1 Microbiology and Infectious Diseases, Institute of Infection, Immunity and Inflammation, The University of Nottingham, Queen's Medical Centre, Nottingham NG7 2UH, UK
2 The Edward Jenner Institute for Vaccine Research, Compton, Newbury, Berkshire RG20 7NN, UK
Correspondence
Jonathan K. Ball
jonathan.ball{at}nottingham.ac.uk
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The GenBank/EMBL/DDBJ accession numbers for the sequence data reported here are AY957985AY958064.
These authors contributed equally to this work.
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
HCV circulates within an infected host as a heterogeneous viral population containing genetically distinct, but closely related variants, known as quasispecies (Bukh et al., 1995; Martell et al., 1992
). The propensity for genetic change is associated primarily with the error-prone nature of the RNA-dependent RNA polymerase, together with the high HCV replicative rate in vivo (Fukumoto et al., 1996
; Neumann et al., 1998
; Ramratnam et al., 1999
; Zeuzem, 2000
). Chronic infection arises, at least in part, through the outgrowth of immune-escape mutants (Farci et al., 2000
; Frasca et al., 1999
; Majid et al., 1999
; Ray et al., 1999
; Wang & Eckels, 1999
). The envelope glycoprotein genes display some of the highest levels of HCV genetic heterogeneity, with E2 exhibiting greater variability than E1. A hypervariable region (HVR1) is located at the N terminus of E2 and this region is the major determinant for strain-specific neutralizing-antibody responses (Bartosch et al., 2003
; Farci et al., 1994
, 1996
; Rosa et al., 1996
; Shimizu et al., 1994
). The rate and nature of nucleotide substitutions within HVR1 during the early stages of infection appear to be correlated with outcome: patients harbouring a stable HVR1 quasispecies frequently resolve infection, whilst those with evidence of a rapidly evolving population develop chronic infection (Farci et al., 2000
; Ray et al., 1999
).
Evolution of the viral quasispecies continues during the chronic phase and differences in evolutionary rates and disease severity in individuals with differing levels of immunocompetency highlight the importance of antibody responses in controlling the infection (Booth et al., 1998; Kumar et al., 1994
). Our current knowledge of adaptive evolution within the envelope genes during HCV chronic infection is based on estimates of synonymous (dS) and non-synonymous (dN) nucleotide-substitution rates, averaged across very small regions of the envelope genes, including HVR1 (Curran et al., 2002
; Gretch et al., 1996
; Honda et al., 1994
; McAllister et al., 1998
; Smith, 1999
). Unfortunately, such analyses are unable to provide insight into the evolution of a number of regions that are critical in envelope glycoprotein function, such as receptor-binding regions. In addition, previous methods utilized average dN/dS ratios across the entire region under study. This is a highly conservative criterion for detecting positive selection, as only a few codons within the protein may be under diversifying selection. The signal could therefore be diluted in a background of purifying selection, maintained via strong functional constraint. To overcome analytical problems associated with differential selection across a region, the distribution of the dN/dS ratio (
) can now be estimated for individual amino acids by assessing competing models of codon substitution within a maximum-likelihood (ML) framework (Yang & Bielawski, 2000
). These ML methods have recently been applied to the identification of site-specific adaptive mutations in human immunodeficiency virus (HIV) env genes (Choisy et al., 2004
) and partial E1E2 sequence datasets from individuals undergoing the acute phase of HCV infection (Sheridan et al., 2004
). The latter study extended earlier findings of Ray et al. (1999)
and Farci et al. (2000)
, revealing a statistically significant association between disease outcome and the number of positively selected sites (Sheridan et al., 2004
).
In this report, we assess the evolutionary dynamics of chronic HCV infection by using temporally spaced, full-length E1E2 sequences generated from patient sera. These novel datasets are utilized for high-resolution phylogenetic reconstruction, identification of codon sites undergoing positive Darwinian selection and estimation of dates of their most recent common ancestor (MRCA), derived from patient-specific HCV mutation rates.
![]() |
METHODS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
Cloning and sequence analysis.
E1E2 amplification products were ligated into a pcDNA3.1 V5 DTOPO expression vector (Invitrogen) and five clones representative of each sequential time point (TP) for each patient were sequenced by using BigDye Terminator chemistry (Perkin Elmer). Nucleotide sequences were aligned by using CLUSTAL_X (Thompson et al., 1997) with manual adjustment. Codon triplets containing gaps, ambiguous nucleotides or premature stop mutations were removed from each alignment prior to evolutionary analysis. Primer sequences at the 5' and 3' ends of the 1752 bp E1E2 amplicons were also removed to prevent any experimentally introduced bias to the phylogenetic analyses. Amino acid translations were performed by using MEGA version 2.1 (Kumar et al., 2001
).
Identification of recombinant sequences.
Individual patient datasets were checked for the presence of recombinant sequences prior to any analysis, as the models utilized for subsequent analyses assume that recombination has not taken place. Patient-specific alignments were divided into three segments of approximately 600 bp and simple neighbour-joining (NJ) (Saitou & Nei, 1987) trees were generated for each segment, utilizing the distance criterion implemented by PAUP* version 4.0b10 (Swofford, 2003
) under a K80 model of nucleotide substitution (Kimura, 1980
). Resultant reconstructed topologies were checked by eye for maintenance of a consistent branching order to identify any possible mosaic sequences. By using this method, a number of putative E1E2 recombinants were identified in datasets SP-1 and MN-2. Suspect sequences were then subjected to an informative-site test (Robertson et al., 1995
) and sequences that demonstrated statistically significant evidence for recombination (P<0·05) were omitted from all subsequent phylogenetic analyses (GenBank accession nos: SP-1, AY957986/AY957997/AY957998/AY958002; MN-2, AY958048/AY958051/AY958059). This analysis is available from the authors on request.
Phylogenetic reconstruction.
