CD25+ FoxP3+ Memory CD4 T Cells Are Frequent Targets of HIV Infection In Vivo

Abstract

Interleukin 2 (IL-2) signaling through the IL-2 receptor alpha chain (CD25) facilitates HIV replication in vitro and facilitates homeostatic proliferation of CD25(+) FoxP3(+) CD4(+) T cells. CD25(+) FoxP3(+) CD4(+) T cells may therefore constitute a suitable subset for HIV infection and plasma virion production. CD25(+) FoxP3(+) CD4(+) T cell frequencies, absolute numbers, and the expression of CCR5 and cell cycle marker Ki67 were studied in peripheral blood from HIV(+) and HIV(-) study volunteers. Different memory CD4(+) T cell subsets were then sorted for quantification of cell-associated HIV DNA and phylogenetic analyses of the highly variable EnvV1V3 region in comparison to plasma-derived virus sequences. In HIV(+) subjects, 51% (median) of CD25(+) FoxP3(+) CD4(+) T cells expressed the HIV coreceptor CCR5. Very high frequencies of Ki67(+) cells were detected in CD25(+) FoxP3(+) memory CD4(+) T cells (median, 27.6%) in comparison to CD25(-) FoxP3(-) memory CD4(+) T cells (median, 4.1%; P < 0.0001). HIV DNA content was 15-fold higher in CD25(+) FoxP3(+) memory CD4(+) T cells than in CD25(-) FoxP3(-) T cells (P = 0.003). EnvV1V3 sequences derived from CD25(+) FoxP3(+) memory CD4(+) T cells did not preferentially cluster with plasma-derived sequences. Quasi-identical cell-plasma sequence pairs were rare, and their proportion decreased with the estimated HIV infection duration. These data suggest that specific cellular characteristics of CD25(+) FoxP3(+) memory CD4(+) T cells might facilitate efficient HIV infection in vivo and passage of HIV DNA to cell progeny in the absence of active viral replication. The contribution of this cell population to plasma virion production remains unclear.

Importance: Despite recent advances in the understanding of AIDS virus pathogenesis, which cell subsets support HIV infection and replication in vivo is incompletely understood. In vitro, the IL-2 signaling pathway and IL-2-dependent cell cycle induction are essential for HIV infection of stimulated T cells. CD25(+) FoxP3(+) memory CD4 T cells, often referred to as regulatory CD4 T cells, depend on IL-2 signaling for homeostatic proliferation in vivo Our results show that CD25(+) FoxP3(+) memory CD4(+) T cells often express the HIV coreceptor CCR5, are significantly more proliferative, and contain more HIV DNA than CD25(-) FoxP3(-) memory CD4 T cell subsets. The specific cellular characteristics of CD25(+) FoxP3(+) memory CD4(+) T cells probably facilitate efficient HIV infection in vivo and passage of HIV DNA to cell progeny in the absence of active viral replication. However, the contribution of this cell subset to plasma viremia remains unclear.

FIG 1

Frequencies and absolute numbers of CD25⁺ FoxP3⁺ CD4 T cells in the peripheral blood in relation to HIV infection. (A) Representative dot plots and gating strategy for the detection of regulatory T cells through CD25 and FoxP3 expression on CD3⁺ CD4⁺ T cells from fresh anticoagulated whole blood of WHIS subjects. (B and C) CD25⁺ Foxp3⁺ CD4 T cell frequencies (B) and absolute numbers (C) are compared between HIV⁻ and HIV⁺ subjects. (D) Correlation analysis of absolute CD4 counts and CD25⁺ Foxp3⁺ CD4 T cell counts. Statistical analysis was performed using the Mann-Whitney test for comparison of groups and the Spearman r statistical test for correlation analyses.

FIG 2

Ex vivo HIV coreceptor (CCR5) expression on CD25⁺ Foxp3⁺ CD4 T cells. (A) A histogram overlay of CCR5 expression on total CD4 T cells (gray) and CD25⁺ Foxp3⁺ CD4 T cells (black). (B) The frequencies of CCR5-expressing CD25⁺ Foxp3⁺ CD4 T cells are compared between HIV-negative and -positive subjects. For maximum staining sensitivity, fresh anticoagulated whole blood of individuals from the WHIS cohort was used to determine CCR5 expression on CD4 T cells. Statistical analysis was performed using the Mann-Whitney test.

