Abstract
The performances of five automated microbial identification systems, relative to that of a reference identification system, for their ability to accurately and repeatedly identify six common food-borne pathogens were assessed. The systems assessed were the MicroLog system (Biolog Inc., Hayward, Calif.), the Microbial Identification System (MIS; MIDI Inc., Newark, Del.), the VITEK system (bioMérieux Vitek, Hazelwood, Mo.), the MicroScan WalkAway 40 system (Dade-MicroScan International, West Sacramento, Calif.), and the Replianalyzer system (Oxoid Inc., Nepean, Ontario, Canada). The sensitivities and specificities of these systems for the identification of food-borne isolates of Bacillus cereus, Campylobacter jejuni, Listeria monocytogenes, Staphylococcus aureus, Salmonella spp., and verotoxigenic Escherichia coli were determined with 40 reference positive isolates and 40 reference negative isolates for each pathogen. The sensitivities of these systems for the identification of these pathogens ranged from 42.5 to 100%, and the specificities of these systems for the identification of these pathogens ranged from 32.5 to 100%. Some of the systems had difficulty correctly identifying the reference isolates when the results were compared to those from the reference identification tests. The sensitivity of MIS for the identification of S. aureus, B. cereus, E. coli, and C. jejuni, for example, ranged from 47.5 to 72.5%. The sensitivity of the Microlog system for the identification of E. coli was 72.5%, and the sensitivity of the VITEK system for the identification of B. cereus was 42.5%. The specificities of four of the five systems for the identification of all of the species tested with the available databases were greater than or equal to 97.5%; the exception was MIS for the identification of C. jejuni, which displayed a specificity of 32.5% when it was tested with reference negative isolates including Campylobacter coli and other Campylobacter species. All systems had >80% sensitivities for the identification of Salmonella species and Listeria species at the genus level. The repeatability of these systems for the identification of test isolates ranged from 30 to 100%. Not all systems included all six pathogens in their databases; thus, some species could not be tested with all systems. The choice of automated microbial identification system for the identification of a food-borne pathogen would depend on the availability of identification libraries within the systems and the performance of the systems for the identification of the pathogen.
Bacterial food-borne pathogens are an important food safety issue worldwide. Rapid and accurate identification of bacterial pathogens isolated from food samples is important both for food quality assurance and for the tracing of outbreaks of bacterial pathogens within the food supply. Automated microbial identification systems have become widely used in both clinical and food microbiology laboratories. These systems offer some important advantages over conventional methods, including reduced labor, reduced human error, increased sample throughput, and faster turnaround times for test results. Some examples of automated microbial identification systems currently on the market include the Microbial Identification System (MIS; MIDI Inc., Newark, Del.), the MicroScan WalkAway 40 system (Dade Diagnostics Corp., Mississauga, Ontario, Canada), the MicroLog system (Biolog Inc., Hayward, Calif.), the VITEK system (bioMérieux Vitek, Hazelwood, Mo.), and the Replianalyzer system (Oxoid Inc., Nepean, Ontario, Canada).
While several studies have examined the performances of automated microbial identification systems for the examination of clinical isolates (11, 18, 21–27, 29), little work has been done to study the sensitivities and specificities of these systems for the testing of pathogens isolated from food samples. Many of the previous studies of clinical isolates were performed with versions of these automated microbial identification systems that contained now obsolete databases (11, 14, 18, 25, 28), and many of the studies did not include species that are often detected as pathogens in food samples. Therefore, it is essential to determine the sensitivities, specificities, and repeatabilities of these systems for the identification of important pathogens isolated from food samples.
The objectives of the study were (i) to determine the sensitivities and specificities of the MicroLog system, MIS, the VITEK system, the WalkAway 40 system, and the Replianalyzer system for the identification of food isolates of Bacillus cereus, Campylobacter jejuni, Listeria monocytogenes, Staphylococcus aureus, Salmonella spp., and verotoxigenic Escherichia coli and (ii) to determine the repeatabilities of these systems for the identification of these food isolates.
MATERIALS AND METHODS
Bacterial isolates.
The bacterial isolates used in this study included 40 reference positive isolates and 40 reference negative isolates each of B. cereus, C. jejuni, L. monocytogenes, S. aureus, Salmonella species, and verotoxigenic E. coli (Table 1). All of the reference positive isolates were obtained from food samples and included five American Type Culture Collection (ATCC) strains and 35 laboratory isolates from a wide variety of food sources. The reference negative isolates were cultured from food, clinical, or environmental samples and included five ATCC strains and 35 laboratory isolates which were related to but not identical to the pathogen of interest. All isolates were confirmed as either reference positive isolates or reference negative isolates by using reference identification tests, and only those isolates which were correctly identified by the reference identification tests at a good confidence level were included in the study.
