Targeting glomerular antigen to model cellular autoimmunity in the kidney

To unravel cytotoxic CD8+ T lymphocyte (CTL)-driven autoimmunity in the kidney, we established a new murine model, based on NOH (nephrin, chicken ovalbumin [OVA], hen egg lysozyme [HEL]) mice, expressing membrane bound OVA on the surface of podocytes (Supplementary Fig. S1A, B) [14]. Next, congenically (CD90.1) marked high affinity OVA257–264/H-2Kb-specific T cell receptor transgenic CD8+ T cells (OT-1 cells) were adoptively transferred into C57BL/6-NOH (NOH) and C57BL/6-wildtype (wt) mice (d1) [15, 16]. OT-1 cells transferred into NOH hosts quickly perished after 1 week (Supplementary Fig. S1C). Thus, subclinical infection with 2.5 × 103 cfu OVA-expressing Listeria monocytogenes (LM-OVA) was performed 24 h after cell transfer (d0), promoting in vivo activation of transferred OT-1 cells [17]. To sustain cellular immunity over time, mice received a subclinical booster infection with 2 × 106 pfu of OVA-expressing vesicular stomatitis virus (VSV-OVA) on day 21 [18, 19]. Weekly blood and urine analyses were performed on NOH and wt mice to monitor transferred OT-1 cells and proteinuria in the cohorts. For endpoint analyses, mice were sacrificed at early (d7; after primary infection) and late time points (d35–56; after booster infection). A detailed experimental plan is illustrated in Fig. 1A.

Fig. 1

OT-1 cells develop a distinct phenotype in an autoreactive environment. A Experimental plan. Initially (d1) 2 × 106 OT-1 cells were i.v. transferred into wt and NOH mice. After 24 h (d0) mice were infected with 2.5 × 103 cfu of OVA-expressing Listeria monocytogenes (LM-OVA). After 21 days, mice were reinfected/boostered with 2 × 106 pfu OVA-expressing vesicular stomatitis virus (VSV-OVA). Blood and urine samples were analyzed weekly. Final analysis was performed at early (d7) and a late time points (d35–56). B Quantitative flow cytometry analysis depicting less OT-1 cells in the spleens of NOH (red) vs. wt mice (blue) after 7 and 35 days. Total cell numbers were calculated by manually counting lymphocytes of whole organ lysates and multiplying counts with fractions obtained by flow cytometry analysis. C Anti-CD90.1 (red channel) immunofluorescence confirming less transferred OT-1 cells in spleens of NOH (right) vs. wt mice (left). D Representative flow cytometry plots and summary analysis (n = 5 per group) showing quicker decline of transferred OT-1 cells in peripheral blood of NOH mice (red) after primary (d7, d21) and secondary booster infection (d35) compared to wt mice (blue) over time. Dashed line indicating time point of booster infection. E CFSE assay demonstrating faster initial proliferation of transferred OT-1 cells in LM-OVA infected NOH (red) compared to wt mice (blue) after 72 h. F Representative flow cytometry plots showing expression of T cell receptor (TCR) chains Vα2 and Vβ5.1 prior to reinfection (d21). Time-course of TCR expression (right) demonstrating earlier TCR-internalization in NOH (red) compared to wt mice (blue). Dashed line indicating time point of booster infection. G Unsupervised UMAP-clustering of ~7000 OT-1 cell transcriptomes identifying 10 distinct clusters (upper plot). Cells from wt (blue) vs. NOH mice (red) clustered separately (lower plot). H Stacked barplots visualizing cluster composition of NOH vs. wt mice. Clusters 0, 4, 6, 7, and 8 mainly defined NOH-derived cells. I Annotated heat map of cluster-defining transcripts. Top five transcripts were identified by highest significant avgLog2FC values. J GO:BP term enrichment analysis of genes overexpressed in cluster 7. Network depicting linkages of genes and biological processes. K Dot plot illustrating the functional classification of clusters 0, 1, 2, 3, and 7 by curated genes associated with T cell effector, memory and inhibitory features. Bar below indicates if clusters were mainly represented by NOH or wt-derived OT-1 cells. L Volcano plot depicting differentially expressed genes comparing clusters 3 and 7. Dashed lines indicate log2 fold change value of 0.5 and p value of 0.05. If not stated differently, bars and whiskers of dot plots representing flow cytometry data depict means and respective standard errors of the mean (SEM). P values were calculated using unpaired student’s t test. All presented datasets are representative of at least three individual experiments with n ≥ 3 mice/group. To obtain single-cell RNA-sequencing data, OT-1 cells were adoptively transferred into wt and NOH mice and isolated 7 days after LM-OVA infection as depicted in (A). Splenocytes of four mice (two wt and two NOH each) were harvested and FACS-sorted to isolate OT-1 cells. Cells were labeled with antibody bound hashtag oligos and pooled together for sequencing (detailed information provided in “Materials and Methods” section)