Molecular phylogenetic reconstructions were generated for each individual dataset (minus recombinants) by utilizing the likelihood criterion implemented by PAUP* version 4.0b10 (Swofford, 2003) under a GTR+I+
model of nucleotide substitution (Sullivan et al., 1999
; Yang, 1994a
, 1994b
). The proportion of invariant sites (I) and the
shape parameter of the gamma distribution (
) were estimated (with eight discrete categories) from an initial NJ tree (Saitou & Nei, 1987
) and subsequently fixed during heuristic optimization, which used the TBR branch-swapping algorithm with nucleotide frequencies and base-exchangeability parameters estimated from the data under the general time-reversible (GTR) model. Statistical confidence limits to infer the robustness of internal nodes were estimated by using the bootstrap approach (Felsenstein, 1985
). Bootstrap values assigned to ML tree nodes were estimated from bootstrap consensus trees and are given as percentages derived from 1000 replicate NJ trees estimated under the GTR substitution model. For MN viral sequences, ML trees were rooted at the monophyletic population observed at TP-A. For SP viral sequences, where the TP-A sequences were not monophyletic, the root was positioned at the mid-point of the TP-A sequences.
Identification of positively selected sites.
Patient-specific E1E2 sequence alignments and their corresponding unrooted phylogenetic trees were subjected to ML methods for identifying specific codon sites under diversifying selection by using the CODEML program of the PAML package, version 3.14 (Yang, 1997). ML methods implemented in CODEML employ competing models of codon substitution that incorporate various statistical distributions to allow for variable
ratios across codon sites (Yang & Bielawski, 2000
). Identification of specific codon sites under diversifying selection can be assessed adequately via implementation of only two models of codon substitution: M7beta and M8beta+
. The M7beta null model incorporates a beta distribution,
(p,q), approximated by 10 discrete categories. Variable
rates are allowed, depending on the values of p and q, but are always between 0 and 1. Thus, M7beta does not permit positive selection. The M8beta+
model is identical to M7beta except that there is an additional class of sites possessing a free parameter,
1, that is unconstrained, permitting a class of sites with
>1 if selection is occurring. M7beta can then be compared with M8beta+
via a likelihood-ratio test (LRT). When M8beta+
suggests the occurrence of sites under diversifying selection, an empirical Bayes method is used to calculate the posterior probabilities of the assignment of
ratios to sites. When sites are identified as being under positive selection (
>1) with significant Bayesian posterior probabilities (>95 %), this is indicative of the action of diversifying selection.
Analysis of the potential of HCV peptide sequences to act as class I-restricted T-cell epitopes.
A database of HCV peptides identified as epitopes recognized by HLA class I-restricted T cells was created by using data reported in the literature. Peptides within patient HCV sequences that were predicted to bind with high affinity to the patient's HLA alleles were determined by using the BIMAS site (www-bimas.dcrt.nih.gov/molbio/hla_bind/index.html) (Parker et al., 1994), as were the predicted HLA-binding affinities of variant versions of peptide sequences.
Estimation of mutation rate and MRCA.
For rapidly evolving viruses, it is possible to estimate their rates of evolution via comparison of sequences isolated at different TPs. Patient-specific HCV mutation rates were inferred by using the dated-tips method (Rambaut, 2000) implemented in the BASEML program of PAML, version 3.14 (Yang, 1997
). The single-rate dated-tips (SRDT) model allows the estimation of the underlying rate of molecular evolution from sequences with different, non-contemporaneous dates of isolation under a constant rate of substitution (molecular clock) enforced at each TP. If the SRDT model is significantly better than the single-rate (SR) model at describing the data (via an LRT), the ML estimates of substitution rates may be considered valid, even if the molecular-clock hypothesis is rejected (Jenkins et al., 2002
). This rate can then be used to date the MRCA.
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
|
The single selected site in SP-2's E2 sequence was found to lie within a region of sequence where overlapping HLA-A2-restricted epitopes have been identified in HCV gt1 viruses (Grüner et al., 2000; Shirai et al., 1995
; Tsai et al., 1998
; Urbani et al., 2001
), although the disparity between the patient's autologous virus (gt3a) sequence and that of the reported epitopes raises doubts as to whether the same sequences would have constituted T-cell epitopes in patient SP-2. This site is also contained within an autologous virus peptide (LFSQGARQNL) that is predicted to bind with very high affinity to HLA-Cw4, another of the patient's HLA alleles, which may thus have constituted an epitope recognized by the CD8 T-cell response in this patient. However, it is unclear whether the amino acid variation that occurred within this sequence in patient SP-2's HCV quasispecies may have represented escape from a T-cell response to this epitope: the observed sequence changes did not reduce the predicted affinity of binding of the putative epitope peptide to HLA-Cw4, although they could potentially have affected the T-cell response via other mechanisms, e.g. by altering T-cell receptor recognition of the peptideMHC complex.
Neither of the selected sites in patient MN-2's E2 sequence falls within previously reported T-cell epitopes; however, the site where particularly strong selection pressure was observed (384V) forms the C-terminal residue of an autologous virus peptide (LLFAGVDAV) that is predicted to bind with very high affinity to HLA-A2, which may have been one of the epitopes targeted by patient MN-2's HCV-specific CD8 T-cell response. The fact that this sequence spans the E1E2 cleavage site would not preclude generation of the putative epitope peptide, as proteasomal processing of proteins within the cytoplasm constitutes a major source of peptide generation for presentation to T cells. Notably, although all viral clones sequenced from this patient at TP-A contained the LLFAGVDAV sequence, 100 % of clones sequenced at all subsequent TPs bore amino acid changes at the C terminus of the putative epitope (a residue typically involved in peptide anchoring to the HLA-A2 molecule) that were predicted to effectively ablate binding of this peptide to HLA-A2. The estimated half-time of dissociation of a complex between HLA-A0201 and the index peptide LLFAGVDAV has a score of 493·042, whilst the residue 9 E, N and H variants subsequently selected for in the patient HCV quasispecies have scores only of 0·106, 0·528 and 0·528, respectively. Likewise, experimental data that we have obtained previously show that E and H, and, to a lesser extent, N, are extremely poor P9 anchors for HLA-A0201 (Doytchinova et al., 2004). These findings are thus consistent with the hypothesis that the strong selection pressure at this site may have been provided by CD8 T cells directed against the A2-restricted epitope LLFAGVDAV, which drove selection for amino acid changes that conferred escape from this response by ablating binding of the epitope peptide to HLA-A2.
