Follicular regulatory T cells restrain kidney allograft rejection in mice by suppressing alloreactive B cells

Zhang, Hengcheng; Podestà, Manuel A.; Cavazzoni, Cecilia B.; Wu, Yumeng; Lee, Jeong-Mi; Li, Xiaofei; Raeder, Paulo Lisboa; Chandrakar, Pragya; Gempler, Maya; Richardson, Sierra; Ghosh, Deepjyoti; Sayin, Ismail; Blazar, Bruce R.; Abdi, Reza; Weins, Astrid; Chong, Anita S.; Sage, Peter T.

doi:10.1038/s41467-025-57468-4

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Published: 04 March 2025

Follicular regulatory T cells restrain kidney allograft rejection in mice by suppressing alloreactive B cells

Nature Communications volume 16, Article number: 2151 (2025) Cite this article

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Abstract

Pathogenic antibodies produced by alloreactive B cells mediate antibody-mediated rejection after kidney transplantation, but the mechanisms remain poorly understood. Follicular regulatory T (Tfr) cells modulate follicular helper T cell-mediated B cell responses, but the functions of Tfr in controlling alloreactive antibody are unknown. Here we study the developmental signals and functions of Tfr cells in mouse allogeneic kidney transplantation models, and show that costimulatory blockade alters the development of Tfr cells disproportionately by decreasing germinal center (GC)-like Tfr cells but increasing follicular-like Tfr cells. Functionally, global Tfr cell deletion results in accelerated graft rejection and increases in donor-specific B cells in both draining lymph nodes and kidney allografts. Mechanistically, Tfr cell deletion increases GC B cell expression of pro-inflammatory cytokines such as IL-15, while neutralization of IL-15 compensates for the loss of Tfr cells and prolongs the survival of mice receiving kidney transplants. Together our preclinical mouse data demonstrate how Tfr restrains kidney allograft rejection by limiting alloreactive B cell responses.

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Introduction

Solid organ transplantation is a crucial therapeutic intervention for patients with end-stage organ failure, not only improving survival but also substantially increasing recipient quality of life^1,2. Despite progress in the treatment of acute rejection with the development of broad immunosuppression, antibody-mediated rejection (ABMR) still represents the main cause of late graft failure with few, if any, successful treatments available^3,4. ABMR is also a barrier to clinical xenotransplantation, a potential source of donor organs^5,6. ABMR is facilitated by the formation of donor-specific antibodies (DSA), which target allografts leading to endothelial injury and intimal arteritis, and ultimately graft loss⁷. Importantly, incidences of ABMR also include some degree of T cell mediated rejection (TCMR). Current therapeutic approaches for treating ABMR have focused on eliminating DSAs, but these methods have only minor clinical benefit and predispose recipients to opportunistic infections⁸. The development of new therapeutic strategies to treat ABMR is hindered by a limited understanding of the mechanisms controlling DSA formation and their roles in mediating ABMR. Part of this paucity of information is the lack of studies in the context of allogeneic kidney transplantation, a setting in which ABMR is particularly relevant.

The majority of antibodies produced by B cells occur within lymphoid organs through a T cell-dependent process in which follicular helper T (Tfh) cells stimulate germinal center (GC) B cells to undergo clonal expansion, class switch recombination (CSR) and somatic hypermutation (SHM), thereby enhancing the pathogenic potential of antibodies^9,10,11. Follicular regulatory T (Tfr) cells provide a counterbalance to Tfh help by setting activation thresholds on GC B cells^12,13,14,15. Tfr cells are a specialized effector subset of regulatory T (Treg) cell that expresses the transcription factor FoxP3 yet have transcriptional and phenotypic overlap with Tfh cells¹⁶. Newer data suggest that Tfr cells can exist in different phenotypic states, including a follicular phenotype marked by expression of CD25 as well as a GC-like phenotype in which CD25 is downregulated¹⁷. Tfr cells limit serological antibody responses specific for both autoreactive and foreign antigens, however their effect on autoreactive antibodies is more robust¹⁸. Recently, it was shown that Tfr cells can promote clonal diversity and affinity maturation of antibodies, suggesting that Tfr cells fine-tune activation thresholds on GC B cells instead of simply dampening antibody output¹⁹. Functionally, Tfr cells control developmental signals and cytokine production in Tfh cells, including IL-21 and IL-13^18,20,21. In the context of solid organ transplantation, Tfh cells have recently been shown to be key mediators of pathogenic B cell responses, DSA and ABMR^22,23,24,25. However, the roles of Tfr cells in the context of solid organ transplantation are less clear. Standard immunosuppression reduces Tfr cells, and the frequency of Tfr cells inversely correlates with ABMR in some clinical settings²⁶, however, an in-depth assessment of Tfr differentiation and function in controlling kidney transplant rejection has not been performed.

In this study, we investigate the developmental signals and functions of Tfr cells in the context of allogeneic kidney transplantation. Our results show that selective deletion of Tfr cells increased alloreactive B cell clones, DSA and ABMR-like disease. We also observe that Tfr cells limit the production of the pleiotropic cytokine IL-15 in GC B cells, and neutralization of IL-15 partially rescues the loss of Tfr cells. Together, these findings indicate that Tfr cells are critical in protecting kidney allografts from rejection. They suggest that targeted modulation of Tfr cells may offer a novel strategy to improve long-term transplant outcomes.

Results

Costimulatory blockade alters Tfr cell development after kidney transplantation

To study the development of Tfr cells during kidney transplantation, we used a previously described allogeneic kidney transplant model^2,25,27. We transplanted kidneys from allogeneic (Balb/c) or syngeneic (C57BL/6) mice into FoxP3 reporter (Foxp3^IRES-GFP) mice on a C57BL/6 background. The spleen, draining lymph nodes (dLNs), graft, and blood were collected on days 10 and 20 post-transplantation (Fig. 1a). Allogeneic recipients exhibited a progressive ABMR-like disease, characterized by elevated serum IgG DSA levels and histological evidence of tubulitis and glomerulitis in the kidney grafts (Fig. 1b, c and Supplementary Fig. 1a). However, TCMR was also present. Although the frequency of total CD4⁺ T cells remained unchanged in dLN, there was a notable increase in Tfh (defined as CD4⁺CD19^-CXCR5⁺FoxP3^-) starting at day 10, as well as an increase in Tfr (CD4⁺CD19^-CXCR5⁺FoxP3⁺) cells, but not until day 20 day after transplantation (Fig. 1d and Supplementary Fig. 1b). CD4⁺FoxP3⁺ cells in contrast did not change in frequency after allogeneic transplantation (Fig. 1e). Similarly to the dLN, splenic Tfr cell frequencies increased starting at day 20 after transplantation, whereas Tfh cells increased starting at day 10 (Supplementary Fig. 1c, d). Consistent with increases in Tfh and DSA, we found increases in the frequency of CD19⁺GL7⁺FAS⁺ germinal center (GC) B cells in both the dLN and spleen after allogeneic kidney transplantation compared to syngeneic controls (Fig. 1f and Supplementary Fig. 1e). These findings indicate that Tfr cells differentiate after allogeneic kidney transplantation but with delayed kinetics compared to Tfh and GC B cells.

**Fig. 1: Costimulatory blockade dampens Tfr cell differentiation after allogeneic kidney transplantation.**

We next sought to determine the role of costimulation on Tfr cell development. CTLA4Ig, a T-cell costimulation blocker, is used in a subset of kidney transplant patients to prevent rejection, offering less toxicity than calcineurin inhibitors in some settings with similar graft survival rates^28,29,30. The impact of CTLA4Ig on Tfr development in the context of kidney transplantation remains unclear. To assess the role of systemic costimulatory blockade on Tfr differentiation, we administered CTLA4Ig two days after transplantation and assessed rejection (Fig. 1g). We observed similar levels of mononuclear cell infiltration with and without CTLA4Ig treatment (Fig. 1h). However, in the CTLA4Ig-treated group, mononuclear cells were predominantly localized to the renal interstitium and around arteries. In contrast, without treatment, the infiltrates were more diffusely distributed across glomeruli, tubules, and peritubular capillaries. Both groups showed high levels of TCMR-like pathological features, including interstitial inflammation and tubulitis (Supplementary Fig. 2a, b). CTLA4Ig treatment slightly reduced TCMR-like pathology but significantly decreased ABMR-associated pathological features, such as peritubular capillaritis and glomerulitis, and C4d deposition in grafts (Fig. 1h). CTLA4Ig treatment also reduced serological IgG DSA production starting on postoperative day 7 which continued until day 20 (Fig. 1i). CTLA4Ig treatment also resulted in a marked reduction in the frequencies of dLN GC B cells (Fig. 1j and Supplementary Fig. 2c). Although CTLA4Ig had a limited effect on the frequency of CD4⁺ T cell infiltration and effector T cell responses (Supplementary Fig. 2d–f), it had a significant inhibitory effect on total CXCR5⁺ follicular T cells as well as Tfh cells in dLN and peripheral blood, potentially by inducing apoptosis and anergy (Fig. 1k and Supplementary Fig. 3a–c). Furthermore, CTLA4Ig reduced the number of Tfr cells in the dLN and kidney allografts without altering the expression of the transcription factor FoxP3 (Supplementary Fig. 3d–f). ICOS expression was substantially lower on Tfr cells from CTLA4Ig-treated, compared to control, recipients (Supplementary Fig. 3g). Together these data demonstrate that while costimulatory blockade dampens Tfh and GC B cell differentiation, it also restrains Tfr cells.

