Skip Navigation

Specific Enfuvirtide-Associated Mutational Pathways in HIV-1 Gp41 Are Significantly Correlated With an Increase in CD4+ Cell Count, Despite Virological Failure

  1. Svicher Valentina1,a,
  2. Stefano Aquaro1,3,a,
  3. Roberta D'Arrigo2,
  4. Anna Artese4,
  5. Salvatore Dimonte1,
  6. Stefano Alcaro4,
  7. Maria Mercedes Santoro1,
  8. Perri Giovanni Di5,
  9. Caputo Sergio Lo6,
  10. Rita Bellagamba2,
  11. Mauro Zaccarelli2,
  12. Ubaldo Visco-Comandini2,
  13. Andrea Antinori2,b,
  14. Pasquale Narciso2 and
  15. Francesca Ceccherini-Silberstein1
  1. 1 Department of Experimental Medicine, University of “Tor Vergata” Rome, Florence, Italy
  2. 2 National Institute of Infectious Diseases (INMI) “L. Spallanzani”, Rome
  3. 3 Department of Pharmaco-Biology, University of Calabria, Rende (CS), Florence, Italy
  4. 4 University of Catanzaro, Florence, Italy
  5. 5 Clinic of Infectious Diseases, University of Turin, Hospital “Amedeo di Savoia”, Turin
  6. 6 SM Annunziata Hospital, Florence, Italy
  1. Reprints or correspondence: Dr. Valentina Svicher, Department of Experimental Medicine, University of Rome “Tor Vergata”, Via Montpellier 1, 00133 Rome, Italy (valentina.svicher{at}uniroma2.it).

  1. Presented in part: 14th Conference on Retroviruses and Opportunistic Infections, Los Angeles, California, 25–28 February, 2007 (abstract 621); XX Conference on Antiviral Research, Palm Spring, California, 29 April 29–3 May, 2007 (abstract 5); XVI International HIV Drug Resistance Workshop: Basic Principles and Clinical Implications, Barbados, 13–17 June, 2007 (abstract 104).

  1. ↵a V. S. and S. A. contributed equally to the work.

 
Next Section

Abstract

Background. Human immunodeficiency virus type 1 (HIV-1) gp41 is a crucial determinant for HIV-1 pathogenicity. We investigated the correlation of enfuvirtide (ENF)-associated gp41 mutational clusters with viroimmunological parameters, as well as the potential underlying mechanisms.

Methods. A total of 172 gp41 sequences and clinical follow-up data from 73 ENF-treated patients were analyzed monthly, from baseline to week 48.

Results. There were 7 novel gp41 mutations positively associated with ENF treatment and correlated with classic ENF mutations. The ENF-associated clusters V38A + N140I and V38A + T18A significantly correlated with an increase in CD4 cell count at week 48 ( an increase from baseline of 112 and 209 cells/μL, respectively), whereas Q40H + L45M + T268A significantly correlated with a decrease in CD4 cell count (-53 cells/μL), without a change in the level of viremia. Residues 38 and 18 are located complementarily to each other in the Rev-responsive element, whereas analysis of molecular dynamics showed that the copresence of V38A + N140I abolishes the interaction between residue 38 and 145 important for stabilization of the 6-helix bundle. In contrast, T268A localizes in the gp41 calmodulin-binding domain responsible for gp41-induced CD4+ T lymphocyte apoptosis.

Conclusion. Specific gp41 mutational clusters associated with ENF treatment significantly correlate with increases in CD4+ cell count. Structural analysis suggests that this immunological gain is associated with mechanisms that act at both the protein level and the RNA level (even under conditions of virological failure). This result may help in the selection of patients who can benefit most from ENF treatment and represents a driving force for the design of the next generation of entry inhibitors.

The HIV-1 envelope glycoprotein gp41 is necessary to mediate the fusion between the virus and the host cell membranes [1, 2]. It consists of several domains, including an N-terminal fusion peptide, N- and C-terminal heptad repeat regions (referred to as HR1 and HR2), a transmembrane domain, and a cytoplasmic tail. The gp41 ectodomain also contains consensus sites (asparagine-X-serine/threonine) for the incorporation of N-linked carbohydrates; their presence acts to decrease the portion of gp41 surface that serves as an immunogenic target.

Enfuvirtide (marketed as T-20 or Fuzeon) is the first fusion inhibitor approved for clinical practice. It interacts with HR1, preventing the formation of the 6-helix bundle, and consequently, the fusion process. To date, 18 mutations at 8 positions in the “enfuvirtide (ENF) target region” that encompass amino acids 36–45 of HR1 have been associated with ENF-resistance [3–8].

There is increasing evidence that additional mutations outside the ENF target region are involved in ENF-resistance, and therefore lead to virological failure in patients who receive ENF therapy. For instance, recent studies have proposed that some additional mutations in HR2 contribute to ENF resistance, but their exact role still remains unclear [9–11].

Another relevant point that has not been still elucidated is the impact of ENF-resistance mutations on HIV-1 fitness and/or cytopathic effect. HIV-1 gp41 has been demonstrated to be a crucial determinant of HIV-1 pathogenicity, given its involvement in mechanisms that trigger the apoptosis of CD4+ T cells [12–17]. Interestingly, some gp41 mutations that are able to impair gp41 fusogenicity have been demonstrated to reduce the ability of HIV-1 to induce apoptosis in CD4+ T cells without interfering with viral replication capacity [17, 18]. In this context, it is conceivable that ENF pressure may be associated with mutations that modulate the cytopathic effects of HIV-1 by mechanisms that are not necessarily related to viral replication capacity. On the basis of these assumptions, we analyzed the full-length gp41 sequences and viroimmunological parameters with the aim of clarifying the gp41 mutational pathways associated with ENF treatment and their correlation with viroimmunological outcome.