Dated-tip estimations of mutation rates and MRCA dates
By using the dated-tips method (Rambaut, 2000), ML predictions of HCV mutation rates (µ) for each patient's viral population were obtained (Table 3
). For patient SP-1, two sequences corresponding to the highly divergent clade (A4 and C2) were omitted from the analysis. Although the data are not strictly clock-like (a differential-rate model fits the data better than SRDT: data not shown), the SRDT model provides a significantly better fit than the SR null model for data obtained from MN-1 and MN-2; therefore, these data can be used to estimate µ and hence the MRCA (Jenkins et al., 2002
). Similarly, for SP-2, the comparison of SRDT with SR is significant, so µ and the MRCA date can be estimated. However, for SP-1, SRDT does not fit the data significantly better than SR, inferring that µ, and subsequently the MRCA, cannot be estimated for this patient with any degree of accuracy. There is no relationship between time and the number of observed nucleotide substitutions for this patient's virus. The estimated dates for the MRCA sequence, obtained for all of the patient-specific quasispecies, fall within the period between the recorded date of initial risk of exposure to HCV and the first HCV PCR-positive sample. The rate of nucleotide substitution ranged from 1·39x104 to 3·95x103 substitutions site1 year1. TipDate analysis was also performed on patient-specific trees rooted with an outgroup strain. Whilst this analysis gave similar results for patient-specific mean mutation rates and MRCAs, the 95 % confidence intervals around the mean were considerably larger.
|
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Phylogenetic analysis of E1E2 during chronic infection
Reconstruction of accurate phylogenies is influenced by the phylogenetic depth, which is linked directly to the choice of gene used for a specific analysis. The HVR1 region of E2, which is considered to be the most rapidly diverging portion of the HCV genome, has been used extensively in recent molecular epidemiological studies for the recovery of shallow intrapatient HCV phylogenies (Alfonso et al., 2004; Allain et al., 2000
; Curran et al., 2002
). However, HVR1 in isolation may not be an ideal candidate for such investigations, given its high level of sequence diversity and relatively short length. Phylogenetic analyses conducted on HVR1 may result in erroneous or misleading data, due to an inability to distinguish between synapomorphic and homoplastic substitutions (McCormack & Clewley, 2002
). By extending the analysis to the entire E1 and E2 glycoprotein genes, we aimed to achieve a more robust and representative phylogenetic analysis. These loci exhibit both variable and conserved regions and constitute a larger dataset on which to perform the analysis, resulting in a more accurate assessment of patient-specific evolutionary trends. The phylogenetic reconstructions presented here suggest that HCV E1E2 evolution is patient-specific. One key observation was the identification of a number of putative recombinant sequences in two of our patient-specific datasets. Whilst it is impossible to discern whether these sequences represent true in vivo recombination events in E1E2, the absence of any observed recombinant lineages suggests that these are chimeric products derived from in vitro template switching during reverse transcription (Zaphiropoulos, 2002
) or cDNA amplification (Meyerhans et al., 1989
). Irrespective of origin, this highlights the importance of checking the robustness of sequence data prior to performing the analyses detailed here. Indeed, the models used in the various analyses detailed assume no recombination, and inclusion of mosaic sequences in a selected-site analysis can erroneously inflate the number of positively selected codons observed.
Selected sites in E1E2
The distribution of selected sites between these functional regions was patient-dependent and diversifying selection within the E1E2-coding region was confined to a relatively small number of sites. A high degree of conservation was observed within E1E2, indicating that the majority of amino acids are functionally constrained. No sites within E1 exhibited positive selection. One possible explanation for this finding is that E1 is hidden and is therefore not a strong target for host antibody responses. Indeed, E1 is reported to be a poor natural immunogen for humoral responses (Fournillier et al., 2001). Computational analysis predicts that HCV E1 is a truncated, class II membrane-fusion protein, homologous to those observed in other members of the family Flaviviridae (Garry & Dash, 2003
), and is unlikely to be surface-exposed (Allison et al., 2001
). Similarly, the transmembrane domains of E1 and E2, which are also occluded from antibody responses, also lacked sites that were under positive selection.
The positively selected sites were located within regions of E2 that are thought to be surface-exposed (Yagnik et al., 2000) and therefore prime targets for host antibody responses (Wack et al., 2001
). Three of the four patients' selected sites mapped to the HVR1 region. Unsurprisingly, none of these HVR1 mutations mapped to residues previously proposed to be functionally constrained (McAllister et al., 1998
; Penin et al., 2001
; Puntoriero et al., 1998
; Smith, 1999
). HVR1 is known to contain potent, strain-specific, neutralizing-antibody determinants (Farci et al., 1994
, 1996
; Shimizu et al., 1994
, 1996
) and our data support the concept of immune-driven evolution in this region (Booth et al., 1998
; Kumar et al., 1994
; Okamoto et al., 1992
; Ray et al., 1999
). HVR1 is implicated in scavenger receptor BI (SR-BI) binding (Scarselli et al., 2002
), although the precise residues involved have yet to be reported. Whether or not these mutations arise to escape SR-BI-blocking antibodies and whether they affect SR-BI-binding affinity are key questions that are currently being investigated.