Autoantigen expression facilitates differentiation of a distinct CTL phenotype

Transferred OT-1 cells were detectable in all mice after transfer and infection, indicating a robust cellular immunization model. Interestingly, when compared to wt mice, the total number of OT-1 cells detected in secondary lymphoid organs of NOH mice was significantly lower after 7 (1.3 [±0.3] × 106 vs. 2.7 [±0.3] × 106 OT-1 splenocytes; P = 0.0261) and 35 days (2.0 [±0.7] × 106 vs. 10.1 [±0.8] × 106 OT-1 splenocytes, P < 0.001) (Fig. 1B, C and Supplementary Fig. S2A, B). Besides lower OT-1 frequencies, a more rapid decline of transferred cells after primary infection (day 21: 2.5 [±1.3]% vs. 14.2 [±3.7]%, P = 0.0114), as well as a limited re-expansion after booster infection (day 35: 35.5 [±3.0]% vs. 76.5 [±12.6]%; P = 0.0132) was detected in peripheral blood of NOH vs. wt mice (Fig. 1D). These findings demonstrate a curtailed systemic immune response in NOH mice as a result of autoantigen expression in the kidney. To better understand how renal autoantigen expression affects early activation and division kinetics, we adoptively transferred CFSE-labeled OT-1 cells into wt and NOH mice and infected them as described. Intriguingly, OT-1 cells in NOH mice divided much faster within the first 72 h after transfer and infection than OT-1 cells in wt mice (30.4 [±2.1]% vs. 62.6 [±3.3]% of CFSE+ OT-1 cells, P < 0.0001; Fig. 1E). Hence, we conclude that renal autoantigen is recognized by adoptively transferred OT-1 cells and fuels their early activation during infection with pathogens expressing the same antigen. Continuous autoantigen recognition in NOH hosts is further corroborated by sustained T cell receptor internalization of OT-1 cells from NOH mice (Fig. 1F) [20].

To characterize the systemic immune response and differentiation of autoantigen-specific CTLs in the context of concurrent renal antigen cross-presentation, we performed single-cell RNA sequencing of OT-1 cells, isolated from splenocyte suspensions of NOH and wt mice 7 days after initial transfer and infection. Unsupervised Uniform Manifold Approximation and Projection (UMAP) clustering of ~7000 OT-1 cells resulted in 10 clusters. Interestingly, OT-1 cells isolated from NOH (red) and wt mice (blue) clustered separately, indicating a distinct transcriptional profile of CTLs in the context of an auto-immune environment (Fig. 1G). Over 80% of NOH-derived OT-1 cells accumulated in clusters 0, 4, 6, 7, and 8, while cells from wt mice were mainly found in clusters 0, 1, 2, and 3 (Fig. 1H). Clusters were classified by their five most upregulated transcripts. We could identify subpopulations of OT-1 cells from NOH mice, expressing proliferation-associated genes, indicating higher proliferative activity of naïve autoreactive OT-1 cells in the NOH environment (clusters 6 and 8; Fig. 1I), which was well in line with CFSE division profiles (Fig. 1E). Properties of terminal T effector differentiation (upregulation of e.g., Klrg1, Cx3cr1, Zeb2, S1pr5, and Gzma) could be found in OT-1 cells derived from both NOH and wt mice, with a higher relative proportion in NOH mice (cluster 0; Fig. 1H, I) [21,22,23]. By contrast, upregulation of T memory (precursor) associated transcripts (e.g., Il7r, Cxcr3, Id2) was mainly found in OT-1 cells isolated from wt mice (clusters 1 and 2, Fig. 1I) [24]. This may indicate a significantly altered T effector and T memory cell differentiation in NOH mice due to permanent antigen exposure. Pseudotemporal ordering of the sequencing data revealed a branched trajectory, suggesting differentiation of T effector and T memory cells originating from common stem cell-like precursors. NOH-derived OT-1 cells mainly clustered at the tips of the trajectories, corroborating a further advanced, distinct differentiation of both T effector and T memory populations in the context of persistent autoantigen recognition (Supplementary Fig. S3A). Interestingly, two clusters shared properties of T central memory (TCM) differentiation (e.g., upregulation of Sell, Ccr7, Tcf7) [25, 26]. One mainly contained wt-derived OT-1 cells, the other one cells from NOH mice (clusters 3 and 7, respectively, Fig. 1I). Functional enrichment analysis on differentially expressed genes (DEGs) of the NOH-derived cluster 7 divulged an upregulation of genes associated with lymphocyte differentiation and regulation of T cell activation (Fig. 1J). Further analysis of feature expression regarding curated effector, memory and inhibitory signatures of clusters 0, 1, 2, 3, and 7 (Fig. 1K) and comparing DEGs of clusters 7 and 3 (Fig. 1L) revealed a distinct T memory phenotype of NOH-derived OT-1 cells in cluster 7: while cells of cluster 3 predominantly expressed T memory associated transcripts (e.g., Sell, Il7r, Tcf7, Ccr7), NOH-derived OT-1 cells of cluster 7 also expressed markers associated with T cell dysfunction (e.g., Tox, Ikzf2, Ctla4, Lag3, Cd200) [24, 27]. Interestingly, Id3, a T memory marker delineating precursors of exhausted T cells was also more highly expressed in cluster 7 (Fig. 1K, L and Supplementary Fig. S3B–D) [28]. A unique phenotype of OT-1 memory cells in NOH mice was further delineated by complementary gene set enrichment (GSEA) and feature expression analyses (Supplementary Fig. S4A, B). Hence, the presented analysis supports a model in which splenic OT-1 cells from NOH mice display a hybrid phenotype, comprising both features of T memory formation and T cell dysfunction.

