Dataset Information

Accurate quantification of within- and between-host HBV evolutionary rates requires explicit transmission chain modelling.

ABSTRACT: Analyses of virus evolution in known transmission chains have the potential to elucidate the impact of transmission dynamics on the viral evolutionary rate and its difference within and between hosts. Lin et al. (2015, Journal of Virology, 89/7: 3512-22) recently investigated the evolutionary history of hepatitis B virus in a transmission chain and postulated that the 'colonization-adaptation-transmission' model can explain the differential impact of transmission on synonymous and non-synonymous substitution rates. Here, we revisit this dataset using a full probabilistic Bayesian phylogenetic framework that adequately accounts for the non-independence of sequence data when estimating evolutionary parameters. Examination of the transmission chain data under a flexible coalescent prior reveals a general inconsistency between the estimated timings and clustering patterns and the known transmission history, highlighting the need to incorporate host transmission information in the analysis. Using an explicit genealogical transmission chain model, we find strong support for a transmission-associated decrease of the overall evolutionary rate. However, in contrast to the initially reported larger transmission effect on non-synonymous substitution rate, we find a similar decrease in both non-synonymous and synonymous substitution rates that cannot be adequately explained by the colonization-adaptation-transmission model. An alternative explanation may involve a transmission/establishment advantage of hepatitis B virus variants that have accumulated fewer within-host substitutions, perhaps by spending more time in the covalently closed circular DNA state between each round of viral replication. More generally, this study illustrates that ignoring phylogenetic relationships can lead to misleading evolutionary estimates.

SUBMITTER: Vrancken B

PROVIDER: S-EPMC5632516 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Accurate quantification of within- and between-host HBV evolutionary rates requires explicit transmission chain modelling.

Vrancken Bram B Suchard Marc A MA Lemey Philippe P

Virus evolution 20170701 2

Analyses of virus evolution in known transmission chains have the potential to elucidate the impact of transmission dynamics on the viral evolutionary rate and its difference within and between hosts. Lin et al. (2015, <i>Journal of Virology</i>, 89/7: 3512-22) recently investigated the evolutionary history of hepatitis B virus in a transmission chain and postulated that the 'colonization-adaptation-transmission' model can explain the differential impact of transmission on synonymous and non-syn ...[more]

PMID: 29026650

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Project description:Transmission lies at the interface of human immunodeficiency virus type 1 (HIV-1) evolution within and among hosts and separates distinct selective pressures that impose differences in both the mode of diversification and the tempo of evolution. In the absence of comprehensive direct comparative analyses of the evolutionary processes at different biological scales, our understanding of how fast within-host HIV-1 evolutionary rates translate to lower rates at the between host level remains incomplete. Here, we address this by analyzing pol and env data from a large HIV-1 subtype C transmission chain for which both the timing and the direction is known for most transmission events. To this purpose, we develop a new transmission model in a Bayesian genealogical inference framework and demonstrate how to constrain the viral evolutionary history to be compatible with the transmission history while simultaneously inferring the within-host evolutionary and population dynamics. We show that accommodating a transmission bottleneck affords the best fit our data, but the sparse within-host HIV-1 sampling prevents accurate quantification of the concomitant loss in genetic diversity. We draw inference under the transmission model to estimate HIV-1 evolutionary rates among epidemiologically-related patients and demonstrate that they lie in between fast intra-host rates and lower rates among epidemiologically unrelated individuals infected with HIV subtype C. Using a new molecular clock approach, we quantify and find support for a lower evolutionary rate along branches that accommodate a transmission event or branches that represent the entire backbone of transmitted lineages in our transmission history. Finally, we recover the rate differences at the different biological scales for both synonymous and non-synonymous substitution rates, which is only compatible with the 'store and retrieve' hypothesis positing that viruses stored early in latently infected cells preferentially transmit or establish new infections upon reactivation.

Dataset Information

Accurate quantification of within- and between-host HBV evolutionary rates requires explicit transmission chain modelling.

Publications

Accurate quantification of within- and between-host HBV evolutionary rates requires explicit transmission chain modelling.

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