The absence of sites under selective pressure in non-exposed regions of the viral glycoproteins [which, although not targeted by antibodies, do contain T-cell epitopes (Ward et al., 2002)] suggests that the humoral response may exert more selective pressure on HCV replication than cell-mediated responses, at least during the chronic phase of infection. Nonetheless, we did find one example of selective change that was highly suggestive of escape from an epitope-specific CD8 T-cell response. Although comprehensive studies of the extent and kinetics of escape from the virus-specific CD8 T-cell response during human HCV infection are currently lacking, work in the chimpanzee model supports the hypothesis that escape may be among the mechanisms by which HCV evades CD8 T-cell control in this infection (Shoukry et al., 2004
).
Positively selected sites were not confined to HVR1, with a number observed downstream, highlighting the importance of analysing the complete E2-coding region. Patient SP-1 possessed an adaptive mutation in the E2 region 412447, a region that contains epitopes recognized by antibodies that inhibit CD81 binding (Flint et al., 1999; Owsianka et al., 2001
) and neutralize infectivity of retroviral pseudotypes complemented by HCV genotype 1 envelope glycoproteins (Hsu et al., 2003
). In addition, two of the four patients' quasispecies possessed adaptive mutations proximal to the CD81-1 binding domain. Again, whether or not these mutations correlate with immune escape and altered CD81 affinity is under investigation.
E1 and E2 are highly glycosylated proteins, with five to six potential N-linked glycosylation sites in E1 and 11 potential sites in E2 (Goffard & Dubuisson, 2003; Meunier et al., 1999
) (Fig. 2
). Glycosylation in HCV envelope proteins is necessary for correct glycoprotein processing and folding (Goffard & Dubuisson, 2003
; Huang et al., 1997
; Li et al., 1993
; Wu et al., 1995
). Some variability in the location and number of N-linked glycosylation sites in our dataset was apparent. However, most sites were highly conserved and whilst two selected sites (416 SP-1; 582 MN-2) were located within N-linked glycosylation motifs (NXT or NXS), neither mutation altered the predicted glycosylation pattern. Glycosylation might mask important epitopes from host antibody responses (Schønning et al., 1996
; Wei et al., 2003
) and, as such, undergo positive selection (Choisy et al., 2004
), but our data show that, in HCV infection, ensuring correct conformation is probably more important than immune shielding.
Consequences of adaptive mutation
Considering the location of the sites under selection, the most likely consequence of the adaptive mutations is escape from antibodies that either block or interfere with CD81 and SR-BI binding or another, as-yet-unidentified component of the entry process. This escape may be at the cost of reduced receptor-binding affinity. Interplay between host immunity and evolution of receptor-binding sites is not unprecedented; numerous studies have highlighted the role of mutations in and around the CD4-binding domain of HIV-1 gp120 and escape from antibodies that block CD4 interaction (Beaumont et al., 2004; Pinter et al., 2004
; Pugach et al., 2004
). The development and implementation of robust retrovirus pseudotype cell-entry assays will allow functional analysis of the E1E2 clone panel, to further elucidate the relationship between E1E2 evolution, host antibody responses and receptor-binding affinities.
Estimated mutation rates and infection dates
Dated-tip estimations of µ for each patient-specific HCV population show limited evidence for a disparity in mutation rates between histologically defined liver-disease status. Mutation rates were patient-specific rather than being correlated with disease status, with estimated rates of 1·39x104 to 3·95x103 substitutions site1 year1, which are comparable to previous estimates (Allain et al., 2000; Curran et al., 2002
; Smith, 1999
). These estimates were then used to calculate the date for the quasispecies MRCA sequence. The Trent HCV Study Cohort (Mohsen, 2001
) patients complete a detailed risk-factor questionnaire to provide patient demographic details, in conjunction with information on the spread of HCV (Ryder et al., 2004
). The recorded dates of HCV infection were taken to be when either intravenous drug use (IVDU) commenced or other activity with associated risk (ear piercing) first occurred (Table 3
). Duration of infection was then estimated heuristically by using the first date of exposure to risk. Epidemiological data suggested that all four patients acquired their HCV infection between 1969 and 1976. However, SRDT MRCA estimations are considerably nearer the present day for both sets of patients. MRCA sequence estimates for the severe progressors appear to extend further back in time than the estimates derived from the mild non-progressors, suggesting a longer period of HCV infection in these patients. Indeed, HCV-induced fibrosis progression is known to be influenced by increased duration of infection, as well as numerous other factors (Serra et al., 2003
). Our data show that quasispecies divergence from the founder viral sequence/population generally increases through time, whilst diversity remains stable. Genetic bottlenecks, selective sweeps and random genetic drift all reduce population diversity and, therefore, time to the MRCA. It is therefore probable that our MRCA estimates will be more recent than the date of transmission.
In conclusion, the evolutionary forces driving the diversity of HCV quasispecies in chronic infection are likely to be dependent on a plethora of factors. The host immune system definitely plays a significant role, but factors such as duration of infection, route of transmission (Gordon et al., 1993), size of original inoculum (Lau et al., 1993
), age at infection, sex, alcohol consumption (Brechot et al., 1996
), HLA type (Isaguliants & Ozeretskovskaya, 2003
) and genotype (Marrone & Sallie, 1996
), as well as hepatitis B virus (Weltman et al., 1995
) and HIV (Martin et al., 1989
) co-infection, all contribute to and affect intrapatient viral evolution. The cumulative effect of all these variables is likely to result in the patient-specific molecular evolution of HCV that we observe in chronic infection. Most importantly, this study has shown that previous studies of envelope adaptive evolution, which utilized methods that rely on average estimates of positive selection or were restricted to HVR1, were unable to highlight important sites under selection. It is significant that, in all patients' quasispecies, we observed a strong association between sites under selection and those regions known, or thought, to be targeted by neutralizing antibodies and cell-mediated immunity, as well as regions involved in receptor binding.
![]() |
ACKNOWLEDGEMENTS |
---|
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Allain, J.-P., Dong, Y., Vandamme, A.-M., Moulton, V. & Salemi, M. (2000). Evolutionary rate and genetic drift of hepatitis C virus are not correlated with the host immune response: studies of infected donor-recipient clusters. J Virol 74, 25412549.
