Dynamics of HIV-1 quasispecies during antiviral treatment dissected using ultra-deep pyrosequencing

Abstract

Background: Ultra-deep pyrosequencing (UDPS) allows identification of rare HIV-1 variants and minority drug resistance mutations, which are not detectable by standard sequencing.

Principal findings: Here, UDPS was used to analyze the dynamics of HIV-1 genetic variation in reverse transcriptase (RT) (amino acids 180-220) in six individuals consecutively sampled before, during and after failing 3TC and AZT containing antiretroviral treatment. Optimized UDPS protocols and bioinformatic software were developed to generate, clean and analyze the data. The data cleaning strategy reduced the error rate of UDPS to an average of 0.05%, which is lower than previously reported. Consequently, the cut-off for detection of resistance mutations was very low. A median of 16,016 (range 2,406-35,401) sequence reads were obtained per sample, which allowed detection and quantification of minority resistance mutations at amino acid position 181, 184, 188, 190, 210, 215 and 219 in RT. In four of five pre-treatment samples low levels (0.07-0.09%) of the M184I mutation were observed. Other resistance mutations, except T215A and T215I were below the detection limit. During treatment failure, M184V replaced M184I and dominated the population in combination with T215Y, while wild-type variants were rarely detected. Resistant virus disappeared rapidly after treatment interruption and was undetectable as early as after 3 months. In most patients, drug resistant variants were replaced by wild-type variants identical to those present before treatment, suggesting rebound from latent reservoirs.

Conclusions: With this highly sensitive UDPS protocol preexisting drug resistance was infrequently observed; only M184I, T215A and T215I were detected at very low levels. Similarly, drug resistant variants in plasma quickly decreased to undetectable levels after treatment interruption. The study gives important insights into the dynamics of the HIV-1 quasispecies and is of relevance for future research and clinical use of the UDPS technology.

Figure 1. Frequency of resistance drug resistance mutations M184V, T215Y, L210W and T215C/D before, during and after treatment.

Treatment history is indicated by bars below each patient's graph; AZT; zidovudine, 3TC; lamivudine, d4T; stavudine, ddI; didanosine, ABC; abacavir, ddC; zalcitabine, TDF; tenofovir, NNRTI; non-nucleoside reverse transcriptase inhibitors, PI; protease inhibitors. Arrows indicate time for sampling. The dashed horizontal lines indicate the detection limit in each patient. ND: not detectible.

Figure 2. HIV-1 variant dynamics before, during and after treatment.

For each patient the 10 most common variants in each time point are illustrated as circles (if recurring) or as cubes (if not recurring). The genetic distance of the variants in nucleotide changes/site (from the most frequent variant at the first time-point) is plotted over time. The frequency of the variants is proportional to the area of the circles and cubes. Treatment history is indicated by bars below each patient's graph; AZT; zidovudine, 3TC; lamivudine, d4T; stavudine, ddI; didanosine, ABC; abacavir, ddC; zalcitabine, TDF; tenofovir, NNRTI; non-nucleoside reverse transcriptase inhibitors, PI; protease inhibitors. Arrows indicate time for sampling. The genotype of the variants is color-coded, thus each combination of drug resistance mutations have a specific color (see guide to the right unique for each patient). There are at maximum six shades of each color enable means to follow specific variants over time. Thus, the most common variant receives the first shade and so on. The last shade is used for the remaining variants and for the non-recurring variants.

Figure 3. HIV-1 variant dynamics before, during and after treatment.

For each patient the 10 most common variants in each time point are illustrated as circles (if recurring) or as cubes (if not recurring). The genetic distance of the variants in nucleotide changes/site (from the most frequent variant at the first time-point) is plotted over time. The frequency of the variants is proportional to the area of the circles and cubes. Treatment history is indicated by bars below each patient's graph; AZT; zidovudine, 3TC; lamivudine, d4T; stavudine, ddI; didanosine, ABC; abacavir, ddC; zalcitabine, TDF; tenofovir, NNRTI; non-nucleoside reverse transcriptase inhibitors, PI; protease inhibitors. Arrows indicate time for sampling. The genotype of the variants is color-coded, thus each combination of drug resistance mutations have a specific color (see guide to the right unique for each patient). There are at maximum six shades of each color enable means to follow specific variants over time. Thus, the most common variant receives the first shade and so on. The last shade is used for the remaining variants and for the non-recurring variants.