Early breaches in B cell tolerance are central to type 1 diabetes progression in mouse and man. Conventional BCR transgenic mouse models (VH125.Tg NOD) reveal the power of B cell specificity to drive disease as APCs. However, in conventional fixed IgM models, comprehensive assessment of B cell development is limited. To provide more accurate insight into the developmental and functional fates of anti-insulin B cells, we generated a new NOD model (VH125SD.NOD) in which anti-insulin VDJH125 is targeted to the IgH chain locus to generate a small (1–2%) population of class switch–competent insulin-binding B cells. Tracking of this rare population in a polyclonal repertoire reveals that anti-insulin B cells are preferentially skewed into marginal zone and late transitional subsets known to have increased sensitivity to proinflammatory signals. Additionally, IL-10 production, characteristic of regulatory B cell subsets, is increased. In contrast to conventional models, class switch–competent anti-insulin B cells proliferate normally in response to mitogenic stimuli but remain functionally silent for insulin autoantibody production. Diabetes development is accelerated, which demonstrates the power of anti-insulin B cells to exacerbate disease without differentiation into Ab-forming or plasma cells. Autoreactive T cell responses in VH125SD.NOD mice are not restricted to insulin autoantigens, as evidenced by increased IFN-γ production to a broad array of diabetes-associated epitopes. Together, these results independently validate the pathogenic role of anti-insulin B cells in type 1 diabetes, underscore their diverse developmental fates, and demonstrate the pathologic potential of coupling a critical β cell specificity to predominantly proinflammatory Ag-presenting B cell subsets.

This article is featured in In This Issue, p.823

Type 1 diabetes (T1D) results from the autoimmune destruction of insulin-producing β cells, leading to chronic hyperglycemia and a lifelong need for exogenous insulin. In humans, T1D is predicted by the emergence of autoantibodies to insulin and other islet Ags before the onset of clinical symptoms (1); thus, an early breach in B cell tolerance is central to disease development. Despite the large body of literature emphasizing the predictive power of autoantibodies for progression to clinical T1D (reviewed in Ref. 2), relatively little is known about the autoreactive B cells that produce them. Although autoantibodies alone cannot induce β cell destruction (3), autoreactive B cells are not benign. In addition to Ab production, B cells function as potent, diabetogenic APCs (4, 5). Evidence of their pathogenic potential was revealed when B cell–deficient NOD mice were found to be protected from diabetes (69). In new-onset T1D patients, selective depletion of B cells with an anti-CD20 mAb (rituximab) temporarily improved β cell function (10). As the critical role that B cells play in driving T1D is increasingly recognized, understanding the relationship between the functional state of B cells and breaches in B cell tolerance is essential for identifying early targets for disease prevention and reversal.

Autoreactive B cells compose up to 75% of the immature B cell repertoire (11). In nonautoimmune environments, autoreactive B cells that evade central tolerance and escape into the periphery are maintained in an anergic state, characterized by developmental arrest, impaired proliferation to B cell mitogens, and functional silencing for autoantibody production (12). In autoimmune conditions, this anergic state is often compromised and autoimmunity results from the failure of autoreactive cells to maintain their unresponsiveness (13, 14). The study of rare B cell populations has been revolutionized by the development of Ig transgenic mouse models that permit the tracking of autoreactive B cells that are below the level of detection in physiologic conditions (13). In the anti-dsDNA transgenic mouse model for systemic lupus erythematous, anti-dsDNA B cells are developmentally arrested in BALB/c mice; however, in the autoimmune-prone MRL strain, B cells overcome both developmental arrest and follicular (FO) exclusion to become Ab-producing B cells (14). To assess the functional state of autoreactive B cells in T1D, our group previously developed an insulin-specific, conventional transgenic mouse model (VH125.Tg), in which an insulin-specific H chain was introduced into the germline of NOD mice as an IgMa transgene (Tg). In these mice, a small population of insulin-binding B cells support the development of T1D, whereas mice harboring the same Tg without insulin binding do not (15, 16). When paired with anti-insulin Vk-125, insulin-binding B cells enter mature subsets and upregulate costimulatory molecules but are anergic to B cell mitogens and fail to produce autoantibodies. These data on a conventional IgM-only Tg model suggest the importance of anti-insulin B cells in the development of T1D and further indicate that functionally anergic anti-insulin B cells may support disease (5, 16, 17).

However, the conventional VH125.Tg model is limited by several factors. The Tg copy number and the integration site in the genome are not known and therefore remain variables that have the power to affect disease development in the conventional model. Further, the IgM-only Tg is not competent to class switch, which limits the precise staging of B cell development. Further, in the absence of class switch recombination, it is impossible to assess the production of IgG autoantibodies, which are currently the most accurate predictors of T1D development in genetically susceptible individuals (1820). To address how a fully functional, anti-insulin VH gene impacts disease, we targeted VDJH125 to the IgH chain locus in embryonic stem cells and used them to produce C57BL/6 (B6) and NOD mice harboring an anti-insulin VH (VH125SD) (21, 22).

In non–autoimmune-prone B6 mice, these autoreactive B cells do not generate insulin autoantibodies spontaneously or in response to T-dependent immunization with heterologous insulin, and they have impaired proliferation to anti-CD40 and insulin in vitro. However, tolerance can be reversed following combined BCR/TLR stimulation, which results in Ag-specific germinal center responses and Ab production (21). Whether tolerance is similarly maintained in an autoimmune environment, however, is unknown. Therefore, we assessed the phenotype, development, and functional capacity of these autoreactive B cells in transgenic NOD mice (VH125SD.NOD). We found that site-directed anti-insulin B cells on the NOD background develop into mature B cell subsets that are enriched at the transitional 2 (T2) and marginal zone (MZ) stages and proliferate in response to B cell mitogens. The enriched T2 population in the spleen is also detected at the site of attack in pancreatic lymph nodes (PLNs), providing a reservoir of B cells that are primed to become MZ-like anti-insulin B cells. Their capacity to proliferate following mitogenic stimulation reflects the unique responsiveness of T2 B cells to innate and environmental stimuli (23). Also consistent with this T2 predominance is the increased IL-10 production by anti-insulin B cells in VH125SD.NOD mice (24). However, anti-insulin Ab responses, both spontaneous autoantibody production and T-dependent Ab responses following immunization, remain impaired. Even in this state, VH125SD.NOD mice develop more intense insulitis and accelerated diabetes development compared with their nontransgenic littermates. Although the B cell repertoire is skewed toward insulin, T cell responses in VH125SD.NOD mice maintain diverse specificities for multiple β cell autoepitopes.

Importantly, this model independently validates the pathogenic role of anti-insulin B cells in T1D that was demonstrated in previous, conventional IgM transgenic models and confirms the capacity of anti-insulin B cells to accelerate the rate of T1D development without an overt loss of tolerance and differentiation to produce autoantibodies. These studies also highlight the multiple, developmental fates of anti-insulin B cells in the periphery, including subsets sensitive to proinflammatory signals in addition to subsets with regulatory potential, as evidenced by increased anti-insulin B cell IL-10 production. Thus, potential opportunities for B cell–directed therapy in T1D include limiting innate environmental cues that expand proinflammatory subsets as well as facilitating expansion of regulatory B cells.

NOD mice were originally procured from Taconic Biosciences. Anti-insulin VDJH-125 from our original H and L chain 125Tg (25) mice was cloned to generate a targeting vector, pIVH-SAH-125-VDJH (21). Founder mice were generated by targeting 129Ola embryonic stem cells and then backcrossed to NOD for at least 10 generations. Southern blot was used to confirm the presence of the targeted allele. All mice were housed under specific pathogen-free conditions, and all studies were approved by the Institutional Animal Care and Use Committee of Vanderbilt University Medical Center, fully accredited by the Association for Assessment and Accreditation of Laboratory Animal Care. Both male and female mice were used to characterize B cell development and function, whereas female mice were employed in disease studies.

