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Open Access Highly Accessed Research article

Identification of human pathogens isolated from blood using microarray hybridisation and signal pattern recognition

Herbert Wiesinger-Mayr1*, Klemens Vierlinger1, Rudolf Pichler1, Albert Kriegner1, Alexander M Hirschl2, Elisabeth Presterl23, Levente Bodrossy4 and Christa Noehammer1

Author Affiliations

1 Molecular Diagnostics, Austrian Research Centers GmbH – ARC, Mendelstrasse 1, A-2444 Seibersdorf, Austria

2 Institute of Hygiene, Medical University of Vienna, Währinger Gürtel 18-20, A-1090 Vienna, Austria

3 Division Infectious Diseases, Department of Medicine I, Medical University of Vienna, Währinger Gürtel 18-20, A-1090 Vienna, Austria

4 Biogenetics and Natural Resources, Austrian Research Centers GmbH – ARC, Mendelstrasse 1, A-2444 Seibersdorf, Austria

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BMC Microbiology 2007, 7:78  doi:10.1186/1471-2180-7-78

Published: 14 August 2007

Abstract

Background

Pathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least 24 hours. However, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. Molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult.

Results

A molecular approach is presented for the rapid identification of pathogens combining PCR amplification with microarray detection. The DNA chip comprises oligonucleotide capture probes for 25 different pathogens including Gram positive cocci, the most frequently encountered genera of Enterobacteriaceae, non-fermenter and clinical relevant Candida species. The observed detection limits varied from 10 cells (e.g. E. coli) to 105 cells (S. aureus) per mL artificially spiked blood. Thus the current low sensitivity for some species still represents a barrier for clinical application. Successful discrimination of closely related species was achieved by a signal pattern recognition approach based on the k-nearest-neighbour method. A prototype software providing this statistical evaluation was developed, allowing correct identification in 100 % of the cases at the genus and in 96.7 % at the species level (n = 241).

Conclusion

The newly developed molecular assay can be carried out within 6 hours in a research laboratory from pathogen isolation to species identification. From our results we conclude that DNA microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios.