M-specific reverse transcription loop-mediated isothermal amplification for detection of pandemic (H1N1) 2009 virus

Authors


Wei-Li Hsu, Graduate Institute of Microbiology and Public Health, College of Veterinary Medicine, National Chung Hsing University, 250 Kou Kuang Road, Taichung 402, Taiwan. Tel.: +886 4 22840694; fax: +886 4 22852186; e-mail: wlhsu@dragon.nchu.edu.tw

Abstract

Eur J Clin Invest 2011; 41 (4): 434–441

Abstract

Background  Since the initial outbreak in March 2009, the novel pandemic (H1N1) 2009 virus has affected individuals worldwide and caused over 18 138 deaths. There is an urgent need for the development of an easy, accurate and simple method for the diagnosis of this novel pandemic virus.

Design  Reverse transcription loop-mediated isothermal amplification assay (RT-LAMP) with primers targeting the M segment was established for the rapid differential diagnosis of pandemic (H1N1) 2009 virus. The performance of this assay was characterized using 111 clinic nasopharyngeal swabs, and the diagnosis accuracy was compared with real-time reverse transcription PCR (RRT-PCR) and virus isolation, the latter being the reference standard.

Results  This method successfully detected pandemic (H1N1) 2009 virus with a detection limit of approximately 20 copies of the target RNA per reaction, which is a comparably sensitivity to the RRT-PCR assay. Furthermore, this assay was able to discriminate pandemic (H1N1) 2009 virus from seasonal influenza viruses, such as H1N1 and H3N2, and other respiratory viruses (parainfluenza type 2 and 3, adenovirus, echovirus 7, and coxsackievirus A10). Based on validation by virus isolation, the specificity and sensitivity of this M-specific RT-LAMP assay were 100% and 98·25%, respectively. Moreover, the RT-LAMP amplification of most positive samples (46 out of 56) was achieved in < 20 min.

Conclusions  This is an accurate and fast analysis system suitable for general diagnostic laboratories with only limited equipment, e.g. first-line health care centre. This assay will help clinicians and public health officials to react effectively during an outbreak.

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