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Journal of Clinical Microbiology, October 2000, p. 3623-3630, Vol. 38, No. 10
Laboratoire de Microbiologie, Centre
Hospitalier Universitaire La Timone, Marseille,1
and Département de Recherche et Développement,
bioMérieux, Marcy-l'Etoile,2 France
Received 17 February 2000/Returned for modification 4 May
2000/Accepted 12 July 2000
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
Accurate identification of bacterial
isolates is an essential task for clinical microbiology laboratories.
For slow-growing and fastidious organisms, traditional phenotypic
identification is difficult and time-consuming, and when phenotypic
methods are used to identify bacteria, interpretation of test
results can involve a substantial amount of subjective judgement
(20). Phenotypic variability among strains belonging to the
same species also results in some bacterial isolates presenting
characteristics that are atypical for a candidate identification.
Reference laboratories, including the Centers for Disease Control and
Prevention in the United States and the Collection de l'Institut
Pasteur and BioMérieux laboratories in France, collected
unidentified microorganisms isolated from environmental, veterinary,
and clinical specimens from various geographic origins and
developed extensive flow charts for their accurate phenotypic
identification. However, numerous isolates remained unidentifiable
after the application of all available phenotypic tests. In these
situations, 16S ribosomal DNA (rDNA)-based molecular identification
could achieve identification, for reasons including its universal
distribution among bacteria (30) and the presence of
species-specific variable regions. This molecular approach has been
extensively used for bacterial phylogeny (32), leading to
the establishment of large public-domain databases (13, 27)
and its application to bacterial identification, including that of
environmental and clinical uncultured microorganisms (17,
22), unique or unusual isolates (7), and collections of phenotypically identified isolates (23, 24). In this
situation, 16S rDNA-based identification has been favorably compared to
computer-assisted cell wall fatty acid analysis and computer-assisted
biochemical profile analysis of a collection of 72 aerobic
gram-negative bacilli (23) and a collection of 52 coryneform
isolates (24). However, its reliability and performance have
never before been evaluated with a collection of unidentifiable
isolates. We have now evaluated 16S rDNA sequence analysis as a tool
for molecular identification of unidentifiable isolates by application
of this molecular tool to the BioMérieux collection of 177 unidentifiable isolates.
Bacterial isolates and conventional identification methods.
As part of its commitment to diagnosis in microbiology,
BioMérieux offers microbiologists the opportunity to submit for
study isolates that remain unidentified when tested using its
commercial identification strips. After the organisms are tested for
purity, they are subjected to an extensive phenotypic investigation,
including the study of respiratory type and temperature of growth, cell morphology after Gram staining, spore-forming ability, oxidase and
catalase activities, and biochemical profile. Gram-positive bacilli
were tested using the APICoryne, catalase-negative gram-positive cocci
were tested using the APIStrep, catalase-positive gram-positive cocci
were tested using the APIStaph and the ID32Staph, oxidase-negative gram-negative bacilli were tested using the API20E, oxidase-positive gram-negative bacilli were tested using the API NE, and
Bacillus spp. were tested using the API20E and the API50CH.
Every questionable test was repeated twice. Once these tests were
completed, phenotypic identifications were achieved by reference to
published descriptions of bacterial species (15, 31). On
average, 300 strains are received every year for analysis, and about
20% of these strains remain unidentified. A collection of 177 such
unidentifiable bacterial isolates collected over 3 years was tested in
this study. These isolates had been taken from environmental sources
(79 of 177; 44.6%), veterinary clinical samples (17 of 177; 9.7%),
and medical clinical samples (81 of 177; 45.7%). Phenotypic data were
reassessed after molecular analysis allowed for identification (see
below) in order to determine what caused the conventional
identification to fail. These faults were classified as growth
requirement determination failures, morphology and Gram stain
determination failures, oxidase and catalase activity determination
failures, and biochemical determination failures.
16S rDNA sequencing.
