New real-time-PCR method to identify single point mutations in hepatitis C virus.

ABSTRACT: To develop a fast, low-cost diagnostic strategy to identify single point mutations in highly variable genomes such as hepatitis C virus (HCV).In patients with HCV infection, resistance-associated amino acid substitutions within the viral quasispecies prior to therapy can confer decreased susceptibility to direct-acting antiviral agents and lead to treatment failure and virological relapse. One such naturally occurring mutation is the Q80K substitution in the HCV-NS3 protease gene, which confers resistance to PI inhibitors, particularly simeprevir. Low-cost, highly sensitive techniques enabling routine detection of these single point mutations would be useful to identify patients at a risk of treatment failure. LightCycler methods, based on real-time PCR with sequence-specific probe hybridization, have been implemented in most diagnostic laboratories. However, this technique cannot identify single point mutations in highly variable genetic environments, such as the HCV genome. To circumvent this problem, we developed a new method to homogenize all nucleotides present in a region except the point mutation of interest.Using nucleotide-specific probes Q, K, and R substitutions at position 80 were clearly identified at a sensitivity of 10% (mutations present at a frequency of at least 10% were detected). The technique was successfully applied to identify the Q80K substitution in 240 HCV G1 serum samples, with performance comparable to that of direct Sanger sequencing, the current standard procedure for this purpose. The new method was then validated in a Catalonian population of 202 HCV G1-infected individuals. Q80K was detected in 14.6% of G1a patients and 0% of G1b in our setting.A fast, low-cost diagnostic strategy based on real-time PCR and fluorescence resonance energy transfer probe melting curve analysis has been successfully developed to identify single point mutations in highly variable genomes such as hepatitis C virus. This technique can be adapted to detect any single point mutation in highly variable genomes.

SUBMITTER: Chen Q 

PROVIDER: S-EPMC5116604 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature