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.     

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.     

Usefulness of the MicroSeq 500 16S rDNA bacterial identification system for identification of anaerobic Gram positive bacilli isolated from blood cultures

Using full 16S ribosomal RNA (rRNA) gene sequencing as the gold standard, 20 non-duplicating anaerobic Gram positive bacilli isolated from blood cultures were analysed by the MicroSeq 500 16S rDNA bacterial identification system. The MicroSeq system successfully identified 13 of the 20 isolates. Four and three isolates were misidentified at the genus and species level, respectively. Although the MicroSeq 500 16S rDNA bacterial identification system is better than three commercially available identification systems also evaluated, its database needs to be expanded for accurate identification of anaerobic Gram positive bacilli.     

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.     

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.     

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.     

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.     

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.     

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.     

Prospective evaluation of the GenoType Assay for routine identification of mycobacteria

In order to evaluate the proficiency of the GenoType Mycobacteria strip hybridization assay (Hain Lifescience, Nehren, Germany) for the routine identification of mycobacteria, the assay was used to identify 178 clinical isolates during a 6-month prospective study. The GenoType results were compared to the identification results obtained with AccuProbe (GenProbe, San Diego, CA, USA) or 16S rDNA sequencing, and an overall agreement of 89.3% between GenoType and the two reference methods was reached. The GenoType assay is, thus, a rapid and reliable method for the identification of clinically important mycobacteria, and it is well suited for use in a routine 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.     

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.     

A high proportion of novel mycobacteria species identified by 16S rDNA analysis among slowly growing AccuProbe-negative strains in a clinical setting

Sequencing of the 16S ribosomal DNA (rDNA) for identification of nontuberculous mycobacteria (NTM) has contributed to the establishment of more than 35 new species during the last decade. Increasingly, NTM are accepted as potential or proven pathogens. We identified, by 16S rDNA sequence analysis, slowly growing NTM isolates negative by AccuProbe (GenProbe, San Diego, CA) that previously were identified by using conventional biochemical techniques, to determine the accuracy of reporting AccuProbe-negative NTM prior to sequence-based identification. Of 82 strains, 30 were deemed novel. An attempt was made to determine the clinical importance of previously misidentified novel species. Clinical cases are described for a number of strains previously identified as Mycobacterium terrae complex, Mycobacterium scrofulaceum, and Mycobacterium avium complex. As sequence-based identification methods become more commonplace in clinical microbiology laboratories, there is a need to understand the significance of previously undescribed species, which often mimic and subsequently are identified as well-established species.     

Use of the INNO-LiPA-MYCOBACTERIA assay (version 2) for identification of Mycobacterium avium-Mycobacterium intracellulare-Mycobacterium scrofulaceum complex isolates

Using INNO-LiPA-MYCOBACTERIA (Lipav1; Innogenetics) and the AccuProbe (Gen-Probe Inc./bioMérieux) techniques, 35 Mycobacterium avium-Mycobacterium intracellulare-Mycobacterium scrofulaceum (MAC/MAIS) complex strains were identified between January 2000 and December 2002. Thirty-four of 35 isolates were positive only for the MAIS complex probe by Lipav1 and were further analyzed by INNO-LiPA-MYCOBACTERIA version 2 (Lipav2), hsp65 PCR restriction pattern analysis (PRA), and ribosomal internal transcribed spacer (ITS), hsp65, and 16S rRNA sequences. Lipav2 identified 14 of 34 strains at the species level, including 11 isolates positive for the newly specific MAC sequevar Mac-A probe (MIN-2 probe). Ten of these 11 isolates corresponded to sequevar Mac-A, which was recently defined as Mycobacterium chimerae sp. nov. Among the last 20 of the 34 MAIS isolates, 17 (by hsp65 PRA) and 18 (by hsp65 sequence) were characterized as M. avium. Ten of the 20 were identified as Mac-U sequevar. All these 20 isolates were identified as M. intracellulare by 16S rRNA sequence except one isolate identified as Mycobacterium paraffinicum by 16S rRNA and ITS sequencing. One isolate out of 35 isolates that was positive for M. avium by AccuProbe and that was Mycobacterium genus probe positive and MAIS probe negative by Lipav1 and Lipav2 might be considered a new species. In conclusion, the new INNO-LiPA-MYCOBACTERIA allowed the identification of 40% of the previously unidentified MAIS isolates at the species level. The results of the Lipav2 assay on the MAIS isolates confirm the great heterogeneity of this group and suggest the use of hsp65 or ITS sequencing for precise identification of such isolates.     

Two-laboratory collaborative study on identification of mycobacteria: molecular versus phenotypic methods.