Single cell suspensions from spleens and PLNs were prepared using HBSS (Invitrogen/Life Technologies) plus 10% FBS (HyClone). Spleen RBCs were lysed using Tris-NH4Cl. Cells were subsequently stained for flow cytometry analysis in 1× PBS containing 0.1% sodium azide, 0.02% EDTA, and 1% FBS using the following reagents and reactive Abs (BD Biosciences or eBioscience): Fixable Viability Stain 700 for cell viability, B220 (6B2), CD19 (1D3), CD21 (7G6), CD23 (B3B4), IgM (15F9), IgD (11-26c), IgMa (DS-1), IL-21 (mhalx21), and IL-10 (JES5-16E3; BioLegend). Insulin-binding BCRs were detected using biotinylated human insulin (Sigma-Aldrich) (26). Insulin-occupied BCRs were detected using biotinylated anti-insulin mAb123 (#HB-123; American Type Culture Collection) (27). The insulin epitope recognized by mAb123 is distinct from the mAb125 insulin epitope used to derive VH125SD.Tg. mAb123 detects anti-insulin VH125SD.NOD BCR occupancy with endogenous insulin, but not insulin bound to the insulin receptor (25, 28). Avidin-fluorochrome conjugates (BD Biosciences) were used to detect biotinylated reagents. Samples were acquired using a BD Biosciences LSR II Flow Cytometer, and FlowJo software (Tree Star) was used for data analysis.

Lymphocytes from the spleen and PLNs of VH125SD.NOD mice were cultured in 96-well plates in the presence or absence of plate-bound anti-CD3ε (145-2C11; BD Biosciences) and soluble anti-CD28 (37.51; BD Biosciences) stimulation. Stimulated wells were coated with anti-CD3ε and washed with PBS prior to adding media and cells. All cells were cultured in cell culture media (RPMI 1640 [Cellgro] containing 10% FBS, 1% l-glutamine, 1% HEPES, 0.2% gentamicin, and 0.1% 2-ME; Life Technologies). For stimulated wells, 1 μg/ml anti-CD28 (clone 37.51; BD Pharmingen) in cell culture media was added. For unstimulated wells, medium alone was added. Cells were cultured at 38°C at 5% CO2 for 60 h. Intracellular cytokine staining for IL-21 (mhalx21; eBioscience) was performed using BD Cytofix/Cytoperm solutions (BD Pharmingen) according to the manufacturer’s instructions after stimulation for 4 h with PMA (50 ng/ml; Sigma-Aldrich), ionomycin (500 ng/ml; Sigma-Aldrich), and monensin (2 μM; eBioscience). Intracellular cytokine staining for IL-10 (JES5-16E3; BioLegend) was performed using BD Cytofix/Cytoperm solutions (BD Pharmingen) after stimulation for 4 h with PMA, ionomycin, LPS, and monensin as previously described (29).

Proliferation of B cells was measured by dye dilution assays. Splenocytes were isolated and resuspended in prewarmed cell culture media (RPMI 1640 [Cellgro] containing 10% FBS, 1% l-glutamine, 1% HEPES, 0.2% gentamicin, and 0.1% 2-ME; Life Technologies). Cells were stained with CellTrace Violet (CTV) dye (Invitrogen) per the manufacturer’s instructions (5 mM stock solution of CTV was prepared by adding 20 μl of DMSO), and 1 μl of CTV was added per 1 × 106 cells. Labeled cells were incubated with LPS, anti-IgM [AffiniPure F(ab′)2 Fragment Goat Anti-Mouse IgM, μ-chain specific; Jackson ImmunoResearch Laboratories], or anti-CD40 (HM40-3; BD Biosciences) with and without IL-4 and incubated at 37°C in 5% CO2 for 3.5 d. After incubation, cells were stained for flow cytometry as described above. Data were analyzed and proliferation index calculations were made with FlowJo software (Tree Star).

Preimmune sera were collected from male, prediabetic NOD or VH125SD.NOD mice between 8 and 12 wk of age. Mice were immunized s.c. at the base of the tail with insulin peptide B:10–23 (10 μg/0.1 ml, Schafer-N) emulsified in CFA. Sera were harvested 2 wk following immunization.

Ninety-six–well Maxisorp Nunc plates (Thermo Scientific) were coated with 1 μg/ml human insulin in borate-buffered saline overnight at 37°C. Sera diluted 1:100 in 1× PBS was added, and plates were incubated overnight at 4°C. Parallel samples were coincubated with 100 μg/ml human insulin to inhibit specific binding. Abs were detected with goat anti-mouse IgG conjugated to alkaline phosphatase (1030-04; Southern Biotech) incubated 1 h at room temperature. Plates were washed with 0.05% TWEEN 20 in 1× PBS after each incubation step. Ten micrograms per milliliter p-nitrophenyl phosphate substrate (Sigma-Aldrich) was added and OD was read at 405 nm using a Microplate Autoreader (Bio-Tek Instruments). Anti-insulin mAb123 (HB-123; American Type Culture Collection) was purified from hybridoma supernatant and used to generate standard curves for quantification of spontaneous anti-insulin IgG production. Specific insulin Ab binding was calculated by subtracting the OD detected in the presence of 10× insulin as an inhibitor.

Insulitis assessment and disease studies were performed using female mice. Pancreata were dissected from nondiabetic mice and fixed with neutral buffered formalin for 4–6 h and then incubated overnight in 70% ethanol at room temperature. Tissues were embedded in paraffin, 5-μm sections were cut, and slides were stained with H&E by the Vanderbilt Translational Pathology Shared Resource Core. Slide images were acquired using a bright field Aperio ScanScope CS (Leica Biosystems). Aperio ImageScope software (Leica Biosystems) was used to blind score images for insulitis according to the following scale: 0 = no insulitis; 1 = <25% lymphocytic infiltration; 2 = 25–50% lymphocytic infiltration; 3 = 50–75% lymphocytic infiltration; 4 = >75% lymphocytic infiltration. All islets in a section were scored (average = 28 per section, minimum = 9, and maximum = 51) and the percentages of islets with each score were averaged across all mice in the cohort to eliminate bias from differences in the number of islets counted per mouse. Blood glucose was measured weekly in mice beginning at 10 wk of age. Mice were considered diabetic after the first of two consecutive readings >200 mg/dl.

IFN-γ–producing cells were assessed via ELISpot for evaluation of proinflammatory T cell responses (3032). Ninety-six–well filter plates (Millipore) were incubated for 5 min in room temperature 70% ethanol. After washing plates with sterile 1× PBS, they were coated with 100 μl of 0.5 μg/ml anti-mouse IFN-γ capture Ab (R4-6A2) diluted in sterile 1× PBS and incubated overnight at 4°C. Blocking solution (RPMI 1640 [Cellgro] containing 10% FBS, 1% l-glutamine, 1% HEPES, 0.2% gentamicin, and 0.1% 2-ME; Life Technologies) was added to wells and incubated for 2 h at room temperature in the dark to block nonspecific membrane binding. Splenocytes were harvested from nontransgenic NOD and VH125SD.NOD female prediabetic mice between 10 and 14 wk of age. HBSS (Invitrogen Life Technologies) plus 10% FBS (HyClone) was used to macerate spleens, and RBCs were lysed using Tris-NH4Cl. Splenocytes were plated at 1 × 106 cells per well in 100 μl plus 100 μl of RPMI 1640 (control) or 100 μl of 10 μM peptide Ag (Schafer-N). Plates were incubated at 37°C in 5% CO2 for 72 h. After incubation, cell suspension was discarded and plates were washed with deionized water, followed by wash buffer (1× PBS/0.05% TWEEN 20). Plates were coated with biotinylated anti-mouse IFN-γ detection Ab (R4-6A2) and incubated at room temperature in the dark for 2 h. HSP–streptavidin Ab was added prior to an additional 1-h incubation at room temperature. Plates were washed with wash buffer followed by 1× PBS. AEC substrate set (BD Biosciences) was used per the manufacturer’s instructions for plate development. Cold deionized water was used to stop the reaction, and dry plates were read on an ImmunoSpot plate reader (Cellular Technology). Data are expressed as the average of technical triplicates of the number of spot forming cells (SFCs) per well.

Statistical analyses were performed using GraphPad Prism 7.0a (GraphPad Software, La Jolla, CA). Throughout, asterisks are used to denote p values by the indicated statistical test: *p < 0.05, **p < 0.01, and ***p < 0.001.