TABLE 1.
Reference isolates used to determine specificities of five automated microbial identification systems for common food-borne pathogens
| Pathogen | Reference positive isolates | Reference negative isolates |
|---|---|---|
| B. cereus | 35 laboratory isolates, ATCC 4342, ATCC 14579, ATCC 7004, ATCC 33018, ATCC 11778 | 16 Bacillus spp. (non-B. cereus), 2 Bacillus amyloliquifaciens, 1 Bacillus circulans, 1 Bacillus megaterium, 1 Bacillus sphaericus, 3 Bacillus subtilis, 3 Bacillus lichenformis, 2 Bacillus pumulis, 1 Bacillus pasteurii, 3 Bacillus circulans, 1 Bacillus lentus, 2 E. coli, 1 S. aureus, 1 Staphylococcus haemolyticus, 1 L. monocytogenes, 1 Listeria seeligeri |
| C. jejuni | 35 laboratory isolates, ATCC 49349, ATCC 33560, ATCC 29428, ATCC 43432, ATCC 33291 | 29 C. coli, 3 Campylobacter lari, 1 Campylobacter fetus, 1 Campylobacter hyointenstinalis, 5 Ochrobactum anthropi, 1 Pseudomonas aeruginosa |
| L. monocytogenes | 35 laboratory isolates, ATCC 19111, ATCC 19112, ATCC 19117, ATCC 19114, ATCC 19116 | 15 Listeria innocua, 10 Listeria welshimeri, 7 Listeria seeligeri, 2 Listeria murrayi, 1 Listeria ivanovii, 1 Listeria grayi, 1 S. haemolyticus, 1 Staphylococcus epidermidis, 1 Streptococcus agalactiae, 1 R. equi |
| S. aureus | 35 laboratory isolates, ATCC 25923, ATCC 29213, ATCC 9144, ATCC 12600, ATCC 27154 | 7 Staphylococcus intermedius, 6 Staphylococcus xylosus, 5 Staphylococcus cohnii subsp., 4 Staphylococcus schleiferi, subsp., 4 S. haemolyticus, 2 Staphylococcus lugdunensis, 4 Staphylococcus hyicus, 1 Staphylococcus sciuri, 2 Staphylococcus saprophyticus, 3 Staphylococcus epidermidis, 1 Staphylococcus chromogenes, 1 Micrococcus luteus |
| Verotoxigenic E. coli | 35 laboratory isolates, ATCC 43887, ATCC 43889, ATCC 43895, ATCC 43894, ATCC 25922 | 14 Enterobacter spp., 6 Klebsiella spp., 8 Citrobacter spp., 2 Hafnia alvei, 2 Serratia spp., 1 Yersinia enterocolitica, 1 Pseudomonas alcaligenes, 1 Acinetobacter baumanii, 1 P. aeruginosa, 1 Kluyvera ascorbata, 3 Shigella spp. |
| Salmonella spp. | 35 laboratory isolates, ATCC 8326, ATCC 8391, ATCC 6962, ATCC 13076, ATCC 14028 | 14 Enterobacter spp., 6 Klebsiella spp., 2 H. alvei, 2 Serratia spp. 1 Y. enterocolitica, 10 Citrobacter spp., 3 E. coli, 1 Edwardsiella tarda, 1 S. sonnei |
Preparation of study isolates.
Stock cultures of reference positive isolates and reference negative isolates were subcultured from a frozen state onto Trypticase soy agar (TSA) with 5% sheep blood (BBL, Cockeysville, Md.) and were incubated aerobically at 35°C for 24 h; however, C. jejuni reference positive isolates and reference negative isolates were incubated microaerophilically for 48 to 72 h. Second and third subcultures were performed with the media and incubation conditions recommended by the manufacturer of each identification system. Isolates from the third subculture was used to test each system.
Reference identification tests.