Previous SectionNext Section

Methods

Study population. The study included 73 nonselected, highly treatment-experienced patients infected with HIV-1 B-subtype who had a history of multiple virological failures, followed up in 3 major centers in Italy. To make the data more clear and readable from the genetic point of view, patients who carried HIV-1 non-B subtypes have been excluded from this analysis. For most patients, ENF was added as a single active drug to the last failing regimen. For 20 patients, minor regimen modifications (i.e., changes limited to a single nucleoside reverse transcriptase inhibitor [NRTI] or to a single protease inhibitor [PI] in the context of extensive multidrug resistance) were made at the time that ENF therapy was started. Of 73 patients, 62 (85.3%) received ENF together with 1–3 NRTIs and at least 1 PI. Only 11 patients received nonnucleoside reverse transcriptase inhibitors (NNRTIs) with ENF due to the high prevalence at baseline of mutations that conferred full resistance to this class of drugs. For each patient, the level of viremia and CD4+ cell count were monitored every month during ENF treatment. A total of 172 plasma samples were obtained from 73 patients at the time of virological failure and at different time points later during treatment with ENF. Baseline samples from 49 (67.1%) of 73 patients were also available for gp41 sequencing. As a control, 38 other patients infected with HIV-1 who had not received treatment with ENF were included in the analysis of gp41 mutations.

Gp41 sequencing. The sequencing of the entire gp41 was performed on plasma samples, as described elsewhere [19]. In brief, RNA was extracted, retrotranscribed, and amplified by use of 2 different sequence-specific primers. Gp41-amplified products were full-length sequenced in sense and antisense orientations by use of 8 different overlapping sequencespecific primers for an automated sequencer (ABI 3100; Applied Biosystems). Sequences with a mixture of wild-type and mutant residues at single positions were considered to have the mutant(s) at that position. Nucleotide sequences were submitted to Genbank (accession number: EU251192–EU251378 and EU281662–EU281733). Subtypes were assessed by the construction of phylogenetic trees generated with the Kimura 2-parameter model. The statistical robustness within each phylogenetic tree was confirmed with a bootstrap analysis using 1000 replicates.

Statistical analysis of mutation prevalence. To assess the association of gp41 mutations with ENF treatment, we calculated the frequency of all mutations in the 345 gp41 residues in isolates from 87 ENF-naive patients (11 were completely naive to antiretroviral drugs and 76 had been treated with highly active antiretroviral therapy; 49 were later treated with ENF) and in isolates from 73 patients who experienced virological failure while receiving ENF (virological failure was defined as viremia of >400 copies/mL in 2 consecutive tests). Fisher exact tests were used to determine whether the differences in frequency between the 2 groups of patients were statistically significant. For patients who had more than one gp41 sequence available during ENF treatment, the sequence obtained most recently during the treatment period was analyzed.

To assess the association of specific ENF-associated mutational clusters with changes in the level of viremia and CD4+ cell count, we compared the mean change in the level of viremia and CD4+ cell count from baseline to week 48 for the subset of patients who had viral isolates with a specific ENF-associated mutational cluster and the subset of patients who had viral isolates without such a cluster. Mann-Whitney U tests were used to assess statistically significant differences. All statistical tests were corrected for multiple hypothesis testing by using Benjamini-Hochberg method at a false discovery rate (FDR) of 0.05 [20].

Statistical analysis of mutation covariation. For the 73 ENF-treated patients, we analyzed patterns of interactions among selected mutations associated with ENF treatment, including novel mutations. The details of this explorative data analysis procedure have been described elsewhere [21, 22]. In brief, for each pair of mutations and corresponding wild-type residues, the Fisher exact test was performed to assess whether co-occurrence of the mutated residues differed significantly from what would be expected under an independence assumption. The Benjamini-Hochberg method was used to correct for multiple testing at an FDR of 0.05 [20]. Samples having a mixture of 2 or more mutations at a given pair of positions were ignored in calculating the covariation, due to the impossibility of identifying whether these mutations were located in the same viral genome. To identify higher-order interactions of mutations, we transformed the pairwise φ correlation coefficients into dissimilarity values. Based on these pairwise dissimilarity values, a dendrogram was computed by hierarchical clustering. To assess the stability of the resulting dendrogram, confidence values for all subtrees in the dendrogram were computed by 500 replicates of the clustering procedure on sequence sets bootstrapped from the original 73 sequences.

Genotypic sensitivity. We used resistance testing information to calculate a genotypic sensitivity score (GSS) [23]. The GSS was calculated by using the Stanford HIV Drug Resistance Database sequence analysis program [24].

Structural analysis. The x-ray crystallographic coordinates of HIV-1 gp41 deposited in the Protein Data Bank [25] with code 1IF3 were used for the structural analysis. From this model, the mutants were generated by single-residue replacement in all chains. Energy-minimized starting structures were subjected to molecular dynamic simulations (MDSs) under the following conditions: (1) 1.5 picoseconds of equilibration time at 300K; (2) 1000 picoseconds of simulation time at 300K; (3) time-step, 1.5 femtoseconds; (4) 200 conformations stored; (5) AMBER* force field [26] and (6) Gibbs-Born surface area water implicit model, to take into account the solvation effect. All simulations were performed by MacroModel (version 7.2; Schrödinger) [27]. To evaluate the most important interactions at interface of the HR1 and HR2 subdomains, the programs LigPlot and DimPlot (open-source software) [28] were used to select the most-involved gp41 residues. All molecular dynamics conformations were analyzed by adopting a distance based descriptor that computed the Boltzmann probability at 300K. Six dummy atoms that averaged all the atoms of the residues 38 and 140 for each chain were generated, and their distances with respect to residue N145 [29–31] were measured. All three-dimensional figures were created using the PyMOL Molecular Graphics System (PyMOL).

