• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of aacPermissionsJournals.ASM.orgJournalAAC ArticleJournal InfoAuthorsReviewers
Antimicrob Agents Chemother. Jan 2011; 55(1): 321–325.
Published online Oct 18, 2010. doi:  10.1128/AAC.01733-09
PMCID: PMC3019647

Cross-Resistance Profile Determination of Two Second-Generation HIV-1 Integrase Inhibitors Using a Panel of Recombinant Viruses Derived from Raltegravir-Treated Clinical Isolates [down-pointing small open triangle]

Abstract

The integrase inhibitor raltegravir (RAL) is currently used for the treatment of both treatment-naïve and treatment-experienced HIV-1-infected patients. Elvitegravir (EVG) is in late phases of clinical development. Since significant cross-resistance between RAL and EVG is observed, there is a need for second-generation integrase inhibitors (INIs) with a higher genetic barrier and limited cross-resistance to RAL/EVG. A panel of HIV-1 integrase recombinants, derived from plasma samples from raltegravir-treated patients (baseline and follow-up samples), were used to study the cross-resistance profile of two second-generation integrase inhibitors, MK-2048 and compound G. Samples with Q148H/R mutations had elevated fold change values with all compounds tested. Although samples with the Y143R/C mutation had reduced susceptibility to RAL, they remained susceptible to MK-2048 and compound G. Samples with the N155H mutation had no reduced susceptibility to compound G. In conclusion, our results allowed ranking of the INIs on the basis of the antiviral activities using recombinant virus stocks from RAL-treated patient viruses. The order according to decreasing susceptibility is compound G, MK-2048, and EVG.

Integration of viral DNA is an essential step in the HIV life cycle and is catalyzed by the viral integrase (IN) enzyme. This protein is encoded by the 3′ end of the HIV-1 pol gene, which contains 288 amino acids and which functions as a tetramer (11). The integration process consists of multiple steps (3, 6, 7). First, a stable complex is formed between the IN enzyme and specific viral sequences at the end of the long terminal repeats (LTRs). The 3′ processing step consists of the cleavage of the GT dinucleotide from each 3′ end of the viral DNA. Subsequently, this preintegration complex migrates toward the nucleus, where the strand transfer, i.e., the stable insertion of the viral DNA into the host genomic DNA, takes place. Finally, the DNA gaps are repaired by host enzymes. Each of these steps can potentially be considered a drug target. Although many compounds have been reported to inhibit IN activity, to date, only the strand transfer inhibitors have been proven to be effective in vivo. While raltegravir (RAL; MK-0518) is currently approved by the FDA for use in both treatment-naïve and treatment-experienced patients, elvitegravir (EVG; GS-9137) is in late stages of clinical development (1, 10). Resistance to RAL occurs through three main pathways: Q148H/K/R, N155H, and less frequently, Y143R/C (3, 5). Additional secondary mutations in IN that either further decrease the susceptibility or increase the fitness of the virus have been reported. In patients failing EVG treatment, the mutations T66I, E92Q, S147G, Q148H/K/R, and N155H were identified (3), suggesting significant cross-resistance between RAL and EVG. There is need for second-generation IN inhibitors (INIs) with a higher genetic barrier and limited cross-resistance to RAL/EVG. Several potential second-generation INIs are in preclinical development, including MK-2048 (19), compound G (19), and S/GSK1349572 (16, 17).

In the study described in this report, a panel of plasma samples from RAL-treated patients was used to generate IN recombinant virus stocks (RVSs), which in turn were used to study the cross-resistance profiles of two second-generation inhibitors, MK-2048 and compound G.

MATERIALS AND METHODS

Samples.

Experiments were performed on a panel of 139 plasma samples derived from 106 HIV-1-infected patients. For some patients, serum samples were collected at different points in time during RAL treatment. Informed consent was available.

Plasmids with SDMs.

