Renal tubular epithelial cells are constitutive non-cognate stimulators of resident T cells

Summary

Understanding the roles of different cell types in regulating T cell homeostasis in various tissues is critical for understanding adaptive immunity. Here, we show that RTEC (renal tubular epithelial cells) are intrinsically programed to polyclonally stimulate proliferation of kidney αβT cells by a cell-cell contact mechanism that is MHC-independent and regulated by CD155, αVβ3-integrin, and vitronectin. Peripheral CD4 and CD8 are resistant to RTEC-mediated stimulation, while the minor subset of double-negative (DN) T cells are responsive. This novel property of RTEC was discovered by using a co-culture system that recapitulates spontaneous in vivo polyclonal proliferation of kidney T cells, which are mainly comprised of T_CM and T_EM cells. This robust cell-intrinsic stimulatory role of RTEC could be underlying the steady-state spontaneous proliferation of kidney T cells. The results have conceptual implications for understanding roles of different cell types in regulating systemic and organ-specific T cell homeostasis.

INTRODUCTION:

During thymic development, CD4 T cells are positively selected on MHC class II (MHCII) molecules and become restricted to recognition of exogenous antigens in the context of MHCII molecules. On the other hand, CD8 T cells are positively selected on MHC class I (MHCI) and become restricted to recognition of exogenous antigens in the context of MHCI molecules. A minor subset of double-negative (DN) T cells that lack the CD4 and CD8 coreceptors and develop in the thymus are rare in peripheral lymphoid organs, but constitute a large percentage of total αβ T cells in the kidney and the gut epithelium.^1,2 Conventional T cells recognize cognate antigens in the context of their MHC restriction molecules expressed on surface of professional antigen presenting cells, APCs (B cells, dendritic cells and macrophages). Furthermore, APCs provide a secondary costimulatory signal via delivered by surface CD80 and CD86 molecules that engage the CD28 costimulatory molecule on T cells.³ Recognition of antigens in the context of MHC molecules by cognate T cells ensures specificity of immune responses and second the signal is necessary for optimal clonal T cell activation. Activated T cells undergo rapid proliferation, leading to clonal expansion and differentiation into antigen specific effectors and memory T cells. The majority of effector T cells undergo apoptosis following antigen clearance while memory T cells slowly cycle in the absence of cognate antigens. The latter have several subsets, including central memory T (T_CM) cells, effector memory T (T_EM) cells, and tissue resident memory (T_RM) cells that exhibit different immunosurveillance patterns.⁴ T_CM cells patrol lymph nodes for antigens and circulate through the blood, whereas T_EM cells transiently pass through tissue to mediate their effector function before returning and circulating through the blood. On the other hand, T_RM cell populations are retained in non-lymphoid tissues and remain numerically stable for long time, fueling intense interest in how the longevity of T_RM cells is regulated in different organs and roles of different cell types in their maintenance.

We have previously shown that kidney DN T cells are actively dividing in the steady state driven by cell-cell dependent mechanisms that is MHC-independent and partly driven by IL-2 secreted by CD8 and CD4 T cells.⁵ However, all cell types involved are unknown. To address this question, we were able to recapitulate spontaneous proliferation of kidney T cells in vitro using crude KMNC preparations where about 30% were RTEC. The results show that the phenomenon is an organ-autonomous and does not require systemic signals. Using sorted T cell subsets and primary RTEC, we identified RTEC as constitutive polyclonal stimulators of the kidney three T cell subpopulations of CD4, CD8 and double-negative (DN) subsets. The stimulatory mechanism, which is mainly mediated by MHC-independent cell-cell contact, is regulated by CD155, αVβ3-integrin and vitronectin. Among peripheral T cells only the minor subpopulation of DN T cells responded to RTEC stimulation but not the two major subpopulations of CD4 and CD8 T cells. Thus, in contrast to professional APCs, which stimulate T cells by MHC-restricted mechanism, RTEC are constitutive polyclonal stimulators of local kidney T cells in the absence of foreign antigens. The results have conceptual implications for understanding the roles of different cell types in regulating T cell homeostasis.

RESULTS

Organ-autonomous proliferation of kidney

We have previously shown that kidney T cells are made of CD4, CD8 and DN T subpopulations that are present at proportionally comparable frequencies in mice and are actively proliferating in the steady state in vivo using the BrdU assay.¹ In concordance with previous results, we detected that high expression of the Ki67 proliferation marker by the majority of kidney CD4, CD8 and DN subsets, confirming their spontaneous proliferation in the steady state (Fig. 1A). In contrast and as expected, the vast majority of peripheral CD4 and CD8 T cells did not express the Ki67 proliferation marker (Fig. 1B). However, about 50% of the minor population of peripheral DN T cells, were proliferating in the steady state as indicated by Ki67 expression (Fig. 1B). To gain insights into the underlying mechanism fueling proliferation of kidney T cells, we began by determining it is organ-driven, mediated by systemic signals, or require both. To distinguish between these possibilities, we determined whether we could recapitulate this phenomenon in vitro using a modified organ culture system (Fig. 1C, diagram). We isolated kidney mononuclear cells (KMNCs) using Percoll gradient as previously described.⁶ FACS analysis showed that T cells comprised about 38% of total lymphocytes in KMNC preparations and about 53% of T cells in lymph node (Fig. S1). This impurity proved to be critical for identifying the stimulatory role of RTEC as described below. We simultaneously prepared lymph node suspensions (hereafter referred to as peripheral T cells) from same donors. We labeled both preparations with CSFE and cultured at 37°C incubator in the absence of any exogenous antigen. Parallel cultures were stimulated with immobilized anti-CD3/CD28 antibodies and used as positive controls. Cultured cells were harvested five days later and stained with the antibody cocktails described in the method section. Different samples were acquired by FACS, and different T cell subsets in each culture were gated and analyzed for CFSE dilution using the FlowJo software. The three kidney subsets (DN, CD4 and CD8 T cells) exhibited strong spontaneous proliferation as indicted by CFSE dilution (Fig. 1C, top histogram panel). In contrast, peripheral CD4 and CD8 T cell subsets, as expected, showed no spontaneous proliferation as compared to their kidney counterparts. However, the rare population of peripheral DN T cells showed a barely detectable in vitro proliferation (Fig. 1C, second top panel). On the other hand, as expected, both kidney and lymph node T cell subsets proliferated strongly in response to anti-CD3/CD28 ex-vivo (Fig. 1C, the two bottom panels), confirming that both were functionally competent. Taken together, these results show that spontaneous in vivo proliferation of kidney T cells can be recapitulated in vitro, demonstrating it is organ-autonomous. This conclusion is emphasized by the failure of DN T cells present in lymph node suspensions to spontaneously divide in vitro, to do so indicates that such stimulators are absent from lymph node cell suspensions.

