2016年11月
Performance of a real-time PCR-based approach and droplet digital PCR in detecting human parechovirus type 3 RNA.
Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology
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- 巻
- 84
- 号
- 開始ページ
- 27
- 終了ページ
- 31
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1016/j.jcv.2016.09.009
BACKGROUND: Human parechovirus type 3 (HPeV3) is an emerging virus that causes sepsis and meningoencephalitis in neonates and young infants. Correct diagnosis of HPeV3 infection is critical in determining appropriate management and predicting patients' clinical course. Real-time reverse transcription PCR (RT-PCR) analysis of serum and/or cerebrospinal fluid (CSF) has been used to diagnose HPeV3 infection; however, the assay detection limits have not been fully evaluated. OBJECTIVES: We tested the hypothesis that droplet digital RT-PCR (RT-ddPCR)-a novel technique that precisely quantitates low-copy target genes by diluting and partitioning samples into compartments-increases the detection rate of HPeV3 RNA as compared with real-time RT-PCR. STUDY DESIGN: Using samples with predetermined HPeV3 copy numbers, we evaluated one-step and two-step RT-ddPCR. Then, we tested two-step RT-ddPCR and real-time RT-PCR, using clinical samples with low copy numbers. Finally, we used two-step RT-ddPCR to evaluate clinical samples obtained from HPeV3-infected patients with positive serum but negative CSF, as determined by real-time RT-PCR. RESULTS: Two-step RT-ddPCR was less variable and more specific than one-step RT-ddPCR. Two-step RT-ddPCR detected HPeV3 RNA in all six CSF samples; four samples (67%) were reproducibly positive and the other two samples (33%) were positive at least once in four replicates. Finally, no nonspecific droplet was positive by two-step RT-ddPCR. CONCLUSIONS: Two-step RT-ddPCR may enhance the rate of HPeV3 RNA detection from samples with low viral loads, thereby improving diagnosis and management of HPeV3-infected patients.
- リンク情報
- ID情報
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- DOI : 10.1016/j.jcv.2016.09.009
- PubMed ID : 27690140