Mutants with site-directed mutations (SDMs) in the IN-coding region known to be associated with INI resistance were constructed in the pUC19-5′HXB2D plasmid (pUC19 containing the HIV genome from the 5′ LTR to the start of Env) by using a QuikChange site-directed mutagenesis kit (Stratagene) (9, 20). In total, 11 SDMs were generated: Q148H/G140S, Q148R, N155H, E92Q, S147G, T66I, T66A, V72I/E92Q/E157Q, E92Q/S147G, Y143R, and E92Q/N155H.

IN amplification and purification.

Viral RNA was isolated starting either from 256 μl plasma using an automated QIAamp virus BioRobot MDx extraction platform (Qiagen) or from 600 μl plasma using the EasyMAG procedure (bioMérieux), according to the manufacturers' instructions. cDNA was generated using Accuscript high-fidelity reverse transcriptase (Stratagene) with random hexamers (Invitrogen). Subsequently, the IN gene was amplified by nested PCR using forward primers 5′INoutR1 (positions 4059 to 4081 in HXB2; GenBank accession number K03455) and 5′INinF1 (positions 4143 to 4164 in HXB2) and reverse primers 3′INoutR2 (positions 5241 to 5262 in HXB2) and 3′INinR1 (positions 5195 to 5217 in HXB2). Both the outer and inner PCRs were performed using the Phusion high-fidelity PCR master mix (Finnzymes). Thermal cycling of both PCRs consisted of a denaturation step at 98°C for 30 s; 30 cycles of 10 s at 98°C, 30 s at 58°C, and 30 s at 72°C; and a final elongation for 10 min at 72°C. Amplicons were purified using the QIAquick PCR purification kit (Qiagen).

Sequencing analysis.

IN sequencing reactions, sequence editing, and contig assembly were performed as described by Van Baelen et al. (20). The following primers were used: 5′INinF (positions 4143 to 4164 in HXB2), IN_F_4540 (positions 4540 to 4558 in HXB2), Inseq2R (positions 4767 to 4748 in HXB2), and VIF_R_5193 (positions 5210 to 5193 in HXB2). Sequence editing and contig assembly were performed using the Sequencher program (version 4.1.4; Gene Codes Corporation) or the SeqScape program (version 2.5; Applied Biosystems) and strain HXB2 as a reference.

Production of replication-competent recombinant viruses.

Replication-competent RVSs were produced via homologous recombination in MT4 cells. An HXB2-based HIV-1 backbone in which the IN region was deleted (i.e., pHXB2-ΔIN) was used. IN amplicons were then recombined within the cells with the pHXB2-ΔIN backbone by Amaxa nucleofection (Amaxa Biosystems, Cologne, Germany), following the manufacturer's recommendations. Cell cultures were microscopically monitored for the appearance of a cytopathic effect (CPE) during the course of infection. When the full CPE was reached, the supernatants containing the recombinant viruses were harvested by centrifugation and stored at −80°C until further use.

Drug susceptibility testing of recombinant viruses (phenotyping).

Recombinant viruses were titrated and subjected to an antiviral experiment in MT4-LTR-eGFP cells as previously described (20). Briefly, MT4-LTR-eGFP cells were inoculated with a titrated amount of virus in the presence of 3-fold dilutions of the compound tested. After 3 days of incubation at 37°C, infection was quantified by means of fluorescent microscopy measuring HIV Tat-induced enhanced green fluorescent protein (eGFP) expression. Using the HIV-1 wild-type strain IIIB as a reference, fold change (FC) values were calculated by dividing the mean 50% effective concentration (EC50) for a recombinant virus stock by that for the reference strain. GFP background levels for this assay were very low in the presence of nonnucleoside reverse transcriptase inhibitors (NNRTIs), nucleoside reverse transcriptase inhibitors (NRTIs), and INIs. Indeed, the average GFP signals, expressed as a function of the signal for the virus control, for a variety of NNRTIs and NRTIs ranged from 0.01% for zidovudine to 0.27% for lamivudine. Similar low GFP background signals were detected in the presence of RAL (0.11%) and EVG (0.29%) (data not shown). The tested compounds (RAL, EVG, MK-2048 [19]) and compound G [19]) were chemically synthesized in-house. Biological cutoff values for RAL and EVG were used as defined elsewhere (20) (i.e., 2.1 for RAL and 2.0 for EVG). In the absence of biological cutoff values for MK-2048 and compound G, arbitrary cutoff values were used, whereby FC values of <2.5 were defined as susceptible, FC values of between 2.5 and 5 were defined as reduced susceptible, and FC values of >5 were defined as severely reduced. Analysis of the resistance profiles were done in the TIBCO Spotfire Enterprise Analytics program (version 3.0).