Figure 1. Organ-autonomous proliferation of kidney.

(A) A representative histogram overlay shows frequency of Ki67^hi among kidney T cell subsets. Graph shows cumulative data with mean ± SEM, from at least three independent experiments. *P<0.001.

(B) A representative histogram overlay shows frequency of Ki67^hi among peripheral T cell subsets. Graph shows cumulative data with mean ± SEM, from at least three independent experiments. ^****P<0.0001.

(C) A schematic overview of experimental design used to examine spontaneous proliferation of kidney and peripheral T cell subsets using KMNC and lymph node preparation, respectively. Top panel, Representative histogram panels show dilution of CFSE by gated kidney and peripheral T cell subsets in respective cultures. Bottom panel, Representative histograms show CFSE dilution by gated kidney and peripheral T cells in response to anti-CD3/CD28 stimulation.

Supporting data, see also figure S1.

RTEC are intrinsically programmed to constitutively activate kidney T cells

Next, we asked whether spontaneous in vitro proliferation of kidney T cells is mediated by cell-intrinsic mechanisms, cell-extrinsic mechanisms or both. Potential cell-extrinsic stimuli include soluble mediators as well as cell-cell interactions. Indeed, RTEC were present at significant numbers among KMNCs, which were prepared by Ficoll density gradient centrifugation. Given that RTEC can serve as non-professional APCs,^7,8 we sought to determine whether RTEC present in KMNC preparations drive in vitro proliferation of kidney T cells. To examine this possibility, we generated primary RTEC layers using an established method^9,10 and assessed their ability to stimulate sorted kidney T cell subpopulations using the CFSE assay. We FACS-sorted kidney T cell subpopulations, labeled each with CFSE and cocultured with primary RTEC or alone and assessed proliferation 5 days later. We also sorted autologous peripheral T cell subpopulations, labeled with CFSE and cocultured with primary RTEC or alone. None of sorted kidney T cell subpopulations showed significant proliferation when cultured alone, ruling out a role for cell-intrinsic mechanisms in mediating their proliferation (Fig. 2A). In contrast, each of the sorted kidney T cell subsets strongly proliferated when cocultured with primary RTEC, implicating RTEC in mediating their proliferation. Use of sorted T cell subsets and in vitro generated primary RTEC show that this phenomenon is a cell-intrinsic property of RTEC. In regards to peripheral T cell subsets, neither CD4 nor CD8 T cells showed any significant proliferation when cultured alone or with RTEC, indicating inability of RTEC to promote their proliferation. However, peripheral DN T cells did show significant proliferation when cocultured with RTEC, desmonstrating the ability of RTEC to induce their proliferation (Fig. 2B). Furthermore, RTEC induced expansion of peripheral DN T cells, but not conventional CD4 and CD8 T cells, when added to lymph node cell cultures (Fig. S2). Furthermore, RTEC significantly reduced apoptosis of peripheral DN T cells in co-cultures (Fig. S3). The results identified a novel function of RTEC as potent constitutive stimulators of kidney T cells.

Figure 2. RTEC are intrinsically programmed to constitutively activate kidney T cells.

(A) Representative histograms show significant CFSE dilution by FACS-sorted kidney T cell subsets only when cocultured with RTEC, but not when cultured alone. Graph shows cumulative data. Data points are shown for each mouse with mean ± SEM, from at least three independent experiments. ^**P<0.01, ^***P<0.001, ^****P<0.0001.

(B) Representative histograms show only peripheral DN, but not CD4 or CD8, T cell subsets, proliferated when cocultured with RTEC. Graph shows cumulative data. Data points are shown for each mouse with mean ± SEM, from at least three independent experiments. ^***P<0.001, ^****P<0.0001.

Supporting data, see also figure S2 and S3.

RTEC-driven T cell proliferation is polyclonal

Next, we determined whether TCRβ repertoires of kidney T cell subsets are different from those of peripheral T cell subsets. We did so by analyzing and comparing repertoires of FACS-sorted kidney and peripheral subsets using the high-throughput ImmunoSEQ assay. We found TCRβ repertoires of the three kidney subsets to be highly polyclonal with comparable Vβ gene usage to those of peripheral T cell subsets. The only noticeable difference was a slightly overrepresented usage of the Vβ13–02 gene by kidney DN T cells (Fig. 3A). There was a limited clonotype sharing within or across the two compartments. Among kidney T cells, CD4 and CD8 T cells shared 2.5% of their clonotypes and CD8 and DN T cells shared 3%. The highest sharing in the kidney was between CD4 and DN T cells that shared 13% of their clonotypes. Among peripheral T cells, the highest sharing was between CD4 and CD8 T cells, which shared 14% of their clonotypes, while the DN subset shared less than 3% of their TCRβ repertoires with either CD4 or CD8 T cells (Fig. 3B). Across the two compartments, we detected clonotypes that were shared between peripheral and kidney CD4 T cells. These clonotypes represented 20–30% of kidney CD4 T cells, but only 1–2% of peripheral CD4 T cells. The same pattern of sharing was observed for CD8 T cells where shared clonotypes represented 20–30% of kidney CD8 T cells, but only 1–2% of peripheral CD8 T cells. On the other hand, there was a very limited clonotype sharing between DN T cells in the two compartments, mounting to only about 3% of their total repertoires (Fig. 3C). Hence, responsiveness of peripheral DN T cells to RTEC-mediated stimulation could not be attributed to clonotype sharing with kidney DN T cells. Likewise, responsiveness of kidney T cell subpopulations to RTEC stimulation could not be attributed to similar clonotypic repertoires. Thus, the stimulatory function of RTEC is polyclonal and not restricted to certain clones

Figure 3. RTEC-driven T cell proliferation is polyclonal.

