Comparative Study Using Various Methods for Identification of Staphylo
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《微生物临床杂志》
Otto von Guericke University, Institute of Medical Microbiology, Leipziger Str. 44, D-39120 Magdeburg, Germany
ABSTRACT
Coagulase-negative staphylococci (CNS) play a predominant role in nosocomial infections. Rapid, reliable identification of these organisms is essential for accurate diagnosis and prompt effective treatment of these infections. Quite recently, the VITEK 2 g-positive (gram-positive [GP]) identification card (bioMerieux) has been redesigned for greater accuracy in the identification of gram-positive cocci. We compared the BD Phoenix (Becton Dickinson) and VITEK 2 (bioMerieux) automated microbiology systems, using their respective update version cards, and the API ID32 STAPH test. The glyceraldehyde-3-phosphate dehydrogenase (gap) gene-based T-RFLP (terminal restriction fragment length polymorphism) method was used for verifying the results. In total, 86 clinical isolates of CNS and 27 reference strains were analyzed. The results show that for identification of CNS, the automated identification methods using the newest VITEK 2 and BD Phoenix identification cards are comparable. However, API ID32 STAPH revealed more correct results compared to both automated microbiology systems. Despite the increased performance of the phenotypic automated identification systems compared to the former versions, molecular methods, e.g., the gap-based T-RFLP method, still show superior accuracy in identifying Staphylococcus species other than Staphylococcus aureus.
INTRODUCTION
So far, 40 species of the genus Staphylococcus have been identified (8). Staphylococcus aureus is the best known and has been frequently implicated in the etiology of a series of infections and intoxications in humans, whereas coagulase-negative staphylococci (CNS), representing the majority of the species, have been considered to be saprophytic or rarely pathogenic. Currently, several species of CNS are recognized as potential pathogens, mainly causing nosocomial infections, often involved in infections related to implanted medical devices such as intravenous catheters, prosthetic heart valves, and orthopedic implants. The species that most frequently cause diseases in humans are Staphylococcus epidermidis, Staphylococcus haemolyticus, and Staphylococcus saprophyticus. Other significant opportunistic pathogens include Staphylococcus hominis, Staphylococcus warneri, Staphylococcus capitis, Staphylococcus simulans, Staphylococcus cohnii, Staphylococcus xylosus, Staphylococcus saccharolyticus, and Staphylococcus lugdunensis (6, 12, 17, 20).
In this regard, comprehensive and accurate identification of the distinct Staphylococcus species is of great importance. A variety of methods have been proposed for identification schemes based on commercial tests and in relation to the publication of Kloos and Schleifer (15). Various automated identification and susceptibility test systems are currently on the market, among them VITEK 2 (bioMerieux, Marcy l'Etoile, France) and the BD Phoenix system (Becton Dickinson Diagnostic Systems, Sparks, MD.). Quite recently, the VITEK 2 gram-positive (GP) identification card (bioMerieux, Marcy l'Etoile, France) has been redesigned for increased accuracy in the identification of gram-positive cocci. In general, methods based on phenotypic characteristics are hampered by the fact that they depend on the expression of metabolic activities and/or morphological features.
A number of PCR amplicon sequencing-based methods for identification of CNS have been reported, i.e., targeting the 16S rRNA gene, sodA, and the gap gene (2, 10, 24). Despite these techniques, terminal restriction fragment length polymorphism (T-RFLP) analysis of the glyceraldehyde-3-phosphate dehydrogenase gene (gap) represents a high-throughput reproducible method that allows the identification of distinct Staphylococcus species (22). The aim of the present study was to evaluate the performances of VITEK 2 in combination with the newly developed VITEK 2 ID-GP identification card (bioMerieux, Marcy l'Etoile, France) and the BD Phoenix system (Becton Dickinson Diagnostic Systems) for identification of Staphylococcus species in comparison with gap-based T-RFLP analysis as a reference method for accuracy.
MATERIALS AND METHODS
Laboratory, strains, culture conditions, and identification. This study was performed at the Institute of Medical Microbiology of the Otto von Guericke University in Magdeburg, Germany. The following reference strains were selected from the German Collection of Microorganisms and Cell Cultures (DSMZ), the Czech Collection of Microorganisms (CCM), and the American Type Culture Collection (ATCC): Staphylococcus arlettae DSM 20672, Staphylococcus carnosus subsp. carnosus DSM 20501, S. cohnii subsp. cohnii DSM 20260, Staphylococcus delphini DSM 20771, S. epidermidis DSM 20044 (CCM 2124), Staphylococcus equorum subsp. equorum DSM 20674, Staphylococcus hyicus DSM 20459, Staphylococcus intermedius DSM 20373 (CCM 5739), Staphylococcus kloosii DSM20676, S. lugdunensis DSM 4804 (ATCC 43809), S. warneri DSM 20316 (CCM 2730), S. capitis subsp. capitis CCM 2734, Staphylococcus caprae CCM 3573, Staphylococcus chromogenes CCM 3387, Staphylococcus gallinarum CCM 3572, S. haemolyticus CCM 1798, S. hominis subsp. hominis CCM 2732, Staphylococcus lentus CCM 3472, Staphylococcus muscae CCM 4175, S. saprophyticus subsp. saprophyticus CCM 883, Staphylococcus sciuri CCM 3473, S. simulans CCM 2705, S. xylosus CCM 2725, Staphylococcus auricularis ATCC 33753, Staphylococcus felis ATCC 49168, and Staphylococcus schleiferi subsp. schleiferi ATCC 43808. All strains were grown on blood agar and incubated at 37°C in air for 24 h.
The clinical isolates included in the present study were collected within a 1-month period. A total of 86 strains of gram-positive cocci were taken from primary isolation plates set up on Columbia sheep blood agar (Becton Dickinson, Heidelberg, Germany) in our routine clinical laboratory for various types of patient specimens (blood culture, wound swab, respiratory, and urine specimens, etc.). All of these strains were obtained from different patients, and consecutive cultures from the same patient were excluded. The 86 strains tested were identified by conventional methods, as well as by VITEK 2 analysis with the new (ID-GP) and old (ID-GPC) gram-positive coccus identification cards, by the BD Phoenix system using the appropriate identification card for gram-positive cocci (ID-13), and by ID32 STAPH (bioMerieux). For identification by conventional methods, the following characteristics were tested: colony pigmentation, hemolysis, catalase and oxidase reactions, and clumping factor test (bioMerieux). All strains were analyzed by the gap-based T-RFLP method. Major discrepancies between the identification results obtained by the phenotypic methods and gap-based T-RFLP analysis were resolved by partial sequencing of the 16S rRNA gene.
VITEK 2 system. The procedures recommended by the manufacturer were strictly followed. Strains were taken out of the freezer, grown on Colombia agar with 5% sheep red blood cells for 16 to 24 h at 37°C, replated, and grown again for 16 to 24 h at 37°C just before testing. For both identification cards, bacterial suspensions were prepared by emulsifying bacterial isolates in 0.45% saline to the equivalent of a 0.5 McFarland turbidity standard with a VITEK 2 instrument (DensiChek; bioMerieux) (software version 4.01). In the VITEK 2 system, the confidence value is expressed by seven different categories of results: excellent identification, very good identification, good identification, acceptable identification (each of these four categories shows only one identification result), low discrimination (more than one identification result is given, whereupon the software suggests performing additional tests such as oxidase, hemolysis, pigmentation, indole, and motility tests in order to obtain the correct identification), inconclusive identification, and unidentified.
