16S Ribosomal DNA Sequence Analysis of a Large Collection of Environmental and Clinical Unidentifiable Bacterial Isolates

By M. Drancourt, C. Bollet, A. Carlioz, Rolland Martelin, J. Gayral, Didier Raoult. Journal of Clinical Microbiology, 2000

1,129 citations recorded by the source corpus.

ABSTRACT 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 ≥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 andPantoea 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.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/343420b7cb72529c94ddac5431aa3b98e5d947f1

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Citations in the corpus

16S rRNA Gene Sequencing for Bacterial Identification in the Diagnostic Laboratory: Pluses, Perils, and Pitfalls (2007, background): “The cumulative results from a limited number of studies to date suggest that 16S rRNA gene sequencing provides genus identification in most cases ( 90%) but less so with regard to species (65 to 83%), with from 1 to 14% of the isolates remaining unidentified after testing (5, 11, 17).”
Advancing our understanding of the human microbiome using QIIME (2013, background): “This level of threshold is traditionally set at 97% of sequence similarity, conventionally assumed to represent bacterial species (Drancourt et al., 2000); other levels approximately represent other taxa, although the fit between molecular data and traditional taxonomy varies for different taxa.”
Exploring prokaryotic diversity in the genomic era (2002, background): “In a recent study, 177 environmental, veterinary and clinical isolates that were not identifiable by traditional phenotypic characterization were evaluated by comparative 16S rRNA analysis [10].”
Then and now: use of 16S rDNA gene sequencing for bacterial identification and discovery of novel bacteria in clinical microbiology laboratories. (2008, background): “16S rDNA sequencing is particularly useful in identifying unusual bacteria that are difficult to identify by conventional methods, providing genus identification in >90% of cases, and identification of 65–83% of these at the species level [7,8].”
Bioremediation of heavy metal-contaminated effluent using optimized activated sludge bacteria (2013, positive): “Because of its size (*1,500 base pairs), the 16S rRNA gene is the most widely used sequence in bacterial identification (Weisburg et al. 1991; Drancourt et al. 2000).”
Impact of 16S rRNA Gene Sequence Analysis for Identification of Bacteria on Clinical Microbiology and Infectious Diseases (2004, background): “published a list of 177 such difficult organisms (27).”
Screening of isolated potential probiotic lactic acid bacteria for cholesterol lowering property and bile salt hydrolase activity (2016, methodology): “Molecular methods are important for bacterial identiﬁcation (Drancourt et al., 2000; Sghir et al., 2000; Greetham et al., 2002; Heilig et al., 2002) and possibly more accurate for LAB than the conventional phenotypic methods.”
The Rebirth of Culture in Microbiology through the Example of Culturomics To Study Human Gut Microbiota (2015, background): “7% of 138 bacterial species from environmental and clinical samples identified at the species level by 16S rRNA amplification and sequencing (53).”
Phytoplankton and bacterial assemblages in ballast water of U.S. military ships as a function of port of origin, voyage time, and ocean exchange practices (2007, background): “Twenty-four clones had a sequence similarity of 1.000 with a sequence available on RDP (1 with Pseudomonas putida [AB029257], which is common in putrefaction and can cause septicemia and septic arthritis in immunocompromised patients—Anaissie et al., 1987; Macfarlane et al., 1991); 1 with an uncultu”