Previous studies used a fixed IgM Tg to investigate anti-insulin B cells in T1D-prone NOD mice (16, 17, 33, 34). To assess the fate and function of more physiologic, class switch–competent, anti-insulin B cells, NOD mice that harbor anti-insulin VDJH-125 site-directed to the IgH chain locus were developed as described in Williams et al. (21) and the 2Materials and Methods. Flow cytometry on splenocytes was used to track the targeted allele (an allotype) and revealed that for VH125SD.NOD mice, allelic exclusion was effective, with >90% of all B cells staining positive for IgMa (Fig. 1B). IgMa pairs with endogenous V κ-chains to generate a small population of anti-insulin B cells (2.1 ± 0.3%, n = 14; Fig. 1A, left panel). The binding specificity is confirmed by competitive inhibition with excess, unlabeled insulin (21). These findings contrast with those in nontransgenic NOD mice (Fig. 1A, right panel), in which insulin binding is rare (<0.1%) and binding is not specifically inhibited by excess insulin (16).

FIGURE 1.

Targeted anti-insulin VDJH (VH125SD.NOD) facilitates detection of anti-insulin B cells in NOD mice. Lymphocytes from spleens and PLNs were isolated from VH125SD.NOD and nontransgenic NOD mice, and B cells (B220+CD19+) were analyzed by flow cytometry. (A) Representative dot plots showing IgMa+ and insulin binding on B cells from VH125SD.NOD mice (left) versus nontransgenic NOD mice (right). Anti-insulin B cells were identified using biotinylated human insulin and are located in the IgMa+Insulin+ gate (upper right quadrants). Plots are representative of ≥14 mice for each genotype. (B) Flow cytometry staining for IgMa (transgenic) and IgMb (nontransgenic) B cells was used to assess allelic exclusion. Representative histograms of splenocytes from VH125SD.NOD mice are gated on B220+ live lymphocytes. (C) Flow cytometry using biotinylated mAb123 to detect insulin-occupied BCRs. B cells (B220+, IgMa+) from VH125SD.NOD mice were stained with biotinylated mAb123 to detect endogenous insulin binding (left panel). B cells were incubated with insulin, washed, and then stained with biotinylated mAb123 to detect fully occupied BCRs (right panel). (D) Lymphocytes from spleen and PLNs were isolated from prediabetic, female, 8- to 12-wk-old mice, and flow cytometry was used to identify IgMa and IgDa expression in non–insulin-binding and insulin-binding B cells. Representative dot plots of IgMa and IgDa distribution are shown. (E) The mean percentage ± SD of IgMa+ lymphocytes that were either IgDa+ or IgDa−, among non–insulin-binding (black), or insulin-binding (white) B cells, n ≥ 3 mice. (F) B cell developmental subsets were identified in non–insulin-binding and insulin-binding B cell populations as follows: T1 (CD21low CD23low IgMhigh), T2 (CD21low CD23high IgMhigh), FO (CD21low CD23high IgMlow), pre-MZ (CD21high CD23high IgMhigh), and MZ (CD21high CD23low IgMhigh). Plots are representative of ≥11 mice. (G) The mean percentage ± SD of each B cell subset is shown for non–insulin-binding (black) and insulin-binding (white) populations. ***p < 0.001, two-tailed t test.

FIGURE 1.

Targeted anti-insulin VDJH (VH125SD.NOD) facilitates detection of anti-insulin B cells in NOD mice. Lymphocytes from spleens and PLNs were isolated from VH125SD.NOD and nontransgenic NOD mice, and B cells (B220+CD19+) were analyzed by flow cytometry. (A) Representative dot plots showing IgMa+ and insulin binding on B cells from VH125SD.NOD mice (left) versus nontransgenic NOD mice (right). Anti-insulin B cells were identified using biotinylated human insulin and are located in the IgMa+Insulin+ gate (upper right quadrants). Plots are representative of ≥14 mice for each genotype. (B) Flow cytometry staining for IgMa (transgenic) and IgMb (nontransgenic) B cells was used to assess allelic exclusion. Representative histograms of splenocytes from VH125SD.NOD mice are gated on B220+ live lymphocytes. (C) Flow cytometry using biotinylated mAb123 to detect insulin-occupied BCRs. B cells (B220+, IgMa+) from VH125SD.NOD mice were stained with biotinylated mAb123 to detect endogenous insulin binding (left panel). B cells were incubated with insulin, washed, and then stained with biotinylated mAb123 to detect fully occupied BCRs (right panel). (D) Lymphocytes from spleen and PLNs were isolated from prediabetic, female, 8- to 12-wk-old mice, and flow cytometry was used to identify IgMa and IgDa expression in non–insulin-binding and insulin-binding B cells. Representative dot plots of IgMa and IgDa distribution are shown. (E) The mean percentage ± SD of IgMa+ lymphocytes that were either IgDa+ or IgDa−, among non–insulin-binding (black), or insulin-binding (white) B cells, n ≥ 3 mice. (F) B cell developmental subsets were identified in non–insulin-binding and insulin-binding B cell populations as follows: T1 (CD21low CD23low IgMhigh), T2 (CD21low CD23high IgMhigh), FO (CD21low CD23high IgMlow), pre-MZ (CD21high CD23high IgMhigh), and MZ (CD21high CD23low IgMhigh). Plots are representative of ≥11 mice. (G) The mean percentage ± SD of each B cell subset is shown for non–insulin-binding (black) and insulin-binding (white) populations. ***p < 0.001, two-tailed t test.

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To determine whether anti-insulin BCRs encounter insulin at physiologic insulin levels in vivo, a biotinylated, anti-insulin mAb (mAb123) was used to detect insulin-occupied BCRs (17, 25, 27, 33). B cells were harvested from VH125SD.NOD mice and stained either immediately with biotinylated mAb123 or after being loaded with human insulin, washed, and then stained with biotinylated mAb123 as a positive control and to assess maximal BCR occupancy (Fig. 1C). Both the percentage of insulin-binding B cells and the mean fluorescence intensity (MFI) of mAb123+ B cells (indicative of occupied BCRs) were lower compared with values using insulin-loaded B cells. These findings are consistent with previous observations that anti-insulin BCRs are occupied by endogenous insulin in VH125SD.B6 mice (21) and NOD mice that express the conventional H and L chain anti-insulin Tg (125Tg) (25) and indicate that under physiologic conditions, in which insulin circulates at low concentrations (1 ng/ml), anti-insulin BCRs in VH125SD.NOD mice encounter endogenous insulin but may not be fully occupied.

Immature B cells that leave the bone marrow complete their development in the periphery to become FO or MZ B cells (35). To investigate peripheral B cell maturation in VH125SD.NOD mice, flow cytometry on lymphocytes was used to identify insulin-binding and non–insulin-binding B cells, and IgM and IgD expression was tracked. Insulin-binding B cells were compared with non–insulin-binding B cells in the spleen and PLNs of VH125SD.NOD mice. The representative flow plots in Fig. 1D reveal both IgMa high and IgMa/Da high B cells in the spleen and primarily IgMa/Da high B cells in the PLNs. The increased percentage of IgMa high/IgDa low B cells in the spleen (28.9 ± 3.5%, n = 3) compared with the PLNs (2.0 ± 0.4%, n = 3) is consistent with previous studies demonstrating increased numbers of MZ splenic B cells in NOD mice (Fig. 1E) (36, 37).

To further interrogate the developmental fate of fully functional, class switch–competent B cells in VH125SD.NOD mice, flow cytometry was used to identify B cell subsets. Transitional 1 (T1) (CD21low CD23low IgMhigh), T2 (CD21low CD23high IgMhigh), FO (CD21low CD23high IgMlow), pre-MZ (CD21high CD23high IgMhigh), and MZ (CD21high CD23low IgMhigh) subsets were detected in both autoreactive insulin-binding and non–insulin-binding B cells (Fig. 1F). Overall, frequencies of insulin-binding and non–insulin-binding B cells were not different in T1 or pre-MZ stages (Fig. 1G). Significantly increased frequencies of T2 and MZ B cells were observed in the insulin-binding B cells compared with non–insulin-binding B cells (p < 0.001 for each subset). Although anti-insulin B cells can enter all peripheral B cell compartments, they are enriched in the T2 and MZ subsets, which are recognized for their heightened responsiveness to innate signals and enhanced capacity for Ag presentation (23, 3840). Conversely, the frequencies of FO B cells were significantly decreased in the insulin-binding population compared with non–insulin-binding B cells (p < 0.001). This is in striking contrast to the developmental fate of site-directed insulin-binding B cells in a nonautoimmune environment, in which anti-insulin B cells in VH125SD.B6 mice predominantly occupy the FO subset with only a small percentage (2.5%) of anti-insulin B cells developing into MZ B cells (21). Together, these results demonstrate that anti-insulin B cells derived from a single Tg in VH125SD.NOD successfully develop into functionally heterogeneous mature B cells, characterized by predominant T2 and MZ compartments.