(A) Graphs show TCRVβ usage by kidney (left) and lymph node (right) T cell subsets.

(B) Venn diagram show TCR clones that are shared among DN, CD4 or CD8 T cell subsets in the kidney (left) and lymph nodes (right). Graphs show cumulative data from three different mice.

(C) Circos circles show TCR clones that are shared among DN, CD4 or CD8 T cell subsets in the kidney (left) and lymph nodes (right). Scatter plots show shared clones between kidney (x-axis) and LN (y-axis) respectively as percentages of total clones in each organ. Data points are shown for each mouse with mean ± SEM.

Majority of responders to RTEC-mediated stimulation are T_RM, T_CM and T_EM cells

Next, we analyzed and compared differentiation states of kidney and peripheral T cell subsets. We found that the majority (>50%) of the kidney CD4, CD8 and DN T cell subsets were antigen-experienced as determined by high expression of the CD44 activation marker. In contrast, only a small minority of peripheral CD8 (4% of total) and CD4 (10% of total) cells were antigen-experienced. However, about 40% of peripheral DN T cells were antigen-experienced as indicated by high expression of CD44 (Fig. 4A). Among antigen-experienced CD44^hi T cells, the three kidney subsets were comprised of T_RM (CD44^hiCD69^hiCD62L^low) and T_EM (CD44^hiCD69^lowCD62L^low) cells, and a minimal number of T_CM (CD44^hiCD69^lowCD62L^hi) cells. In contrast, CD44^hi antigen-experienced peripheral CD4, CD8 and DN T cells were comprised mainly of T_EM and T_CM subsets, with some CD4 T_RM cells (Fig. 4B). Thus, most of kidney T cell subsets and RTEC-responsive peripheral DN T cells are in an activated-state, consistent with their steady state proliferation.

Figure 4. Responders to RTEC-mediated stimulation are T_RM, T_CM and T_EM cells.

(A) Representative dot plots show percentages of CD44^hi among kidney (top panel) and peripheral (bottom) T cell subsets ex vivo. Numbers indicate percentages. Graph shows cumulative data. Data points are shown for each mouse with mean ± SEM, from at least three independent experiments. ^***P<0.001, ^****P<0.0001.

(B) Representative dot plots showing percentages of T_RM (CD44^hiCD69^hiCD62L^low), T_EM (CD44^hiCD69^lowCD62L^low) and T_CM (CD44^hiCD69^lowCD62L^hi) among gated CD44^hi kidney and lymph node T cell subsets. Graph shows cumulative data. Data points are shown for each mouse with mean ± SEM, from at least three independent experiments.

RTEC-induced T cell proliferation is MHC-independent

Upon coculturing of unfractionated peripheral T cells with RTEC, the majority of DN, but only few CD4 and CD8 T cells, proliferated. We took advantage of this observation and generated a hybrid system to investigate the stimulatory function of RTEC using proliferation of peripheral DN T cells as readout. In this system, we cultured primary RTEC with unfractionated peripheral T cells and examined proliferation of DN T cells under different conditions. We began by determining whether the stimulatory capacity of RTEC requires direct cell-cell contact, soluble factors or both using the Transwell assay. As a positive control, we cocultured peripheral T cells directly on RTEC layers. Separating T cells from RTEC in transwells significantly, but not completely, inhibited proliferation of DN T cells as compared to DN T cells in direct cocultures (Fig. S4). The results indicated that RTEC-stimulatory function is mainly through direct cell-cell contact with a complementing role for soluble factors. The role of soluble factors was confirmed by the ability of co-culture supernatants to induce appreciable proliferation of peripheral DN T cells (Fig. S4). Subsequently, we focused on the role of cell-cell contact in mediating RTEC-stimulatory function and determined whether it is driven by MHC / TCR interactions. We examined and compared the stimulatory ability of primary RTEC derived from wild type or mice lacking MHC class I and β2m-dependent non-classical MHC molecules (β2m KO), MHC class II molecules (MHCII KO) or both MHCI and MHCII (DKO). None of MHC deficiencies impaired the stimulatory ability of RTEC. Not only that, but deficiency of both MHCI and MHCII molecules significantly enhanced RTEC-mediated proliferation of DN T cells (Fig. 5A and 5B). The results show that the stimulatory capacity of RTEC was not due to presentation of self-antigens by β−2m-dependent MHCI or MHCII molecules (Fig. 5A & 5B). These results extend our previous findings that homeostasis of the majority of kidney DN T cells, except for a NK1.1+ subset, is β2-m- and MHC class II-independent.⁵ Consistent with the potent stimulatory function of MHC-deficient RTEC, culturing of KMNCs in the presence of MHCI-, MHCII-neutralizing antibodies or both caused only partial inhibition of spontaneous proliferation of kidney T cell subsets (Fig. 5C). Collectively, the results implicate RTEC in inducing proliferation of kidney T cells by MHC-independent mechanisms.

Figure 5. RTEC-induced T cell proliferation is MHC-independent.

RTEC prepared from kidneys of age-matched WT, β2m KO, MHCII KO, or DKO mice were cocultured with CFSE-labeled lymph node cells isolated from the same WT donors. Proliferation of DN T cells in different cultures was analyzed by FACS.

(A) Representative dot plots show percentages of CD4, CD8, and DN T cells in lymph node cells isolated from wildtype donors and cultured alone or with RTEC derived from WT, β2m KO, MHCII KO, or DKO mice. Numbers in quadrants indicate percentages. Graph shows percentages and absolute numbers from three independent experiments (mean ± SEM). *P<0.05, ^**P<0.01, ^****P<0.0001.