ID-GPC identification card. The old VITEK 2 ID-GPC identification card for gram-positive cocci contained 46 fluorimetric tests that included pH change tests and derivatives to detect aminopeptidases and aminooxidases. Substrates used for detection of aminopeptidases are coupled with 7-amino-methylcoumarin; substrates for the detection of aminooxidases are usually coupled with 4-methylumbelliferone. Furthermore, the ID-GPC card included 16 fermentation tests (for D-raffinose, amygdalin, arbutin, D-galactose, glycerol, D-glucose, L-arabinose, lactose, D-maltose, D-mannitol, N-acetylglucosamine, salicin, D-sorbitol, D-trehalose, D-melibiose, and D-xylose), two decarboxylase tests (for ornithine and arginine), and six miscellaneous tests (for urease, pyruvate, optochin, novobiocin, polymyxin B sulfate, and 6% NaCl).
ID-GP identification card. The format of the ID-GP identification card is the same as that of the ID-GPC card, i.e., a 64-well plastic card which now contains 43 instead of 47 tests (see above). The ID-GP identification card includes colorimetric tests for the following reactions: phosphatidylinositol phospholipase C, arginine dihydrolase (two tests), -galactosidase, -glucosidase, alanine-phenylalanine-proline arylamidase, L-aspartic acid arylamidase, -galactosidase, -mannosidase, alkaline phosphatase, L-leucine arylamidase, proline arylamidase, -glucuronidase (two tests), -galactosidase, L-pyroglutamic acid arylamidase, alanine arylamidase, tyrosine arylamidase, and urease. The ID-GP identification card also tests acid production from the following substrates: amygdalin, xylose, -cyclodextrin, sorbitol, galactose, ribose, lactate, lactose, N-acetylglucosamine, maltose, mannitol, mannose, methyl--D-glucopyranoside, pullulan, raffinose, salicin, sucrose, and trehalose. Finally, growth in 6.5% NaCl and tests for resistance to polymyxin B, bacitracin, novobiocin, O129, and optochin are also included in the ID-GP identification card.
In comparison to the ID-GPC database, the ID-GP database of the VITEK 2 system was extended by the following taxa: S. arlettae, S. caprae, S. carnosus, S. equorum, S. gallinarum, and S. vitulinus.
BD Phoenix system. The BD Phoenix ID panel PMIC/ID-13 for gram-positive cocci (called a "combi" panel) contains 45 wells with distinct substrates. Identification is based on the analysis of 20 enzymatic reactions, utilization of 16 carbohydrates and seven other carbon sources, and resistance to two antibiotics (colistin and polymyxin B). The procedures recommended by the manufacturer were strictly followed. Strains were taken out of the freezer, grown on Colombia agar with 5% sheep red blood cells for 16 to 24 h at 37°C, isolated, and grown again for 16 to 24 h at 37°C just before testing. A suspension with a turbidity equal to a 0.5 McFarland standard (accepted range, 0.5 to 0.6) was prepared in ID broth (Becton Dickinson, Erembodegem, Belgium) and poured within 30 min into the panel, which was then loaded into the instrument within 30 min. The BD Phoenix instrument (software version 1.06; BD Phoenix 100) leads to an identification result when a species or group of species is identified with a more than 90% confidence level. This level of confidence is a measurement of the likelihood that the identification obtained is the only correct identification. The average time required to achieve an identification result ranges from 3 to 4 h.
With regard to the Staphylococcus species under study, the databases of VITEK 2 and the BD Phoenix system differ as follows. S. pasteuri und S. felis were only represented in the BD Phoenix system. S. arlettae was only in the VITEK 2 database. S. delphini and S. muscae were not represented in the VITEK 2 and BD Phoenix system databases.
ATB system. The comparison method was based on the use of ID 32 STAPH strips (bioMerieux), which were read automatically after 24 h by using an ATB Expression instrument and ATB Plus software (version ATB Plus 2.9.8 Expert V 2.3.5; bioMerieux). Both the assay strips and the reading equipment were used according to the manufacturer's instructions.
Isolation of genomic DNA. Chromosomal DNA was received from overnight cultures grown on blood agar at 37°C. Genomic DNA was extracted by using the QIAGEN DNA extraction kit according to the manufacturer's suggestions with the modification that 20 μl of lysostaphin (1 mg/ml) and 20 μl of lysozyme (100 mg/ml) were added at the cell lysis step. The concentration of the DNA was assessed spectrophotometrically.
T-RFLP analysis. (i) PCR for T-RFLP. Extracted genomic DNA was used as the template to amplify a 933-bp DNA fragment by PCR as described by Yugueros et al. (24). The primers used for PCR were GF1-HEX (sense; 5'-ATGGTTTTGGTAGAATTGGTCGTTTA-3') and GF2-FAM (antisense; 5'-GACATTTCGTTATCATACCAAGCTG-3'), which were synthesized by MWG-Biotech AG. GF1-HEX was 5' end labeled with phosphoramidite fluorochrome 6-hexachlorofluorescein (5' 6-HEX), whereas GF2-FAM was 5' end labeled with phosphoramidite fluorochrome 6-carboxyfluorescein (5' 6-FAM). Each reaction mixture contained both primers at 1.0 μM, 1x Ex Taq buffer, 800 μM deoxynucleoside triphosphate, 8 mM MgCl2, 1.25 U of TaKaRa Ex Taq polymerase, 5 μl of DNA-containing sample, and high-performance liquid chromatography (HPLC) grade water to a final volume of 50 μl. Amplification was carried out under the following conditions: an initial denaturation step of 2 min at 94°C, followed by 40 cycles of 20 s of denaturation at 94°C, 30 s of annealing at 55°C, and 40 s of extension at 72°C and a final extension step of 72°C for 5 min. The PCR products were purified with the QIAGEN gel extraction kit (QIAGEN).
(ii) Restriction digests. We used three independent restriction digests, as described by Moyer et al. (18), to obtain more-precise information for a single sample. Each digest consisted of 10 μl of the double-fluorescence-marked PCR products, 10 U of a tetrameric restriction enzyme (TacI, BspHI, or DdeI; New England BioLabs), the respective restriction buffer at 1x (New England BioLabs), and HPLC grade water to a final volume of 20 μl. Incubation was carried out at 37°C (BspHI, DdeI) or 65°C (TacI) for 12 h.
(iii) Internal size standard. Escherichia coli C2 was used to obtain additional fragments for the internal size standard. The PCR conditions used for amplification of the 730-bp and 981-bp fragments of the genomic E. coli C2 DNA, fragment cloning, sequencing of selected plasmids, and generation of fluorescently labeled fragments from the plasmids were those previously described by Trotha et al. (22), with some modifications. The primers used for amplification of the 730-bp fragment were 776F (5'-GCAAACAGGATTAGATA-3') and 1492R (5'-TACCTTGTTACGACTT-3'), and those used for the 981-bp fragment were 515F (5'-GCCAGCAGCCGGGGTAA-3') and 1492R (5'-TACCTTGTTACGACTT-3'). 1492R was labeled with ROX at the 5' end for amplification of the fragments from the plasmids. The resulting DNA solution was diluted with HPLC grade water to a concentration of 12 ng/μl and stored at 4°C until use.