We next sought to determine whether insulin-binding B cells were characterized by a distinct developmental fate in VH125SD.NOD mice. Because the incidence of diabetes development is known to be higher in female compared with male NOD mice (41), we examined B cell subsets from both genders. When VH125SD.NOD anti-insulin B cells are identified by flow cytometry, distinct populations emerge in the spleen in both male and female mice and can be distinguished by differential insulin binding and IgM expression (Fig. 2A, 2E). Similar distinct populations are identified in the PLNs, the initial site of interaction between islet autoantigens and autoreactive lymphocytes (Fig. 2C, 2G). Given the developmental and functional heterogeneity of anti-insulin B cells, we sought to determine whether distinct populations of anti-insulin B cells tracked with different developmental fates. Anti-insulin B cells identified in VH125SD.NOD spleens and PLNs were divided into two groups based on their intensity of insulin binding, “low MFI” and “high MFI,” and each group was interrogated for developmental phenotypes by flow cytometry (Fig. 2B, 2D, 2F, 2H). In the spleen and PLNs of both male and female mice, the percentage of low MFI anti-insulin B cells in the T2 subset was significantly lower than the percentage of high MFI anti-insulin B cells (p < 0.001 for female spleen cells and male PLN cells, p < 0.01 for male spleen cells, and p < 0.05 for female PLN cells) (Fig. 2I). In the FO subset, there was a significantly increased percentage of low MFI populations compared with high MFI populations in all groups (p < 0.001 for female spleen cells and male PLN cells, p < 0.01 for male spleen cells, and p < 0.05 for female PLN cells). Although the overall percentages of anti-insulin B cells that distributed into the T1 subset were universally <10%, a statistically significant increase in the percentage of T1 cells that were low MFI compared with high MFI was observed in the female and male spleen cells (p < 0.05 and p < 0.001), but not in the PLNs. For all groups, high MFI anti-insulin B cells reside primarily in T2 subsets, whereas low MFI anti-insulin B cells distributed between the T2 and FO subsets. Although not statistically different between high MFI and low MFI populations, small but identifiable populations of MZ cells were noted in the PLNs in both female and male mice (Fig. 2I). The qualitative similarity in B cell subsets of insulin-binding cells in male and female NOD mice are consistent with previously published observations reporting similar islet lymphocyte subset distribution in male and female mice (42). These results show that in VH125SD.NOD mice, anti-insulin B cells have the capacity to enter all mature subsets but are enriched in the MZ subset compared with non–insulin-binding B cells (Fig. 1G). Anti-insulin B cells with higher insulin affinity (high MFI) are enriched in T2 subsets in the spleen and PLNs, yet only lower-affinity (low MFI) anti-insulin B cells developed into FO subsets, indicating that BCR affinity for self-antigen influences anti-insulin B cell developmental fate.

FIGURE 2.

Insulin-binding B cells are enriched in distinct subsets in VH125SD.NOD mice. Cell suspensions from the spleen and PLNs of male and female, prediabetic, 8- to 12-wk-old mice were analyzed by flow cytometry. (AG) Representative dot plots on B cells (B220+CD19+) from spleens and PLNs stained with IgM and biotinylated insulin to identify different populations of insulin-binding B cells (A, C, E, and G) designated as low MFI and high MFI (boxes). (B, D, E, and H) Flow cytometry phenotyping on insulin-binding B cells residing in low MFI (left) and high MFI (right) populations. Upper plots identify T1, MZ, and T2-FO subsets based on CD23 and CD21 staining. Lower plots (arrow) distinguish T2 and FO subsets using IgM and CD21 staining. Percentages reflect the percentage of the parent population. (I) Mean ± SD for percentages of B cell subsets for the spleen and PLNs in male and female mice; n ≥ 3 mice per group. *p < 0.05, **p < 0.01, ***p < 0.001, paired, two-tailed t test.

FIGURE 2.

Insulin-binding B cells are enriched in distinct subsets in VH125SD.NOD mice. Cell suspensions from the spleen and PLNs of male and female, prediabetic, 8- to 12-wk-old mice were analyzed by flow cytometry. (AG) Representative dot plots on B cells (B220+CD19+) from spleens and PLNs stained with IgM and biotinylated insulin to identify different populations of insulin-binding B cells (A, C, E, and G) designated as low MFI and high MFI (boxes). (B, D, E, and H) Flow cytometry phenotyping on insulin-binding B cells residing in low MFI (left) and high MFI (right) populations. Upper plots identify T1, MZ, and T2-FO subsets based on CD23 and CD21 staining. Lower plots (arrow) distinguish T2 and FO subsets using IgM and CD21 staining. Percentages reflect the percentage of the parent population. (I) Mean ± SD for percentages of B cell subsets for the spleen and PLNs in male and female mice; n ≥ 3 mice per group. *p < 0.05, **p < 0.01, ***p < 0.001, paired, two-tailed t test.

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T2 B cells have been shown to correspond to regulatory, IL-10–producing B cell subsets in autoimmune disease models (24). In NOD mice, IL-10+ B cells diminished inflammatory T cell responses to islet-associated peptides ex vivo (43). Given the T2 predominance observed in insulin-binding B cells with high insulin affinity, we interrogated these cells for IL-10 production via intracellular cytokine staining. CD19+IL-10+ cells expressed higher surface levels of MHC class II (MHC-II) and CD1d (44) Ag-presenting molecules compared with their CD19+IL-10 counterparts. Surprisingly, they also exhibited high levels of insulin binding (Fig. 3A, 3B). Interrogating the IL-10 production capacity within different CD1d and insulin-binding subsets revealed a 5-fold increase in CD19+CD1d insulin-binding cells and a >20-fold increase in CD19+CD1d2+ insulin-binding cells relative to the CD19+CD1d non–insulin-binding lymphocyte subset. Thus, whereas anti-insulin B cells are favorably selected into subsets known to sense inflammatory signals (23), these subsets also include B cells with the potential for immune regulation.

FIGURE 3.

Anti-insulin B cells have enhanced IL-10 production and express higher surface levels of Ag presentation molecules. Splenic B cells from VH125SD.NOD mice (n = 5 female, prediabetic mice, 12–16 wk old) were assessed for IL-10 production capacity and surface expression of MHC-II, CD1d, and insulin binding (HINS). (A) CD19+IL-10+ cells display increased surface levels of CD1d, MHC-II, and insulin binding (HINS). (B) Summary of the MFI for CD1d, MHC-II, and insulin binding (HINS) in IL-10 and IL-10+ B cells. (C) Representative gating of CD19+ cell surface expression of CD1d and HINS. Corresponding gates indicate IL-10 competence within each subset. (D) Summary of the percentages of CD19+IL-10+ cells within each subset. **p < 0.01, unpaired, heteroscedastic t test.

FIGURE 3.

Anti-insulin B cells have enhanced IL-10 production and express higher surface levels of Ag presentation molecules. Splenic B cells from VH125SD.NOD mice (n = 5 female, prediabetic mice, 12–16 wk old) were assessed for IL-10 production capacity and surface expression of MHC-II, CD1d, and insulin binding (HINS). (A) CD19+IL-10+ cells display increased surface levels of CD1d, MHC-II, and insulin binding (HINS). (B) Summary of the MFI for CD1d, MHC-II, and insulin binding (HINS) in IL-10 and IL-10+ B cells. (C) Representative gating of CD19+ cell surface expression of CD1d and HINS. Corresponding gates indicate IL-10 competence within each subset. (D) Summary of the percentages of CD19+IL-10+ cells within each subset. **p < 0.01, unpaired, heteroscedastic t test.

