The receptor repertoire and functional profile of follicular T cells in HIV-infected lymph nodes

Abstract

Follicular helper CD4⁺ T cells (T_FH) play an integral role in promoting B cell differentiation and affinity maturation. While T_FH cell frequencies are increased in lymph nodes (LN) from individuals infected with HIV, humoral immunity remains impaired during chronic HIV infection. Whether HIV inhibits T_FH responses in LNs remains unclear. Advances in this area have been limited by the difficulty of accessing human lymphoid tissues. Here, we combined highdimensional mass cytometry with TCR repertoire sequencing to interrogate the composition of T_FH cells in primary human LNs. We found evidence for intact antigen-driven clonal expansion of T_FH cells and selective utilization of specific CDR3 motifs during chronic HIV infection, but the resulting T_FH cells acquired an activation-related T_FH cell signature characterized by IL-21 dominance. These IL-21⁺ T_FH cells contained an oligoclonal HIV-reactive population, preferentially accumulated in patients with severe HIV infection, and associated with aberrant B cell distribution in the same LN. These data indicate that T_FH cells remain capable of responding to HIV antigens during chronic HIV infection but become functionally skewed and oligoclonally restricted under persistent antigen stimulation.

One Sentence Summary:

Follicular T cells undergo clonal expansion and express an altered functional phenotype during chronic HIV infection.

Introduction

Follicular helper T cells (T_FH) provide key signals necessary for B cell recruitment and selection to generate protective antibody responses (1, 2). During untreated chronic HIV infection, T_FH cells become highly expanded in the lymph nodes (LN) (3, 4). Despite this, HIV⁺ patients generate diminished protective antibody responses against immune challenges. For example, HIV-infected individuals produce lower titers of antibodies and less durable responses to seasonal influenza vaccines (5, 6). The prevailing model suggests that T_FH cells from HIV patients are ineffective at providing B cell help based on in vitro assays that showed less robust antibody production by B cells co-cultured with T_FH cells from HIV⁺ patients (7–9). A proposed mechanism for this involves upregulation of PD-L1 by B cells, which interacts with PD-1 on T_FH cells to inhibit TCR-dependent activation of T_FH cells (7). However, the extent to which T_FH cells express impaired antigen responsiveness in vivo remains unclear. As T_FH cells need to appropriately sense antigen signals in order to discriminate between B cells, defective response to antigen not only impairs provision of T cell help to individual B cells, but would also imperil the process of B cell selection on a global level.

Here, we interrogated the functional phenotype and TCR repertoire composition of primary T_FH cells isolated directly from LNs from HIV⁺ individuals. We utilized the presence or absence of antigen-dependent TCR signatures to address the responsiveness of T_FH cells to antigen engagement and applied high dimensional mass cytometry to elucidate how HIV infection alters the functional phenotype of T_FH cells in the lymphoid compartment. Our data revealed clonal expansion and convergent selection for Gag-reactive TCRs in T_FH cells in the germinal centers (GC) of HIV-infected LNs, indicating that T_FH cells remain capable of responding to HIV antigens during chronic HIV infection. However, T_FH cells in LNs from HIV⁺ individuals acquire an activated phenotype dominated by IL-21 production, which were less polyfunctional and correlated with aberrant changes in B cell development. By combining antigen-specific analyses with single-cell TCR sequencing, we further demonstrated that IL-21⁺ T_FH cells contained an HIV-reactive population expressing a restricted TCR repertoire and GC phenotype. Thus, TCR-directed response to HIV alters T_FH cell diversity and composition in the lymphoid compartment.