(iv) Fragment analysis. One microliter of the restriction digest product was mixed with 19.5 μl of deionized formamide and 1.5 μl of a DNA fragment length standard. A mixture of GS-500 ROX (Applied Biosystems), a ROX 730-bp fragment, and a ROX 981-bp fragment served as an internal size standard. The sizes of the terminal restriction fragments were analyzed by electrophoresis on an ABI PRISM 3100 genetic analyzer (Applied Biosystems) with the data collection software in sequencing mode and the following run parameters: run temperature, 50°C; capillary fill voltage, 184 steps; prerun voltage, 244 V/cm; prerun time, 180 s; injection voltage, 30 V/cm; injection time, 20 s; run voltage, 244 V/cm; data delay time, 1,200 s; run time, 6,500 s. The linear polymer matrix consisted of performance-optimized polymer type 6 (Applied Biosystems). After electrophoresis, the sequencing files produced (.ab1 format) were readjusted in Genescan files (.fsa format). The lengths of the fluorescently FAM- and HEX-labeled fragments were determined by comparison with the fluorescently ROX-labeled size standard consisting of Genescan 500 ROX and the generated 739-bp and 981-bp fragments by using Genescan analysis software 3.7 with the following analysis parameters: analysis range, 400 to 11,000 data points; light smooth option; peak amplitude threshold for dyes Y, G, and R, 50 fluorescence units; for dye B, 15 fluorescence units; minimal peak half width, 2 points; polynomial degree, 3; peak window size, 19 points; slope threshold for peak start, 0.0; slope threshold for peak end, 0.0; full-size call range; local Southern algorithm as size-calling method; baselining, 251 points (see Table 2).
Sequencing of the 16S rRNA gene and the gap gene. Sequencing of the 16S rRNA gene was performed according to a previously described protocol (2). Consensus gap PCR primers Gap1-for (5'-ATGGTTTTGGTAGAATTGGTCGTTTA-3') and Gap2-rev (5'-GACATTTCGTTATCATACCAAGCTG-3') were used to amplify a 933-bp fragment. Sequencing was carried out with the BigDye Terminator v3.1 cycle sequencing kit (Applied Biosystems) according to the manufacturer's instructions on an ABI PRISM 3100 genetic analyzer (Applied Biosystems).
Data analysis. All isolates were tested by the BD Phoenix system, VITEK 2, and gap-based T-RFLP analysis. gap-based T-RFLP analysis is considered the "gold standard" method for identification of CNS. VITEK 2 or BD Phoenix identification results that differed from those obtained by T-RFLP analysis were repeated one more time. If the BD Phoenix or VITEK 2 results did not coincide with the T-RFLP results after repetition, then the ATB procedure was conducted. If the ATB and T-RFLP results differed, then 16S rRNA gene sequencing of the isolated strains was performed.
For verification, gap gene sequencing was applied to all reference strains. Additionally the 16S rRNA gene from reference strains S. delphini, S. muscae, and S. felis was sequenced as these species have not been included in the databases of different automated systems.
RESULTS
Identification of staphylococcal reference strains by automated identification systems. Sequencing of the gap gene was applied to all 27 Staphylococcus sp. reference strains (GenBank accession numbers DQ321674 to DQ321700). In the next step, gap-based T-RFLP was performed with all 27 Staphylococcus sp. reference strains as a basis for correct identification of clinical Staphylococcus species (Table 1). Detailed identification results obtained for each staphylococcal strain by the various phenotypic identification systems are given in Table 2. In this regard, the VITEK 2 system with the ID-GPC card provided the correct species level identification for 11 (42.3%) of the reference strains; 3 strains were identified with low discrimination (11.54%), 4 strains were misidentified (15.38%), 1 strain was unidentified (3.85%), and 8 strains could not be identified (30.77%) because of absence from the database of the system. By the VITEK 2 system with the new ID-GP card, 20 (70.07%) of the reference strains were correctly identified to the species level, 1 strain was identified with low discrimination (3.7%), 4 strains were misidentified (14.81%), 3 strains were not identified (11.11%), and 3 strains were not in the database (11.11%). Thus, the VITEK 2 system with the new ID-GP card showed better performance than with the ID-GPC card.
The BD Phoenix system correctly identified 18 reference strains (66.67%) and misidentified 5 reference strains (18.52%). The BD Phoenix system was not able to identify the reference strains of S. arlettae, S. delphini, and S. muscae (11.11%) because of their absence from the database.
Table 3 summarizes the rates of concordance between identification results obtained with the ID-GPC card and the ID-GP card of the VITEK 2 system and with the BD Phoenix system (ID-13) and those obtained by the molecular gap-based T-RFLP method for the 27 staphylococcal reference species tested.
The ID32 STAPH test (bioMerieux), which is preferentially used as a reference method, misidentified one reference strain (S. kloosii). Three Staphylococcus species from the reference strain panel (S. delphini, S. felis, and S. muscae) were not in the database and thus were not identified. Sequencing of the 16S rRNA gene was performed in those cases to confirm the species. Low-discrimination identifications were obtained as well with API STAPH (S. hyicus, S. intermedius, and S. cohnii) (Table 2).
gap-based T-RFLP method results for clinical staphylococcal isolates. All 27 Staphylococcus sp. reference strains were used as a basis for the identification of CNS by gap-based T-RFLP analysis (Table 1). The 86 staphylococcal clinical isolates were identified as follows: S. capitis, n = 6; S. cohnii subsp. cohnii, n = 1; S. epidermidis, n = 42; S. haemolyticus, n = 30; S. hominis, n = 4; S. lugdunensis, n = 1; S. simulans, n = 1; S. warneri, n = 1 (Table 4).
Identification of clinical non-S. aureus isolates by automated identification systems. With regard to the VITEK 2 system, only the performance of the new ID-GP card was evaluated for the 86 clinical Staphylococcus species. In total, the VITEK 2 system misidentified six strains (6.98%). Two S. epidermidis strains were misidentified as S. hominis, three S. haemolyticus strains were misidentified as S. lentus and S. warneri, and one S. warneri strain was misidentified as S. lentus (Table 4).
The BD Phoenix system misidentified 12 strains (13.95%). The eight misidentified clinical S. epidermidis isolates were identified as members of five different species (S. warneri, S. capitis, S. hominis, S. aureus, and S. cohnii). Furthermore, two S. haemolyticus strains (n = 30) were misidentified as S. epidermidis and S. caprae and four strains (S. epidermidis, S. haemolyticus, and S. hominis) were not identified (4.65%) (Table 4). Thus, the concordances between the T-RFLP results and the VITEK 2 and BD Phoenix system results were 95.24% and 76.19% for S. epidermidis. The results for the individual Staphylococcus species are summarized in Table 5. Table 3 shows the comparison between the identification results obtained with the ID-GP card of the VITEK 2 system and the BD Phoenix system (ID-13) and those obtained by the molecular gap-based T-RFLP method for the 86 clinical staphylococcal strains tested.