Previous SectionNext Section

Results

Patient characteristics. Table 1 summarizes the demographic and clinical characteristics of the 73 ENF-treated patients. All patients were heavily treatment-experienced, with resistance to multiple NRTIs, NNRTIs, and PIs. They were experiencing virological failure in response to their last antiretroviral regimen, with the level of viremia stable at about 5 log10 copies/mL and CD4+ cell count in progressive decline during the last 12 weeks prior ENF therapy. The addition of ENF to the antiretroviral regimen induced a significant decrease in the level of viremia at week 8 to 4.0 log10 copies/mL (interquartile range [IQR], 2.7–5.0 copies/mL; P = .007), as well as a significant increase in CD4+ cell count from 48 cells/μL (IQR, 34–141 cells/μL) at baseline to 138 cells/μL (IQR, 87–206 cells/μL) (P = .008). Viremia reached levels of <50 copies/mL in 4 patients (5.3%). Although the level of viremia rapidly rebounded to 4.8 log10 copies/mL (IQR, 3.7–5.1 copies/mL) at week 12 and remained stable at this value up to week 48, CD4+ cell count continued to increase up to a median value of 166 cells/μL (IQR, 61–257 cells/μL) at week 48, with a 3.5-fold increase, compared with baseline values (P = .008).

Table 1.
View larger version:
Table 1.

Demographic and clinical characteristics of 73 patients who were treated with enfuvirtide (ENF).

Gp41 mutations in patients who experienced virological failure during ENF therapy. The classic ENF-resistance mutations were observed in 68 (93.1%) of 73 ENF-treated patients who experienced virological failure. Among them, the frequency of G36D/V, V38A/E, Q39H, Q40H, N42T, N43D, L44M, and L45M showed a significant increase in isolates recovered from ENF-treated patients, compared with isolates recovered from ENF-naive patients (P = .05 to <.001) (figure 1A). Beyond the classic ENF-resistance mutations, we identified 7 other gp41 mutations that were significantly associated with ENF treatment (P < .05) (figure 1B). In particular, T18A/P, N126K, and D239H occurred at a frequency of 2.2%, 1.1%, and 3.4%, respectively, in isolates from ENF-naive patients; they increased to frequencies of 12.3%, 16.4%, and 15.1%, respectively, in isolates from ENF-treated patients (P = .01 to .001). The other novel gp41 mutations (S129D, N140I, and T268A) were already present in isolates from ENF-naive patients at frequencies of 13.8%, 9.2%, 34.5%, respectively, which increased after ENF treatment to 28.8%, 21.9%, 52.0% (P = .02, in all 3 cases) (figure 1B). No other gp41 mutations showed a statistically significant increase in frequency among ENF-treated patients.

Associations among gp41 mutations. Some novel gp41 mutations were positively correlated into pairs with the classic ENF-resistance mutations (P < .05) (table 2). In particular, the most frequently selected ENF-resistance mutation, V38A, was strongly correlated with the novel mutations T18A (φ, 0.41) and N140I (φ, 0.16). T18A never occurred without the presence of V38A. V38A was negatively correlated with the classic ENF resistance mutations N43D (φ, -0.25), Q40H (φ, -0.23), and L45M (φ, -0.22). In contrast, the classic ENF-resistance mutations Q40H and L45M were strongly correlated with each other (φ, 0.93) and with the novel D239H mutation (φ, 0.22), whereas G36V was significantly associated with the novel mutation N126K (φ, 0.36).

Table 2.
View larger version:
Table 2.

Gp41 mutations associated with classic enfuvirtide (ENF)-resistance mutations.

Clusters of correlated mutations. The topology of the dendrogram (figure 2) suggests the existence of at least 5 distinct clusters of mutations that involve both novel and classic ENF-resistance mutations. In particular, a strong cluster was formed by the classic ENF-resistance mutations Q40H and L45M to which the novel mutations D239H and T268A were linked as well. In contrast, V38A and G36V clustered with the novel mutations T18A + N140I and N126K, respectively (figure 2).

Table 3.
View larger version:
Table 3.

Percentage of occurrence of Van der Waals interaction between residues 38 and 145.

Figure 1.
View larger version:
Figure 1.

Frequency of the classic (A) and novel (B) gp41 mutations significantly associated with virological failure in patients who received enfuvirtide (ENF). The frequency of mutations was calculated in isolates from 87 ENF-naive patients and 73 patients who experienced virological failure to ENF. Statistically significant differences were assessed by Fisher exact tests. P values were significant at a false discovery rate of .05 after correction for multiple comparison. *, P < .05; **, P < .01; ***, P < .001.

Figure 2.
View larger version:
Figure 2.

Dendrogram obtained from average linkage hierarchical agglomerative clustering that shows clusters of known enfuvirtide-resistance mutations and novel mutations. The length of branches reflects the distances between mutations in the original distance matrix. Bootstrap values, indicating the significance of clusters, are reported in the boxes. Bold type indicates novel mutations.