Statistics.

Fold change values were log transformed and genotypically assigned to either one of six primary mutation groups (i.e., Q148R, Q148H, N155H, Y143C, Y143R, or Q148K). FC values derived from no primary mutation (NPM) genotypes were used as a reference. Possible differences in log FC values were evaluated using the proc mixed model (12) in the SAS program (version 9.1), contrasting the main factors genotype, compound, and their interaction. The dissemination of the mixed procedure in SAS has provided a whole class of statistical models for routine use (12). Unlike classical analysis of variance (ANOVA) techniques, which are based on ordinary-least-squares (OLS) computations, proc mixed is a likelihood-based method (12). Although ANOVA has been used for several decades, its application in mixed models uses OLS computations, whereby random effects are treated as fixed. These computations are subsequently adapted for mixed models with no central theoretical basis and may result in idiosyncrasies and/or inadequacies (12). In contrast, the likelihood-based method, in which the covariance parameters are estimated via the residual maximum-likelihood method (REML) and in which the parameter means are estimated via the generalized least-squares method (GLS), matches the models and therefore provides the basis for optimal results (12). The proc mixed model was subsequently followed by a post hoc Tukey-Kramer test to investigate possible differences in log FC values between the NPM group and each of the six primary mutation genotype groups. Departures from values for the NPM group were regarded as being indicative of reduced susceptibility. A significance level of 5% was used throughout.

RESULTS AND DISCUSSION

Cross-resistance among four INIs was studied in two populations of recombinant viruses, one derived from a selection of SDMs and one derived from clinical isolates.

First, testing for susceptibility to RAL and EVG was performed on 11 SDMs (9, 20) known to be associated with resistance to INIs. Results were in concordance with previous data (20) and confirmed the high degree of cross-resistance between RAL and EVG using SDMs (Table (Table1).1). The 11 mutants with SDMs were also tested for their susceptibility to two second-generation INIs, MK-2048 and compound G (Table (Table1).1). FC values ranged from 0.2 (T66I) to 12.6 (Q148H/G140S) for MK-2048 and from 0.3 (T66I) to 5.3 (N155H) for compound G. Two double mutants (Q148H/G140S and E92Q/N155H) had reduced susceptibility to MK-2048. Only the N155H mutation resulted in a slightly elevated fold change value for compound G.

TABLE 1.
Susceptibility testing of 11 SDMs to INIsa

Second, a total of 139 RVSs derived from patient plasma samples were available for testing for susceptibility to the different INIs. Thirty-six samples contained a primary mutation known to cause resistance to RAL. Secondary mutations at residue 140 were found in all isolates with the Q148H/K/R pathway; three samples also had the E138K/A mutation. In the Y143R/C pathway, additional mutations, such as T97A, E138D, and Q95K, were found. The mutations E92Q/A, Q95K, and E138D were also found in the N155H pathway (Table (Table2).2). The coexistence of these mutations with the primary mutation pathways are in concordance with the findings of previously reported studies (2, 4, 5, 8, 13-15, 18).