Each isolate was plated onto either
Trypticase soy agar, 5% sheep blood agar, or chocolate agar
(BioMérieux). Bacteria were lysed either by boiling for 15 min
(gram-negative bacilli) or by boiling for 20 min in a 20% Chelex
suspension (gram-positive cocci) (21). Alternatively,
gram-positive bacilli were lysed using a 1-h incubation at 37°C in
100 µl of Tris-EDTA buffer (10 mM Tris, 1 mM EDTA, 0.1 M NaCl, pH
8.0) followed by a 1-h incubation at 55°C in a solution of 25 mg of
proteinase K per ml and 10% sodium dodecyl sulfate. Next, 200 µl of
4 M guanidine thiocyanate was added to each tube, left for an hour at
room temperature, and then heated at 100°C for 10 min with 50 µl of
0.5 M NaOH. Extraction of nucleic acids was carried out using a QIAamp
kit (Qiagen, Hilden, Germany). Extracted DNA was amplified by using PCR
technology and the universal 16S rDNA primers fD1 and rp2 (30) (Eurogentec, Seraing, Belgium). Amplifications and
sequencing of amplified products were done as previously described
(6). 16S rDNA sequences were compared with those available
in the GenBank, EMBL, and DJB databases using the gapped BLASTN 2.0.5 program through the National Center for Biotechnology Information
server (1). Comparisons were performed using the BLOSUM 62 matrix with default parameters including a gap existence cost of 11, a
cost-per-residue gap of 1, and a lambda ratio of 0.85. Every sequence
was aligned with the first 10 database sequences giving the highest
scores of sequence similarity, and the quality of the database
sequences was assessed. Only 16S rDNA database sequences containing
<1% undetermined positions were retained for analysis; unknown
positions (N), purine positions (R), and pyrimidine positions (Y) were
considered undetermined bases. In case a database sequence exhibited
>1% undetermined positions, the 16S rDNA gene sequence was determined
for the type strain.
Criteria for identification.
Identification to the species
level was defined as a 16S rDNA sequence similarity of Phylogenetic analysis of unidentified isolates.
For those
isolates which were not identified by 16S rDNA sequence analysis,
taxonomic relationships were inferred from 16S rDNA sequence
comparison. Sequences were obtained from the GenBank database and
aligned by using the multisequence alignment program ClustalW
(26) in the BISANCE software package (5).
Phylogenetic relationships were inferred from this alignment by using
programs in version 3.4 of the PHYLIP software package (8,
9). A distance matrix was generated using DNADIST under the
assumptions of Jukes and Cantor (11) and Kimura
(12). Phylogenetic trees were derived from these matrices
using neighbor joining. Isolates were assigned to the taxonomic group
of the two bacterial strains forming the taxonomic frame of the
unidentified isolate.
Analysis of discrepancies.
In the case of a low similarity
score resulting from 16S rDNA sequences containing >1% undetermined
positions in GenBank (as defined above), the 16S rDNA sequences of type
strains obtained from the Collection de l'Institut Pasteur (Institut
Pasteur, Paris, France) and the American Type Culture Collection
(Manassas, Va.) were determined in order to refine molecular analysis.
Statistics.
Comparisons of identification ratios were
performed with Epiinfo, version 6 (Centers for Disease Control and Prevention).
16S rDNA sequence analysis and bacterial identification.
An
almost-complete 16S rDNA sequence containing fewer than 1%
undetermined positions was obtained for all of the isolates included in
the study; thus, 177 query sequences were available for comparison
(Table
1). For
three isolates (1.7%) belonging to the genus
Corynebacterium and an unidentified species, DNA extraction
had to be repeated after initial 16S rDNA amplification attempts
failed. For two isolates (1.1%), the 16S rDNA sequencing procedure had
to be carried out twice after the first analysis demonstrated probable
mixed sequences. 16S rDNA-based analysis resulted in the classification
of the isolates into three categories (Table 1 and Fig.
1). A total of 139 of 177 isolates
(78.5%) possessed a 16S rDNA sequence with
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Copyright © 2000, American Society for Microbiology. All rights reserved.
16S Ribosomal DNA Sequence Analysis of a Large Collection of
Environmental and Clinical Unidentifiable Bacterial Isolates
ABSTRACT
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
97%, and for 139 isolates (78.5%) there was at least one
sequence in GenBank that yielded a similarity score of 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.
