Dataset Information

Identification of nocardia species by restriction endonuclease analysis of an amplified portion of the 16S rRNA gene.

ABSTRACT: Identification of clinical isolates of Nocardia to the species level is important for defining the spectrum of disease produced by each species and for predicting antimicrobial susceptibility. We evaluated the usefulness of PCR amplification of a portion of the Nocardia 16S rRNA gene and subsequent restriction endonuclease analysis (REA) for species identification. Unique restriction fragment length polymorphism (RFLP) patterns were found for Nocardia sp. type strains (except for the N. asteroides type strain) and representative isolates of the drug pattern types of Nocardia asteroides (except for N. asteroides drug pattern type IV, which gave inconsistent amplification). A variant RFLP pattern for Nocardia nova was also observed. Twenty-eight clinical isolates were evaluated both by traditional biochemical identification and by amplification and REA of portions of the 16S rRNA gene and the 65-kDa heat shock protein (HSP) gene. There was complete agreement among the three methods on identification of 24 of these isolates. One isolate gave a 16S rRNA RFLP pattern consistent with the biochemical identification but was not identifiable by its HSP gene RFLP patterns. Three isolates gave 16S rRNA RFLP patterns which were inconsistent with the identification obtained by both biochemical tests and HSP gene RFLP; sequence analysis suggested that two of these isolates may belong to undefined species. The PCR and REA technique described appears useful both for the identification of clinical isolates of Nocardia and for the detection of new or unusual species.

SUBMITTER: Conville PS

PROVIDER: S-EPMC86045 | biostudies-literature | 2000 Jan

REPOSITORIES: biostudies-literature

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Identification of nocardia species by restriction endonuclease analysis of an amplified portion of the 16S rRNA gene.

Conville P S PS Fischer S H SH Cartwright C P CP Witebsky F G FG

Journal of clinical microbiology 20000101 1

Identification of clinical isolates of Nocardia to the species level is important for defining the spectrum of disease produced by each species and for predicting antimicrobial susceptibility. We evaluated the usefulness of PCR amplification of a portion of the Nocardia 16S rRNA gene and subsequent restriction endonuclease analysis (REA) for species identification. Unique restriction fragment length polymorphism (RFLP) patterns were found for Nocardia sp. type strains (except for the N. asteroid ...[more]

PMID: 10618080

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Project description:BACKGROUND: The intra- and inter-species genetic diversity of bacteria and the absence of 'reference', or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia. METHODS: A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM) of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization. RESULTS: The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52%) corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578. CONCLUSION: The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra-species variability.

Dataset Information

Identification of nocardia species by restriction endonuclease analysis of an amplified portion of the 16S rRNA gene.

Publications

Identification of nocardia species by restriction endonuclease analysis of an amplified portion of the 16S rRNA gene.

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