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Distinct HIV-1 entry phenotypes are associated with transmission, subtype specificity, and resistance to broadly neutralizing antibodies.

Chikere K, Webb NE, Chou T, Borm K, Sterjovski J, Gorry PR, Lee B - Retrovirology (2014)

Bottom Line: First, we profiled a panel of reference subtype B transmitted/founder (T/F) and chronic Envs (n = 12) by analyzing the infectivity of each Env across 25 distinct combinations of CD4/CCR5 expression levels.Lastly, mutations known to confer resistance to VRC01 or PG6/PG19 BNAbs, when engineered into subtypes A-D Envs, resulted in significantly decreased CD4/CCR5 usage efficiency.GGR Affinofile profiling reveals pathophysiological phenotypes associated with varying HIV-1 entry efficiencies, and highlight the fitness costs associated with resistance to some broadly neutralizing antibodies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Microbiology, Immunology, and Molecular Genetics, Los Angeles, USA. benhur.lee@mssm.edu.

ABSTRACT

Background: The efficiency of CD4/CCR5 mediated HIV-1 entry has important implications for pathogenesis and transmission. The HIV-1 receptor affinity profiling (Affinofile) system analyzes and quantifies the infectivity of HIV-1 envelopes (Envs) across a spectrum of CD4/CCR5 expression levels and distills these data into a set of Affinofile metrics. The Affinofile system has shed light on how differential CD4/CCR5 usage efficiencies contributes to an array of Env phenotypes associated with cellular tropism, viral pathogenesis, and CCR5 inhibitor resistance. To facilitate more rapid, convenient, and robust analysis of HIV-1 entry phenotypes, we engineered a reporter Affinofile system containing a Tat- and Rev-dependent Gaussia luciferase-eGFP-Reporter (GGR) that is compatible with the use of pseudotyped or replication competent viruses with or without a virally encoded reporter gene. This GGR Affinofile system enabled a higher throughput characterization of CD4/CCR5 usage efficiencies associated with differential Env phenotypes.

Results: We first validated our GGR Affinofile system on isogenic JR-CSF Env mutants that differ in their affinity for CD4 and/or CCR5. We established that their GGR Affinofile metrics reflected their differential entry phenotypes on primary PBMCs and CD4+ T-cell subsets. We then applied GGR Affinofile profiling to reveal distinct entry phenotypes associated with transmission, subtype specificity, and resistance to broadly neutralizing antibodies (BNAbs). First, we profiled a panel of reference subtype B transmitted/founder (T/F) and chronic Envs (n = 12) by analyzing the infectivity of each Env across 25 distinct combinations of CD4/CCR5 expression levels. Affinofile metrics revealed that at low CCR5 levels, our panel of subtype B T/F Envs was more dependent on high levels of CD4 for HIV-1 entry compared to chronic Envs. Next, we analyzed a reference panel of 28 acute/early subtype A-D Envs, and noted that subtype C Envs could be distinguished from the other subtypes based on their infectivity profiles and relevant Affinofile metrics. Lastly, mutations known to confer resistance to VRC01 or PG6/PG19 BNAbs, when engineered into subtypes A-D Envs, resulted in significantly decreased CD4/CCR5 usage efficiency.

Conclusions: GGR Affinofile profiling reveals pathophysiological phenotypes associated with varying HIV-1 entry efficiencies, and highlight the fitness costs associated with resistance to some broadly neutralizing antibodies.

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HIV envelopes exhibit subtype-specific differences in CD4/CCR5 usage efficiencies. (A) Normalized infection data from each subtype A, B, C and D envelope clones (n = 28) were analyzed by VERSA. The vector metrics were averaged for at least two independent infections (with a variance <5%) for each envelope in each subtype group. Vector angle (θ), mean infectivity (M), and vector amplitude (Δ) values for each envelope are shown as grouped by subtypes. P values were generated by the non- parametric unpaired t test (p*** < 0.005, **p < 0.05). B) 2-D contour plots of the average infectivity profile for each subtype, generated and color coded as in Figure 4G. The colored dashed square boxes compare the infectivity differences noted between subtype C (blue) Envs and others (red) in the lower left (LL) and upper right (UR) quadrants. Each Env clone was independently profiled twice. (C) Polar plot of the averaged sensitivity vectors obtained from each subtype, generated as in Figure 3E.
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Figure 6: HIV envelopes exhibit subtype-specific differences in CD4/CCR5 usage efficiencies. (A) Normalized infection data from each subtype A, B, C and D envelope clones (n = 28) were analyzed by VERSA. The vector metrics were averaged for at least two independent infections (with a variance <5%) for each envelope in each subtype group. Vector angle (θ), mean infectivity (M), and vector amplitude (Δ) values for each envelope are shown as grouped by subtypes. P values were generated by the non- parametric unpaired t test (p*** < 0.005, **p < 0.05). B) 2-D contour plots of the average infectivity profile for each subtype, generated and color coded as in Figure 4G. The colored dashed square boxes compare the infectivity differences noted between subtype C (blue) Envs and others (red) in the lower left (LL) and upper right (UR) quadrants. Each Env clone was independently profiled twice. (C) Polar plot of the averaged sensitivity vectors obtained from each subtype, generated as in Figure 3E.