INTRODUCTION
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
MATERIALS AND METHODS
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
99% with that
of the prototype strain sequence in GenBank; identification at the
genus level was defined as a 16S rDNA sequence similarity of 97%
with that of the prototype strain sequence in GenBank. A failure to
identify was defined as a 16S rDNA sequence similarity score of lower
than 97% with those deposited in GenBank at the time of analysis (May 1999).
RESULTS
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
99% similarity to that
of a previously characterized bacterial species. A total of 159 of 177 (89.8%) possessed a 16S rDNA sequence with 97% similarity to that
of a genus member. Among these 159 isolates, Enterobacter and Pantoea exhibited a 99% 16S rDNA sequence similarity
with GenBank sequences significantly less frequently than isolates belonging to the other genera (P = 0.04; odds
ratio = 0.32 [95% confidence interval, 0.10 to 1.14]
[Fischer's exact test]). A total of 18 of 177 isolates (10.2%) had
a 16S rDNA sequence with <97% similarity with the closest sequence in
GenBank. The efficiency in achieving a 99% 16S rDNA similarity level
was not significantly different between isolates obtained from clinical
or environmental sources. However, 12 of 18 isolates with <97%
similarity to other GenBank sequences originated from environmental
sources (P = 0.07 by the Mantel-Haenszel test). A total
of 41 original 16S rDNA sequences corresponding to new species and new
genera have been deposited in public databases (Table 1).
TABLE 1.
16S rDNA-based identification of a collection of 177 phenotypically unidentified bacterial isolates
View larger version (29K):
[in a new window]
FIG. 1.
Identification scheme for 177 phenotypically
unidentifiable bacterial isolates.
Taxonomic relationships of unidentified isolates.
16S rDNA
analysis determined that 6 of 18 unidentified isolates belonged to
low-percent-G+C-content gram-positive bacteria, 4 of 18 belonged to
high-percent-G+C-content gram-positive bacteria, 6 of 18 belonged to
gamma subgroup Proteobacteria, and 2 of 18 belonged to the
Bacteroides-Cytophaga phylum. The phylogenetic relationships
of these isolates as inferred by neighbor-joining analysis are
presented in Fig. 2.
|
Analysis of conventional-identification failures. Failures in appropriate conventional identification are presented in Fig. 1. Among 16 Bacillus isolates analyzed, 16S rDNA-based identification confirmed conventional identification for 3 isolates; inaccurate conventional identification was a result of unmatched Gram determination for 7 isolates, unmatched biochemical profile determination for 5 isolates, and unmatched growth requirement determination for 1 isolate. Failure to accurately identify Escherichia coli isolates when using conventional methods was a result of unmatched biochemical profile determination for eight of nine isolates and of inaccurate oxidase activity determination for one of nine isolates. Failure of conventional identification of Staphylococcus spp. resulted from inaccurate biochemical profile determination for all nine isolates examined.
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DISCUSSION |
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Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
|
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In this study, inappropriate DNA extraction prevented 16S rDNA-based identification of 2% of isolates. Various extraction protocols have been published (23), but no optimum approach became widely accepted. Improved, reliable methods are therefore required, particularly with the advent of automation. Mixed cultures led to 1% of 16S rDNA-based identification failures, either because the wrong colony was selected on subculture or because more than one bacterial species was inadvertantly included in the amplification, resulting in ambiguous 16S rDNA data. The frequency of chimeric molecule formation was determined to be as high as 30 to 32% in a model of mixed genomic DNAs from two nearly identical actinomycete 16S rDNA sequences (28, 29). Much attention should therefore be paid to achieving a pure culture prior to 16S rDNA-based identification. Alternatively, mixed 16S rDNA sequences could be separated by, for example, denaturing gradient gel electrophoresis prior to sequencing (18, 25). Likewise, PCR-induced chimeras formed between different rRNA gene copies (29) in bacterial species exhibiting heterogeneous 16S rDNA sequences among multiple ribosomal operons (3) may lead to the description of nonexistent species. Particular attention should be paid to the careful examination of double peaks in the electropherogram. Lastly, unlike protein-encoding genes, the 16S rDNA is not organized into codons, and thus the accuracy of every base position determination cannot be verified before the sequence is compared.
