Rapid Universal Identification of Bacterial Pathogens from Clinical Cultures by Using a Novel Sloppy Molecular Beacon Melting Temperature Signature Technique
- 1 January 2010
- journal article
- research article
- Published by American Society for Microbiology in Journal of Clinical Microbiology
- Vol. 48 (1) , 258-267
- https://doi.org/10.1128/jcm.01725-09
Abstract
A real-time PCR assay with the ability to rapidly identify all pathogenic bacteria would have widespread medical utility. Current real-time PCR technologies cannot accomplish this task due to severe limitations in multiplexing ability. To this end, we developed a new assay system which supports very high degrees of multiplexing. We developed a new class of mismatch-tolerant “sloppy” molecular beacons, modified them to provide an extended hybridization range, and developed a multiprobe, multimelting temperature (Tm) signature approach to bacterial species identification. Sloppy molecular beacons were exceptionally versatile, and they were able to generate specific Tm values for DNA sequences that differed by as little as one nucleotide to as many as 23 polymorphisms. Combining the Tm values generated by several probe-target hybrids resulted in Tm signatures that served as highly accurate sequence identifiers. Using this method, PCR assays with as few as six sloppy molecular beacons targeting bacterial 16S rRNA gene segments could reproducibly classify 119 different sequence types of pathogenic and commensal bacteria, representing 64 genera, into 111 Tm signature types. Blinded studies using the assay to identify the bacteria present in 270 patient-derived clinical cultures including 106 patient blood cultures showed a 95 to 97% concordance with conventional methods. Importantly, no bacteria were misidentified; rather, the few species that could not be identified were classified as “indeterminate,” resulting in an assay specificity of 100%. This approach enables highly multiplexed target detection using a simple PCR format that can transform infectious disease diagnostics and improve patient outcomes.Keywords
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