Next, multi-color flow cytometry analysis was performed to explore the differentiation phenotype and evaluate the cytotoxic potential of autoreactive OT-1 cells. As indicated by histological analysis (Fig. 1B, C), lower percentages of transferred OT-1 cells (12.1 vs. 29.6%, P = 0.0017) could be retrieved from NOH mice at day 7 (Fig. 2A). OT-1 cells from NOH mice displayed a strong skewing toward a T effector phenotype with elevated frequencies of KLRG-1+ (39.4 vs. 7.4%, P < 0.0001), CD62L−CD44+ (48.7 vs. 34.1%, P = 0.0027), and CX3CR1+ (41.9 vs. 21.5%, P = 0.0005; Fig. 2B and Supplementary Fig. S5A, B). Besides pronounced effector characteristics, OT-1 cells from NOH mice expressed higher levels of the inhibitory receptors programmed death-1 (PD-1; normalized MFI 1.0 vs. 1.9, P < 0.0001) and T cell immunoglobulin mucin-3 (Tim-3; normalized MFI 1.0 vs. 1.3, P = 0.0395), even at an early time point (Fig. 2C and Supplementary Fig. S5C–F). To assess the cytotoxic capacity of OT-1 cells, splenocytes were restimulated in vitro with their cognate antigen (SIINFEKL): after restimulation, fewer OT-1 cells from NOH vs. wt mice were capable of producing the pro-inflammatory cytokines IFN-γ (64.7 vs. 87.1%, P < 0.0001), TNF (33.5 vs. 63.3% double positive, P < 0.0001), and IL2 (non-significant trend at d7; Fig. 2D–F). Exposing OT-1 cells to increasing amounts of SIINFEKL and measuring cytokine production in vitro, showed lower functional avidity in OT-1 cells from NOH mice, which could not be compensated for with higher antigen concentrations (data shown for IFN-γ; Fig. 2G). Figure 2H summarizes the immune phenotype of OT-1 cells isolated from both NOH and wt mice on day 7. The results align with our single-cell data, supporting the conclusion of an aberrant differentiation in the context of autoantigen recognition.

