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Previous Article | Next Article 
Journal of Virology, October 1998, p. 7895-7899, Vol. 72, No. 10
0022-538X/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
Mortality among Human Immunodeficiency Virus Type 2-Positive
Villagers in Rural Guinea-Bissau Is Correlated with Viral
Genotype
Nicholas C.
Grassly,1,*
Zheng
Xiang,2
Koya
Ariyoshi,3
Peter
Aaby,4
Henrik
Jensen,4
Maarten
Schim van
der Loeff,4
Francisco
Dias,5
Hilton
Whittle,3 and
Judith
Breuer2
Wellcome Trust Centre for the Epidemiology of
Infectious Diseases, Department of Zoology, University of Oxford,
Oxford,1 and
Department of Medical
Microbiology, St. Bartholomew's and The Royal London School of
Medicine and Dentistry, London,2 United
Kingdom;
MRC Laboratories, Medical Research Council,
Banjul, The Gambia, West Africa3;
Department of Epidemiology, Staten Serum Institute,
Copenhagen, Denmark4; and
Laboratorio
Nacional de Sande Publica, Bissau, Guinea Bissau5
Received 30 January 1998/Accepted 17 June 1998
 |
ABSTRACT |
We present the results of a 6-year study of 131 human
immunodeficiency virus (HIV) type 2 (HIV-2)-infected individuals from a
rural population in Guinea-Bissau. Proviral DNA sequences 1.3 kb in
length were obtained from each individual and, together with clinical
data, including proviral load and CD4 and CD8 levels, were used to
assess whether viral genotype influences clinical outcome. With a
phylogenetic model, a correlation was found between viral genotype and
mortality; this correlation was not due to confounding factors, such as
age-specific viral strains or cohabitation of patients. The data
provide strong evidence for the involvement of viral genetic factors in
determining HIV disease progression in vivo. The pattern of association
found suggests that virulence factors are multiple and scattered
throughout the HIV-2 genome and can be rapidly gained or lost by the
virus through a combination of mutation and recombination. These
findings may lead to the identification of viral determinants of
HIV disease progression.
| |
INTRODUCTION |
The majority of individuals infected
with human immunodeficiency virus (HIV) type 1 (HIV-1) develop AIDS
within 10 years. However, approximately 10% of cases progress rapidly
(2 to 3 years) to AIDS, while 5 to 10% of cases are slow or
nonprogressive, with patients remaining clinically asymptomatic after
10 years (20, 34). HIV type 2 (HIV-2) is claimed to have a
longer incubation period between infection and overt AIDS than HIV-1
(29) but has recently been clearly characterized as having a
similar diversity of clinical outcome (36). Among adults
under the age of 45 years, the ratio of mortality in HIV-2-infected to
uninfected individuals has been shown to be 5:1. However, unlike
mortality with HIV-1, which rises with age (6), the
mortality ratio for older people with HIV-2 infection is close to 1:1
(36), suggesting a dichotomy between rapid progression to
AIDS and slow progression or even nonprogression.
Susceptibility to HIV-1 infection and the rate of progression of
disease have been strongly associated with polymorphisms in host genes
coding for the CCR5 (11, 32) and CCR2 (39) chemokine receptors, which also function as HIV coreceptors. In addition, there is some effect from host immunoregulatory factors, including the major histocompatibility complex (30). In
contrast, although HIV-1 and HIV-2 have been shown to differ in
biological properties in vitro (8, 38), little evidence
has accumulated concerning the importance of viral genetic
factors in determining disease progression in vivo (33,
40, 41). A reason for the current lack of certainty about
the existence and role of viral virulence factors is the difficulty in
classifying clinical outcome for HIV-1 infection, due to the continuum
in the lengths of incubation period between infection and full-blown
AIDS (7, 34). In contrast, the clear dichotomy in clinical
outcome for HIV-2 infection (36) provides an
opportunity to carry out systematic investigations into the relative
roles of host versus viral genetic factors in determining the rate
of progression to AIDS. Such investigations not only are
important for the understanding and control of HIV-2 but also may
reveal important features concerning the mechanisms leading to AIDS in
chronic retroviral infections. In addition, there is some evidence that
HIV-2 infection may protect against HIV-1 infection (2, 19, 23,
42). If viral genetic determinants of nonprogressive clinical
outcome could be found for HIV-2, then this may have implications for
the development of vaccines against both HIV-1 and HIV-2.