Results

HIV infected LNs contain clonally expanded GC T_FH cells

LNs from untreated HIV⁺ patients contain a high frequency of T_FH cells, but the mechanism that drives expansion of T_FH cells remains unclear. The enrichment of HIV antigens (10, 11) and the highly pro-inflammatory milieu (12, 13) in the LNs could lead to antigen-driven and/or bystander T cell expansion. To address whether proliferation of T_FH cells is antigen-dependent, we tested whether HIV induces selective proliferation of certain T cell clones. We focused on GC T_FH cells because the frequency of these cells becomes greatly increased during chronic HIV infection (3, 4). To identify GC T_FH cells, we selected memory CD4⁺ T cells that express T_FH cell markers CXCR5 and PD-1. CD57 is a glycan carbohydrate epitope expressed by T_FH cells in the GC, and we used this marker to further demarcate the GC subset (14–17). Naïve CD4⁺ T cells were identified by CD45RO^-CXCR5^-CD57^-CCR7⁺ expression, and memory CD4⁺ T cells were CD45RO⁺CXCR5^-PD-1^-ICOS^- (Fig. 1A). We sorted 1,464 to 15,000 naïve, memory, and GC T_FH cells from freshly thawed LN samples and analyzed the TCR sequences of these subsets using a molecular identifier (MID)-based approach to increase the accuracy of repertoire sequencing (Table S1) (18, 19). Because the variability of TCR sequences is encoded in the complementarity determining region 3 (CDR3) region, we used the number of transcripts detected for a particular CDR3 sequence to define TCR clone size. On average 11,839 TCR transcripts were detected for each sample (Table S2). Unique TCR frequencies range from 1 in 37,129 (0.003%) for the rarest clones to 250 in 2,498 (~10%) for the most expanded clone. To compare the degree of relative clonal expansion, we categorized TCR frequency into 6 groups, ranging from rare (<0.1%) to >2%, according to the clone size relative to the total TCR transcripts detected in that sample. As expected, the TCR repertoire of naïve CD4⁺ T cells was composed mostly of rare clones. In contrast, the TCR repertoire of GC T_FH cells had a much higher fraction of TCRs occupied by abundant clones (>0.1%) compared to naïve and memory CD4⁺ T cells (Fig. 1B, Fig. S1). The degree of TCR clonal expansion was quantified by normalized Shannon entropy (NSE) (20, 21). Consistent with the hypothesis that the increase in GC T_FH cell frequency is due to selective proliferation of certain T cell clones, GC T_FH cells had a lower NSE score compared to naive and memory cells (Fig. 1C). Taken together, our data demonstrated a notable expansion of clone size in GC T_FH cell populations.

Figure 1:

GC T_FH cells become clonally expanded. (A) Representative plots showing sorting strategy to identify naïve, memory, and GC T_FH cells. (B) Breakdown of the proportion of the TCR repertoire represented by clones of different sizes for sorted naïve, memory, and GC T_FH cells from HIV⁺ LNs. TCR clone size was normalized by the total number of TCR transcripts on nucleotide sequences. (C) Normalized Shannon entropy of the TCR repertoire of sorted naïve, memory, and GC T_FH cells. Grey lines link the same patient. Bars indicate means. * P < 0.05 by two-tailed Wilcoxon signed-rank test, n = 8 HIV-infected LNs.

TCRs from GC T_FH cells exhibit signatures of antigen-driven clonal convergence

Next, to test whether clonal expansion in GC T_FH cells from HIV-infected LNs was antigendriven, we analyzed the TCR sequences for evidence of convergence to the same amino acid sequence from distinct nucleotide sequences. Unlike B cells, which can undergo somatic hypermutation, the TCR sequence of a naïve T cell is determined during maturation in the thymus and remains fixed throughout the lifespans of the T cell and its progeny. Thus, with the exception of clones that express 2 TCR α or β sequences, distinct TCR nucleotide sequences necessarily arise from distinct naïve T cells. However, multiple nucleotide sequences of different TCRs may encode the same amino acid sequence. These degenerate TCR sequences are typically rare, and the presence of these sequences suggests antigen selection pressure that favors certain TCR motifs that recognize particular antigen(s). Thus, having highly abundant CDR3 amino acid sequences that are encoded by multiple distinct nucleotide sequences indicates preferential expansion of T cells with that specificity (20). On the other hand, we would not expect multiple nucleotide sequences to converge on the amino acid level in the absence of strong antigen-driven selection. Following this logic, we translated the TCR nucleotide sequences into amino acid sequences and tallied the number of different nucleotide sequences that encode each CDR3 amino acid sequence. These CDR3 amino acid sequences can be broken into 4 quadrants based on the level of degeneracy and frequency in the repertoire (Fig. 2A and Fig. S2). Q1 contains highly expanded amino acid CDR3 sequences that are encoded by 2 or more nucleotide sequences. These degenerate, abundant clones likely arose from strong antigen-driven selection and proliferation. Q2 contains low frequency amino acid CDR3 sequences that are also encoded by 2 or more nucleotide sequences. Degenerate clones can stochastically arise in the repertoire, but these are typically rare as reflected by the low frequency of non-clonally expanded sequences in Q2. Q3 contains amino acid CDR3 sequences that show neither clonal expansion nor amino acid convergence and make up the majority of the repertoire. Q4 contains expanded amino acid CDR3 sequences derived from a single nucleotide sequence and are therefore non-degenerate. This TCR degeneracy analysis revealed a significant degree of antigen-driven clonal convergence in GC T_FH cells compared to naïve and memory T cells (Fig. 2B-C). Together with the NSE decrease in GC T_FH cells, these data provide further evidence that antigen-driven clonal expansion is preserved in GC T_FH cells.