FIG 3

Ki67 expression in CD25⁺ FoxP3⁺ and CD25⁻ FoxP3⁻ memory CD4 T cells in HIV⁺ subjects. (A) Representative dot plots for Ki67 staining. (B) Comparison of the frequencies of Ki67⁺ cells in CD25⁺ FoxP3⁺ and CD25⁻ FoxP3⁻ memory CD4 T cells in HIV⁺ subjects. (C) Correlation analysis of the frequency of Ki67⁺ cells between CD25⁺ FoxP3⁺ (y axis) and CD25⁻ FoxP3⁻ (x axis) memory CD4 T cells. (D and E) Correlation analysis of the frequency of Ki67⁺ cells among CD25⁺ FoxP3⁺ (D) and CD25⁻ FoxP3⁻ (E) CD4 T cells versus CD4 T cell frequencies (% of CD3). The analysis was done using cryopreserved PBMC samples from HIV⁺ HHECO study participants. Memory status of CD4 T cells was determined by CD45RA staining. Statistical analysis was performed using the Mann-Whitney test for comparison of groups and the Spearman r statistical test for correlation analyses.

FIG 4

Quantification of cell-associated HIV gag DNA in sorted memory CD4 T cell subsets. (A) Gating/sorting strategy used to sort different memory CD4 T cell populations delineated by Helios, CD25, and FoxP3 expression. (B) Numbers of gag DNA copies/10⁶cells detected in CD25⁻ FoxP3⁻ and CD25⁺ FoxP3⁺ memory CD4 T cells from 21 different subjects. (C) Numbers of gag DNA copies/10⁶cells detected in these memory CD4 T cell subsets further delineated by Helios expression. gag DNA within different CD4 T cell populations of the same subject was quantified during the same real-time (RT)-PCR run. Cryopreserved PBMCs from the WHIS and HISIS cohorts were used for cell sorting. Statistical analysis was performed using the Wilcoxon rank matched-pairs test.

FIG 5

Phylogenetic relationship of HIV envelope sequences derived from plasma and sorted memory CD4 T cell populations. Plasma- and cell-derived sequences of the highly variable EnvV1V3 region (Hxb 6559 to 7320) were amplified, cloned, sequenced (n = 384, Sanger method), and analyzed for 6 viremic subjects from the WHIS and HISIS cohorts with differing HIV infection durations (H574, H605, 6233K12 [6233], 9440A11 [9440], 8710U11 [8710], 8975T11 [8975]). (A and B) The phylogenetic relationship was inferred by the maximum-likelihood method based on the general time-reversible substitution model (GTR+G). (C) Correlation between frequency of cell-derived sequences that were quasi-identical to plasma-derived sequences and the estimated infection duration. (D and E) Linear regression analysis (green line) between the distance of the EnvV1V3 sequences derived from plasma to the sequences extracted from the corresponding cellular fractions and the estimated duration of infection (D) and plasma sequence diversity plotted against the estimated duration of infection (E). The red line indicates a nonlinear analysis performed using a second-order polynomial equation taking into account the best-fit values. The evolutionary distances were computed using the Kimura 2-parameter method (77) and are given in units of the number of base substitutions per site, including both transitions and transversions. The rate variation among sites was modeled with a gamma distribution. The analysis was conducted in MEGA6 (44). No sequence diversity was observed in the subject 8710 plasma fraction, probably because the number of viruses sampled in each PCR was very low (Table 2). We therefore excluded the results for subject 8710 from the linear regression analysis. P and r values were calculated with the Pearson two-tailed statistical test.

FIG 6

Phylogenetic analyses of HIV envelope sequences derived from plasma and sorted memory CD4 T cell populations using next-generation sequencing. Shown are the phylogenetic analyses of EnvV1V3 sequences from the 50 most frequently detected sequences derived from either plasma or the different sorted memory CD4 T cell subsets for two viremic subjects of the WHIS cohort. The phylogenetic relationship was inferred by the maximum-likelihood method based on the general time-reversible substitution model (GTR+G). EnvV1V3 amplicons were directly subjected to next-generation sequencing. Quasispecies reconstruction was performed using the software QuasiRecomb. The methods used are described in detail in Materials and Methods.