Interpretation of the sequences was hampered by a percentage of position ambiguities higher than 1% (~15 positions) either in the query sequence or in database sequences, and we recommend routinely obtaining a 16S rDNA sequence with less than 1% ambiguity. For some genera, too few species have been deposited in the databases so that the similarity level for a particular query sequence never exceeds of 97%. When several 16S rDNA sequences are available for the same species, a level of intraspecific 16S rDNA sequence variation exceeding 1% of the sequence has been reported for as many as 48% of the deposited sequences (4). An accurate commercial 16S rDNA database, proposed for the identification of bacteria (23), circumvents this difficulty, but sequence accuracy may be offset by there being limited number of sequences. In assessing the percent similarities between sequences, nongapped programs usually result in higher scores than gapped programs if only a limited portion of the gene is compared (data not shown). Whether only the most variable regions of the gene should be incorporated in 16S rDNA-based identification remains to be determined. This solution has been proposed for the identification of aerobic gram-negative bacilli (23). In this case, nongapped programs should be used. In this study, in order to achieve results using exactly the same method whatever the query sequence, we obtained similarity percentages using a gapped program applied to the entire 16S rDNA sequence. The degree of freedom for gap placement remains to be determined. Indeed, in our experience, when the same sequence was compared against the same database using different programs, different similarity results were obtained, resulting in the assignment of different identities. Similarity scores depend on the lengths of the sequences under analysis and on the number of gaps introduced in the query sequence to optimize the similarity. Unfortunately, there are no guidelines regarding the use of these parameters during the identification process. Based on results of the present study, we recommend that a comparison include at least 1,500 positions, that all of the sequences included in the similarity search have the same length, and that an ungapped program be used. The question of gapped versus ungapped analysis, however, will require more data.
There are also no accepted guidelines regarding computer-aided comparison of sequence similarity for 16S rDNA-based bacterial identification. A 97% similarity level has been proposed for the bacterial species delineation using the 16S rDNA sequence (19), but this recommendation has been questioned (10). Recently, it has been suggested that a difference rate of >0.5% could be considered indicative of a new species within a known genus (16). In a previous study of 16S rDNA-based bacterial identification, no cutoff values were established (23). In the present study, in the absence of an accepted cutoff value, we retained a 99% similarity as a suitable cutoff for identification at the species level and a 97% similarity as a suitable cutoff for identification at the genus level. While the introduction of these sharp values was necessary to analyze a large collection of unidentified isolates belonging to different genera, further evaluations need to be performed to assess the accuracy of these values. Because bacterial genera do not evolve at the same speed, it may be necessary to use different cutoff values depending on the bacterial genus under investigation.
Evaluation of 16S rDNA-based identification has previously been limited to comparison with phenotypic identification and has found 70 of 72 unusual aerobic gram-negative bacillus isolates (97.2%) identified to the genus level (P = 0.051) and 58 of 65 (89.2%) identified to the species level (P = 0.039; odds ratio = 0.41 [95% confidence interval, 0.15 to 1.01]). We evaluated this molecular tool with a large collection of phenotypically unidentifiable isolates for the first time, and we found this approach efficient in the majority of cases, with 88.7% of isolates being identified to the genus level and 76.3% being identified to the species level. Even those isolates which could not be identified at the genus level could be assigned a phylogenetic position. In contrast to phenotypic identification, which is biased by errors and the variability of character expression, 16S rDNA sequencing provides unambiguous data even for rare isolates, which are reproducible in and between laboratories.
We found that Enterobacter isolates were significantly unidentifiable at the species level. In a previous study (23), six isolates identified as Enterobacter cloacae by the conventional method fell into three different clusters after 16S rDNA sequence analysis, with a 1.52% divergence rate among them. A 16S rDNA-based phylogenetic tree suggests that current Enterobacter taxonomy may not be appropriate, with several species clustering with Escherichia coli. We have previously reported failures in the 16S rDNA-based approach to the identification of enteric bacteria (14). Although not statistically significant, identification of Bacillus isolates to the species level also proved difficult in our study because of low similarity levels, suggesting that too few Bacillus sequences have been deposited in GenBank. In addition, the fact that two distinct Bacillus species may possess identical 16S rDNA sequences has previously been reported (2, 10). In this study, 18 isolates remained unidentified after 16S rDNA sequence analysis, but these were assigned to phylogenetic locations and probably represent new taxa. The majority of these isolates had been collected from environmental sources, suggesting that efforts should be made towards the isolation and culture of fastidious environmental microorganisms and not just towards their 16S rDNA-based detection in environmental samples (22). These isolates may represent prototype strains of new genera or species, which underlines the necessity for a careful description of any unusual bacterial isolate.