DISCUSSION
To the best of our knowledge, this is the first report of a direct comparison between the VITEK 2 system operating with the new colorimetric ID-GP identification card and the BD Phoenix system with the respective ID-GP identification card and a molecular reference method (gap-based T-RFLP) applied to all of the strains under study.
Reliable automated identification and susceptibility testing of clinically relevant bacteria is an essential routine for microbiology laboratories, thus improving patient care. Examples of automated identification systems include the BD Phoenix system (Becton Dickinson) and VITEK 2 (bioMerieux). There exist only a few reports with regard to the evaluation of identification cards for Staphylococcus species on the VITEK 2 instrument. In agreement with the study of Ligozzi et al. (16), 86 of a total of 100 CNS strains were correctly identified to the species level, 10 strains were identified with low discrimination, 1 strain was misidentified, and 3 strains were not identified. In detail, S. epidermidis was identified with an accuracy of 92.7%. Spanu et al. analyzed 275 CNS strains with the VITEK 2 system and the fluorimetric ID-GPC card (21). The VITEK results were considered correct when they were confirmed by use of the ATB ID32 STAPH system (bioMerieux, Marcy l'Etoile, France) plus supplementary manual testing. Overall, VITEK 2 correctly identified 90.5% of the CNS isolates tested. Thus, Spanu et al. clearly stated that there is still a need for improvement in the identification of certain CNS species, especially S. hominis.
Funke and Funke-Kissling used the new colorimetry-based VITEK 2 ID-GP identification card. Eighty-nine of a total of 95 CNS strains were correctly identified to the species level, 5 strains were identified with low discrimination, and only 1 strain was misidentified (11). They stated that the new VITEK 2 ID-GP identification card provides reliable results for the identification of gram-positive cocci under routine laboratory conditions. Wallet et al. used the VITEK 2 system with the fluorimetric (ID-GPC) and colorimetric (ID-GP) cards for the identification of gram-positive bacteria (23). Gram-positive bacteria, including staphylococci, were better identified with the colorimetric card than with the fluorimetric card. For members of the family Micrococcaceae, readings of fluorimetric and colorimetric cards led to 87.2% and 98.3% correct results, respectively. Quite recently, Ben-Ami et al. described the erroneous reporting of CNS as Kocuria spp. by the VITEK 2 system (ID-GPC), which most likely represents misidentification of CNS (4). Determination of whether erroneous reporting of CNS as Kocuria spp. will still occur with the new ID-GP identification card has to await further studies (4, 5).
In our study, we first tested 27 Staphylococcus reference strains with the VITEK 2 system by using the ID-GPC and ID-GP identification cards, with the BD Phoenix system, and with the ATB ID32 STAPH system. The VITEK 2 system with the fluorogenic ID-GPC card correctly identified only 42.3% of the staphylococcal reference strains. The colorimetry-based ID-GP identification card contains new tests allowing an improvement of the VITEK 2 databases. In this regard, 74.1% of the reference strains could be correctly identified. Furthermore, the species S. arlettae, S. caprae, S. carnosus, and S. equorum were added to the database. However, the reference strain of S. arlettae was misidentified with the new VITEK ID-GP card. Only a few studies have been published about the performance of the BD Phoenix system with gram-positive strains, especially staphylococci. In a two-center trial, Fahr et al. focused on the performance of the BD Phoenix system with gram-positive strains (9). They showed that the identification results of the BD Phoenix system were in very high agreement with those of the commercially available comparator system (VITEK 2 with the ID-GPC card) used in that study. The data from our study support these results. The databases for Staphylococcus species from both automated identification systems, VITEK 2 and BD Phoenix, and ID32 STAPH are now quite similar. In this regard, the BD Phoenix system identified 66.7% of the reference strains correctly. When we studied the clinical staphylococcal isolates (n = 86), the range of strains was chosen in such a manner that the typical distribution of staphylococcal subspecies in a human routine microbiological laboratory was reflected. The two automated identification systems, the VITEK system (ID-GP) and the BD Phoenix system, showed different results and misidentified 6.98% and 13.95% of the clinical isolates, respectively. In our study, clinical staphylococcal isolates were misidentified or showed ambiguous results when the automated identification systems were used. This was shown for species seldom associated with infections and was also shown for commonly encountered staphylococcal species, e.g., S. epidermidis and S. haemolyticus. Besides the utmost importance of S. aureus identification, precise identification results—at least at the species level—are relevant for the differentiation of CNS isolates. CNS are increasingly characterized as emerging pathogens and have substantial consequences for the management of nosocomial infections (14). CNS are both an important cause of nosocomially induced bloodstream infections and the most common contaminants of blood cultures. Evaluation of the clinical significance of CNS is vital but often difficult and can have a profound impact on an institution's infection rates (3).
One pitfall in nearly all published studies is the fact that the ID32 STAPH system is widely used as a comparison method for the evaluation of other phenotypic identification systems, including VITEK 2 and the BD Phoenix system. Thus, when VITEK 2 or BD Phoenix results were concordant with each other or with the comparison method, molecular confirmation was not undertaken. Theoretically, some of the strains correctly identified by the new system might actually have been misidentified by both the new system, VITEK 2 or BD Phoenix, and the reference system, e.g., ID32 STAPH. Cunha et al. showed the inability of ID32 STAPH to identify Staphylococcus species correctly (7). They compared their reference method, the scheme for CNS identification proposed by Kloos and Schleifer (15) and modified by Bannerman (1), with ID32 STAPH (19). Renneberg et al. showed in their study that the ID32 STAPH system correctly identified 82.1% of the CNS strains tested (19), whereas in our study the ID32 STAPH system identified 89.4% of the reference and clinical staphylococcal strains correctly. Cunha et al. observed inaccurate identification by the ID32 STAPH method for S. epidermidis (2.2%), S. hominis (25%), S. haemolyticus (37.5%), and S. warneri (47.1%) (7). In our study, a clinical isolate of S. epidermidis (n = 7) was misidentified once (14.3%) and a reference strain of S. kloosii (n = 1) could not be correctly identified.
In our study, we performed a gap-based T-RFLP analysis of all of the staphylococcal isolates tested and used this as the reference method for the automated identification systems. In the case of large discrepancies between phenotypic and genotypic characterizations (T-RFLP), the 16S rRNA genes (2, 13) were additionally sequenced for a definite identification. Because the ID32 STAPH system is regularly used as a reference method, we added results obtained with ID32 STAPH as well.
In summary, the results obtained in this study demonstrate the good performances of the new VITEK 2 cards, allowing their use in routine practice with a highly acceptable level of identification accuracy. Partially similar results were obtained with the BD Phoenix system. However, when unambiguous identification of distinct Staphylococcus species is necessary, molecular identification, e.g., gap-based T-RFLP analysis, is still superior to both phenotypic automated identification systems, as described in this report.
FOOTNOTES
Corresponding author. Mailing address: Otto-von Guericke University, Institute of Medical Microbiology, Leipziger Str. 44, D-39120 Magdeburg, Germany. Phone: 493916713353. Fax: 493916713538. E-mail: Brigitte.koenig@medizin.uni-magdeburg.de.