Follicular to GC-like differentiation of Tfr cells is abrogated by costimulatory blockade

To characterize the developmental dynamics of Tfr cells and understand which specific stages are sensitive to costimulatory blockade, we performed single-cell RNA sequencing (scRNAseq) on sorted CD4⁺CD19^-CXCR5⁺FoxP3⁺ Tfr and CD4⁺CD19^-CXCR5^-FoxP3⁺ Treg cells from the dLN of allogeneic kidney transplant recipients, with or without CTLA4Ig treatment (Fig. 2a). Utilizing uniform manifold approximation and projection (UMAP) for dimensionality reduction, we identified 9 unique clusters from all cells (Fig. 2b and Supplementary Fig. 4a). Treg cells predominantly occupied cluster 0 and portions of cluster 2. In contrast, Tfr cells occupied all other clusters as well as portions of cluster 2 (Fig. 2c and Supplementary Fig. 4b). All clusters expressed Foxp3 and Tfr-containing clusters exhibited substantial expression of Cxcr5 which is highly expressed in Tfr cells (Fig. 2d and Supplementary Fig. 4c). Next we assessed whether individual clusters of Tfr cells were reflective of distinct activation states. Cluster 0 and 6 which contained CXCR5^- Tregs but also some Tfr cells, had high expression of Il2ra/CD25 and the naïve T cell homing receptor Sell/CD62L (Fig. 2d, e and Supplementary Fig. 4c–e). We referred to these clusters as naïve-like clusters. Both Sell and Il2ra were also expressed in clusters 4 and 5, but these clusters also contained higher expression of the inducible costimulatory molecule Icos and to a lesser extent higher levels of Cxcr5 compared to naïve-like cluster 0. Therefore, we referred to clusters 4 and 5 as “follicular-like” clusters. Interestingly, Prdm1/Blimp-1 was enriched in Icos-expressing clusters, particularly cluster 5. Pdcd1/PD-1 was enriched in clusters 1, 3, 7 and 8 which was also largely enriched in Bcl6, an important transcription factor for the development and maintenance of Tfh and Tfr cells. Moreover, we found Il2ra/CD25 was lowest in Pdcd1⁺Bcl6⁺ clusters and highest in Pdcd1^-Prdm1⁺ Tfr clusters. Since CD25 has been reported to be downregulated in Tfr cells that reside in GCs¹⁷, we have termed clusters 1, 2, 3, 7 and 8, “GC-like” Tfr clusters. Monocle pseudotime analysis indicated a directional progression from naïve-like cluster 0 towards Tfr clusters with Bcl6 expressing clusters 1,2,3 having higher pseudotime values compared to Prdm1-expressing clusters, except for cluster 7 (Fig. 2f and Supplementary Fig. 4f). In vitro experiments in which we sorted and cultured PD-1⁺ or PD-1^- Tfr cells with Tfh and B cells showed that both subsets contained the ability to suppress Tfh-mediated B cell activation, with the PD-1⁺ subset showing a slightly higher inhibitory capacity (Supplementary Fig. 5a). These data indicate that Tfr cells exist in distinct cellular states with unique programming.

**Fig. 2: The follicular to GC-like developmental transition in Tfr cells is sensitive to costimulatory blockade.**

Next, we compared how costimulatory blockade altered Tfr cellular states of the cells that were still present after CTLA4Ig treatment. We found most Tfr cell clusters remained unchanged except for GC-like Tfr clusters 3 and 7, which were decreased in CTLA4Ig-treated recipients, and follicular-like Tfr cluster 4 which was more abundant in CTLA4Ig-treated recipients (Fig. 2g, h). The enrichment of coinhibitory receptors such as Tigit, Pdcd1 and Ctla4 in GC-like cluster 3, as well as the enrichment of Sell, Ccr7 and Il2ra (CD25) in follicular-like Tfr cluster 4, combined with directional pseudotime analysis suggest CTLA4Ig treatment disproportionately limits the conversion of Tfr cells in the follicular-like state to the GC-like state (Fig. 2i, j). In support of this, these genes were differentially expressed between clusters 3 and 4 (Fig. 2i). Interestingly, the most profoundly affected GC-like cluster by costimulatory blockade was cluster 7 which expressed genes consistent with type-1 interferon responses such as Ifit3 and Ifit1 (Fig. 2i). The overall maintenance of core Tfr genes with CTLA4Ig treatment suggested costimulatory blockade did not alter global Tfr programs (Fig. 2k). We identified 12 genes, encompassing Cxcr5, Pdcd1, Tbc1d4, Tigit, and Cst7, that were significantly upregulated in Tfr vs. Treg cells, and 4 genes - Satb1, Klf2, Igfbp4, and Ly6c1 - that were markedly downregulated in Tfr vs. Treg cells regardless of whether the Tfr cells originated from control or CTLA4Ig treated condition (Fig. 2k). Flow cytometry confirmed that naïve-like Tfr cells increased after CTLA4Ig treatment (Supplementary Fig. 5b, c). Together, these data indicate that the Tfr population that develops after solid organ transplantation is phenotypically heterogeneous and that costimulatory blockade disproportionately impedes GC-like Tfr cells compared to other Tfr cell populations.

To assess clonal dynamics of Tfr cells after costimulatory blockade, TCR sequences from the scRNAseq dataset were analyzed. In control recipients, clonal expansion was found mostly in Bcl6-expressing GC-like Tfr clusters 1, 2 and 3 and to a lesser extent in Prdm1-expressing follicular-like cluster 5 (Fig. 3a, b). CTLA4Ig treatment diminished the extent of clonal expansion in Tfr cells, but not Treg cells, which showed little clonal expansion. To assess the possibility of Treg cell clones differentiating into Tfr cells, we assessed clonal overlap between these compartments. We found similar shared clones between Treg and Tfr cells for both control and CTLA4Ig treated recipients (Fig. 3c). To confirm that cells from naïve-cluster 0 could develop into other cell states, we performed clonal sharing analysis starting with cluster 0 as the clonal origin. We found shared clones with cluster 0 for both GC and follicular-like Tfr clusters (Fig. 3d). Clonal sharing of expanded clones between clusters showed substantial sharing within and between follicular-like and GC-like Tfr clusters (Fig. 3e). Together, these data elucidate developmental trajectories of Tfr cells from a naïve state, through a follicular-like state and ultimately into an activated GC-like state after kidney transplantation and that costimulatory blockade disproportionately inhibits the GC-like state and clonal expansion of Tfr cells.