Association of ENF-resistance mutations with viroimmunological outcome among ENF-treated patients. By investigating the correlation of ENF-resistance mutations with viroimmunological parameters, we found that the viroimmunological outcome for ENF-treated patients varied remarkably according to which gp41 mutational pathways occurred during ENF treatment. We observed that the presence of mutations V38A + T18A or V38A + N140I was significantly associated with a sharp and sustained increase of CD4+ cell count, despite the maintenance of virological failure. Specifically, the mean change in CD4+ cell count from baseline to week 48 in the presence of V38A + T18A or V38A + N140I was 112 cells/μL and 209 cells/μL, respectively (figure 3A). These changes were 6.7-fold and 20.7-fold higher than those observed in the absence of such mutations (P = .01 and P = .03, respectively), and 1.5-fold and 4.5-fold higher than those observed in the presence of V38A alone (P = .02 and P = .04, respectively) (figure 3A). V38A + T18A or V38A + N140I were not associated with any significant changes in the level of viremia from baseline to week 48 (0.27 and -0.15 log10 copies/mL, in the presence of V38A + T18A and V38A + N140I, respectively), or when compared with viral changes observed in the absence of these mutations (-0.30 log10 copies/mL) or in the presence of V38A alone (-0.23 log10 copies/mL) (P > .8). Similarly, the presence of N126K was associated with a mean change of CD4+ cell count from baseline to week 48 that was 5-fold higher than that observed in the absence of this mutation (154 vs. -7.5 cells/μL; P = .012), without any significant effect on the level of viremia (-0.11 log10 copies/mL in the presence of N126K vs. -0.50 log10 copies/mL in the absence of N126K; P = .8) (figure 3B).

Figure 3.
View larger version:
Figure 3.

Mean change in CD4+ cell count from baseline to weeks 12, 24, and 48, as observed in the presence of different gp41 mutational pathways. A, P values in bold type indicate a statistically significant difference in the mean change in CD4+ cell count at week 48 between patients with V38A + N140I or V38A + T18A and patients without mutations at positions 18, 38, and 140. P values in italics indicate a statistically significant difference in the mean change of CD4+ cell count at week 48 between patients with V38A + N140I or V38A + T18A and patients with V38A alone. Mean changes in the level of viremia were not statistically significant (P > .8). B, P value indicates a statistically significant difference in the mean change in CD4+ cell count at week 48 between patients with N126K and patients without mutations at position 126. Mean changes in the level of viremia were not statistically significant (P = .9). C, P value indicates a statistically significant difference in the mean change in CD4+ cell count at week 48 between patients with Q40H + L45M + T268A and patients without mutations at positions 40, 45, and 268. The mean change in CD4+ cell count in presence of Q40H + L45M (without T268A) was similar to that observed without mutations at position 40, 45, and 268, and it was not reported because the pair Q40H + L45M (without T268A) was present in only 2 patients. Mean changes in the level of viremia were not statistically significant (P = .9). All P values remained significant after correction for multiple hypothesis testing [20], with the exception of the P values reported in italics. WT, wild type.

Such increases in CD4+ cell count are not related to residual efficacy of the drugs administered together with ENF or to an accumulation of mutations in the protease (PR) and reverse transcriptase (RT) genes in HIV-1. Indeed, the median GSS were very similar (ranging from a median value of 0.35 to 0.38), and the median increase in the number of PR and RT mutations after 48 weeks was 0 (IQR, 0–1) and 1 (IQR, 0–1), respectively, in patients with the different patterns of mutations.

In contrast, the other ENF-associated cluster—Q40H + L45M + T 268 A—was significantly correlated with a decrease in CD4+ cell count at week 48 (-53 cells/μL in the presence of this cluster vs. 94 cells/μL in the absence of this cluster; P = .04) (figure 3C), but (again) without significant changes in the level of viremia (-0.22 log10 copies/mL vs. -0.63 log10 copies/mL; P = .9).

MDS. The stability of the 6-helix bundle requires hydrophobic interactions between specific HR1 and HR2 residues in each hairpin [29–31] (figure 4A). One of them is just residue 38, which establishes Van der Waals interaction with residue 145 (figure 4A). By performing MDS, we investigated the impact of mutations at position 38 and 140 on the formation of this important interaction, by monitoring for 1 nanosecond, every 5 picoseconds (for a total of 201 observations), the distance and the frequency of occurrence of the Van der Waals interaction between residues 38 and 145 (figure 4B). Our MDS showed that in the presence of V38A + N140I, the distance between the residues 38A and 145N was increased in all 3 hairpins (>6.5Å) (table 3). This, in turn, significantly reduced the frequency of occurrence of the Van der Waals interaction in all the 3 hairpins (P < .001). Thus, in presence of V38A + N140I the interaction between residues 38 and 145, which is important for the formation of the 6-helix bundle, is drastically impaired.

Figure 4.
View larger version:
Figure 4.

A, Residues in HR1 and HR2 whose interaction is critical for the formation and stabilization of the 6-helix bundle. In the picture, the residues in HR1 and HR2 involved in the formation and stabilization of the 6-helix bundle are reported in bold type [29–31]. Lines, interaction between these residues. Residues 38 and 145 are in bold type. B, Insight of the gp41 6-helix bundle showing the distance between residues 38 and 145 in the wild-type gp41 protein and in presence of V38A ± N140I. Side chains of residues 38, 140, and 145 are highlighted in wire-frame. Each hairpin is represented by a different color.

Previous SectionNext Section

Discussion

This study, which involved one of the largest cohorts of ENF-treated patients assembled thus far, shows that ENF pressure is associated with intriguing patterns of gp41 mutations that significantly correlate with an increase or decrease in CD4+ cell count, without any significant correlation with the level of viremia. This suggests the potential involvement of gp41's structure in the modulation of HIV-1-induced damage to the immune system, by mechanisms not necessarily related to viral replication capacity. In this context, our findings represent an interesting concept with potential relevance for the design of the next generation of entry inhibitors.