Figure 2:

Antigen-driven clonal selection signature in GC T_FH cells of HIV-infected LNs. (A) Representative degeneracy plot from sample H2. Coding degeneracy level (number of unique TCR nucleotide (nt) sequences encoding a common CDR3 amino acid (aa) sequence) of each CDR3 aa sequence is plotted against their frequency (measured as % of total TCR transcripts) in naïve, memory, and GC T_FH cells. Each dot is a unique CDR3 aa sequence. Red dashed lines indicate cutoffs for degenerate (2 or more nt sequences coding for the same aa sequence, horizontal) and expanded (0.1% or more of TCR transcripts, vertical) clones. Red arrow points to example degenerate clone in (B). (B) An example of CDR3 aa degeneracy. aa (top row) and nt (bottom row) sequences for 3 distinct nt sequences (0.41% of total TCR transcripts) that code for the same aa sequence as indicated by arrow in (A): Y=3, X=0.41%. Red boxes and highlights indicate redundant codons. (C) Comparison of Q1 degenerate-abundant clone percentage in naïve, memory, and GC T_FH cells. Grey lines link the same patient. Bars indicate means. *P < 0.05 by two-tailed Wilcoxon signed-rank test, n = 8 HIV-infected LNs.

HIV promotes selective expansion of HIV-reactive T_FH cells.

To determine if clonally expanded and/or convergently selected TCRs include HIV-specific sequences, approximately 2 – 3 million thawed LN cells were cultured with an HIV-1 consensus B Gag peptide pool for 3–4 weeks, then restimulated with the same peptide pool for 4 hours to identify antigen-specific T cells by CD40L and CD69 upregulation (Fig. S3). LN cells were also stimulated with an overlapping set of hemagglutinin (HA) peptides from influenza virus (A/California/7/2009) as a non-HIV control. TCRs from CD40L⁺CD69⁺ Gag- or HA-reactive T cells were used to generate a reference TCR panel (Table S3). These antigen-specific TCR sequences were mapped onto our bulk T cell sequencing data from freshly thawed LN cells to determine which sequences were Gag- or HA-specific. Common sequences shared between naïve, memory, or GC T_FH cells were shown as connecting lines on circos plots (Fig. 3A).

Figure 3:

GC T_FH cells exhibit HIV-antigen-driven clonal expansion and selection. (A) Gagspecific TCR clones overlap with HIV⁺ LN CD4⁺ T cell populations. Each thin slice of the arc represents a unique TCR sequence, ordered by the clone size (darker green for larger clones, inner circle). Grey curves indicate Gag-specific TCR nucleotide sequences found in naïve (black, outer circle), memory (blue, outer circle), and GC T_FH (orange, outer circle) populations. No Gag-overlapping clones were detected for one subject, H8 (not shown). (B) Number of Gagspecific TCR clones observed in naïve, memory, and GC T_FH populations. Grey lines link the same patient. Bars indicate means. P-values by two-tailed paired t test. (C) Mean clone size of Gag-specific T cells, HA-specific T cells, and bulk clones of unknown specificity from the GC T_FH population. (D) The number of distinct nucleotide sequences per CDR3 amino acid sequence, of Gag-specific T cells, HA-specific T cells, or bulk GC T_FH cells. Data from all 4 subjects were aggregated for C and D. Error bars indicate SEM. N.S. indicates not significant, *** P < 0.001 by two-tailed t-test.

We found several Gag-specific TCR sequences in the GC T_FH (0 to 7 clones) population. Though we did not have enough data points to reach significance, the overlapping between Gag-specific TCR sequences was minimal in memory T cells (0 or 1 clones), and no Gagspecific sequences were found in the naïve T cell population (Fig. 3B). A similar trend of enrichment of antigen-specific clones in the GC T_FH phenotype was also observed for HAspecific TCR sequences (Fig. S4). This is unsurprising, as these individuals have likely been exposed to influenza infection and/or vaccinated against HA in the past. However, analysis of combined TCR sequencing data from all individuals clearly showed that these Gag-specific GC T_FH cells, but not the HA-specific clones, were highly expanded compared to the bulk GC T_FH cells of unknown specificity (Fig. 3C). Translating these antigen-specific TCR sequences into amino acid sequences showed that the Gag-specific TCR sequences within the GC T_FH population, but not the HA-specific sequences, have a significantly higher degree of coding degeneracy (Fig. 3D). Thus, the Gag-specific GC T_FH cells were preferentially expanded and degenerate. Collectively, these data indicate that Gag-specific T_FH cells respond to antigen stimulation and become selectively expanded in the LNs.