Previous studies have indicated that the conventional tests used for the identification of mycobacteria may (i) frequently result in erroneous identification and (ii) underestimate the diversity within the genus Mycobacterium. To address this issue in a more systematic fashion, a study comparing phenotypic and molecular methods for the identification of mycobacteria was initiated. Focus was given to isolates which were difficult to identify to species level and which yielded inconclusive results by conventional tests performed under day-to-day routine laboratory conditions. Traditional methods included growth rate, colonial morphology, pigmentation, biochemical profiles, and gas-liquid chromatography of short-chain fatty acids. Molecular identification was done by PCR-mediated partial sequence analysis of the gene encoding the 16S rRNA. A total of 34 isolates was included in this study; 13 of the isolates corresponded to established species, and 21 isolates corresponded to previously uncharacterized taxa. For five isolates, phenotypic and molecular analyses gave identical results. For five isolates, minor discrepancies were present; four isolates remained unidentified after biochemical testing. For 20 isolates, major discrepancies between traditional and molecular typing methods were observed. Retrospective analysis of the data revealed that the discrepant results were without exception due to erroneous biochemical test results or interpretations. In particular, phenotypic identification schemes were compromised with regard to the recognition of previously undescribed taxa. We conclude that molecular typing by 16S rRNA sequence determination is not only more rapid (12 to 36 h versus 4 to 8 weeks) but also more accurate than traditional typing.     

Development and evaluation of a quality-controlled ribosomal sequence database for 16S ribosomal DNA-based identification of Staphylococcus species

To establish an improved ribosomal gene sequence database as part of the Ribosomal Differentiation of Microorganisms (RIDOM) project and to overcome the drawbacks of phenotypic identification systems and publicly accessible sequence databases, both strands of the 5' end of the 16S ribosomal DNA (rDNA) of 81 type and reference strains comprising all validly described staphylococcal (sub)species were sequenced. Assuming a normal distribution for pairwise distances of all unique staphylococcal sequences and choosing a reporting criterion of > or =98.7% similarity for a "distinct species," a statistical error probability of 1.0% was calculated. To evaluate this database, a 16S rDNA fragment (corresponding to Escherichia coli positions 54 to 510) of 55 clinical Staphylococcus isolates (including those of the small-colony variant phenotype) were sequenced and analyzed by the RIDOM approach. Of these isolates, 54 (98.2%) had a similarity score above the proposed threshold using RIDOM; 48 (87.3%) of the sequences gave a perfect match, whereas 83.6% were found by searching National Center for Biotechnology Information (NCBI) database entries. In contrast to RIDOM, which showed four ambiguities at the species level (mainly concerning Staphylococcus intermedius versus Staphylococcus delphini), the NCBI database search yielded 18 taxon-related ambiguities and showed numerous matches exhibiting redundant or unspecified entries. Comparing molecular results with those of biochemical procedures, ID 32 Staph (bioMerieux, Marcy I'Etoile, France) and VITEK 2 (bioMerieux) failed to identify 13 (23.6%) and 19 (34.5%) isolates, respectively, due to incorrect identification and/or categorization below acceptable values. In contrast to phenotypic methods and the NCBI database, the novel high-quality RIDOM sequence database provides excellent identification of staphylococci, including rarely isolated species and phenotypic variants.     

16S ribosomal DNA sequence analysis of a large collection of environmental and clinical unidentifiable bacterial isolates

Some bacteria are difficult to identify with phenotypic identification schemes commonly used outside reference laboratories. 16S ribosomal DNA (rDNA)-based identification of bacteria potentially offers a useful alternative when phenotypic characterization methods fail. However, as yet, the usefulness of 16S rDNA sequence analysis in the identification of conventionally unidentifiable isolates has not been evaluated with a large collection of isolates. In this study, we evaluated the utility of 16S rDNA sequencing as a means to identify a collection of 177 such isolates obtained from environmental, veterinary, and clinical sources. For 159 isolates (89.8%) there was at least one sequence in GenBank that yielded a similarity score of > or =97%, and for 139 isolates (78.5%) there was at least one sequence in GenBank that yielded a similarity score of > or =99%. These similarity score values were used to defined identification at the genus and species levels, respectively. For isolates identified to the species level, conventional identification failed to produce accurate results because of inappropriate biochemical profile determination in 76 isolates (58.7%), Gram staining in 16 isolates (11.6%), oxidase and catalase activity determination in 5 isolates (3.6%) and growth requirement determination in 2 isolates (1.5%). Eighteen isolates (10.2%) remained unidentifiable by 16S rDNA sequence analysis but were probably prototype isolates of new species. These isolates originated mainly from environmental sources (P = 0.07). The 16S rDNA approach failed to identify Enterobacter and Pantoea isolates to the species level (P = 0.04; odds ratio = 0.32 [95% confidence interval, 0.10 to 1.14]). Elsewhere, the usefulness of 16S rDNA sequencing was compromised by the presence of 16S rDNA sequences with >1% undetermined positions in the databases. Unlike phenotypic identification, which can be modified by the variability of expression of characters, 16S rDNA sequencing provides unambiguous data even for rare isolates, which are reproducible in and between laboratories. The increase in accurate new 16S rDNA sequences and the development of alternative genes for molecular identification of certain taxa should further improve the usefulness of molecular identification of bacteria.     

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.     

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.