Mentions: We next used the GGR Affinofile cells to characterize a panel of 28 subtype A, B, C and D Envs [see Additional file4: Table S2]. As might be expected from a diverse panel of subtype Envs, there was a high degree of intra- and inter- subtype variability in all three metrics (Figure 6A). An additional figure shows the infectivity profile for each subtype Env examined [see Additional file5: Figure S3]. Despite this variability, significant differences in CD4/CCR5 usage patterns between HIV-1 subtypes can be appreciated. For example, subtype C Envs had the highest θ and M values (Figure 6A), indicating that this subtype, as a group, used CCR5 more efficiently than Envs from other HIV-1 subtypes. The aggregate infectivity data confirms that subtype C Envs do, indeed, achieve a higher level of infection in response to increasing CCR5 levels, especially when CD4 levels are limiting (Figure 6B, compare the lower left quadrants). Interestingly, when CCR5 levels are low, subtype C Envs exhibited markedly reduced levels of infectivity compared to Envs from other HIV-1 subtypes, even at the highest CD4 levels (Figure 6B, compare upper right quadrants). Although this subtle nuance is not captured in ∆, infectivity profiles serve as an alternative method that adds depth to the existing algorithm. Finally, Envs from both HIV-1 subtypes A and C have significantly higher M values than subtype B Envs (Figure 6A). The polar plot in Figure 6C shows that subtype C envelopes can be clearly distinguished from other subtype envelopes based on their and metrics even if the amplitudes (∆) do not differ significantly between the subtypes.


Distinct HIV-1 entry phenotypes are associated with transmission, subtype specificity, and resistance to broadly neutralizing antibodies.

Chikere K, Webb NE, Chou T, Borm K, Sterjovski J, Gorry PR, Lee B - Retrovirology (2014)

HIV envelopes exhibit subtype-specific differences in CD4/CCR5 usage efficiencies. (A) Normalized infection data from each subtype A, B, C and D envelope clones (n = 28) were analyzed by VERSA. The vector metrics were averaged for at least two independent infections (with a variance <5%) for each envelope in each subtype group. Vector angle (θ), mean infectivity (M), and vector amplitude (Δ) values for each envelope are shown as grouped by subtypes. P values were generated by the non- parametric unpaired t test (p*** < 0.005, **p < 0.05). B) 2-D contour plots of the average infectivity profile for each subtype, generated and color coded as in Figure 4G. The colored dashed square boxes compare the infectivity differences noted between subtype C (blue) Envs and others (red) in the lower left (LL) and upper right (UR) quadrants. Each Env clone was independently profiled twice. (C) Polar plot of the averaged sensitivity vectors obtained from each subtype, generated as in Figure 3E.
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Figure 6: HIV envelopes exhibit subtype-specific differences in CD4/CCR5 usage efficiencies. (A) Normalized infection data from each subtype A, B, C and D envelope clones (n = 28) were analyzed by VERSA. The vector metrics were averaged for at least two independent infections (with a variance <5%) for each envelope in each subtype group. Vector angle (θ), mean infectivity (M), and vector amplitude (Δ) values for each envelope are shown as grouped by subtypes. P values were generated by the non- parametric unpaired t test (p*** < 0.005, **p < 0.05). B) 2-D contour plots of the average infectivity profile for each subtype, generated and color coded as in Figure 4G. The colored dashed square boxes compare the infectivity differences noted between subtype C (blue) Envs and others (red) in the lower left (LL) and upper right (UR) quadrants. Each Env clone was independently profiled twice. (C) Polar plot of the averaged sensitivity vectors obtained from each subtype, generated as in Figure 3E.
Mentions: We next used the GGR Affinofile cells to characterize a panel of 28 subtype A, B, C and D Envs [see Additional file4: Table S2]. As might be expected from a diverse panel of subtype Envs, there was a high degree of intra- and inter- subtype variability in all three metrics (Figure 6A). An additional figure shows the infectivity profile for each subtype Env examined [see Additional file5: Figure S3]. Despite this variability, significant differences in CD4/CCR5 usage patterns between HIV-1 subtypes can be appreciated. For example, subtype C Envs had the highest θ and M values (Figure 6A), indicating that this subtype, as a group, used CCR5 more efficiently than Envs from other HIV-1 subtypes. The aggregate infectivity data confirms that subtype C Envs do, indeed, achieve a higher level of infection in response to increasing CCR5 levels, especially when CD4 levels are limiting (Figure 6B, compare the lower left quadrants). Interestingly, when CCR5 levels are low, subtype C Envs exhibited markedly reduced levels of infectivity compared to Envs from other HIV-1 subtypes, even at the highest CD4 levels (Figure 6B, compare upper right quadrants). Although this subtle nuance is not captured in ∆, infectivity profiles serve as an alternative method that adds depth to the existing algorithm. Finally, Envs from both HIV-1 subtypes A and C have significantly higher M values than subtype B Envs (Figure 6A). The polar plot in Figure 6C shows that subtype C envelopes can be clearly distinguished from other subtype envelopes based on their and metrics even if the amplitudes (∆) do not differ significantly between the subtypes.