Allison, S. L., Schalich, J., Stiasny, K., Mandl, C. W. & Heinz, F. X. (2001). Mutational evidence for an internal fusion peptide in flavivirus envelope protein E. J Virol 75, 42684275.
Alter, M. J., Margolis, H. S., Krawczynski, K. & other authors (1992). The natural history of community-acquired hepatitis C in the United States. The Sentinel Counties Chronic non-A, non-B Hepatitis Study Team. N Engl J Med 327, 18991905.[Abstract]
Bartosch, B., Vitelli, A., Granier, C. & 7 other authors (2003). Cell entry of hepatitis C virus requires a set of co-receptors that include the CD81 tetraspanin and the SR-B1 scavenger receptor. J Biol Chem 278, 4162441630.
Beaumont, T., Quakkelaar, E., van Nuenen, A., Pantophlet, R. & Schuitemaker, H. (2004). Increased sensitivity to CD4 binding site-directed neutralization following in vitro propagation on primary lymphocytes of a neutralization-resistant human immunodeficiency virus IIIB strain isolated from an accidentally infected laboratory worker. J Virol 78, 56515657.
Booth, J. C., Kumar, U., Webster, D., Monjardino, J. & Thomas, H. C. (1998). Comparison of the rate of sequence variation in the hypervariable region of E2/NS1 region of hepatitis C virus in normal and hypogammaglobulinemic patients. Hepatology 27, 223227.[CrossRef][Medline]
Brechot, C., Nalpas, B. & Feitelson, M. A. (1996). Interactions between alcohol and hepatitis viruses in the liver. Clin Lab Med 16, 273287.[Medline]
Bukh, J., Miller, R. H. & Purcell, R. H. (1995). Genetic heterogeneity of hepatitis C virus: quasispecies and genotypes. Semin Liver Dis 15, 4163.[Medline]
Choisy, M., Woelk, C. H., Guégan, J.-F. & Robertson, D. L. (2004). Comparative study of adaptive molecular evolution in different human immunodeficiency virus groups and subtypes. J Virol 78, 19621970.
Curran, R., Jameson, C. L., Craggs, J. K., Grabowska, A. M., Thomson, B. J., Robins, A., Irving, W. L. & Ball, J. K. (2002). Evolutionary trends of the first hypervariable region of the hepatitis C virus E2 protein in individuals with differing liver disease severity. J Gen Virol 83, 1123.
Doytchinova, I. A., Walshe, V. A., Jones, N. A., Gloster, S. E., Borrow, P. & Flower, D. R. (2004). Coupling in silico and in vitro analysis of peptide-MHC binding: a bioinformatic approach enabling prediction of superbinding peptides and anchorless epitopes. J Immunol 172, 74957502.
Farci, P., Alter, H. J., Wong, D. C., Miller, R. H., Govindarajan, S., Engle, R., Shapiro, M. & Purcell, R. H. (1994). Prevention of hepatitis C virus infection in chimpanzees after antibody-mediated in vitro neutralization. Proc Natl Acad Sci U S A 91, 77927796.
Farci, P., Shimoda, A., Wong, D. & 7 other authors (1996). Prevention of hepatitis C virus infection in chimpanzees by hyperimmune serum against the hypervariable region 1 of the envelope 2 protein. Proc Natl Acad Sci U S A 93, 1539415399.
Farci, P., Shimoda, A., Coiana, A. & 9 other authors (2000). The outcome of acute hepatitis C predicted by the evolution of the viral quasispecies. Science 288, 339344.
Felsenstein, J. (1985). Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39, 783791.
Flint, M., Maidens, C., Loomis-Price, L. D., Shotton, C., Dubuisson, J., Monk, P., Higginbottom, A., Levy, S. & McKeating, J. A. (1999). Characterization of hepatitis C virus E2 glycoprotein interaction with a putative cellular receptor, CD81. J Virol 73, 62356244.
Fournillier, A., Wychowski, C., Boucreux, D., Baumert, T. F., Meunier, J.-C., Jacobs, D., Muguet, S., Depla, E. & Inchauspé, G. (2001). Induction of hepatitis C virus E1 envelope protein-specific immune response can be enhanced by mutation of N-glycosylation sites. J Virol 75, 1208812097.
Frasca, L., Del Porto, P., Tuosto, L., Marinari, B., Scottà, C., Carbonari, M., Nicosia, A. & Piccolella, E. (1999). Hypervariable region 1 variants act as TCR antagonists for hepatitis C virus-specific CD4+ T cells. J Immunol 163, 650658.
Fukumoto, T., Berg, T., Ku, Y., Bechstein, W. O., Knoop, M., Lemmens, H., Lobeck, H., Hopf, U. & Neuhaus, P. (1996). Viral dynamics of hepatitis C early after orthotopic liver transplantation: evidence for rapid turnover of serum virions. Hepatology 24, 13511354.[Medline]
Garry, R. F. & Dash, S. (2003). Proteomics computational analyses suggest that hepatitis C virus E1 and pestivirus E2 envelope glycoproteins are truncated class II fusion proteins. Virology 307, 255265.[CrossRef][Medline]
Goffard, A. & Dubuisson, J. (2003). Glycosylation of hepatitis C virus envelope proteins. Biochimie 85, 295301.[CrossRef][Medline]
Gordon, S. C., Elloway, R. S., Long, J. C. & Dmuchowski, C. F. (1993). The pathology of hepatitis C as a function of mode of transmission: blood transfusion vs. intravenous drug use. Hepatology 18, 13381343.[CrossRef][Medline]
Goulder, P. J. R. & Watkins, D. I. (2004). HIV and SIV CTL escape: implications for vaccine design. Nat Rev Immunol 4, 630640.[CrossRef][Medline]
Gretch, D. R., Polyak, S. J., Wilson, J. J., Carithers, R. L., Jr, Perkins, J. D. & Corey, L. (1996). Tracking hepatitis C virus quasispecies major and minor variants in symptomatic and asymptomatic liver transplant recipients. J Virol 70, 76227631.[Abstract]
Grüner, N. H., Gerlach, T. J., Jung, M.-C. & 9 other authors (2000). Association of hepatitis C virus-specific CD8+ T cells with viral clearance in acute hepatitis C. J Infect Dis 181, 15281536.[CrossRef][Medline]
Honda, M., Kaneko, S., Sakai, A., Unoura, M., Murakami, S. & Kobayashi, K. (1994). Degree of diversity of hepatitis C virus quasispecies and progression of liver disease. Hepatology 20, 11441151.[CrossRef][Medline]
Hsu, M., Zhang, J., Flint, M., Logvinoff, C., Cheng-Mayer, C., Rice, C. M. & McKeating, J. A. (2003). Hepatitis C virus glycoproteins mediate pH-dependent cell entry of pseudotyped retroviral particles. Proc Natl Acad Sci U S A 100, 72717276.
