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DNA microarray technology: a new tool for the epidemiological typing of bacterial pathogens?

Garaizar J, Rementeria A, Porwollik S

Department of Immunology, Microbiology, and Parasitology, Faculty of Pharmacy, University of the Basque Country, Vitoria-Gasteiz, Spain. javier.garaizar@ehu.es

Genomic hybridization on whole genome arrays detects the presence or absence of similar DNA regions in sufficiently related microorganisms, allowing genome-wide comparison of their genetic contents. A whole genome array is based on a sequenced bacterial isolate, and is a collection of DNA probes fixed on a solid support. In a single hybridization experiment, the absence/presence status of all genes of the sequenced microbe in the queried isolate can be examined. The objective of this minireview is to summarize the past usage of DNA microarray technology for microbial strain characterizations, and to estimate its future utilization in epidemiological studies and molecular typing of bacterial pathogens. The studies reviewed here confirm the usefulness of microarray technology for the detection of genetic polymorphisms. However, the construction or purchase of DNA microarrays and the performance of strain to strain hybridization experiments are still prohibitively expensive for routine application. Future use of arrays in epidemiology is likely to depend on the development of more cost-effective protocols, more robust and simplified formats, and the adequate evaluation of their performance (efficacy) and convenience (efficiency) compared with other genotyping methods. It seems more likely that a more focused assay, concentrating on genomic regions of variability previously detected by genome-wide microarrays, will find broad application in routine bacterial epidemiology.

Published 11 July 2006 in FEMS Immunol Med Microbiol, 47(2): 178-89.
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Microarrays Books

DNA Methylation Microarrays: Experimental Design and Statistical Analysis (Chapman & Hall/Crc Biostatistics Series)

DNA Methylation Microarrays: Experimental Design and Statistical Analysis (Chapman & Hall/Crc Biostatistics Series)