Usefulness of the MicroSeq 500 16S ribosomal DNA-based bacterial identification system for identification of clinically significant bacterial isolates with ambiguous biochemical profiles

Due to the inadequate automation in the amplification and sequencing procedures, the use of 16S rRNA gene sequence-based methods in clinical microbiology laboratories is largely limited to identification of strains that are difficult to identify by phenotypic methods. In this study, using conventional full-sequence 16S rRNA gene sequencing as the "gold standard," we evaluated the usefulness of the MicroSeq 500 16S ribosomal DNA (rDNA)-based bacterial identification system, which involves amplification and sequencing of the first 527-bp fragment of the 16S rRNA genes of bacterial strains and analysis of the sequences using the database of the system, for identification of clinically significant bacterial isolates with ambiguous biochemical profiles. Among 37 clinically significant bacterial strains that showed ambiguous biochemical profiles, representing 37 nonduplicating aerobic gram-positive and gram-negative, anaerobic, and Mycobacterium species, the MicroSeq 500 16S rDNA-based bacterial identification system was successful in identifying 30 (81.1%) of them. Five (13.5%) isolates were misidentified at the genus level (Granulicatella adiacens was misidentified as Abiotrophia defectiva, Helcococcus kunzii was misidentified as Clostridium hastiforme, Olsenella uli was misidentified as Atopobium rimae, Leptotrichia buccalis was misidentified as Fusobacterium mortiferum, and Bergeyella zoohelcum was misidentified as Rimerella anatipestifer), and two (5.4%) were misidentified at the species level (Actinomyces odontolyticus was misidentified as Actinomyces meyeri and Arcobacter cryaerophilus was misidentified as Arcobacter butzleri). When the same 527-bp DNA sequences of these seven isolates were compared to the known 16S rRNA gene sequences in the GenBank, five yielded the correct identity, with good discrimination between the best and second best match sequences, meaning that the reason for misidentification in these five isolates was due to a lack of the 16S rRNA gene sequences of these bacteria in the database of the MicroSeq 500 16S rDNA-based bacterial identification system. In conclusion, the MicroSeq 500 16S rDNA-based bacterial identification system is useful for identification of most clinically important bacterial strains with ambiguous biochemical profiles, but the database of the MicroSeq 500 16S rDNA-based bacterial identification system has to be expanded in order to encompass the rarely encountered bacterial species and achieve better accuracy in bacterial identification.     

Sequence-based identification of Mycobacterium species using the MicroSeq 500 16S rDNA bacterial identification system

We evaluated the MicroSeq 500 16S rDNA Bacterial Sequencing Kit (PE Applied Biosystems), a 500-bp sequence-based identification system, for its ability to identify clinical Mycobacterium isolates. The organism identity was determined by comparing the 16S rDNA sequence to the MicroSeq database, which consists primarily of type strain sequences. A total of 113 isolates (18 different species), previously recovered and identified by routine methods from two clinical laboratories, were analyzed by the MicroSeq method. Isolates with discordant results were analyzed by hsp65 gene sequence analysis and in some cases repeat phenotypic identification, AccuProbe rRNA hybridization (Gen-Probe, Inc., San Diego, Calif.), or high-performance liquid chromatography of mycolic acids. For 93 (82%) isolates, the MicroSeq identity was concordant with the previously reported identity. For 18 (16%) isolates, the original identification was discordant with the MicroSeq identification. Of the 18 discrepant isolates, 7 (six unique sequences) were originally misidentified by phenotypic analysis or the AccuProbe assay but were correctly identified by the MicroSeq assay. Of the 18 discrepant isolates, 11 (seven unique sequences) were unusual species that were difficult to identify by phenotypic methods and, in all but one case, by molecular methods. The remaining two isolates (2%) failed definitive phenotypic identification, but the MicroSeq assay was able to definitively identify one of these isolates. The MicroSeq identification system is an accurate and rapid method for the identification of Mycobacterium spp.     

In silico analysis of 16S ribosomal RNA gene sequencing-based methods for identification of medically important anaerobic bacteria

This study is the first study that provides useful guidelines to clinical microbiologists and technicians on the usefulness of full 16S rRNA sequencing, 5'-end 527-bp 16S rRNA sequencing and the existing MicroSeq full and 500 16S rDNA bacterial identification system (MicroSeq, Perkin-Elmer Applied Biosystems Division, Foster City, California, USA) databases for the identification of all existing medically important anaerobic bacteria. Full and 527-bp 16S rRNA sequencing are able to identify 52-63% of 130 Gram-positive anaerobic rods, 72-73% of 86 Gram-negative anaerobic rods and 78% of 23 anaerobic cocci. The existing MicroSeq databases are able to identify only 19-25% of 130 Gram-positive anaerobic rods, 38% of 86 Gram-negative anaerobic rods and 39% of 23 anaerobic cocci. These represent only 45-46% of those that should be confidently identified by full and 527-bp 16S rRNA sequencing. To improve the usefulness of MicroSeq, bacterial species that should be confidently identified by full and/or 527-bp 16S rRNA sequencing but not included in the existing MicroSeq databases should be included.     

Identification of Mycobacterium spp. by using a commercial 16S ribosomal DNA sequencing kit and additional sequencing libraries

Current methods for identification of Mycobacterium spp. rely upon time-consuming phenotypic tests, mycolic acid analysis, and narrow-spectrum nucleic acid probes. Newer approaches include PCR and sequencing technologies. We evaluated the MicroSeq 500 16S ribosomal DNA (rDNA) bacterial sequencing kit (Applied Biosystems, Foster City, Calif.) for its ability to identify Mycobacterium isolates. The kit is based on PCR and sequencing of the first 500 bp of the bacterial rRNA gene. One hundred nineteen mycobacterial isolates (94 clinical isolates and 25 reference strains) were identified using traditional phenotypic methods and the MicroSeq system in conjunction with separate databases. The sequencing system gave 87% (104 of 119) concordant results when compared with traditional phenotypic methods. An independent laboratory using a separate database analyzed the sequences of the 15 discordant samples and confirmed the results. The use of 16S rDNA sequencing technology for identification of Mycobacterium spp. provides more rapid and more accurate characterization than do phenotypic methods. The MicroSeq 500 system simplifies the sequencing process but, in its present form, requires use of additional databases such as the Ribosomal Differentiation of Medical Microorganisms (RIDOM) to precisely identify subtypes of type strains and species not currently in the MicroSeq library.     

Evaluation of partial 16S ribosomal DNA sequencing for identification of nocardia species by using the MicroSeq 500 system with an expanded database

Identification of clinically significant nocardiae to the species level is important in patient diagnosis and treatment. A study was performed to evaluate Nocardia species identification obtained by partial 16S ribosomal DNA (rDNA) sequencing by the MicroSeq 500 system with an expanded database. The expanded portion of the database was developed from partial 5' 16S rDNA sequences derived from 28 reference strains (from the American Type Culture Collection and the Japanese Collection of Microorganisms). The expanded MicroSeq 500 system was compared to (i). conventional identification obtained from a combination of growth characteristics with biochemical and drug susceptibility tests; (ii). molecular techniques involving restriction enzyme analysis (REA) of portions of the 16S rRNA and 65-kDa heat shock protein genes; and (iii). when necessary, sequencing of a 999-bp fragment of the 16S rRNA gene. An unknown isolate was identified as a particular species if the sequence obtained by partial 16S rDNA sequencing by the expanded MicroSeq 500 system was 99.0% similar to that of the reference strain. Ninety-four nocardiae representing 10 separate species were isolated from patient specimens and examined by using the three different methods. Sequencing of partial 16S rDNA by the expanded MicroSeq 500 system resulted in only 72% agreement with conventional methods for species identification and 90% agreement with the alternative molecular methods. Molecular methods for identification of Nocardia species provide more accurate and rapid results than the conventional methods using biochemical and susceptibility testing. With an expanded database, the MicroSeq 500 system for partial 16S rDNA was able to correctly identify the human pathogens N. brasiliensis, N. cyriacigeorgica, N. farcinica, N. nova, N. otitidiscaviarum, and N. veterana.     

