Introduction

Despite options for testing and treatment, progress against HIV is slowing, emphasizing the urgent need for an HIV vaccine(Fauci 2017, Eisinger and Fauci 2018). While advances have been made in immunogen design and vaccine approaches, the main challenge lies in generating durable, high-affinity antibodies against the HIV-1 Envelope (Env) glycoprotein, crucial for protection. To design a vaccine that confers long-term protective immunity, effective stimulation of CD4 T follicular helper (T_fh) cells is essential, as they provide vital costimulatory and cytokine support to B cells within germinal centers (GC), leading to the production of persistent antibodies following immunization (Slifka, Antia et al. 1998, Crotty 2014). T_fh cells possess distinctive T_h1, T_h2, and T_h17-type cell attributes, programmed by the inflammatory response during the T-cell priming phase, with each T_fh subset differentially contributing to GC B cell proliferation, survival, and differentiation (Morita, Schmitt et al. 2011, Barbet, Sander et al. 2018) (Gao, Luo et al. 2023). Therefore, in addition to antigen selection, promoting the differentiation and expansion of optimal T_fh subsets to generate potent and enduring humoral immunity is critical for vaccine design. Guiding the type of adaptive response to produce the most effective forms of immunity for each specific pathogen achieve qualitative alteration of the immune response. For vaccines currently under development, adjuvants are increasingly used to promote types of immunity not effectively generated by the nonadjuvanted antigens. For example, adjuvants have been used in preclinical and clinical studies to: (1) provide functionally appropriate types of immune response (e.g., T helper 1 [T_h1] cell versus T_h2 cell, CD8⁺ versus CD4⁺ T cells, specific antibody isotypes). Clinical studies have demonstrated that booster immunization with a T_h1 glucopyranosyl lipid adjuvant-stable emulsion (GLA-SE)-formulated malaria antigen leads to enhanced antibodies at memory time points compared to an aluminum adjuvanted vaccine(Hill, Pierson et al. 2019). We demonstrated that promoting the induction of T_fh1 cells by utilizing interferon-induced protein (IP)10, a ligand for and an inducer of CXCR3, as a molecular adjuvant to a DNA vaccine (DNAIP10) followed by boosting with protein adjuvanted with Army Liposome Formulation (ALFQ) consisting of liposomal monophosphoryl lipid A (MPLA) plus a saponin derivative, QS-21 (Alving, Peachman et al. 2012, Rao, Onkar et al. 2018) enhanced GC responses, increased HIV anti-Env binding antibodies, and stimulated significantly higher cross-clade reactivity with increased specificity to V1V2 conformational epitopes, and higher avidity (Verma, Schmidt et al. 2019). Similarly, a recent macaque study utilizing Clade C DNA+GLA-SE adjuvanted Env protein immunization revealed that frequencies of Env-specific CD28+ IFNγ+ cells, indicative of T_h1 responses, correlated with the development of Env antibodies following the final immunization (Felber, Lu et al. 2020).

In addition to IFNγ, interleukin 17 (IL-17) has been shown to enhance cognate T-B cell interactions, leading to an effective GC response (Moyron-Quiroz, Rangel-Moreno et al. 2004, Mitsdoerffer, Lee et al. 2010, Kumar, Chen et al. 2013). Studies conducted in mice have further demonstrated that T_fh17 cells support efficient antibody recall responses (Gao, Luo et al. 2023). Notably, the persistence of peripheral T_fh17 cells specific to measles has been observed in adults who have received the live attenuated measles virus vaccine (LAMV) during childhood, suggesting that measles vaccine triggers T_fh17 responses which persist beyond the GC phase (Gao, Luo et al. 2023). Intriguingly, earlier studies exploring peripheral CD4 T cell determinants of serological memory elicited by LAMV have led to the hypothesis that LAMV promotes both T_h1 and T_h2 CD4 differentiation programs, based on production of IFNγ⁺ and IL-4, which are cytokines also produced by T_fh cells (Ovsyannikova, Dhiman et al. 2003) (Ward and Griffin 1993, Ovsyannikova, Reid et al. 2003). However, our understanding of the GC T_fh cell response to LAMV, which plays a crucial role in establishing long-term immunity against measles, remains incomplete.

In this study, based on GC T_fh profiles evoked by LAMV, we explored the potential of a T_fh1 or mixed T_fh1/17 targeted vaccine to enhance HIV-1 Env antibodies in rhesus macaques using an DNA-prime/protein boost approach. After booster immunization with a Clade C gp140 protein formulated in CAF01(Wørzner, Hvannastein et al. 2021), a cationic liposome-based formulation, we observed the generation of T_fh1/17 cells within GCs, while T_fh1 cells were induced when monophosphoryl lipid A (MPLA)+QS-21 was used as the adjuvant. Notably, stimulating T_fh1 cell induction with MPLA resulted in significantly greater antibody persistence at week 8 and up to 30 weeks after the final immunization. Moreover, the T_fh1 regimen with MPLA adjuvant led to higher tier 1 neutralization titers, increased levels of IgG1 subclass antibodies, and improved antibody effector functions. These findings highlight a unique potential of T_fh1 cells in promoting humoral immunity against HIV and suggest that vaccine strategies maximizing T_fh1 cell induction may hold promise for eliciting durable protective immunity against HIV.

Results

GC T_fh1 and GC T_fh17 cells recalled by measles booster

To decipher the specific T_h subset of T_fh cells contributing to the establishment of durable serological memory, we employed live attenuated measles virus vaccine (LAMV) as a model and investigated T_fh responses in peripheral blood and lymph nodes (LN) in a cohort of 16 healthy adult female rhesus macaques (Figure 1A). Consistent with documented evidence of long-term persistence of the memory B cell response to LAMV, rapid recall of measles virus (MeV) IgG ensued at week 2 post LAMV, irrespective of the booster interval (Figure 1B). By week 20, MeV IgG concentrations displayed a 2.6-fold increase compared to baseline, signifying the efficacy of LAMV booster in generating persistent antibodies. These augmented levels of memory antibodies were accompanied by enhanced antibody avidity (Figure 1C), underscoring robustness of the humoral immune response elicited by LAMV.

Figure 1.

Tracking MeV-specific T_fh cells using the activation-induced marker (AIM) assay showed induction of peripheral (p)T_fh cells at day 7 post-vaccination (Fig Supplementary Figure 1A). Confirming T_fh cell induction in response to LAMV, activated pT_fh cells, identified by co-expression of ICOS and Ki-67, were transiently upregulated at day 7 (Fig 1D, Supplementary Figure 1B). These responding pT_fh cells were PD-1+ and their frequencies at day 7, but not day 0, significantly correlated with MeV IgG at Week 20 (Fig 1E). We next proceeded to analyze heterogeneity within pT_fh cells with respect to expression of T_h1/2/17 chemokine receptors. Our temporal analysis of the responding pT_fh compartment demonstrated significant induction of CXCR3+ T_fh1 cells at day 7 (Fig 1F). In contrast, we observed a decrease in frequencies of CCR4-expresisng pT_fh2 subsets and CCR6-expressing pT_fh17 subsets. Utilizing Boolean analysis, we further identified that the majority of responding pT_fh cells expressed CXCR3, indicating induction of pT_fh1 cells in response to LAMV (Fig 1G).

