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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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Affinofile profiling reveals that resistance to broadly neutralizing antibodies (BNAbs) also results in reduced entry efficiency. (A-C) N160K and N279/280A mutations were engineered into a random sample of 12 subtype A-D Envs. The resultant (PG9/PG16)R and (VRC01)R resistant Envs were assayed for CD4 and CCR5 usage efficiency along with their parental BNAb sensitive Envs. GGR Affinofile profiling was performed as previously described. 2-D contour plots of the averaged infectivity profiles for (A) WT, (B) (PG9/PG16)R, and (C) (VRC01)R Envs are shown. The infectivity profile for the individual Envs are shown in supplementary Figure S5. Axes and color-codes are identical to previous contour plots. (D-E) The median values and interquartile ranges of the Mean infectivity (M) are shown for (PG9/PG16)R or (VRC01)R resistant Envs compared to their WT counterparts. P values calculated via a non-parametric paired t-test.
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Figure 7: Affinofile profiling reveals that resistance to broadly neutralizing antibodies (BNAbs) also results in reduced entry efficiency. (A-C) N160K and N279/280A mutations were engineered into a random sample of 12 subtype A-D Envs. The resultant (PG9/PG16)R and (VRC01)R resistant Envs were assayed for CD4 and CCR5 usage efficiency along with their parental BNAb sensitive Envs. GGR Affinofile profiling was performed as previously described. 2-D contour plots of the averaged infectivity profiles for (A) WT, (B) (PG9/PG16)R, and (C) (VRC01)R Envs are shown. The infectivity profile for the individual Envs are shown in supplementary Figure S5. Axes and color-codes are identical to previous contour plots. (D-E) The median values and interquartile ranges of the Mean infectivity (M) are shown for (PG9/PG16)R or (VRC01)R resistant Envs compared to their WT counterparts. P values calculated via a non-parametric paired t-test.

Mentions: To determine potential entry efficiency consequences related to these BNab resistance mutations we generated resistant N160K and N279/280A mutants in 24 Envs representing subtypes A through D, and examined their CD4/CCR5 entry efficiencies using the GGR Affinofile system. Figure 7A, B and C, shows the mean infectivity profiles for wt Envs (n = 12, 3 each from subtype A-D), and their respective isogenic N160K, and N279/280A mutants, each Env examined across 25 distinct CD4/CCR5 expression levels. An additional figure shows the individual infectivity profile for all 36 Envs examined [see Additional file6: Figure S4]. The PG9/PG16 (N160K) and VRC01 (N279/280A) resistance mutations reduce the efficiency of entry; both requiring higher levels of CD4 and CCR5 to achieve similar levels of infection as their wt counterparts. This can be appreciated by comparing the CD4/CCR5 expression level combinations that give rise to low levels of infection (green areas), or conversely, those that give rise to the highest level of infection (red areas), between the wt and mutant Envs (Figure 7A-C). This reduced entry efficiency phenotype across all subtypes tested is quantitatively reflected in the values, where the average M for PG9/PG16 and VRC01 resistant mutants is lower than that of their wt counterparts (Figure 7D and E). However, due to marked variability when comparing across all HIV-1 subtypes, only the difference between VRC01 resistance mutants and wt reached significance (p = 0.007). Our results suggest that resistance to BNAbs comes at the cost of reduced HIV-1 entry efficiency, and provides one functional explanation for the high conservation of these residues across HIV-1 subtypes. Both these reasons bode well for vaccine design that will elicit these kinds of BNAbs.


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)

Affinofile profiling reveals that resistance to broadly neutralizing antibodies (BNAbs) also results in reduced entry efficiency. (A-C) N160K and N279/280A mutations were engineered into a random sample of 12 subtype A-D Envs. The resultant (PG9/PG16)R and (VRC01)R resistant Envs were assayed for CD4 and CCR5 usage efficiency along with their parental BNAb sensitive Envs. GGR Affinofile profiling was performed as previously described. 2-D contour plots of the averaged infectivity profiles for (A) WT, (B) (PG9/PG16)R, and (C) (VRC01)R Envs are shown. The infectivity profile for the individual Envs are shown in supplementary Figure S5. Axes and color-codes are identical to previous contour plots. (D-E) The median values and interquartile ranges of the Mean infectivity (M) are shown for (PG9/PG16)R or (VRC01)R resistant Envs compared to their WT counterparts. P values calculated via a non-parametric paired t-test.
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Figure 7: Affinofile profiling reveals that resistance to broadly neutralizing antibodies (BNAbs) also results in reduced entry efficiency. (A-C) N160K and N279/280A mutations were engineered into a random sample of 12 subtype A-D Envs. The resultant (PG9/PG16)R and (VRC01)R resistant Envs were assayed for CD4 and CCR5 usage efficiency along with their parental BNAb sensitive Envs. GGR Affinofile profiling was performed as previously described. 2-D contour plots of the averaged infectivity profiles for (A) WT, (B) (PG9/PG16)R, and (C) (VRC01)R Envs are shown. The infectivity profile for the individual Envs are shown in supplementary Figure S5. Axes and color-codes are identical to previous contour plots. (D-E) The median values and interquartile ranges of the Mean infectivity (M) are shown for (PG9/PG16)R or (VRC01)R resistant Envs compared to their WT counterparts. P values calculated via a non-parametric paired t-test.
Mentions: To determine potential entry efficiency consequences related to these BNab resistance mutations we generated resistant N160K and N279/280A mutants in 24 Envs representing subtypes A through D, and examined their CD4/CCR5 entry efficiencies using the GGR Affinofile system. Figure 7A, B and C, shows the mean infectivity profiles for wt Envs (n = 12, 3 each from subtype A-D), and their respective isogenic N160K, and N279/280A mutants, each Env examined across 25 distinct CD4/CCR5 expression levels. An additional figure shows the individual infectivity profile for all 36 Envs examined [see Additional file6: Figure S4]. The PG9/PG16 (N160K) and VRC01 (N279/280A) resistance mutations reduce the efficiency of entry; both requiring higher levels of CD4 and CCR5 to achieve similar levels of infection as their wt counterparts. This can be appreciated by comparing the CD4/CCR5 expression level combinations that give rise to low levels of infection (green areas), or conversely, those that give rise to the highest level of infection (red areas), between the wt and mutant Envs (Figure 7A-C). This reduced entry efficiency phenotype across all subtypes tested is quantitatively reflected in the values, where the average M for PG9/PG16 and VRC01 resistant mutants is lower than that of their wt counterparts (Figure 7D and E). However, due to marked variability when comparing across all HIV-1 subtypes, only the difference between VRC01 resistance mutants and wt reached significance (p = 0.007). Our results suggest that resistance to BNAbs comes at the cost of reduced HIV-1 entry efficiency, and provides one functional explanation for the high conservation of these residues across HIV-1 subtypes. Both these reasons bode well for vaccine design that will elicit these kinds of BNAbs.

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