The identities of the reference positive isolates and the reference negative isolates of verotoxigenic E. coli and Salmonella spp. were confirmed with the API 20E identification kit (bioMérieux Vitek) according to directions that accompanied the product. The identities of the reference positive isolates and the reference negative isolates of B. cereus were confirmed by a biochemical testing scheme consisting of Gram staining, catalase reaction, hemolysin production on TSA plus 5% sheep blood (BBL), and lecithinase production on B. cereus selective agar (Oxoid) supplemented with polymyxin B (Oxoid) and egg yolk emulsion (Oxoid). The identities of the B. cereus isolates were further confirmed by using the API 50 CHB (bioMérieux Vitek) test kit. The identities of the C. jejuni reference positive isolates and reference negative isolates were confirmed by using a biochemical identification scheme consisting of Gram staining, catalase reaction, oxidase reaction, the presence of corkscrew-like motility as seen under a dark-field microscope, hippurate hydrolysis, and sensitivity to nalidixic acid and resistance to cephalothin (20). The reference method used in this study to confirm the identities of the L. monocytogenes reference positive isolates and reference negative isolates was a biochemical scheme, which included Gram staining, catalase reaction, esculin hydrolysis on Oxford agar, hemolysis on horse blood agar, CAMP reaction, fermentation of rhamnose, xylose, and mannitol, and the presence of tumbling motility. A modified version of the simplified scheme of Kloos and Schleifer (13) was used to confirm the identities of the S. aureus reference positive isolates and reference negative isolates. This scheme consisted of Gram staining, hemolysin production on TSA plus 5% sheep blood (BBL), colony pigment production, catalase reaction, tube coagulase test, urea and nitrate reactions, and fermentation of arabinose, lactose, maltose, mannitol, sucrose, trehalose, and xylose. These reference identification tests were designed to identify the reference positive isolates to the species level and to confirm that the reference negative isolates were species other than that of the reference positive isolate to which they were being compared.
Bacterial identification systems.
The automated microbial identification systems included in this study are listed in Table 2. The WalkAway 40 and the VITEK systems both entail inoculation of a microbial suspension into prepared microwell plates for the WalkAway 40 system or test cards for the VITEK system. These microwell plates and test cards contain a variety of conventional and proprietary biochemical substrates and antibiotics. Growth of bacteria within the microwells (WalkAway 40 system) or test card wells (VITEK system) results in biochemical substrate changes which can be interpreted by a specialized plate reader (WalkAway 40 system) or automated test card reader (VITEK system) to produce a biochemical profile. This profile can be compared to the profiles of known microorganisms to generate an identification. Operation of the MicroLog system also involves inoculation of a microbial suspension into specialized microwell plates. The wells of these plates contain buffered media with different carbon sources and an indicator dye, tetrazolium violet. The dye is reduced when different carbon sources are utilized, resulting in a biochemical profile which can be compared to the profiles of known microorganisms to generate an identification. The Replianalyzer is similar to the WalkAway 40 and VITEK systems in that a profile of biochemical reactions is generated and compared to those of known microorganisms, but this system uses agar plates rather than microwell plates. MIS is significantly different from the other systems because it is based on a comparison of the fatty acid methyl ester profiles for unknown microorganisms to those for known microorganisms to generate an identification.
TABLE 2.
Summary of automated bacterial identification systems included in the study and the food-borne bacterial pathogens used to test these systemsa
| Species | Reference test | System used
|
||||
|---|---|---|---|---|---|---|
| WalkAway 40 | MIS | VITEK | Replianalyzer | MicroLog | ||
| L. monocytogenes | Biochemical scheme | Yes | Yes | Yes | No | Yes |
| S. aureusb | Biochemical scheme | Yes | Yes | Yes | No | Yes |
| B. cereusb | Biochemical scheme, API 50 CHB | No | Yes | Yes | No | Yes |
| C. jejuni | Biochemical scheme | No | Yes | No | No | No |
| Salmonella spp. | API 20E | Yes | Yes | Yes | Yes | Yes |
| E. coli | API 20E | Yes | Yes | Yes | Yes | Yes |
The following database versions of the automated microbial identification systems were used in this study: WalkAway 40 system, version 20.37; MIS, version 3.8; VITEK system, version DSAMSO-R10.3; Replianalyzer system, version 2.11; MicroLog system, version 3.5.
S. aureus and B. cereus cultures were not tested with the Biolog databases because these databases were in the process of being revised at the time of the study.