Fig. 2

Autoreactive OT-1 cells express more inhibitory markers and produce less cytokines, 7 (A–H) and 35 days (I–P) after adoptive cell transfer. Representative flow cytometry plots discriminating transferred OT-1 cells from native CD8+ cells (CD90.1−) in splenocyte suspensions. Dot plot (right) shows significantly lower OT-1 cell fractions in NOH (red) compared to wt mice (blue) on day 7 (A) and day 35 (I). Representative flow cytometry plots illustrating KLRG1 and CD127 expression of transferred OT-1 cells. Dot plot and stacked bar plot depicting higher percentages of KLRG1+ CD127− short-lived effector OT-1 cells, compared to KLRG1− CD127+ memory precursor OT-1 cells in NOH (red) vs. wt mice (blue) on day 7 (B) and day 35 (J). Representative histograms illustrating PD-1 expression of transferred OT-1 cells. Dot plot comparing normalized mean fluorescent intensities (MFIs) of the PD-1 signal, showing higher PD-1 expression in OT-1 cells from NOH (red) vs. wt mice (blue) on day 7 (C) and day 35 (K). Flow cytometry plots illustrating interferon-γ (IFNγ) and tumor necrosis factor (TNF) production of transferred OT-1 cells after in vitro restimulation with 10−6 M SIINFEKL peptide; cytokine excretion blocked with brefeldin A. Dot plots showing lower fractions of IFNγ+ and IFNγ+TNF+ double-positive OT-1 cells in NOH (red) vs. wt mice (blue) on day 7 (D) and day 37 (L). Flow cytometry plots illustrating tumor necrosis factor (TNF) and IL2 production of transferred IFNγ+-OT-1 cells after in vitro restimulation. Dot plots indicating lower fractions of IL2+IFNγ+TNF+ triple positive OT-1 cells in NOH (red) vs. wt mice (blue) on day 7 (E) and day 35 (M). Radial charts comparing cytokine production of OT-1 cells in NOH (red) vs. wt mice (blue). SP single positive, (IFNγ+); DP double positive, (IFNγ+TNF+); TP triple positive, (IL2+IFNγ+TNF+) on day 7 (F) and day 35 (N). Functional avidity testing demonstrated that higher SIINFEKL concentrations could not increase the capability of IFNγ production in OT-1 cells from NOH mice (red) on day 7 (G) and day 35 (O). Spider graphs summarizing relative expression of activation markers, inhibitory receptors and cytokine production on day 7 (H) and day 35 (P). Bars and whiskers of dot plots depict means and respective standard errors of the mean (SEM). P values were calculated using unpaired student’s t test. All presented datasets are representative of at least three individual experiments with n = 5 mice per group. Normalized Median Fluorescence Intensities (MFIs) were calculated by dividing the MFIs of each sample by the mean MFI of the respective wt group

Autoreactive OT-1 cells bear the potential of re-expansion upon systemic reencounter with the autoantigen. As demonstrated histologically and in the time-course analysis of peripheral blood (Fig. 1B–D), OT-1 proliferation was curtailed in NOH mice after booster infection with VSV-OVA (15.6 vs. 48.6%, P < 0.0001, Fig. 2I). The above described hybrid phenotype of NOH-derived OT-1 cells was even more striking after re-challenge with VSV-OVA. Skewing toward effector differentiation of NOH-derived OT-1 cells was even more pronounced at day 35 (KLRG1+ 45.3 vs. 14.5%, P = 0.0007; CD62L− 88.5 vs. 66.7%, P < 0.0001; CX3CR1+ 71.7 vs. 35.2%, P < 0.0001; Fig. 2J and Supplementary Fig. S5G, H). Additionally, more inhibitory receptors were upregulated in OT-1 cells of NOH vs. wt mice at the late time point (Fig. 2K and Supplementary Fig. S5I–L). While the capability of IFN-γ production was maintained in NOH-derived OT-1 cells at day 35 (IFN-γ+: 68.8 vs. 85.5%, P < 0.0001), fractions of IFN-γ+TNF+-double positive (12.8 vs. 29.9%, P < 0.0001) and INF-γ+TNF+IL2+-triple positive (0.9 vs. 2.4%, P = 0.0004) cells were generally lower at the late time point (Fig. 2L–N), and the reduced functional avidity in NOH vs. wt OT-1 cells was still apparent (Fig. 2O). Figure 2P summarizes the immune phenotype of OT-1 cells at day 35. Comparable results could be observed when a higher LM-OVA dose (250,000 cfu) was administered as a booster infection (homologous prime-boost system) instead of VSV-OVA (Supplementary Fig. S6).

In summary, autoantigen exposure resulted in a restricted systemic immune response in NOH mice: First, a more rapid decline of peripheral OT-1 cells was induced. Second, it imposed the development of a stable hybrid OT-1 phenotype in NOH mice, which was characterized by both T memory features and T inhibitory traits. Lastly, while higher proportions of effector OT-1 cells differentiated in NOH mice, their capacity to produce cytokines was notably restricted.

Autoreactive CTLs can induce a renal phenotype

Despite the abrogated activation and differentiation of OT-1 cells, NOH mice developed significant proteinuria after OT-1 transfer and infection compared to wt mice, indicating renal pathology driven by podocyte-specific OVA expression. Neither adoptive OT-1 transfer nor prime-boost infection with OVA-expressing pathogens alone could induce a detectable renal phenotype (Fig. 3A). Pathological proteinuria in NOH mice was measurable beginning 14–21 days after OT-1 transfer and remained elevated over the entire observational period (Fig. 3B). Accordingly, serum creatinine levels were higher in NOH vs. wt mice after 35 days (6.5 [±0.5] vs. 4.2 [±0.7] µmol/l; P = 0.0166; Fig. 3C). Both findings indicate renal damage in the context of CTL-driven autoimmunity.