Expanding our investigation to include phenotypic and molecular features of CXCR5⁺ PD-1⁺⁺ GC T_fh cells (Fig 1H, Supplementary Figure 1C), we found predominance of CXCR3 expression within the GC T_fh population. Additionally, we observed that up to 25% of GC T_fh cells expressed CCR6. Notably, our analysis did not reveal substantial expression of CCR4 within GC T_fh cells. Molecular analysis of sorted CXCR5+ PD-1+/++ LN T_fh cells (Supplementary Figure 1D) further provided insights into their functional specialization, with the induction of key transcription factors BATF and IRF4, as well as the expression of chemokine receptors CCR5 and CCR6, indicating the activation of T_h1 and T_h17 programs within GC T_fh cells (Figure 1J-K). Collectively, these findings demonstrate that both blood and GC T_fh cells, during the peak effector response following LAMV immunization, exhibit a predominant T_fh1 helper bias, with GC T_fh cells also demonstrating a T_fh17 bias.

HIV-1 vaccine modalities for inducing GC T_fh1 and GC T_fh17 subsets

Building on our observations made with LAMV, we next investigated the potential of fine-tuning T_fh responses towards T_fh1 and T_fh17 profiles for generation of persistent anti-HIV-1 Env antibodies. We immunized two cohorts of rhesus macaques against HIV Env using a DNA prime and protein boost vaccination strategy tailored towards either a T_fh1 (n=6) or mixed T_fh1/17 (n=6) response (Figure Supplementary Figure 2). For both vaccine regimens, animals received an initial intradermal DNA prime vaccine encoding HIV-1 Env gp160 (C.1086C) at weeks 0, 4, 8, followed by an subcutaneous HIV C.ZA 1197MB Env gp140 protein boost vaccination at weeks 12 and 20. To tailor vaccine induced T_fh responses, we included additional T_fh polarizing factors with DNA prime vaccines encoding for cytokines IP-10 (T_fh1 regimen) or IP-10 and IL-6 (mixed T_fh1/17 regimen), coupled with corresponding gp140 protein boost formulated in either the T_h1 polarizing adjuvants, MPLA+QS-21, or the T_h1/17 polarizing CAF01 adjuvant platform, respectively. Over the course of both the priming and boost stages, we performed routine collection of both blood and rectal secretions from animals to assess the extent of systemic and mucosal humoral immunity elicited by the two regimens. Additionally, we collected inguinal LN biopsies and fine needle aspirates of LN (FNA) at baseline, during the DNA prime stage, and following both protein boost to comprehensively characterize vaccine-elicited GC T_fh responses in draining LNs. GC responses typically peak between 2-3 weeks post first booster with more rapid recall kinetics after the second booster (Iyer, Gangadhara et al. 2015). Our rationale for sampling LN 3 weeks following the 2^nd booster was to assess whether the reported effects of CAF01 on sustained antigen release might result in GC persistence (Henriksen-Lacey, Christensen et al. 2011, Pedersen, Wørzner et al. 2020).

Induction of Robust T Cell Activation in GCs with HIV-1 Env Formulated in CAF01 and MPLA+QS-21 Adjuvants

To gain insights into LN T_fh responses induced by MPLA and CAF01 platforms, we utilized complementary approaches of situ protein expression analysis of GCs and RNA sequencing of Env-stimulated CD95+ CD4 T cells of selected animals in each vaccine group (Figure 2A).To track immunological changes within GCs, we applied the GeoMx Digital Spatial Profiler to assess protein expression of key immune targets longitudinally at baseline (BL, prior to DNA immunization), week 2 of protein 1 (P1w2) and week 3 of protein 2 (P2w3). We stained tissue sections with morphological markers (CD20, CD3, Ki-67) and collected circular regions of interest (ROI) based on co-localization of CD3 with CD20+ Ki-67+ GC B cells. For each tissue, two to three ROIs were selected to ensure adequate representation of GCs within each animal. This approach allowed us to accurately identify GCs and analyze protein expression of both T and B cells within these specific regions (Figure 2B).

Figure 2.

Thirty-two protein targets were profiled simultaneously, along with isotype controls (Ms IgG1, Ms IgG2A, Rb IgG) and housekeeping proteins (S6, Histone H3, GAPDH). After applying quality control measures, we calculated the signal-to-noise ratio for each target which provided robust assessment of protein expression levels (Supplementary Figure 3A-d). CD45 and B2M were among the most abundantly expressed proteins while LAG3 and PD-L1 demonstrated low signal expression. To address variations in ROI surface area and tissue quality, normalized protein expression (NPE) was calculated for each protein. NPE analysis revealed robust expression of key lineage proteins, CD45, CD20, CD3, CD4, and CD8, as well as GC markers PD-1 and Ki-67 within ROIs (Figure 2C). We observed notable associations between protein expression patterns within the GC microenvironment; specifically, a strong correlation between the expression of CD4 and CD20 was observed (Supplementary Figure 3E). Furthermore, a significant association between the co-stimulatory molecule 4-1BB and CD4 expression (Supplementary Figure 3F) was observed within the GC. Association of the innate immune protein stimulator of interferon genes (STING) with both 4-1BB and CD4 expression suggested a potential interplay between innate and adaptive immune pathways within the context of GC responses. Altogether, the protein expression data provide evidence for coordinated expression of key proteins involved in GC function in both vaccine groups (Supplementary Figure 3G).

To identify specific proteins and pathways activated in response to vaccination, we performed differential expression analysis on a per-protein basis. We modeled NPE using a linear mixed-effect model (LMM), which allowed us to account for sampling multiple ROIs per tissue within each animal (FDR p value cut-off, < 0.05). Volcano plots illustrate proteins induced at P1w2 (Figure 2D) and P2w3 (Figure 2E) following vaccination. Induction of 4-1BB, ICOS, PD-1, CD44 post boost indicated activation of T cells to antigen stimulation within GCs in both vaccine groups (Figure 2F). The higher relative expression of these proteins at P2w3 was consistent with the reported effects of CAF01 in GC persistence. We found that expression of the checkpoint inhibitors CTLA4 and PD-L1 was significantly reduced post CAF01 vaccination, while CD4 expression increased. In contrast, expression of the regulatory enzyme, IDO1; checkpoint inhibitor, PD-L2; and CD256 (B7-H3), and the innate sensor, STING, was significantly higher post vaccination in the MPLA group (Figure 2D-E, G).

Across vaccine regimens, significant differences were observed at P1w2 (Figure 2H). Significantly higher expression of Ki-67 with MPLA compared to CAF01 was suggestive of a more rapid GC response (Figure 2H). Furthermore, the check point inhibitory receptors LAG3, CTLA4, as well as IDO1, exhibited higher expression levels with MPLA at P1w2. Importantly, no significant differences were observed at BL, validating the specificity of immune activation to vaccination. Altogether, the in-situ protein analysis indicated robust induction of GC responses across vaccine platforms with distinct qualitative and quantitative effects initiated by MPLA versus CAF01 suggesting potential differences in regulatory mechanisms and immune activation pathways between the vaccine regimens.