Isolates to be identified with MIS were grown and processed as described in the MIS operating manual (17) for the CLIN library and were tested with the Sherlock, version 1.06, CLIN library database, version 3.8. Isolates to be identified with the Microscan WalkAway 40 system were grown and processed as described in the WalkAway 40 system operating manual (5), inoculated into Dried Overnight Gram Positive ID panels (L. monocytogenes and S. aureus) or Dried Overnight Gram Negative ID panels (Salmonella spp. and verotoxigenic E. coli), and evaluated with the Microscan Data Management System, version 20.57, database. Isolates to be identified with the Replianalyzer system were grown and processed as described in the Replianalyzer operating manuals (3) and were evaluated with the Replianalyzer, version 2.11, database. Isolates to be identified with the MicroLog system were grown and processed as described in the Biolog system manual (6), inoculated into GP MicroPlates (L. monocytogenes) or GN MicroPlates (Salmonella spp. and verotoxigenic E. coli), and analyzed with the version DE, release 3.5, database. Isolates to be identified with the VITEK system were grown and processed as described in the VITEK operator’s manual (7), inoculated into the GPI card (L. monocytogenes and S. aureus), the GNI card (Salmonella spp. and verotoxigenic E. coli), or the BAC card (B. cereus), and evaluated with the VITEK, version DSAMSO-R10.3, database. Reference negative isolates and reference positive isolates of each pathogen were examined with the same systems under the same conditions.
Analysis of results.
The different systems generated identification results in different formats. Most of the automated systems had a specific minimum level of probability that was required for the identification of an unknown organism to be interpreted with good confidence. The MicroLog system required a minimum similarity index of 0.500. MIS required a minimum similarity index of 0.300 with a minimum separation of 0.100 between the first identification and any secondary identifications. The WalkAway 40 system required a probability of greater than or equal to 85%. The Replianalyzer system required a probability of 95%. The VITEK system did not have a specific probability cutoff level for acceptable identifications. A probability of greater than or equal to 95% was used so that the results obtained with the VITEK system could be directly compared with those obtained with the other systems.
The sensitivities of the test systems were determined by testing each system with 40 known reference positive isolates of each of the six pathogens. Sensitivity in this study was defined as the proportion of the reference positive isolates which were correctly identified with the automated microbial identification systems with an acceptable identification confidence level, as specified by the system’s manufacturer. The proportion of reference positive isolates which were correctly identified with the automated microbial identification systems but with unacceptably low confidence levels was also examined.
The specificities of the test systems were determined by testing each system with 40 isolates of bacteria which were not the pathogen of interest but which showed similarities in terms of their biochemical reactions and Gram staining results to those of the pathogen of interest. Specificity in this study was defined as the proportion of reference negative isolates which were not identified as the pathogen of interest.
The repeatabilities of the test systems were determined by performing repeat analyses for 20 randomly selected ATCC strains and laboratory isolates from among both the reference positive isolates and the reference negative isolates of each pathogen. The second subculture of the first analysis was used as a starting point for the replicate analysis of each isolate, and the replicate analysis was performed once for each isolate on days different from the days of performance of the initial analysis. The identification results and the confidence levels of the identifications were examined. Repeatability of identification was defined as the proportion of repeat analyses which generated the same identification with similar confidence levels, i.e., having either acceptable or unacceptable confidence levels in both analyses. The proportion of repeat analyses which generated the same identification but at different confidence levels was also examined.
RESULTS
The sensitivities and specificities of the automated microbial identification systems for each of the pathogens of interest are summarized in Table 3. The data indicate the sensitivity and specificity of each system for the pathogens of interest when identification results with acceptable confidence levels were analyzed. The repeatabilities of the different automated microbial identification systems for reference positive isolates and reference negative isolates for the pathogens of interest are presented in Table 4. The values represent the proportions of repeat analyses which generated the same identification with similar confidence levels.
TABLE 3.
Summary of sensitivities and specificities of several automated bacterial identification systems tested with food-borne pathogens
| Pathogen and system | % Sensitivitya | % Specificityb |
|---|---|---|
| Listeria species | ||
| WalkAway 40 | 100 | 100 |
| MIS | 90 | 100 |
| VITEK | 97.5 | 100 |
| MicroLog | 97.5 | 100 |
| S. aureus | ||
| WalkAway 40 | 97.5 | 100 |
| MIS | 47.5 | 100 |
| VITEK | 95 | 95 |
| B. cereus | ||
| MIS | 55 | 97.5 |
| VITEK | 42.5 | 97.5 |
| C. jejuni, MIS | 72.5 | 32.5 |
| Salmonella species | ||
| WalkAway 40 | 97.5 | 100 |
| MIS | 85 | 100 |
| VITEK | 100 | 100 |
| Replianalyzer | 95 | 100 |
| MicroLog | 95 | 100 |
| E. coli | ||
| WalkAway 40 | 100 | 100 |
| MIS | 52.5 | 97.5 |
| VITEK | 100 | 97.5 |
| Replianalyzer | 90 | 100 |
| MicroLog | 72.5 | 100 |
Proportion of reference positive strains which were correctly identified with an acceptable confidence rating.