**Fig. 3: Costimulatory blockade restricts Tfr clonal expansion.**

Tfr cells limit allo-antibody production and rejection of kidney allografts

To elucidate the precise roles of Tfr cells in the context of kidney allograft rejection, we utilized a previously described intersectional genetics-based Tfr-deleter (Tfr-DTR) mouse model that selectively eliminates Tfr cells with administration of diphtheria toxin (DT)^18,19,27. This strain harbors both a Cxcr5^{LoxSTOPLoxDTR} allele and a Foxp3^CreYFP allele, positing DTR on the surface of Tfr cells but not other follicular T, nor Treg, cells. We performed allogeneic kidney transplantation to control (Tfr-Con; Foxp3^CreYFPCxcr5^wt) or Tfr-DTR (Foxp3^CreYFPCxcr5^{LoxSTOPLoxDTR}) mice and administered a single dose of CTLA4Ig on day 2 to lengthen the time of rejection, thereby facilitating a more complete understanding of Tfr functions (Fig. 4a). In survival transplant models (where recipient native kidneys were rendered non-functional via bilateral ureter obstruction so that the transplanted organ sustains the life of the recipient), Tfr cell deletion starting on day 3 reduced recipient survival time to 25 ± 5.04 days, in contrast to the median survival of 60 ± 20.08 days observed in the Tfr-Con group, and 20 ± 1.79 days without any treatment (Fig. 4b). At 20 days post-transplantation (utilizing mechanistically similar non-survival transplant surgeries), Tfr-deleted mice displayed significantly enlarged grafts and spleens, characterized by increased GC structures (Fig. 4c and Supplementary Fig. 6a). Both Tfr deleted and sufficient groups exhibited similarly high levels of TCMR-like pathological features, including tubulitis, arteritis, and interstitial inflammation. In non-deleted control mice, mononuclear cells were primarily localized to the renal interstitium and around arteries. In contrast, in Tfr-deleted mice, the infiltrates were more diffusely distributed across glomeruli, tubules, and peritubular capillaries (Fig. 4d and Supplementary Fig. 6b, c). There was also evidence of thrombotic microangiopathy and substantial C4d deposition (Fig. 4d and Supplementary Fig. 6b, c). Together, these parameters indicate more severe ABMR-like disease in Tfr-deleted mice. These findings also suggest that Tfr cells regulate ABMR-like disease processes more substantially than TCMR-like processes. Additionally, although CD4⁺ and CD8⁺ T cell infiltration remained largely unchanged, CD68⁺ macrophage infiltration was significantly enhanced in Tfr-deleted mice (Supplementary Fig. 6d). While the overall B cell infiltration in Tfr-deleted recipients was equal or even reduced compared to control recipients, local IgG deposition was increased (Fig. 4d).

**Fig. 4: Tfr cells prevent allo-antibody formation and rejection of kidney allografts.**

Deletion of Tfr cells did not alter the serum levels of IL-2 and IFN-γ production (Supplementary Fig. 6e). Serological analyses of DSA indicated that total IgG DSA levels began increasing from day 14 and showed a three-fold increase in Tfr-DTR, compared to control, recipients by day 20 after transplantation (Fig. 4e and Supplementary Fig. 6f). When we assessed individual allo-epitopes using single antigen beads, we found a pronounced elevation in IgG antibodies targeting MHC-Class II (I-A^d and I-E^d) antigens in the absence of Tfr cells (Fig. 4f). We and others have previously shown that deletion/perturbation of Tfr cells results in increases in autoreactive antibodies^18,31. Therefore, we next assessed autoreactive antibodies using a Hep-2 antibody detection assay with subcellular distribution assessment³². We observed heightened autoreactive antibodies from Tfr-deleted compared to control mice and these antibodies recognized cytoplasmic and nuclear targets (Fig. 4g). Together, our data demonstrate that Tfr cells have potent roles in limiting features of ABMR and promoting recipient survival after allogeneic kidney transplantation by controlling both donor-specific and autoreactive antibody responses.

Tfr cells restrain lymph node and intragraft GC B cell development

Next, we examined the role of Tfr cells in controlling GC B cell responses (Fig. 5a). We and others have previously shown that pathogenic GC-like B cells can be present in both lymph nodes and kidney allografts^2,25. In the dLN after transplantation, a marked reduction in Tfr, but not total Treg nor non-Tfr Treg cells, was observed in Tfr-DTR recipients validating specificity of deletion (Fig. 5b and Supplementary Fig. 7a, b). The frequency and total number of Tfh cells (gated as CD4⁺CXCR5⁺Foxp3^-) in the dLN, but not the blood (Supplementary Fig. 7c), increased with Tfr deletion suggesting Tfh cells are restrained by Tfr cells after transplantation, a finding that has been reported during vaccine settings^18,33. Compared to Tfr-sufficient control mice, Tfr cell deletion culminated in a significant augmentation in the frequency of GC B, memory-like B, and total IgG⁺ B cells in the dLN (Fig. 5c, d). Conversely, there was a notable decline in the naive B cell (gated as CD19⁺CD38⁺IgG1^-) population in Tfr-deleted mice. Within the allograft, the Tfr cell frequency and cell numbers mirrored the observations in dLN, with a substantial attenuation in Tfr-DTR mice (Fig. 5e and Supplementary Fig. 7d). Previous studies have shown that kidney allograft infiltrating B cells have a GC-like phenotype marked by GL7 expression even though they transcriptionally resemble innate-like B cells^2,32. We found the frequency and total number of intragraft GL7⁺ B cells increased in the absence of Tfr cells compared to Tfr sufficient controls (Fig. 5f and Supplementary Fig. 7d). Together, these data demonstrate that Tfr cells significantly restrain GC-like B cell responses simultaneously in dLNs as well as in kidney allografts.

**Fig. 5: Tfr cells restrain lymph node and intragraft germinal center B cell differentiation.**

Tfr cells restrict pathogenic B responses within lymph nodes and grafts

To understand the role of Tfr cells in controlling alloreactive GC B cells that produce pathogenic antibodies in lymph nodes and grafts we performed a GC single-cell culture system which allows interrogation of antigen specificity at a clonal level utilizing highly sensitive ELISA assays to assess broad alloreactivity (Fig. 5g)^2,25. For this, individual GL7⁺ B cells from dLN or kidney allografts from allogeneic transplant recipients on day 20 after transplantation were cultured with NB21 feeder cells allowing expansion and antibody secretion¹⁹. Culture supernatants were screened for IgG positivity by ELISA and IgG⁺ clones were further screened for alloreactivity (Fig. 5h). We found ~40% of IgG⁺ GC B cells from the dLN were donor-specific in control transplant recipients. This increased to ~46% in recipients in which Tfr cells were deleted starting on day 3 post-transplant, further compounding the already 3-fold increase in the frequency of total GC B cells (Fig. 5i, c). We have previously shown that although intragraft GC-like B cells are rarely class-switched, the few IgG⁺GL7⁺ B cells in grafts can be alloreactive². Consistent with this, we found that ~42% of IgG⁺GL7⁺ B cells in allografts of transplanted Tfr-sufficient recipients were specific for alloantigen. In Tfr-deleted recipients, this increased to ~50%, although the difference did not reach statistical significance. Together these data indicate that Tfr cells not only control the frequency of GC-like B cells but also the proportion of pathogenic alloreactive B cell clones within these compartments in both lymph nodes and kidney allografts.

Intensified B cell alloimmunity after Tfr cell deletion does not require CD8 T cells

We next assessed whether CD8 T cells were required for the intensified rejection which occurred after Tfr cell deletion. To do this, we administered a CD8-depleting antibody to control and Tfr-DTR mice and assessed B cell alloimmunity and graft pathology (Fig. 6a). Flow cytometry and immunohistochemistry confirmed a marked reduction in CD8⁺ T cells in both the dLN and grafts of anti-CD8 treated recipients without significant changes in the populations of CD44⁺CD62L^- effector CD4⁺ T cells or CD69⁺ activated effector CD4⁺ T cells (Supplementary Fig. 8a–e). Moreover, Tfr cell deletion occurred normally (Supplementary Fig. 8f). IgG DSA levels increased in the serum of Tfr-deleted, compared to control, mice as did GC B cells and IgG1⁺ GC B cells in both the dLN and grafts (Fig. 6b–d and Supplementary Fig. 8g). Despite effective CD8 + T cell depletion, histological analysis revealed interstitial cellular infiltration in both groups, with no significant differences in TCMR-like pathological scoring (Fig. 6e and Supplementary Fig. 8h). T cell-related cytokines IL-2 and IFN-γ in the serum also showed no significant differences with the deletion of Tfr cells (Supplementary Fig. 8i). The intensified B cell responses and number of GC B cells in the graft also correlated with increased glomerulitis, peritubular capillaritis and C4d deposition in the grafts of Tfr deleted, compared to control, mice (Fig. 6e and Supplementary Fig. 8j, k). These findings suggest that the intensified B cell alloimmunity and ABMR-like disease that occurs after Tfr deletion does not require CD8 T cells.

