High-throughput identification of clinically important bacterial pathogens using DNA microarray

Cited 22 time in webofscience Cited 22 time in scopus
  • Hit : 472
  • Download : 117
Rapid and accurate detection of pathogenic bacteria is important for the treatment of patients with suitable antibiotics. Here we report the development of a diagnostic DNA microarray for the high-throughput identification of 39 pathogenic bacteria selected based on their high prevalence rate and/or difficulty of cultivation. The 23S ribosomal DNA and 16S-23S rDNA intergenic spacer region were used as target DNAs for pathogen detection. Universal- and species-specific probes were designed based on the unique and common sites within the target DNA sequences. New target DNA sequences were determined for the detection of 19 bacteria] pathogens. The usefulness of the designed probes was validated using 39 reference bacteria and also with 515 clinical isolates from various clinical samples including blood, stool, pus, sputum, urine and cerebrospinal fluid. The DNA microarray developed in this study allowed efficient detection of bacterial pathogens with the specificities of 100%. The sensitivities were 100% as well except for the two pathogens, Enterobacter cloacae (75%) and Enterococcus faecium (85%). These results suggest that the DNA microarray-based assay developed in this study outperforms current diagnostic systems with respect to sensitivity, specificity, and high-throughput detection, and thus should be useful in pathogen diagnosis in the clinical setting. (C) 2009 Elsevier Ltd. All rights reserved.
Publisher
ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD
Issue Date
2009-06
Language
English
Article Type
Article
Citation

MOLECULAR AND CELLULAR PROBES, v.23, no.3-4, pp.171 - 177

ISSN
0890-8508
DOI
10.1016/j.mcp.2009.03.004
URI
http://hdl.handle.net/10203/10870
Appears in Collection
CBE-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 22 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0