Proportion of reference negative strains which were not identified as the pathogen of concern with an acceptable confidence rating.
TABLE 4.
Repeatabilities of identifications generated by automated bacterial identification systems against food-borne pathogens and closely related species
| Pathogen and system | Repeatability (%) in replicate analysesa
|
|
|---|---|---|
| Reference positive isolates | Reference negative isolates | |
| L. monocytogenes | ||
| Biochemicals | 100 | 100 |
| WalkAway 40 | 100 | 90 |
| MIS | 30 | 55 |
| VITEK | 100 | 85 |
| MicroLog | 100 | 85 |
| S. aureus | ||
| Biochemicals | 100 | 85 |
| WalkAway 40 | 100 | 75 |
| MIS | 60 | 90 |
| VITEK | 90 | 65 |
| B. cereus | ||
| Biochemicals | 100 | 100 |
| MIS | 90 | 80 |
| VITEK | 60 | 80 |
| C. jejuni | ||
| Biochemicals | 100 | 100 |
| MIS | 90 | 75 |
| Salmonella spp. | ||
| API 20E | 100 | 90 |
| WalkAway 40 | 95 | 90 |
| MIS | 90 | 65 |
| VITEK | 100 | 100 |
| Replianalyzer | 100 | 85 |
| MicroLog | 85 | 65 |
| E. coli | ||
| API 20E | 100 | 90 |
| WalkAway 40 | 100 | 90 |
| MIS | 70 | 65 |
| VITEK | 95 | 100 |
| Replianalyzer | 100 | 85 |
| MicroLog | 70 | 65 |
Proportion of replicate analyses which generated the same identification with similar confidence rating.
DISCUSSION
There are a number of factors to be considered when determining which automated microbial identification system is most appropriate for the detection of food-borne pathogens within a particular laboratory. These factors include the initial investment that is required, operating costs, technician time, range of organisms within the system’s database, and the ability of the system to correctly identify food pathogens of interest. The last two variables were examined in this study. The automated microbial identification systems evaluated included MIS, the WalkAway 40 system, the MicroLog system, the VITEK system, and the Replianalyzer system.
The WalkAway 40 system, the VITEK system, and the MicroLog system all contained databases for the identification of Listeria spp. MIS contained a database for the identification of L. monocytogenes specifically. To compare the systems fairly, only identifications to the genus level are reported in Table 3. All four of the systems performed well in identifying L. monocytogenes to the genus level, with sensitivities of 90 to 100% and specificities of 100%. A much lower specificity was observed when MIS was used to identify L. monocytogenes to the species level because Listeria innocua isolates were frequently identified as L. monocytogenes. The repeatabilities observed for the different systems were also good, with the exception of the MIS, which showed a lower repeatability than the other systems. The repeatability of the MIS was increased to 70% when species identification, but not confidence rating, was considered. While all of these systems could be used reliably as a screening method for the detection of Listeria spp. to the genus level, further biochemical tests would be required to determine whether the isolate was a potentially pathogenic L. monocytogenes isolate or a nonpathogenic Listeria species. Presumptive identification of Listeria species from colonies on selective media, such as Oxford agar, requires only a few simple tests, so there is at present little advantage in using these automated identification systems for the identification of L. monocytogenes.
The WalkAway 40 system, the VITEK system, and MIS all contained databases for the identification of S. aureus. The MicroLog and the Replianalyzer system databases for the identification of Staphylococcus and related species were being developed or upgraded, and they were not included in this study. The WalkAway 40 and the VITEK systems both showed good sensitivities and specificities for the identification of S. aureus. MIS showed 100% specificity for the identification of S. aureus but a sensitivity of only 47.5%. This sensitivity of MIS for the identification of S. aureus increased to 87.5% if correct identifications with low confidence levels were included, suggesting that the fatty acid compositions of the food isolates examined were slightly different from those of the isolates within the database. The specificity of the system was reduced to 90% when results with low confidence levels were included in the analysis. Repeatability levels for all three systems were slightly higher for reference positive isolates than for reference negative isolates, ranging from 60 to 100% when both identification and confidence level were considered. Presumptive identification of S. aureus requires only a few biochemical tests which are available in most nonautomated methods; hence, there is little advantage in using these automated identification systems for the identification of this organism.
