کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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5672943 | 1593429 | 2017 | 6 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A high resolution melting (HRM) technology-based assay for cost-efficient clinical detection and genotyping of herpes simplex virus (HSV)-1 and HSV-2 A high resolution melting (HRM) technology-based assay for cost-efficient clinical detection and genotyping of herpes simplex virus (HSV)-1 and HSV-2](/preview/png/5672943.png)
- A melting (HRM) technology-based HSV assay was designed and optimized.
- HRM assay showed comparable performance to two other commercially available assays.
- The developed HRM assay showed a more cost-effective alternative to genotype HSV.
Genital herpes can be caused by two very similar viruses, herpes simplex virus (HSV)-1 or HSV-2. These two HSV types cannot be distinguished clinically, but genotyping is recommended in the first-episodes of genital herpes to guide counselling and management. Quantitative polymerase chain reaction (qPCR) is the preferred diagnostic method for HSV typing. However, commercial qPCR methods use expensive fluorescent labeled probes for detection. Furthermore, most low-cost methods are not able to differentiate between HSV-1 and -2. The aim of this study was to develop a high resolution melting (HRM) technology-based assay for sensitive HSV-1 and HSV-2 detection and genotyping. Using a panel of 46 clinical specimens, the performance of the HRM assay was compared to two commercial HSV tests: the HRM assay detected HSV in all 23 positive samples, with no false positive results (100% concordance with HSV I/II Real-TM assay). Additionally, the HRM assay correctly genotyped both HSV types in a subset of these clinical samples, as determined by the Realstar HSV PCR Kit. The HSV HRM assay provides a cost-effective alternative method to conventional more expensive assays and can be used in routine clinical specimens, in cases where it is particularly necessary to detect and distinguish HSV-1 from -2.
Journal: Journal of Virological Methods - Volume 248, October 2017, Pages 181-186