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ABSTRACT
Coagulase-negative staphylococci (CNS) play a predominant role in nosocomial infections. Rapid, reliable identification of these organisms is essential for accurate diagnosis and prompt effective treatment of these infections. Quite recently, the VITEK 2 g-positive (gram-positive [GP]) identification card (bioMerieux) has been redesigned for greater accuracy in the identification of gram-positive cocci. We compared the BD Phoenix (Becton Dickinson) and VITEK 2 (bioMerieux) automated microbiology systems, using their respective update version cards, and the API ID32 STAPH test. The glyceraldehyde-3-phosphate dehydrogenase (gap) gene-based T-RFLP (terminal restriction fragment length polymorphism) method was used for verifying the results. In total, 86 clinical isolates of CNS and 27 reference strains were analyzed. The results show that for identification of CNS, the automated identification methods using the newest VITEK 2 and BD Phoenix identification cards are comparable. However, API ID32 STAPH revealed more correct results compared to both automated microbiology systems. Despite the increased performance of the phenotypic automated identification systems compared to the former versions, molecular methods, e.g., the gap-based T-RFLP method, still show superior accuracy in identifying Staphylococcus species other than Staphylococcus aureus.
INTRODUCTION
So far, 40 species of the genus Staphylococcus have been identified (8). Staphylococcus aureus is the best known and has been frequently implicated in the etiology of a series of infections and intoxications in humans, whereas coagulase-negative staphylococci (CNS), representing the majority of the species, have been considered to be saprophytic or rarely pathogenic. Currently, several species of CNS are recognized as potential pathogens, mainly causing nosocomial infections, often involved in infections related to implanted medical devices such as intravenous catheters, prosthetic heart valves, and orthopedic implants. The species that most frequently cause diseases in humans are Staphylococcus epidermidis, Staphylococcus haemolyticus, and Staphylococcus saprophyticus. Other significant opportunistic pathogens include Staphylococcus hominis, Staphylococcus warneri, Staphylococcus capitis, Staphylococcus simulans, Staphylococcus cohnii, Staphylococcus xylosus, Staphylococcus saccharolyticus, and Staphylococcus lugdunensis (6, 12, 17, 20).
In this regard, comprehensive and accurate identification of the distinct Staphylococcus species is of great importance. A variety of methods have been proposed for identification schemes based on commercial tests and in relation to the publication of Kloos and Schleifer (15). Various automated identification and susceptibility test systems are currently on the market, among them VITEK 2 (bioMerieux, Marcy l'Etoile, France) and the BD Phoenix system (Becton Dickinson Diagnostic Systems, Sparks, MD.). Quite recently, the VITEK 2 gram-positive (GP) identification card (bioMerieux, Marcy l'Etoile, France) has been redesigned for increased accuracy in the identification of gram-positive cocci. In general, methods based on phenotypic characteristics are hampered by the fact that they depend on the expression of metabolic activities and/or morphological features.
A number of PCR amplicon sequencing-based methods for identification of CNS have been reported, i.e., targeting the 16S rRNA gene, sodA, and the gap gene (2, 10, 24). Despite these techniques, terminal restriction fragment length polymorphism (T-RFLP) analysis of the glyceraldehyde-3-phosphate dehydrogenase gene (gap) represents a high-throughput reproducible method that allows the identification of distinct Staphylococcus species (22). The aim of the present study was to evaluate the performances of VITEK 2 in combination with the newly developed VITEK 2 ID-GP identification card (bioMerieux, Marcy l'Etoile, France) and the BD Phoenix system (Becton Dickinson Diagnostic Systems) for identification of Staphylococcus species in comparison with gap-based T-RFLP analysis as a reference method for accuracy.
MATERIALS AND METHODS
Laboratory, strains, culture conditions, and identification. This study was performed at the Institute of Medical Microbiology of the Otto von Guericke University in Magdeburg, Germany. The following reference strains were selected from the German Collection of Microorganisms and Cell Cultures (DSMZ), the Czech Collection of Microorganisms (CCM), and the American Type Culture Collection (ATCC): Staphylococcus arlettae DSM 20672, Staphylococcus carnosus subsp. carnosus DSM 20501, S. cohnii subsp. cohnii DSM 20260, Staphylococcus delphini DSM 20771, S. epidermidis DSM 20044 (CCM 2124), Staphylococcus equorum subsp. equorum DSM 20674, Staphylococcus hyicus DSM 20459, Staphylococcus intermedius DSM 20373 (CCM 5739), Staphylococcus kloosii DSM20676, S. lugdunensis DSM 4804 (ATCC 43809), S. warneri DSM 20316 (CCM 2730), S. capitis subsp. capitis CCM 2734, Staphylococcus caprae CCM 3573, Staphylococcus chromogenes CCM 3387, Staphylococcus gallinarum CCM 3572, S. haemolyticus CCM 1798, S. hominis subsp. hominis CCM 2732, Staphylococcus lentus CCM 3472, Staphylococcus muscae CCM 4175, S. saprophyticus subsp. saprophyticus CCM 883, Staphylococcus sciuri CCM 3473, S. simulans CCM 2705, S. xylosus CCM 2725, Staphylococcus auricularis ATCC 33753, Staphylococcus felis ATCC 49168, and Staphylococcus schleiferi subsp. schleiferi ATCC 43808. All strains were grown on blood agar and incubated at 37°C in air for 24 h.
The clinical isolates included in the present study were collected within a 1-month period. A total of 86 strains of gram-positive cocci were taken from primary isolation plates set up on Columbia sheep blood agar (Becton Dickinson, Heidelberg, Germany) in our routine clinical laboratory for various types of patient specimens (blood culture, wound swab, respiratory, and urine specimens, etc.). All of these strains were obtained from different patients, and consecutive cultures from the same patient were excluded. The 86 strains tested were identified by conventional methods, as well as by VITEK 2 analysis with the new (ID-GP) and old (ID-GPC) gram-positive coccus identification cards, by the BD Phoenix system using the appropriate identification card for gram-positive cocci (ID-13), and by ID32 STAPH (bioMerieux). For identification by conventional methods, the following characteristics were tested: colony pigmentation, hemolysis, catalase and oxidase reactions, and clumping factor test (bioMerieux). All strains were analyzed by the gap-based T-RFLP method. Major discrepancies between the identification results obtained by the phenotypic methods and gap-based T-RFLP analysis were resolved by partial sequencing of the 16S rRNA gene.
VITEK 2 system. The procedures recommended by the manufacturer were strictly followed. Strains were taken out of the freezer, grown on Colombia agar with 5% sheep red blood cells for 16 to 24 h at 37°C, replated, and grown again for 16 to 24 h at 37°C just before testing. For both identification cards, bacterial suspensions were prepared by emulsifying bacterial isolates in 0.45% saline to the equivalent of a 0.5 McFarland turbidity standard with a VITEK 2 instrument (DensiChek; bioMerieux) (software version 4.01). In the VITEK 2 system, the confidence value is expressed by seven different categories of results: excellent identification, very good identification, good identification, acceptable identification (each of these four categories shows only one identification result), low discrimination (more than one identification result is given, whereupon the software suggests performing additional tests such as oxidase, hemolysis, pigmentation, indole, and motility tests in order to obtain the correct identification), inconclusive identification, and unidentified.
