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Effective surveillance and treatment strategies are required to control the hepatitis C virus (HCV) epidemic. Phylogenetic analyses are powerful tools for reconstructing the evolutionary history of viral outbreaks and identifying transmission clusters. These studies often rely on Sanger sequencing which typically generates a single consensus sequence for each infected individual. For rapidly mutating viruses such as HCV, consensus sequencing underestimates the complexity of the viral quasispecies population and could therefore generate different phylogenetic tree topologies. Although deep sequencing provides a more detailed quasispecies characterization, in-depth phylogenetic analyses are challenging due to dataset complexity and computational limitations. Here, we apply deep sequencing to a characterized population to assess its ability to identify phylogenetic clusters compared with consensus Sanger sequencing. For deep sequencing, a sample specific threshold determined by the 50th percentile of the patristic distance distribution for all variants within each individual was used to identify clusters. Among seven patristic distance thresholds tested for the Sanger sequence phylogeny ranging from 0.005-0.06, a threshold of 0.03 was found to provide the maximum balance between positive agreement (samples in a cluster) and negative agreement (samples not in a cluster) relative to the deep sequencing dataset. From 77 HCV seroconverters, 10 individuals were identified in phylogenetic clusters using both methods. Deep sequencing analysis identified an additional 4 individuals and excluded 8 other individuals relative to Sanger sequencing. The application of this deep sequencing approach could be a more effective tool to understand onward HCV transmission dynamics compared with Sanger sequencing, since the incorporation of minority sequence variants improves the discrimination of phylogenetically linked clusters., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Unlabelled: Improved surveillance methods are needed to better understand the current hepatitis C virus (HCV) disease burden and to monitor the impact of prevention and treatment interventions on HCV transmission dynamics. Sanger sequencing (HCV NS5B, HVR1 and Core-E1-HVR1) and phylogenetics were applied to samples from individuals diagnosed with HCV in British Columbia, Canada in 2011. This included individuals with two or three sequential samples collected <1 year apart. Patristic distances between sequential samples were used to set cutoffs to identify recent transmission clusters. Factors associated with transmission clustering were analyzed using logistic regression. From 618 individuals, 646 sequences were obtained. Depending on the cutoff used, 63 (10%) to 92 (15%) unique individuals were identified within transmission clusters of predicted recent origin. Clustered individuals were more likely to be <40 years old (Adjusted Odds Ratio (AOR) 2.12, 95% CI 1.21-3.73), infected with genotype 1a (AOR 6.60, 95% CI 1.98-41.0), and to be seroconverters with estimated infection duration of <1 year (AOR 3.13, 95% CI 1.29-7.36) or >1 year (AOR 2.19, 95% CI 1.22-3.97)., Conclusion: Systematic application of molecular phylogenetics may be used to enhance traditional surveillance methods through identification of recent transmission clusters., (Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.)