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J Virol. Nov 2002; 76(22): 11715–11720.
PMCID: PMC136752

Immune-Mediated Positive Selection Drives Human Immunodeficiency Virus Type 1 Molecular Variation and Predicts Disease Duration


Using likelihood-based evolutionary methods, we demonstrate that the broad genetic diversity of human immunodeficiency virus type 1 (HIV-1) in an infected individual is a consequence of site-specific positive selection for diversity, a likely consequence of immune recognition. In particular, the extent of positive selection appears to be a good predictor of disease duration. Positively selected sites along HIV-1 partial env sequences are numerous but not distributed uniformly. In a sample of eight patients studied longitudinally, the proportion of sites per sample under positive selection was a statistically significant predictor of disease duration. Among long-term progressors, positive selection persisted at sites over time and appears to be associated with helper T-cell epitopes. In contrast, sites under positive selection shifted from one longitudinal sample to the next in short-term progressors. Our study is consistent with the hypothesis that a broad and persistent immunologic response is associated with a slower rate of disease progression. In contrast, narrow, shifting immune responses characterize short-term progressors.

The broad genetic diversity of human immunodeficiency virus type 1 (HIV-1) that is seen in an infected individual (34) is hypothesized to result from positive immune-mediated selection for viral diversity (2), but evidence for this is contradictory and inconclusive (20, 27, 33, 45, 46). In an infected individual, the envelope gene (env) diverges from founding genomes approximately 1% per annum (34). The envelope glycoprotein (gp120) plays a primary role in cell infection through possession of cell membrane binding receptors (1, 4-8, 22, 35), cytotropism phenotypes (3), and recognition sites for neutralizing antibodies (Abs) (10, 14), cytotoxic T lymphocytes (CTLs) (39, 40), and helper T lymphocytes (HTLs) (9). The error-prone reverse transcription of HIV (23) provides raw viral genetic material upon which selection for novelty can create sequences that escape from immune recognition (reviewed in reference 24).

The occurrence of positive selection is routinely estimated from an excess of nonsynonymous (amino-acid-changing) substitutions over synonymous (silent) substitutions (26). However, a single, and effectively average, estimate of selection across the sequence may mask individual sites under strong negative (purifying) or positive (diversifying) selection. Maximum likelihood methods which permit selection to vary among sites have shown in HIV-1 genes (27, 50) that positive selection has acted on a small proportion of sites, whereas the majority were under neutral or strong purifying selection.

We tested the hypothesis that the development of genetic diversity of HIV-1 within infected individuals is the result of positive selection by applying the methods of Nielsen and Yang (27) to a large data set of HIV-1 partial env sequences sampled from three long-term infected progressors (LTPs) and five short-term infected progressors (STPs) over several years (17, 34).

Subjects and samples.

We analyzed partial nucleotide sequences of the HIV-1 env gene (C2-V5 region) previously obtained in a longitudinal study (17, 34). We analyzed 922 sequences derived from 94 samples from eight subjects taken on average every 8 months over 6 to 11 years. Each sample contained an average of 9.8 (range, 6 to 17) sequences. Subjects P2, P8, and P9 were classified as LTPs on the basis of their continued survival. Subjects P1, P3, P5, P6, and P7 were classified as STPs on the basis of their deaths 7.1 to 9.1 years after seroconversion. Reverse transcriptase inhibitors were prescribed to all members of LTP and to four members of STP. Only subject P8 received a protease inhibitor (saquinavir) at the last sample point. LTPs are presently receiving highly active antiretroviral therapy.

Nucleotide sequence accession numbers and alignment.

All sample sequences were derived from GenBank (accession numbers AF137629 to AF137715, AF137766 to AF138163, AF138166 to AF138263, and AF138305 to AF138643). Sequences were aligned collectively (38) and then manually adjusted within subjects. Gaps were removed in a balanced manner to preserve codon alignment (32). Both entire and gap-balanced sequences were aligned against reference sequences (HIV-1 type B accession numbers K03455, M17451, U63632, and U21135 from the Los Alamos database [19]). The sample sequences correspond to amino acid positions 342 to 594 in the reference sequences and to amino acid positions 267 to 471 in the reference epitope sequences (see below). Supplementary material, including the sequence alignments, is available at http://www.cebl.auckland.ac.nz/ross.

Phylogenetic reconstruction and parameter estimation.

For each sample a neighbor-joining (NJ) tree was constructed using a general time reversible model of substitution and site variation in substitution rates (Γ-distributed with four bins) (36, 37). For each sample, the NJ tree was fixed, and the parameters of both the neutral (M1) and selection (M2) models of codon substitution (27) were estimated using the PAML software (48). Model M1 assumes two categories of codon sites in a gene: sites at which nonsynonymous substitutions are fatally deleterious (dN/dS ratio ω0 = 0), occurring with frequency p0, and sites at which nonsynonymous substitutions are neutral to selection (dN/dS ratio ω1 = 1) occurring with a frequency p1 = (1 − p0). Model M2 extends model M1 by including a third category of positively selected codons which have a higher relative rate of nonsynonymous than of synonymous substitutions (ω2 > 1) and occur with frequency p2 = (1 − p0p1). All sites were classified as experiencing purifying (ω = 0), neutral (ω = 1), or positive (ω > 1) selection by using an empirical Bayesian approach. The neutral and selection models were compared by the likelihood ratio test, in which twice the difference between the log-likelihoods of M2 and M1 were distributed as a χ2 distribution with df = 2 (13, 27).