**Fig. 6: Intensified graft rejection after Tfr cell deletion does not require CD8 T cells.**

To confirm whether the increased DSA in Tfr-deleted mice was sufficient to induce ABMR-like disease we conducted passive transfer experiments. We collected serum from kidney transplanted control or Tfr-DTR recipients (performed as in Fig. 4). Serum was transferred to kidney transplanted μMT (Ighm^−/−) mice that lack most mature B cells and therefore cannot produce DSA (Fig. 6f). The transplantedμMT recipients that received serum from Tfr-DTR mice showed significantly higher IgG and C4d deposition in kidney grafts compared to those that received serum from control mice (Fig. 6g). These findings suggest that the alloantibodies produced after Tfr cell deletion contribute to disease.

Tfr cells fail to control the later stages of ABMR after kidney transplantation

Previous studies have demonstrated that Tfr cells have more potent roles in controlling early GC responses but have less substantial roles after GC formation¹⁸. To further understand the role of Tfr cells in controlling later stages of ABMR after kidney transplantation, we transplanted allogeneic kidneys into Tfr-DTR or control mice, gave CTLA4Ig on day 2, and administered DT to delete Tfr cells starting on day 20, a timepoint during which the rejection process is already underway. We evaluated B cell alloimmunity on day 30 (Fig. 7a). Tfr-DTR mice had similar IgG DSA as control mice suggesting Tfr cells did not restrain pathogenic antibody after GC formation (Fig. 7b and Supplementary Fig. 9a). By day 30 post-transplantation, grafts from both Tfr sufficient and deleted groups showed similar signs of rejection including mononuclear cell infiltration and pathological features of ABMR (Fig. 7c). As expected, a marked reduction in Tfr cells was observed in the Tfr-DTR mice, while the frequencies and number of Tfh and other naïve Treg cells remained unchanged (Fig. 7d and Supplementary Fig. S9b). Consistent with the lack of changes in the Tfh compartment, we did not find any substantial differences in the percentage and number of GC B cells in lymph nodes between Tfr-DTR and control mice (Fig. 7e and Supplementary Fig. 9c). Moreover, we did not find any differences in the frequencies of naïve B cells, IgG1 or IgG2-switched B cells, nor memory-like B cells when Tfr cells were deleted starting at day 20 (Fig. 7e, f). These data demonstrate that Tfr cells have strong roles in restraining ABMR early after kidney transplantation but are unable to dampen ongoing ABMR.

**Fig. 7: Tfr cells fail to control the later stages of rejection after kidney transplantation.**

Tfr cells control kidney transplant rejection by restraining proinflammatory cytokines in GC B cells

To uncover mechanisms by which Tfr cells control rejection after kidney transplantation, we isolated LN GC B cells from control or Tfr-DTR recipients 20 days post-transplantation and performed bulk RNAseq transcriptional analyses (Fig. 8a). Our analysis identified 662 differentially expressed genes (p < 0.05), with 275 genes exhibiting increased expression in Tfr-deleted recipients (Fig. 8b). KEGG pathway analysis indicated that differentially expressed genes were enriched in pathways such as cytokine-cytokine receptor interaction, MAPK, TNF, and JAK-STAT signaling (Fig. 8c). In the cytokine pathway, Il15 transcripts were found to be upregulated in GC B cells from Tfr-DTR mice compared to Tfr-Con mice (Fig. 8b). IL-15 is a pleiotropic cytokine that activates T and NK cells and has roles in promoting B cell responses by enhancing Tfh cells^34,35,36. To validate Tfr cells control IL-15 protein levels, we compared IL-15 concentrations in dLN interstitial fluid by ELISA. The concentration of IL-15 was elevated in Tfr-DTR compared to control recipients (Fig. 8d). Flow cytometry further confirmed a minor increase in IL-15 and IL15ra expression in dLN GC B cells in the absence of Tfr cells (Supplementary Fig. 10a, b).

**Fig. 8: Tfr cells dampen transplant rejection by limiting B cell production of IL-15.**

To assess the potential roles of increased IL-15 in promoting pathogenic B cell responses, we performed an in vitro functional assay where Tfh and Tfr cells, isolated from allogeneic kidney transplantation recipients, were co-cultured with B cells in the presence of anti-CD3/IgM (Fig. 8e)^2,25. Tfh cells cultured with B cells resulted in increases in IL-15 in culture supernatants and addition of Tfr cells reduced IL-15 levels significantly (Fig. 8f). To specifically assess the impact of IL-15 on B cell responses, we introduced a blocking antibody to neutralize IL-15. Tfh cells stimulated approximately 50% of B cells to express the activation marker GL7 which was substantially reduced when IL-15 was blocked (Fig. 8g and Supplementary Fig. 10c). In addition, while anti-IL-15 treatment dampened Tfh-induced IgG production by B cells, it did not further amplify the inhibitory effect of Tfr cells (Fig. 8h). Prior single-cell sequencing of Tfh in dLN and grafts of kidney transplantation mice did not show evidence of Il15 transcript²⁵ (Supplementary Fig. 10d). Although myeloid cells in the kidney can produce IL-15, culture of these cells with Tfr cells did not result in any differences in IL-15 secretion (Supplementary Fig. 10e, f). Our findings indicate that IL-15 production by B cells is induced by Tfh cells and inhibited by Tfr cells.

To further investigate the role of IL-15 in rejection, we evaluated the immune response in kidney transplanted IL-15Rα-deficient mice (IL-15Rα KO) (Fig. 8i, j). IL-15Rα KO mice had diminished GC B cell and IgG DSA responses (Fig. 8j and Supplementary Fig. 10g, h). Furthermore, in vitro functional assays in which IL-15Rα KO or control B cells were cultured with Tfh cells demonstrated reduced B cell and Tfh cell activation, indicating that B cells may be capable of trans-presenting IL-15 (Supplementary Fig. 10i-l). To confirm that IL-15 could be sensed by Tfh cells, we cultured Tfh cells sorted from the dLN of transplant recipients with IL-15 for 6 h and performed bulk RNA sequencing (Supplementary Fig. 10m, n). Transcriptomic analysis revealed that IL-15-stimulated Tfh cells exhibited a transcriptional profile consistent with enhanced activation and metabolic reprogramming (Supplementary Fig. 10o–q).

To assess the roles of IL-15 in the intensified ABMR-like disease in Tfr-deleted mice we neutralized IL-15 in vivo after Tfr deletion in transplanted mice receiving costimulatory blockade (Fig. 8k). Tfr-DTR recipients treated with both DT and anti-IL-15 neutralizing antibodies had increased survival compared to control Tfr-DTR mice that received DT alone (Fig. 8l). At 20 days post-transplantation, the anti-IL-15 treatment resulted in reduced GC B cells and serological IgG DSA production in Tfr-deleted mice (Fig. 8m and Supplementary Fig. 11a). IL-15 blockade did not significantly alter the frequency of Tfh/Tfr cells in dLN, IL-2 and IFN-γ production in the serum, nor infiltration of T cells/ MHC class II+ cells in the grafts (Supplementary Fig. 11b–d). IL-15 blockade alone in the presence of normal Tfr cells did not significantly diminish germinal center B cell responses nor DSA levels (Supplementary Fig. 11e, f). In contrast to kidney transplantation settings, anti-IL-15 treatment did not significantly suppress GC B cells nor antigen-specific IgG in the context of NP-OVA vaccination of Tfr deleted mice, indicating the IL-15 pathway may be unique to transplantation (Supplementary Fig. 11g). Collectively, our findings indicate that Tfr cells potently restrain rejection after kidney transplantation by limiting alloreactive B cell responses (Fig. 8n).

Discussion

Organ transplantation, a transformative therapeutic intervention for end-stage organ failure, is continually challenged by occurrences of ABMR³⁷. Although the roles of Tfh cells in promoting DSA and ABMR after solid organ transplantation have been studied, the functions of Tfr cells are less understood due to a lack of mouse models to investigate the precise roles of these cells in vivo. In kidney transplant patients, previous research has established an inverse correlation between the absolute number of circulating Tfr cells and the incidence of ABMR²⁶. Our study identified dynamics of Tfr cell differentiation after kidney transplantation, which occurred alongside the progression of ABMR-like disease. Tfr cells existed in distinct phenotypic states including naïve-like, follicular-like and activated GC-like Tfr cells with the naïve-like Tfr cells overlapping substantially with conventional Treg cells. The core Tfr program is characterized by the upregulation of key genes including Cxcr5, Pdcd1/PD-1, and Tigit compared to conventional Treg cells. Previous studies have shown that interfering with PD1-PDL1 interactions early in mouse kidney transplantation leads to increased acute rejection³⁸. Another study demonstrated that activating the TIGIT pathway enhances the suppressive effects of FoxP3⁺ Treg cells on human memory T cell population³⁹. Consistent with our findings, Tfr cells begin exerting regulatory and inhibitory effects early post-transplantation, commensurate with upregulation of PD1 and TIGIT.