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Previous studies used H and L chain anti-insulin BCRs from NOD and B6 mice to show that anti-insulin B cells were anergic (5, 21). In these studies, H and L chain insulin specificity was required to enable adequate cell numbers for assessment of proliferation via thymidine incorporation assay. To directly assess the functional capacity of the small, naturally occurring anti-insulin B cell population in VH125SD.NOD mice, we used flow cytometry and CTV labeling to investigate proliferative responses to B cell mitogens. To ensure that the capacity to proliferate was not affected by the Tg itself, proliferative responses for all B cells from nontransgenic NOD and VH125SD.NOD mice were first compared. Splenic B cells were cultured with B cell mitogens LPS, anti-IgM, or anti-CD40, and proliferation was tracked. The percentage of divided cells was used to quantify and compare proliferative responses. There was no significant difference in proliferative responses for nontransgenic NOD B cells compared with VH125SD.NOD B cells (p = 0.5) (Supplemental Fig. 1A). We then gated on insulin-binding and non–insulin-binding VH125SD.NOD B cells and compared responses to determine whether insulin binding affected proliferation. A dose response was quantified to determine optimal stimulation concentration for each mitogen (Fig. 4A). After culture with mitogen, B cell proliferation was quantified by measuring the percentage of dividing cells and determining the proliferation index. Proliferative responses were observed for both non–insulin-binding and insulin-binding B cells for each stimulus. A representative dot plot and histogram in Fig. 4B reveal that proliferation for anti-insulin B cells was comparable to proliferation for non–insulin-binding B cells. Further, no differences between the percentage of dividing cells or the proliferation index were detected (Fig. 4C). As expected, CD86 expression was upregulated in both non–insulin-binding and insulin-binding B cells following stimulation (Supplemental Fig. 1B). Therefore, targeted anti-insulin B cells in VH125SD.NOD mice are not anergic to optimal stimulation by B cell mitogens, unlike the conventional H and L anti-insulin transgenic B cells in previous models. Further, these responses are consistent with the unique T2 predominance that characterizes VH125SD.NOD anti-insulin B cells, as T2 B cells have been shown to exhibit heightened responsiveness to mitogenic stimulation (23).

FIGURE 4.

Insulin-binding B cells in VH125SD.NOD mice proliferate normally in response to mitogens. B cells purified from VH125SD.NOD mice were cultured with LPS, anti-IgM, or anti-CD40, and proliferation was assessed using CTV labeling, gated on insulin-binding and non–insulin-binding B cells. (A) Dose responses to LPS, anti-IgM, and anti-CD40 were assessed for non–insulin binding and insulin binding using B cells purified from VH125SD.NOD mice. Mean response ± SEM is shown for each dose (n = 5). [(B), top panel] Representative dot plot illustrating proliferation in response to 10 μg/ml LPS for non–insulin-binding B cells (blue) and insulin-binding B cells (red). Box designates proliferating cell populations. Cells were gated on B220+CD19+IgMa+ live lymphocytes. [(B), bottom panel] Representative histogram showing proliferation peaks for non–insulin-binding cells (blue tinted background and line) compared with insulin-binding cells (red line) after stimulation with 10 μg/ml anti-IgM. Cells were gated on B220+CD19+ live lymphocytes. (C) Summary of proliferative responses as assessed by percentage of dividing cells (top panel) and proliferation index calculated using FlowJo version 10.2 software (bottom panel) of B cells purified from VH125SD.NOD mice (n ≥ 3) and cultured for 3.5 d with media alone (no stimulation), LPS, anti-IgM, anti-CD40, or anti-CD40 plus IL-4 as a positive control. Closed and open histograms denote non–insulin-binding and insulin-binding B cell populations, respectively. Error bars denote SEM.

FIGURE 4.

Insulin-binding B cells in VH125SD.NOD mice proliferate normally in response to mitogens. B cells purified from VH125SD.NOD mice were cultured with LPS, anti-IgM, or anti-CD40, and proliferation was assessed using CTV labeling, gated on insulin-binding and non–insulin-binding B cells. (A) Dose responses to LPS, anti-IgM, and anti-CD40 were assessed for non–insulin binding and insulin binding using B cells purified from VH125SD.NOD mice. Mean response ± SEM is shown for each dose (n = 5). [(B), top panel] Representative dot plot illustrating proliferation in response to 10 μg/ml LPS for non–insulin-binding B cells (blue) and insulin-binding B cells (red). Box designates proliferating cell populations. Cells were gated on B220+CD19+IgMa+ live lymphocytes. [(B), bottom panel] Representative histogram showing proliferation peaks for non–insulin-binding cells (blue tinted background and line) compared with insulin-binding cells (red line) after stimulation with 10 μg/ml anti-IgM. Cells were gated on B220+CD19+ live lymphocytes. (C) Summary of proliferative responses as assessed by percentage of dividing cells (top panel) and proliferation index calculated using FlowJo version 10.2 software (bottom panel) of B cells purified from VH125SD.NOD mice (n ≥ 3) and cultured for 3.5 d with media alone (no stimulation), LPS, anti-IgM, anti-CD40, or anti-CD40 plus IL-4 as a positive control. Closed and open histograms denote non–insulin-binding and insulin-binding B cell populations, respectively. Error bars denote SEM.

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To determine whether VH125SD.NOD B cells remained functionally silent for Ab production, insulin Ab was assessed in nontransgenic male NOD and VH125SD.NOD mice before and after immunization with the immunodominant B:9–23 insulin peptide in CFA (45). Anti-insulin serum IgG was measured prior to and 2 wk following immunization. Although nontransgenic NOD mice mounted a significant increase in Ab production 2 wk after immunization (mean OD405 0.158, p < 0.05), VH125SD.NOD mice did not (Fig. 5A). Spontaneous autoantibody production prior to immunization was also reduced in VH125SD.NOD mice compared with nontransgenic controls. Some, albeit reduced, Ab production was observed in a proportion of VH125SD.NOD mice (mean OD405 0.019). When these low levels of Ab were interrogated for allotype and IgG isotype, we found that IgG anti-insulin Abs produced by VH125SD.NOD mice were universally “b” allotype. Thus, small populations of endogenous B cells, and not transgenic anti-insulin B cells, are responsible for low-level Ab production in VH125SD.NOD mice (Fig. 5B). The IgG2a isotype predominated responses by both transgenic and nontransgenic NOD mice, which is consistent with previous observations (46). Together these findings indicate that anti-insulin B cells in VH125SD.NOD mice are functionally silenced for undergoing differentiation into Ab-producing cells in response to T-dependent immunization.

FIGURE 5.

Anti-insulin Ab production is impaired in VH125SD.NOD mice. (A) Serum anti-insulin Ab production was measured by ELISA in nontransgenic NOD (n = 5) and VH125SD.NOD (n = 6) mice before and 2 wk after immunization with insulin B:10–23 in CFA. All mice were male, prediabetic and 8–12 wk of age. *p < 0.05, two-tailed t test. (B) Sera from nontransgenic NOD or VH125SD.NOD mice was harvested before immunization with B:10–23 in CFA (preimmune) or 2 wk following immunization. Insulin-specific Ab binding was measured by ELISA using secondary reagents for IgG1a, IgG1b, IgG2aa, or IgG2ab. Each symbol represents an individual mouse. Black bars represent mean, n ≥ 3. * p < 0.05, Mann–Whitney U test.

FIGURE 5.

Anti-insulin Ab production is impaired in VH125SD.NOD mice. (A) Serum anti-insulin Ab production was measured by ELISA in nontransgenic NOD (n = 5) and VH125SD.NOD (n = 6) mice before and 2 wk after immunization with insulin B:10–23 in CFA. All mice were male, prediabetic and 8–12 wk of age. *p < 0.05, two-tailed t test. (B) Sera from nontransgenic NOD or VH125SD.NOD mice was harvested before immunization with B:10–23 in CFA (preimmune) or 2 wk following immunization. Insulin-specific Ab binding was measured by ELISA using secondary reagents for IgG1a, IgG1b, IgG2aa, or IgG2ab. Each symbol represents an individual mouse. Black bars represent mean, n ≥ 3. * p < 0.05, Mann–Whitney U test.