ID-GPC identification card. The old VITEK 2 ID-GPC identification card for gram-positive cocci contained 46 fluorimetric tests that included pH change tests and derivatives to detect aminopeptidases and aminooxidases. Substrates used for detection of aminopeptidases are coupled with 7-amino-methylcoumarin; substrates for the detection of aminooxidases are usually coupled with 4-methylumbelliferone. Furthermore, the ID-GPC card included 16 fermentation tests (for D-raffinose, amygdalin, arbutin, D-galactose, glycerol, D-glucose, L-arabinose, lactose, D-maltose, D-mannitol, N-acetylglucosamine, salicin, D-sorbitol, D-trehalose, D-melibiose, and D-xylose), two decarboxylase tests (for ornithine and arginine), and six miscellaneous tests (for urease, pyruvate, optochin, novobiocin, polymyxin B sulfate, and 6% NaCl).
ID-GP identification card. The format of the ID-GP identification card is the same as that of the ID-GPC card, i.e., a 64-well plastic card which now contains 43 instead of 47 tests (see above). The ID-GP identification card includes colorimetric tests for the following reactions: phosphatidylinositol phospholipase C, arginine dihydrolase (two tests), -galactosidase, -glucosidase, alanine-phenylalanine-proline arylamidase, L-aspartic acid arylamidase, -galactosidase, -mannosidase, alkaline phosphatase, L-leucine arylamidase, proline arylamidase, -glucuronidase (two tests), -galactosidase, L-pyroglutamic acid arylamidase, alanine arylamidase, tyrosine arylamidase, and urease. The ID-GP identification card also tests acid production from the following substrates: amygdalin, xylose, -cyclodextrin, sorbitol, galactose, ribose, lactate, lactose, N-acetylglucosamine, maltose, mannitol, mannose, methyl--D-glucopyranoside, pullulan, raffinose, salicin, sucrose, and trehalose. Finally, growth in 6.5% NaCl and tests for resistance to polymyxin B, bacitracin, novobiocin, O129, and optochin are also included in the ID-GP identification card.
In comparison to the ID-GPC database, the ID-GP database of the VITEK 2 system was extended by the following taxa: S. arlettae, S. caprae, S. carnosus, S. equorum, S. gallinarum, and S. vitulinus.
BD Phoenix system. The BD Phoenix ID panel PMIC/ID-13 for gram-positive cocci (called a "combi" panel) contains 45 wells with distinct substrates. Identification is based on the analysis of 20 enzymatic reactions, utilization of 16 carbohydrates and seven other carbon sources, and resistance to two antibiotics (colistin and polymyxin B). The procedures recommended by the manufacturer were strictly followed. Strains were taken out of the freezer, grown on Colombia agar with 5% sheep red blood cells for 16 to 24 h at 37°C, isolated, and grown again for 16 to 24 h at 37°C just before testing. A suspension with a turbidity equal to a 0.5 McFarland standard (accepted range, 0.5 to 0.6) was prepared in ID broth (Becton Dickinson, Erembodegem, Belgium) and poured within 30 min into the panel, which was then loaded into the instrument within 30 min. The BD Phoenix instrument (software version 1.06; BD Phoenix 100) leads to an identification result when a species or group of species is identified with a more than 90% confidence level. This level of confidence is a measurement of the likelihood that the identification obtained is the only correct identification. The average time required to achieve an identification result ranges from 3 to 4 h.
With regard to the Staphylococcus species under study, the databases of VITEK 2 and the BD Phoenix system differ as follows. S. pasteuri und S. felis were only represented in the BD Phoenix system. S. arlettae was only in the VITEK 2 database. S. delphini and S. muscae were not represented in the VITEK 2 and BD Phoenix system databases.
ATB system. The comparison method was based on the use of ID 32 STAPH strips (bioMerieux), which were read automatically after 24 h by using an ATB Expression instrument and ATB Plus software (version ATB Plus 2.9.8 Expert V 2.3.5; bioMerieux). Both the assay strips and the reading equipment were used according to the manufacturer's instructions.
Isolation of genomic DNA. Chromosomal DNA was received from overnight cultures grown on blood agar at 37°C. Genomic DNA was extracted by using the QIAGEN DNA extraction kit according to the manufacturer's suggestions with the modification that 20 μl of lysostaphin (1 mg/ml) and 20 μl of lysozyme (100 mg/ml) were added at the cell lysis step. The concentration of the DNA was assessed spectrophotometrically.
T-RFLP analysis. (i) PCR for T-RFLP. Extracted genomic DNA was used as the template to amplify a 933-bp DNA fragment by PCR as described by Yugueros et al. (24). The primers used for PCR were GF1-HEX (sense; 5'-ATGGTTTTGGTAGAATTGGTCGTTTA-3') and GF2-FAM (antisense; 5'-GACATTTCGTTATCATACCAAGCTG-3'), which were synthesized by MWG-Biotech AG. GF1-HEX was 5' end labeled with phosphoramidite fluorochrome 6-hexachlorofluorescein (5' 6-HEX), whereas GF2-FAM was 5' end labeled with phosphoramidite fluorochrome 6-carboxyfluorescein (5' 6-FAM). Each reaction mixture contained both primers at 1.0 μM, 1x Ex Taq buffer, 800 μM deoxynucleoside triphosphate, 8 mM MgCl2, 1.25 U of TaKaRa Ex Taq polymerase, 5 μl of DNA-containing sample, and high-performance liquid chromatography (HPLC) grade water to a final volume of 50 μl. Amplification was carried out under the following conditions: an initial denaturation step of 2 min at 94°C, followed by 40 cycles of 20 s of denaturation at 94°C, 30 s of annealing at 55°C, and 40 s of extension at 72°C and a final extension step of 72°C for 5 min. The PCR products were purified with the QIAGEN gel extraction kit (QIAGEN).
(ii) Restriction digests. We used three independent restriction digests, as described by Moyer et al. (18), to obtain more-precise information for a single sample. Each digest consisted of 10 μl of the double-fluorescence-marked PCR products, 10 U of a tetrameric restriction enzyme (TacI, BspHI, or DdeI; New England BioLabs), the respective restriction buffer at 1x (New England BioLabs), and HPLC grade water to a final volume of 20 μl. Incubation was carried out at 37°C (BspHI, DdeI) or 65°C (TacI) for 12 h.
(iii) Internal size standard. Escherichia coli C2 was used to obtain additional fragments for the internal size standard. The PCR conditions used for amplification of the 730-bp and 981-bp fragments of the genomic E. coli C2 DNA, fragment cloning, sequencing of selected plasmids, and generation of fluorescently labeled fragments from the plasmids were those previously described by Trotha et al. (22), with some modifications. The primers used for amplification of the 730-bp fragment were 776F (5'-GCAAACAGGATTAGATA-3') and 1492R (5'-TACCTTGTTACGACTT-3'), and those used for the 981-bp fragment were 515F (5'-GCCAGCAGCCGGGGTAA-3') and 1492R (5'-TACCTTGTTACGACTT-3'). 1492R was labeled with ROX at the 5' end for amplification of the fragments from the plasmids. The resulting DNA solution was diluted with HPLC grade water to a concentration of 12 ng/μl and stored at 4°C until use.
