Evaluation of clinical applicability of reverse transcription-loop-mediated isothermal amplification assay for detection and subtyping of Influenza A viruses

评估逆转录环介导等温扩增法检测和分型甲型流感病毒的临床应用价值

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Abstract

BACKGROUND: Influenza A viruses (IAVs) have always remain a serious concern for the global economy and public health. A rapid, specific and sensitive detection method is always needed to control the influenza in its early stages by timely intervention of therapy and early clinical management. OBJECTIVES: To develop RT-LAMP assays for detection of influenza A viruses, their further subtyping into seasonal (H1N1, H3N2) and novel pandemic H1N1 viruses and to evaluate clinical applicability of optimized RT-LAMP assays on patients' samples. STUDY DESIGN: In this study, we optimized RT-LAMP assay to detect IAVs by using primers against matrix gene and subtyping of IAVs was done by using primers against hemagglutinin gene. Optimized RT-LAMP assays were applied on clinical samples from patients having influenza like illness and results were compared with conventional one-step RT-PCR and real-time RT-PCR. RESULTS: RT-LAMP assays successfully detected and differentiated IAVs into H1N1, H3N2 and pdm09/H1N1 subtypes. One hundred and sixty seven clinical swab samples from influenza suspected patients were taken and tested with RT-LAMP assay, detecting 30 (17.9%) samples positive for Influenza A virus. Out of 30 samples, 21, 7 and 2 were found positive for pdm09/H1N1, H3N2 and seasonal H1 respectively. Conventional one-step RT-PCR detected a total of 27 (16.2%) samples for influenza A and further subtyping showed 20 and 7 samples positive for pdm09/H1N1 and H3N2 virus respectively whereas none was found positive for seasonal H1N1. RT-LAMP assay demonstrated higher sensitivity (93.8%) than conventional RT-PCR (84.4%) for influenza A viruses detection in clinical samples. CONCLUSIONS: RT-LAMP assay is rapid, sensitive, specific and cost effective method for detection of influenza A viruses than conventional one-step RT-PCR and it can serve as a good alternate for diagnosis and surveillance studies during influenza outbreaks in resource-limited setups of developing countries.

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