In particular, we found that the patterns of mutations V38A + T18A and V38A + N140I were associated with a significant increase in CD4+ cell count, despite full virological failure. The V38A mutation has recently been shown to be associated with an increase in CD4+ cell count, even in presence of ongoing viral replication, in different independent data sets, including that from the ENF phase 3 clinical trials [19,32]. In this study, we found that the increase in CD4+ cell count associated with V38A is strongly and significantly reinforced by the concomitant presence of T18A or N140I. Because this is one of the most interesting (and clinically relevant) phenomena related to ENF treatment, we analyzed our data and others' data to find potential explanations of this result.

We first excluded the possibility that V38A, N140I, and T18A confer changes in known HLA-restricted cytotoxic T lymphocyte gp41 epitopes [33]. In addition, a recent study demonstrated that the V38A mutation does not increase the sensitivity of gp41 to the neutralizing antibodies 2F5 and 4E10 [34]. Thus, these findings suggest that the increase in CD4+ cell count induced by V38A + T18A or N140I is not directly associated with cytotoxic T lymphocyte responses and/or neutralizing antibodies, but is instead related to completely different and peculiar mechanisms.

By performing MDS, we observed that, in presence of V38A + N140I, the interaction between the gp41 residues 38 and 145 that is important for the stabilization of the 6-helix bundle [29–31] is drastically impaired. Thus, one might hypothesize that the abrogation of this interaction might reduce the gp41 fusogenic activity at a level sufficient to affect the induction of CD4+ T cell apoptosis but insufficient to affect fusion with the host cell. This model might explain why, in the presence of V38A + N140I, we observed a significant increase in CD4+ cell count but not a significant decrease in the level of viremia.

The mechanism of interaction for V38A and N140I at the protein level seems not to apply to the cluster V38A + T18A, thus we explored the reason(s) of the co-evolution of these 2 latter mutations by analyzing the nucleotidic sequence of gp41. Interestingly, T18A- and V38A-corresponding nucleotides are located complementarily to each other in the stem IIA of the Rev-responsive element (RRE). This stem has been shown to participate in the Rev interaction [35–37], thus promoting the stability and transport of unspliced and partially spliced HIV-1 mRNAs out of the nucleus, a step that is essential for the HIV-1 life cycle. V38A and T18A each derive from a nucleotide substitution, GUG to GCG, and ACU to GCU, respectively. The release of free energy observed with the mutated base pair C:G is even higher than that observed with the wild-type base-pair U:A (ΔG, -3.4 Kcal/mol vs. ΔG, -2.1 Kcal/mol) [38]. In addition, the copresence of T18A (GCU) and V38A (GCG) is associated with a higher level of viremia at virological failure. Overall findings suggest that these mutations, when copresent, may contribute to stabilize the secondary structure of the RRE, to influence the Rev-RRE interaction, and thus to potentially increase the replication capacity of HIV-1. Our hypothesis is consistent with the results of a previous study that demonstrated that the amino acid mutation I37T in the gp41 protein corresponds to a nucleotide change in the RRE, which impairs the stability of this RNA element. It has been suggested that the mutations A30V and G36D may appear in the gp41 protein as a consequent readjustment of the secondary structure of the RRE, and thus rescue RRE stability [37]. These findings suggest that changes in the nucleotide sequence of the RRE, induced by the ENF pressure, may alter its conformation and the Rev-RRE interaction. Thus, they highlight the importance of the correct interplay between the different HIV-1 genes and proteins during the HIV-1 life cycle and the ability of ENF (and of entry inhibitors in general) to modulate the viral life cycle at different steps at both the protein and RNA levels simultaneously.

Similarly, N126K was also associated with a significant increase in CD4+ cell count, despite virological failure. This crease might be related to the ability of the N126K mutation to abrogate the fourth gp41 N-linked glycosylation site, thus potentially resulting in the exposure of a previously hidden immunogenic epitope.

Unlike the previous gp41 mutational patterns, the ENF-associated cluster Q40H + L45M + T268A is significantly associated with a decrease in CD4+ cell count. Interestingly, the novel mutation T268A is located within the lentivirus lyticpeptide 2 (LLP2) domain, which plays a key role in the modulation of HIV-1 cytopathic effect. In particular, it has been demonstrated that deletions in the LLP2 domain result in a more fusogenic virus able to induce the apoptosis of CD4++ T lymphocytes more efficiently [39]. In addition, it has been shown that LLP2 directly interacts with calmodulin, thus triggering the Fas-mediated apoptosis of CD4+ T lymphocytes [12, 40]. Although further in vitro studies are necessary, it is conceivable that the presence of the T268A mutation alone or together with the resistance mutations Q40H + L45M might enhance the cytopathic properties of gp41. This hypothesis is supported by a recent study showing that mutations in the LLP2 domain represent important determinants for the acquisition of the cytopathic phenotype by CCR5-using HIV-1 strains at late stages of disease progression [41].

Because the early virological response has previously been demonstrated to predict the immunological response [42, 43], we have determined virological responses at week 8 and week 12 in the subsets of patients with V38A, V38A + T18A, V38A + N140I, N126K, and Q40H + L45M + T268A, and we have verified that virological responses are similar and not significantly different in the 5 groups of patients (P > .5; data not shown). Thus, differences in the mean changes in level of viremia at early time points seem not to be related to the increase in CD4+ cell count in the presence of specific mutational patterns. This supports the hypothesis that the increase in CD4+ cell count associated with specific gp41 mutational patterns has no direct relationship to decreases in the level of viremia under ENF treatment.