T_h1 molecular programs potentiated by HIV-1 Env/MPLA+QS-21

To assess the extent of T_h1/T_h17 programming in CD4 T cells induced by vaccination, we profiled the transcriptome of CD95+ CD4 T cells isolated from the LN. We sort purified and RNA sequenced naive (CD95-) and CD95+ CD4 T cells at BL, P1w2, and P2w3 following overnight stimulation with HIV-1 Clade C Env peptide pools. A total of 18 samples per group, which included three biological replicates per subset, were sequenced in parallel resulting in over 25 million high-quality reads per sample (Figures 3A, Supplementary Figure S4A-B). The transcriptomes of naive versus CD95+ CD4 T cells post immunization, in alignment with their distinctive biological states, exhibited clear demarcations along distinct dimensions within the principal component analysis (PCA) plot (Figure 3B). Transcription factors (TF) involved in regulating distinct cellular differentiation programs were enriched in CD95+ CD4 T cells at P1w2 and P2w3. These included HOPX, IKZF2, PRDM1, RUNX2, associated with effector differentiation. Additionally, TF such as BATF, BCL6, BHLHE40, EGR2, and TOX2 involved in T_fh differentiation were also identified. Furthermore, we identified genes regulating T_h1 (STAT1, TBX21, EOMES), T_h17 (AHR), and Treg (FOXP3, NR4A2) programs. Moreover, the expression of interferon regulatory factors (IRFs) controlling T cell differentiation (IRF1, IRF5, IRF8) was observed, demonstrating that CD95+ cells post vaccination encompassed effector and fully differentiated CD4 T cell subsets (Figure 3C).

Figure 3.

We first assessed temporal changes in gene expression by focusing on differentially expressed genes (DEGs) within CD95+ cells at P1w2 and P2w3, compared to BL (Venn diagram in 3D). Notably, a significantly higher level of transcriptional perturbation was observed in response to CAF01, particularly at P2w3, within both naive and CD95+ CD4 T cells (top bubble plot in 3D, S4C), suggesting that CAF01 induces extensive gene expression changes in a cell-extrinsic manner. By specifically examining genes induced exclusively in CD95+ cells, but not naive cells, at P1w2, we made several observations. The T_h1 transcriptional regulator STAT1, as well as IFNγ-induced genes such as IRF7, IRF8, IFI30, XAF-1, and CXCL11, were among the most highly expressed genes in MPLA (bottom bubble plot, 3D), highlighting the activation of T_h1 programs following vaccination. Indeed, interrogation of top 3 eniched pathways utilizing the Reactome database (Fabregat, Sidiropoulos et al. 2017) revealed that genes encompassing IFNγ, IL-7, and IL-10 signaling networks were induced with MPLA at P1w2. In the CAF01 group, we observed enrichment of co-stimulatory molecules TNFRSF8 (CD30) and TNFRS13B (TACI), expressed by activated T cells, along with expression of the anti-apoptotic molecule BCL-2 and the transcription factor Foxp3.

Analysis of genes downregulated showed pathways regulating cell cycle inhibitors p21 and p53 were enriched with MPLA while pathways regulating cellular responses to stimuli and stress were downregulated with CAF01 (Figure 3E). Collectively, transcriptional profiles demonstrated activation of effector programs within CD4 T cells with common and unique pathways induced across vaccine platforms.

Consistent with this, CD95⁺ CD4 T cells at P1w2 and P2w3 exhibited notable clustering patterns across vaccine regimens. Particularly, tighter, and more distinct clusters were observed at P1w2 compared to P2w3 notably with CAF01 (Figures 3F, Supplementary Figure 4D-E). Exploration of genes regulating T_h1 and T_h17 programs within CD95+ CD4 T cells at P1w2 showed that CD95+ CD4 T cells in both MPLA and CAF01 groups exhibited overlapping expression profiles, with genes regulating major classes of cytokine-cytokine receptor interactions represented. The MPLA group exhibited higher expression levels of IFN-induced chemokines CXCL10 and CXCL11, IL1 family members IL18 and IL1RAP, IL15 family members IL15 and IL15RA, as well as TNF cytokine family members FAS, TNFα, TNFRSF8 (CD30), and TNFRSF9 (4-1BB) (Figure 3G-H, Supplementary Figure 4F).

In contrast, the CAF01 group demonstrated expression of the T_h17 receptor IL23R, along with TNF family members FASLG, TNFRSF13B (TACI), TNFRSF11 (RANKL), and TNFRSF12 (DR3) within CD95+ cells with higher relative expression of IL17A observed with CAF01, indicative of T_h17 responses (Figure 3I, Supplementary Figure 4G). Collectively, this gene-level analysis indicated strong engagement of T_h1 molecular programs within LN CD4 T cells with MPLA.

Phenotypically and functionally specialized GC T_fh1 / T_fh17 subsets elicited with HIV-1 Env Formulated in CAF01 and MPLA+QS-21 Adjuvants

After confirming the robust induction of GC responses by both vaccines and observing distinct molecular programs in CD4 T cells, we proceeded to investigate the phenotypic and functional characteristics of T_fh cells. We examined the GC T_fh cell subset characterized by the expression of CXCR5 and high levels of PD-1, using the gating strategy outlined in Supplementary Figure 5A. Our analysis of the lymph nodes revealed an increase in the frequencies of GC T_fh cells following each protein boost in both groups compared to baseline. Importantly, there were no statistically significant differences observed between the two adjuvant platforms, as shown in Figure 4A. We further examined the frequencies of T_fh cells characterized by the expression of CXCR5 and PD-1 (CXCR5+ PD-1+), which also exhibited a significant increase following the first protein boost in both groups (Supplementary Figure 5B).

Figure 4.

To gain insights into the T_fh helper profiles within the GC, we assessed the expression of CXCR3 (T_fh1) and CCR6 (T_fh17) on the GC T_fh cells. Both adjuvants induced GC T_fh1 cells, as evidenced by the expression of CXCR3. However, a selective increase in GC T_fh1/17 cells was observed with CAF01, as shown in Figure 4B. While the frequencies of GC T_fh17 cells did not show a significant increase following immunization, Boolean analysis revealed a higher relative proportion of this subset with CAF01, along with a corresponding higher proportion of GC T_fh1 subset with MPLA at P1w2, as demonstrated in Figure 4C.

Following the observed induction of LN T_fh1 responses, we quantified the Env-specific CD4 T cell response using intracellular cytokine staining (ICS). The analysis revealed higher relative frequencies of Env-specific T_fh cells and Env-specific CXCR5-CD4 T cells producing IFNγ with MPLA compared to CAF01 (Supplementary Figure 5C). To obtain a more comprehensive understanding of the cytokine profile within the LN T_fh1 and T_fh17 subsets, we assessed cytokine production after PMA/Ionomycin stimulation (Figure 4D). By utilizing the discrete expression patterns of CXCR3 and CCR6 on CXCR5+ CD4 T cells in the LN, in conjunction with the canonical cytokines IFNγ (T_h1), IL-17 (T_h17), and IL-21 (T_fh), we made several important observations. Firstly, we found that within the T_fh1 subset, IL-21+ IFNγ+ co-producing cells were more abundant, and their levels were significantly increased with MPLA stimulation (Figure 4E). Conversely, within the T_fh17 subset, we observed that IL-21+ IL-17+ co-producing cells were more abundant, and their levels were significantly higher in the CAF01 group. Notably, the T_fh1/17 subset demonstrated the highest degree of polyfunctionality, as evidenced by the production of multiple cytokines.