The overall performance of 16S rDNA sequence analysis was excellent, since it was able to resolve almost 90% of identifications, when applied to a large collection of phenotypically unidentifiable bacterial isolates. In order to improve this performance, efforts should be made to complete 16S rDNA databases with high-quality sequences and to develop electronic tools for sequence comparison and interpretation. The ongoing progress with DNA microarrays should offer the technological support for its routine application.
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FOOTNOTES |
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* Corresponding author. Mailing address: Unité des Rickettsies, Faculté de Médecine, 27 Boulevard Jean Moulin, 13385 Marseille cedex 5, France. Phone: 33 04 91 38 55 17. Fax: 33 04 91 83 03 90. E-mail: Didier.Raoult{at}medecine.univ-mrs.fr.
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Discussion
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Journal of Clinical Microbiology, October 2000, p. 3623-3630, Vol. 38, No. 10
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de la Tabla Ducasse, V. O., Gonzalez, C. M., Saez-Nieto, J. A., Gutierrez, F.
(2008). First case of post-endoscopic retrograde cholangiopancreatography bacteraemia caused by Acinetobacter ursingii in a patient with choledocholithiasis and cholangitis. J Med Microbiol
57: 1170-1171
[Abstract] [Full Text] -
Chiquet, C., Cornut, P.-L., Benito, Y., Thuret, G., Maurin, M., Lafontaine, P.-O., Pechinot, A., Palombi, K., Lina, G., Bron, A., Denis, P., Carricajo, A., Creuzot, C., Romanet, J.-P., Vandenesch, F., for the French Institutional Endophthalmitis Study,
(2008). Eubacterial PCR for Bacterial Detection and Identification in 100 Acute Postcataract Surgery Endophthalmitis. IOVS
49: 1971-1978
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Nazef, L., Belguesmia, Y., Tani, A., Prevost, H., Drider, D.
(2008). Identification of Lactic Acid Bacteria from Poultry Feces: Evidence on Anti-Campylobacter and Anti-Listeria Activities. Poult. Sci.
87: 329-334
[Abstract] [Full Text] -
Abbas Hilmi, H. T., Surakka, A., Apajalahti, J., Saris, P. E. J.
(2007). Identification of the Most Abundant Lactobacillus Species in the Crop of 1- and 5-Week-Old Broiler Chickens. Appl. Environ. Microbiol.
73: 7867-7873
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Janda, J. M., Abbott, S. L.
(2007). 16S rRNA Gene Sequencing for Bacterial Identification in the Diagnostic Laboratory: Pluses, Perils, and Pitfalls. J. Clin. Microbiol.
45: 2761-2764
[Full Text] -
Chiquet, C., Pechinot, A., Creuzot-Garcher, C., Benito, Y., Croize, J., Boisset, S., Romanet, J. P., Lina, G., Vandenesch, F., for the French Institutional Endophthalmitis Study,
(2007). Acute Postoperative Endophthalmitis Caused by Staphylococcus lugdunensis. J. Clin. Microbiol.
45: 1673-1678
[Abstract] [Full Text] -
Landais, C., Doudier, B., Imbert, G., Fenollar, F., Brouqui, P.
(2007). Application of rrs Gene Sequencing To Elucidate the Clinical Significance of Eggerthela lenta Infection. J. Clin. Microbiol.
45: 1063-1065
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Boudewijns, M., Bakkers, J. M., Sturm, P. D. J., Melchers, W. J. G.
(2006). 16S rRNA Gene Sequencing and the Routine Clinical Microbiology Laboratory: a Perfect Marriage?. J. Clin. Microbiol.
44: 3469-3470
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Zucol, F., Ammann, R. A., Berger, C., Aebi, C., Altwegg, M., Niggli, F. K., Nadal, D.