This paper presents results from a prospective study of HIV-2-infected
residents of a village in rural Guinea-Bissau who, together with
uninfected controls, have been monitored with clinical, virological,
and immunological investigations for over 6 years (37, 43).
These HIV-2-infected residents have suffered approximately three times
the mortality rate of uninfected controls (37) and show
a dichotomy in the rate of disease progression (1), in accordance with the findings for a similar cohort of HIV-2-infected individuals monitored in Bissau, the capital of Guinea-Bissau (36). Using novel phylogenetic methods, we investigated
whether the mortality rate of HIV-2-infected individuals within
this cohort depends upon viral genotype.
| |
MATERIALS AND METHODS |
Subjects.
A total of 134 HIV-2-positive subjects were
originally entered into a cohort study between March and June 1991 and
followed up with annual censuses until 1997 (37). All
subjects were of the same ethnic origin, and none had received blood
transfusions or blood products. Subjects were examined clinically, and
blood samples were taken in both 1991 and 1997 and cryopreserved. The CD4 and CD8 levels in the cryopreserved blood samples taken in 1991 were measured previously (37, 43). In addition, a
quantitative PCR was used to assess proviral load (4).
Postmortem interviews were conducted with the relatives of all those
who died. Lymphocyte DNA from 131 of the 134 HIV-2-positive subjects
from whom samples were obtained in 1991 was available for analysis.
PCR amplification and sequencing.
Proviral DNA was extracted
from one 200-µl aliquot of frozen lymphocytes obtained in 1991, and
the gag, pol, env, and long terminal
repeat (LTR) regions were amplified by the PCR. Primer sequences (with
International Union of Pure and Applied Chemistry mixed base codes) and
positions (in nucleotides) (numbered according to HIV-2ROD)
were as follows: Gag 1, AGGTTACGGCCCGGCGGAAAGAAAA (603 to
627); Gag 2, CCTACTCCCTGACAGGCCGTCAGCATTTCTTC (1612 to 1581); Gag 3, GGATTAGCAGAGAGCCTGTTGGA (677 to 700); Gag 4 (44), CCTTAAGCTTTTGTAGAATCTATCTACATA (1466 to
1437); Pol 1, AATATTATAGTAGAYTCACARTATGT (603 to 627); Pol
2, CCWAYYCCYTGRCADGYXGTYARCATYTCYTC (1612 to 1581); Pol 3, TATGTTGCATGGGTCCCAGCCC (3397 to 3992); Pol 4, TTCATTGCTTCCACTACTCC (1279 to 1258); Env 1, TRCTATDARRTTTAGRTAYTG (6807 to 6851); Env 2, TCYCTDGGAGGCAAATAHAC (7340 to 7316); Env 3, TAGRTAYTGTGCACCRCCRGG (6911 to 6935); Env 4, TSCCTACYTTRTGCCAVGTRT (9301 to 9277); LTR 1, TAACCAAGGGAGGGACATGGG (9411 to 9431); LTR 2, TGGTGAGAGTCTAGCAGGG (9592 to 9574); LTR 3, AGGAGCTGGTGGGGAACGCCCT (9432 to 9453); and LTR 4 (5), AACACCCAGGCTCTACCTGCT (9573 to 9553).
A reaction mixture (50 µl) containing 200 to 400 ng of extracted
proviral DNA, 1.5 mM MgCl2, 5 µl of 10× reaction buffer
(Perkin Elmer), 200 mM each deoxynucleoside triphosphate, 50 pmol of
each primer, and 1 U of Taq polymerase (Perkin Elmer) was
subjected to hot-start denaturation at 95°C for 3 min followed by 35 cycles of 94°C for 1 min, 40°C for 2 min, and 72°C for 1.5 min
and a final cycle of 94°C for 1 min, 40°C for 2 min, and 72°C for
2 min. Nested PCRs were carried out under the same conditions, except that 0.5 µl of the first-round product was added to the reaction mixture and the annealing temperature was raised to 55°C. Nested PCR
products were electrophoresed on a 1.5% low-melting-temperature agarose gel, and a product of the correct size was extracted with the
Wizard DNA purification system (Promega). The mixture was ethanol
precipitated and directly cycle sequenced in both directions on an ABI
377 sequencer with fluorescent dye terminators. The env and
LTR products were sequenced with the PCR primers. Additional primers
used to sequence gag and pol were as follows: Gag
5, CACGCAGAAGAGAAAGTGAAA (810 to 830); Gag 6, TCTACTGTGCTTGTTGTTCCTG (1279 to 1258); Pol 5, TATGTTGCATGGGTCCCAGCCC (3971 to 3992); and Pol 6, TTCATTGCTTCCACTACTCC (4521 to 4502). In the majority of
cases, the consensus sequence was verified by sequencing of products
from two separate PCRs.
