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. 2013;11(4):e1001523.
doi: 10.1371/journal.pbio.1001523. Epub 2013 Apr 2.

Immune Activation Promotes Evolutionary Conservation of T-cell Epitopes in HIV-1

Free PMC article

Immune Activation Promotes Evolutionary Conservation of T-cell Epitopes in HIV-1

Rafael Sanjuán et al. PLoS Biol. .
Free PMC article


The immune system should constitute a strong selective pressure promoting viral genetic diversity and evolution. However, HIV shows lower sequence variability at T-cell epitopes than elsewhere in the genome, in contrast with other human RNA viruses. Here, we propose that epitope conservation is a consequence of the particular interactions established between HIV and the immune system. On one hand, epitope recognition triggers an anti-HIV response mediated by cytotoxic T-lymphocytes (CTLs), but on the other hand, activation of CD4(+) helper T lymphocytes (TH cells) promotes HIV replication. Mathematical modeling of these opposite selective forces revealed that selection at the intrapatient level can promote either T-cell epitope conservation or escape. We predict greater conservation for epitopes contributing significantly to total immune activation levels (immunodominance), and when TH cell infection is concomitant to epitope recognition (trans-infection). We suggest that HIV-driven immune activation in the lymph nodes during the chronic stage of the disease may offer a favorable scenario for epitope conservation. Our results also support the view that some pathogens draw benefits from the immune response and suggest that vaccination strategies based on conserved TH epitopes may be counterproductive.

Conflict of interest statement

The authors have declared that no competing interests exist.


Figure 1
Figure 1. Association between amino acid variability and T-cell epitopes in subtype B HIV-1 (A, B) and HCV 1a (C).
Mean ± SEM entropy (H) is shown for sites not mapping to any T-cell epitopes (white) and for those mapping to TH epitopes (blue), CTL epitopes (red), or both (purple). In (A) and (C) amino acid entropy was quantified at the host population level (100 sequences from different patients), whereas in (B) it was quantified at the intrapatient level (average from 100 patients containing ≥10 sequences each). For HIV, only Gag, Pol, Env, and Nef are shown because they contain the vast majority of T-cell epitopes. No significant differences in variability associated with T-cell epitopes were found in other genes. Regions with overlapping reading frames were excluded from the analysis. For HCV, only genes with at least five sites in each category were plotted. Notice that the y-axis is broken to accommodate the extremely variable epitopes in E2.
Figure 2
Figure 2. Association between amino acid variability and T-cell immunogenicity in HIV-1 subtype C using data from a high-throughput study , controlling for epitope detection bias (see text).
The average entropy (H) is shown for peptides that produced at least one positive immune reaction (red) versus those showing no reactivity (blue). Only genes with at least five peptides in each category are shown. Genome regions with overlapping reading frames were excluded. Dotted lines indicate ANOVA-estimated marginal means. ** 0.001<p<0.01; *** p<0.001. n.s., not significant.
Figure 3
Figure 3. Schematic representation of the HIV immune activation model and the control model.
(A) Model of the cellular immune response against HIV. In the absence of immune activation, pools of resting TH (CD4) cells, CTLs (CD8), and pAPCs divide at rates, ρ4, ρ8, ρD and die at rates formula image, formula image, and formula image, reaching homeostatic concentrations formula image, formula image, and formula image, respectively. Activated TH cells become infected through contact with free virions at a rate constant σ, whereas resting cells are assumed to be non-susceptible to the virus. TH cells are activated at a rate constant a4 after contacting a pAPC with an HIV epitope or by other antigens at rate constant b (background activation). TH cells establishing synapses with pAPCs have a probability d of being concomitantly infected with the same viral type. Infected cells release virions at a rate constant α and die at a rate constant formula image. CTL pre-activation occurs after contacting infected cells (a8) or pAPCs (a8D). A co-stimulatory signal from activated TH cells is necessary for completing CTL activation (a8′). Infected cells are lysed by CTLs at a rate constant k. Death rate constants for activated TH cells formula image, CTLs formula image, and pAPCs formula image and virion inactivation rates (ΓV) are not shown for simplicity. The full list of variables and parameters is available in Appendix S1, which also provides references to empirical work justifying the parameter values used (see also main text). A fraction μ of the virions released in each cell infection become escape mutants. Avoidance of CTL activation or CTL-mediated killing leads to CTL escape (red bars), whereas avoidance of TH cell activation leads to TH escape (blue bars). The model allows full T-cell (purple), TH-only (blue), and CTL-only (red) escape mutants. (B) Control model in which the virus targets a nonimmune cell type C (e.g., hepatocytes, epithelial cells, etc.) instead of TH cells. Two key differences with the HIV model are that viral replication is not dependent upon immune activation and that transinfection does not take place. Variables, parameters, and equations for this model are also shown in Appendix S1.
Figure 4
Figure 4. Simulated viral load versus time for combinations of parameter values producing biologically meaningful peak loads, viral loads at set point (copies/mL), and escape rates (days−1).
In top panels, wild-type and T-cell (CTL/TH) escape variants are shown in black and purple, respectively. Solid lines refer to the HIV model, whereas dashed lines correspond to the control model. HIV-specific activation rate constants (a4, a8, a8D, a8′), the background activation rate constant (b), and transinfection probability (d) were as indicated below, whereas all other parameters values were set as indicated in the text. (A) a4 = a8 = a8D = a8′ = 0.1, b = 0.001, d = 0.03; (B) a4 = a8 = a8D = a8′ = 0.1, b = 0.001, and d = 0.037; (C) a4 = a8 = a8D = a8′ = 0.15, b = 0.001, d = 0.03, and the infection was started with a T-cell escape mutant. (D, E, and F) Changes in the intrapatient frequency of the escape mutant for the HIV (solid) and control (dashed) models obtained in (A), (B), and (C), respectively. (D) The calculated rate of escape, as defined in previous work , was 0.012 day−1 in the HIV model and 0.091 day−1 in the control model. (E) The escape mutant reached a stationary frequency of 0.324 in the HIV model and became fixed in the control model (fixation rate: 0.091 day−1). (F) The escape mutant was selected against and reverted to the wild-type in the HIV case (reversion rate: 0.012 day−1), whereas it remained fixed in the control model.
Figure 5
Figure 5. Immune escape dependence on the HIV-driven T-cell activation rate constant (a4), trans-infection probability (d), and background activation (b).
Shaded areas indicate parameter combinations for which T-cell escape mutants became dominant (frequency >0.5) after t = 1000 iterations (days). T-cell activation rate constants were set equal to one another (a8 = a8D = a8′ = a4), and the rest of parameter values were as indicated in the text.

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R.S. was financially supported by grant BFU2011-25271 and the Ramón y Cajal Research Program from the Spanish MICINN (, and Starting Grant 2011-281191 from the European Research Council (ERC; M.N. was supported by a Juan de la Cierva postdoctoral contract from MICINN. J.B.P. was supported by a pre-doctoral fellowship funded by ERC. J.A. was supported by the Red Investigación en Sida (RIS; and grants RD06/0006/0037 and PI08/0752 from the Instituto de Salud Carlos III ( The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.