T_FH cells acquire distinct phenotypic characteristics in HIV-infected LNs

To investigate HIV-driven changes on the phenotypic level, we designed a mass cytometry panel to examine phenotypic and functional features of T_FH cells (Table S4). Cryopreserved cervical LNs from 25 Mexican HIV⁺ patients were obtained and analyzed together with cervical, mesenteric, and iliac LNs from 7 local healthy controls (Table S5). To interrogate the functional potential of T_FH cells, three to five million cryopreserved LN cells were thawed and stimulated with phorbol-12-myristate-13-acetate (PMA) and ionomycin in the presence of Brefeldin A and monensin for 5 hours. Cells were then stained with metal-conjugated antibodies and acquired on the mass cytometer CyTOF 2. Bead-based standards were used to correct for machine performance and batch differences (22) (Fig. S5). To broadly define CD4⁺ T cells with T_FH cell features, we performed manual gating to select CD4⁺ T cells positive for CXCR5 and CD45RO staining. GC T_FH cells were further identified by PD-1 and CD57 expression and imported into Cytobank (Fig. 4A, Fig. S6). T-Distributed Stochastic Neighbor Embedding (t-SNE) was performed using the viSNE implementation to create two-dimensional plots that placed cells with similar phenotypic characteristics in close proximity.

Figure 4:

High-dimensional analysis of lymphoid CD4⁺ T cells identified distinct T_FH cell subsets in HIV⁺ patients and healthy controls. (A) Representative gates used to identify GC T_FH cells for t-SNE analysis. (B) t-SNE plots of GC T_FH T cells and CXCR5⁺CD45RO⁺CD4⁺ T cells generated using “cytofkit” package in R. Data include cells from 25 HIV⁺ patients and 7 HC. (C) Phenotypic clusters identified from CXCR5⁺ memory CD4⁺ T cells using DensVM. (D) Heatmap shows the average staining signal of indicated markers within each of the clusters identified in (C). Memory and naïve cells are shown at the bottom of the heatmap for comparison. Red-blue scale indicates staining intensity. Green-brown scale represents the relative frequency of HIV⁺ cells to total numbers of cells in each cluster. (E) The frequency of CD38 expression in CXCR5⁺ T_FH cells or GC T_FH cells from HC (n = 7) or HIV⁺ patients (n = 25). Data are mean ± SEM. ** P < 0.005; *** P < 0.0005 by two-tailed t-test. (F) The frequency of CD57⁺PD1⁺ GC subset within CXCR5⁺ T_FH cells that was positive or negative for CD38 expression (n = 25 HIV). *** P < 0.0005 by paired two-tailed t-test. (G) The relationship between IL-21 expression and CD38 frequency in CXCR5⁺ T_FH cells. (H) The relationship between peripheral CD4⁺ T cell count and IL-21⁺ GC T_FH cells frequency. For G and H, data are from 25 HIV⁺ patients, association was determined by Pearson correlation.

We used contour maps to facilitate visualization of cellular distribution, which clearly showed a different pattern between GC T_FH cells from HC and HIV⁺ patient-derived samples (Fig. 4B). Hypothesizing that HIV can broadly impact T_FH cells beyond the GC subset, we also analyzed other CD4⁺ T cells positive for CXCR5 expression. Similar to the observation with GC T_FH cells, CXCR5⁺ memory CD4⁺ T cells from patient samples occupied regions on the t-SNE map that overlapped with cells from HCs and additional areas that were unique (Fig. 4B). To delineate which T_FH phenotypes were the dominant HIV-related features, we performed DensVM to automatically identify t-SNE clusters in an unbiased fashion (23) (Fig. 4C, Fig. S7). We then generated a heat map to visualize the staining intensity for individual markers and the relative contribution of HC or HIV-derived cells to each clusters (Fig. 4D). This analysis revealed a high abundance of activated CD38⁺ T_FH cells in LN cells from HIV⁺ individuals (clusters 1 and 2). CD38⁺ T_FH cells also co-localized with cells that expressed the highest levels of Ki67, PD-1, ICOS, BCL-6, and IL-21 on the t-SNE maps (Fig. S8). Manual gating for CD38 on total CXCR5⁺ memory CD4⁺ T cell and GC T_FH cells confirmed that T_FH cells from HIV⁺ patients were indeed more highly activated compared to cells from HCs (Fig. 4E). A significantly higher proportion of CD38⁺CXCR5⁺ memory CD4⁺ T cells stained for the GC marker CD57, and the expression of a CD38⁺ activated phenotype additionally correlated with the capacity to produce IL-21 upon T cell stimulation (Fig. 4F-G). While LN location (cervical vs others) may contribute to some differences between cells from HIV⁺ patients and HCs, changes in T_FH cell phenotypes were also related to the severity of HIV infection in cells obtained from the same site. Within the CD57⁺ GC subset from HIV infected cervical LN samples, high IL-21 expression correlated with a higher level of peripheral CD4⁺ T cell depletion by low CD4⁺ T cell count (Fig. 4H). Other clinical features, including viral load or anti-viral treatment at the time of lymph node excision, were not significantly associated with CD38 or IL-21 positivity in GC T_FH cells (Fig. S9). Collectively, high-dimensional T_FH cell analyses identified an activation-related T_FH cell signature in infected LNs characterized by an IL-21 dominant functional phenotype.