Fig. 3

Autoreactive OT-1 cells induce a renal phenotype. A Dot plot illustrating semi-quantitative proteinuria assessed via colorimetric dipstick assays after 35 days. NOH mice (red) develop significant proteinuria after OT-1 cell transfer and infection, compared to wt mice (blue) and NOH mice after either infection (green) or OT-1 transfer (yellow). B Time-course showing persistent proteinuria in NOH mice (red). Dashed line indicates time point of booster infection. C Dot plot showing higher serum creatinine levels in NOH (red) vs. wt (blue) mice after 35 days. D Quantitative flow cytometry analysis depicting more OT-1 cells in the kidney of NOH (red) vs. wt mice (blue) after 7 (left) and 35 (right) days. Total cell numbers were calculated by manually counting lymphocytes of whole organ lysates and multiplying counts with fractions obtained by flow cytometry analysis. E Dot plot comparing anti-OVA IgG levels in serum of NOH (red) vs. wt (blue) mice. Lower IgG levels were detected in NOH vs. wt mice after 35 days, indicating a curtailed humoral immune response. F Immunofluorescence of whole kidney sections, labeled with FITC-anti-CD8α- (green channel) and PE-anti-CD90.1-antibodies (red channel), depicting the OT-1 cell infiltration in wt (left) and NOH mice (right) after 7 days. G Dot plots showing higher OT-1 cell density/mm2 (upper graph) and percentage of infiltrated cortex area (lower graph) in NOH (red) vs. wt mice (blue) after 7 days. H Immunofluorescence of whole kidney sections, labeled with FITC-anti-CD8α- (green channel) and PE-anti-CD90.1-antibodies (red channel), depicting the OT-1 cell infiltration in wt (left) and NOH mice (right) after 35 days. I Dot plots showing higher OT-1 cell density/mm2 (upper graph) and percentage of infiltrated cortex area (lower graph) in NOH (red) vs. wt mice (blue) after 35 days. J 16-plex 4i immunofluorescence of whole kidney sections, labeling immune cell entities and structural markers after 35 days. K Dot plot showing a higher number of immune cells per infiltrated periglomerular area in NOH (red) mice. n depicts the number of analyzed glomeruli/sample. Comparison of three NOH mice (red) to wt control (blue). L Dot plot illustrating fractions of affected glomeruli/whole kidney section. M Dot plot illustrating immune-cell composition of periglomerular infiltrates. Bars and whiskers of dot plots depict means and respective standard errors of the mean (SEM). P values were calculated using unpaired student’s t test or one-way ANOVA with post-hoc Tukey’s multiple comparisons method if two or more groups were analyzed. All presented datasets are representative of at least three individual experiments with n ≥ 3 mice/group

In contrast to limited OT-1 expansion in the periphery, transferred cells accumulated in the kidneys of NOH mice, where the autoantigen is expressed. Significantly more OT-1 cells were detected in kidneys of NOH vs. wt mice, 7 (2.6 [±1.2] × 104 vs. 0.4 [±0.1] × 104; P = 0.0492) and 35 days (7.0 [±1.9] × 104 vs. 1.2 [±0.2] × 104; P = 0.0110) after transfer (Fig. 3D). Although OVA-specific immunoglobulin G levels remained lower in NOH vs. wt mice (Fig. 3E), humoral immune response may additionally contribute to the observed phenotype.

We performed histopathological analysis of whole kidney sections to further characterize renal infiltrations. Tissues were stained for CD8 and the congenic marker CD90.1 to label transferred OT-1 cells in host kidneys of NOH and wt mice. Seven days (early time point) after OT-1 transfer and primary LM-OVA infection, only a few OT-1 cells were randomly scattered throughout kidneys of wt mice, whereas dense OT-1 infiltrates with predominantly periglomerular and proximal peritubular localization could be detected in kidneys of NOH mice (Fig. 3F). Semi-automated cell type identification and infiltrate detection (Supplementary Fig. S7 and “Materials and Methods” section) confirmed higher numbers of infiltrating OT-1 cells in kidney sections of NOH vs. wt mice (435 [±85] vs. 204 [±33] OT-1 cells/mm2; p= 0.0355) and larger infiltrated cortex areas (13.0 [±2.8] vs. 4.8 [±1.1]% of infiltrated cortex area; p = 0.0266) (Fig. 3G). Corresponding to chronic proteinuria, histopathological analysis on day 35 revealed persistent infiltration (390 [±61] vs. 70 [±12] OT-1 cells/mm2; P = 0.0009 and 13.2 [±2.6] vs. 0.2 [±0.2]% of infiltrated cortex area; P = 0.0010) in kidneys of NOH mice. As opposed to peripheral OT-1 counts, the number of renal OT-1 cells declined in wt mice over time (Fig. 3H, I). Complementary brightfield histology of both time points corroborated these findings (Supplementary Fig. S8A, B). Additional in-depth histopathological analysis on day 35 also revealed features of structural kidney damage in NOH mice (Supplementary Fig. S8C–E).