We further analyzed the cytokine profiles by gating IFNγ and IL-21 co-producers versus IL-21 single producers. This analysis revealed that both subsets, T_fh1 and T_fh17, produced IL-2 and TNFα. However, IL-17 production was predominantly observed in IFNγ-negative, IL-21+ cells (Supplementary Figure 5D). To assess systemic levels of IL-21, we measured serum IL-21. We found a significant induction of IL-21 in both vaccine groups at day 7 post-immunization, with no observable differences observed across the adjuvant platforms (Supplementary Figure 5E). This suggests that the induction of IL-21 is a common feature of both vaccine formulations. Overall, these findings suggest that MPLA preferentially induces the production of IL-21+ IFNγ+ cells within the T_fh1 subset, while CAF01 promotes the generation of IL-21+ IL-17+ cells within the T_fh17 subset. Furthermore, the T_fh1/17 subset exhibits the most diverse cytokine production profile among the subsets examined.

To investigate whether the effects of MPLA versus CAF01 adjuvants were also evident in circulating T_fh counterparts, we assessed pT_fh responses. We observed a significant increase in proliferating pT_fh cells, with a predominant induction of pT_fh1 cells similar to the phenotype observed in the LN, when MPLA was used as the adjuvant (Figure 4F). In contrast, no evidence of a T_fh17 or T_fh1/17 bias in pT_fh cells was observed with CAF01 (data not shown).

To evaluate Env-specific T_fh cell abundance, we utilized the AIM assay (Supplementary Figure 5F). The analysis showed a higher relative induction of Env-specific T_fh responses with MPLA at P1w1 but not P2w1 (Figure 4G), which was further corroborated by ICS assays (Figure 4H). The frequencies of CXCR5+ cells co-producing IL-2 and IFNγ, as well as cells co-producing IL-21 and IFNγ, indicated that higher numbers of IFNγ+ Env-specific pT_fh cells were induced with MPLA at P1w1 and P2w1 (Figure 4I). Therefore, formulation of gp140 with MPLA induced strong T_h1-polarized GC T_fh responses, characterized by a higher magnitude of IFNγ+ anti-Env T_fh cells.

Induction of persistent anti-Env IgG antibodies with HIV-1 Env/MPLA+QS-21

We next sought to determine whether induction of higher frequencies of Env-specific T_fh1 cells with MPLA could effectively enhance B cell proliferation and differentiation, in turn, promoting the development of Env antibodies with heightened affinity and increased durability. To this end, we performed a wide repertoire of quantitative and functional assays to assess the magnitude, durability, affinity, avidity, breadth, and effector functionality of vaccine induced humoral responses to Env. Longitudinal measures of binding antibody concentrations in sera against C.1086 Env showed rapid and equivalent recall in all animals post P1, with antibodies reaching peak levels after the 2^nd protein boost. While antibody kinetics were comparable across vaccine groups, significantly higher antibody magnitude was elicited by MPLA at week 8 post 2^nd boost and until 30 weeks after final immunization (Figure 5A). At this protracted memory time point, serum antibody concentrations were, on average, 2.5-fold higher with MPLA (median [ng/ml]; MPLA, 5566 versus CAF01, 2155) (Figure 5B). To assess CD4 correlates of antibody durability, we asked whether the magnitude of vaccine-elicited GC T_fh subsets after each boost predicted antibody concentrations at week 30. Two key cellular determinants of antibody durability emerged from our analysis: GC T_fh1 cell magnitude (p < 0.05, r=0.65) (Figure 5C) and frequencies of IFNγ+ IL-2+ Env-specific LN T_fh cells (p < 0.05, r = 0.62) (Figure 5D). These data in concert with IFNγ-regulated molecular programs induced in LN CD4 T cells support a role for GC T_fh1 induction in antibody persistence.

Figure 5.

Using a binding antibody multiplex assay (BAMA), we further confirmed that stronger memory responses were elicited by MPLA evidenced by higher median serum IgG antibody concentrations to C.1086 gp140 and gp120 antigens measured as area-under-the curve (AUC) over time (Figure 5E-F). Thus, utilizing two orthogonal approaches, the data showed significantly higher and protracted serum antibody responses against autologous Env with MPLA, indicative of efficient T_fh cell mediated B cell recruitment into the long-lived plasma cell pool.

We next sought to understand if T_fh1 profile was also associated with improved Env antibody breadth. Therefore, we tested serum reactivity against an antigen panel comprising of consensus gp140 proteins and found that antibodies with higher cross-clade reactivity were induced with MPLA relative to CAF01 (Figure 5G-H). We extended these analyses to assess reactivity to V1V2 loops of 1086C and noted that antibodies with significantly higher specificity to these important regions within Env were induced in both vaccine regimens (Figure 5I).

Having established induction of robust serum Env antibodies with MPLA, we next determined whether Env-specific IgG reactivity would also be higher within rectal secretions. After normalization for total IgG levels within rectal secretions, the data showed that Env antibodies were effectively recalled in most animals at week 2 post 2^nd protein boost and persisted in all animals 8 weeks after final immunization. However, akin to the systemic compartment, gp140 IgG in rectal secretions were significantly higher with MPLA at memory time point (Figure 5J), with 6-fold higher levels in MPLA relative to CAF01 at week 8 after final immunization (Figure 5K). In both vaccine regimens, the induction of Env-IgA antibodies was poor, preventing a quantitative assessment of IgA responses in secretions.

Induction of IgG1 subclass antibodies with greater effector functions with HIV-1 Env/MPLA+QS-21

Since antibody effector functions, facilitated by interaction of Ig constant region with cognate Fc receptors on innate cells, mediate protection from acquisition and viral control (Carpenter and Ackerman 2020), we assessed the IgG subclass profile at week 2 post 2^nd protein boost. Both CAF01 and MPLA+QS-21 induced Env-specific IgG1, and modest levels of IgG2, and IgG4 isotypes with higher IgG1 in all animals, with exception of one animal with higher IgG4 (S6).

Significantly higher IgG1 was induced by MPLA relative to CAF01 (Figure 6A), while IgG2 and IgG4 antibody subclasses were comparably induced (Figure 6B-C). The improved IgG1 subtype antibody responses with MPLA prompted us to determine whether a corresponding increase in antibody effector functions might also be observed. Measurement of antibody-dependent phagocytosis (ADP) suggested enhanced effector functions with MPLA (Figure 6D-E) which strongly correlated with Env IgG1 but not IgG2 or IgG4 (Figure 6F).

Figure 6.

Finally, we observed higher levels of neutralizing antibodies against the tier 1A MW965.26 at peak (2 weeks post 2^nd protein boost) with MPLA relative to the CAF01 platform (Figure 6G). Antibody avidity measurements revealed relatively higher avidity with MPLA against autologous Env including V1V2 loops and to consensus Env proteins (Figure 6H-L). Collectively, these findings provide compelling evidence for significantly increased antibody quality associated with induction of GC T_fh1 cells.

Differentiation of GC T_fh Subsets initiated during the DNA Priming Phase

Finally, we sought to determine the degree to which T_fh responses elicited during the priming phase influenced antibody responses post 1^st protein boost. To this end, we analyzed blood samples at weeks 0, 1, 2, and 4, while also evaluating FNA of the draining LN at week 2 after the 3^rd DNA prime (Figure 7A).

Figure 7.