HIV infection

As IL-21 plays a key role in B cell selection and differentiation, we further dissected the sequence repertoire, antigen-specificity, and functional potential of IL-21-producing T cells. We adapted the method by Schultz et al. and optimized cell capture using a streptavidin-based scaffold protein to couple anti-IL-21 antibodies onto the surface of memory T cells (Fig. S10) (24, 25). LN cells were incubated with IL-21 capturing complex and Gag peptides for 18 hours and then stained with an IL-21 detection antibody. Individually sorted single IL-21⁺ T cells were processed for TCR beta-chain amplification and sequencing (Fig. 5A) (26, 27). In total, we analyzed TCR sequences from 185 Gag-reactive T cells in four untreated HIV⁺ patients (Table S6, Fig. 5B). Clonally expanded T cells were detected in three out of the four individuals. In samples where clonal expansion was observed, 3.6%, 12.5%, or 24.5% of Gag-reactive T cells express the exact same TCR sequence as that of another cell from the same person, with a single TCR clonotype occupying approximately a tenth of sequence repertoire from IL-21⁺ T cells in two individuals (8.5% and 12.5%, Fig. 5B). These data provided a quantitation of clonotypic diversity of the T cell response to Gag peptides in HIV infected LNs and demonstrated a highly restricted repertoire of IL-21-producing T cells in some HIV⁺ patients.

Figure 5:

Gag-reactive T_FH cells express IL-21 and acquire GC phenotype. (A) Representative plots showing IL-21 staining used to identify Gag-reactive T cells. LN cells were stimulated for 18 hours with vehicle alone (left) or Gag peptides (right). (B) TCRb sequencing of Gag-reactive IL-21⁺ T cells. Each pie chart represents TCR sequences from one individual. Light-gray color represents unique TCRs. Filled-colors represent the fraction of cells expressing a TCR identical to that of another cell in each individual. The number of TCR sequences analyzed is indicated at the center of pie chart. (C) The phenotype of Gag-reactive IL-21⁺ T cells (red) overlaid onto bulk CD4⁺ T cells (gray). (D) The frequency of each indicated phenotypic subset within IL-21⁺ Gag-reactive T cells or IL-21^- bulk memory T cells from HIV⁺ individuals (n = 11). ** P < 0.005, *** P < 0.0005 by two-tailed t-test. (E) Representative plots showing identification of Gagreactive T cells by CD25 and OX40 expression. (F) CD57⁺PD-1⁺ frequency of Gag-reactive T cells from HIV⁺ individuals (n = 6) identified using IL-21 capture or by CD25 and OX40 upregulation. (G) The frequency of CD25⁺OX40⁺CXCR5⁺PD-1⁺ T_FH cells that co-expressed IL-21 following Gag- or HA-peptide stimulation from 6 HIV⁺ individuals. (H) IL-21 expression within GC T_FH subset in LN cells from 11 HIV⁺ patients stimulated by Gag or HA peptides. The lines connect data from the same donor. For F, G, H, * P < 0.05, ** P < 0.005 by paired two-tailed Wilcoxon signed-rank test.

The majority of IL-21⁺ Gag-reactive T cells expressed a classic T_FH cell phenotype, as indicated by high CXCR5, ICOS, and PD-1 expression (Fig. 5C-D). These cells were also enriched for CD57 compared to bulk memory T cells in the same LN (Fig. 5C-D). While we did not detect a significant correlation between CD57 signal intensity and IL-21 frequency on CyTOF analyses (Fig. S11), we additionally identified Gag-reactive T cells in a subset of donors using a cytokine-independent approach (28) and showed that Gag-reactive T cells identified by CD25 and OX40 upregulation were also enriched for CD57 expression (Fig. 5E-F). Taken together, these data indicate that T cell response to HIV antigens alters T_FH cell phenotypes.