TABLE 2.
Combined genotype and phenotype data of the RVSs derived from 139 clinical isolates

The 139 RVSs derived from clinical isolates were tested for their susceptibility to RAL and EVG. The median of the RAL and EVG FC values was calculated (Table (Table2).2). The proc mixed model showed that the two main factors (i.e., genotype and compound) contributed significantly to the observed variation in log FC. In addition, the two-way interaction was also highly significant, indicating that differences in log FC among the four compounds varied depending on the genotype taken under consideration (Table (Table3).3). This significant interaction was largely determined by the fact that the highest FC values were found for EVG for all genotype groups except Y143R and Y143C, where they dropped below the RAL FC values (Tables (Tables22 and and3;3; Fig. Fig.1).1). Viruses with Q148H/K/R mutations had highly reduced susceptibility to both RAL and EVG, while susceptibility to these compounds was only slightly reduced for samples with mutations in the N155H pathway (Fig. (Fig.1,1, genotype group comparison to NPM group; all P values were <0.05). Although the mutant with the Y143R SDM had reduced susceptibility only to RAL, the RVSs derived from the clinical isolates had higher FC values for both compounds. The difference in FC values for RAL between the mutant with the Y143R SDM (FC value, 8.9) and the clinical isolates (median FC value, 99.7) could be explained by the presence of the secondary mutation T97A in all five clinical isolates. Moreover, addition of the E138D/L74M/G163N mutation in one sample resulted in an FC value for RAL of 1,242. A similar observation was made for EVG (Table (Table22).

FIG. 1.
Graphical representation of the mean log10 FC values with standard errors for the different genotype groups. Gray symbols represent groups with one observation only, where the post-hoc Tukey-Kramer test for departure from the NPM genotype group was not ...
TABLE 3.
Results of the proc mixed model for possible differences in log10 FC among the genotype groups, compounds, and their interactiona

In addition, 75 out of the 139 RVSs derived from clinical isolates were tested for their susceptibility to MK-2048 and compound G (Table (Table2;2; Fig. Fig.1).1). Compound G resulted in the lowest FC values, irrespective of the genotype which is taken under consideration (Table (Table2;2; Fig. Fig.1).1). Samples with the Q148R or Q148H mutation had reduced susceptibility to both MK-2048 and compound G (Table (Table2;2; Fig. Fig.1).1). A large difference in FC values between the mutant with the Q148R SDM and the clinical isolates containing the Q148R mutation could be found for all compounds tested (for MK-2048, an FC value of 2 for SDM Q148R versus a mean FC value of 245 for the clinical isolates). This could be explained by the presence of the secondary mutation at position 140 (G140S or G140A) in all clinical isolates containing the Q148R mutation (Table (Table2).2). Although samples with the Y143R/C mutation had reduced susceptibility to RAL, they remained susceptible to two second-generation INIs investigated (P > 0.05) (Fig. (Fig.1).1). The presence of the secondary mutation T97A did not reduce the susceptibility to the two compounds (Table (Table2).2). However, one sample containing the Y143R, T97A, E138D, L74M, and G163N mutations had a slightly reduced susceptibility to MK-2048 (FC value, 4.5). Samples with the N155H mutation had no reduced susceptibility to compound G (median FC value, 1.2; Fig. Fig.1).1). A few samples with the N155H mutation had, however, slightly increased FC values for MK-2048, due to the presence of secondary mutations. For example, one sample containing both the N155H and Q95K mutations had an FC value of 13.7 for MK-2048 (Table (Table22).