Both MIS and the VITEK system contained databases for the identification of B. cereus isolates. At the time of this study, the MicroLog system database for B. cereus was being upgraded; therefore, this system was not evaluated for B. cereus. Neither MIS nor the VITEK system was able to identify B. cereus with a high sensitivity, even if correct identifications with low confidence levels were included. Some investigators have proposed that B. cereus, Bacillus mycoides, and Bacillus thuringiensis are very closely related and should be merged into a single species (2, 8). When the results were reanalyzed with the definition of a correct identification expanded to include B. mycoides and B. thuringiensis species, the sensitivities of MIS and the VITEK system increased to 82.5 and 67.5%, respectively. The two systems showed a high specificity (97.5%) for B. cereus. The repeatability of the VITEK system for this organism was somewhat low at 60%, while MIS showed a repeatability of 90%. The results obtained by the API 50 CHB test kit corresponded well with those obtained by the biochemical reference scheme when tests were performed with B. cereus isolates.
MIS was the only system with a database for the identification of Campylobacter species. The sensitivity and specificity of this system for the identification of C. jejuni were 72.5 and 32.5%, respectively. The sensitivity increased to 92.5% if correct identifications with low confidence levels were included. However, the specificity of the system declined to 30% when other Campylobacter species misidentified as C. jejuni with low confidence levels were included in the estimation of specificity. The low specificity of MIS for C. jejuni may be due to the fact that most of the reference negative isolates used in the study were Campylobacter coli and the system appears to have difficulty distinguishing C. coli from the closely related species C. jejuni. Both C. jejuni and C. coli are common food-borne pathogens; thus, MIS may be useful as a screening method for the identification of pathogenic Campylobacter isolates. The repeatability of MIS was found to be 90% for C. jejuni and 75% for related species when the same identification and confidence levels were considered in the analysis. The identification of C. jejuni is similar to that of L. monocytogenes in that presumptive identification from selective media requires only a few simple laboratory tests; hence, there is little advantage in the use of automated systems for the identification of Campylobacter to the genus level unless these systems are able to differentiate pathogenic and nonpathogenic Campylobacter species with high specificities and sensitivities.
All of the systems included in this study had developed databases for the identification of Salmonella spp., and all of the systems showed good sensitivities for Salmonella identification, with values ranging from 85 to 100%. Specificities of 100% were observed for all of the systems tested, suggesting that false-positive identifications would not be a problem for Salmonella isolates. The repeatabilities of the different systems when they were tested with Salmonella spp. and related isolates were highest with the VITEK, the WalkAway 40, and the Replianalyzer systems and were somewhat higher for reference positive isolates than for reference negative isolates.
While all of the systems included in this study had databases for the identification of E. coli, none of these databases distinguished between verotoxigenic E. coli and other E. coli strains. One study, however, reported that a limited number of biochemical profiles were generated when E. coli O157:H7 strains were screened with the MicroScan Overnight Panel System (1). The Replianalyzer database may also detect E. coli O157:H7 on the basis of a sorbitol-negative reaction. The WalkAway 40, the VITEK, and the Replianalyzer systems appeared to be well adapted for the identification of E. coli isolates, with sensitivities of 90 to 100% and specificities of 97.5 to 100%. Both the MicroLog system and MIS reported somewhat lower sensitivities; however, these sensitivities increased to acceptable levels if correct identifications with low confidence levels were included in the analysis. Inclusion of results with lower confidence levels in the analysis resulted in a slightly lower specificity of MIS for this organism. The WalkAway 40, VITEK, and Replianalyzer systems appeared to be the most repeatable for verotoxigenic E. coli and related isolates, while MIS and the MicroLog system had somewhat lower repeatabilities.
In summary, none of the systems appeared to offer any advantage over biochemical identification schemes for L. monocytogenes identification; however, very good results (>90% sensitivity) were obtained for the identification of S. aureus, Salmonella spp., and verotoxigenic E. coli by the WalkAway 40 and the VITEK systems. The Replianalyzer system had a ≥90% sensitivity for the identification of Salmonella and verotoxigenic E. coli. The MicroLog system had >90% sensitivity for the identification of Salmonella spp. and >90% sensitivity for the identification of verotoxigenic E. coli when correct identification results with or without acceptable confidence ratings were included in the results. Similarly, MIS had >90% sensitivity for the identification of the B. cereus group, C. jejuni, and Salmonella spp. when correct identification results with or without acceptable confidence ratings were included in the analysis. The lower sensitivities observed when some of these pathogens were tested with MIS may be influenced by the fact that the reference systems for these species were based on biochemical reactions, while the MIS identifications are based on the analysis of the fatty acid composition of the unknown microorganism. MIS showed promising results for the identification of Campylobacter species, and both the VITEK system and MIS showed a fairly good ability to identify B. cereus group isolates.