Phylogenetic trees.
The consensus sequences were aligned
with ClustalV (21). Maximum-likelihood (ML) phylogenetic
trees were constructed with a test version of PAUP* (d54) made
available by David Swofford. Trees were constructed for all sequences
independently and for a joint alignment of gag, LTR, and
pol sequences. These trees were used when assessing the
correlation between viral phenotype (see below) and various clinical
features. In the case of any missing individual clinical data, trees
were constructed with the relevant number of taxa. The env
sequences were not included in a joint alignment, as in only 79 subjects were sequences available for all four regions. The
substitution model used to construct the ML phylogenetic trees was F84
(for a description, see reference 16). ML estimates
of the transition/transversion ratio were obtained for each tree. In
the case of the joint gag, LTR, and pol
alignment, different relative substitution rates were allowed for each
gene.
Phylogenetic models.
To assess whether there are viral
genetic determinants of clinical aspects of HIV-2 infection (which we
term the viral phenotype), models of how viral phenotype changes with
underlying viral genotype are required. The phenotypic characters
modelled in this paper are the status of the infected individual (dead
or alive), CD4 and CD8 levels (and their ratio), and viral load. The
genotype of the virus is the consensus sequence obtained by direct
sequencing from the infected individual and is represented by its
position in the phylogenetic tree.
In a very simple model, an HIV-2 isolate can be said to be either
benign (found in nonprogressors) or fatal. If the virus changes its
state at rate 
, then the probability (P) of change between benign and fatal states over any time t is given
by
where f is the equilibrium frequency of benign or
fatal isolates in the viral population. Given that a virus is in
state i at time 0 and state j at time
t, the likelihood (L) of this situation for a
given rate is calculated simply as
L(,t|ij) = Pij (t).
A measure of the time of separation of two viral isolates is simply the
number of substitutions per site that have occurred in their nucleotide
sequences, estimated with an appropriate substitution model. Thus,
given two viral nucleotide sequences (e.g., the gag gene)
and their viral phenotypes, the likelihood for this simple model of
phenotypic change for a given rate can be calculated. If
substitutional information about the time of separation of the two
viral isolates is discarded and the rate of phenotypic change and time
are treated as a compound parameter t, the ML estimate of
this parameter for two viral isolates given their viral phenotypes can
be found. For more than two isolates, substitutional information can be
used to construct a phylogenetic tree which best represents their
relatedness (as is done with PAUP*). The ML for a distribution of
benign and fatal isolates on this phylogenetic tree can be found with a
"pruning" algorithm (13-15), which relies only upon the
accuracy of the reconstructed phylogenetic topology (not branch
lengths).
With a similar procedure, the ML for a distribution of continuous
phenotypic characters (e.g., CD4 and CD8 levels and viral load) on a
given phylogeny can be calculated. The model implemented in this paper
is that of Brownian motion (see, e.g., reference 14). In other words, the mean phenotype undergoes
a random diffusion on an infinite linear scale. Thus, the
probability (P) that a character with value
x1 has value x2 after
time t follows the normal density function
where µ is the rate parameter. As for the discrete model, this
probability is equivalent to the likelihood
L(µ,t|x1,x2) = Px1x2(t).
Again, the compound parameter µt is considered and
substitutional information is used only to construct a phylogenetic
tree relating the sequences. The ML for a distribution of continuous
characters on a phylogeny can be calculated with a pruning algorithm
similar to that used for discrete characters but in which the length of
the internal branch is altered following pruning (14).
The significance of each ML value calculated for the phylogenetic model
relating viral genotype to clinical features was assessed by first
calculating the MLs for 100 randomizations of the clinical data. The
observed ML was then ranked among these likelihoods to obtain a
P value. If the observed ML fell within or was better than
the best five randomized likelihoods, then it was concluded that the
data fit the model significantly better than would be expected by
chance at the 5% level.
