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Quantitative deep sequencing reveals dynamic HIV-1 escape and large population shifts during CCR5 antagonist therapy in vivo.

Tsibris AM, Korber B, Arnaout R, Russ C, Lo CC, Leitner T, Gaschen B, Theiler J, Paredes R, Su Z, Hughes MD, Gulick RM, Greaves W, Coakley E, Flexner C, Nusbaum C, Kuritzkes DR - PLoS ONE (2009)

Bottom Line: Profound baseline V3 loop sequence heterogeneity existed; predicted CXCR4-using populations were identified in a largely CCR5-using population.Greater V3 diversity was observed post-selection.This previously unreported degree of V3 loop sequence diversity has implications for viral pathogenesis, vaccine design, and the optimal use of HIV-1 CCR5 antagonists.

View Article: PubMed Central - PubMed

Affiliation: Massachusetts General Hospital, Boston, Massachusetts, United States of America.

ABSTRACT
High-throughput sequencing platforms provide an approach for detecting rare HIV-1 variants and documenting more fully quasispecies diversity. We applied this technology to the V3 loop-coding region of env in samples collected from 4 chronically HIV-infected subjects in whom CCR5 antagonist (vicriviroc [VVC]) therapy failed. Between 25,000-140,000 amplified sequences were obtained per sample. Profound baseline V3 loop sequence heterogeneity existed; predicted CXCR4-using populations were identified in a largely CCR5-using population. The V3 loop forms associated with subsequent virologic failure, either through CXCR4 use or the emergence of high-level VVC resistance, were present as minor variants at 0.8-2.8% of baseline samples. Extreme, rapid shifts in population frequencies toward these forms occurred, and deep sequencing provided a detailed view of the rapid evolutionary impact of VVC selection. Greater V3 diversity was observed post-selection. This previously unreported degree of V3 loop sequence diversity has implications for viral pathogenesis, vaccine design, and the optimal use of HIV-1 CCR5 antagonists.

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Related in: MedlinePlus

Shannon Entropy Plots.The number of times each form is found is plotted against the number of forms found with a given frequency. Week 0, yellow; intermediate time point, red; VF, blue. 95% CI for the Shannon Entropy are calculated by 100 bootstrap re-samples of the distribution of forms at each time point. The rise and decline of the two most common forms at each time point are tracked through the figures and are represented by the colored lines; the coloring of these lines facilitates tracking the most common forms at the first time point (yellow), second time point (red), and third time point (blue) through the time sequence.
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pone-0005683-g005: Shannon Entropy Plots.The number of times each form is found is plotted against the number of forms found with a given frequency. Week 0, yellow; intermediate time point, red; VF, blue. 95% CI for the Shannon Entropy are calculated by 100 bootstrap re-samples of the distribution of forms at each time point. The rise and decline of the two most common forms at each time point are tracked through the figures and are represented by the colored lines; the coloring of these lines facilitates tracking the most common forms at the first time point (yellow), second time point (red), and third time point (blue) through the time sequence.

Mentions: Each unique V3 form at each time point was considered, and the number of times each form appears was used to calculate the Shannon entropy of the sample (Fig 5). In this analysis the V3 loop is being treated as a functional unit, and every distinct form considered independently of distance measures, to obtain a different perspective regarding population complexity. The 95% confidence intervals (CI) for the Shannon Entropy were calculated by 100 random-with-replacement re-samples (bootstrap) of the primary V3 loop data at each time point. To illustrate the sample diversity for each point, we plotted the number of times each form was found on the y-axis, by the number of forms found with given frequency on the x-axis. Thus, at week 0 for subject 07 there were 112,818 V3 sequences that were intact with no frame shifts or stop codons (N = 112,818). The most common sequence was found 56,546 times (the top left hand point). There were 585 unique sequences that might be viable as they were intact in the V3 region, but they were each found only once in the sample (gold point on the bottom right). The Shannon entropy, H, was 1.83 [95% CI 1.81–1.84]; the 95% CI of the entropy for this time point and the next did not overlap, so the second sample was significantly more diverse. After VVC selection, the total V3 diversity increased in each subject with emergent X4 or VVC-resistant virus, corresponding to a significant increase in the overall sample Shannon entropy in subjects 07 and 19. The seeming paradox of increasing entropy of V3 forms upon selection in these cases suggests that the resistant viruses may have the opportunity to explore sequence space and variants can compete more effectively after drug pressure selects against the previously dominant and fit baseline form(s).