(iv) Fragment analysis. One microliter of the restriction digest product was mixed with 19.5 μl of deionized formamide and 1.5 μl of a DNA fragment length standard. A mixture of GS-500 ROX (Applied Biosystems), a ROX 730-bp fragment, and a ROX 981-bp fragment served as an internal size standard. The sizes of the terminal restriction fragments were analyzed by electrophoresis on an ABI PRISM 3100 genetic analyzer (Applied Biosystems) with the data collection software in sequencing mode and the following run parameters: run temperature, 50°C; capillary fill voltage, 184 steps; prerun voltage, 244 V/cm; prerun time, 180 s; injection voltage, 30 V/cm; injection time, 20 s; run voltage, 244 V/cm; data delay time, 1,200 s; run time, 6,500 s. The linear polymer matrix consisted of performance-optimized polymer type 6 (Applied Biosystems). After electrophoresis, the sequencing files produced (.ab1 format) were readjusted in Genescan files (.fsa format). The lengths of the fluorescently FAM- and HEX-labeled fragments were determined by comparison with the fluorescently ROX-labeled size standard consisting of Genescan 500 ROX and the generated 739-bp and 981-bp fragments by using Genescan analysis software 3.7 with the following analysis parameters: analysis range, 400 to 11,000 data points; light smooth option; peak amplitude threshold for dyes Y, G, and R, 50 fluorescence units; for dye B, 15 fluorescence units; minimal peak half width, 2 points; polynomial degree, 3; peak window size, 19 points; slope threshold for peak start, 0.0; slope threshold for peak end, 0.0; full-size call range; local Southern algorithm as size-calling method; baselining, 251 points (see Table 2).
Sequencing of the 16S rRNA gene and the gap gene. Sequencing of the 16S rRNA gene was performed according to a previously described protocol (2). Consensus gap PCR primers Gap1-for (5'-ATGGTTTTGGTAGAATTGGTCGTTTA-3') and Gap2-rev (5'-GACATTTCGTTATCATACCAAGCTG-3') were used to amplify a 933-bp fragment. Sequencing was carried out with the BigDye Terminator v3.1 cycle sequencing kit (Applied Biosystems) according to the manufacturer's instructions on an ABI PRISM 3100 genetic analyzer (Applied Biosystems).
Data analysis. All isolates were tested by the BD Phoenix system, VITEK 2, and gap-based T-RFLP analysis. gap-based T-RFLP analysis is considered the "gold standard" method for identification of CNS. VITEK 2 or BD Phoenix identification results that differed from those obtained by T-RFLP analysis were repeated one more time. If the BD Phoenix or VITEK 2 results did not coincide with the T-RFLP results after repetition, then the ATB procedure was conducted. If the ATB and T-RFLP results differed, then 16S rRNA gene sequencing of the isolated strains was performed.
For verification, gap gene sequencing was applied to all reference strains. Additionally the 16S rRNA gene from reference strains S. delphini, S. muscae, and S. felis was sequenced as these species have not been included in the databases of different automated systems.
RESULTS
Identification of staphylococcal reference strains by automated identification systems. Sequencing of the gap gene was applied to all 27 Staphylococcus sp. reference strains (GenBank accession numbers DQ321674 to DQ321700). In the next step, gap-based T-RFLP was performed with all 27 Staphylococcus sp. reference strains as a basis for correct identification of clinical Staphylococcus species (Table 1). Detailed identification results obtained for each staphylococcal strain by the various phenotypic identification systems are given in Table 2. In this regard, the VITEK 2 system with the ID-GPC card provided the correct species level identification for 11 (42.3%) of the reference strains; 3 strains were identified with low discrimination (11.54%), 4 strains were misidentified (15.38%), 1 strain was unidentified (3.85%), and 8 strains could not be identified (30.77%) because of absence from the database of the system. By the VITEK 2 system with the new ID-GP card, 20 (70.07%) of the reference strains were correctly identified to the species level, 1 strain was identified with low discrimination (3.7%), 4 strains were misidentified (14.81%), 3 strains were not identified (11.11%), and 3 strains were not in the database (11.11%). Thus, the VITEK 2 system with the new ID-GP card showed better performance than with the ID-GPC card.
The BD Phoenix system correctly identified 18 reference strains (66.67%) and misidentified 5 reference strains (18.52%). The BD Phoenix system was not able to identify the reference strains of S. arlettae, S. delphini, and S. muscae (11.11%) because of their absence from the database.
Table 3 summarizes the rates of concordance between identification results obtained with the ID-GPC card and the ID-GP card of the VITEK 2 system and with the BD Phoenix system (ID-13) and those obtained by the molecular gap-based T-RFLP method for the 27 staphylococcal reference species tested.
The ID32 STAPH test (bioMerieux), which is preferentially used as a reference method, misidentified one reference strain (S. kloosii). Three Staphylococcus species from the reference strain panel (S. delphini, S. felis, and S. muscae) were not in the database and thus were not identified. Sequencing of the 16S rRNA gene was performed in those cases to confirm the species. Low-discrimination identifications were obtained as well with API STAPH (S. hyicus, S. intermedius, and S. cohnii) (Table 2).
gap-based T-RFLP method results for clinical staphylococcal isolates. All 27 Staphylococcus sp. reference strains were used as a basis for the identification of CNS by gap-based T-RFLP analysis (Table 1). The 86 staphylococcal clinical isolates were identified as follows: S. capitis, n = 6; S. cohnii subsp. cohnii, n = 1; S. epidermidis, n = 42; S. haemolyticus, n = 30; S. hominis, n = 4; S. lugdunensis, n = 1; S. simulans, n = 1; S. warneri, n = 1 (Table 4).
Identification of clinical non-S. aureus isolates by automated identification systems. With regard to the VITEK 2 system, only the performance of the new ID-GP card was evaluated for the 86 clinical Staphylococcus species. In total, the VITEK 2 system misidentified six strains (6.98%). Two S. epidermidis strains were misidentified as S. hominis, three S. haemolyticus strains were misidentified as S. lentus and S. warneri, and one S. warneri strain was misidentified as S. lentus (Table 4).
The BD Phoenix system misidentified 12 strains (13.95%). The eight misidentified clinical S. epidermidis isolates were identified as members of five different species (S. warneri, S. capitis, S. hominis, S. aureus, and S. cohnii). Furthermore, two S. haemolyticus strains (n = 30) were misidentified as S. epidermidis and S. caprae and four strains (S. epidermidis, S. haemolyticus, and S. hominis) were not identified (4.65%) (Table 4). Thus, the concordances between the T-RFLP results and the VITEK 2 and BD Phoenix system results were 95.24% and 76.19% for S. epidermidis. The results for the individual Staphylococcus species are summarized in Table 5. Table 3 shows the comparison between the identification results obtained with the ID-GP card of the VITEK 2 system and the BD Phoenix system (ID-13) and those obtained by the molecular gap-based T-RFLP method for the 86 clinical staphylococcal strains tested.