Model M2, which includes positive selection, was statistically more likely (P < 0.05) than model M1, allowing only deleterious or selectively neutral substitutions, in 55 of the 94 samples. Positive selection was found at sites throughout the C2-V5 region. Although there was no significant difference between LTPs and STPs in the proportion of samples in which selection was detected, the maximum likelihood estimate of the proportion of sites under positive selection (p2) was higher in LTPs than in STPs (Table (Table1).1). This is most strikingly illustrated in Fig. Fig.1.1. As one moves from P6, who had the shortest longevity, leftward to P9, who is among the longest survivors, we see a clear increase in the proportion of selected sites and in the breadth of their distribution along the sequence. The LTP subjects have broadly distributed sites of selection, whereas the STP subjects have isolated instances or regions where selection was observed. Subject P3 is intermediate in having a frequency and pattern of selection similar to those in LTP, but this subject experienced disease progression similar to those with the lower frequency.

FIG. 1.
The location of sites classified as experiencing positive selection in the C2-V5 region of the HIV-1 env gene. Individual sites are color coded when ω is >1 in at least one sample. The proportion of sites with ω > 1 is ...
Evolutionary rate and positive selection in the C2-V5 region of the HIV-1 env gene

Rate of substitution.

For each subject a maximum likelihood estimate of the rate of substitution (μ) over all samples was obtained by using the single rate with dated tips (SRDT) model of the TipDate software (31) and the parameters and tree previously estimated. The difference in the proportion of positively selected sites between LTPs and STPs is not attributable to a higher rate of substitution in LTP; the rate of substitution did not differ significantly between LTPs and STPs (Table (Table1)1) (Mann-Whitney U test, P > 0.05), averaging 0.71% year−1 (95% confidence interval, 0.58 to 0.84% year−1).

Cross-validation test.

The difference in the proportion of positively selected sites between LTPs and STPs (Table (Table1)1) suggests that this proportion could be used as a prognostic indicator of disease duration. To investigate its predictive power we performed a cross-validation test, using each sample to classify the subject from which it was obtained as either LTP or STP. First, all samples of a subject were excluded from the data, and the mean proportions of positively selected sites per sample were calculated for LTPs and STPs by using samples from the remaining subjects. Then, the proportion of positively selected sites for each sample from the excluded subject was compared to the group means. A sample was designated as LTP or STP depending on which group mean was closer to the sample proportion. Once this was done for all samples for a subject, the samples were replaced, and the process was repeated for the next subject. To correct for time-related effects, samples were used only from the period 0 to 73 months, corresponding to the sample period for the shortest-surviving subject. This test correctly assigned 69% of the samples to LTPs or STPs (Fisher exact test; P < 0.008), thus providing strong evidence that the value of the proportion of selected sites is a prognostic marker of a subject's longevity.

Persistence of selection.

Figure Figure11 also suggests that selection acts at the same sites over longer periods of time in LTPs than in STPs. To measure this persistence of positively selected sites across samples, we plotted an index of recurring positive selection, estimated by calculating the proportion of selected sites common to two samples against the time interval between the samples (Fig. (Fig.2).2). We used Jaccard's index, J = 2SAB/(SA + SB), where SAB is the number of sites selected in both samples A and B, and SA (or SB) is the number of selected sites in sample A (or B). All pair-wise comparisons were made among the samples from each individual subject. A steep decline in the plot indicates episodic, nonrecurring selection, whereas a shallow decline signals persistent, recurring selection.

FIG. 2.
Persistence of positive selection in the two groups of subjects. The proportion of sites under positive selection in both of two samples, in all pair-wise comparisons, is plotted against the time interval between samples. The results for each subject ...

The LTP subjects all have a relatively shallow decline in the recurrence of selected sites, indicating that the same sites are under positive selection for longer periods of time. In contrast, most of the STP subjects have a relatively steep decline in recurrence, and thus a consequently shorter persistence time. Subject P3, while classified as STP, has a persistence similar to that of the LTP subjects. Nevertheless, there was a significant difference between the groups in the slopes of the lines of best fit (Mann-Whitney U test; P = 0.03). Restricting the analysis to just the period of 0 to 73 months, corresponding to the sample period for the shortest-surviving subject, changes the ranking of subject P3 and makes the results not statistically significant. Overall, this analysis indicates that selection is less episodic and occurs over broader time periods in LTPs relative to STPs.

Epitope distributions and selection.