(B) A representative histogram overlay shows percentages of DN T cells in different cocultures as defined by genotype of RTEC used. Right graph shows cumulative data. Data points (mean ± SEM) are from at least three independent experiments. ^**P<0.01, ^***P<0.001, ^****P<0.0001.

(C) Representative histograms show percentages of CFSE^low among gated DN, CD4 or CD8 T cell subsets in KMNC culture that were cultured in the absence or the presence of anti-MHCI, anti-MHCII antibody or both antibodies. Graph shows cumulative data. Data points (mean ± SEM) are from at least three independent experiments. *P<0.05, ^***P<0.001, ^****P<0.0001.

Supporting data, see also figure S4.

Interactions of RTEC and lymph node T cells lead to robust changes in their production of soluble factors

We examined whether RTEC and lymph node cells modulate the ability of each other to produce immunomodulators. For this purpose, we used an Abcam cytokine array kit that analyzes a set of 96 immunomodulators of cytokines, chemokines/receptors, and inflammatory mediators. We isolated lymph node cells and cultured alone or added to a monolayer of RTEC. We used another monolayer of RTEC as a control for their baseline production of indicated modulators. After five days of incubation at 37 °C, we harvested supernatants from different cultures and examined for the modulators as per the manufacturer’s instructions. We found that 33 out of the 96 examined mediators were present exclusively in the RTEC cultures, whereas 18 were present only in the lymph node cultures. On the other hand, 36 modulators were detected in the co-cultures. Among these is the C-C motif chemokine 22 (CCL-22) which was barely detectable in either culture but was abundantly produced in the cocultures. Likewise, IL-1α was not detectable in individual cultures, but was significantly induced in the cocultures (120 and 50-fold above basal level respectively). On the other hand, soluble (shed) sCD62L was detected in lymph node cultures, but not in RTEC individual cultures, but was significantly increased (4-fold) in cocultures relative to its level in lymph node cultures. Conversely, GC-CSF was detected only in RTEC cultures, but not in cocultures, indicating lymph node cells inhibited its production by RTEC. There were also significant up and down modulations of several other mediators (Fig. 6A & 6B). These results show a reciprocal ability of RTEC and T cells to modulate the ability of each other to produce important immunodulators.

Figure 6. Coculturing of RTEC and lymph node cells results in profound changes in their secreted mediators.

(A) Representative array images of immunoblots depicting soluble mediators produced by lymph node cells and RTEC when cultured separately or cocultured together as described in the Methods section. A total of 96 mediators that were imprinted in duplicates (vertical adjacent dots) in membrane C3 and C4 as described in Methods. Red boxes indicate selected mediators that were positively modulated in cocultures relative to single cultures, whereas blue boxes indicate selected mediators that were negatively modulated in cocultures. Size of each dot reflects its intensity.

(B) Graphs show quantification of selected proteins measured using densitometry quantitative and expressed as Arbitrary Units. Data points (mean ± SEM) are acquired from duplicates. ^***P<0.001, ^****P<0.0001.

CD155 and αVβ3-integrin regulate stimulatory function of RTEC

Alfred Singer and colleagues,^11–13 have identified the CD155 adhesion molecule as a native self-protein that binds αβ TCR and activates mature thymic DN T cells by an MHC-independent mechanism. Binding assays and crystal structure analysis show that the CD155 interacts with the TCRαβ with high affinity (~200nM).^12,14 We found that CD155 was expressed by about 45% of RTEC (Fig. S5), leading us to assess whether CD155 is involved in RTEC-mediated stimulation of DN T cells. As postulated, we found that CD155 blockade significantly inhibited RTEC-induced proliferation and expansion of DN T cells as compared to positive controls (Fig. 7A & 7C). The ability of RTEC to upregulate surface CD69 on responding DN T cells was also significantly impaired by CD155 blockade as compared to control cocultures (Fig. 7B). Furthermore, as shown below, recombinant CD155 directly stimulated DN T cell proliferation in the absence of RTEC (Fig S8). On the other hand, blockade of CD226 (the primary ligand of Cd155) using a neutralizing antibody did not inhibit the ability of RTEC to induce DN T cell proliferation (Fig S6), ruling a major role for CD155/CD226 interactions in mediating the stimulatory function of RTEC. Additionally, consistent with the findings of Singer et. al.^11–13 who thoroughly investigated CD155 interactions with soluble TCRs that were cloned from DN T cells, we examined whether CD155 could directly interact with soluble TCRs extracted from LN T cells using the IP-FCM (Immunoprecipitation Detection by flow cytometry) assay. We covalently linked CD155 to CML-beads per manufacturer’s instructions and used it to capture soluble TCRs from T cell lysates. We used fluorochrome-conjugated anti-TCR antibody to detect its binding to the CML-CD155 beads. As a positive control, we used CML-CD155 to capture CD226, its primary ligand. In three independent experiments, we were able to detect TCR bound to CD155 beads by FACS (Fig 7D). Thus, whereas neutralizing experiments implicates CD155 in RTEC-mediated stimulation of DN T cells, IP-FCM experiments show that CD155 can directly interacts with TCRs.

Figure 7. Stimulatory capacity of RTEC is regulated by the CD155 adhesion molecule.

(A) A representative histogram overlay shows CFSE dilution by gated DN T cells among lymph node cells that were cultured alone (top histogram) or with RTEC in the absence (middle histogram) or presence (bottom histogram) of anti-CD155-neutralizing antibody. Graphs shows cumulative data of frequency and absolute number of CFSE^low of DN T cells in each of the three culture conditions. Data points (mean ± SEM) are from at least three independent experiments. ^***P<0.001, ^****P<0.0001.

(B) A representative histogram overlay show percentage of CD69 of gated DN T cells. Graphs show cumulative data of percentages of CD69^hi under the three culture conditions. Data points (mean ± SEM) are from at least three independent experiments. ^***P<0.001, ^****P<0.0001.

(C) Representative dot plots show frequency of DN T cells in cultures of lymph node alone (left) or cocultures of lymph nodes and RTEC in the absence (middle) or presence of anti-CD155-neutralizing antibody. Numbers in quadrants indicate percentages. Graphs show cumulative data denoting frequency and absolute numbers of DN T cells in each of the cultures from three independent experiments. Data points (mean ± SEM) are from at least three independent experiments. *P<0.05, ^***P<0.001, ^****P<0.0001.