Our results allowed ranking of the INIs on the basis of the antiviral activities using recombinant virus stocks from RAL-treated patient virus. The order according to decreasing susceptibility was compound G, MK-2048, and EVG. This could be confirmed by the slopes of the linear regression curves comparing the cross-resistance profiles between the three compounds and RAL in Fig. Fig.22 (for compound G, b = 0.19; for MK-2048, b = 0.57; and for EVG, b = 0.95). In more detail, samples with the Q148H/R mutation had elevated FC values not only for RAL and EVG but also for the two other compounds. The Y143 pathway was almost exclusive for RAL, and samples with the N155H mutation most often had elevated FC values only for RAL and EVG. Criteria for efficient new second-generation INIs are low cross-resistance profiles compared with those of the currently approved drugs, high genetic barrier, a good toxicity/safety profile, and reasonable dosing. The recombinant virus stocks derived from RAL-treated clinical isolates are very useful to investigate one aspect, i.e., the cross-resistance profile. Using recombinant virus stocks from RAL-treated patient virus, our results allowed ranking of the INIs on the basis of the antiviral activities.

FIG. 2.
Cross-resistance profiles of four INIs using recombinant virus stocks from 75 clinical isolates. The x axis represents the RAL FC values; the y axis represents EVG (A), MK-2048 (B), and compound G (C) FC values. Red, RVS with mutations at residue 143; ...

Acknowledgments

We thank our academic and clinical collaborators for providing the original clinical plasma samples for research purposes.

Footnotes

[down-pointing small open triangle]Published ahead of print on 18 October 2010.