Beyond a general Tfr program, we also uncovered unique Tfr cell states with overlapping clonality indicating that Tfr cells differentiate from a naïve-like state, through a “follicular-like” state and into an activated GC-like state. Importantly, this nomenclature refers to activation states (and not anatomical location) and were identified by altered expression of PD-1 and CD25, which have been shown to correlate with presence or absence on Tfr cells in GCs, respectively¹⁷. Importantly, both follicular-like and GC-like Tfr cells had suppressive capacity. Therefore, Tfr cells may require sequential developmental stages to achieve full differentiation, similar to what has been recently shown for Tfh cells³³. However, additional studies need to be performed to determine the etiology and function of these putative developmental stages.

There have been few, if any, therapeutics developed that limit ABMR. While CTLA4Ig treatment has shown improved graft survival and kidney function compared to calcineurin inhibitors, its association with a higher incidence of acute cellular rejection prevents broad usage^40,41,42. Multiple studies indicate that CTLA4Ig compromises the suppressive function of Treg⁴³. Interestingly, we found that costimulatory blockade strategies inhibited the differentiation of Tfr cells, but did so disproportionately, resulting in diminished GC-like and interferon-responsive Tfr cells. The GC-like Tfr cluster 3 was characterized by the expression of genes like Sh2d1a, Tigit, and Pdcd1. Agonism of TIGIT was observed to enhance Treg function, which was suppressed by CTLA4Ig, in skin transplantation⁴⁴. Therefore, co-administering agents that promote GC-like Tfr differentiation alongside CTLA4Ig may retain the clinical benefits of CTLA4Ig without compromising Tfr function. Additionally, while the use of CTLA4Ig in this study provided a valuable approach to prolong allograft rejection facilitating downstream mechanistic studies on Tfr functions, it is important to note that only a small percentage of kidney transplant patients receive CTLA4Ig.

The roles of Tfr cells in disease progression can be multifaceted and complex. While Tfr cells have been shown to broadly inhibit autoantibody responses, studies have indicated both positive and negative effects of Tfr cells in foreign antigen specific responses. We recently showed that Tfr cells set activation thresholds on the GC reaction during vaccination and therefore can promote somatic hypermutation and affinity maturation¹⁸. Our current study establishes the crucial role of Tfr cells in rejection using a Tfr-DTR mouse model that perturbs Tfr cells without affecting other Treg populations. We demonstrated that the absence of Tfr cells in kidney recipients leads to reduced renal graft survival, heightened pathological manifestations of ABMR-like disease (with less, if any, effects on TCMR-like disease) in grafts, and elevated serologic DSA levels. Although previous studies have shown that CXCR5⁺ CD8 T cells can influence DSA production⁴⁵, our data show that the regulatory effects of Tfr cells on B cell alloimmunity do not require CD8 T cells. The ability of Tfr cells to limit rejection was only found during the early stages of rejection, suggesting early suppression of Tfh and GC B cells is important to control ABMR-like disease. However, since the Tfr-DTR model may lose deletion potency over time as a consequence of host antibodies neutralizing DT, it is possible Tfr cells may have additional roles at other timepoints. These findings provide the first clear evidence of the negative regulatory role of Tfr in kidney transplantation, particularly in the context of ABMR. Moreover, these data suggest that promoting Tfr cells early after kidney transplantation may have the most robust and durable responses clinically.

Mechanistically, we found that Tfr cell suppression of rejection occurred through regulation of DSA-specific B cell responses both in lymph nodes and within kidney allografts. Since Tfh cells can promote pathogenic B cell responses both in lymph nodes and grafts²⁵, this suggests Tfr cells may limit Tfh-induced B cell responses wherever they occur. Tfr suppression of ABMR-like disease was achieved, in part, through the transcriptional reprogramming of GC B cells which included limiting production of cytokines such as IL-15. Inhibiting IL-15 antagonized the accelerated rejection in Tfr-DTR mice. Although IL-15 is a pleiotropic cytokine that has effects on many cell types involved in rejection including CD8 T cells and NK cells, it can also affect Tfh and B cell responses. Some studies have reported that IL-15 stimulates B cell proliferation and differentiation⁴⁶, and controls immature B-cell homing⁴⁷. Moreover, IL-15 can enhance Bcl6 expression and promote Tfh cell responses⁴⁸. Mechanistically dissecting the multifaceted roles of IL-15 in vivo is difficult due to broad and mechanistically complex sensing of this cytokine. However, our study suggest B cells can make IL-15 to promote Tfh cells, which in turn promote further GC B cell responses. It is important to note that our study cannot exclude the involvement of non-B cells in IL-15 mediated responses, nor can it fully differentiate between the effects of trans-presented versus non-trans-presented IL-15 in vivo. Although Tfr-mediated regulation of IL-15 in GC B cells may be only one of several factors in ABMR-like disease, the involvement of IL-15 in Tfh/GC B, CD8 T, and NK cells suggests synergy amongst multiple arms of the immune system. Moreover, although CD8 T cells were not required for the increased rejection in Tfr-deleted mice, it is possible that TCMR and ABMR-like diseases may be intertwined through the IL-15 pathway. Together, our data suggest that Tfr cells have potent roles in limiting ABMR-like disease indicating enhancing Tfr cells after transplantation may be a strategy to provide durable prevention of ABMR.

Methods

Animals

All animal research was conducted according to the guidelines of the Brigham and Women’s Hospital Institutional Animal Care and Use Committee and National Institute of Health. Balb/c (#000651), IL-15Rα KO (#003723) and B6129SF2/J (#101045), Ighm^−/−(μMT, #002288) mice were obtained from Jackson Laboratories. The Foxp3^IRES-GFP and Tfr-DTR (Foxp3^IRES-CreYFP Cxcr5^{IRES-LoxP-STOP-LoxP-DTR}) mice on the C57BL/6 background were previously published¹⁸. Experimental and control mice were co-housed in a specific pathogen-free facility, under 12/12 h dark/light cycle, at 22 °C and 42% humidity. Males and females between 6 and 10 weeks of age were used in the study. Mice were fed 5053 PicoLab rodent diet 20 (LabDiet). Mice were humanely euthanized using CO₂ inhalation followed by cervical dislocation as confirmation.

Mouse kidney transplantation and treatment

The left kidney from the donor was transplanted along with its ureter into the abdominal cavity of the recipient mice^2,25,27. The donor kidney’s artery and vein were connected to the recipient’s abdominal aorta and vena cava, respectively, using 10-0 sutures in an “end-to-side” manner. To reconstruct the urinary tract, the graft’s ureter was implanted into the recipient’s bladder. The surgical procedures typically lasted for 2 h, including an approximately 25-minute anastomotic phase. The recipients were harvested on day 20 post-transplantation as indicated. For the life-sustaining surgeries, the ureters of the remaining native kidneys were ligated on postoperative days 2–4 to limit function. This procedure renders the transplanted kidney the only kidney supporting the life of the recipient, and mechanistically maintains the rejection process similar to non-survival surgeries (Supplementary Fig. 12). On day 2 after the transplantation procedure, a dose of 250 μg of CTLA4Ig (Abatacept, Bristol-Myers Squibb) was administered via intraperitoneal injection. Deletion experiments involved intraperitoneal administration of 0.5 μg of diphtheria toxin in PBS at the specified time points. To block IL-15 signaling, 200 μg of anti-mouse IL-15 (Clone: AIO.3, Bioxcell, #BE0315) was administered intravenously five times (day 3, 6, 9, 12, 15) after kidney transplantation. For CD8 depletion, 200 μg of rat anti-mouse CD8a (clone 2.43, Bioxcell, #BE0061) was administered intraperitoneally beginning on day 0 and continued every 4 days until 20 days post-transplantation.

Donor-specific antibody (DSA) measurements

For the determination of DSA, we used a flow cytometric crossmatch (FCXM) assay. Fresh splenocytes (5 × 10⁵) from donor wildtype Balb/c mice were incubated with recipients’ serum samples at 1:50 dilution for IgG, or undiluted supernatant from single-cell cultures for 30 minutes, allowing DSA to bind to specific antigens on the surface of the donor cells. Next, the splenocytes were stained with anti-CD19 (6D5, Biolegend) in the presence of Fc-block (Biolegend) followed by an additional stain using FITC-labeled anti-IgG or anti-IgM. For assays involving single alloantigens, MHC beads (K^b, K^d, L^d, I-A^d, I-E^d) were incubated with serum at a dilution of 1:50 or serial dilution at 4 °C for 1 h^49,50. Bound antibodies were detected using FITC-labeled anti-IgG. The signal of bound IgG on CD19⁺ splenocytes was measured and expressed as mean fluorescence intensity (MFI).