To test the hypothesis that positive selection occurs in response to immunological challenge, we compared temporal changes in the frequency of positive selection at a site with the number of epitopes reported at that site. For the LTP and STP groups, we calculated at each site the change in the proportion of samples classified as being positively selected (Δsi) between the early (0 to 36 months) and late (37 to 73 months) periods, corresponding to the first and second half of the sample period for the shortest-surviving subject. Frequency distributions of published Ab, CTL, and HTL epitopes (18) were constructed for the gp120 protein by counting the number of each type of epitope at each position in the expressed sequence. Since we have not accounted for the HLA specificity of different subjects, this distribution provides a very crude indicator, but one of exploratory value, of immune recognition, and hence selection pressure, at each codon. It gives a first approximation of the probability distribution that any particular site will be recognized by the immune system, as viewed from a population rather than an individual patient perspective.

The propensity to increased selection from the early to late period was greater in LTPs than STPs. The values of Δsi were highly correlated between LTPs and STPs (Spearman rank correlation rS = 0.41; P < 0.0001), indicating that these two groups were responding to similar challenges, but the slope (0.29) of a linear regression (STP versus LTP) of these changes indicates that STPs responded much less intensively than did LTPs.

For both Abs and CTLs, we found no correlation between Δsi and the number of epitopes, nor did we find any association between the presence of an epitope and the presence of a positive value of Δsi (2 by 2 contingency χ2). For HTLs, Δsi was positively correlated with the number of epitopes (rS = 0.2; P ≈ 0.1, Bonferroni corrected), especially in the first half of the sequence (rS = 0.42; P < 0.001, Bonferroni corrected) in LTPs, but there was no equivalent correlation in STPs. Too few sites lacked an HTL epitope to permit a contingency test.

Positive selected sites were distributed nonuniformly. We found strong positive selection in the V3 region, where Ab, CTL, and HTL epitopes are common and where other investigators have found specific sites to be under selection both within and among patients (27, 46, 47), but at only three of the seven sites identified by Yamaguchi and Gojobori (46, 47). Selection was found at sites relating to cytotropism (3), Ab binding (44), and the syncytium-inducing phenotype (3). We also identified diversifying selection in regions having few epitopes, at six of the seven sites in the C3 region and three of the six sites in the C4 region where Yamaguchi and Gojobori (46, 47) had previously detected it.

Our results corroborate previous evidence for positive selection in the env gene (2, 12, 27, 46, 47, 49) and parallel that for the nef gene (50). Although we have not accounted for HLA type, the co-occurrence of selected sites with known points of immunogenic recognition suggests that selection to escape from immunogenic attack drives diversity in this gene (24). The association that we have shown between the distribution of HTL epitopes and the frequency of selection supports the hypothesis that HTLs are significant agents in the maintenance of CTL response (9, 15, 16, 43) and hold potential as targets for antiretroviral vaccines (41). The lack of a similar correlation for CTL epitopes may result from HLA allele-specific positive selection, as found for HIV-1 reverse transcriptase sequences (25).

HIV-1 has an error-prone reverse transcriptase (23) that provides raw viral genetic material for immune-mediated selection. Variants that are able to escape immune detection have the potential to infect susceptible target cells and reproduce. Mathematical models developed by Nowak and colleagues (28-30) predict a negative correlation between viral load and viral genetic diversity when there is variation among patients in their immunological responsiveness to variable epitopes. When the rate of disease progression correlates with viral load, a weak immune response by a patient will lead to rapid disease progression without significant development of viral genetic diversity. Conversely, a strong immune response will select for additional viral diversity. The models (42) also predict that long-lived memory CTL precursors will mount a broad attack on antigenic variants and so prevent the establishment of escape mutations. Interestingly, our analysis shows that, in LTPs, more extensive positive selection occurs at sites associated with HTL epitopes than at those associated with CTL or Ab recognition.

Our phylogenetic method assumes the absence of recombination which, if undetected, would inflate estimates of selection. However, we expect such bias to be uniform across patients and estimators. If the difference in the estimates of positive selection between the LTP and STP groups is attributable to a difference in recombination rate, or opportunities for recombination, then a similar difference should be observed in the substitution rate. Since such a difference was not observed, we can conclude that our observations are not seriously compromised by undetected recombination.

LTPs had virus sequences under positive selection at more sites over longer periods of time than did STPs, corroborating earlier indications of a relationship between patient survival and selection pressure acting on the pathogen (11, 21, 45). Although our samples were small, our findings are consistent with the hypothesis that individuals who mount a broad and persistent immune defense against HIV have a greater probability of surviving longer with HIV infection. In contrast, individuals who mount a limited and shifting immunologic response to HIV have fewer and less persistent positively selected sites and progress more rapidly to AIDS. Our results suggest that anti-HIV vaccines which stimulate broad immune responses by encoding the maximum number of immunogenic epitopes may be more effective at controlling HIV-1 and lengthening the asymptomatic period. The development of vaccines containing recombinant forms of the envelope protein, gp120, whether in native or deglycosylated form, and of polyepitope vaccines containing concatenated epitope sequences should strive to present a broad range of epitopes (16). Finally, our results indicate that the estimated proportion of positively selected sites is a statistically significant predictor of the expected duration of disease and deserves further investigation as a diagnostic tool.


We thank Alexei Drummond, Russell Gray, Mark Jensen, John Mittler, Jim Mullins, Martin Nowak, David Nickle, and Daniel Shriner for comments. Matthew Goode provided programming assistance.

This work was supported by NIH grants.


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