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Previous studies show that a conventional IgM anti-insulin VH Tg supported T1D development in NOD mice and suggested a role for anti-insulin B cells in T1D (16). To determine how the same anti-insulin VH expressed from its physiologic locus impacts diabetes development, cohorts of female VH125SD.NOD mice and their nontransgenic NOD age-matched controls were assessed for insulitis, hyperglycemia, and spontaneous insulin autoantibody production (n ≥ 5 mice per group). Insulitis was assessed histologically and was quantified based on the percentage of islet infiltration as described in the 2Materials and Methods. In VH125SD.NOD mice, greater percentages of islets were infiltrated throughout disease progression (assessed at 8–12, 13–16, and 17–20 wk) compared with nontransgenic NOD age-matched controls (Fig. 6A). Further, insulitis scores, which quantified the extent of islet infiltration, were consistently higher in VH125SD.NOD mice compared with nontransgenic NOD mice and were significantly higher in the 13- to 16-wk cohort (p < 0.01) (Fig. 5B). To determine whether spontaneous autoantibody production could be detected over time, anti-insulin serum IgG was measured for each cohort. In nontransgenic NOD mice, spontaneous Ab production was observed as early as 8 wk and increased between 13 and 20 wk (Fig. 6C, black diamonds). In VH125SD.NOD mice, no spontaneous Ab production was detected prior to 17 wk. After 17 wk, anti-insulin IgG was identified in some mice, but its production was overall blunted compared with nontransgenic NOD mice, despite the increased frequency of insulin-binding B cells (Fig. 6C, white diamonds).

FIGURE 6.

Anti-insulin VDJH125 targeted to the IgH locus accelerates insulitis and diabetes development in NOD mice. (A) Summary of insulitis scores in pancreata histology from nontransgenic NOD and VH125SD.NOD mice. Female mice from the indicated age groups were used, n ≥ 5 mice per group. Scoring, described in 2Materials and Methods, ranges from 0 (no insulitis) to 4 (extensive invasion). (B) Average insulitis score per mouse is shown for nontransgenic NOD and VH125SD.NOD mice in the indicated age group. **p < 0.01, two-tailed t test. (C) Spontaneous production of IgG autoantibodies to insulin in sera by ELISA from nontransgenic NOD (closed diamonds) or VH125SD.NOD mice (open diamonds) (n = 18 per genotype, prediabetic, 8–20 wk of age). *p < 0.05, **p < 0.01, two-tailed t test. (D) Diabetes incidence curve in cohorts of female VH125SD.NOD mice (n = 13, solid line) compared with their nontransgenic littermates (n = 13, dashed line). Mice were considered diabetic after the first of two consecutive blood glucoses were >200 mg/dl. ***p < 0.001 as calculated by a log-rank test. (E) Table comparing mean age of diabetes onset and number of weeks at which diabetes incidence was >50% (I-50%) in different cohorts of conventional (VH125Tg.NOD) and site-directed (VH125SD.NOD mice) and their littermate controls. Differences (Δ) in weeks between transgenic and control NOD mice are shown for each cohort.

FIGURE 6.

Anti-insulin VDJH125 targeted to the IgH locus accelerates insulitis and diabetes development in NOD mice. (A) Summary of insulitis scores in pancreata histology from nontransgenic NOD and VH125SD.NOD mice. Female mice from the indicated age groups were used, n ≥ 5 mice per group. Scoring, described in 2Materials and Methods, ranges from 0 (no insulitis) to 4 (extensive invasion). (B) Average insulitis score per mouse is shown for nontransgenic NOD and VH125SD.NOD mice in the indicated age group. **p < 0.01, two-tailed t test. (C) Spontaneous production of IgG autoantibodies to insulin in sera by ELISA from nontransgenic NOD (closed diamonds) or VH125SD.NOD mice (open diamonds) (n = 18 per genotype, prediabetic, 8–20 wk of age). *p < 0.05, **p < 0.01, two-tailed t test. (D) Diabetes incidence curve in cohorts of female VH125SD.NOD mice (n = 13, solid line) compared with their nontransgenic littermates (n = 13, dashed line). Mice were considered diabetic after the first of two consecutive blood glucoses were >200 mg/dl. ***p < 0.001 as calculated by a log-rank test. (E) Table comparing mean age of diabetes onset and number of weeks at which diabetes incidence was >50% (I-50%) in different cohorts of conventional (VH125Tg.NOD) and site-directed (VH125SD.NOD mice) and their littermate controls. Differences (Δ) in weeks between transgenic and control NOD mice are shown for each cohort.

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Diabetes development was assessed in cohorts of female VH125SD.NOD mice and their nontransgenic littermates (n = 13 for each group) through weekly monitoring for hyperglycemia. Compared with nontransgenic littermates, VH125SD.NOD mice develop diabetes at an accelerated rate. Average age of disease onset did not differ between groups (12 wk). However, by 17 wk, over 50% of VH125SD.NOD mice had developed diabetes, whereas over 50% of their nontransgenic littermates remained disease free until 27 wk. By 33 wk, disease penetrance was 100% for VH125SD.NOD mice, compared with only 54% for nontransgenic littermates (Fig. 6D). These results are consistent with our previously published disease studies in conventional (fixed IgM) VH125Tg.NOD mice compared with nontransgenic (wild-type) NOD littermates (16, 17, 34). The outcomes in these previous cohorts are compared with the current study in Fig. 6E. To compare cohorts of mice studied at different times and from different suppliers, we determined the age at which the incidence of diabetes first exceeded 50% in transgenic NOD mice and littermate controls. In all cohorts, disease is shown to be accelerated by 9–10 wk in mice that harbor anti-insulin Tgs, either conventional or targeted. In contrast, when we determined the age of diabetes onset in each cohort, the absolute difference in the mean age of onset for all disease studies ranged from 0 to 2 wk. Thus, onset of diabetes is not increased in mice harboring anti-insulin VH Tgs; however, disease progression is markedly accelerated when an anti-insulin Tg is present (Fig. 6E). Together, these data further support the observation that B cell specificity has the power to alter disease progression and that increased frequencies of insulin-specific B cells will accelerate disease development, despite functional silencing of autoantibody production.

Given the imperative role that B cells play as APCs in diabetes development (5, 47), we sought to determine whether the disease acceleration observed in VH125SD.NOD mice was the result of skewing the T cell repertoire toward anti-insulin pathological responses. IFN-γ production was assessed for a broad array of autoepitopes, including insulin, proinsulin (PI), and noninsulin epitopes recognized as autoantigens in T1D, including mouse PI-1 (PI 15–23; SPGDLQTLALEVARQKRG), mouse PI-2 (PI 19–31; LELGGGPGAGDLQTLALEVA), mouse glutamic acid decarboxylase (GAD) 524–543 (GADp35; SRLSKVAPVIKARMMEYGTT), mouse GAD 217–236 (GADp15; EYVTLKKMREIIGWPGGSGD) (32), a chromogranin A (ChgA)–derived epitope ChgA 342–355 (WE14; WSKMDQLAKELTAE) (35), and a recently identified fusion peptide (HIP; LQTLAL-WSRMD) (48). We used an anti–MHC-II Ab to confirm that the majority of IFN-γ production observed was the result of CD4 T cell–B cell interaction upon Ag presentation. In the presence of anti–MHC-II Ab, the percentage of IFN-γ–producing cells was reduced by 91.0 ± 3.1% and 78.2 ± 4.7% in nontransgenic NOD and VH125SD.NOD mice, respectively (data not shown). Responses were not restricted to insulin; rather, they included multiple noninsulin epitopes. A clear trend toward increased responses to insulin epitopes as well as multiple noninsulin epitopes was observed in VH125SD.NOD mice (Fig. 7A). Given the heterogeneous nature of diabetes progression in mice and man, the variability of inflammatory responses was anticipated. To determine whether similar trends toward increased IFN-γ responses persisted when variability was minimized, we cultured splenocytes from age-matched VH125SD.NOD and their nontransgenic NOD littermates in the presence or absence of insulin and the immunodominant B chain epitope (B:10–23, HLVEALYLVCGERG), and IFN-γ production was assessed. In VH125SD.NOD mice, there was a trend toward increased IFN-γ production at baseline (in the absence of Ag) and after culture with insulin and B:10–23, compared with nontransgenic NOD littermates, and a statistically significant increase of IFN-γ production in response to insulin compared with no stimulation in VH125SD.NOD mice (p < 0.05) was revealed in VH125SD.NOD splenocytes, specifically (Fig. 7B). An increased frequency of B cells favoring insulin binding in VH125SD.NOD mice supports a breach in tolerance to multiple β cell autoantigens and is consistent with studies suggesting that insulin is an important early and/or primary target in T1D (49).

FIGURE 7.

