Detection of rare drug resistance mutations by digital PCR in a human influenza A virus model system and clinical samples

摘要: Digital PCR (dPCR) is being increasingly used for the quantification of sequence variations, including single nucleotide polymorphisms (SNPs), due to its high accuracy and precision in comparison with techniques such as quantitative (qPCR) melt curve analysis. To develop evaluate dPCR SNP detection using DNA, RNA, clinical samples, an influenza virus model resistance oseltamivir (Tamiflu) was used. First, this study able recognize reduce off-target amplification quantification, thereby enabling technical sensitivities down 0.1% abundance at a range template concentrations, 50-fold improvement on qPCR assay routinely clinic. Second, method developed determining false-positive rate (background) signal. Finally, results samples demonstrated potential impact could have research patient management by earlier (trace) rare drug-resistant variants. Ultimately quantity ineffective drugs taken facilitate early switching alternative medication when available. In short term methods advance our understanding microbial dynamics therapeutic responses infectious diseases HIV, viral hepatitis, tuberculosis. Furthermore, findings presented here are directly relevant other diagnostic areas, SNPs malignancy, monitoring graft rejection, fetal screening.