Quantitative deep sequencing reveals dynamic HIV-1 escape and large population shifts during CCR5 antagonist therapy in vivo.

Tsibris AM, Korber B, Arnaout R, Russ C, Lo CC, Leitner T, Gaschen B, Theiler J, Paredes R, Su Z, Hughes MD, Gulick RM, Greaves W, Coakley E, Flexner C, Nusbaum C, Kuritzkes DR - PLoS ONE (2009)

Shannon Entropy Plots.The number of times each form is found is plotted against the number of forms found with a given frequency. Week 0, yellow; intermediate time point, red; VF, blue. 95% CI for the Shannon Entropy are calculated by 100 bootstrap re-samples of the distribution of forms at each time point. The rise and decline of the two most common forms at each time point are tracked through the figures and are represented by the colored lines; the coloring of these lines facilitates tracking the most common forms at the first time point (yellow), second time point (red), and third time point (blue) through the time sequence.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2682648&req=5

pone-0005683-g005: Shannon Entropy Plots.The number of times each form is found is plotted against the number of forms found with a given frequency. Week 0, yellow; intermediate time point, red; VF, blue. 95% CI for the Shannon Entropy are calculated by 100 bootstrap re-samples of the distribution of forms at each time point. The rise and decline of the two most common forms at each time point are tracked through the figures and are represented by the colored lines; the coloring of these lines facilitates tracking the most common forms at the first time point (yellow), second time point (red), and third time point (blue) through the time sequence.
Mentions: Each unique V3 form at each time point was considered, and the number of times each form appears was used to calculate the Shannon entropy of the sample (Fig 5). In this analysis the V3 loop is being treated as a functional unit, and every distinct form considered independently of distance measures, to obtain a different perspective regarding population complexity. The 95% confidence intervals (CI) for the Shannon Entropy were calculated by 100 random-with-replacement re-samples (bootstrap) of the primary V3 loop data at each time point. To illustrate the sample diversity for each point, we plotted the number of times each form was found on the y-axis, by the number of forms found with given frequency on the x-axis. Thus, at week 0 for subject 07 there were 112,818 V3 sequences that were intact with no frame shifts or stop codons (N = 112,818). The most common sequence was found 56,546 times (the top left hand point). There were 585 unique sequences that might be viable as they were intact in the V3 region, but they were each found only once in the sample (gold point on the bottom right). The Shannon entropy, H, was 1.83 [95% CI 1.81–1.84]; the 95% CI of the entropy for this time point and the next did not overlap, so the second sample was significantly more diverse. After VVC selection, the total V3 diversity increased in each subject with emergent X4 or VVC-resistant virus, corresponding to a significant increase in the overall sample Shannon entropy in subjects 07 and 19. The seeming paradox of increasing entropy of V3 forms upon selection in these cases suggests that the resistant viruses may have the opportunity to explore sequence space and variants can compete more effectively after drug pressure selects against the previously dominant and fit baseline form(s).

Bottom Line: Profound baseline V3 loop sequence heterogeneity existed; predicted CXCR4-using populations were identified in a largely CCR5-using population.Greater V3 diversity was observed post-selection.This previously unreported degree of V3 loop sequence diversity has implications for viral pathogenesis, vaccine design, and the optimal use of HIV-1 CCR5 antagonists.

View Article: PubMed Central - PubMed

Affiliation: Massachusetts General Hospital, Boston, Massachusetts, United States of America.

ABSTRACT
High-throughput sequencing platforms provide an approach for detecting rare HIV-1 variants and documenting more fully quasispecies diversity. We applied this technology to the V3 loop-coding region of env in samples collected from 4 chronically HIV-infected subjects in whom CCR5 antagonist (vicriviroc [VVC]) therapy failed. Between 25,000-140,000 amplified sequences were obtained per sample. Profound baseline V3 loop sequence heterogeneity existed; predicted CXCR4-using populations were identified in a largely CCR5-using population. The V3 loop forms associated with subsequent virologic failure, either through CXCR4 use or the emergence of high-level VVC resistance, were present as minor variants at 0.8-2.8% of baseline samples. Extreme, rapid shifts in population frequencies toward these forms occurred, and deep sequencing provided a detailed view of the rapid evolutionary impact of VVC selection. Greater V3 diversity was observed post-selection. This previously unreported degree of V3 loop sequence diversity has implications for viral pathogenesis, vaccine design, and the optimal use of HIV-1 CCR5 antagonists.

Show MeSH
Related in: MedlinePlus