T cell responses to a broad array of autoepitopes are increased in VH125SD.NOD mice. (A) Splenocytes from female, prediabetic nontransgenic NOD (closed diamonds) or VH125SD.NOD mice (open diamonds) (n ≥ 3 for each Ag) were cultured with the indicated insulin Ags (insulin and the immunodominant B chain peptide B:10–23), PI peptides (PI: 15–23, mouse PI-1; PI: 19–23, mouse PI-2), or peptide epitopes from islet-associated autoantigens (HIP, fusion peptide; mouse GAD 217–236, GADp15, mouse GAD 524–534, GADp35; ChgA 342–355, WE14) for 72 h, and IFN-γ SFCs were quantified. Each point represents the mean number of IFN-γ SFCs for an individual mouse. A two-way ANOVA of Ag and genotype (VH125SD.NOD and nontransgenic NOD) on IFN-γ production was conducted, and a significant main effect of genotype on IFN-γ production was found, F(1, 95) = 11.75, p < 0.001. (B) Splenocytes from age-matched female, prediabetic, nontransgenic NOD and their VH125SD.NOD littermates (n = 3 for each genotype) were cultured in the presence or absence of insulin or B:10–23 peptide for 72 h. Response was assessed by quantifying number of IFN-γ SFCs. A two-way ANOVA of Ag and genotype (VH125SD.NOD and nontransgenic NOD) on IFN-γ production was conducted with Dunnett multiple comparisons test, F(1, 4) = 1.582, p = 0.277. *p < 0.05.

FIGURE 7.

T cell responses to a broad array of autoepitopes are increased in VH125SD.NOD mice. (A) Splenocytes from female, prediabetic nontransgenic NOD (closed diamonds) or VH125SD.NOD mice (open diamonds) (n ≥ 3 for each Ag) were cultured with the indicated insulin Ags (insulin and the immunodominant B chain peptide B:10–23), PI peptides (PI: 15–23, mouse PI-1; PI: 19–23, mouse PI-2), or peptide epitopes from islet-associated autoantigens (HIP, fusion peptide; mouse GAD 217–236, GADp15, mouse GAD 524–534, GADp35; ChgA 342–355, WE14) for 72 h, and IFN-γ SFCs were quantified. Each point represents the mean number of IFN-γ SFCs for an individual mouse. A two-way ANOVA of Ag and genotype (VH125SD.NOD and nontransgenic NOD) on IFN-γ production was conducted, and a significant main effect of genotype on IFN-γ production was found, F(1, 95) = 11.75, p < 0.001. (B) Splenocytes from age-matched female, prediabetic, nontransgenic NOD and their VH125SD.NOD littermates (n = 3 for each genotype) were cultured in the presence or absence of insulin or B:10–23 peptide for 72 h. Response was assessed by quantifying number of IFN-γ SFCs. A two-way ANOVA of Ag and genotype (VH125SD.NOD and nontransgenic NOD) on IFN-γ production was conducted with Dunnett multiple comparisons test, F(1, 4) = 1.582, p = 0.277. *p < 0.05.

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In addition to IFN-γ, IL-21 production was also assessed to more fully interrogate the inflammatory T cell responses in VH125SD.NOD mice, as IL-21 has been shown to be requisite for disease development and correlate with disease severity (50, 51). Because we were unable to assess Ag-specific IL-21 responses, intracellular cytokine staining was used to detect IL-21 production by transgenic and nontransgenic NOD mice in response to anti-CD3 and anti-CD28 stimulation. CD4 T cells in the spleens of VH125SD.NOD mice produced IL-21 in response to mitogenic stimulation (Supplemental Fig. 2A), which was not different from IL-21 production by nontransgenic NOD mice (Supplemental Fig. 2B). IL-21 production in response to mitogenic stimulation was detected in both the spleen and PLNs of VH125SD.NOD and nontransgenic NOD mice. Although there was a statistically significant increase in IL-21 production before and after stimulation in the spleens and PLNs of VH125SD.NOD mice, there was no significant difference between IL-21 MFI in transgenic compared with nontransgenic mice either at baseline or after stimulation (Supplemental Fig. 2C).

In this study, we describe an anti-insulin BCR transgenic NOD mouse model (VH125SD.NOD) in which anti-insulin VDJH125 is targeted to the IgH chain locus and recombines with endogenous V κ-chains to generate functional BCRs. This single copy VH Tg generates a small population (1–2%) of class switch–competent, insulin-binding B cells and accelerates the development of insulitis and diabetes in the NOD mouse. Previous studies in a coadoptive transfer model show that these anti-insulin B cells interact with TCR transgenic T cells that recognize a diabetogenic epitope (22). In this study, we examine the development and function of anti-insulin B cells in the natural, polyclonal repertoire of NOD mice. BCRs in VH125SD.NOD mice provide more accurate insight into the developmental status and functional state of anti-insulin B cells in the context of autoimmune diabetes. Although anti-insulin B cells have multiple fates, we find a majority are preferentially skewed into T2- and MZ-like subsets that have increased sensitivity to proinflammatory and innate signals (23, 52). Consistent with this heightened sensitivity to innate signals, anti-insulin B cells in VH125SD.NOD mice proliferate normally in response to B cell mitogens. This finding in a polyclonal repertoire differs from the anergic state observed in anti-insulin B cells from monoclonal (H and L chain) repertoires (5, 21, 25) and may explain why disease progression in NOD mice that harbor anergic H and L chain anti-insulin BCRs is less aggressive (16, 36). T cell responses in VH125SD.NOD mice are not focused on insulin epitopes, as demonstrated by increased CD4 T cell responses to a broad array of diabetes-associated Ags, including GAD epitopes and a recently identified hybrid insulin peptide (48). Together, these studies suggest that the developmental skewing of anti-insulin B cells into T2- and MZ-like subsets may foster their Ag-presenting functions and connect innate signals with adaptive autoimmunity.

Autoreactive B cell development is influenced by a multitude of factors, including, but not limited to, the quantity of circulating Ag and its interaction with BCRs (53, 54). By using a second anti-insulin mAb to detect endogenous rodent insulin on BCRs in VH125SD.NOD mice, we verify that autoreactive B cell development is not simply the result of clonal ignorance. Rather, our data confirm and extend the concept that, despite its low levels, insulin in circulation is sufficient to engage anti-insulin BCRs and affect anti-insulin B cell fate. Studies on BCR occupancy indicate that not all potential insulin-binding BCRs are engaged, a finding that reflects the dynamic nature of circulating insulin levels required to maintain glucose homeostasis. This observation highlights the importance of physiologic models of tolerance compared with Tg expression of foreign proteins (13, 5557). Previous work by our group shows that different insulin-binding populations are characterized by two predominant L chains (5, 17, 40). In VH125SD.NOD mice, distinct insulin-binding populations can also be visualized. In addition to the populations detected in the conventional VH125Tg, the targeted Tg reveals a population of insulin-binding B cells in which IgM is downregulated, and this hallmark of tolerance (57) is observed in the spleen and at the site of autoimmune attack in PLNs. Therefore, functional diversity arises in anti-insulin B cells that emerge in VH125SD.NOD mice as a consequence of differences in BCR affinity and variable encounters with the hormone in circulation.

Intact class switch recombination in the VH125SD.NOD model permits more precise tracking of anti-insulin B cell developmental fate as characterized by differential IgM and IgD expression. In NOD mice, the MZ subset (IgMhighIgDlow) is recognized to be increased at the expense of FO (IgDhighIgMlow) B cells (39). In VH125SD.NOD mice, anti-insulin B cells track predominantly to the T2 subset (IgMhighIgDhigh), and these cells are observed in both the spleen and draining PLNs. Some anti-insulin B cells also enter mature MZ and FO subsets. In contrast to non–insulin-binding B cells, the frequency of MZ anti-insulin B cells exceeds that of FO anti-insulin B cells in VH125SD.NOD mice. Thus, the fate of anti-insulin B cells in NOD mice differs appreciably from anti-insulin B cells in VH125SD.B6 mice and other murine models of disease in nonautoimmune (B6) backgrounds, such as B cells that express the Ptpn22 autoimmune risk variant (58), which are characterized by a FO subset predominance (21). Therefore, whereas anti-insulin B cells are competent to enter both MZ and FO subsets, the balance of their developmental fate is governed by the genetic environment. MZ-like B cells have been shown to colonize extrasplenic locations in female NOD mice, including PLNs and the pancreas where they are considered to act as potent APCs for diabetogenic T cells (52). We also identify small numbers of MZ-like B cells (CD21highCD23low) in PLNs of VH125SD.NOD mice. As the T2 subset is recognized to be uniquely sensitive to innate environmental signals with the potential to expand into Ag-specific MZ B cells (23), we propose that T2 B cells in VH125SD.NOD mice are poised to become MZ-like B cells at the site of autoimmune attack. Recent elegant studies demonstrate that islet macrophages in NOD mice display an increased inflammatory signature that is associated with early T1D (59). Our findings suggest that the heightened sensitivity of T2 and MZ anti-insulin B cells to these same innate signals further enhance the pathogenic microenvironment in VH125SD.NOD mice.