ML values have limited statistical power in differentiating hypotheses,
since even randomized data may have an ML value that is quite high
(12). Tests for significance based on ML values therefore
tend to be conservative. The likelihood ratio is a far more powerful
test statistic but relies on the existence of two competing hypotheses
for which ML values can be calculated. An alternative hypothesis
against which to test the models of genotype-phenotype correlation
described here is difficult to develop. It is possible to use the
normal distribution as an alternative hypothesis for the observed
continuous characters and the binomial distribution for the discrete
characters. However, care would need to be taken in interpreting
nonsignificant likelihood ratios (i.e., ratios for which the hypothesis
of genotype-phenotype correlation cannot be rejected), since the
validity of such results would depend upon the validity of the
alternative hypothesis. Thus, at present, only the ML statistic is
used.
Investigation of other correlates of mortality.
Possible
correlates of mortality, other than viral genotype, were investigated
by survival analysis because of their suggested importance in a
previous study (36). Factors investigated included subject
age, gender, area of residence, spouse HIV-2 status, and activity as a
prostitute. A Cox proportional-hazards model was used (9),
with time since blood sampling as the underlying time scale. For
analyses other than that of age of subject, age was controlled for as a
background variable.
Identification of motifs and base changes associated with
pathogenic viruses.
For each site in the gag,
pol, LTR, and V3 alignments, the minimum number of changes
in the respective ML phylogenetic trees necessary to explain the
distribution of sequence diversity was calculated with MacClade
(28). These changes were then subdivided into those
occurring in viral lineages whose descendants were exclusively
associated with mortality and those occurring in all other lineages. By
use of a program written in C it was possible to obtain plots of the
frequencies of nucleotide changes along the aligned sequences similarly
subdivided. These plots displayed the site-specific changes associated
with mortality against the background of changes occurring in all other
lineages and hence allowed identification of any changes and/or motifs
associated with mortality. A nonphylogenetic method for detecting
"signature patterns" of query sequences was also used to assess
whether there is a correlation of certain nucleotides with mortality
(27). A signature pattern is comprised of nucleotides for
which the ratio of their frequencies in the query sequence alignment
and the background alignment is above a certain threshold. A computer program, VESPA (27), implementing this method was used to
determine the frequencies of the nucleotides comprising the putative
signature of sequences associated with mortality and their frequencies
in the alignment of sequences isolated from individuals alive at the
end of the follow-up period.
Nucleotide sequence accession numbers.
The following
sequences were deposited in the EMBL database under accession no.
AJ008441 and AJ011191, 539 and 222 for gag, respectively;
AJ008540, 667 for pol; AJ008283 and AJ011223, 316 and 272 for env, respectively; and AJ008317, 440 for the LTR.
| |
RESULTS |
Subjects and nucleotide sequences.
During the study, 26 people
died. Proviral gag (350 bp), pol (415 bp),
env (V3; 357 bp), and LTR (164 bp) sequences were amplified from 123, 127, 84, and 124 patients, respectively. In 117 of the 131 subjects analyzed, including 25 of the 26 patients who died, at least
three regions (gag, pol, and LTR) were amplified.
The other patient who died and from whom sequences of the
gag and V3 regions only were available was a 32-year-old
woman who had a CD4 count of 32% and who died 4 days postpartum.
Postmortem interviews conducted with the relatives of the other 25 subjects who died could not exclude HIV as a cause of death in all
cases, with the possible exception of a 44-year-old man. However, all 25 patients who died were included in the analyses.
All sequences were found to be HIV-2 subtype A, in agreement with a
previous analysis of a subset of the gag gene data set (44). The sequences have been deposited in the EMBL sequence database.
Phylogenetic trees.
Figure 1
shows an ML phylogenetic tree for the 117 sequences of the joint
alignment of gag, pol, and LTR sequences;
sequences isolated from people who subsequently died are marked.
View larger version (26K):
[in this window]
[in a new window]
|
FIG. 1.
ML phylogenetic tree of the HIV-2 isolates for the joint
alignment of gag, pol, and LTR sequences, showing
sequences isolated from people who subsequently died (marked by black
circles). The estimated relative rates of substitution for the three
regions of the HIV-2 genome were 1.19, 0.77, and 1.02, respectively.