Identification of coryneform bacterial isolates by ribosomal DNA sequence analysis

Identification of coryneform bacteria to the species level is important in certain circumstances for differentiating contamination and/or colonization from infection, which influences decisions regarding clinical intervention. However, methods currently used in clinical microbiology laboratories for the species identification of coryneform bacteria are often inadequate. We evaluated the MicroSeq 500 16S bacterial sequencing kit (Perkin-Elmer Biosystems, Foster City, Calif.), which is designed to sequence the first 527 bp of the 16S rRNA gene for bacterial identification, by using 52 coryneform gram-positive bacilli from clinical specimens isolated from January through June 1993 at the Mayo Clinic. Compared to conventional and supplemented phenotypic methods, MicroSeq provided concordant results for identification to the genus level for all isolates. At the species level, MicroSeq provided concordant results for 27 of 42 (64.3%) Corynebacterium isolates and 5 of 6 (83.3%) Corynebacterium-related isolates, respectively. Within the Corynebacterium genus, MicroSeq gave identical species-level identifications for the clinically significant Corynebacterium diphtheriae (4 of 4) and Corynebacterium jeikeium (8 of 8), but it identified only 50.0% (15 of 30) of other species (P < 0.01). Four isolates from the genera Arthrobacter, Brevibacterium, and Microbacterium, which could not be identified to the species level by conventional methods, were assigned a species-level identification by MicroSeq. The total elapsed time for running a MicroSeq identification was 15.5 to 18.5 h. These data demonstrate that the MicroSeq 500 16S bacterial sequencing kit provides a potentially powerful method for the definitive identification of clinical coryneform bacterium isolates.     

Comparison of Phenotypic and Genotypic Techniques for Identification of Unusual Aerobic Pathogenic Gram-Negative Bacilli

Rapid and accurate identification of bacterial pathogens is a fundamental goal of clinical microbiology, but one that is difficult or impossible for many slow-growing and fastidious organisms. We used identification systems based on cellular fatty acid profiles (Sherlock; MIDI, Inc., Newark, Del.), carbon source utilization (Microlog; Biolog, Inc., Hayward, Calif.), and 16S rRNA gene sequence (MicroSeq; Perkin-Elmer Applied Biosystems Division, Foster City, Calif.) to evaluate 72 unusual aerobic gram-negative bacilli isolated from clinical specimens at the Mayo Clinic. Compared to lengthy conventional methods, Sherlock, Microlog, and MicroSeq were able to identify 56 of 72 (77.8%), 63 of 72 (87.5%), and 70 of 72 (97.2%) isolates to the genus level (P = 0.002) and 44 to 65 (67.7%), 55 of 65 (84.6%), and 58 of 65 (89.2%) isolates to the species level (P = 0.005), respectively. Four Acinetobacter and three Bordetella isolates which could not be identified to the species level by conventional methods were identified by MicroSeq. In comparison to the full 16S rDNA sequences, the first 527 bp provided identical genus information for all 72 isolates and identical species information for 67 (93.1%) isolates. These data show that MicroSeq provides rapid, unambiguous identification of clinical bacterial isolates. The improved turnaround time provided by genotypic identification systems may translate into improved clinical outcomes.     

Evaluation of RIDOM, MicroSeq, and Genbank services in the molecular identification of Nocardia species

The molecular identification of Nocardia species, when compared to phenotypic identification, has two primary advantages: rapid turn-around time and improved accuracy. The information content in the 5'-end of the 16S ribosomal RNA gene is sufficient for identification of most bacterial species. An evaluation was performed to demonstrate the quality of results provided by two specialized databases (RIDOM and MicroSeq 500 versions 1.1 and 1.4.3, library version 500-0125, respectively) and the more general GenBank database. In addition, these results were compared with phenotypic identifications. Partial 5'-16S rDNA sequences from 64 culture collection strains (DSM, CIP, JCM, and ATCC) were derived, in duplicate, independently in two laboratories. Furthermore, the sequences and the conventional identification results of 91 clinical Nocardia isolates were determined. With the exception of N. soli and N. cummidelens, all Nocardia type strains were distinguishable using 5'-16S rDNA sequencing. Assuming a normal distribution for the pairwise distances of all unique Nocardia sequences and choosing a reporting criterion of > or = 99.12% similarity for a "distinct species", a statistical error probability of 1.0% can be calculated. When the various databases were searched with the clinical isolate sequences RIDOM gave a perfect match in 71.4% of cases whereas MicroSeq yielded a perfect match in only 26.4%. The GenBank service gave a 100% similarity in 59.3% but in 70.4% of these cases the results obtained were not exclusive for a single Nocardia species. Conventional methods gave a correct identification in 59 cases, although most recent taxonomic changes were not taken into account. The RIDOM service (http://www.ridom-rdna.de/) is in the process of making available a comprehensive and high-quality database for bacterial identification purposes and provides excellent results for the majority of Nocardia isolates.     