Animals were immunized with C.1086 DNA expressing IP10 (DNAIP10) which primes stronger GC T_fh responses relative to DNA-alone (Verma, Schmidt et al. 2019). To further enhance GC T_fh responses, beyond that induced by DNAIP10, we engineered DNAIP10 to co-express IL-6, a key cytokine promoting T_fh differentiation. Our vector achieved coordinate expression of Gag and Env antigens together with IP10+IL6 as confirmed in transfected 293T cells (Figure 7B). Following three rounds of intradermal immunization with DNAIP10 or DNAIP10+IL6, we assessed proliferating pT_fh cells (Ki-67⁺ PD-1⁺ of CXCR5+ CD4 T cells in blood, 7C). We observed a significant increase at weeks 1 and 2 with DNAIP10+IL6 but not DNAIP10 indicating that IP10+IL6 incorporation promoted T_fh differentiation. Additionally, T_fh induction was accompanied by notable T_fh1 skewing within proliferating pT_fh cells (median pT_fh1 at day 0 (% CD95), 0.89% versus 1.48% at day 7 and 14). Measurement of antigen-specific responses by AIM assay demonstrated induction of Env and Gag-specific pT_fh cells with a trend for higher responses elicited by DNAIP10+IL6 (median, 0.42%, IQR 0.3-1.7%) relative to DIP10 (median, 0.12%; IQR: 0.04 – 1.4%, Supplementary Figure 7).

Based on the transient accumulation of pT_fh cells in the blood, we further explored GC T_fh responses. Out of twelve collected FNAs, eight were successful (four per vaccine group), and demonstrated significant increase in GC T_fh frequencies following vaccination (Figure 7D). Gating on Ki-67+ cells encompassing both CXCR5+ PD-1+ and PD-1++ subsets, an increase in activated T_fh cells within the LN was observed (Figure 7E), accompanied by a corresponding increase in the T_fh1 subset (Figure 7F). Altogether, these data demonstrate induction of GC T_fh1 responses during the priming phase post immunization with DNAIP10 or DNAIP10+IL6.

Measurement of C.1086 Env antibodies in serum revealed induction of antibody responses after the 3^rd prime in 8/12 animals, with comparable kinetics across vaccine groups. Notably, antibody concentrations 4 weeks post 3^rd DNA prime strongly correlated with both the frequencies of proliferating T_fh cells (Ki-67+ PD-1+ CXCR5+) within the LN and with the proliferating T_fh1 (Ki-67+ PD-1+ CXCR5+ CXCR3+) subset at 2 weeks post 3^rd DNA prime (Figure 7G-H). Moreover, the strong association of antibody concentrations after the 3^rd DNA prime with peak antibodies following the 1^st protein boost (Figure 7I) indicated efficient recall of Env-specific memory B cells induced during the prime. Overall, the data show that stimulation of T_fh1 cells during the DNA priming stage is closely linked with robust antibodies post boost.

In summary, our results strongly support maximizing GC T_fh1 responses during both the prime and boost phases as a strategy to generate potent and durable humoral immunity. These findings have significant implications for the development of more effective vaccination strategies aimed at eliciting robust and long-lasting immune responses.

Discussion

T_fh cells are fundamental in establishing long-lasting humoral immunity with vaccination. The dynamic interplay between innate immune activation and the ensuing inflammatory response directs the magnitude and composition of T_fh cell populations, ultimately shaping quantitative and qualitative features of humoral memory (Hirota, Turner et al. 2013, Barbet, Sander et al. 2018, Olatunde, Hale et al. 2021). Here we show that maximizing induction of CXCR3+ T_fh1 cells correlates with serum Env antibodies which exhibit higher persistence. Our studies with LAMV revealed the robust induction of pT_fh1 and GC T_fh1 responses, along with a moderate induction of T_fh17 and T_fh1/17 cells. These findings led us to compare the adjuvants MPLA+QS-21 and CAF01, known to elicit T_h1 and mixed T_h1/17 responses (Christensen, Bollehuus Hansen et al. 2019), (Pedersen, Andersen et al. 2018) respectively, to determine the optimal strategy for maximizing Env antibody persistence. Through proteomic and transcriptomic analysis of lymph nodes, we uncovered evidence of robust GC responses induced by both vaccine adjuvants following a DNA prime. Moreover, we observed notable skewing of T_fh responses, which corresponded with the elicitation of distinct immunogenicity profiles. Interesting, although peak antibody responses following each protein boost were similar across the vaccine platforms, our investigation revealed a notable distinction in antibody persistence. Specifically, the MPLA+QS-21 regimen exhibited higher antibody levels at week 8,12, and 30, suggestive of enhanced support from T_fh cells in promoting plasma cell differentiation. Moreover, T_fh1 cell induction during the DNA priming phase was linked to effective boosting upon subsequent protein immunization. These findings highlight the critical role of T_fh1 cells in driving the longevity of antibody responses and emphasize the potential of stimulating T_fh1 cells during the prime and boost to elicit durable humoral immunity against HIV Env.

A significant finding in RV144 vaccine recipients was the correlation between Env-specific peripheral CD4 T cell subsets co-producing IFNγ, TNFα, CD40L, and IL4, and a reduced risk of HIV acquisition [40]. This correlation suggests that productive GC responses elicited by the vaccine fostered protective humoral immunity (Lin, Finak et al. 2015). More recently, follow up analysis of this population in n=6 subjects immunized with the RV144 vaccine regimen in South Africa (HVTN 097) reported a pT_h2 biased transcriptional profile based on observed IL4 and IL13 transcripts (Cohen, Tian et al. 2022). However, it is important to note that in addition to T_h2 cells CD4 T_fh cells also produce IL-4 in a SLAM/SAP dependent manner (McCausland, Yusuf et al. 2007) and T_h1 cells can produce IL-13 in the presence of IL18 is documented (Hayashi, Yoshimoto et al. 2007). These findings indicate the need for utilizing multiple immune parameters when categorizing CD4 T cell help and underscore the importance of studying both lymph node and peripheral blood CD4 T_fh cells to fully understand their respective roles in fostering Env antibody responses.

In the context of vaccination, our observed association between T_fh1 cells and persistent antibody responses raises the possibly that higher relative production of IL-21 and CD40L may support the proliferation of GC B cells in concert with IFNγ-mediated B cell proliferation. This contention is supported by the observation of higher relative Ki-67 protein levels in the MPLA group at week 2 of the first protein boost. In the context of a T_h1 driven GC response rich in CXCL chemokines CXCL9, 10, and 11; CXCR3 expression on T_fh cells may furthermore enable proximity and interaction with GC B cells. CAF01 is composed of cationic liposomal vesicle (dimethyldioctadecylammonium, DDA) together with a synthetic analog of a mycobacterial cell wall (trehalose dibehenate, TDB), a potent activator of macrophages and dendritic cells through the macrophage inducible Ca2⁺-dependent lectin receptor Mincle, a pattern recognition receptor recognizing bacterial lipids (Davidsen, Rosenkrands et al. 2005, Martinez-Lopez, Iborra et al. 2019). CAF01 elicits CD4 T_h1 responses while concurrently driving strong T_h17 responses to a mycobacterium TB subunit vaccine via induction of proinflammatory cytokines IL-1β, IL-6, and TNF-α (Werninghaus, Babiak et al. 2009). We observed that CAF01 was effective in inducing robust cellular responses, which were skewed towards a T_h1/T_h17 profile within GCs. It is possible that employing the CAF06 platform which incorporates MPL into the bilayer of DDA/TDB liposomes may drive stronger T_h1 responses together with T_h17 cells thereby enhancing protective immunity by eliciting strong humoral immune responses.