We need to emphasize that the proposed mechanisms of action of gp41 mutations are models that require validation by in vitro experiments. In addition, it should be pointed out that our data were derived under a “worst case scenario” situation, that is, under clinical conditions in which ENF was added as single active drug. Thus, it is possible that the specific mutations and the clusters of mutations that we observed under these conditions might not be recapitulated among patients who received several active agents simultaneously.

In conclusion, our study shows that ENF pressure can be associated with specific patterns of mutations that correlate with an increase or decrease in CD4+ cell count, without any significant correlation with the level of viremia. The models proposed to explain the mechanisms of action of these mutational patterns suggest that they may alter the Rev-RRE interactions, decrease HIV-1 cytopathic effect, and/or enhance immune response by mechanisms that may operate even under conditions of virological failure. Of course, further analyses of enlarged databases (that include genotypic and clinical data), complemented by experimental validation will provide insights regarding the hypotheses formulated and may lead to an improved understanding of the impact of these mutations on HIV-1 pathogenicity. Confirmation of these hypotheses may support the correct positioning of ENF in therapy for HIV-infected patients and may represent an attractive driving force for the design of the next generation entry inhibitors.

MEMBERS OF THE COLLABORATIVE GROUP FOR CLINICAL USE OF HIV-1 GENOTYPE RESISTANCE TEST AT THE NATIONAL INSTITUTE FOR INFECTIOUS DISEASES “LAZZARO SPALLANZANI” IN ROME, ITALY

Andrea Antinori (co-chair), Gianfranco Anzidei, Francesco Baldini, Rita Bellagamba, Maria Concetta Bellocchi, Ada Bertoli, Sandro Bonfigli, Evangelo Boumis, Francesca Ceccherini-Silberstein, Bruno Christian Ciancio, Fabio Continenza, Roberta D'Arrigo, Patrizio De Longis, Gianpiero D'Offizi, Federica Forbici, Sara Giannella, Enrico Girardi, Caterina Gori, Giuseppina Liuzzi, Patrizia Lorenzini, Patrizia Marconi, Pasquale Narciso, Emanuele Nicastri, Pasquale Noto, Carlo Federico Perno (co-chair), Pietro Sette, Fabio Soldani, Maria Paola Trotta, Valerio Tozzi, Ilaria Uccella, Ubaldo Visco-Comandini, Mauro Zaccarelli, and Daniela Zinzi.

Previous SectionNext Section

Acknowledgments

We thank Caterina Gori, Fabio Continenza, Daniele Pizzi, Andrea Biddittu, and Amalia Mastrofrancesco for sequencing and data management.

Previous SectionNext Section

Footnotes

  • ↵b For the INMI-Collaborative Group for Clinical Use of HIV Genotype Resistance Test. Members of the group are listed at the end of the text.

  • Potential conflicts of interest: none reported.

  • Financial support: Italian National Institute of Health; the Ministry of University and Scientific Research (grant ISS20G.16); Current and Finalized Research of the Italian Ministry of Health (grant PRIN2006067294_003); the European Community (grant QLK2-CT-2000–00291 and the Descartes Prize [HPAW-90001]). Computational work was supported by the LNF-INFN AMICO project coordinated by Dr. Vitaliano Chiarella (Laboratori Nazionali di Frascati- Istituto Nazionale di Fisica Nucleare, Frascati, Rome, Italy).