Because IL-21⁺ GC T_FH cells were most abundant in patients with more severe HIV infection, we hypothesized that HIV-specific T cells preferentially contributed to the increased IL-21 functional phenotype in the infected lymphoid environment. To test this idea, we compared IL-21 expression between Gag- and HA-reactive T cells from the same donor (Fig. S12). LN-derived T cells specific for each antigen were identified by the CD25⁺OX40⁺ phenotype following peptide stimulation. IL-21-producing cells were measured as a subset of CD25⁺OX40⁺ T_FH cells. Our data showed that significantly more Gag-reactive T_FH cells produced IL-21 compared to the HAreactive T cells (Fig. 5G, average Gag: 14.7% vs HA: 5.7%). As a percentage of GC T_FH cells, Gag peptides also induced a larger IL-21 response compared to HA (Fig. 5H, average Gag: 0.83% vs HA: 0.52%). Taken together, these data indicate that Gag-reactive T cells preferentially acquire a GC phenotype and produce IL-21 during chronic antigen stimulation in infected LNs.

HIV infected is associated with less polyfunctional T_FH cells

While IL-21 is critical for T_FH cell function, we also detected expression of other cytokines on CyTOF (Fig. 4D). These data are consistent with past analyses of pediatric tonsil cells, which revealed an abundance of cellular diversity within T_FH cells that included effector type T_FH cells capable of producing different combinations of IFN-γ, IL-2, TNF-α, or IL-17A (29). To better delineate the impact of HIV infection on the functional diversity of T_FH cells, we performed manual gating to measure the frequency of T_FH cells that produced IL-21, IFN-γ, TNF-α, IL-2, IL4, and granzyme A. We restricted this part of the analyses to the GC subset using strictly defined T_FH cell markers and utilized unstimulated cells to establish the baseline signal for each effector molecule in the absence of T cell activation (Fig. S13). Our data showed positive staining for IFN-γ, TNF-α, IL-2, IL-4, and granzyme A in T_FH cells, but T_FH cells from HIV⁺ patients secreted significantly less IFN-γ and granzyme A compared to HCs (Fig. 6A). While not statistically significant, GC T_FH cells from HIV⁺ patients also secreted less TNF-α and had lower IL-2 production. To validate these observations, we used polychromatic flow cytometry to analyze a second set of samples that included 8 new HIV⁺ patients, 5 additional HCs, and two HCs analyzed previously by CyTOF. GC T_FH cells defined using the same gating strategy by CXCR5, CD45RO, PD-1, and CD57 expression on CD4⁺ T cells also showed an HIV-associated decrease in IFN-γ and granzyme A production (Fig. S14). Collectively, our data revealed changes in T_FH cell subsets that favor IL-21-producing populations in the setting of chronic antigen stimulation.

Figure 6:

Dominant IL-21 expression in T_FH cells correlate with B cell pathology in HIV-infected LNs. (A) The frequency of GC T_FH cells that positively stained for each indicated effector molecule as determined by CyTOF. ** P < 0.005, *** P < 0.0005 by two-tailed t-test (n = 7 HC, 25 HIV). (B) Bar-graph showing the frequency of single-IL-21-producing T cells as a percentage of total IL-21⁺ T cells within each indicated T_FH cell subset. * P < 0.05, ** P < 0.005, *** P < 0.0005 by two-tailed Wilcoxon signed-rank test (PBMCs: n = 4 HC, 16 HIV; LN: n = 6 HC, 25 HIV). (C) Plot shows the correlation between the abundance of single-IL-21⁺ T cells (as a percentage of total IL-21⁺ T cells) in paired PBMC and LN from 4 HC and 15 HIV⁺ individuals. Association is determined by Pearson correlation. (D) IgD⁺CD27^- naïve B cells were excluded (also see Fig. S16). Plots showing gating strategy to identify switched memory B cells (IgDCD38^-) and plasma cells (IgD^-CD38^high) on non-naïve B cells. (E-H) Correlation between switched memory B cell and plasma cells with the abundance of single IL-21⁺ T cells in GC T_FH cells (E-F) or CXCR5⁺CD45RO⁺ CD4⁺ T cells (G-H), n = 7 HC and 25 HIV. Association was measured by Pearson correlation (E and G) or Spearman’s rank correlation (F and H), depending on data normality as determined by D’Agnostina-Pearson test.