Flow cytometry

Antibodies were purchased from BioLegend unless otherwise stated. Mouse antibodies (with their clone numbers, 1:200 dilution unless otherwise specified) against the following proteins were used: anti-CD4 (GK1.5), anti-CD19 (1D3), anti-ICOS (15F9), anti-CXCR5 (L138D7), anti-PD-1 (RMP1-30), anti-FoxP3 (eBiosciences, FJK-16s), anti-CD45 (30-F11), anti-CD38 (90/CD38), anti-GL7 (GL-7), anti-FAS (BD Biosciences, JO2), anti-IgG1 (BD Biosciences, A85-1), anti-IgG (SouthernBiotech), anti-Ki67 (16A8), anti-IL-15Ra (6B4C88), anti-CD44 (IM7), anti-CD62L (MEL-14), anti-CD69 (H1.2F3), anti-Ly6C (HK1.4), anti-TIGIT (1G9), anti-FR4 (eBiosciences, eBio12A5), anti-CD73 (TY/11.8), anti-CD8 (53-6.7) and LIVE/DEAD Fixable Blue Dead Cell Stain Kit (1:1000, Invitrogen) was used to label cells live/dead. The catalog numbers are listed in the Reporting Summary. Single-cell suspensions of draining lymph nodes, spleen, and grafts were prepared. Ficoll-paque (Cytiva) was utilized following the published protocol to separate graft-infiltrating lymphocytes. Surface marker staining was done at 4 °C for 30 min. The Foxp3 Fix/Perm buffer set was used as per the manufacturer’s instructions (eBioscience) for intracellular staining. For intracellular cytokine staining, cells were stimulated with Cell Activation Cocktail (BioLegend) for 4 h, then permeabilized and stained with corresponding antibodies. Fluorescence signals were detected using a Cytek Aurora flow cytometer and analyzed with FlowJo software.

Bulk RNA sequencing

We conducted RNA-seq using an Illumina NextSeq sequencer with 50-basepair reads and analyzed the data using CLC Genomics Workbench v.8.0.1 by Qiagen. Differently expressed genes (DEGs) were filtered by at least 2-fold change and p-value < 0.05. We analyzed the Kyoto Encyclopedia of Genes and Genomes (KEGG) on the DAVID website (https://david.ncifcrf.gov/) with a p-value cut-off of 0.05.

Single cell RNAseq and analysis

Draining lymph nodes from allogeneic kidney transplant recipients who did or did not receive CTLA4Ig treatment were harvested 20 days post-transplant. Single cell suspensions were stained with fluorochrome-labeled cell surface antibodies and distinct barcoded antibodies (Cell-Hashing antibody, TotalSeq-C, Biolegend)⁵¹. Live CD4⁺CD19^-CXCR5⁺Foxp3⁺ Tfr and CD4⁺CD19^-CXCR5^-Foxp3⁺ naïve Treg cells were sorted from each mouse group, pooled together, and resuspended in PBS 0.4% BSA at a concentration of 2000 cells/μl. Samples were subsequently loaded onto a single lane (Chromium chip K, 10X Genomics) followed by encapsulation (Single Cell 5′kit V2, 10X Genomics) at the Brigham and Women’s Hospital Single Cell Genomics Core. cDNA and library generation were performed according to the manufacturer’s protocol. The 5’ mRNA library was sequenced to an average of 50,000 reads per cell, whereas the V(D)J library and HTO (Cell Hashing antibodies) library were both sequenced to an average of 5000 reads per cell, all using Illumina Novaseq. Reads were processed with Cell Ranger, and quantification was performed using the STAR aligner against the mm10 transcriptome. CellRanger output data were loaded into the R programming environment and analyzed with the Seurat package. Sample demultiplexing and doublet exclusion were performed with the HTODemux function, and only singlets were selected for further analysis. Additional quality-control filtering was performed, imposing as thresholds unique UMI counts ≥ 2000, UMI counts <15000, gene counts ≥ 1000, log-transformed genes per UMI > 0.8 and mitochondrial RNA content <4%. Count data were subjected to normalization and variance stabilization using the SCTransform function (v.2), based on the 3000 most variable genes and by concomitantly regressing cell-cycle phase, mitochondrial, and ribosomal mapping percentages. Additional filtering based on identity was applied after a comparison of each cell with the Immunologic Genome Project dataset (using the SingleR pipeline), to exclude contaminating cells (e.g. CD8⁺ T, and NKT cells)⁵². Uniform manifold approximation and projection (UMAP) was used for dimensionality reduction according to the standard Seurat pipeline, but TCR-related genes were excluded from the list of variable features to avoid clustering based on clonotype. Differential gene expression was computed with the FindAllMarkers command (logFC threshold = 0.1, min.pct = 0.1) and module scores were calculated with the AddModuleScore function, using as input a previously generated gene set comprising upregulated genes in Tfr compared to Treg cells in our bulk RNAseq dataset. Differential abundance analysis across clusters between untreated and CTLA4Ig mouse samples was conducted with miloR⁵³. TCR clonotype analysis was performed with the scRepertoire package⁵⁴. Pseudotime trajectory analysis was carried out with Monocle3⁵⁵.

In Vitro functional assays

Tfh, Tfr, and B cells were isolated from spleens of FoxP3 reporter, IL15Rα KO or B6129SF2/J mice post-20 days allogeneic kidney transplantation. In vitro assays involved co-culturing 5 × 10⁴ B cells with 3 × 10⁴ Tfh or Tfr cells in 96-well U bottom plates, stimulated with anti-CD3 (2 μg/mL, Bioxcell, 2C11) and anti-IgM (5 μg/mL, Jackson ImmunoResearch), and maintained in a complete medium (RPMI-1640 supplemented with 10% FBS and 1% penicillin-streptomycin) at 37 °C and 5% CO₂ for 4 days. Cultures were maintained in complete medium for 4 days. To block IL-15 signaling, 100 ng/ml of anti-mouse IL-15 (Clone: AIO.3, Bioxcell) was supplemented to each well. Subsequent to the culture period, cells and supernatants were harvested for flow cytometry and ELISA.

Single B cell cultures

Single GC B cells (CD45⁺B220⁺CD4^–GL7⁺CD38^lo/–) from lymph nodes and kidney grafts were isolated and individually sorted into 96-well plates containing 1×10³ NB21.2D9 feeder cells (provided by Garnett Kelsoe, Duke University, Durham, North Carolina, USA). The cells were cultured for 6 days, and IgG-positive clones were identified via ELISA. Clones positive for IgG were subsequently tested for DSA reactivity as above.

ELISA

To determine serum or cell culture supernatant levels of IL-15, IL-2 and IFN-γ, mouse ELISA Kits (ThermoFisher) were used according to the instructions of the manufacturer. At 450 nm, the OD values of each sample were measured to express the concentration of cytokines.

Histopathological staining

Graft samples were harvested and either immediately submerged in 10% formalin for embedding in paraffin or preserved in Tissue-Tek OCT Compound. Hematoxylin and eosin (HE), immunohistochemistry (IHC) and immunofluorescence (IF) staining were carried out⁵⁶. The antibodies employed in the experiments included anti-CD3 (D4V8L, 1:100), anti-CD4 (D7D2Z, 1:100), anti-CD8 (D4W2Z, 1:500), anti-CD68 (E3O7V, 1:200), from Cell Signaling Technology, anti-B220 (RA3-6B2, 1:200), anti-GL7 (GL7, 1:100), anti-IgD (11-26 c.2a, 1:500) from Biolegend, anti-MHCII-I-A/I-E(M5/114.15.2) from eBioscience and C4d (16D2, 1:100) from Novus Biologicals. The catalog numbers are listed in the Reporting Summary. Microscopic images were captured using a ZEISS Axiolab 5 microscope. Pathological manifestations were evaluated based on Banff 2018 classification⁵⁷ with i (interstitial inflammation), t (tubulitis), g (glomerulitis), ptc (peritubular capillaritis) and v (vasculitis) components.