(2006). Real-Time Quantitative Broad-Range PCR Assay for Detection of the 16S rRNA Gene Followed by Sequencing for Species Identification.. J. Clin. Microbiol.
44: 2750-2759
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Yam, W.-C., Yuen, K.-Y., Kam, S.-Y., Yiu, L.-S., Chan, K.-S., Leung, C.-C., Tam, C.-M., Ho, P.-O., Yew, W.-W., Seto, W.-H., Ho, P.-L.
(2006). Diagnostic application of genotypic identification of mycobacteria. J Med Microbiol
55: 529-536
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Thomas, V., Herrera-Rimann, K., Blanc, D. S., Greub, G.
(2006). Biodiversity of Amoebae and Amoeba-Resisting Bacteria in a Hospital Water Network. Appl. Environ. Microbiol.
72: 2428-2438
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Bosshard, P. P., Zbinden, R., Abels, S., Boddinghaus, B., Altwegg, M., Bottger, E. C.
(2006). 16S rRNA Gene Sequencing versus the API 20 NE System and the VITEK 2 ID-GNB Card for Identification of Nonfermenting Gram-Negative Bacteria in the Clinical Laboratory. J. Clin. Microbiol.
44: 1359-1366
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Fenollar, F., Roux, V., Stein, A., Drancourt, M., Raoult, D.
(2006). Analysis of 525 Samples To Determine the Usefulness of PCR Amplification and Sequencing of the 16S rRNA Gene for Diagnosis of Bone and Joint Infections.. J. Clin. Microbiol.
44: 1018-1028
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Kim, D.-M., Kang, C.-I., Lee, C. S., Kim, H.-B., Kim, E.-C., Kim, N. J., Oh, M.-d., Choe, K.-W.
(2006). Treatment Failure Due to Emergence of Resistance to Carbapenem during Therapy for Shewanella algae Bacteremia.. J. Clin. Microbiol.
44: 1172-1174
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Mnif, B., Boujelbene, I., Mahjoubi, F., Gdoura, R., Trabelsi, I., Moalla, S., Frikha, I., Kammoun, S., Hammami, A.
(2006). Endocarditis Due to Kytococcus schroeteri: Case Report and Review of the Literature.. J. Clin. Microbiol.
44: 1187-1189
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Zhang, T., Fan, X., Hanada, S., Kamagata, Y., Fang, H. H. P.
(2006). Bacillus macauensis sp. nov., a long-chain bacterium isolated from a drinking water supply. Int. J. Syst. Evol. Microbiol.
56: 349-353
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Bothelo, E., Gouriet, F., Fournier, P.-E., Roux, V., Habib, G., Thuny, F., Metras, D., Raoult, D., Casalta, J.-P.
(2006). Endocarditis Caused by Cardiobacterium valvarum. J. Clin. Microbiol.
44: 657-658
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Higashiguchi, D. T., Husseneder, C., Grace, J. K., Berestecky, J. M.
(2006). Pilibacter termitis gen. nov., sp. nov., a lactic acid bacterium from the hindgut of the Formosan subterranean termite (Coptotermes formosanus). Int. J. Syst. Evol. Microbiol.
56: 15-20
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Adekambi, T., Berger, P., Raoult, D., Drancourt, M.
(2006). rpoB gene sequence-based characterization of emerging non-tuberculous mycobacteria with descriptions of Mycobacterium bolletii sp. nov., Mycobacterium phocaicum sp. nov. and Mycobacterium aubagnense sp. nov.. Int. J. Syst. Evol. Microbiol.
56: 133-143
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Han, X. Y., Kamana, M., Rolston, K. V. I.
(2006). Viridans Streptococci Isolated by Culture from Blood of Cancer Patients: Clinical and Microbiologic Analysis of 50 Cases. J. Clin. Microbiol.
44: 160-165
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Saito, D., de Toledo Leonardo, R., Rodrigues, J. L. M., Tsai, S. M., Hofling, J. F., Goncalves, R. B.
(2006). Identification of bacteria in endodontic infections by sequence analysis of 16S rDNA clone libraries. J Med Microbiol
55: 101-107
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Pearce, D. A., van der Gast, C. J., Woodward, K., Newsham, K. K.