Additional phenotypic diversity in anti-insulin B cells is observed in our finding of an increase in IL-10–producing anti-insulin B cells compared with non–insulin-binding B cells in the same mice. Thus, despite their overall detrimental influence on T1D, some anti-insulin B cells with regulatory potential remain in the repertoire. Regulatory B cells with T2 and pre-MZ phenotypes have been identified in models of autoimmune disease and have regulatory effects via IL-10 production (24). Interestingly, signals that rely on innate receptors TLR4 and TLR9 are also capable of IL-10 regulatory B cell expansion (60). However, IL-10 production in VH125SD.NOD mice does not appear to exert meaningful disease suppression. A possible explanation for this apparent paradox is that anti-inflammatory properties of IL-10 may be influenced by site of exposure, as demonstrated by the acceleration of diabetes in NOD mice with islet-specific IL-10 expression compared with prevention of diabetes with systemic IL-10 treatment (61). Future studies evaluating the production of IL-10 by anti-insulin B cells in the PLNs and islets in VH125SD.NOD mice are needed to more fully understand the relationship between B cells, IL-10, and disease progression in the NOD mouse.

Using an approach that differs from previous models, assessment anti-insulin B cell function in VH125SD.NOD mice reveals that anti-insulin B cell mitogen responses remain intact in a polyclonal repertoire. In IgM-restricted H and L chain BCR transgenic mouse models, tolerance has been characterized by anergy to stimulation through the BCR (anti-IgM), TLR4 (LPS), and CD40 (anti-CD40) (36). Unexpectedly, VH125SD.NOD anti-insulin B cells, generated with the same VH125Tg used in conventional models, are not anergic to stimulation with B cell mitogens. We used CTV and flow cytometry–based tracking to evaluate rare, insulin-binding populations in a polyclonal repertoire to show that the large majority of insulin-binding B cells undergo cell division in response to a panel of conventional B cell mitogens. These data are consistent with the recognized responsiveness of T2 B cells to stimulation by innate signals, and this may extend to the site of autoimmune attack (23, 38, 59).

Insulin autoantibodies are strong predictors of T1D development in humans and in mice (62). In particular, IgG insulin autoantibodies have been associated with aggressive disease progression. However, prior to the development of VH125SD.NOD mice, IgG autoantibodies for insulin could not be assessed because conventional transgenic mouse models are unable to class switch. Class switch–competent VH125SD.NOD mice develop accelerated diabetes, but insulin autoantibody production is significantly impaired. When low levels of IgG anti-insulin Abs are detected following immunization, they originate from endogenous (b allotype) rather than transgenic B cells. Thus, anti-insulin B cells harboring VDJH125 are functionally silenced for autoantibody production in the polyclonal repertoire of VH125SD.NOD mice. However, in a coadoptive transfer model, anti-insulin TCR transgenic T cells are able to reverse the tolerant state of VH125SD.NOD anti-insulin B cells, resulting in germinal center and Ab production (22). Together, these results suggest that Ab production by anti-insulin B cells in VH125SD.NOD mice requires a critical threshold of T cell help, and that functional silencing for Ab production is reversed when T cell help is increased using TCR transgenic T cells.

This threshold may be achieved incrementally. Initially, innate signals may enhance Ag presentation by T2- and MZ-like anti-insulin B cells that capture Ag and present key autoepitopes, such as B:9-23, to rare pathogenic T cells. As pathogenic T cells expand they may interact with and reverse tolerance of silent anti-insulin B cells, or they may encounter naive anti-insulin B cells and drive their differentiation in germinal center reactions. In this way, IgG autoantibodies to insulin provide a barometer for generation of autoreactive T cells and evidence that cognate T cell–B cell interactions capable of driving disease have occurred.

IFN-γ has proved a useful cytokine for identifying correlates of T1D exacerbation in NOD mice (3032). Using this response as a metric of autoreactivity, we show that VH125SD.NOD mice have significantly increased spontaneous IFN-γ production by CD4 T cells and increased production of IFN-γ to a broad array of β cell autoantigens, in addition to insulin. However, the role of IFN-γ in NOD mice is complex and incompletely understood, encompassing potentially protective tolerogenic as well as diabetogenic effects (63). Among T cell subsets, T FO helper (Tfh) cells are the most dependent on B lymphocytes for their development and function (64). Several studies suggest that Tfh cells play an important role in mouse and human T1D (6567), and IL-21, the principal cytokine produced by Tfh cells, is shown to be critical for disease progression in NOD mice (50, 51). Approaches to assess Ag-specific induction of IL-21 are not available, but we do find that both VH125SD.NOD and nontransgenic, wild-type NOD mice produce comparable IL-21 responses following polyclonal stimulation. Although IL-21 production was not different between transgenic and nontransgenic NOD mice, Th1- and IL-21–producing Tfh cells are known to share molecular regulators, including T-bet and Bcl6 (68); therefore, increased differentiation of IFN-γ–producing T cells in VH125SD.NOD mice is expected to provide a reservoir for the generation of IL-21–secreting Tfh cells. Understanding how insulin-specific B cells impact the Tfh cell compartment is an important area for future investigation.

These studies provide several important caveats that are relevant to therapeutic interventions in T1D. Small increases in unfavorable B cell specificities in the repertoire have a large effect on the rate of T1D progression, at least in part by enhancing autoantigen/epitope spread. Thus, removal of limited pernicious specificities from the repertoire may delay or prevent disease without the risks associated with total B cell depletion (10). Targeting of autoantigen-binding V regions by anti-idiotypes (69) or other serologic agents (70) could accomplish this goal. However, current studies tend to focus on specificities identified for circulating autoantibodies; our findings suggest that these specificities may reflect the interactions that occur late in the autoimmune process when the autoreactive T cell population is well expanded. Identifying critical early B cell specificities rather than circulating Abs may uncover more accurate targets. Emerging technologies for capturing and expanding rare B cells are well suited for achieving this goal (71). Critical B cell specificities, such as our anti-insulin VH125SD, reside in B cell subsets that are programmed to respond to innate signals; therefore, modifications to the innate environment could alter their response potential. For example, gut microbiota are recognized to alter T1D outcomes (72, 73), and their innate signals may be expected to modify the responses of T2- and MZ-like B cells. Further, not all anti-insulin B cells are pathogenic. Rare anti-insulin B cells that produce IL-10 are clearly present and could be expanded so that their regulatory potential can be favorably exploited. Studies on the role of B cells in T1D beyond autoantibody production have been limited. Our findings tracking B cells that recognize one key β cell autoantigen, insulin, illustrate the potential importance of B cells in understanding the pathogenesis of T1D and identify new approaches for disease intervention.

This work was supported by National Institutes of Health (NIH) Grant R01 AI051448, National Institute of Child Health and Human Development Grant 5T32HD060554-06A1, Clinical and Translational Science Award UL1TR000445 from the National Center for Advancing Translational Sciences, and funding from the Endocrine Fellows Foundation. This work was supported through the Vanderbilt Translational Pathology Shared Resource (supported by NIH Grants 5U24 and DK059637) and the Vanderbilt Medical Center Flow Cytometry Shared Resource (supported by Vanderbilt Ingram Cancer Center Grant P30 CA68485). Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the NIH.

The online version of this article contains supplemental material.

Abbreviations used in this article:

B6

C57BL/6

ChgA

chromogranin A

CTV

CellTrace Violet

FO

follicular

GAD

glutamic acid decarboxylase

MFI

mean fluorescence intensity

MHC-II

MHC class II

MZ

marginal zone

PI

proinsulin

PLN

pancreatic lymph node

SFC

spot forming cell

T1

transitional 1

T1D

type 1 diabetes

T2

transitional 2

Tfh

T FO helper

Tg

transgene.

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The authors have no financial conflicts of interest.

Supplementary data