Because IL-21 and other effector molecules have overlapping but also distinct patterns of distribution on the t-SNE map (Fig. S8B), next we asked how HIV impacts the effector profile of IL-21⁺ T_FH cells. We used Boolean combination gates to create all possible combinations of IL-21 with other effector molecules stained by CyTOF (IFN-γ, TNF-α, IL-2, IL-4, granzyme A). IL21⁺ cells were then grouped according to the number of additional effector molecules produced. Our data showed a decrease in polyfunctional IL-21⁺ T cells that can produce multiple effector molecules in T_FH cells from HIV⁺ patients compared to controls (Fig. S15). Instead, more dedicated single IL-21-producing T_FH cells were found in HIV⁺ patients (Fig. 6B). To determine whether a similar type of IL-21⁺ cells also circulated in the blood during chronic HIV infection, PBMCs were obtained from a subset of HC and HIV⁺ donors from whom we had paired LN samples. Circulating T_FH cells (cT_FH) were identified as IL-21-producing CD4⁺ T cells according to a recent study by Streeck and colleagues (24). We showed that, similar to cells in the LN, cT_FH cells were more functionally focused on IL-21 expression in HIV⁺ patients, and the abundance of IL-21 single positive cells was tightly associated between lymphoid and circulatory compartments (Fig. 6B-C). Collectively, these data revealed an IL-21-dominant phenotype as a prevailing feature broadly shared by different types of T_FH cells from HIV⁺ patients.

Untreated HIV is associated with defective B cell differentiation. Past studies clearly demonstrated that LNs from HIV⁺ patients contain fewer memory B cells and more plasma cells (3, 4), but how aberrant B cell subset distribution relates to changes in T_FH cells remained unclear. Hypothesizing that IL-21-dominant T_FH cells promote abnormal B cell development, we examined the relationship between the frequency of single IL-21⁺ T_FH cells and B cell phenotype. Memory B cells and plasma cells were identified using the same gating strategy as Perreau et al. (Fig. 6D and Fig. S16) (3). We found that having a low frequency of isotypeswitched memory B cells was associated with more single IL-21-producing cells (Fig. 6E, 6G). A reciprocal relationship was observed for plasma cells, which increased proportionally with single IL-21-producing cells (Fig. 6F, 6H). These data indicate that the accumulation of functionally focused IL-21⁺ T_FH cells is associated with lymphoid B cell pathology during HIV infection.

Discussion

How HIV impacts lymphoid T_FH cells have been studied under limited settings. In part, the challenge has been the inaccessibility of human lymphoid tissues and the tools available to interrogate a small number of cells. Here, we overcame these challenges using LNs obtained for clinical diagnostics from a mostly untreated HIV⁺ cohort. The data described here represent a comprehensive phenotype and TCR analysis of T_FH cells in the LNs, including that of HIVreactive T cells. We also analyzed LN samples from HIV negative HCs, but due to ethical and practical limitations, HC-derived LNs were obtained from different body sites and should be interpreted with this potential caveat. Our data based on TCR repertoire sequencing analyses provided clear evidence for antigen-driven expansion of T_FH cells and selection for certain preferred CDR3 sequences during chronic HIV infection. We further demonstrated these GC T_FH cells acquire a distinct functional phenotype and become dominated by an IL-21⁺ functional subset.

The biological relevance for having different subsets of T_FH cells is just now beginning to be understood. Using IL-21 and IL-4 reporter genes in mice to trace T_FH cells that produce, IL-21, IL-4 or both, Weinstein et al. demonstrated temporal differences in the kinetics of IL-21 and IL-4 production and showed that IL-21⁺, IL-21⁺IL-4⁺, and IL-4⁺ T_FH cells each provide specialized follicular helper function and support distinct aspects of B cell function and development (30). Here, we also detected various functional T_FH cell subsets in healthy human LNs and showed that T cells identified using the classic T_FH lineage markers have the potential to secrete many distinct types of effector molecules. Our data is consistent with the diversity of functional phenotypes previously observed in tonsils (29), and highlights the heterogeneity of T_FH cells at a healthy baseline.

We used HIV infection to ask how prolonged antigen stimulation alters the composition of T_FH cells in the LN. In vitro studies have suggested that T_FH cells could become inhibited in the context of chronic inflammation and fail to activate appropriately to TCR stimulation via induction of PD-1 mediated inhibitory signals (7). The increase in T_FH cells could then be explained by an overabundance of cytokine signals in HIV-infected LNs that activated T cells in an antigen-independent fashion (12, 13). While our data do not rule out a contribution from bystander T cell expansion, our data are most consistent with the model where T_FH cell pathology, manifested as clonal expansion and reduced polyfunctionality, is primarily an antigen-driven process. By TCR repertoire sequencing, we showed that certain TCR clonotypes become expanded within GC T_FH cells. Notably, a small portion of HIV-specific clones harbor distinct nucleotide sequences that converge to the same amino acid sequence – a signature of antigendriven selection. Convergent selection of TCR sequences is expected only when there is external pressure to select for certain CDR3 binding motifs. These data provide strong evidence for an antigen-driven process and additionally suggest that B cells, in their capacity as antigenpresenting cells, also shape the composition of T_FH cells. We measured the extent of clonal restriction by single cell TCR sequencing. We found different clonal frequencies in Gag-reactive IL-21⁺ T cells between different HIV⁺ patients, with expanded clones occupying a significant proportion of Gag-reactive response in some individuals. While we did not evaluate Envreactivity directly, reduced TCR diversity will likely also impact T cells that recognize other HIV antigens. How T_FH cell repertoire relates to the selection of protective and/or neutralizing antibody responses remains poorly understood. The density of peptide-MHC complexes presented by competing B cells clearly determines the magnitude of T cell help (31–33), but the diversification of antigenic variants by viral mutation provides an additional layer of complexity in the selection of relevant B cells during chronic HIV infection (34). Previous studies have shown that early HIV Env gene diversity predicts development of antibody breadth (35). This raised the possibility that a diverse repertoire of HIV-specific T_FH cells may be necessary to capture the breadth of viral variants, and an oligoclonal T_FH population that focuses T cell reactivity to nonproductive but common antigenic viral sequences may neglect rare B cells that have neutralizing potential. Future studies to determine if individuals with more diverse HIV-specific T_FH cell repertoire are more successful at generating broadly neutralizing antibodies will provide additional insights.