Autoantibody detection

For autoantibody detection, we used the Hep-2 antibody detection kit according to the manufacturer’s instructions. The serum samples were applied to Hep-2-coated slides and incubated to allow binding of autoantibodies to antigens. Post-wash, fluorophore-conjugated secondary antibodies were added, binding to the primary antibodies. After a final wash, slides were examined under a fluorescence microscope, capturing images for analysis.

Statistics

Student’s unpaired t-test or Mann-Whitney test were used as indicated utilizing GraphPad Prism, version 9 (GraphPad Software). Multiple comparisons were conducted using one-way ANOVA followed by Tukey’s test. Graft survival was compared using Kaplan-Meier survival analysis and a log-rank test. We considered significance at a P value below 0.05. The graphs depict values that represent the standard error of the mean (SEM), NS: not significant; *P < 0.05; **P < 0.01,**P < 0.01, ***P < 0.001.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The sequencing data generated in this study have been deposited in the GEO database under GSE286975. All data are included in the Supplementary Information or available from the authors, as are unique reagents used in this Article. The raw numbers for charts and graphs are available in the Source Data file whenever possible. Source data are provided with this paper.

References

Vanholder, R. et al. Organ donation and transplantation: a multi-stakeholder call to action. Nat. Rev. Nephrol. 17, 554–568 (2021).
Article PubMed PubMed Central MATH Google Scholar
Zhang, H. et al. Transcriptionally Distinct B Cells Infiltrate Allografts After Kidney Transplantation. Transplantation 107, e47–e57 (2023).
Article PubMed CAS Google Scholar
Gassen, R. B. et al. T cell depletion increases humoral response by favoring T follicular helper cells expansion. Am. J. Transpl. 22, 1766–1778 (2022).
Article CAS Google Scholar
Wojciechowski, D. & Wiseman, A. Long-Term Immunosuppression Management: Opportunities and Uncertainties. Clin. J. Am. Soc. Nephrol. 16, 1264–1271 (2021).
Article PubMed PubMed Central MATH CAS Google Scholar
Mohiuddin, M. M. et al. Graft dysfunction in compassionate use of genetically engineered pig-to-human cardiac xenotransplantation: a case report. Lancet 402, 397–410 (2023).
Article PubMed PubMed Central Google Scholar
Loupy, A. et al. Immune response after pig-to-human kidney xenotransplantation: a multimodal phenotyping study. Lancet 402, 1158–1169 (2023).
Article PubMed MATH CAS Google Scholar
Louis, K., Macedo, C., Lefaucheur, C. & Metes, D. Adaptive immune cell responses as therapeutic targets in antibody-mediated organ rejection. Trends Mol. Med 28, 237–250 (2022).
Article PubMed PubMed Central CAS Google Scholar
Chong, A. S., Rothstein, D. M., Safa, K. & Riella, L. V. Outstanding questions in transplantation: B cells, alloantibodies, and humoral rejection. Am. J. Transpl. 19, 2155–2163 (2019).
Article MATH CAS Google Scholar
Crotty, S. T Follicular Helper Cell Biology: A Decade of Discovery and Diseases. Immunity 50, 1132–1148 (2019).
Article PubMed PubMed Central MATH CAS Google Scholar
Tas, J. M. et al. Visualizing antibody affinity maturation in germinal centers. Science 351, 1048–1054 (2016).
Article ADS PubMed PubMed Central MATH CAS Google Scholar
Sage, P. T., Paterson, A. M., Lovitch, S. B. & Sharpe, A. H. The coinhibitory receptor CTLA-4 controls B cell responses by modulating T follicular helper, T follicular regulatory, and T regulatory cells. Immunity 41, 1026–1039 (2014).
Article PubMed PubMed Central CAS Google Scholar
Sage, P. T., Francisco, L. M., Carman, C. V. & Sharpe, A. H. The receptor PD-1 controls follicular regulatory T cells in the lymph nodes and blood. Nat. Immunol. 14, 152–161 (2013).
Article PubMed CAS Google Scholar
Sage, P. T. & Sharpe, A. H. T follicular regulatory cells. Immunol. Rev. 271, 246–259 (2016).
Article PubMed CAS Google Scholar
Wing, J. B., Lim, E. L. & Sakaguchi, S. Control of foreign Ag-specific Ab responses by Treg and Tfr. Immunol. Rev. 296, 104–119 (2020).
Article PubMed MATH CAS Google Scholar
Fonseca, V. R., Ribeiro, F. & Graca, L. T follicular regulatory (Tfr) cells: Dissecting the complexity of Tfr-cell compartments. Immunol. Rev. 288, 112–127 (2019).
Article PubMed CAS Google Scholar
Hou, S. et al. FoxP3 and Ezh2 regulate Tfr cell suppressive function and transcriptional program. J. Exp. Med 216, 605–620 (2019).
Article PubMed PubMed Central MATH CAS Google Scholar
Wing, J. B. et al. A distinct subpopulation of CD25(-) T-follicular regulatory cells localizes in the germinal centers. Proc. Natl. Acad. Sci. USA 114, E6400–E6409 (2017).
Article PubMed PubMed Central CAS Google Scholar
Clement, R. L. et al. Follicular regulatory T cells control humoral and allergic immunity by restraining early B cell responses. Nat. Immunol. 20, 1360–1371 (2019).
Article PubMed PubMed Central MATH CAS Google Scholar
Cavazzoni, C. B. et al. Follicular T cells optimize the germinal center response to SARS-CoV-2 protein vaccination in mice. Cell Rep. 38, 110399 (2022).
Article PubMed PubMed Central MATH CAS Google Scholar
Sage, P. T. et al. Suppression by T(FR) cells leads to durable and selective inhibition of B cell effector function. Nat. Immunol. 17, 1436–1446 (2016).
Article PubMed PubMed Central MATH CAS Google Scholar
Jandl, C. et al. IL-21 restricts T follicular regulatory T cell proliferation through Bcl-6 mediated inhibition of responsiveness to IL-2. Nat. Commun. 8, 14647 (2017).
Article ADS PubMed PubMed Central CAS Google Scholar
Sage, P. T. Preventing Antibody-mediated Rejection During Transplantation: The Potential of Tfr Cells. Transplantation 102, 1597–1598 (2018).
Article PubMed MATH Google Scholar
Mohammed, M. T. & Sage, P. T. Follicular T-cell regulation of alloantibody formation. Curr. Opin. Organ Transpl. 25, 22–26 (2020).
Article MATH CAS Google Scholar
Zhang, H. & Sage, P. T. Role of T follicular helper and T follicular regulatory cells in antibody-mediated rejection: new therapeutic targets? Curr. Opin. Organ Transpl. 27, 371–375 (2022).
CAS Google Scholar
Zhang, H. et al. IL-21-producing effector Tfh cells promote B cell alloimmunity in lymph nodes and kidney allografts. JCI Insight 8, e169793 (2023).
Article PubMed PubMed Central Google Scholar
Niu, Q. et al. Immunosuppression Has Long-Lasting Effects on Circulating Follicular Regulatory T Cells in Kidney Transplant Recipients. Front Immunol. 11, 1972 (2020).
Article PubMed PubMed Central MATH CAS Google Scholar
Mohammed, M. T. et al. Follicular T cells mediate donor-specific antibody and rejection after solid organ transplantation. Am. J. Transpl. 21, 1893–1901 (2021).
Article MATH CAS Google Scholar
Charpentier, B. et al. Long-term exposure to belatacept in recipients of extended criteria donor kidneys. Am. J. Transpl. 13, 2884–2891 (2013).
Article MATH CAS Google Scholar
Grinyo, J. M. et al. Safety and Efficacy Outcomes 3 Years After Switching to Belatacept From a Calcineurin Inhibitor in Kidney Transplant Recipients: Results From a Phase 2 Randomized Trial. Am. J. Kidney Dis. 69, 587–594 (2017).
Article PubMed CAS Google Scholar
Schulte, K. et al. Late conversion from tacrolimus to a belatacept-based immuno-suppression regime in kidney transplant recipients improves renal function, acid-base derangement and mineral-bone metabolism. J. Nephrol. 30, 607–615 (2017).
Article PubMed CAS Google Scholar
Fu, W. et al. Deficiency in T follicular regulatory cells promotes autoimmunity. J. Exp. Med. 215, 815–825 (2018).
Article PubMed PubMed Central MATH CAS Google Scholar
Asano, Y. et al. Innate-like self-reactive B cells infiltrate human renal allografts during transplant rejection. Nat. Commun. 12, 4372 (2021).
Article ADS PubMed PubMed Central MATH CAS Google Scholar
Podesta, M. A. et al. Stepwise differentiation of follicular helper T cells reveals distinct developmental and functional states. Nat. Commun. 14, 7712 (2023).
Article ADS PubMed PubMed Central MATH CAS Google Scholar
Komlosi, Z. I. et al. Human CD40 ligand-expressing type 3 innate lymphoid cells induce IL-10-producing immature transitional regulatory B cells. J. Allergy Clin. Immunol. 142, 178–194 e111 (2018).
Article PubMed MATH CAS Google Scholar
Rafei, M. et al. A granulocyte-macrophage colony-stimulating factor and interleukin-15 fusokine induces a regulatory B cell population with immune suppressive properties. Nat. Med 15, 1038–1045 (2009).
Article PubMed MATH CAS Google Scholar
Patidar, M., Yadav, N. & Dalai, S. K. Interleukin 15: A key cytokine for immunotherapy. Cytokine Growth Factor Rev. 31, 49–59 (2016).
Article PubMed MATH Google Scholar
Schinstock, C., Tambur, A. & Stegall, M. Current Approaches to Desensitization in Solid Organ Transplantation. Front. Immunol. 12, 686271 (2021).
Article PubMed PubMed Central CAS Google Scholar
Shim, Y. J. et al. Early T cell infiltration is modulated by programed cell death-1 protein and its ligand (PD-1/PD-L1) interactions in murine kidney transplants. Kidney Int 98, 897–905 (2020).
Article PubMed PubMed Central CAS Google Scholar
Sun, H. et al. TIGIT regulates apoptosis of risky memory T cell subsets implicated in belatacept-resistant rejection. Am. J. Transpl. 21, 3256–3267 (2021).
Article MATH CAS Google Scholar
Wyatt, C. M. & Arons, R. R. The burden of acute renal failure in nonrenal solid organ transplantation. Transplantation 78, 1351–1355 (2004).
Article PubMed MATH Google Scholar
Bluestone, J. A., St Clair, E. W. & Turka, L. A. CTLA4Ig: bridging the basic immunology with clinical application. Immunity 24, 233–238 (2006).
Article PubMed CAS Google Scholar
Vincenti, F. et al. Belatacept and Long-Term Outcomes in Kidney Transplantation. N. Engl. J. Med. 374, 333–343 (2016).
Article PubMed MATH CAS Google Scholar
Sakaguchi, S., Yamaguchi, T., Nomura, T. & Ono, M. Regulatory T cells and immune tolerance. Cell 133, 775–787 (2008).
Article PubMed MATH CAS Google Scholar
Hartigan, C. R., Tong, K. P., Liu, D., Laurie, S. J. & Ford, M. L. TIGIT agonism alleviates costimulation blockade-resistant rejection in a regulatory T cell-dependent manner. Am. J. Transpl. 23, 180–189 (2023).
Article CAS Google Scholar
Zimmerer, J. M. et al. Antibody-suppressor CXCR5(+) CD8(+) T cellular therapy ameliorates antibody-mediated rejection following kidney transplant in CCR5 KO mice. Am. J. Transpl. 22, 1550–1563 (2022).
Article CAS Google Scholar
Armitage, R. J., Macduff, B. M., Eisenman, J., Paxton, R. & Grabstein, K. H. IL-15 has stimulatory activity for the induction of B cell proliferation and differentiation. J. Immunol. 154, 483–490 (1995).
Article PubMed CAS Google Scholar
Hart, G., Avin-Wittenberg, T. & Shachar, I. IL-15 regulates immature B-cell homing in an Ly49D-, IL-12, and IL-18 dependent manner. Blood 111, 50–59 (2008).
Article PubMed CAS Google Scholar
Cooley, I. D., Read, K. A. & Oestreich, K. J. Trans-presentation of IL-15 modulates STAT5 activation and Bcl-6 expression in TH1 cells. Sci. Rep. 5, 15722 (2015).
Article ADS PubMed PubMed Central CAS Google Scholar
Yang, J. et al. Tracing Donor-MHC Class II Reactive B cells in Mouse Cardiac Transplantation: Delayed CTLA4-Ig Treatment Prevents Memory Alloreactive B-Cell Generation. Transplantation 100, 1683–1691 (2016).
Article PubMed PubMed Central MATH CAS Google Scholar
Young, J. S., McIntosh, C., Alegre, M. L. & Chong, A. S. Evolving Approaches in the Identification of Allograft-Reactive T and B Cells in Mice and Humans. Transplantation 101, 2671–2681 (2017).
Article PubMed PubMed Central Google Scholar
Stoeckius, M. et al. Cell Hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics. Genome Biol. 19, 224 (2018).
Article PubMed PubMed Central CAS Google Scholar
Aran, D. et al. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat. Immunol. 20, 163–172 (2019).
Article PubMed PubMed Central MATH CAS Google Scholar
Dann, E., Henderson, N. C., Teichmann, S. A., Morgan, M. D. & Marioni, J. C. Differential abundance testing on single-cell data using k-nearest neighbor graphs. Nat. Biotechnol. 40, 245–253 (2022).
Article PubMed CAS Google Scholar
Borcherding, N., Bormann, N. L. & Kraus, G. scRepertoire: An R-based toolkit for single-cell immune receptor analysis. F1000Res 9, 47 (2020).
Article PubMed PubMed Central MATH CAS Google Scholar
Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014).
Article PubMed PubMed Central CAS Google Scholar
Zhang, H. et al. Combined Immunotherapy With Belatacept and BTLA Overexpression Attenuates Acute Rejection Following Kidney Transplantation. Front Immunol. 12, 618737 (2021).
Article PubMed PubMed Central CAS Google Scholar
Roufosse, C. et al. A 2018 Reference Guide to the Banff Classification of Renal Allograft Pathology. Transplantation 102, 1795–1814 (2018).
Article PubMed PubMed Central MATH Google Scholar