DISCUSSION
To the best of our knowledge, this is the first report of a direct comparison between the VITEK 2 system operating with the new colorimetric ID-GP identification card and the BD Phoenix system with the respective ID-GP identification card and a molecular reference method (gap-based T-RFLP) applied to all of the strains under study.
Reliable automated identification and susceptibility testing of clinically relevant bacteria is an essential routine for microbiology laboratories, thus improving patient care. Examples of automated identification systems include the BD Phoenix system (Becton Dickinson) and VITEK 2 (bioMerieux). There exist only a few reports with regard to the evaluation of identification cards for Staphylococcus species on the VITEK 2 instrument. In agreement with the study of Ligozzi et al. (16), 86 of a total of 100 CNS strains were correctly identified to the species level, 10 strains were identified with low discrimination, 1 strain was misidentified, and 3 strains were not identified. In detail, S. epidermidis was identified with an accuracy of 92.7%. Spanu et al. analyzed 275 CNS strains with the VITEK 2 system and the fluorimetric ID-GPC card (21). The VITEK results were considered correct when they were confirmed by use of the ATB ID32 STAPH system (bioMerieux, Marcy l'Etoile, France) plus supplementary manual testing. Overall, VITEK 2 correctly identified 90.5% of the CNS isolates tested. Thus, Spanu et al. clearly stated that there is still a need for improvement in the identification of certain CNS species, especially S. hominis.
Funke and Funke-Kissling used the new colorimetry-based VITEK 2 ID-GP identification card. Eighty-nine of a total of 95 CNS strains were correctly identified to the species level, 5 strains were identified with low discrimination, and only 1 strain was misidentified (11). They stated that the new VITEK 2 ID-GP identification card provides reliable results for the identification of gram-positive cocci under routine laboratory conditions. Wallet et al. used the VITEK 2 system with the fluorimetric (ID-GPC) and colorimetric (ID-GP) cards for the identification of gram-positive bacteria (23). Gram-positive bacteria, including staphylococci, were better identified with the colorimetric card than with the fluorimetric card. For members of the family Micrococcaceae, readings of fluorimetric and colorimetric cards led to 87.2% and 98.3% correct results, respectively. Quite recently, Ben-Ami et al. described the erroneous reporting of CNS as Kocuria spp. by the VITEK 2 system (ID-GPC), which most likely represents misidentification of CNS (4). Determination of whether erroneous reporting of CNS as Kocuria spp. will still occur with the new ID-GP identification card has to await further studies (4, 5).
In our study, we first tested 27 Staphylococcus reference strains with the VITEK 2 system by using the ID-GPC and ID-GP identification cards, with the BD Phoenix system, and with the ATB ID32 STAPH system. The VITEK 2 system with the fluorogenic ID-GPC card correctly identified only 42.3% of the staphylococcal reference strains. The colorimetry-based ID-GP identification card contains new tests allowing an improvement of the VITEK 2 databases. In this regard, 74.1% of the reference strains could be correctly identified. Furthermore, the species S. arlettae, S. caprae, S. carnosus, and S. equorum were added to the database. However, the reference strain of S. arlettae was misidentified with the new VITEK ID-GP card. Only a few studies have been published about the performance of the BD Phoenix system with gram-positive strains, especially staphylococci. In a two-center trial, Fahr et al. focused on the performance of the BD Phoenix system with gram-positive strains (9). They showed that the identification results of the BD Phoenix system were in very high agreement with those of the commercially available comparator system (VITEK 2 with the ID-GPC card) used in that study. The data from our study support these results. The databases for Staphylococcus species from both automated identification systems, VITEK 2 and BD Phoenix, and ID32 STAPH are now quite similar. In this regard, the BD Phoenix system identified 66.7% of the reference strains correctly. When we studied the clinical staphylococcal isolates (n = 86), the range of strains was chosen in such a manner that the typical distribution of staphylococcal subspecies in a human routine microbiological laboratory was reflected. The two automated identification systems, the VITEK system (ID-GP) and the BD Phoenix system, showed different results and misidentified 6.98% and 13.95% of the clinical isolates, respectively. In our study, clinical staphylococcal isolates were misidentified or showed ambiguous results when the automated identification systems were used. This was shown for species seldom associated with infections and was also shown for commonly encountered staphylococcal species, e.g., S. epidermidis and S. haemolyticus. Besides the utmost importance of S. aureus identification, precise identification results—at least at the species level—are relevant for the differentiation of CNS isolates. CNS are increasingly characterized as emerging pathogens and have substantial consequences for the management of nosocomial infections (14). CNS are both an important cause of nosocomially induced bloodstream infections and the most common contaminants of blood cultures. Evaluation of the clinical significance of CNS is vital but often difficult and can have a profound impact on an institution's infection rates (3).
One pitfall in nearly all published studies is the fact that the ID32 STAPH system is widely used as a comparison method for the evaluation of other phenotypic identification systems, including VITEK 2 and the BD Phoenix system. Thus, when VITEK 2 or BD Phoenix results were concordant with each other or with the comparison method, molecular confirmation was not undertaken. Theoretically, some of the strains correctly identified by the new system might actually have been misidentified by both the new system, VITEK 2 or BD Phoenix, and the reference system, e.g., ID32 STAPH. Cunha et al. showed the inability of ID32 STAPH to identify Staphylococcus species correctly (7). They compared their reference method, the scheme for CNS identification proposed by Kloos and Schleifer (15) and modified by Bannerman (1), with ID32 STAPH (19). Renneberg et al. showed in their study that the ID32 STAPH system correctly identified 82.1% of the CNS strains tested (19), whereas in our study the ID32 STAPH system identified 89.4% of the reference and clinical staphylococcal strains correctly. Cunha et al. observed inaccurate identification by the ID32 STAPH method for S. epidermidis (2.2%), S. hominis (25%), S. haemolyticus (37.5%), and S. warneri (47.1%) (7). In our study, a clinical isolate of S. epidermidis (n = 7) was misidentified once (14.3%) and a reference strain of S. kloosii (n = 1) could not be correctly identified.
In our study, we performed a gap-based T-RFLP analysis of all of the staphylococcal isolates tested and used this as the reference method for the automated identification systems. In the case of large discrepancies between phenotypic and genotypic characterizations (T-RFLP), the 16S rRNA genes (2, 13) were additionally sequenced for a definite identification. Because the ID32 STAPH system is regularly used as a reference method, we added results obtained with ID32 STAPH as well.
In summary, the results obtained in this study demonstrate the good performances of the new VITEK 2 cards, allowing their use in routine practice with a highly acceptable level of identification accuracy. Partially similar results were obtained with the BD Phoenix system. However, when unambiguous identification of distinct Staphylococcus species is necessary, molecular identification, e.g., gap-based T-RFLP analysis, is still superior to both phenotypic automated identification systems, as described in this report.
FOOTNOTES
Corresponding author. Mailing address: Otto-von Guericke University, Institute of Medical Microbiology, Leipziger Str. 44, D-39120 Magdeburg, Germany. Phone: 493916713353. Fax: 493916713538. E-mail: Brigitte.koenig@medizin.uni-magdeburg.de.
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