Tag Archives: virus

Full-Length Characterization of Hepatitis C Virus Subtype 3a Reveals Novel Hypervariable Regions under Positive Selection during Acute Infection

Humphreys I, Fleming V, Fabris P, Parker J, Schulenberg B, Brown A, Demetriou C, Gaudieri S, Pfafferott K, Lucas M, Collier J, Huang KH, Pybus OG, Klenerman P, Barnes E.

J Virol. 2009 Nov;83(22):11456-66. Epub 2009 Sep 9.

Hepatitis C virus subtype 3a is a highly prevalent and globally distributed strain that is often associated with infection via injection drug use. This subtype exhibits particular phenotypic characteristics. In spite of this, detailed genetic analysis of this subtype has rarely been performed. We performed full-length viral sequence analysis in 18 patients with chronic HCV subtype 3a infection and assessed genomic viral variability in comparison to other HCV subtypes. Two novel regions of intragenotypic hypervariability within the envelope protein E2, of HCV genotype 3a, were identified. We named these regions HVR495 and HVR575. They consisted of flanking conserved hydrophobic amino acids and central variable residues. A 5-amino-acid insertion found only in genotype 3a and a putative glycosylation site is contained within HVR575. Evolutionary analysis of E2 showed that positively selected sites within genotype 3a infection were largely restricted to HVR1, HVR495, and HVR575. Further analysis of clonal viral populations within single hosts showed that viral variation within HVR495 and HVR575 were subject to intrahost positive selecting forces. Longitudinal analysis of four patients with acute HCV subtype 3a infection sampled at multiple time points showed that positively selected mutations within HVR495 and HVR575 arose early during primary infection. HVR495 and HVR575 were not present in HCV subtypes 1a, 1b, 2a, or 6a. Some variability that was not subject to positive selection was present in subtype 4a HVR575. Further defining the functional significance of these regions may have important implications for genotype 3a E2 virus-receptor interactions and for vaccine studies that aim to induce cross-reactive anti-E2 antibodies.

Estimating the Date of Origin of An HIV-1 Circulating Recombinant Form

Virology. 2009 Apr 25;387(1):229-34. Epub 2009 Mar 9.
Tee KK, Pybus OG, Parker J, Ng KP, Kamarulzaman A, Takebe Y.

HIV is capable of frequent genetic exchange through recombination. Despite the pandemic spread of HIV-1 recombinants, their times of origin are not well understood. We investigate the epidemic history of a HIV-1 circulating recombinant form (CRF) by estimating the time of the recombination event that lead to the emergence of CRF33_01B, a recently described recombinant descended from CRF01_AE and subtype B. The gag, pol and env genes were analyzed using a combined coalescent and relaxed molecular clock model, implemented in a Bayesian Markov chain Monte Carlo framework. Using linked genealogical trees we calculated the time interval between the common ancestor of CRF33_01B and the ancestors it shares with closely related parental lineages. The recombination event that generated CRF33_01B (t(rec)) occurred sometime between 1991 and 1993, suggesting that recombination is common in the early evolutionary history of HIV-1. The proof-of-concept approach provides a new tool for the investigation of HIV molecular epidemiology and evolution.

Correlating Viral Phenotypes With Phylogeny: Accounting for Phylogenetic Uncertainty

Infect Genet Evol. 2008 May;8(3):239-46. Epub 2007 Aug 21.
Parker J, Rambaut A, Pybus OG.

Many recent studies have sought to quantify the degree to which viral phenotypic characters (such as epidemiological risk group, geographic location, cell tropism, drug resistance state, etc.) are correlated with shared ancestry, as represented by a viral phylogenetic tree. Here, we present a new Bayesian Markov-Chain Monte Carlo approach to the investigation of such phylogeny-trait correlations. This method accounts for uncertainty arising from phylogenetic error and provides a statistical significance test of the null hypothesis that traits are associated randomly with phylogeny tips. We perform extensive simulations to explore and compare the behaviour of three statistics of phylogeny-trait correlation. Finally, we re-analyse two existing published data sets as case studies. Our framework aims to provide an improvement over existing methods for this problem.