Huang, X., Barchi, J. J., Jr, Lung, F.-D. T., Roller, P. P., Nara, P. L., Muschik, J. & Garrity, R. R. (1997). Glycosylation affects both the three-dimensional structure and antibody binding properties of the HIV-1IIIB GP120 peptide RP135. Biochemistry 36, 1084610856.[CrossRef][Medline]
Isaguliants, M. G. & Ozeretskovskaya, N. N. (2003). Host background factors contributing to hepatitis C virus clearance. Curr Pharm Biotechnol 4, 185193.[CrossRef][Medline]
Ishak, K., Baptista, A., Bianchi, L. & 13 other authors (1995). Histological grading and staging of chronic hepatitis. J Hepatol 22, 696699.[CrossRef][Medline]
Jenkins, G. M., Rambaut, A., Pybus, O. G. & Holmes, E. C. (2002). Rates of molecular evolution in RNA viruses: a quantitative phylogenetic analysis. J Mol Evol 54, 156165.[CrossRef][Medline]
Kimura, M. (1980). A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 16, 111120.[Medline]
Knodell, R. G., Ishak, K. G., Black, W. C., Chen, T. S., Craig, R., Kaplowitz, N., Kiernan, T. W. & Wollman, J. (1981). Formulation and application of a numerical scoring system for assessing histological activity in asymptomatic chronic active hepatitis. Hepatology 1, 431435.[Medline]
Kumar, U., Monjardino, J. & Thomas, H. C. (1994). Hypervariable region of hepatitis C virus envelope glycoprotein (E2/NS1) in an agammaglobulinemic patient. Gastroenterology 106, 10721075.[Medline]
Kumar, S., Tamura, K., Jakobsen, I. B. & Nei, M. (2001). MEGA2: molecular evolutionary genetic analysis software. Bioinformatics 17, 12441245.
Lau, J. Y., Davis, G. L., Kniffen, J., Qian, K. P., Urdea, M. S., Chan, C. S., Mizokami, M., Neuwald, P. D. & Wilber, J. C. (1993). Significance of serum hepatitis C virus RNA levels in chronic hepatitis C. Lancet 341, 15011504.[CrossRef][Medline]
Li, Y., Luo, L., Rasool, N. & Kang, C. Y. (1993). Glycosylation is necessary for the correct folding of human immunodeficiency virus gp120 in CD4 binding. J Virol 67, 584588.[Abstract]
Lindenbach, B. D. & Rice, C. M. (2001). Flaviviridae: the viruses and their replication. In Fields Virology, 4th edn, pp. 9911041. Edited by D. M. Knipe & P. M. Howley. Philadelphia, PA: Lippincott Williams & Wilkins.
Majid, A., Jackson, P., Lawal, Z., Pearson, G. M. J., Parker, H., Alexander, G. J. M., Allain, J.-P. & Petrik, J. (1999). Ontogeny of hepatitis C virus (HCV) hypervariable region 1 (HVR1) heterogeneity and HVR1 antibody responses over a 3 year period in a patient infected with HCV type 2b. J Gen Virol 80, 317325.[Abstract]
Marrone, A. & Sallie, R. (1996). Genetic heterogeneity of hepatitis C virus. The clinical significance of genotypes and quasispecies behavior. Clin Lab Med 16, 429449.[Medline]
Martell, M., Esteban, J. I., Quer, J., Genescà, J., Weiner, A., Esteban, R., Guardia, J. & Gómez, J. (1992). Hepatitis C virus (HCV) circulates as a population of different but closely related genomes: quasispecies nature of HCV genome distribution. J Virol 66, 32253229.[Abstract]
Martin, P., Di Bisceglie, A. M., Kassianides, C., Lisker-Melman, M. & Hoofnagle, J. H. (1989). Rapidly progressive non-A, non-B hepatitis in patients with human immunodeficiency virus infection. Gastroenterology 97, 15591561.[Medline]
McAllister, J., Casino, C., Davidson, F., Power, J., Lawlor, E., Peng, L. Y., Simmonds, P. & Smith, D. B. (1998). Long-term evolution of the hypervariable region of hepatitis C virus in a common-source-infected cohort. J Virol 72, 48934905.
McCormack, G. P. & Clewley, J. P. (2002). The application of molecular phylogenetics to the analysis of viral genome diversity and evolution. Rev Med Virol 12, 221238.[CrossRef][Medline]
Meunier, J.-C., Fournillier, A., Choukhi, A., Cahour, A., Cocquerel, L., Dubuisson, J. & Wychowski, C. (1999). Analysis of the glycosylation sites of hepatitis C virus (HCV) glycoprotein E1 and the influence of E1 glycans on the formation of the HCV glycoprotein complex. J Gen Virol 80, 887896.[Abstract]
Meyerhans, A., Cheynier, R., Albert, J., Seth, M., Kwok, S., Sninsky, J., Morfeldt-Månson, L., Asjö, B. & Wain-Hobson, S. (1989). Temporal fluctuations in HIV quasispecies in vivo are not reflected by sequential HIV isolations. Cell 58, 901910.[CrossRef][Medline]
Mohsen, A. H. (2001). The epidemiology of hepatitis C in a UK health regional population of 5·12 million. Gut 48, 707713.
