Contribution of human immunodeficiency virus type 1 minority variants to reduced drug susceptibility in patients on an integrase strand transfer inhibitor-based therapy

Abstract

The role of HIV-1 minority variants on transmission, pathogenesis, and virologic failure to antiretroviral regimens has been explored; however, most studies of low-level HIV-1 drug-resistant variants have focused in single target regions. Here we used a novel HIV-1 genotypic assay based on deep sequencing, DEEPGEN (Gibson et al 2014 Antimicrob Agents Chemother 58∶2167) to simultaneously analyze the presence of minority variants carrying mutations associated with reduced susceptibility to protease (PR), reverse transcriptase (RT), and integrase strand transfer integrase inhibitors (INSTIs), as well as HIV-1 coreceptor tropism. gag-p2/NCp7/p1/p6/pol-PR/RT/INT and env/C2V3 PCR products were obtained from twelve heavily treatment-experienced patients experiencing virologic failure while participating in a 48-week dose-ranging study of elvitegravir (GS-US-183-0105). Deep sequencing results were compared with (i) virological response to treatment, (ii) genotyping based on population sequencing, (iii) phenotyping data using PhenoSense and VIRALARTS, and (iv) HIV-1 coreceptor tropism based on the phenotypic test VERITROP. Most patients failed the antiretroviral regimen with numerous pre-existing mutations in the PR and RT, and additionally newly acquired INSTI-resistance mutations as determined by population sequencing (mean 9.4, 5.3, and 1.4 PI- RTI-, and INSTI-resistance mutations, respectively). Interestingly, since DEEPGEN allows the accurate detection of amino acid substitutions at frequencies as low as 1% of the population, a series of additional drug resistance mutations were detected by deep sequencing (mean 2.5, 1.5, and 0.9, respectively). The presence of these low-abundance HIV-1 variants was associated with drug susceptibility, replicative fitness, and coreceptor tropism determined using sensitive phenotypic assays, enhancing the overall burden of resistance to all four antiretroviral drug classes. Further longitudinal studies based on deep sequencing tests will help to clarify (i) the potential impact of minority HIV-1 drug resistant variants in response to antiretroviral therapy and (ii) the importance of the detection of HIV minority variants in the clinical practice.

Figure 1. Replicative fitness of 12 patient-derived p2-INT-recombinant viruses in the absence of drug pressure.

(A) Thirteen p2-INT-recombinant viruses (i.e., 12 patient-derived and the HIV-1_NL4-3 wild-type virus) were evaluated for their ability to replicate in MT-4 cells in the absence of drug pressure. Virus replication was quantified by measuring reverse transcriptase (RT) activity in the cell-free supernatant. (B) Viral replication slopes were calculated using the slopes between RLU values at days 0 & 3, 0 & 4, 0 & 5, 0 & 6, and 0 & 7, corresponding to exponential viral growth. All five slope values for each virus were used to calculate the mean, standard deviation, and 10^th & 90^th percentiles. Differences in the mean values were calculated using a One Way Analysis of Variance test and the significance difference from HIV-1_NL4-3 calculated using the Bonferroni's Multiple Comparison Test. The replication kinetics of viruses marked with an asterisk (*) were significantly different to the HIV-1_NL4-3 control (p<0.05, 95% CI). Mutations in the protease (PR), reverse transcriptase (RT), and integrase (INT) coding regions are indicated for each virus. WT, wild-type (HIV-1_NL4-3 virus).

Figure 2. Coverage, i.e., number of reads per nucleotide position, obtained by deep sequencing the 12 patient-derived and the HIV-1_NL4-3 wild-type virus.

The gag-p2/NCp7/p1/p6/pol-PR/RT/IN and env-C2V3 fragments from all thirteen viruses were RT-PCR amplified and sequenced as described . See Materials and Methods for details.

Figure 3. Phylogenetic and HIV-1 genetic diversity analysis.

(A) Neighbor-joining phylogenetic trees constructed using population (Sanger) sequencing of 105-bp fragments corresponding to the HIV-1 protease, RT, integrase, and V3 regions from the 12 patients. Phylogenetic trees were rooted using the HIV-1_HXB2 sequence (GenBank accession number AF033819). (B) Neighbor-joining phylogenetic trees constructed using reads with a frequency >1 corresponding to 105-bp fragments from the protease, RT, integrase, and V3 regions. Each color-coded dot represents a unique variant, frequency is not depicted. Bootstrap resampling (1,000 data sets) of the multiple alignments tested the statistical robustness of the trees, with percentage values above 75% indicated by an asterisk. s/nt, substitutions per nucleotide. (C) HIV-1 intra- and inter-patient genetic diversities were determined using MEGA 5.05 .

Figure 4. Comparison of the HIV-1 drug-resistant mutations identified by standard population (Sanger) and deep sequencing.

Plasma samples from the 12 treatment-experienced HIV-infected individuals participating in the GS-US-183-0105 study of elvitegravir were analyzed as described in Materials and Methods. The top plot compares the number of drug resistance mutations detected by Sanger and deep sequencing in each patient. The total numbers of drug resistance mutations identified by each sequencing method are indicated. The mean difference in the numbers of drug resistance mutations detected by population and deep sequencing in the protease (PR), reverse transcriptase (RT), and integrase (INT) regions is indicated in the bottom graph. Deep, deep sequencing; Pop, population sequencing.

Figure 5. Frequency of amino acids detected in positions associated with HIV-1 drug resistance in the protease, reverse transcriptase, and integrase coding regions using Sanger (population) and deep sequencing (DEEPGEN) in patient 08–189.

Amino acid substitutions associated with HIV-1 drug resistance are indicated in red.

Figure 6. HIV-1 coreceptor tropism determination using deep sequencing (DEEPGEN [43]) and a phenotypic assay (VERITROP [54]).

(A) Hierarchical clustering analysis was used to group the two HIV-1 coreceptor tropism determinations by similarity. Dendograms were calculated using the Euclidean distance and Complete cluster methods with 100 bootstrap iterations as described (http://www.hiv.lanl.gov/content/sequence/HEATMAP/heatmap.html). Bootstrap values are indicated. Green and red blocks indicate the absence or presence of non-R5 (X4) viruses, respectively, as determined by each assay. (B) Concordance between DEEPGEN and VERITROP.