Use of the MicroSeq 500 16S rRNA gene-based sequencing for identification of bacterial isolates that commercial automated systems failed to identify correctly

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 Phoenix (Becton Dickinson) and the VITEK 2 (bioMerieux). However, more and more frequently, microbiologists must isolate "difficult" strains that automated systems often fail to identify. An alternative approach could be the genetic identification of isolates; this is based on 16S rRNA gene sequencing and analysis. The aim of the present study was to evaluate the possible use of MicroSeq 500 (Applera) for sequencing the 16S rRNA gene to identify isolates whose identification is unobtainable by conventional systems. We analyzed 83 "difficult" clinical isolates: 25 gram-positive and 58 gram-negative strains that were contemporaneously identified by both systems--VITEK 2 and Phoenix--while genetic identification was performed by using the MicroSeq 500 system. The results showed that phenotypic identifications by VITEK 2 and Phoenix were remarkably similar: 74% for gram-negative strains (43 of 58) and 80% for gram-positive strains were concordant by both systems and also concordant with genetic characterization. The exceptions were the 15 gram-negative and 9 gram-positive isolates whose phenotypic identifications were contrasting or inconclusive. For these, the use of MicroSeq 500 was fundamental to achieving species identification. In clinical microbiology the use of MicroSeq 500, particularly for strains with ambiguous biochemical profiles (including slow-growing strains), identifies strains more easily than do conventional systems. Moreover, MicroSeq 500 is easy to use and cost-effective, making it applicable also in the clinical laboratory.     

Experience with the MicroSeq D2 large-subunit ribosomal DNA sequencing kit for identification of commonly encountered, clinically important yeast species

Experience with a MicroSeq D2 large-subunit (LSU) ribosomal DNA (rDNA) sequencing kit for identification of yeast species commonly encountered in the mycology laboratory at Mayo Clinic is described here. A total of 131 isolates of yeasts recovered from clinical specimens were included in the study. Phenotypic methods used for initial identification included germ tube formation, urease production, microscopic morphological features on cornmeal agar, and an API 20C AUX system; all isolates were sequenced using a MicroSeq D2 LSU rDNA sequencing kit. Nucleic acid sequencing identified 93.9% of the isolates to the correct genus and species. A total of 100 of the isolates (representing 19 species of Candida) were sequenced, and 98% gave results concordant with identifications made by the API 20C AUX system; distance scores ranged from 0 to 1.88%, with an average value of 0.23%. Candida dubliniensis was not included in the MicroSeq database and was identified as Candida albicans. A total of 32 isolates representing 9 other genera (including Cryptococcus, Filobasidium, Kloeckera, Malassezia, Pichia, Sporidiobolus, Rhodotorula, Zygosaccharomyces, and Trichosporon) were included, and 81.3% showed concordant results when phenotypic and sequencing results were compared. Most discrepancies were attributed to the lack of inclusion of the species in the MicroSeq or API 20C AUX database. The MicroSeq D2 LSU rDNA sequencing kit appears to be accurate and useful for the identification of yeasts that might be seen in a clinical laboratory.     

Evaluation of the MicroSeq system for identification of mycobacteria by 16S ribosomal DNA sequencing and its integration into a routine clinical mycobacteriology laboratory

