Literature DB >> 17309636

Suitability of partial 16S ribosomal RNA gene sequence analysis for the identification of dangerous bacterial pathogens.

W Ruppitsch1, A Stöger, A Indra, K Grif, C Schabereiter-Gurtner, A Hirschl, F Allerberger.   

Abstract

AIMS: In a bioterrorism event a rapid tool is needed to identify relevant dangerous bacteria. The aim of the study was to assess the usefulness of partial 16S rRNA gene sequence analysis and the suitability of diverse databases for identifying dangerous bacterial pathogens. METHODS AND
RESULTS: For rapid identification purposes a 500-bp fragment of the 16S rRNA gene of 28 isolates comprising Bacillus anthracis, Brucella melitensis, Burkholderia mallei, Burkholderia pseudomallei, Francisella tularensis, Yersinia pestis, and eight genus-related and unrelated control strains was amplified and sequenced. The obtained sequence data were submitted to three public and two commercial sequence databases for species identification. The most frequent reason for incorrect identification was the lack of the respective 16S rRNA gene sequences in the database.
CONCLUSIONS: Sequence analysis of a 500-bp 16S rDNA fragment allows the rapid identification of dangerous bacterial species. However, for discrimination of closely related species sequencing of the entire 16S rRNA gene, additional sequencing of the 23S rRNA gene or sequencing of the 16S-23S rRNA intergenic spacer is essential. SIGNIFICANCE AND IMPACT OF THE STUDY: This work provides comprehensive information on the suitability of partial 16S rDNA analysis and diverse databases for rapid and accurate identification of dangerous bacterial pathogens.

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Year:  2007        PMID: 17309636     DOI: 10.1111/j.1365-2672.2006.03107.x

Source DB:  PubMed          Journal:  J Appl Microbiol        ISSN: 1364-5072            Impact factor:   3.772


  6 in total

1.  STITCH: algorithm to splice, trim, identify, track, and capture the uniqueness of 16S rRNAs sequence pairs using public or in-house database.

Authors:  Dianhui Zhu; Parag A Vaishampayan; Kasthuri Venkateswaran; George E Fox
Journal:  Microb Ecol       Date:  2010-11-27       Impact factor: 4.552

2.  Comparison between two PCR-based bacterial identification methods through artificial neural network data analysis.

Authors:  Jie Wen; Xiaohui Zhang; Peng Gao; Qiuhong Jiang
Journal:  J Clin Lab Anal       Date:  2008       Impact factor: 2.352

Review 3.  Performance and Application of 16S rRNA Gene Cycle Sequencing for Routine Identification of Bacteria in the Clinical Microbiology Laboratory.

Authors:  Deirdre L Church; Lorenzo Cerutti; Antoine Gürtler; Thomas Griener; Adrian Zelazny; Stefan Emler
Journal:  Clin Microbiol Rev       Date:  2020-09-09       Impact factor: 26.132

4.  Occurrence of Vibrio cholerae serogroups other than O1 and O139 in Austria.

Authors:  Steliana Huhulescu; Alexander Indra; Gebhard Feierl; Anna Stoeger; Werner Ruppitsch; Banwarial Sarkar; Franz Allerberger
Journal:  Wien Klin Wochenschr       Date:  2007       Impact factor: 1.704

5.  The Identification and Differentiation between Burkholderia mallei and Burkholderia pseudomallei Using One Gene Pyrosequencing.

Authors:  Damian H Gilling; Vicki Ann Luna; Cori Pflugradt
Journal:  Int Sch Res Notices       Date:  2014-10-02

6.  Species identification and molecular typing of human Brucella isolates from Kuwait.

Authors:  Abu S Mustafa; Nazima Habibi; Amr Osman; Faraz Shaheed; Mohd W Khan
Journal:  PLoS One       Date:  2017-08-11       Impact factor: 3.240

  6 in total

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