(D) Top panel, Diagram depicting capture of CD226 by CD155-beads. Representative dot plots show detecting CD155-CD226 complexes by FACs after incubating CD155 beads with T cell lysates or tissue culture as negative control. Bottom panel, Diagram depicting capture of TCR by CD155-beads. Representative dot plots show detecting CD155-TCR complexes by FACs after incubating CD155 beads with T cell lysates or tissue culture as negative control. Graph shows cumulative for capturing of TCR by CD155 beads.

Data points (mean ± SEM) are from at least three independent experiments. ^***P<0.001.

Supporting data, see also figure S5, S6 and S8.

Integrins are transmembrane receptors that regulate cell-cell and cell-extracellular matrix (ECM) adhesion. Upon ligand binding, integrins via multiple transduction pathways induce signals that allow rapid and flexible responses, receptors movement to the cell membrane and cell cycle.¹⁵ These include αVβ3 integrin that localize with ectodomain of CD155 on the cell plasma membrane¹⁶ and interacts with vitronectin found in the extracellular matrix.^17,18 A large percentage of peripheral and kidney DN T cells express αVβ3 (Fig. S7). Kidney CD4 and CD8 T cells also expressed αVβ3 at levels higher than on peripheral T cells (Fig. S7). Expression of αVβ3 by T cells, even at low level, has been reported to contribute to pan-T cell activation by promoting T-T cell clustering and IL-2 signaling.¹⁹ Using a neutralizing antibody, we examined the role of αVβ3 in regulating RTEC-mediated activation of DN T cells. Our results show that blockade of αVβ3 significantly inhibited DN T cell activation as determined by CD69 upregulation and significantly inhibited their proliferation and expansion (Fig. 8A–C). Vitronectin is a αVβ3 receptor that has been implicated in activating T cells.^20,21 To directly examine the individual and combined roles of CD155 and vitronectin in regulating DN T cell proliferation, we immobilized recombinant CD155 (rCD155) and vitronectin (rVN) separately or together and cultured with lymph node cells for 5 days at 37 °C. Whereas both rCD155 and (rVN) were able to significantly induce proliferation and expansion of DN T cells as compared to control cultures, CD155 was more potent than rVN in inducing DN T cells proliferation (Fig. S8). In addition, mixture of rCD155 and rVN produced led to more proliferation DN T cells than when used separately.

Figure 8. Blockade of αVβ3 decreases percentage and absolute cell numbers of peripheral DN T cells in co-cultures.

(A) A representative histogram overlay showing CFSE dilution by gated DN T cells when cultured alone or cocultured with RTEC in the absence (middle) or presence (bottom) of an αVβ3-neutralizing antibody. Graphs show cumulative data of frequency and absolute number of CFSE^low of DN T cells in the three culture conditions. Data points (mean ± SEM) are from at least three independent experiments. ^***P<0.001, ^****P<0.0001.

(B) A representative histogram showing percentages of CD69^hi DN T cells in the three different cultures. Graph shows cumulative data. Data points (mean ± SEM) are from at least three independent experiments. *P<0.05.

(C) Representative dot plots showing frequency of DN T cells in cultures of lymph node alone (left) or cocultures of lymph nodes and RTEC in the absence (middle) or presence of an anti-αVβ3-neutralizing antibody. Numbers in quadrants indicate percentages. Graphs show cumulative data denoting frequency and absolute numbers of DN T cells in each of the cultures. Data points (mean ± SEM) are from at least three independent experiments. *P<0.05, ^**P<0.01, ^***P<0.001, ^****P<0.0001.

(D) Representative dot plots show representative histogram of CFSE dilution of CD4, CD8 and DN T cells from KMNC in culture in the presence and absence of anti-CD155 and anti-αVβ3 blocking antibody. Graphs show cumulative frequency and absolute numbers of CFSE^low of gated T cells from cultured KMNCs. Data points (mean ± SEM) are from at least three independent experiments. *P<0.05, ^**P<0.01, ^***P<0.001, ^****P<0.0001.

Supporting data, see also figure S7 and S8.

These results directly implicate CD155 and vitronectin in inducing DN T cell proliferation. Furthermore, blockade of CD155 or αVβ3-integrin significantly inhibited proliferation of kidney T cells among unfractionated KMNC (Fig. 8D). In addition, blockade of αVβ3, but not that of CD155, significantly reduced percentage and absolute cell number of gated EPCAM+ RTEC (Fig. S9). Thus, while both CD155 and αVβ3-integrin are critical regulatory of RTEC-induced T cell stimulation, only αVβ3-integrin, but not CD155, regulate RTEC cell survival.

DISCUSSION

In this study, we show that RTEC have a constitutive cell-intrinsic stimulatory function that is MHC-independent and regulated by the CD155 adhesion molecule and the αVβ3 integrin. All kidney T cell subsets are polyclonally responsive to RTEC-mediated stimulation. Peripheral CD4 and CD8 T cells are unresponsive, whereas the minor population of unconventional DN T cells are responsive to the RTEC-mediated stimulation. Taken together, our results show that RTEC are intrinsically programmed to constitutively induce proliferation of local kidney T cells. The polyclonal nature of the TCRβ repertoires of kidney T cell subsets indicates a generalized role for RTEC to keep kidney T cells in steadily proliferating state under normal physiologic conditions. The results could have important conceptual implications for understanding the roles of epithelial cells in regulating local T cell homeostasis.