  • Received July 17, 2007.
  • Accepted November 16, 2007.
Previous Section
 

References

  1. 1.↵
    1. Derdeyn CA,
    2. Decker JM,
    3. Sfakianos JN,
    4. et al
    . Sensitivity of human immunodeficiency virus type 1 to fusion inhibitors targeted to the gp41 first heptad repeat involves distinct regions of gp41 and is consistently modulated by gp120 interactions with the coreceptor. J Virol 2001;75:8605-14.
    Abstract/FREE Full Text
  2. 2.↵
    1. Jiang S,
    2. Zhao Q,
    3. Debnath AK
    . Peptide and non-peptide HIV fusion inhibitors. Curr Pharm Des 2002;8:563-80.
    CrossRefMedlineWeb of Science
  3. 3.↵
    1. Mink M,
    2. Mosier SM,
    3. Janumpalli S,
    4. et al
    . Impact of human immunodeficiency virus type 1 gp41 amino acid substitutions selected during enfuvirtide treatment on gp41 binding and antiviral potency of enfuvirtide in vitro. J Virol 2005;79:12447-54.
    Abstract/FREE Full Text
  4. 4.
    1. Greenberg M,
    2. Cammack N,
    3. Salgo M,
    4. et al
    . HIV fusion and its inhibition in antiretroviral therapy. Rev Med Virol 2004;14:321-37.
    CrossRefMedlineWeb of Science
  5. 5.
    1. Miller MD,
    2. Hazuda DJ
    . HIV resistance to the fusion inhibitor enfuvirtide: mechanisms and clinical implications. Drug Resist Updat 2004;7:89-95.
    CrossRefMedlineWeb of Science
  6. 6.
    1. Reeves JD,
    2. Lee FH,
    3. Miamidian JL,
    4. et al
    . Enfuvirtide resistance mutations: impact on human immunodeficiency virus envelope function, entry inhibitor sensitivity, and virus neutralization. J Virol 2005;79:4991-99.
    Abstract/FREE Full Text
  7. 7.
    1. Mink M,
    2. Mosier SM,
    3. Janumpalli S,
    4. et al
    . Impact of human immunodeficiency virus type 1 gp41 amino acid substitutions selected during enfuvirtide treatment on gp41 binding and antiviral potency of enfuvirtide in vitro. J Virol 2005;79:12447-54.
    Abstract/FREE Full Text
  8. 8.↵
    1. Johnson VA,
    2. Brun-Vezinet F,
    3. Clotet B,
    4. et al
    . Update of the drug resistance mutations in HIV-1: Fall 2006. Top HIV Med 2006;14:125-30.
    Medline
  9. 9.↵
    1. Xu L,
    2. Pozniak A,
    3. Wildfire A,
    4. et al
    . Emergence and evolution of enfuvirtide resistance following long-term therapy involves heptad repeat 2 mutations within gp41. Antimicrob Agents Chemother 2005;49:1113-19.
    Abstract/FREE Full Text
  10. 10.
    1. Su C,
    2. Melby T,
    3. De Masi R,
    4. et al
    . Genotypic changes in human immunodeficiency virus type 1 envelope glycoproteins on treatment with the fusion inhibitor enfuvirtide and their influence on changes in drug susceptibility in vitro. J Clin Virol 2006;36:249-57.
    CrossRefMedlineWeb of Science
  11. 11.↵
    1. Loutfy MR,
    2. Raboud JM,
    3. Montaner JS,
    4. et al
    . Assay of HIV gp41 amino acid sequence to identify baseline variation and mutation development in patients with virologic failure on enfuvirtide. Antiviral Res 2007;75:58-63.
    CrossRefMedlineWeb of Science
  12. 12.↵
    1. Micoli KJ,
    2. Pan G,
    3. Wu Y,
    4. et al
    . Requirement of calmodulin binding by HIV-1 gp160 for enhanced FAS-mediated apoptosis. J Biol Chem 2000;275:1233-40.
    Abstract/FREE Full Text
  13. 13.
    1. Perfettini JL,
    2. Castedo M,
    3. Roumier TK,
    4. et al
    . Mechanisms of apoptosis induction by the HIV-1 envelope. Cell Death Differ 2005;12(Suppl 1):916-23.
    CrossRef
  14. 14.
    1. Garg H,
    2. Blumenthal R
    . HIV gp41-induced apoptosis is mediated by caspase-3-dependent mitochondrial depolarization, which is inhibited by HIV protease inhibitor nelfinavir. J Leukoc Biol 2006;79:352-62.
  15. 15.
    1. Micoli KJ,
    2. Mamaeva O,
    3. Piller SC,
    4. et al
    . Point mutations in the C-terminus of HIV-1 gp160 reduce apoptosis and calmodulin binding without affecting viral replication. Virology 2006;344:468-79.
    CrossRefMedline
  16. 16.
    1. Meissner EG,
    2. Zhang L,
    3. Jiang S,
    4. et al
    . Fusion-induced apoptosis contributes to thymocyte depletion by a pathogenic human immunodeficiency virus type 1 envelope in the human thymus. J Virol 2006;80:11019-30.
    Abstract/FREE Full Text
  17. 17.↵
    1. Garg H,
    2. Joshi A,
    3. Freed EO,
    4. et al
    . Site-specific mutations in HIV-1 gp41 reveal a correlation between HIV-1-mediated bystander apoptosis and fusion/hemifusion. J Biol Chem 2007;282:16899-06.
    Abstract/FREE Full Text
  18. 18.↵
    1. Yang X,
    2. Kurteva S,
    3. Ren X,
    4. et al
    . Stoichiometry of envelope glycoprotein trimers in the entry of human immunodeficiency virus type 1. J Virol 2005;79:12132-47.
    Abstract/FREE Full Text
  19. 19.↵
    1. Aquaro S,
    2. D'Arrigo R,
    3. Svicher V,
    4. et al
    . Specific mutations in HIV-1 gp41 are associated with immunological success in HIV-1 infected patients receiving enfuvirtide treatment. J Antimicrob Chemother 2006;58:714-22.
    Abstract/FREE Full Text
  20. 20.↵
    1. Benjamini Y,
    2. Hochberg Y
    . Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser 1995;57:289-300.
  21. 21.↵
    1. Jorge A,
    2. Torgo L,
    3. Brazdil P,
    4. Camacho R,
    5. Gama J
    1. Sing T,
    2. Svicher V,
    3. Beerenwinkel N,
    4. et al
    . Characterization of novel HIV drug resistance mutations using clustering, multidimensional scaling, and SVM-based feature ranking. In: Jorge A, Torgo L, Brazdil P, Camacho R, Gama J, editors. Knowledge discovery in databases: PKDD 2005: 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 2005 proceedings. New York: Sprinter; 2005. p. 285-96.