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Acknowledgements

We would like to thank Dr. Marcus Clark for help with autoreactivity assays and Dr. Garnett Kelsoe for reagents. This work was funded through grants from the National Institute of Health, P01AI056299, P01AI175397, R01AI153124 to P.T.S. and R35HL166640 to R.A. P.L.R. received a scholarship from The São Paulo Research Foundation (2022/07035-3). Portions of figures were created with BioRender.com.

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These authors contributed equally: Manuel A. Podestà, Cecilia B. Cavazzoni.

Authors and Affiliations

Transplantation Research Center, Renal Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
Hengcheng Zhang, Manuel A. Podestà, Cecilia B. Cavazzoni, Yumeng Wu, Jeong-Mi Lee, Xiaofei Li, Paulo Lisboa Raeder, Pragya Chandrakar, Maya Gempler, Sierra Richardson, Reza Abdi & Peter T. Sage
Department of Immunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
Paulo Lisboa Raeder
Section of Rheumatology and The Knapp Center for Lupus and Immunology Research, Department of Medicine, The University of Chicago, Chicago, IL, USA
Deepjyoti Ghosh
Department of Surgery, Section of Transplantation, University of Chicago, Chicago, IL, USA
Ismail Sayin & Anita S. Chong
Department of Pediatrics, Division of Blood & Marrow Transplant & Cellular Therapies, University of Minnesota, Minneapolis, MN, USA
Bruce R. Blazar
Department of Pathology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
Astrid Weins

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Hengcheng Zhang
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Manuel A. Podestà
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Cecilia B. Cavazzoni
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Yumeng Wu
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Contributions

H.Z. designed and performed experiments, acquired and analyzed data, and wrote the manuscript. M.A.P. and C.B.C. performed experiments and analyzed data. Y.W., J.L., X.L., P.L.R., P.C., M.G., S.R., and I.S. performed experiments. D.G., B.R.B., R.A., A.W. and A.S.C. provided key technical help. P.T.S. designed experiments, analyzed data, secured funding, and wrote the manuscript. All authors edited the manuscript.

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Correspondence to Peter T. Sage.

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Zhang, H., Podestà, M.A., Cavazzoni, C.B. et al. Follicular regulatory T cells restrain kidney allograft rejection in mice by suppressing alloreactive B cells. Nat Commun 16, 2151 (2025). https://doi.org/10.1038/s41467-025-57468-4

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Received: 24 March 2024
Accepted: 24 February 2025
Published: 04 March 2025
DOI: https://doi.org/10.1038/s41467-025-57468-4