Uncovering this novel function of RTEC is a fruition of our continued and long-term interest in understanding mechanisms regulating homeostasis of kidney T cells. This interest was fueled by our original observations that DN T cells comprise a large percentage of kidney T cells and highly responsive to AKI.¹ Not only that, but kidney T cells are vigorously dividing in the steady state. Our subsequent analyses show that kidney T cells contain two subsets, a PD1+ subset and a NK1.1+ subset.⁵ The NK1.1+ subset homeostasis is dependent on unidentified non-classical MHC class I molecule(s) as they are largely absent from thymi and kidneys of β2-m deficient, but not mice lacking classical MHC class I or class II molecules. On the other hand, the PD1+ subset is not dependent on any known MHC molecules as they are present in mice lacking classical MHC molecules and β2-m-dependent non-classical MHC molecules. In addition, PD1+ DN T cells are highly responsive to external stimuli and interaction with autologous CD8 T cells that serve as an IL-2 source that fuels proliferation of kidney T cells.⁵ Our present study extends our previous findings to show that kidney CD4 and CD8 T cells are highly similar to kidney DN T cells in terms of steady state proliferation. Our in vitro analysis shows that the steady state proliferation of kidney T cells is an organ-specific phenomenon that is recapitulated using an in vitro coculture system. This notion is accentuated by identifying of RTEC as drivers of this phenomenon.

The stimulatory function of RTEC is robust and involves redundant mechanisms as our results implicate CD155, vitronectin and αVβ3 as well as soluble factors in the process. The stimulatory function of RTEC is clearly MHC-independent as indicated by the ability of in vitro propagated RTEC to induce proliferation of sorted kidney T cell subsets. However, most likely APCs that present antigens in the context of MHC class I or II molecules will be playing a role in activating kidney T cells upon infections. Thus, it will be interesting to dissect relative roles of APCs and RTECs in regulating activation and homeostasis of kidney T cells. Whereas our results are novel in describing the roles of these molecules in the contexts of RTEC and kidney T cells, Singer and colleagues had implicated CD155 and several other native self-proteins, including CD48 and CD102 in mediating the ability of thymic epithelium to activate mature DN T cells ¹¹. A common theme between our studies and findings of Singer and colleagues is the involvement of DN T cells and epithelium and overlapping set of native self-proteins. Intriguing, however, is the ability of RTEC to induce proliferation of kidney CD4 and CD8 T cells, but not peripheral CD4 or CD8 T cells.

MHC restriction is a central tenet of the adaptive immune system that is imprinted on thymocytes through positive selection via the TCR interaction with MHC molecules expressed on thymic epithelium. ²² As a result, mature CD4 T cells become restricted to recognition of cognate antigens in the context of MHCII, whereas mature CD8 T cells become restricted to recognition of cognate antigens in the context of MHC class I molecules. In the periphery, naive T cells circulate through blood and survey lymph nodes and spleens scanning MHC molecules on surface of APCs for cognate antigens. Interactions of TCRs on surface of naive T cells with cognate antigen-MHC peptide complexes on surface of professional APCs provides what is referred to as signal 1. A second obligatory costimulatory signal (signal 2) provided by the interaction of the CD28 molecule on the T cell surface with its CD80 and CD86 ligands on APC is required for optimal T cells. ³ The two-signal system provides a fail/safe mechanism that guards against incidental activation of naive T cell activation and limits immune responses to those initiated in response to bona fides derived from invading pathogens. Once legitimately activated, naive T cells proliferate and differentiate into effector and memory T cells that are often products of well-vetted T cell activation processes. The majority of effector T cells die by apoptosis after clearance of antigens, while memory T cells persist to protect against future infections.²³ Given the stringency placed on primary T cell activation and need for rapid secondary immune responses, antigen activation requirements of memory T cells are less stringent than those placed on naive T cells. These include mechanisms that do not require signal 2 and MHC-independent mechanisms are implicated in maintaining homeostasis of tissue-resident T cells in barrier tissues such as the skin and gut epithelium.^24,25

We speculate that RTEC may be endowed by an unrestricted ability to stimulate antigen-experienced T cells upon encounter as indicated by their ability to activate peripheral DN T cells and small percentages of cocultured peripheral CD4 and CD8 T cells ex vivo. Nevertheless, the stimulatory capacity of RTEC will be valid and applicable only to peripheral T cells that infiltrate the kidney following rigorous controlled activation by APCs and differentiation into effector T_EM or T_RM cells that are programmed and ready to respond to specific exogenous antigens upon exposure. RTEC by being able to stimulate tissue infiltrates and resident in non-cognate manners ensure maintenance of homeostasis of invaluable mixtures of T_EM and T_RM with highly diverse repertoires and likely highly heterogeneous antigen specificities poised to readily to protect against reinfections. In addition, resistance of peripheral T cells to RTEC-mediated stimulation indicate that if such cells wandered in the kidney are not going to be non-specifically stimulated. Thus, RTEC stimulatory function appears to be critical for maintaining homeostasis of activated T cells in the kidney by keeping them proliferating. Thus, perhaps professional APCs and RTEC play complementary roles in initiating and maintaining homeostasis of kidney T cells, respectively.

Limitations of the study

A major strength of our study is the use of in vitro systems to directly demonstrate the stimulatory function of RTEC. The ex vivo systems was also critical for demonstrating that proliferation of unfractionated KMNCs is an active process that is not dependent on systemic signals and recapitulated in vivo steady state proliferation of KMNCs. This TCR-MHC independent system is robust with redundant ligands (CD155, CD48, CD102, αVβ3, vitronectin) making it very difficult to block by targeting one molecule and the renal tubular epithelium as a structural component of the kidney cannot be deleted. In lieu of that, Singer and colleagues using transgenic mice show that MHC-independent αβTCRs require in vivo expression of their cognate ligand for thymic selection. Our ex vivo results demonstrate implicate the mechanism in regionalized maintenance of kidney T cells. Collectively, our results are setting the stage and foundation that we can zoom in on and better understand the molecular mechanisms underlying the interactions between kidney T cells and RTEC and implications for organ homeostasis.

STAR METHODS

RESOURCE AVAILABILITY

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Abdel Rahim A. Hamad (ahamad@jhmi.edu).

Materials availability

This study did not generate new unique reagents.