The estimated transition/transversion ratio was 1.65. The scale bar
indicates the length of a branch with one substitution per 10 nucleotide sites.
|
|
Phylogenetic models.
A correlation was found between the death
of HIV-2-infected individuals and viral genetic identity (Table
1). This correlation was highly
significant for the joint alignment of LTR, gag, and pol sequences (P, <0.01) but became
nonsignificant when the gag, pol, and LTR genes
were examined individually (P, 0.45, 0.07, and 0.07, respectively). This result may reflect the increased phylogenetic
resolution provided by use of a joint alignment with appropriate models
for each gene (22) (although this effect may be counteracted
by recombination occurring between the genes). A previous cohort study
of HIV-2-infected individuals showed that deaths early in the follow-up
period are more likely to involve rapid progressors (36).
This trend was recently confirmed for the cohort studied here, with no
excess mortality occurring in the HIV-2-positive cohort after 1995 (mortality rate ratio, 0.94, versus 3.38 before 1995 [1]). Analysis of only those deaths occurring prior to
1995 revealed a significant correlation with viral genotype for all but
the gag sequences (Table 1).
View this table:
[in this window]
[in a new window]
|
TABLE 1.
Log likelihoods for a model of clinical outcome dependent
upon viral genotype represented by different genes for a range of
clinical features, together with P values denoting the
probability of obtaining a likelihood this good
by chancea
|
|
No correlation was found between mortality and the V3 region of the
envelope gene (P was 0.5 for both the analysis of all deaths
and the analysis of deaths prior to 1995). This result may reflect the
smaller number of V3 sequences than of gag, pol, and LTR sequences available for analysis. It may also reflect a lack of
statistical power of the ML statistic.
It was possible to use these sequences to predict the in vitro
replication phenotype of the HIV-2 isolates, since this phenotype was
recently shown to correlate with certain amino acid changes in the V3
loop (3) as has been previously demonstrated for HIV-1
(18). The syncytium-inducing phenotype was, however,
suggested by amino acid changes in only two subjects and was not found
to correlate with mortality (
2 test of independence:
2, 0.683; P, 0.41). These results suggest the
importance of some other viral virulence factor(s) and confirm the
observation that the syncytium-inducing phenotype tends to be more
prevalent only close to the onset of AIDS (26, 38).
No correlation was found between viral genotype and high proviral load
or low CD4 count (Table 1), despite previous findings of a relationship
between the latter two and progression to AIDS in HIV-2-infected people
(4). This result may be explained by the fact that of the 25 deaths included in our analysis, only 15 were associated with a high
viral load (>100 copies/105 CD4 cells) and low CD4 levels
(<29%) at the time of blood sampling (in accordance with previous
definitions for these categories [37]). Furthermore,
the levels of HIV-2 provirus varied considerably, and the mean level
was high even in subjects with high CD4 levels. Thus, it appears that
these markers for disease progression are not consistent if the onset
of AIDS is not imminent. A more suitable marker allowing early
prognosis of the rate of progression to death in HIV-2-positive
individuals may therefore be plasma viral load, as is the case for
HIV-1 (31).
Investigation of other correlates of mortality.
Using the Cox
proportional-hazards model (9), we found no correlation
between mortality and subject gender, area of residence, spouse HIV-2
status, or prostitution (P, 0.385, 0.984, 0.056, and 0.433, respectively). A significant correlation was found, however, between
mortality and the age of HIV-2-positive individuals when the latter was
treated as a continuous variable (mortality rate ratio, 1.06 per year
[95% confidence interval, 1.03 to 1.09]; P, <0.001).
Further analysis revealed that, although mortality was higher in those
over 65 years old, there was no increase in mortality with age in those
under 65 years old (test for trend: P, 0.593) (Table
2). This finding agrees with the
dichotomy in clinical progression for HIV-2 infection (36)
and previous observations for the same community (37).
View this table:
[in this window]
[in a new window]
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TABLE 2.
Mortality of HIV-2-positive individuals subdivided
according to age group relative to the oldest age group
|
|
Identification of motifs and base changes associated with
pathogenic viruses.