ACKNOWLEDGMENTS
We acknowledge the financial support received from the Enhanced Food Quality and Safety Program administered by the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA) and the contributions of consumable supplies by Dade Diagnostics Corp., MicroLog Inc., bioMérieux VITEK, and Oxoid Canada Inc. We also thank the following people for contributing bacterial isolates for this study: David Woodward, National Laboratory for Enteric Pathogens, Health Canada; Peter Boleszczuk and Mike Brodsky, Ontario Ministry of Health, Laboratory Services Branch, Etobicoke, Ontario, Canada; Luba Stokes, Victoria Hospital, London, Ontario, Canada; Roger Shuttleworth, University Hospital, London, Ontario, Canada; Noni Smart, Laboratory Services Division, University of Guelph, Guelph, Ontario, Canada; and C. E. Park, Health Canada, Ottawa, Ontario, Canada.
REFERENCES
- 1.Abbott S L, Hanson D F, Felland T D, Connell S, Shum A H, Janda J M. Escherichia coli O157:H7 generates a unique biochemical profile on MicroScan conventional gram-negative identification panels. J Clin Microbiol. 1994;32:823–824. doi: 10.1128/jcm.32.3.823-824.1994. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Ash C, Farrow J A E, Dorsh M, Stackebrant E, Collins M D. Comparative analysis of Bacillus anthracis, Bacillus cereus, and related species on the basis of reverse transcriptase sequencing of 16S rRNA. Int J Syst Bacteriol. 1991;41:343–346. doi: 10.1099/00207713-41-3-343. [DOI] [PubMed] [Google Scholar]
- 3.AutoMed Cathra Systems. Cathra microbiology manual, Cathra Replidex manual, Cathra Replianalyzer II manual. Arden Mills, Minn: AutoMed Cathra Systems; 1994. [Google Scholar]
- 4.Bannerman T L, Kleeman K T, Kloos W E. Evaluation of the VITEK systems Gram-Positive Identification card for species identification of coagulase-negative staphylococci. J Clin Microbiol. 1993;31:1322–1325. doi: 10.1128/jcm.31.5.1322-1325.1993. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Baxter Diagnostics Inc. MicroScan operators manual for Walkaway systems. West Sacramento, Calif: Baxter Diagnostics Inc.; 1992. [Google Scholar]
- 6.Biolog Inc. MicroLog operating manual. Hayward, Calif: Biolog Inc.; 1992. [Google Scholar]
- 7.bioMérieux Vitek. VITEK System manual. Hazelwood, Mo: bioMérieux Vitek; 1996. [Google Scholar]
- 8.Carlson C R, Caugant D A, Kolstø A B. Genotypic diversity among Bacillus cereus and Bacillus thuringiensis strains. Appl Environ Microbiol. 1994;60:1719–1725. doi: 10.1128/aem.60.6.1719-1725.1994. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Champagne C P, Laing R R, Roy D, Mafu A A, Griffiths M W. Psychrotrophs in dairy products: their effects and their control. Crit Rev Food Sci Nutr. 1994;34:1–30. doi: 10.1080/10408399409527648. [DOI] [PubMed] [Google Scholar]
- 10.Holmes B, Costas M, Ganner M, On S L W, Stevens M. Evaluation of Biolog system for identification of some gram-negative bacteria of clinical importance. J Clin Microbiol. 1994;32:1970–1975. doi: 10.1128/jcm.32.8.1970-1975.1994. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Hussain Z, Stokes L, Stevens D L, Schieven B C, Lannigan R, Jones C. Comparison of the MicroScan system with the API Staph-Ident system for species identification of coagulase-negative staphylococci. J Clin Microbiol. 1986;23:126–128. doi: 10.1128/jcm.23.1.126-128.1986. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Klingler J M, Stowe R P, Obenhuber D C, Groves T O, Mishra S K, Pierson D L. Evaluation of the Biolog automated microbial identification system. Appl Environ Microbiol. 1992;58:2089–2092. doi: 10.1128/aem.58.6.2089-2092.1992. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Kloos W E, Schleifer K H. Simplified scheme for routine identification of human Staphylococcus species. J Clin Microbiol. 1975;1:82–88. doi: 10.1128/jcm.1.1.82-88.1975. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Kloos W E, George C G. Identification of Staphylococcus species and subspecies with the MicroScan Pos ID and Rapid Pos ID panel systems. J Clin Microbiol. 1991;29:738–744. doi: 10.1128/jcm.29.4.738-744.1991. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Knight M T, Wood D W, Black J F, Gosney G, Rigney R O, Agin J R. Gram-Negative Identification card for identification of Salmonella, Escherichia coli, and other Enterobacteriaceae isolated from foods: collaborative study. J Assoc Off Chem. 1990;73:729–733. [PubMed] [Google Scholar]