(2005). Significant changes in the bacterioplankton community structure of a maritime Antarctic freshwater lake following nutrient enrichment. Microbiology
151: 3237-3248
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Iida, K.-i., Ueda, Y., Kawamura, Y., Ezaki, T., Takade, A., Yoshida, S.-i., Amako, K.
(2005). Paenibacillus motobuensis sp. nov., isolated from a composting machine utilizing soil from Motobu-town, Okinawa, Japan. Int. J. Syst. Evol. Microbiol.
55: 1811-1816
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Song, Y., Liu, C., Bolanos, M., Lee, J., McTeague, M., Finegold, S. M.
(2005). Evaluation of 16S rRNA Sequencing and Reevaluation of a Short Biochemical Scheme for Identification of Clinically Significant Bacteroides Species. J. Clin. Microbiol.
43: 1531-1537
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Abbott, S. L., Waddington, M., Lindquist, D., Ware, J., Cheung, W., Ely, J., Janda, J. M.
(2005). Description of Campylobacter curvus and C. curvus-Like Strains Associated with Sporadic Episodes of Bloody Gastroenteritis and Brainerd's Diarrhea. J. Clin. Microbiol.
43: 585-588
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Adekambi, T., Drancourt, M.
(2004). Dissection of phylogenetic relationships among 19 rapidly growing Mycobacterium species by 16S rRNA, hsp65, sodA, recA and rpoB gene sequencing. Int. J. Syst. Evol. Microbiol.
54: 2095-2105
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Iversen, C., Waddington, M., On, S. L. W., Forsythe, S.
(2004). Identification and Phylogeny of Enterobacter sakazakii Relative to Enterobacter and Citrobacter Species. J. Clin. Microbiol.
42: 5368-5370
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Clarridge, J. E. III
(2004). Impact of 16S rRNA Gene Sequence Analysis for Identification of Bacteria on Clinical Microbiology and Infectious Diseases. Clin. Microbiol. Rev.
17: 840-862
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Matulionyte, R, Rohner, P, Uckay, I, Lew, D, Garbino, J
(2004). Secular trends of nocardia infection over 15 years in a tertiary care hospital. J. Clin. Pathol.
57: 807-812
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Feurer, C., Clermont, D., Bimet, F., Candrea, A., Jackson, M., Glaser, P., Bizet, C., Dauga, C.
(2004). Taxonomic characterization of nine strains isolated from clinical and environmental specimens, and proposal of Corynebacterium tuberculostearicum sp. nov.. Int. J. Syst. Evol. Microbiol.
54: 1055-1061
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Romero Gomez, M. P., Peinado Esteban, A. M., Sobrino Daza, J. A., Saez Nieto, J. A., Alvarez, D., Pena Garcia, P.
(2004). Prosthetic Mitral Valve Endocarditis Due to Ochrobactrum anthropi: Case Report. J. Clin. Microbiol.
42: 3371-3373
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Bosshard, P. P., Abels, S., Altwegg, M., Bottger, E. C., Zbinden, R.
(2004). Comparison of Conventional and Molecular Methods for Identification of Aerobic Catalase-Negative Gram-Positive Cocci in the Clinical Laboratory. J. Clin. Microbiol.
42: 2065-2073
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Drancourt, M., Berger, P., Raoult, D.
(2004). Systematic 16S rRNA Gene Sequencing of Atypical Clinical Isolates Identified 27 New Bacterial Species Associated with Humans. J. Clin. Microbiol.
42: 2197-2202
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Bosshard, P. P., Abels, S., Zbinden, R., Bottger, E. C., Altwegg, M.
(2003). Ribosomal DNA Sequencing for Identification of Aerobic Gram-Positive Rods in the Clinical Laboratory (an 18-Month Evaluation). J. Clin. Microbiol.
41: 4134-4140
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Rovery, C., Rolain, J. M., Raoult, D., Brouqui, P.
(2003). Shell Vial Culture as a Tool for Isolation of Brucella melitensis in Chronic Hepatic Abscess. J. Clin. Microbiol.