  22. 22.↵
    1. Svicher V,
    2. Sing T,
    3. Santoro MM,
    4. et al
    . Involvement of novel human immunodeficiency virus type 1 reverse transcriptase mutations in the regulation of resistance to nucleoside inhibitors. J Virol 2006;80:7186-98.
    Abstract/FREE Full Text
  23. 23.↵
    1. De Gruttola V,
    2. Dix L,
    3. D'Aquila R,
    4. et al
    . The relation between baseline HIV drug resistance and response to antiretroviral therapy: re-analysis of retrospective and prospective studies using a standardized data analysis plan. Antivir Ther 2000;5:41-48.
    MedlineWeb of Science
  24. 24.↵
    Stanford HIV Drug Resistance Database. [15 January 2007]. Available at: http://hivdb.stanford.edu.
  25. 25.↵
    Protein Data Bank. [20 January 2007]. Available at: http://www.rcsb.org/PDB.
  26. 26.↵
    1. McDonald DQ,
    2. Still WC
    . AMBER torsional parameters for the peptide backbone. Tetrahedron Lett 1992;33:7743-46.
    CrossRefWeb of Science
  27. 27.↵
    1. Mohamadi F,
    2. Richards NGJ,
    3. Guida WC,
    4. et al
    . MacroModel: an integrated software system for modeling organic and bioorganic molecules using molecular mechanics. J Comput Chem 1990;11:440-67.
    CrossRefWeb of Science
  28. 28.↵
    1. Wallace AC,
    2. Laskowski RA,
    3. Thornton JM
    . LigPlot: a program to generate schematic diagrams of protein-lig and interactions. Protein Eng 1995;8:127-34.
    Abstract/FREE Full Text
  29. 29.↵
    1. Chan DC,
    2. Fass D,
    3. Berger JM,
    4. et al
    . Core structure of gp41 from the HIV envelope glycoprotein. Cell 1997;89:263-73.
    CrossRefMedlineWeb of Science
  30. 30.
    1. Lu M,
    2. Stoller MO,
    3. Wang S,
    4. et al
    . Structural and functional analysis of interhelical interactions in the human immunodeficiency virus type 1 gp41 envelope glycoprotein by alanine-scanning mutagenesis. J Virol 2001;75:11146-56.
    Abstract/FREE Full Text
  31. 31.↵
    1. Liu S,
    2. Lu H,
    3. Niu J,
    4. et al
    . Different from the HIV fusion inhibitor C34, the anti-HIV drug Fuzeon (T-20) inhibits HIV-1 entry by targeting multiple sites in gp41 and gp120. J Biol Chem 2005;280:11259-73.
    Abstract/FREE Full Text
  32. 32.↵
    1. Melby T,
    2. DeSpirito M,
    3. De Masi R,
    4. et al
    . Association between specific enfuvirtide resistance mutations and CD4 cell response during enfuvirtide-based therapy. AIDS 2007;21:2537-9.
    CrossRefMedlineWeb of Science
  33. 33.↵
    HIV Molecular Immunology Database. [28 January 2007]. Available at: http://www.hiv.lanl.gov.
  34. 34.↵
    1. Barry AP,
    2. Stanfield-Oakley SA,
    3. Mosier SM,
    4. Greenberg ML
    . Impact of HR1 enfuvirtide resistance mutations on sensitivity to HR2-directed neutralizing antibodies [abstract 103]. Antivir Ther 2007 [5 July 2007];12(suppl 1):S114-S114. Available at: http://www.informedhorizons.com/resistance2007.
  35. 35.↵
    1. Holland SM,
    2. Ahmad N,
    3. Maitra PK,
    4. et al
    . Human immunodeficiency virus rev protein recognizes a target sequence in rev-responsive element RNA within the context of RNA secondary structure. J Virol 1990;64:5966-75.
    Abstract/FREE Full Text
  36. 36.
    1. Kjems J,
    2. Frankel AD,
    3. Sharp PA
    . Specific regulation of mRNA splicing in vitro by a peptide from HIV-1. Cell 1991;67:169-78.
    CrossRefMedlineWeb of Science
  37. 37.↵
    1. 37 Nameki D,
    2. Kodama E,
    3. Ikeuchi M,
    4. et al
    . Mutations conferring resistance to human immunodeficiency virus type 1 fusion inhibitors are restricted by gp41 and Rev-responsive element functions. J Virol 2005;79:764-70.
    Abstract/FREE Full Text
  38. 38.↵
    1. Jaeger JA,
    2. SantaLucia J,
    3. Tinoco I
    . Determination of RNA structure and thermodynamics. Annu Rev Biochem 1993;62:255-87.
    CrossRefMedlineWeb of Science
  39. 39.↵
    1. Wyss S,
    2. Dimitrov AS,
    3. Baribaud F,
    4. et al
    . Regulation of human immunodeficiency virus type 1 envelope glycoprotein fusion by a membrane-interactive domain in the gp41 cytoplasmic tail. J Virol 2005;79:12231-41.
    Abstract/FREE Full Text
  40. 40.↵
    1. Ishikawa H,
    2. Sasaki M,
    3. Noda S,
    4. et al
    . Apoptosis induction by the binding of the carboxyl terminus of human immunodeficiency virus type 1 gp160 to calmodulin. J Virol 1998;72:6574-80.
    Abstract/FREE Full Text
  41. 41.↵
    1. Olivieri K,
    2. Scoggins RM,
    3. Bor Y,
    4. et al
    . The envelope gene is a cytopathic determinant of CCR5 tropic HIV-1. Virology 2007;358:23-38.
    CrossRefMedline
  42. 42.↵
    1. Deeks SG,
    2. Barbour JD,
    3. Martin JN,
    4. et al
    . Sustained CD4+ T cell response after virologic failure of protease inhibitor-based regimens in patients with human immunodeficiency virus infection. J Infect Dis 2000;181:946-53.
    Abstract/FREE Full Text
  43. 43.↵
    1. Deeks SG,
    2. Barbour JD,
    3. Grant RM,
    4. et al
    . Duration and predictors of CD4 T-cell gains in patients who continue combination therapy despite detectable plasma viremia. AIDS 2002;16:201-7.
    CrossRefMedlineWeb of Science
| Table of Contents

This Article

  1. J Infect Dis. (2008) 197 (10): 1408-1418. doi: 10.1086/587693
  1. AbstractFree
  2. » Full Text (HTML)Free
  3. Full Text (PDF)Free

Classifications

Share

  1. Email this article

Navigate This Article

Current Issue

  1. March 1, 2012 205 (5)
  1. Journal of Infectious Diseases
  1. Alert me to new issues

Most