvious choice when molecular diagnostic tests based on DNA arrays have been developed. One important drawback of using rrs genes is their conservative nature. Takahashi et al. pointed out that closely related species of staphylococci could have nearly identical rrs base composition (46), decreasing the discriminatory potential of that gene for staphylococci. To bypass this problem, some authors have used more-divergent genes to identify staphylococcal strains. The femA (24, 49), rpoB (14), gla (53), cpn60 (19), and sodA (36) genes have been used. Array techniques have been used with the femA and cpn60 genes. With femA a microarray was developed allowing discrimination of only five Staphylococcus species (S. aureus, S. epidermidis, S. haemolyticus, S. hominis, and S. saprophyticus) (24). The use of amplification products of the HSP60-encoding gene (cpn60) as probes produced better results; Goh et al. identified strains belonging to 30 species (20). However, their system failed to distinguish S. intermedius from S. delphini strains and did not identify some other strains, probably because they belonged to species not included in their 30-species panel. We choose sodA to develop our tool because sequences of that gene were available for 33 out of the 36 species of staphylococci as opposed to 15 for femA, 27 for rpoB, and 30 for cpn60. In the present work, the available sequence data were completed with the sodA partial base composition of the five type strains of S. equorum subsp. linens, S. fleurettii, S. nepalensis, S. succinus subsp. succinus, and S. succinus subsp. casei. This gene proved to be discriminatory at species level, since the sequences obtained were more than 5% divergent from the other sodA sequences present in GenBank. However, the sodAint sequences of the two subspecies of S. succinus showed an identical base pair composition, like the sodAint sequences of the two subspecies of S. equorum. These results confirmed the lack of discriminatory power of the sodAint sequences at the subspecies level (36).
After initial database screening, oligonucleotide probes were selected on the basis of hybridization results obtained by using reference strains as templates. The conditions of hybridization allowed some mismatched duplexes to form. Consequently, cross-hybridization of several probes with some targets obtained from strains belonging to closely related species was observed. However, a unique pattern of hybridization was obtained for each staphylococcal species, allowing us to identify unknown strains. We used the "Staph. Array" system to identify 76 strains from clinical, food, or environmental food samples, and these identifications were compared with those obtained by the VITEK 2 system. VITEK 2 is one of the laboratories' routine identification systems and has been shown to provide reliable results compared to other systems based on phenotypic identification (17, 30). Nineteen species commonly encountered in clinical isolates are included in the ID-GPC database of the VITEK 2 system. We showed that strains can be misidentified or not identified by the commercial system, even strains of species whose identification is covered by the VITEK 2 database; this is especially true for strains isolated from food or food plants. Strangely, identifications with good or higher levels of confidence were obtained when some strains belonging to species not included in the ID-GPC database were submitted to the VITEK 2 system (Table 5). Therefore, caution should be taken when VITEK 2 is used with unsuitable species. The problem of identification by the VITEK 2 system could be explained by the intraspecies variability of the phenotypic traits. In contrast to their phenotypic traits, the patterns obtained with "Staph. Array" were stable for strains belonging to the same species, whatever their origins. This result confirmed the low intraspecies variation of the sodAint sequences (36, 43).
Recent studies have shown that molecular methods give more-accurate results than kits based on biochemical assays (5, 43). Interestingly, one of these studies used sodA sequencing to identify staphylococcal strains from clinical isolates (43). Identification was based on 97% sequence identity with the type strain sequence and a 5% difference in sequence from the next closest species. However, these criteria did not allow discrimination of S. condimenti and S. carnosus (96.7% nucleotide identity) or of S. condimenti and S. piscifermentans (95.6% nucleotide identity). With "Staph. Array," the hybridization profiles of S. carnosus, S. piscifermentans, and S. condimenti were clearly distinct, so these three species can be identified (Fig. 1).
The specificity of the probes we designed was ensured by comparison with the sequences available in GenBank (7). To date, screening of GenBank revealed that the sodA gene is present in about 30 bacterial genera, but most of the data covered strains of Staphylococcus, Enterococcus, Streptococcus, Pasteurella, and Mycobacterium. We cannot exclude the possibility that yet unknown targets hybridize to our probes, but it is unlikely that targets from nonstaphylococcal strains produce patterns of hybridization that can be confused with staphylococcal patterns.
In conclusion, the tool "Staph. Array" allowed the rapid (less than 24 h) and accurate identification of staphylococcal strains at species level. It is the only tool described to date that distinguishes in one shot the 36 validated staphylococcal species and also discriminates the two subspecies of S. cohnii.
ACKNOWLEDGMENTS
We are grateful to Caroline Michaud, Christine Lamadon, and Laurent Lanore for excellent technical assistance.
This work was financially supported by the European project "Tradisausage" QLK1-CT-2002-02240.
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