Data availability

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

EXPERIMENTAL MODEL DETAILS

Mice

C57BL/6J (WT), B6.129P2-Β2m^tm1Unc/J (β2m KO), B6.129S2-H2^dlAb1-Ea/J (MHC II KO) mice were purchased from Jackson laboratory. B6 MHC class I and class II double KO (DKO) mice were development and inbreed at JHU animal facility. All mice were kept and bred under specific pathogen-free conditions at the Animal Facility of the Johns Hopkins University. Age-matched mice between the age of 8 and 10 weeks were used in the study, unless stated otherwise. All experiments were performed using experimental protocols approved by the Animal Care and Use Committee of the Johns Hopkins University.

METHOD DETAILS

Antibodies

Fluorochrome-conjugated monoclonal antibodies (mAbs) were purchased from BD Biosciences, BioLegend or eBioscience for flow cytometry analysis. mAbs to mouse antigens used: CD45-APC-Cy7 (30-F11), αβTCR-Pacific blue/Alexa fluor 488 (H57–597), CD8α-PerCP/FITC (53–6.7), CD4-APC (RM4–5), CD69-BV421/Pacific blue/APC-Cy7 (H1.2F3), CD155-PE (4.24.1), CD51-PE (RMV-7), CD61-FITC (2C9.G3), EpCam-APC (G8.8), CD62L-PE (MEL-14), CD44-BV650 (IM7), Ki67-PE/ Pacific blue (16A8) and Annexin V-PE/FITC. Mouse CD1d tetramers were from the NIH tetramer core facility, USA. Blocking antibodies for mouse antigens were purchased from BioLegend or eBioscience or BioXcell or Leinco Technologies,Inc: MHCII (M5/114), MHCI (M1/42.3.9.8), CD51 (RMV-7), CD61 (2C9.G3), CD155 (4.24.1) and CD226 (480.1). Recombinant proteins rCD155 (50259-M08H) and rVTN (50585-M08H) were purchased from Sino Biological Inc., USA. CellTrace^™ CFSE Cell Proliferation Kit were purchased from Thermo scientific, USA.

Isolation of lymphocytes from kidneys and lymph node

Mononuclear cells from kidneys were isolated as previously described^5,6. Briefly, kidneys were minced and incubated in 5 mg/ml collagenase D (Sigma-Aldrich, St. Louis, MO, USA) solution for 30 minutes at 37 °C. Single cell suspensions of kidney digestions were obtained by mechanical disruption of tissues using 70-μm strainers (BD bioscience) and then filter using 40-μm strainers. Centrifuge the cell suspension at 400×g for 10 min at 4°C to obtain the cell pellet. The cell pellet was then re-suspended, performed a Percoll gradient and the mononuclear cells are isolated. The absolute numbers of viable lymphocytes in each sample was determined using the trypan blue exclusion dye in a haemocytometer under light microscope and absolute numbers of each population determined by multiplying total cell number per organ by percentage of the specific population as determined in FACS dot plots. Lymphocytes from peripheral lymph lode were isolated as previously described ⁵. The isolated lymphocytes were then used for staining or co-culture with RTEC for further analysis.

Flow cytometry analysis and gating strategy

Flow Cytometric analysis was performed using standard methods^5,26. Briefly, cells were stained in FACS buffer (PBS, 2% FBS, 0.1% Sodium azide) and preincubated with anti-CD16/CD32 antibody for 10 mins to minimize nonspecific binding through Fc-receptors. Cells were incubated with appropriate cocktails of fluorochrome-conjugated mAbs for 30 mins at 4°C, washed and resuspended in FACS buffer. Samples were acquired using an Attune^™ NxT Acoustic Focusing Cytometer with 3 lasers line colors (405 nm, 488 nm and 637 nm). Data were analyzed using the FlowJo V10 software (USA, Treestar Software).

CFSE cell proliferation assay

Proliferation of T cells was examined using standard CFSE dye dilution methods as described previously²⁷. Lymphocytes were isolated, stained with CFSE working solution (5μM conc.) for 3 mins at RT, washed and re-suspended in RPMI buffer. Cells were then counted and used for appropriate analysis.

Annexin V apoptosis assay

Apoptosis was assessed using PE-Annexin V apoptosis kit according to manufacturer’s instruction (BD Pharmingen, USA). Cells were stained for surface markers for 30 min at 4°C, washed twice with FACS buffer, re-suspended in annexin V binding buffer with anti-Annexin mAbs for 15 min in dark at room temperature, acquired by flow cytometer, and analyzed by FlowJo.

Isolation and co-culture of RTEC and sorted T lymphocytes

RTEC were isolated from kidney using a modified method as described previously ^9,10. Briefly, kidneys were minced and incubated in 5 mg/ml collagenase D (Sigma-Aldrich, St. Louis, MO, USA) solution for 30 minutes at 37 °C. Single cell suspensions of kidney digestions were obtained by mechanical disruption of tissues using 70-μm strainers (BD bioscience) and then filter using 40-μm strainers. The isolated single cell suspensions were then placed on culture plates, incubated for 2h to facilitate the adherence of contaminating glomeruli. The non-adherent tubules were then collected and seeded onto collagen-coated plates and left unstirred for 48 h at 37°C and 95% air-5% CO₂ in a standard humidified incubator (Jouan, Winchester, VA), after which the culture medium was changed for the first time. The medium was then replaced every 2 days. After 7 days, cell cultures were organized as a confluent monolayer and evaluated for their morphology and purity. T cells (CD4, CD8 and DN T cells) from WT mice were sorted from kidneys (1.2 to1.8 × 10⁵ DN T cells per sort from six mice) or LN using established procedures. Briefly, sorted T cells (CD4 or CD8 or DN T cells) and RTEC (70% confluence) were cultured together or separately in complete tissue culture media (ThermoFisher, Waltham, MA) containing 10% FBS and 100 U/ml penicillin and streptomycin. Cells were harvested, counted, and stained using appropriate cocktails of fluorochrome-conjugated mAbs, acquired and percentage of each subpopulation determined using FlowJo. The absolute cell numbers of T cells were calculated.