- 16.Kramer J M, Gilbert R J. Bacillus cereus and other Bacillus species. In: Doyle M P, editor. Foodborne bacterial pathogens. New York, N.Y: Marcel Dekker, Inc.; 1989. pp. 21–70. [Google Scholar]
- 17.Microbial ID Inc. Microbial Identification System operating manual, version 4. Newark, Del: Microbial ID Inc.; 1993. [Google Scholar]
- 18.Miller J M, Biddle J W, Quenzer V K, McLaughlin J C. Evaluation of Biolog for identification of members of the family Micrococcaceae. J Clin Microbiol. 1993;31:3170–3173. doi: 10.1128/jcm.31.12.3170-3173.1993. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Miller M, Rhoden D L. Preliminary evaluation of Biolog, a carbon source utilization method for bacterial identification. J Clin Microbiol. 1991;29:1143–1147. doi: 10.1128/jcm.29.6.1143-1147.1991. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Nachamkin I. Campylobacter and Arcobacter. In: Murray P R, Baron E J, Pfaller M A, Tenover F C, Yolken R H, editors. Manual of clinical microbiology. 6th ed. Washington, D.C: American Society for Microbiology; 1995. pp. 483–491. [Google Scholar]
- 21.O’Hara C M, Miller J M. Evaluation of the autoSCAN-W/A system for rapid (2 hour) identification of members of the family Enterobacteriaceae. J Clin Microbiol. 1992;30:1541–1543. doi: 10.1128/jcm.30.6.1541-1543.1992. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.O’Hara C M, Tenover F C, Miller J M. Parallel comparison of accuracy of API 20E, Vitek GNI, Microscan Walk/Away Rapid ID, and Becton Dickinson Cobos Micro ID-E/NF for identification of members of the family Enterobacteriaceae and common gram-negative, non-glucose-fermenting bacilli. J Clin Microbiol. 1993;31:3165–3169. doi: 10.1128/jcm.31.12.3165-3169.1993. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Osterhout G J, Shull V H, Dick J D. Identification of clinical isolates of gram-negative nonfermentative bacteria by an automated cellular fatty acid identification system. J Clin Microbiol. 1991;29:1822–1830. doi: 10.1128/jcm.29.9.1822-1830.1991. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Pfaller M A, Sahm D, O’Hara C, Ciaglia C, Yu M, Yamane N, Scharnweber G, Rhoden D. Comparison of the AutoSCAN-W/A Rapid Bacterial Identification system and the Vitek AutoMicrobic system for identification of gram-negative bacilli. J Clin Microbiol. 1991;29:1422–1428. doi: 10.1128/jcm.29.7.1422-1428.1991. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Rhoads S, Marinelli L, Imperatrice C A, Nachamkin I. Comparison of MicroScan WalkAway system and Vitek system for identification of gram-negative bacteria. J Clin Microbiol. 1995;33:3044–3046. doi: 10.1128/jcm.33.11.3044-3046.1995. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Robinson A, McCarter Y S, Tetreault J. Comparison of Crystal Enteric/Nonfermenter System, API 20E System, and the Vitek Automicrobic System for identification of gram-negative bacilli. J Clin Microbiol. 1995;33:364–370. doi: 10.1128/jcm.33.2.364-370.1995. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Stager C E, Davis J R. Automated systems for identification of microorganisms. J Clin Rev. 1992;5:302–327. doi: 10.1128/cmr.5.3.302. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Stokes L, Schieven B C, Ofori E, Ewan P, Lannigan R, Hussain Z. Evaluation of Microscan Rapid Pos combo panels for identification of staphylococci. J Clin Microbiol. 1992;30:93–95. doi: 10.1128/jcm.30.1.93-95.1992. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Stokes L, John M A, Lannigan R, Schieven B C, Ramos M, Harley D, Hussain Z. Gas-liquid chromatography of cellular fatty acids for identification of staphylococci. J Clin Microbiol. 1994;32:1908–1910. doi: 10.1128/jcm.32.8.1908-1910.1994. [DOI] [PMC free article] [PubMed] [Google Scholar]