One important open question is why an excess of expanded T_FH cells in the LNs fails to provide superior B cell help during chronic HIV infection. Our data provided evidence that HIV infection alters the functional quality of T_FH cells and shifts T_FH cells toward an IL-21-dominant subset. In support of an antigen-dependent model of T cell activation, Gag-reactive T cells preferentially acquire GC features and secrete IL-21, indicating that HIV-reactive T cells directly contributed to altered T_FH cell phenotype in infected LNs. In addition, as the majority of GC T_FH cells also acquire an altered phenotype, there are likely other secondary effects of HIV infection that extend beyond HIV-specific T cells. Notably, IL-21⁺ T_FH cells in HIV infected LNs produce less of other types of cytokines. This IL-21-focused T_FH cell subset could represent a more differentiated T_FH cell population in response to persistent antigen stimulation. However, as having more IL-21⁺ T_FH cells in the LN was associated with severe HIV infection and aberrant B cell distribution, the accumulation of IL-21⁺ T_FH cells is likely counterproductive in the setting of HIV infection. The notion that an excess of the IL-21-producing subset could contribute to HIVrelated B cell changes is consistent with previous studies in mice that showed IL-21 is required to maintain BCL-6 expression in B cells and promotes plasma cells differentiation (30, 36, 37). Changes in B cell subsets could also result from a relative decrease in other T_FH cell subsets, which would agree with recent studies that showed specialization of T_FH cell subsets in regulating distinct aspects of B cell differentiation (34). Finally, whether having a highly specialized population of clonally restricted T_FH cells could divert T cell help to unprotective B cells remains to be determined.

We have defined the TCR and phenotypic repertoire of T_FH cells during chronic HIV stimulation. Our work highlights an antigen-driven process that alters the composition of T_FH cells in the lymphoid compartment. Collectively, our data suggest that in addition to the size of the germinal center reaction, the functional profile and the compositional complexity of T_FH cells are additional key measurements that could impact the quality of T_FH cell responses to vaccines and infections.

Material and Methods

Study Design

The goal of the study was to define T_FH cell diversity in primary human LNs. All samples were de-identified and obtained with IRB approval from the University of Pennsylvania. Subject characteristics are shown in Table S5. Please see the Supplementary Materials for details on sample collection.

CyTOF staining and data analyses

Cryopreserved cells were thawed and stained with metal-conjugated antibody panel (Table S4), following a 5 hour stimulation with PMA and ionomycin in the presence monensin and Brefeldin A. Antibody stained cells were mixed with normalization beads and acquired on CyTOF 2. Bead standards were used to normalize CyTOF runs with the Matlab-based Nolan lab normalizer. Data analyses were performed using Cytobank and “cytofkit” package in R.

TCRβ sequencing and analyses

TCR sequences from single cells were obtained by a series of three nested PCR reactions as previously described (26, 27). TCR junctional region analysis was performed using IMGT/VQuest. For bulk cell analyses, TCR library generation and raw sequence processing were performed using MIDs with primers listed in Table S1. (18, 19).

Statistical Methods

Assessment of normality was performed using D’Agostino-Pearson test. Pearson or Spearman correlation was used depending on the normality of the data to measure the degree of association. The best-fitting line was calculated using least squares fit regression. Statistical comparisons were performed using two-tailed Student’s t-test or Wilcoxon signed-rank test, using a p-value of <0.05 as a cutoff to determine statistical significance. Multiple-way comparisons were corrected using Holm-Sidak method. Statistical analyses were performed using GraphPad Prism. Please see the Supplementary Materials for detailed methods on T cell staining for phenotypic characterization and TCR sequencing experiments and data analysis.