As expected, neither an isolated (prime-boost) infection nor an isolated adoptive OT-1 transfer was sufficient to induce renal CTL infiltrations (Supplementary Fig. S9A, B). By contrast, comparably dense OT-1 infiltrations were also observed in the context of a homologous prime-boost system, applying a higher LM-OVA dose (250,000 cfu) instead of VSV-OVA as booster infection on day 21 (Supplementary Fig. S10A, B).

To characterize the structure and composition of renal infiltrates, multiplex immunofluorescence staining was performed, targeting a total of 16 different immune cell and structural tissue markers (Fig. 3I and Supplementary Fig. S11). Periglomerular infiltrates appeared significantly denser (1354 [±118] vs. 237 [±32] immune cells/mm2, P < 0.05; Fig. 3K) and more glomeruli were affected in NOH vs. wt mice (Fig. 3L). As expected, infiltrates were composed by several different immune cell entities. Besides CD8+ CTLs (641 [±72] cells/mm2), CD4+ T cells (1561 [±227] cells/mm2), CD11c+ dendritic cells or tissue macrophages (235 [±47] cells/mm2), and F4/80+ macrophages (1111 [±41] cells/mm2) could be detected within the periglomerular infiltrates (Fig. 3M).

Collectively, activated autoreactive OT-1 cells could initiate renal autoimmunity in NOH mice, despite the limited systemic cellular immune response in presence of autoantigen expression.

Glomerullary shedded antigens are presented in the periglomerular space

Since OVA-expressing podocytes in NOH mice reside within the enclosed Bowman’s capsule, they are not directly accessible by immune cells [29]. Hence, we wondered how OT-1 cells are able to sense their cognate antigen in NOH mice and why infiltrates largely surrounded glomeruli and proximal tubules.

To assess cross-presentation of antigens that pass through the nephron, fluorescent dye tagged OVA was injected intravenously (i.v.) into wt mice. With a molecular size of ~45 kDa, the conjugate is filtered through the glomerular slit diaphragm. Immunofluorescence imaging of kidney sections 60 min after conjugate injection depicted bright OVA signals in brush borders and apical poles of proximal tubular epithelial cells (PTECs; Fig. 4A). To identify PTECs, anti-EpCam-staining was performed, mainly labeling distal tubular and collecting duct epithelial cells [30]. Quantification of OVA signals by multi-color flow cytometry confirmed initial OVA uptake in proximal, rather than distal tubular or collecting duct epithelial cells (Fig. 4B). Signal intensity in proximal tubular cells slowly declined over time, most likely due to further procession and degradation of the protein. Tubular OVA uptake appeared very effective, with almost all filtrated proteins being taken up by PTECs. To test the efficacy of protein uptake, in vitro antigen stimulation of OT-1 cells with urine of mice 60 min after OVA or SIINFEKL injection was performed. Urine from these mice was not sufficient to induce relevant OT-1 proliferation, compared to urine from control mice that was spiked with OVA or SIINFEKL (Fig. 4C).