Bottom Line: First, we profiled a panel of reference subtype B transmitted/founder (T/F) and chronic Envs (n = 12) by analyzing the infectivity of each Env across 25 distinct combinations of CD4/CCR5 expression levels.Lastly, mutations known to confer resistance to VRC01 or PG6/PG19 BNAbs, when engineered into subtypes A-D Envs, resulted in significantly decreased CD4/CCR5 usage efficiency.GGR Affinofile profiling reveals pathophysiological phenotypes associated with varying HIV-1 entry efficiencies, and highlight the fitness costs associated with resistance to some broadly neutralizing antibodies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Microbiology, Immunology, and Molecular Genetics, Los Angeles, USA. benhur.lee@mssm.edu.

ABSTRACT

Background: The efficiency of CD4/CCR5 mediated HIV-1 entry has important implications for pathogenesis and transmission. The HIV-1 receptor affinity profiling (Affinofile) system analyzes and quantifies the infectivity of HIV-1 envelopes (Envs) across a spectrum of CD4/CCR5 expression levels and distills these data into a set of Affinofile metrics. The Affinofile system has shed light on how differential CD4/CCR5 usage efficiencies contributes to an array of Env phenotypes associated with cellular tropism, viral pathogenesis, and CCR5 inhibitor resistance. To facilitate more rapid, convenient, and robust analysis of HIV-1 entry phenotypes, we engineered a reporter Affinofile system containing a Tat- and Rev-dependent Gaussia luciferase-eGFP-Reporter (GGR) that is compatible with the use of pseudotyped or replication competent viruses with or without a virally encoded reporter gene. This GGR Affinofile system enabled a higher throughput characterization of CD4/CCR5 usage efficiencies associated with differential Env phenotypes.

Results: We first validated our GGR Affinofile system on isogenic JR-CSF Env mutants that differ in their affinity for CD4 and/or CCR5. We established that their GGR Affinofile metrics reflected their differential entry phenotypes on primary PBMCs and CD4+ T-cell subsets. We then applied GGR Affinofile profiling to reveal distinct entry phenotypes associated with transmission, subtype specificity, and resistance to broadly neutralizing antibodies (BNAbs). First, we profiled a panel of reference subtype B transmitted/founder (T/F) and chronic Envs (n = 12) by analyzing the infectivity of each Env across 25 distinct combinations of CD4/CCR5 expression levels. Affinofile metrics revealed that at low CCR5 levels, our panel of subtype B T/F Envs was more dependent on high levels of CD4 for HIV-1 entry compared to chronic Envs. Next, we analyzed a reference panel of 28 acute/early subtype A-D Envs, and noted that subtype C Envs could be distinguished from the other subtypes based on their infectivity profiles and relevant Affinofile metrics. Lastly, mutations known to confer resistance to VRC01 or PG6/PG19 BNAbs, when engineered into subtypes A-D Envs, resulted in significantly decreased CD4/CCR5 usage efficiency.

Conclusions: GGR Affinofile profiling reveals pathophysiological phenotypes associated with varying HIV-1 entry efficiencies, and highlight the fitness costs associated with resistance to some broadly neutralizing antibodies.

Show MeSH
Related in: MedlinePlus