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Evaluation of one- and two-color gene expression arrays for microbial comparative genome hybridization analyses in routine applications.


ABSTRACT: DNA microarray technology has already revolutionized basic research in infectious diseases, and whole-genome sequencing efforts have allowed for the fabrication of tailor-made spotted microarrays for an increasing number of bacterial pathogens. However, the application of microarrays in diagnostic microbiology is currently hampered by the high costs associated with microarray experiments and the specialized equipment needed. Here, we show that a thorough bioinformatic postprocessing of the microarray design to reduce the amount of unspecific noise also allows the reliable use of spotted gene expression microarrays for gene content analyses. We further demonstrate that the use of only single-color labeling to halve the costs for dye-labeled nucleotides results in only a moderate decrease in overall specificity and sensitivity. Therefore, gene expression microarrays using only single-color labeling can also reliably be used for gene content analyses, thus reducing the costs for potential routine applications such as genome-based pathogen detection or strain typing.

SUBMITTER: Schwarz R 

PROVIDER: S-EPMC2937706 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature

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Evaluation of one- and two-color gene expression arrays for microbial comparative genome hybridization analyses in routine applications.

Schwarz Roland R   Joseph Biju B   Gerlach Gabriele G   Schramm-Glück Anja A   Engelhard Kathrin K   Frosch Matthias M   Müller Tobias T   Schoen Christoph C  

Journal of clinical microbiology 20100630 9


DNA microarray technology has already revolutionized basic research in infectious diseases, and whole-genome sequencing efforts have allowed for the fabrication of tailor-made spotted microarrays for an increasing number of bacterial pathogens. However, the application of microarrays in diagnostic microbiology is currently hampered by the high costs associated with microarray experiments and the specialized equipment needed. Here, we show that a thorough bioinformatic postprocessing of the micro  ...[more]

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