Fig. 4

Uptake and presentation of ovalbumin in the kidney. A Wt kidney section 60 min after AF488-OVA injection and PBS-perfusion through the renal artery. Representative immunofluorescence showing OVA (green channel) accumulation in proximal tubular cells, identified by low signal of co-staining with anti-CD326 (EpCam)-antibody (red channel). B FACS analysis of proximal (CD45−EpCamlow) vs. distal (CD45−EpCamhi) renal tubular epithelial cells, 60 (left) and 120 min (right) after AF555-OVA injection, demonstrating the OVA uptake in proximal tubular segments. Control: CD45−EpCamlow renal cells 60 min after PBS injection. C In vitro stimulation of CFSE-labeled OT-1 cells for 72 h, demonstrating high effectiveness of OVA uptake in proximal tubular cells. Division rates of OT-1 T cells stimulated with urine of wt mice taken 60 min after i.v. OVA- or SIINFEKL injection were compared to positive controls of OT-1 CD8+ T cells stimulated with urine spiked with OVA protein or SIINFEKL peptide. D Wt kidney section 60 min after AF488-OVA injection (green channel) and PBS-perfusion through the renal artery; co-staining against MHCII. Representative immunofluorescence demonstrating OVA uptake (green channel; ►) in periglomerular MHCII+-antigen-presenting cells (magenta channel). E Unsupervised clustering of kidney cells (dimensionality reduction with UMAP and cluster detection with FlowSOM algorithm applied on flow cytometry data), characterizing the renal immune cell compartment (left) and heat map showing relative marker expression of detected clusters (right). F Representative flow cytometry plots of kidney cell suspensions 60 min after AF488-OVA injection, demonstrating OVA uptake and SIINFEKL-cross-presentation via MHCII+CX3CR1hiCD11cint antigen-presenting cells (central plot). Control: 60 min after PBS injection (right plot). G Superimposition of AF488-OVA (green, left dot plot) and MHCI-SIINFEKL signals (red, right dot plot) on UMAP, demonstrating processing and cross-presentation of injected OVA in antigen-presenting cells (APCs). Histograms illustrating AF488-OVA (green, left histogram plot) and MHCI-SIINFEKL (red, right histogram plot) signals in APCs, 30, 60, and 120 min after AF488-OVA injection. Graphs on the right comparing percentages (left graph) and MFIs (right graph) of OVA+ (green) and MHCI-SIINFEKL+ (red) over time. H Schematic, illustrating cross-presentation of podocyte antigens: dying podocytes release antigens/epitopes (e.g., OVA) within Bowman’s capsule. They are transcellularly transported in the periglomerular space by proximal tubular epithelial cells. Endocytosis and antigen presentation by APCs can initiate adaptive immunity within the kidney

Co-staining the tissue sections with anti-MHCII-antibody revealed OVA uptake in MHCII+ antigen-presenting cells (APCs) in the interstitium, indicating transcytosis through PTECs (Fig. 4D). To confirm uptake and cross-presentation via APCs, renal immune cells were classified by unsupervised clustering and cluster identification of flow cytometry data from kidney single-cell suspensions (Fig. 4E). MHCII+CX3CR1hiCD11cint APCs were identified to accumulate fluorescence dye tagged OVA. Moreover, these APCs also cross-presented OVA in the periglomerular and proximal peritubular space. This was demonstrated by flow cytometry staining with the monoclonal antibody 25-D1.16 that recognizes OVA-derived SIINFEKL bound to the MHC class I molecule H2-Kb (Fig. 4F). We found that OVA and MHCI-SIINFEKL signals were both enriched in the APC cluster (Fig. 4G). Temporal analysis showed quick OVA uptake in APCs, with signals plateauing 30–60 min after injection. Accordingly, antigen uptake, processing, and cross-presentation were time delayed with signals constantly increasing during the observational period of 120 min (Fig. 4G).

Consequently, our results promoted a model for intrarenal antigen cross-presentation: antigens that are either filtered or shedded within the glomerulus are most likely taken up by PTECs and from there released into the renal interstitium. Here, surveilling APCs can capture, process, and render the antigens accessible to CTLs. Figure 4H illustrates the concepts of this model.

Autoantigen promotes formation of potential TRM cells fueling local autoimmunity

Although systemic T memory formation of autoreactive OT-1 cells was limited in NOH mice, renal infiltrations persisted and even increased after booster infection. The previously identified autoreactive T memory subpopulation in NOH mice (cluster 7) may have initially fed renal infiltrations. However, these cells were probably not the only factor promoting sustained renal autoimmunity. Especially, since splenic autoreactive OT-1 cells exhibited features of T cell dysfunction (Fig. 1K, L). To explore the phenotype of kidney-specific T cells and distinguish them from their circulating counterparts, flow cytometry analyses of kidney single-cell suspensions were performed. In line with histological findings, more OT-1 cells were found in single-cell suspensions of NOH vs. wt kidneys. OT-1 frequencies further increased after booster infection (19.4 vs. 9.8% of single cells, P = 0.0180; Fig. 5A and Supplementary Fig. S12A).