The present studies are the first to our knowledge to assess immunological responses across HIV vaccine platforms with MPLA and CAF01-based adjuvants and strongly support GC T_fh1 cell induction for enhancing Env antibody responses. However, our study has several limitations. First, priming modalities across MPLA and CAF01 were not identical. Animals boosted with MPLA were primed with DNAIP10, whereas CAF01 boosted animals received the DNAIP10+IL6 prime. Given the stronger immunogenicity of DNAIP10+IL6, it is possible that our studies underestimate immune recall potential of MPLA relative to CAF01. Second, 5/6 animals in each vaccine group were males and therefore our findings do not capture possible variability in vaccine response between sexes. Because females develop higher antibody responses than males, it is important to test our hypothesis in animals of both sexes(Fischinger, Boudreau et al. 2019). Third, the interplay of innate immune cells and the follicular dendritic cell network in regulation of T_fh help for antibody responses is an important consideration for future studies. Finally, we did not assess vaccine efficacy and therefore whether GC T_fh1 cells constitute an important correlate of protection from acquisition remains an important unanswered question.

In summary, our findings demonstrate significant skewing of the GC T_fh response by adjuvants inducing distinct inflammatory responses. We further demonstrate that induction of T_fh1 cells results in superior persistence of Env antibodies indicating that strategies to harness this CD4 subset may promote protective humoral immunity against HIV.

Materials and methods

Rhesus Macaques

For LAMV studies, sixteen female colony-bred rhesus Indian origin rhesus macaques (Macaca mulatta) were utilized. Animals were dichotomized by age into two groups; young [n=8, mean=4 years] and aged [n=8, mean=16 years]. Young adults with a higher baseline weight [mean=5.9kg] were selected for the cohort to closer match the aged animals in size [mean=8.6kg]. For the HIV vaccine study, twelve adult (10 males and 2 females) Indian origin rhesus macaques (Macaca mulatta) were utilized. At study initiation, animals were 3.4 – 5.6 years of age with a median weight of 6.8 kg. Animals in both studies were SIV negative (SIV-), simian T-cell leukemia virus negative (STLV-), and simian retrovirus negative (SRV-); and had no history of dietary, pharmacological, or surgical manipulation (Supplementary Table 1a). All animals were bred and housed at the California National Primate Research Center (CNPRC) in accordance with the American Association for Accreditation of Laboratory Animal Care (AAALAC) guidelines. All studies were approved by the University of California, Davis Institutional Animal Care and Use Committee (IACUC).

LAMV Immunization

The animals received an IM booster vaccination of canine distemper-measles vaccine (Vanguard).

HIV-1 Immunization

Animals were immunized with DNA vaccines intradermally in both thighs at weeks 0, 4, and 8. At each prime, animals received 4mg of the pGA2/JS2 plasmid DNA encoding either SHIV C.1086 T/F Env + rhesus interferon-induced protein (IP)-10 (Group 1; n=6) or SHIV C.1086 T/F Env + rhesus interferon-induced protein (IP)-10 + rhesus interleukin (IL)-6 (Group 2; n=6). Subsequent protein boosters were administered at weeks 12 and 20 with Group 1 animals receiving 50μg C.ZA 1197MB gp140 protein adjuvanted with MPLA + QS-21 and Group 2 animals receiving 50μg C.ZA 1197MB gp140 protein adjuvanted with CAF01 delivered in a 175μL volume subcutaneously into each thigh.

Cationic Adjuvant Formulation 01 (CAF01)

CAF01 was generously provided by Statens Serum Institut, Denmark. Admixing with protein was performed by addition of 25μg of C.ZA 1197MB gp140 protein (Immune Technology, USA) to 250µL of CAF01 (625μg DDA+ 125μg TDB) adjuvant formulation. The solution was vortexed vigorously for 15-30 seconds followed by visual inspection. Remaining protein was added in 10μg increments with intermittent vortexing until a final amount of 100μg gp140 was achieved.

Monophosphoryl Lipid A (MPLA)

Synthetic MPLA was purchased from InvivoGen, USA. 100μg C.ZA 1197MB gp140 protein was dissolved in a solution of 100μg MPLA with 50μg QS-21 saponin [Desert King International, USA] (2:2:1) in PBS.

Specimen collection and processing

Lymph node (LN) biopsies were obtained at baseline (week0), week 14 (week 2 post 1^st protein boost) and week 23 (week 3 post 2^nd protein boost) and processed as described previously(Verma, Schmidt et al. 2019). Isolated cells were washed in complete media, counted, and cryopreserved until subsequent analysis. Two weeks after the 3^rd DNA immunization, fine needle aspirates of LN were obtained using a 22-gauge needle, as previously described(Verma, Schmidt et al. 2019). PBMCs were isolated from whole blood collected in CPT vacutainer tubes at weeks 0, 4, 9, 10, 13, 21, and 32. Serum was collected from animals at weeks 0, 4, 8, 8+day3, 9,10, 12, 13, 14, 16, 20, 20+day3, 21, 22, 23, 28, 32, 50 timepoints and stored at −80°C until subsequent analysis. Rectal secretions were collected for assessment of mucosal antibody production using premoistened Weck-Cel sponges as previously described(Verma, Schmidt et al. 2019).

Activation induced Marker and Intracellular cytokine staining assay

Detection of antigen specific CD4 T cells detection was quantified by Activation induced Marker (AIM) and intracellular cytokine staining (ICS). PBMCs/LN cells were stimulated with overlapping peptide pools of HIV consensus C and HIV-1 C.1086 Env gp140C protein (NIH AIDS Reagent Program) in AIM/R10 media in the presence of 0.2μg CD28/49d co-stimulatory antibodies (BD) per test. As a positive control, cells were stimulated with 1X Cell Stimulation Cocktail (PMA and ionomycin) (eBioscience, USA). Unstimulated controls were treated with volume-controlled DMSO (Sigma-Aldrich). Tubes were incubated in 5% CO2 at 37°C overnight for AIM assay. For ICS assay, after 1 hour of stimulations, protein transport inhibitors 2μl/mL GolgiPlug (Brefeldin A) and 1.3μl/mL GolgiStop (Monensin) (BD, Biosciences, USA) were added to the tubes for 8 hours at 37°C, 5% CO2. Following stimulation, the cells were stained for AIM and ICS surface markers (see the Table 1). Cells were then fixed with cytofix/cytoperm for 10 min at 4°C, permeabilized with 1X Perm wash buffer (BD, Biosciences, USA), and stained with intracellular markers (see the Table 1) for 45 min. Cells were then washed and acquired the same day on a BD FACSymohony.

T_fh cell staining by flow cytometry and cell sorting

T_fh cell staining was performed on whole blood and LN cells as previously described(Verma, Schmidt et al. 2019). Samples were acquired on BD FACSymphony with FACS Diva version 8.0.1 software and data were analyzed using FlowJo (Versions 9 and 10). For cell sorting, cryopreserved cells were enriched by NHP CD4 isolation kit (Miltenyi Biotec,USA) and cells stained with CD3, CD4, CXCR5, CD95, and live/dead in complete media (incubated for 1 hour at 4°C on a shaker). Stained cells were washed twice with 5mL RPMI plain media (Gibco, USA) and cell pellets were resuspended in 0.5mL sorting buffer containing 2% FBS+PBS. The cells were then filtered through a 40μM strainer into 5mL sterile FACS tube (Blue cap tube). Cell sorting was performed using a BD FACSAria III. Naive, and CD95+ CD4 T cell populations were collected in complete media supplemented with 20% FBS. Sorted cells were stimulated with overlapping peptide pools of HIV consensus C and HIV-1 C.1086 Env gp140C protein (NIH AIDS Reagent Program) in R10 media in the presence of 0.2μg/mL CD28/49d co-stimulatory antibodies (BD) for 14 hours. The culture supernatant and stimulated cells were collected and stored at −80°C for subsequent analysis.

