کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8747116 | 1593423 | 2018 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Development of recombinase polymerase amplification assays for the rapid detection of peste des petits ruminants virus
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
ایمنی شناسی و میکروب شناسی
ویروس شناسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Peste des petits ruminants (PPR) is a severe infectious disease of small ruminants caused by PPR virus (PPRV). Rapid and sensitive detection of PPRV is critical for controlling PPR. This report describes the development and evaluation of a conventional reverse transcription recombinase polymerase amplification (RT-RPA) assay and a real-time RT-RPA assay, targeting the PPRV N gene. Sensitivity analysis revealed that the conventional RT-RPA assay could detect 852 copies of standard PPRV RNA per reaction at 95% probability within 20â¯min at 41â¯Â°C, and the real-time RT-RPA assay could detect 103 copies of RNA molecules per reaction at 95% probability. Specificity analysis showed that both assays have no cross-reactivity with nucleic acid templates prepared from other selected viruses or common pathogens. Clinical evaluation using 162 ovine and hircine serum and nasal swab samples showed that the performance of both the real-time RT-RPA assay and the conventional RT-RPA assay were comparable to that of real-time RT-PCR. The overall agreements between real-time RT-PCR and real-time RT-RPA, and conventional RT-RPA were 99.4% (161/162) and 98.8% (160/162), respectively. The R2 value of real-time RT-RPA and real-time RT-PCR was 0.900 by linear regression analysis. Our results suggest that both RT-RPA assays have a potential application in the rapid, sensitive and specific detection of PPRV.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Virological Methods - Volume 254, April 2018, Pages 35-39
Journal: Journal of Virological Methods - Volume 254, April 2018, Pages 35-39
نویسندگان
Yongning Zhang, Jianchang Wang, Zhou Zhang, Lin Mei, Jinfeng Wang, Shaoqiang Wu, Xiangmei Lin,