Fig. 5

Autoreactive OT-1 cells accumulate in NOH-kidneys originating a potential TRM subpopulation. A Representative flow cytometry plots identifying transferred OT-1 cells in kidney single-cell suspensions. Dot plot (right) showing a significantly higher percentage of OT-1 cells in kidneys of NOH (red) compared to wt mice (blue) on day 35. B Unsupervised clustering of kidney cells (dimensionality reduction with UMAP and cluster detection with FlowSOM algorithm applied on flow cytometry data) depicting a TRM OT-1 cell subpopulation in kidneys of NOH mice (purple cluster [2]; >100 cells required per defined cluster). Marker-specific histograms and summarizing heatmap showing expression of TRM markers CD103 and CD69, as well as higher levels of inhibitory makers (PD-1, CD39, NKG2A, CD94, LAG3) in cells of the purple cluster (2). C Representative flow cytometry plots illustrating CD69 and CD103 expression of renal OT-1 cells on day 35 after heterologous prime-boost infection. Dot plots depicting a higher percentage of CD69+ cells (left) and double positive CD69+CD103+ OT-1 TRM cells (right) in kidneys of NOH (red) vs. wt mice (blue). D Immunofluorescence of kidney section, labeled with APC-anti-CD103- (blue channel) and PE-anti-CD90.1-antibodies (red channel), depicting OT-1 TRM cells in periglomerular infiltrates of NOH mice. E Representative histograms illustrating PD-1 expression of double positive (CD69+CD103+), single positive (CD69+CD103−) and double negative (CD69−CD103−) renal OT-1 cells in NOH mice on day 35. Dot plot comparing normalized mean fluorescent intensities (MFIs) of the PD-1 signal, showing higher PD-1 expression in double positive (CD69+CD103+) vs. single positive (CD69+CD103−) and double negative (CD69−CD103−) renal OT-1 cells. F Representative immunofluorescence of wt (upper picture) and NOH (lower picture) kidney sections, showing elevated PD-L1 expression (green channel) in proximal tubular epithelial cells of infiltrated areas. Co-staining for transferred OT-1 cells (red channel) and renal APCs (magenta channel). G Immunofluorescence of kidney sections, labeled with FITC-anti-CD8α- (green channel) and PE-anti-CD90.1-antibodies (red channel), demonstrating that renal OT-1 infiltration can be detected in NOH mice on day 35 after primary infection, followed by weekly OVA injections (right). No infiltrates were detected in wt mice after infection and weekly OVA injections (upper left) and NOH mice after primary infection alone (lower left). H Time-course showing persistent proteinuria in NOH mice (red) after primary infection, followed by weekly OVA injections. I Representative flow cytometry plots illustrating CD69 and CD103 expression of renal OT-1 cells on day 35 after primary infection and weekly OVA injections. Dot plots depicting a higher percentage of double positive CD69+CD103+ OT-1 TRM cells (right) in kidneys of NOH (red) vs. wt mice (blue). J Summary analysis (n = 3/group) showing a decline of transferred OT-1 cells in peripheral blood of NOH (red) vs. wt (blue) mice after primary infection and weekly OVA injections. Bars and whiskers of dot plots depict means and respective standard errors of the mean (SEM). P values were calculated using unpaired student’s t test or one-way ANOVA with post-hoc Tukey’s multiple comparisons method if two or more groups were analyzed. All presented datasets are representative of at least three individual experiments with n ≥ 3 mice/group. Normalized MFIs were calculated by dividing the MFIs of each sample by the mean MFI of the respective wt group

Unsupervised clustering of flow cytometry data revealed a specific OT-1 subpopulation in NOH mice, expressing the tissue-resident TRM cell markers CD103 and CD69, but also higher levels of the inhibitory receptors PD-1, lymphocyte activating gene-3 (LAG3) and CD39 (Fig. 5B). The majority of OT-1 cells derived from NOH mice expressed CD69, while a smaller subpopulation also expressed CD103 (CD69+/CD103+: 13.5 vs. 0.5%, P < 0.0001; Fig. 5C). Additional histological analysis, focusing on CD103 as a surrogate marker, revealed that these potential TRM cells resided within the periglomerular and peritubular infiltrates in kidneys of NOH mice (Fig. 5D). Expression of TRM makers increased over time. After primary infection, expression of CD69 and CD103 in NOH mice was lower compared to the later time point (Fig. 5C and Supplementary Fig. S12B). Hence, CD69 expression is most likely induced in the context of TRM differentiation or persistent antigen recognition, and not in the context of early activation. This was further corroborated by comparable expression patterns of activation and memory markers in NOH and wt-derived renal OT-1 cells at both time points (Supplementary Fig. S12C–E, J–L). Interestingly, potential TRM differentiation in the auto-immune environment appeared to correlate with increasing expression of inhibitory receptors over time (Supplementary Fig. S12F–I, M–O). Highest expression levels of PD-1 were found in CD69+CD103+ double-positive cells, with gradually lower expression of PD-1 in CD69+ single positive and CD69−CD103− double negative OT-1 cells in the kidney (normalized MFI 3.9 vs. 3.0 vs. 1.0, global P = 0.0075; Fig. 5E). The inhibitory receptors LAG3 and CD39 were found to have comparable expression patterns (Supplementary Fig. S12P, Q). Additionally, PD-L1 expression was significantly upregulated in PTECs of infiltrated areas (Fig.