tetano
Editor, Senior Moderator
J Clin Microbiol. 2015 Dec 9. pii: JCM.02611-15. [Epub ahead of print]
[h=1]Detection of rare drug resistance mutations by digital PCR in a human influenza A virus model system and clinical samples.[/h] Whale AS[SUP]1[/SUP], Bushell C[SUP]2[/SUP], Grant PR[SUP]3[/SUP], Cowen S[SUP]4[/SUP], Gutierrez-Aguirre I[SUP]5[/SUP], O'Sullivan DM[SUP]2[/SUP], ?el J[SUP]5[/SUP], Milavec M[SUP]5[/SUP], Foy CA[SUP]2[/SUP], Nastouli E[SUP]3[/SUP], Garson JA[SUP]6[/SUP], Huggett JF[SUP]7[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] 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 PCR (qPCR) and melt curve analysis. To develop and evaluate dPCR for SNP detection using DNA, RNA and clinical samples, an influenza model of resistance to oseltamivir (Tamiflu) was used. Firstly, this study was able to recognise and reduce off-target amplification in dPCR quantification thereby enabling technical sensitivities down to 0.1% SNP abundancy at a range of template concentrations; a 50-fold improvement on the qPCR assay used routinely in the clinic. Secondly, a method was developed for determining the false positive rate (background) signal. Finally, comparison of dPCR with qPCR on clinical samples demonstrated the potential impact dPCR could have on clinical research and patient management by earlier (trace) detection of rare drug resistant sequence variants. Ultimately this could reduce the quantity of ineffective drugs taken and facilitate early switching to alternative medication when available. In the short term such methods could advance our understanding of microbial dynamics and therapeutic responses in a range of infectious diseases such as HIV, viral hepatitis and tuberculosis. Furthermore, the findings presented here are directly relevant to other diagnostic areas such as the detection of rare SNPs in malignancy, monitoring of graft rejection and foetal screening.
Copyright ? 2015 Whale et al.
PMID: 26659206 [PubMed - as supplied by publisher]
[h=1]Detection of rare drug resistance mutations by digital PCR in a human influenza A virus model system and clinical samples.[/h] Whale AS[SUP]1[/SUP], Bushell C[SUP]2[/SUP], Grant PR[SUP]3[/SUP], Cowen S[SUP]4[/SUP], Gutierrez-Aguirre I[SUP]5[/SUP], O'Sullivan DM[SUP]2[/SUP], ?el J[SUP]5[/SUP], Milavec M[SUP]5[/SUP], Foy CA[SUP]2[/SUP], Nastouli E[SUP]3[/SUP], Garson JA[SUP]6[/SUP], Huggett JF[SUP]7[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] 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 PCR (qPCR) and melt curve analysis. To develop and evaluate dPCR for SNP detection using DNA, RNA and clinical samples, an influenza model of resistance to oseltamivir (Tamiflu) was used. Firstly, this study was able to recognise and reduce off-target amplification in dPCR quantification thereby enabling technical sensitivities down to 0.1% SNP abundancy at a range of template concentrations; a 50-fold improvement on the qPCR assay used routinely in the clinic. Secondly, a method was developed for determining the false positive rate (background) signal. Finally, comparison of dPCR with qPCR on clinical samples demonstrated the potential impact dPCR could have on clinical research and patient management by earlier (trace) detection of rare drug resistant sequence variants. Ultimately this could reduce the quantity of ineffective drugs taken and facilitate early switching to alternative medication when available. In the short term such methods could advance our understanding of microbial dynamics and therapeutic responses in a range of infectious diseases such as HIV, viral hepatitis and tuberculosis. Furthermore, the findings presented here are directly relevant to other diagnostic areas such as the detection of rare SNPs in malignancy, monitoring of graft rejection and foetal screening.
Copyright ? 2015 Whale et al.
PMID: 26659206 [PubMed - as supplied by publisher]