Immunoprecipitation detected by flow cytometry (IP-FCM)

The technical details and protocols of multiplex IP-FCM have been previously described ²⁸. Briefly, the concentration of the purchased CML latex beads (0.2μm, Thermo scientific, USA) were determined by diluting in PBS and counted in hemocytometer. Approximately pipette 20 × 10⁶ beads into a 1.5 ml microcentrifuge tube and wash the beads in 1ml MES coupling buffer × 3 times and centrifuged at 20,000g for 3 minutes at 25°C. After the wash, the beads are re-suspended and activated with 20μl of freshly prepared EDAC-MEC for 15 minutes at 25°C. The activated beads are then washed in 0.5 ml PBS × 3 times and centrifuged at 20,000g for 3 minutes at 25°C. The activated beads are then incubated with 20μg of rCD155 for 3 to 4 hours at 25°C in a vibrating shaker. The beads are then washed in 0.5 ml PBS × 3 times and centrifuged at 20,000g for 3 minutes at 25°C. The CD155 coupled beads are then re-suspended in 100μl QBS buffer and can be stored or used immediately for downstream purpose. Multiplex immunoprecipitation was performed by adding couple CD155 beads to each post nuclear lysate. Following overnight incubation at 4°C, beads were washed and stained with fluorochrome-conjugated probe antibodies to the desired protein of interest. The stained proteins are then analyzed by flow cytometry ²⁶.

Mouse cytokine antibody array

Mouse cytokine antibody arrays (ab193659; Abcam, membrane C3: 62 targets and membrane C4: 34 targets) was used to quantify levels of cytokines and chemokines in the culture supernatants collected from LN or RTEC cells that are cultured alone or together and was performed according to the manufacturer’s instructions. Targets analyzed were as follows: Axl, Bfgf, BLC (CXCL13), CD30 Ligand (TNFSF8), CD30 (TNFRSF8), CD40 (TNFRSF5), CRG-2, CTACK (CCL27), CXCL16, CD26 (DPPIV), Dtk, Eotaxin-1 (CCL11), Eotaxin-2 (MPIF-2/CCL24), E-Selectin, Fas Ligand (TNFSF6), Fc gamma RIIB (CD32b), Flt-3 Ligand, Fractalkine (CX3CL1), GCSF, GITR (TNFRSF18), GM-CSF, HGFR, ICAM-1 (CD54) IFN-gamma, IGFBP-2, IGFBP-3, IGFBP-5, IGFBP-6, IGF-1, IGF-2, IL-1 beta (IL-1 F2), IL-10, IL- 12 p40/p70, IL-12 p70, IL-13, IL-15, IL-17A, IL-17 RB, IL-1 alpha (IL-1 F1), IL-2, IL-3, IL-3 R beta, IL-4, IL-5, IL-6, IL-7, IL-9, I-TAC (CXCL11), KC (CXCL1), Leptin, Leptin R, LIX, L-Selectin (CD62L), Lungkine (CXCL15), Lymphotactin (XCL1), MCP-1 (CCL2), MCP-5, M-CSF, MDC (CCL22), MIG (CXCL9), MIP-1 alpha (CCL3), MIP-1 gamma, MIP-2, MIP-3 beta (CCL19), MIP- 3 alpha (CCL20), MMP-2, MMP-3, Osteopontin (SPP1), Osteoprotegerin (TNFRSF11B), Platelet Factor 4 (CXCL4), Pro-MMP-9, P-Selectin, RANTES (CCL5), Resistin, SCF, SDF-1 alpha (CXCL12 alpha), Sonic Hedgehog N-Terminal (Shh-N), TNF RI(TNFRSF1A), TNF RII (TNFRSF1B), TARC (CCL17), I-309 (TCA-3/CCL1), TECK (CCL25), TCK-1 (CXCL7), TIMP-1, TIMP-2, TNF alpha, Thrombopoietin (TPO), TRANCE (TNFSF11), TROY(TNFRSF19), TSLP, VCAM-1 (CD106), VEGF-A, VEGFR1, VEGFR2, VEGFR3, and VEGF-D. Array images were captured and the intensity of spots was calculated by ImageJ. Relative cytokine levels were compared after densitometry analysis. Results are expressed as arbitrary units.

Cell sorting and DNA extraction for ImmunoSEQ analysis

For repertoire analysis, CD4, CD8 and DN T cells from kidney and lymph node were sorted using a FACS Aria II (BD Biosciences, Bedford, MA) cell sorter. Briefly, lymphocytes were isolated from kidney and lymph nodes were stained for CD45, TCRβ, CD4 and CD8 for 30 min on ice, washed thoroughly, and suspended in a pre-sort buffer (BD Biosciences). Propidium iodide (PI) was added immediately prior to sorting to exclude non-viable cells. Sorted cells were collected in RPMI medium supplemented with 50% FBS on ice. Total DNA was directly extracted from sorted cells using QIAmp DNA blood mini-Kit (QIAGEN) according to the manufacturer’s instructions. DNA from sorted cells were used for TCRBV sequencing.

High throughput immunoSEQ and data analysis

Analyses of TRBV clonotypes were performed on genomic DNA from each sorted cell type using the immunoSEQ platform at survey level resolution (Adaptive Biotechnologies). The immunoSEQ assay combines multiplex PCR with high-throughput sequencing and sophisticated bioinformatics pipeline for CDR3 region analysis. Raw ImmunoSeq data from individual samples were processed with ImmunoSeq Analyzer 2.0 software (Adaptive Biotechnologies). Measurement metrics of processed data were exported in the tsv file format and analyzed using the R platform. Clones of uncertain vGene identity or out-of-frame were excluded from downstream analysis. Percentages were visualized with bar plots to make straight comparisons of vGene usages between different cell types. The presence or absence of vGenes in the different cell subsets was determined based on the vGene usages. Unique and shared vGenes clones among different cell subsets were identified and displayed in Venn diagrams using the functions of R Limma package.

Statistical analysis

Data were collected from at least three independent experiments and expressed as mean ± SEM, n; indicates the number of animals per group. Unpaired t tests were used for comparison of repeated measures in the same group. Comparisons between multiple groups were performed by a one-way or two-way ANOVA test followed by the Tukey’s or Sidak’s multiple comparison test where appropriate. Statistical analysis was performed using Prism 6; GraphPad Software and significance was determined as P<0.05.