Serum IL-21 ELISA

Serum IL-21 cytokine was quantified using an IL-21 ELISA Development kit (Novus Bio, USA) in accordance with manufacturer’s protocol. Briefly, the capture mAb (MT216G) diluted to 2μg/mL in PBS, pH 7.4 was added (100μL/well) to 96-well microtiter plates with high binding capacity (Thermo Fisher, USA) and incubated overnight at 4°C. The next day, plates were aspirated, and wells blocked with 200μL/well of PBS with 0.05% Tween 20 and 0.1% BSA (incubation buffer). After 1 hour of incubation, plates were washed 5 times with PBS containing 0.05% Tween 20 (300μL/well). Samples or working standards were added at 100uL/well and incubated for 2 hours at room temperature. After washing, plates were incubated for one hour with 100μL/well of detection mAb diluted to 1μg/mL in incubation buffer. Streptavidin-HRP diluted 1: 1000 in incubation buffer was added to the plates at 100uL/well for 1 hour followed by washing. Plates were washed and then developed with TMB substrate (Thermo Fisher, USA), and the reaction quenched with 0.2M H2SO4 (Sigma, USA). Absorbance was recorded using a Spectramax 5 plate reader (Molecular Devices) at 450 nm with a reference filter at 570 nm within 15 min. The concentration of IL-21 in serum was calculated based on an IL-21 standard curve using SoftMax Pro.

RNA Sequencing and Bioinformatics

RNA was extracted from sorted naive, and CD95+ CD4 T cells using a RNeasy plus mini kit (QIAgen). Isolated RNA sample quality was assessed using BioAnalyzer RNA pico assay (Agilent Technologies Inc., California, USA) and quantified by Qubit 2.0 RNA HS assay (ThermoFisher, Massachusetts, USA). Library construction was performed based on manufacturer’s recommendation for SMART-Seq® v4 Ultra® Low Input RNA Kit (Takara Bio USA Inc., California, USA) followed by Nextera® XT DNA Library Prep Kit (Illumina, California, USA). Final library quantity was measured by KAPA SYBR® FAST qPCR and library quality evaluated by TapeStation D1000 ScreenTape (Agilent Technologies, CA, USA). Final library size was about 450bp with an insert size of about 300bp. Illumina® 8-nt dual-indices were used. Equimolar pooling of libraries was performed based on QC values and sequenced on an Illumina® NovaSeq S4 (Illumina, California, USA) with a read length configuration of 150 PE for 40 M PE reads per sample (20M in each direction). Reference rhesus macaque genome (Macaca_mulatta _GCF_003339765.1_Mmul_10) and gene model annotation files were downloaded from genome website directly. Index of the reference genome was built using Hisat2 v2.0.5 and paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5. The mapped reads of each sample were assembled by StringTie (v1.3.3b) in a reference-based approach.

The quality of the raw RNA-seq data was assessed using FastQC, and poor-quality ends were trimmed (Trimgalore). High-quality sequences were aligned against the Macaca mulatta reference genome using STAR aligner v2.7.9, and counts were generated using featureCount (Dobin, Davis et al. 2013). A list of differentially expressed genes (DEGs) were generated using DESeq2 based on the negative binomial distribution(Love, Huber et al. 2014). The resulting DEGs between the groups were defined at cut-off criteria of |log2 fold-change| ≥ 1.5 and p-value < 0.05 adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate (Liao, Smyth et al. 2013). Gene set enrichment analysis (Subramanian, Tamayo et al. 2005) was used to assess the statistical enrichment of gene ontologies, and pathways, and visualized using Clusterprofiler v4.8.1(2012). All statistical analyses were performed using R 4.2.0.

GeoMx Digital Spatial Profiling (DSP)

Formalin-fixed paraffin-embedded (FFPE) blocks were prepared using lymph node tissue from biopsies at baseline, week2 post protein1, and week3 post protein2 immunization timepoints to analyze the spatial protein profiling using the Nanostring GeoMx Digital Spatial Profiler (DSP). The tissue sections of 5-μm thickness were cut from FFPE blocks and mounted on GeoMx-NGS BOND RX slide as per manufacturer’s recommendations. Sections were baked at 60°C for 30 minutes, deparaffinized, rehydrated in CitriSolv, ethanol and washed in water. For antigen retrieval, slides were placed in staining jar containing 1X Citrate Buffer (pH 6) for 15 minutes using a preheated pressure cooker (high pressure and high temp). The tissue slides were washed with 1X TBS-T and blocked tissue sections with Buffer W for 1 hour at room temperature in a closed humidity chamber. Tissue slides were stained with a cocktail of fluorescent morphological markers SYTO13 (nuclear stain; AF532), CD20 (Clone: L26; AF488), CD3 (Clone: CD3-12; AF594), and Ki-67 (Clone: B56; AF647) at 1:10000, 1:250, 1:100, and 1:1000 dilutions, respectively. For protein detection, a multiplex cocktail of primary antibodies was used from core panels; GeoMx immune cell profiling panel, GeoMx IO drug target module, and GeoMx immune activation status module (See supplementary Table2). In total, 60 regions of interest (ROIs) were selected within GCs based on co-localization of CD3 with CD20+ Ki-67+ GC B cells. Indexing oligos were released from each ROI by exposure to UV light as described(Merritt, Ong et al. 2020), and 10μl of liquid from above the ROI was collected by a microcapillary tip and deposited in a 96-well plate.

Indexing oligos from each ROI were PCR amplified using GeoMx Seq Code primers. PCR products were pooled and purified twice with AMPure XP beads (Beckman Coulter, Brea, CA). Library concentration and purity were measured using a high-sensitivity DNA Bioanalyzer chip (Agilent Technologies, Santa Clara, CA). Paired-end sequencing was performed on an Illumina HiSeq 2000 instrument (Illumina, San Diego, CA). After sequencing, fastq files were run through the GeoMx NGS Pipeline where reads were trimmed, merged, and aligned to a list of indexing oligos to identify the source probe. Analysis of filtered normalized gene expression data was performed in R with Bioconductor. We profiled 32 proteins along with core protein in GeoMx Human Protein array. We first calculated the signal-to-noise ratio by dividing raw count values by the geometric mean of the negative IgG probes. The data were normalized using three negative control IgG probes with the GeomxTools package. Normalized expression values were used for downstream analyses. Dimensionality reduction analysis was performed with principal component analysis using the facomineR package(Lê, Josse et al. 2008). Differential expression analysis was conducted with the mixedModelDE function from the GeomxTools package. We tested for differences between time points and/or vaccine groups using linear mixed effect models that incorporated animal ID as a random effect term to account for non-independence of the multiple ROIs sampled per animal. Differential expression results were visualized in heatmap plots generated using the ComplexHeatmap R package(Gu, Eils et al. 2016).

