Quantifying the Diversification of Hepatitis C Virus (HCV) during Primary Infection: Estimates of the In Vivo Mutation Rate

University of Texas at Austin, United States of America
PLoS Pathogens (Impact Factor: 7.56). 08/2012; 8(8):e1002881. DOI: 10.1371/journal.ppat.1002881
Source: PubMed


Hepatitis C virus (HCV) is present in the host with multiple variants generated by its error prone RNA-dependent RNA polymerase. Little is known about the initial viral diversification and the viral life cycle processes that influence diversity. We studied the diversification of HCV during acute infection in 17 plasma donors, with frequent sampling early in infection. To analyze these data, we developed a new stochastic model of the HCV life cycle. We found that the accumulation of mutations is surprisingly slow: at 30 days, the viral population on average is still 46% identical to its transmitted viral genome. Fitting the model to the sequence data, we estimate the median in vivo viral mutation rate is 2.5×10⁻⁵ mutations per nucleotide per genome replication (range 1.6-6.2×10⁻⁵), about 5-fold lower than previous estimates. To confirm these results we analyzed the frequency of stop codons (N = 10) among all possible non-sense mutation targets (M = 898,335), and found a mutation rate of 2.8-3.2×10⁻⁵, consistent with the estimate from the dynamical model. The slow accumulation of mutations is consistent with slow turnover of infected cells and replication complexes within infected cells. This slow turnover is also inferred from the viral load kinetics. Our estimated mutation rate, which is similar to that of other RNA viruses (e.g., HIV and influenza), is also compatible with the accumulation of substitutions seen in HCV at the population level. Our model identifies the relevant processes (long-lived cells and slow turnover of replication complexes) and parameters involved in determining the rate of HCV diversification.

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Article: Quantifying the Diversification of Hepatitis C Virus (HCV) during Primary Infection: Estimates of the In Vivo Mutation Rate

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    • "HCV is a positive-strand, 1 Â 10 4 -nucleotide RNA virus that replicates through a negative-strand intermediate using a viral RNA-dependent RNA polymerase NS5B. The polymerase lacks error-correction and has an in vivo mutation rate of 2.5 Â 10 À 5 mutations per nucleotide per replication (Ribeiro et al., 2012). As HCV has a high replication rate, producing as many as 10 12 virions per day, one could predict that every position in the virus would be mutated daily with the certainty of multiple mutations among the genomes (Neumann et al., 1998). "
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    • "HCV RNA-dependent RNA polymerase (RdRp) lacks proof-reading mechanisms which result in high error rates during replication (Moradpour et al., 2007). The mutation rate has been estimated to be $2.5 Â 10 À5 mutations per nucleotide per genome replication (Ribeiro et al., 2012). As a consequence, HCV is genetically heterogeneous and is represented by seven HCV genotypes and multiple subtypes (Smith et al., 2014). "
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    ABSTRACT: Hepatitis C virus (HCV) genotype 3a accounts for ∼80% of HCV infections in Pakistan, where ∼ 10 million people are HCV-infected. Here, we report analysis of the genetic heterogeneity of HCV NS3 and NS5b subgenomic regions from genotype 3a variants obtained from Pakistan. Phylogenetic analyses showed that Pakistani genotype 3a variants were as genetically diverse as global variants, with extensive intermixing. Bayesian estimates showed that the most recent ancestor for genotype 3a in Pakistan was last extant in ∼1896-1914 C.E. (range: 1851-1932). This genotype experienced a population expansion starting from ∼1905 until ∼1970 after which the effective population leveled. Death/birth models suggest that HCV 3a has reached saturating diversity with decreasing turnover rate and positive extinction. Taken together, these observations are consistent with a long and complex history of HCV 3a infection in Pakistan.
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    • "These programs can be used for suggesting point mutations, investigating the effect of deleterious and compensatory mutations in allosteric ribozymes and riboswitches and analyzing regulatory RNA sequences by their mutational profile. Ribeiro et al. [7] measured the accumulative rate of mutations and fitted the model to the sequence data of HCV by estimating the median in vivo viral mutation rate. "
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    ABSTRACT: Hepatitis C virus (HCV) is a widely spread disease all over the world. HCV has very high mutation rate that makes it resistant to antibodies. Modeling HCV to identify the virus mutation process is essential to its detection and predicting its evolution. This paper presents a model based framework for estimating mutation rate of HCV in two steps. Firstly profile hidden Markov model (PHMM) architecture was builder to select the sequences which represents sequence per year. Secondly mutation rate was calculated by using pair-wise distance method between sequences. A pilot study is conducted on NS5B zone of HCV dataset of genotype 4 subtype a (HCV4a) in Egypt. Keywords: Hepatitis C virus (HCV), Profile Hidden Markov Model (PHMM), Non-structure 5 B(NS5B), Phylogenetic tree, pair-wise distance.
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