Muller, R. (1996). The natural history of hepatitis C: clinical experiences. J Hepatol 24, 5254.[CrossRef][Medline]
Neumann, A. U., Lam, N. P., Dahari, H., Gretch, D. R., Wiley, T. E., Layden, T. J. & Perelson, A. S. (1998). Hepatitis C viral dynamics in vivo and the antiviral efficacy of interferon- therapy. Science 282, 103107.
Okamoto, H., Kojima, M., Okada, S. I. & 7 other authors (1992). Genetic drift of hepatitis C virus during an 8·2-year infection in a chimpanzee: variability and stability. Virology 190, 894899.[CrossRef][Medline]
Owsianka, A., Clayton, R. F., Loomis-Price, L. D., McKeating, J. A. & Patel, A. H. (2001). Functional analysis of hepatitis C virus E2 glycoproteins and virus-like particles reveals structural dissimilarities between different forms of E2. J Gen Virol 82, 18771883.
Parker, K. C., Bednarek, M. A. & Coligan, J. E. (1994). Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains. J Immunol 152, 163175.
Penin, F., Combet, C., Germanidis, G., Frainais, P.-O., Deléage, G. & Pawlotsky, J.-M. (2001). Conservation of the conformation and positive charges of hepatitis C virus E2 envelope glycoprotein hypervariable region 1 points to a role in cell attachment. J Virol 75, 57035710.
Pinter, A., Honnen, W. J., He, Y., Gorny, M. K., Zolla-Pazner, S. & Kayman, S. C. (2004). The V1/V2 domain of gp120 is a global regulator of the sensitivity of primary human immunodeficiency virus type 1 isolates to neutralization by antibodies commonly induced upon infection. J Virol 78, 52055215.
Pugach, P., Kuhmann, S. E., Taylor, J., Marozsan, A. J., Snyder, A., Ketas, T., Wolinsky, S. M., Korber, B. T. & Moore, J. P. (2004). The prolonged culture of human immunodeficiency virus type 1 in primary lymphocytes increases its sensitivity to neutralization by soluble CD4. Virology 321, 822.[CrossRef][Medline]
Puntoriero, G., Meola, A., Lahm, A. & 9 other authors (1998). Towards a solution for hepatitis C virus hypervariability: mimotopes of the hypervariable region 1 can induce antibodies cross-reacting with a large number of viral variants. EMBO J 17, 35213533.
Rambaut, A. (2000). Estimating the rate of molecular evolution: incorporating non-contemporaneous sequences into maximum likelihood phylogenies. Bioinformatics 16, 395399.[Abstract]
Ramratnam, B., Bonhoeffer, S., Binley, J. & 7 other authors (1999). Rapid production and clearance of HIV-1 and hepatitis C virus assessed by large volume plasma apheresis. Lancet 354, 17821785.[CrossRef][Medline]
Ray, S. C., Wang, Y.-M., Laeyendecker, O., Ticehurst, J. R., Villano, S. A. & Thomas, D. L. (1999). Acute hepatitis C virus structural gene sequences as predictors of persistent viremia: hypervariable region 1 as a decoy. J Virol 73, 29382946.
Robertson, D. L., Hahn, B. H. & Sharp, P. M. (1995). Recombination in AIDS viruses. J Mol Evol 40, 249259.[CrossRef][Medline]
Roccasecca, R., Ansuini, H., Vitelli, A. & 11 other authors (2003). Binding of the hepatitis C virus E2 glycoprotein to CD81 is strain specific and is modulated by a complex interplay between hypervariable regions 1 and 2. J Virol 77, 18561867.
Rosa, D., Campagnoli, S., Moretto, C. & 11 other authors (1996). A quantitative test to estimate neutralizing antibodies to the hepatitis C virus: cytofluorimetric assessment of envelope glycoprotein 2 binding to target cells. Proc Natl Acad Sci U S A 93, 17591763.
Ryder, S. D., Irving, W. L., Jones, D. A., Neal, K. R. & Underwood, J. C. (2004). Progression of hepatic fibrosis in patients with hepatitis C: a prospective repeat liver biopsy study. Gut 53, 451455.
Saito, I., Miyamura, T., Ohbayashi, A. & 10 other authors (1990). Hepatitis C virus infection is associated with the development of hepatocellular carcinoma. Proc Natl Acad Sci U S A 87, 65476549.
Saitou, N. & Nei, M. (1987). The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4, 406425.[Abstract]
Scarselli, E., Ansuini, H., Cerino, R. & 7 other authors (2002). The human scavenger receptor class B type I is a novel candidate receptor for the hepatitis C virus. EMBO J 21, 50175025.
Schønning, K., Jansson, B., Olofsson, S. & Hansen, J.-E. S. (1996). Rapid selection for an N-linked oligosaccharide by monoclonal antibodies directed against the V3 loop of human immunodeficiency virus type 1. J Gen Virol 77, 753758.[Abstract]
Serra, M. A., Rodríguez, F., del Olmo, J. A., Escudero, A. & Rodrigo, J. M. (2003). Influence of age and date of infection on distribution of hepatitis C virus genotypes and fibrosis stage. J Viral Hepat 10, 183188.[CrossRef][Medline]
Sheridan, I., Pybus, O. G., Holmes, E. C. & Klenerman, P. (2004). High-resolution phylogenetic analysis of hepatitis C virus adaptation and its relationship to disease progression. J Virol 78, 34473454.