Consistent patterns of base changes in
lineages leading to the pathogenic viruses were not found by use of the
phylogenetic approach described. Similarly, no signature patterns were
found to define the sequences associated with mortality. Table
3 shows the putative signature
nucleotides of pathogenic sequences and their frequencies in both these
pathogenic sequences and sequences isolated from patients alive at the
end of the follow-up period. These frequencies are not very different,
indicating no clear correlation between a particular viral motif or
single nucleotide change and mortality in the regions sequenced. This
finding probably reflects the fact that a relatively small proportion
(1,300 bases) of the entire HIV-2 genome (~10,000 bases) was
sequenced.
View this table:
[in this window]
[in a new window]
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TABLE 3.
Putative signature patterns for the V3, gag,
LTR, and pol sequences associated with mortality,
as detected with VESPA (27)
|
|
| |
DISCUSSION |
The data reported here reveal a correlation between viral genotype
and mortality in HIV-2 infection in vivo. Furthermore, the fact that no
distinct viral phylogenetic group (clade) is associated with mortality
(Fig. 1) suggests that several viral virulence factors found within or
linked to the gag, pol, and LTR regions sequenced
can be gained or lost by the virus. Because such motifs were not
detected within the sequences analyzed with the methods described here,
linkage seems the most likely explanation.
It is possible that the correlation was confounded by other factors,
which may covary in some way with both viral genotype and mortality.
Gender, area of residence, spouse HIV-2 status, and prostitution,
previously suggested as risk factors (36), were all found
not to correlate with mortality. However, age was found to correlate
with the mortality of HIV-2-positive individuals when treated as a
continuous variable (P, <0.001). In addition, age was found
to correlate with viral genotype for the gag and LTR
sequences when assessed with the likelihood methods described previously (P, 0.02 and 0.03, respectively). It is therefore
possible that certain viral strains were circulating at certain times, infecting specific age groups when they were sexually active, and that
the death of older subjects caused a correlation between mortality and
viral genotype. However, although mortality was higher in those over 65 years old, there was no correlation between mortality and age in those
under 65 years old (Table 2). Since consideration of the deaths of only
people under 65 years old still resulted in a significant correlation
with viral genotype (Table 1), age could not be confounding the in vivo
correlation between viral genotype and mortality.
The possibility that discrete viral genetic elements are associated
with mortality in HIV-2 infections is supported by experimental evidence derived from strains of simian immunodeficiency virus. Acquisition of virulence by some strains of simian immunodeficiency virus has been associated with changes occurring in the env
(17, 24, 35), gag (25, 35),
tat (17), and nef (35)
genes and the LTR (24, 35). Furthermore, deletions in the
HIV-1 nef gene have been described for a cohort of unrelated
long-term nonprogressors who received transfusions from a single donor, supporting the notion that viral determinants may influence disease progression (10).
In conclusion, this paper provides evidence for heritable viral
virulence factors important in determining the rate of disease progression in vivo. These results are compatible with the role of
other determinants of virulence, including both host factors and viral
genetic changes that may occur within individual hosts (intrahost
evolution). Given the rapid mutation rate and turnover of HIV-2 within
humans, the latter may be of importance, in particular with
regard to escape from immune recognition or the use of a broader range
of receptors. However, the recognition of heritable virulence
factors now prompts the need for their precise identification and
further research toward an understanding of the mechanisms by which
they are acquired and interact with host determinants of disease
progression.
| |
ACKNOWLEDGMENTS |
We are indebted to the people who took part in the
community-based study and to Andrew Wilkins for his contribution to the design of the study. We also thank Pedro Biri Gomes for additional clinical data, Thiru Surentheran for technical help, and Eddie Holmes,
Paul Harvey, and Robin Weiss for constructive criticism regarding the
manuscript.
This work was supported by the MRC (J.B.) and BBSRC (grants to
N.C.G.).
| |
FOOTNOTES |
*
Corresponding author. Mailing address: Wellcome Trust
Centre for the Epidemiology of Infectious Diseases, Department of
Zoology, University of Oxford, South Parks Rd., Oxford OX1 3PS,
United Kingdom. Phone: 44 1865 271263. Fax: 44 1865 310447. E-mail: nicholas.grassly{at}zoo.ox.ac.uk.
| |
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Journal of Virology, October 1998, p. 7895-7899, Vol. 72, No. 10
0022-538X/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
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Abstract
Introduction