Serum IgG ELISA

Serum IgG titers against HIV-1 C.1086 Env gp140 were determined by ELISA as described previously (Verma, Schmidt et al. 2019). In brief, 96-well microtiter plates with high binding capacity (Thermo Fisher, USA) were coated overnight at 4°C with C.1086 Env gp140 protein from the NIH AIDS Reagent Program (ARP) diluted in coating buffer. Plates were washed and blocked with nonfat dry milk in PBS for two hours at room temperature and washed five times with 1X PBS-0.05% tween20 (PBST). Diluted standard and serum samples were added to plate wells and incubated overnight at 4°C. Plates were washed, and HRP conjugated goat anti-monkey IgG (Nordic MUbio, Netherlands) was added to plate wells and incubated at room temperature for 1 hour. Plates were then washed and developed with the addition of TMB substrate (Thermo Fisher, USA). Absorbance was recorded at 450 nm with a reference filter at 570 nm using a Spectramax 5 plate reader (Molecular Devices, USA). Baseline sera from each animal served as negative control and optical density (OD) values 2-fold above baseline were considered positive and extrapolated using in-plate standards to determine anti-Env antibody concentrations.

IgG subclass antibodies

ELISA was used to measure concentrations of gp120-specific IgG1-4 antibodies. Ten rows of a 96-well Immulon 4 microtiter plate (VWR) were coated overnight at 4°C with 50ng C.1086 gp120ý7 (HIV Reagent Program) per well in PBS, pH 7.2. To generate a standard curve with a known amount of IgG1, IgG2, IgG3 or IgG4 antibody, 2 rows of the plate were coated with 50ng per well recombinant CD40 (NHP Reagent Resource). The following day, the plate was washed with PBST and blocked with PBST containing 0.1% BSA (ELISA buffer: EB). Serum samples diluted in EB were then added to gp120 wells. Duplicate dilutions of anti-CD40 rhesus IgG1, IgG2, IgG3 or IgG4 antibody (NHP Reagent Resource) were added to the CD40 wells. Following overnight reaction at 4°C, the plate was washed and treated for 1h at 37°C with 0.5µg/ml of the appropriate following biotinylated monoclonal antibody (all from NHP Reagent Resource) diluted in EB: anti-rhesus IgG1 clone 7H11 (ena), anti-rhesus IgG2 clone 8D11 (dio), anti-rhesus IgG3 clone 6F5 (tria) or anti-rhesus IgG4 clone 7A8 (tessera). Plates were washed, treated with 1/4,000 neutralite avidin peroxidase (SouthernBiotech) for 30min at room temperature, and developed with TMB substrate and H2SO4 stop solution. After recording absorbance at 450nm, a standard curve constructed from the anti-CD40 IgG subclass antibody was used to interpolate the concentration of anti-gp120 IgG of the same subclass in samples

ADP assay

Serum antibodies were evaluated for ability to enhance phagocytosis of gp120 expressing fluorescent beads by THP-1 monocytes as previously described (Verma 2020). Briefly, 1µm avidin-coated fluorospheres (Invitrogen) were labeled with biotinylated anti-His tag monoclonal antibody (ThermoScientific) and used to capture His-tagged clade C gp120 Du151 protein (Immune Technologies). The gp120-expressing beads were then incubated with triplicate 5-fold dilutions of heat-inactivated serum samples in V-bottom plates for 1h at 37°C. THP-1 cells (2×10⁴ per well) were then added and incubated at 37°C in 5% CO2. After 5h, cells were washed with Ca^+2/Mg⁺²-free DPBS, then treated with 0.12% trypsin-EDTA for 5 min at 37°C. The cells were washed and resuspended in 1% paraformaldehyde. Fluorescence was measured using a FACSCanto (BD Biosciences) and FlowJo 9 software. Phagocytosis was quantified by multiplying the percentage of fluorescent cells by their median fluorescence intensity. A phagocytic score was then calculated by dividing the phagocytosis measured in each test sample by the phagocytosis observed for pooled preimmune serum at the same dilution.

Neutralization assay

Serum neutralizing activity was quantified using a previously described pseudovirus infectivity assay where TZM-bl cells were co-incubated with tier 1 clade C pseudovirus MW965.26, tier 2 clade C virus Ce1086_B2, tier 2 clade C Ce1176_A3, or a control MLV-pseudotyped virus (to measure non-HIV-specific activity). Neutralization titers were measured in serum samples collected at week 0 and week 2 following the 2^nd protein boost. Samples neutralizing antibody activity against SIV pseudoviruses was measured relative to MLV pseudovirus negative controls.

Mucosal antibodies

A custom binding antibody multiplex assay (BAMA) assay with C.1086 gp140 K160N-conjugated Bio-Rad Bio-plex Pro magnetic COOH beads was used to quantify Env-specific IgG in rectal secretions and specific IgA in IgG-depleted sera and rectal secretions as previously described (Verma, Schmidt et al. 2019). Briefly, 50µg gp140 was conjugated to 10 x 10⁶ beads as described (Iyer, Gangadhara et al. 2015). The gp140-labeled beads (3500 per well) were shaken overnight at 1100 rpm and 4°C with 10-fold dilutions of serum or secretion and standard [Verma 2020]. Beads were then washed with PBST and reacted for 30min at room temperature with biotinylated goat anti-human IgG (Southern Biotech) or goat whole IgG containing anti-monkey IgA (Novus) followed by phycoerythrin-labeled neutralite avidin (Southern Biotech). Fluorescence was measured with a Bio-Rad Bioplex 200. Antibody concentrations were determined using standard curves prepared with Bioplex Manager software (Bio-Rad). Concentrations of gp120-specific IgG in secretions were divided by the concentration of total IgG or IgA measured in the sample by ELISA to obtain the specific activity (ng of gp140-specific IgG or IgA antibody per µg of total IgG or IgA, respectively).

Statistical analysis

Statistical analysis was performed using Prism v.9.5.1 (Graph Pad). Gaussian distribution was not assumed, thus comparisons across time, between groups, and correlations were analyzed using non-parametric tests. For within group comparisons, Wilcoxon matched pairs signed rank test was used. For between group comparisons, Mann-Whitney rank comparisons were used. Correlation coefficients were computed using Spearman correlation. P values < 0.05 were considered significant.

Acknowledgements

The authors are grateful to Dennis Christensen, previously at the SSI, for provision of CAF01 adjuvant for the studies. The authors are grateful to Brian Schmidt for technical assistance with the LAMV study; Wilhelm Von Morgenland and Miles Christensen and the CNPRC SAIDS team for coordination of macaque studies; Stephenie Liu at the UC Davis Genomics Resource for optimization of morphological markers for spatial profiling, and Daniel Newhouse at the Spatial Data Analysis Service (sDAS) for analysis of spatial proteomics data. We thank Robert L. Wilson for excellent technical assistance in processing secretions and measuring mucosal antibodies. The authors acknowledge funding support from NIAID, NIH R56AI150409 (SSI); Duke CFAR Grant P30 AI064518 (GDT). Reagents for measurement of rhesus IgG subclasses were obtained from the NIH Nonhuman Primate Reagent Resource supported by AI126683 and OD10976.

Data and materials availability

RNA-seq dataset is accessible at GSE234813 (submission in progress).

Figure legends

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S2.

S3, Supplement to Figure 2.

S4, Supplement to Figure 3.

S5, Supplement to Figure 4.

S6, Supplement to Figure 6.

S7, Supplement to Figure 7.