Enzymatic on-Chip Enhancement for High Resolution Genotyping DNA Microarrays
Antibiotic resistance among pathogenic microorganisms is emerging as a major human healthcare concern. While there are a variety of resistance mechanisms, many can be related to single nucleotide polymorphisms and for which DNA microarrays have been widely deployed in bacterial genotyping. However,...
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Published in | Analytical chemistry (Washington) Vol. 84; no. 11; pp. 5080 - 5084 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Washington, DC
American Chemical Society
05.06.2012
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Subjects | |
Online Access | Get full text |
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Summary: | Antibiotic resistance among pathogenic microorganisms is emerging as a major human healthcare concern. While there are a variety of resistance mechanisms, many can be related to single nucleotide polymorphisms and for which DNA microarrays have been widely deployed in bacterial genotyping. However, genotyping by means of allele-specific hybridization can suffer from the drawback that oligonucleotide probes with different nucleotide composition have varying thermodynamic parameters. This results in unpredictable hybridization behavior of mismatch probes. Consequently, the degree of discrimination between perfect match and mismatch probes is insufficient in some cases. We report here an on-chip enzymatic procedure to improve this discrimination in which false-positive hybrids are selectively digested. We find that the application of CEL1 Surveyor nuclease, a mismatch-specific endonuclease, significantly enhances the discrimination fidelity, as demonstrated here on a microarray for the identification of variants of carbapenem resistant Klebsiella pneumoniae carbapenemases and monitored by end point detection of fluorescence intensity. Further fundamental investigations applying total internal reflection fluorescence detection for kinetic real-time measurements confirmed the enzymatic enhancement for SNP discrimination. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0003-2700 1520-6882 |
DOI: | 10.1021/ac3007945 |