An evaluation of the MicroSeq 500 microbial identification system by nucleic acid sequencing and the Mayo Clinic experience with its integration into a routine clinical laboratory setting are described. Evaluation of the MicroSeq 500 microbial identification system was accomplished with 59 American Type Culture Collection (ATCC) strains and 328 clinical isolates of mycobacteria identified by conventional and 16S ribosomal DNA sequencing by using the MicroSeq 500 microbial identification system. Nucleic acid sequencing identified 58 of 59 (98.3%) ATCC strains to the species level or to the correct group or complex level. The identification results for 219 of 243 clinical isolates (90.1%) with a distance score of <1% were concordant with the identifications made by phenotypic methods. The remaining 85 isolates had distance scores of >1%; 35 (41.1%) were identified to the appropriate species level or group or complex level; 13 (15.3%) were identified to the species level. All 85 isolates were determined to be mycobacterial species, either novel species or species that exhibited significant genotypic divergence from an organism in the database with the closest match. Integration of nucleic acid sequencing into the routine mycobacteriology laboratory and use of the MicroSeq 500 microbial identification system and Mayo Clinic databases containing additional genotypes of common species and added species significantly reduced the number of organisms that could not be identified by phenotypic methods. The turnaround time was shortened to 24 h, and results were reported much earlier. A limited number of species could not be differentiated from one another by 16S ribosomal DNA sequencing; however, the method provides for the identification of unusual species and more accurate identifications and offers the promise of being the most accurate method available.     

Evaluation of the Microbact-24E bacterial identification system.

The Microbact 24E (MB24E) system is a commercial microsystem for the identification of common clinical isolates of Enterobacteriaceae and non-fermenting Gram negative bacilli, and consists of dehydrated substrates distributed in the wells of microtitre trays. This system was compared with the API20E for the identification of 386 bacterial isolates, which included 284 clinical and 102 environmental organisms. There was 97% and 91% agreement for the identification of clinical isolates of Enterobacteriaceae and other Gram negative bacilli, respectively. The identification of environmental isolates by both systems was less satisfactory. The API20E has a more extensive database than the MB24E and is thus more reliable for the identification of rare or unusual organisms, but the MB24E is cheaper, is easy and convenient to use, and is suitable for a routine microbiology laboratory.     

Direct identification of bacteria from positive blood cultures by amplification and sequencing of the 16S rRNA gene: evaluation of BACTEC 9240 instrument true-positive and false-positive results

In a previous study which evaluated the BACTEC 9240 automated blood culture system (Becton Dickinson Diagnostic Instrument Systems, Sparks, Md.), we noted a 1.3% "instrument false-positive" rate. That is, the BACTEC system signaled that a bottle (BACTEC Plus Aerobic/F bottle or BACTEC Anaerobic Lytic/10 bottle) culture was positive but a Gram stain was negative and there was no growth of bacteria or yeasts on subculture to chocolate agar. Furthermore, from the same sample of blood, cultures for fungi using the Isolator blood culture system (Wampole Laboratories, Cranbury, N.J.) were negative for growth. For the present study, we evaluated 76 instrument false-positive samples for the presence of 16S ribosomal DNA using the MicroSeq 500 kit (PE Biosystems, Foster City, Calif.). These samples also were negative for fungi by the Isolator method. This kit has a PCR module and sequencing module for the amplification and sequencing of the 16S RNA gene and provides a database for sequence alignment and identification of bacteria. To optimize the assay, we evaluated the effect of adding 0.5% bovine serum albumin to the sample from blood culture bottles and found that it decreased the effects of inhibitors on the PCR. Two control groups of blood culture specimens were also evaluated. One group (n = 45) were "instrument true positives"; the instrument signaled positive, and subsequent Gram stains were positive and subcultures on chocolate agar grew bacteria. The other group (n = 20) were "instrument true negatives"; the instrument signaled negative, the Gram stain was negative, and subcultures on chocolate agar and from the Isolator tube on fungal media showed no growth. None of the 76 instrument false-positive samples had evidence for 16S rRNA gene sequences. All of the instrument true-positive samples and all of the instrument true-negative specimens were positive and negative, respectively, using the MicroSeq 500 kit. Total peripheral white blood cell counts were statistically significantly higher for patients who had instrument false-positive results than for patients who had instrument true-positive or true-negative results (P = 0.001). We conclude that instrument false positives signaled by the BACTEC 9240 system are not due to bacteria in the blood culture samples.     