41: 4460-4461
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Harris, K. A., Hartley, J. C.
(2003). Development of broad-range 16S rDNA PCR for use in the routine diagnostic clinical microbiology service. J Med Microbiol
52: 685-691
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Gorkiewicz, G., Feierl, G., Schober, C., Dieber, F., Kofer, J., Zechner, R., Zechner, E. L.
(2003). Species-Specific Identification of Campylobacters by Partial 16S rRNA Gene Sequencing. J. Clin. Microbiol.
41: 2537-2546
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Schlegel, L., Grimont, F., Ageron, E., Grimont, P. A. D., Bouvet, A.
(2003). Reappraisal of the taxonomy of the Streptococcus bovis/Streptococcus equinus complex and related species: description of Streptococcus gallolyticus subsp. gallolyticus subsp. nov., S. gallolyticus subsp. macedonicus subsp. nov. and S. gallolyticus subsp. pasteurianus subsp. nov.. Int. J. Syst. Evol. Microbiol.
53: 631-645
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Song, Y., Liu, C., McTeague, M., Finegold, S. M.
(2003). 16S Ribosomal DNA Sequence-Based Analysis of Clinically Significant Gram-Positive Anaerobic Cocci. J. Clin. Microbiol.
41: 1363-1369
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Gauduchon, V., Chalabreysse, L., Etienne, J., Celard, M., Benito, Y., Lepidi, H., Thivolet-Bejui, F., Vandenesch, F.
(2003). Molecular Diagnosis of Infective Endocarditis by PCR Amplification and Direct Sequencing of DNA from Valve Tissue. J. Clin. Microbiol.
41: 763-766
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Cooper, K. L. F., Goering, R. V.
(2003). Development of a Universal Probe for Electronic Microarray and Its Application in Characterization of the Staphylococcus aureus polC Gene. J. Mol. Diagn.
5: 28-33
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Drancourt, M., Jacomo, V., Lepidi, H., Lechevallier, E., Grisoni, V., Coulange, C., Ragni, E., Alasia, C., Dussol, B., Berland, Y., Raoult, D.
(2003). Attempted Isolation of Nanobacterium sp. Microorganisms from Upper Urinary Tract Stones. J. Clin. Microbiol.
41: 368-372
[Abstract] [Full Text] -
Fournier, P.-E., Robson, J., Zeaiter, Z., McDougall, R., Byrne, S., Raoult, D.
(2002). Improved Culture from Lymph Nodes of Patients with Cat Scratch Disease and Genotypic Characterization of Bartonella henselae Isolates in Australia. J. Clin. Microbiol.
40: 3620-3624
[Abstract] [Full Text] -
Harris, K. A., Fidler, K. J., Hartley, J. C., Vogt, J., Klein, N. J., Monsell, F., Novelli, V. M.
(2002). Unique Case of Helicobacter sp. Osteomyelitis in an Immunocompetent Child Diagnosed by Broad-Range 16S PCR. J. Clin. Microbiol.
40: 3100-3103
[Abstract] [Full Text] -
Janda, J. M., Abbott, S. L.
(2002). Bacterial Identification for Publication: When Is Enough Enough?. J. Clin. Microbiol.
40: 1887-1891
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Cloud, J. L., Neal, H., Rosenberry, R., Turenne, C. Y., Jama, M., Hillyard, D. R., Carroll, K. C.
(2002). Identification of Mycobacterium spp. by Using a Commercial 16S Ribosomal DNA Sequencing Kit and Additional Sequencing Libraries. J. Clin. Microbiol.
40: 400-406
[Abstract] [Full Text] -
Whitelaw, A. C., Shankland, I. M., Elisha, B. G.
(2002). Use of 16S rRNA Sequencing for Identification of Actinobacillus ureae Isolated from a Cerebrospinal Fluid Sample. J. Clin. Microbiol.
40: 666-668
[Abstract] [Full Text] -
Rolph, H. J., Lennon, A., Riggio, M. P., Saunders, W. P., MacKenzie, D., Coldero, L., Bagg, J.
(2001). Molecular Identification of Microorganisms from Endodontic Infections. J. Clin. Microbiol.
39: 3282-3289
[Abstract] [Full Text]
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