Shimizu, Y. K., Hijikata, M., Iwamoto, A., Alter, H. J., Purcell, R. H. & Yoshikura, H. (1994). Neutralizing antibodies against hepatitis C virus and the emergence of neutralization escape mutant viruses. J Virol 68, 14941500.[Abstract]
Shimizu, Y., Igarashi, H., Kiyohara, T., Cabezon, T., Farci, P., Purcell, R. H. & Yoshikura, H. (1996). A hyperimmune serum against a synthetic peptide corresponding to the hypervariable region 1 of hepatitis C virus can prevent viral infection in cell cultures. Virology 223, 409412.[CrossRef][Medline]
Shirai, M., Arichi, T., Nishioka, M., Nomura, T., Ikeda, K., Kawanishi, K., Engelhard, V. H., Feinstone, S. M. & Berzofsky, J. A. (1995). CTL responses of HLA-A2.1-transgenic mice specific for hepatitis C viral peptides predict epitopes for CTL of humans carrying HLA-A2.1. J Immunol 154, 27332742.
Shoukry, N. H., Cawthon, A. G. & Walker, C. M. (2004). Cell-mediated immunity and the outcome of hepatitis C virus infection. Annu Rev Microbiol 58, 391424.[CrossRef][Medline]
Smith, D. B. (1999). Evolution of the hypervariable region of hepatitis C virus. J Viral Hepat 6, 4146.[CrossRef][Medline]
Sullivan, J., Swofford, D. L. & Naylor, G. J. P. (1999). The effect of taxon sampling on estimating rate heterogeneity parameters of maximum-likelihood models. Mol Biol Evol 16, 13471356.
Swofford, D. L. (2003). PAUP*: Phylogenetic Analysis Using Parsinomy (*and other methods), version 4. Sunderland. MA: Sinauer Associates.
Thompson, J. D., Gibson, T. J., Plewniak, F., Jeanmougin, F. & Higgins, D. G. (1997). The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 25, 48764882.
Tsai, S. L., Chen, Y. M., Chen, M. H., Huang, C. Y., Sheen, I. S., Yeh, C. T., Huang, J. H., Kuo, G. C. & Liaw, Y. F. (1998). Hepatitis C virus variants circumventing cytotoxic T lymphocyte activity as a mechanism of chronicity. Gastroenterology 115, 954965.[Medline]
Urbani, S., Uggeri, J., Matsuura, Y., Miyamura, T., Penna, A., Boni, C. & Ferrari, C. (2001). Identification of immunodominant hepatitis C virus (HCV)-specific cytotoxic T-cell epitopes by stimulation with endogenously synthesized HCV antigens. Hepatology 33, 15331543.[CrossRef][Medline]
Wack, A., Soldaini, E., Tseng, C.-T. K., Nuti, S., Klimpel, G. R. & Abrignani, S. (2001). Binding of the hepatitis C virus envelope protein E2 to CD81 provides a co-stimulatory signal for human T cells. Eur J Immunol 31, 166175.[CrossRef][Medline]
Wang, H. & Eckels, D. D. (1999). Mutations in immunodominant T cell epitopes derived from the nonstructural 3 protein of hepatitis C virus have the potential for generating escape variants that may have important consequences for T cell recognition. J Immunol 162, 41774183.
Ward, S., Lauer, G., Isba, R., Walker, B. & Klenerman, P. (2002). Cellular immune responses against hepatitis C virus: the evidence base 2002. Clin Exp Immunol 128, 195203.[CrossRef][Medline]
Wei, X., Decker, J. M., Wang, S. & 12 other authors (2003). Antibody neutralization and escape by HIV-1. Nature 422, 307312.[CrossRef][Medline]
Weltman, M. D., Brotodihardjo, A., Crewe, E. B., Farrell, G. C., Bilous, M., Grierson, J. M. & Liddle, C. (1995). Coinfection with hepatitis B and C or B, C and delta viruses results in severe chronic liver disease and responds poorly to interferon-alpha treatment. J Viral Hepat 2, 3945.[Medline]
WHO (1999). Global surveillance and control of hepatitis C. J Viral Hepat 6, 3547.[CrossRef][Medline]
Wu, Z., Kayman, S. C., Honnen, W. & 7 other authors (1995). Characterization of neutralization epitopes in the V2 region of human immunodeficiency virus type 1 gp120: role of glycosylation in the correct folding of the V1/V2 domain. J Virol 69, 22712278.[Abstract]
Yagnik, A. T., Lahm, A., Meola, A., Roccasecca, R. M., Ercole, B. B., Nicosia, A. & Tramontano, A. (2000). A model for the hepatitis C virus envelope glycoprotein E2. Proteins 40, 355366.[CrossRef][Medline]
Yang, Z. (1994a). Estimating the pattern of nucleotide substitution. J Mol Evol 39, 105111.[Medline]
Yang, Z. (1994b). Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods. J Mol Evol 39, 306314.[CrossRef][Medline]
Yang, Z. (1997). PAML: a program package for phylogenetic analysis by maximum likelihood. Comput Appl Biosci 13, 555556.[Medline]
Yang, Z. & Bielawski, J. P. (2000). Statistical methods for detecting molecular adaptation. Trends Ecol Evol 15, 496503.[CrossRef][Medline]
Yu, K., Petrovsky, N., Schonbach, C., Koh, J. Y. & Brusic, V. (2002). Methods for prediction of peptide binding to MHC molecules: a comparative study. Mol Med 8, 137148.[Medline]
Zaphiropoulos, P. G. (2002). Template switching generated during reverse transcription? FEBS Lett 527, 326.[CrossRef][Medline]
Zeuzem, S. (2000). Hepatitis C virus: kinetics and quasispecies evolution during anti-viral therapy. Forum 10, 3242.[Medline]
Received 9 February 2005;
accepted 21 March 2005.
HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
INT J SYST EVOL MICROBIOL | MICROBIOLOGY | J GEN VIROL |
J MED MICROBIOL | ALL SGM JOURNALS |