Experience with the MicroSeq D2 large-subunit ribosomal DNA sequencing kit for identification of filamentous fungi encountered in the clinical laboratory

Described herein is our experience with the MicroSeq D2 large-subunit rDNA sequencing kit for the identification of filamentous fungi encountered in the mycology laboratory at the Mayo Clinic. A total of 234 filamentous fungi recovered from clinical specimens were used in the evaluation. All were identified by using phenotypic characteristics as observed macroscopically and microscopically on any medium or a combination of media, which included Sabouraud's dextrose, inhibitory mold, cornmeal, Czapek-Dox, potato dextrose, and V8 juice agars; all isolates were sequenced using the MicroSeq D2 large-subunit rDNA sequencing kit. Of the of 234 isolates, 158 were correctly identified to the appropriate genus or genus and species by using nucleic acid sequencing. Sequences for 70 (29.9%) of the isolates (27 genera) were not included in the MicroSeq library. Of the 80 dematiaceous and 154 hyaline fungi sequenced, 65 and 51.2%, respectively, gave results concordant with those determined by phenotypic identification. Nucleic acid sequencing using the MicroSeq D2 large-subunit rDNA sequencing kit offers promise of being an accurate identification system; however, the associated library needs to include more of the clinically important genera and species.     

Application of SmartGene IDNS software to partial 16S rRNA gene sequences for a diverse group of bacteria in a clinical laboratory

Laboratories often receive clinical isolates for bacterial identification that have ambiguous biochemical profiles by conventional testing. With the emergence of 16S rRNA gene sequencing as an identification tool, we evaluated the usefulness of SmartGene IDNS, a 16S rRNA sequence database and software program for microbial identification. Identification by conventional methods of a diverse group of bacterial clinical isolates was compared with gene sequences interrogated by the SmartGene and MicroSeq databases. Of 300 isolates, SmartGene identified 295 (98%) to the genus level and 262 (87%) to the species level, with 5 (2%) being inconclusive. MicroSeq identified 271 (90%) to the genus level and 223 (74%) to the species level, with 29 (10%) being inconclusive. SmartGene and MicroSeq agreed on the genus for 233 (78%) isolates and the species for 212 (71%) isolates. Conventional methods identified 291 (97%) isolates to the genus level and 208 (69%) to the species level, with 9 (3%) being inconclusive. SmartGene, MicroSeq, and conventional identifications agreed for 193 (64%) of the results. Twenty-seven microorganisms were not represented in MicroSeq, compared to only 2 not represented in SmartGene. Overall, SmartGene IDNS provides comprehensive and accurate identification of a diverse group of bacteria and has the added benefit of being a user-friendly program that can be modified to meet the unique needs of clinical laboratories.     

Comparison of conventional and molecular methods for identification of aerobic catalase-negative gram-positive cocci in the clinical laboratory

Over a period of 18 months we have evaluated the use of 16S ribosomal DNA (rDNA) sequence analysis as a means of identifying aerobic catalase-negative gram-positive cocci in the clinical laboratory. A total of 171 clinically relevant strains were studied. The results of molecular analyses were compared with those obtained with a commercially available phenotypic identification system (API 20 Strep system; bioMérieux sa, Marcy l'Etoile, France). Phenotypic characterization identified 67 (39%) isolates to the species level and 32 (19%) to the genus level. Seventy-two (42%) isolates could not be discriminated at any taxonomic level. In comparison, 16S rDNA sequencing identified 138 (81%) isolates to the species level and 33 (19%) to the genus level. For 42 of 67 isolates assigned to a species with the API 20 Strep system, molecular analyses yielded discrepant results. Upon further analysis it was concluded that among the 42 isolates with discrepant results, 16S rDNA sequencing was correct for 32 isolates, the phenotypic identification was correct for 2 isolates, and the results for 8 isolates remained unresolved. We conclude that 16S rDNA sequencing is an effective means for the identification of aerobic catalase-negative gram-positive cocci. With the exception of Streptococcus pneumoniae and beta-hemolytic streptococci, we propose the use of 16S rDNA sequence analysis if adequate species identification is of concern.     

Clinical evaluation of the RapID-ANA II panel for identification of anaerobic bacteria.