REFERENCES

1. Al-Mawsawi, L. Q., R. I. Al-Safi, and N. Neamati. 2008. Anti-infectives: clinical progress of HIV-1 integrase inhibitors. Expert Opin. Emerg. Drugs 13:213-225. [PubMed]
2. Canducci, F., M. Sampaolo, M. C. Marinozzi, E. Boeri, V. Spagnuolo, A. Galli, A. Castagna, A. Lazzarin, M. Clementi, and N. Gianotti. 2009. Dynamic patterns of human immunodeficiency virus type 1 integrase gene evolution in patients failing raltegravir-based salvage therapies. AIDS 23:455-460. [PubMed]
3. Ceccherini-Silberstein, F., I. Malet, R. D'Arrigo, A. Antinori, A. G. Marcelin, and C. F. Perno. 2009. Characterization and structural analysis of HIV-1 integrase conservation. AIDS Rev. 11:17-29. [PubMed]
4. Charpentier, C., M. Karmochkine, D. Laureillard, P. Tisserand, L. Belec, L. Weiss, A. Si-Mohamed, and C. Piketty. 2008. Drug resistance profiles for the HIV integrase gene in patients failing raltegravir salvage therapy. HIV Med. 9:765-770. [PubMed]
5. Cooper, D. A., R. T. Steigbigel, J. M. Gatell, J. K. Rockstroh, C. Katlama, P. Yeni, A. Lazzarin, B. Clotet, P. N. Kumar, J. E. Eron, M. Schechter, M. Markowitz, M. R. Loutfy, J. L. Lennox, J. Zhao, J. Chen, D. M. Ryan, R. R. Rhodes, J. A. Killar, L. R. Gilde, K. M. Strohmaier, A. R. Meibohm, M. D. Miller, D. J. Hazuda, M. L. Nessly, M. J. DiNubile, R. D. Isaacs, H. Teppler, and B. Y. Nguyen. 2008. Subgroup and resistance analyses of raltegravir for resistant HIV-1 infection. N. Engl. J. Med. 359:355-365. [PubMed]
6. Delelis, O., K. Carayon, A. Saib, E. Deprez, and J. F. Mouscadet. 2008. Integrase and integration: biochemical activities of HIV-1 integrase. Retrovirology 5:114. [PMC free article] [PubMed]
7. Engelman, A., K. Mizuuchi, and R. Craigie. 1991. HIV-1 DNA integration: mechanism of viral DNA cleavage and DNA strand transfer. Cell 67:1211-1221. [PubMed]
8. Fransen, S., S. Gupta, R. Danovich, D. Hazuda, M. Miller, M. Witmer, C. J. Petropoulos, and W. Huang. 2009. Loss of raltegravir susceptibility by human immunodeficiency virus type 1 is conferred via multiple nonoverlapping genetic pathways. J. Virol. 83:11440-11446. [PMC free article] [PubMed]
9. Goethals, O., R. Clayton, M. Van Ginderen, I. Vereycken, E. Wagemans, P. Geluykens, K. Dockx, R. Strijbos, V. Smits, A. Vos, G. Meersseman, D. Jochmans, K. Vermeire, D. Schols, S. Hallenberger, and K. Hertogs. 2008. Resistance mutations in human immunodeficiency virus type 1 integrase selected with elvitegravir confer reduced susceptibility to a wide range of integrase inhibitors. J. Virol. 82:10366-10374. [PMC free article] [PubMed]
10. Hicks, C., and R. M. Gulick. 2009. Raltegravir: the first HIV type 1 integrase inhibitor. Clin. Infect. Dis. 48:931-939. [PubMed]
11. Jaskolski, M., J. N. Alexandratos, G. Bujacz, and A. Wlodawer. 2009. Piecing together the structure of retroviral integrase, an important target in AIDS therapy. FEBS J. 276:2926-2946. [PMC free article] [PubMed]
12. Littel, R. C. 2002. Analysis of unbalanced mixed model data: a case study comparison of ANOVA versus REML/GLS. J. Agric. Biol. Environ. Stat. 7:472-490.
13. Malet, I., O. Delelis, M. A. Valantin, B. Montes, C. Soulie, M. Wirden, L. Tchertanov, G. Peytavin, J. Reynes, J. F. Mouscadet, C. Katlama, V. Calvez, and A. G. Marcelin. 2008. Mutations associated with failure of raltegravir treatment affect integrase sensitivity to the inhibitor in vitro. Antimicrob. Agents Chemother. 52:1351-1358. [PMC free article] [PubMed]
14. McColl, D. J., and X. Chen. 2010. Strand transfer inhibitors of HIV-1 integrase: bringing IN a new era of antiretroviral therapy. Antiviral Res. 85:101-118. [PubMed]
15. Miller, M. 2007. Resistance to integrase inhibitors. J. HIV Ther. 12:101. [PubMed]
16. Min, S., I. Song, J. Borland, S. Chen, Y. Lou, T. Fujiwara, and S. C. Piscitelli. 2010. Pharmacokinetics and safety of S/GSK1349572, a next-generation HIV integrase inhibitor, in healthy volunteers. Antimicrob. Agents Chemother. 54:254-258. [PMC free article] [PubMed]
17. Sato, A., M. Kobayashi, T. Yoshinga, T. Fujiwara, M. Underwood, B. Johns, S. Foster, R. Hazen, R. Ferris, K. Brown, and E. Garvey. 2009. Abstr. 5th Int. AIDS Soc. Conf., abstr. WEPEA097.
18. Sichtig, N., S. Sierra, R. Kaiser, M. Daumer, S. Reuter, E. Schulter, A. Altmann, G. Fatkenheuer, U. Dittmer, H. Pfister, and S. Esser. 2009. Evolution of raltegravir resistance during therapy. J. Antimicrob. Chemother. 64:25-32. [PubMed]
19. Vacca, J. P., J. S. Wai, E. F. Thorsten, M. W. Embrey, D. J. Hazuda, M. D. Miller, P. J. Felock, M. V. Witmer, L. J. Gabryelski, R. Anari, C. Kochansky, J. Ellis, and T. A. Lyde. 2007. Abstr. 4th Int. AIDS Soc. Conf., abstr. WEPEA088.
20. Van Baelen, K., E. Rondelez, V. Van Eygen, K. Arien, M. Clynhens, P. Van den Zegel, B. Winters, and L. J. Stuyver. 2009. A combined genotypic and phenotypic human immunodeficiency virus type 1 recombinant virus assay for the reverse transcriptase and integrase genes. J. Virol. Methods 161:231-239. [PubMed]

Articles from Antimicrobial Agents and Chemotherapy are provided here courtesy of American Society for Microbiology (ASM)
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...