The accuracy of the RapID-ANA II system (Innovative Diagnostic Systems, Inc., Atlanta, Ga.) was evaluated by comparing the results obtained with that system with results obtained by the methods described by the Virginia Polytechnic Institute and State University. Three hundred anaerobic bacteria were tested, including 259 clinical isolates and 41 stock strains of anaerobic microorganisms representing 16 genera and 48 species. When identifications to the genus level only were included, 96% of the anaerobic gram-negative bacilli, 94% of the Clostridium species, 83% of the anaerobic, nonsporeforming, gram-positive bacilli, and 97% of the anaerobic cocci were correctly identified. When correct identifications to the genus and species levels were compared, 86% of 152 anaerobic gram-negative bacilli, 76% of 34 Clostridium species, 81% of 41 anaerobic, nonsporeforming, gram-positive bacilli, and 97% of 73 anaerobic cocci were correctly identified. Eight isolates (3%) produced inadequate identification in which the correct identification was listed with one or two other possible choices and extra tests were required for separation. A total of 9 isolates (3%) were misidentified by the RapID-ANA II panel. Overall, the system was able to correctly identify 94% of all the isolates to the genus level and 87% of the isolates to the species level in 4 h by using aerobic incubation.     

基质辅助激光解析离子-飞行时间质谱仪在临床分离革兰阴性杆菌鉴定中的应用

目的 了解基质辅助激光解析离子-飞行时间质谱仪(MALDI-TOF-MS)在临床分离革兰阴性杆菌鉴定中的应用,为临床医师正确诊断提供科学依据.方法 采用 MALDI-TOF-MS技术对1625株临床常见革兰阴性杆菌进行鉴定.VITEK MS鉴定结果与VITEK-2 Compact全自动微生物鉴定系统对比,结果差异的菌株采用16S rDNA测序验证.结果 VITEK MS共鉴定出常见革兰阴性杆菌1625株,肠杆菌科1219株共6种,非发酵菌属406株共4种.VITEK MS系统与VITEK-2 Compact系统鉴定结果比较,120株常见革兰阴性杆菌鉴定符合率为95.83%.5株鉴定结果不符菌株用16S rDNA测序验证,与VITEK-2 Compact 鉴定符合率为2/5(40%),与VITEK MS鉴定符合率为3/5(60%).结论 VITEK MS能快速鉴定出常见革兰阴性杆菌,为临床治疗及鉴别感染病原菌提供了快速的筛选方法.     

Tuf gene sequence analysis has greater discriminatory power than 16S rRNA sequence analysis in identification of clinical isolates of coagulase-negative staphylococci

We compared and analyzed 16S rRNA and tuf gene sequences for 97 clinical isolates of coagulase-negative staphylococci (CNS) by use of the GenBank, MicroSeq, EzTaxon, and BIBI databases. Discordant results for definitive identification were observed and differed according to the different databases and target genes. Although higher percentages of sequence identity were obtained with GenBank and MicroSeq for 16S rRNA analysis, the BIBI and EzTaxon databases produced less ambiguous results. Greater discriminatory power and fewer multiple probable identifications were observed with tuf gene analysis than with 16S rRNA analysis. The most pertinent results for tuf gene analysis were obtained with the GenBank database when the cutoff values for the percentage of identity were adjusted to be greater than or equal to 98.0%, with >0.8% separation between species. Analysis of the tuf gene proved to be more discriminative for certain CNS species; further, this method exhibited better distinction in the identification of CNS clinical isolates.     

Evaluation of the new RapID-ANA II system for the identification of clinical anaerobic isolates.

The RapID-ANA II System (Innovative Diagnostic Systems, Inc., Atlanta, Ga.) is a recently revised and marketed 4-h system for the identification of anaerobic bacteria. The system was compared with conventional identification methods for its ability to identify 566 clinical anaerobic isolates. Overall, the system identified correctly to genus and species 68% of the total isolates (62% of 204 gram-negative bacilli, 70% of 69 nonsporeforming gram-positive bacilli, 74% of 130 Clostridium isolates, and 72% of 163 anaerobic cocci), without the use of additional tests. With the additional tests suggested by the manufacturer, 78% of the total isolates were identified correctly to species. The routine use of a few simple and practical tests (e.g., egg yolk agar for Clostridium spp.), in addition to the RapID-ANA II, would improve significantly the accuracy of the system in the identification of anaerobic bacteria. This second-generation system offers a number of improvements over the original system, including an updated data base and the option of overnight refrigeration of the system before the addition of reagents.