T cells play a central role in adaptive immunity by recognizing peptide Ags presented by MHC molecules (pMHC) via their clonotypic TCRs. αβTCRs are heterodimers, consisting of TCRα and TCRβ subunits that are composed of variable (Vα, Vβ) and constant (Cα, Cβ) domains. Whereas the Vα, Vβ, and Cβ domains adopt typical Ig folds in the extracellular space, the Cα domain lacks a top β sheet and instead has two loosely associated top strands (C- and F-strands) on its surface. Previous results suggest that this unique Ig-like fold mediates homotypic TCR interactions and influences signaling in vitro. To better understand why evolution has selected this unique structure, we asked, what is the fitness cost for development and function of mouse CD4+ T cells bearing a mutation in the Cα C-strand? In both TCR retrogenic and transgenic mice we observed increased single-positive thymocytes bearing mutant TCRs compared with those expressing wild-type TCRs. Furthermore, our analysis of mutant TCR transgenic mice revealed an increase in naive CD4+ T cells experiencing strong tonic TCR signals, increased homeostatic survival, and increased recruitment of responders to cognate pMHC class II upon immunization compared with the wild-type. The mutation did not, however, overtly impact CD4+ T cell proliferation or differentiation after immunization. We interpret these data as evidence that the unique Cα domain has evolved to fine-tune TCR signaling, particularly in response to weak interactions with self-pMHC class II.

Important roles are played by αβT cells in immunity by scanning the surface of APCs for peptide Ags presented by class I or class II major MHC molecules (pMHC-I/II) (1). CD8+ T cells are restricted to pMHC-I and, after activation, differentiate to CTLs that kill infected or transformed cells. CD4+ T cells are pMHC-II restricted and differentiate to a variety of Th phenotypes, including Th1, Th2, Th17, or T follicular helper (Tfh) cells, as well as regulatory T cells, which help direct the responses of other immune cells (2, 3). Although it is now apparent that a variety of molecular events contribute to T cell–mediated immunity, the fine details remain incompletely described.

T cell recognition of pMHC-I/II is mediated by five-module receptor complexes. The TCR is the receptor module (Supplemental Fig. 1A). It directly recognizes the composite surface of peptide Ags embedded in MHC-I/II and relays information about the nature of its interactions with pMHC-I/II to the associated CD3 signaling modules (CD3γε, CD3δε, and CD3ζζ) (Supplemental Fig. 1B). The CD4 and CD8 coreceptors bind MHC-II and MHC-I, respectively, interact with the Src kinase, Lck, and assemble with TCR-CD3 around the same pMHC-I/II in a reciprocal and regulated manner to initiate signaling (47). The nature of these interactions and the strength of the signals they generate determine whether a developing thymocyte undergoes positive selection and commits to the CD4+ or CD8+ T cell lineage, or negative selection that induces their death to ensure central tolerance to self-antigens (8). In the periphery, weak tonic signaling to self-pMHC allows naive T cells to maintain homeostasis, whereas strong signals in response to agonist pMHC-I/II drive activation and differentiation to effector phenotypes (3, 9). Parameters including the dwell time of the TCR on pMHC-I/II are determinants of the effector phenotype to which they differentiate (3). In sum, the five-module complexes that recognize and signal in response to pMHC-I/II are central to T cell development and function.

How pMHC-I/II recognition drives T cell fate decisions remains an area of active investigation. Considerable effort has been dedicated to determining the architecture of the TCR–CD3 complex, as well as TCR–CD3–pMHC-I/II–CD8/4 assemblies, to understand how the spatial relationship of the individual modules impact T cell responses. Structure–function analyses and a recent cryogenic electron microscopy structure of the TCR–CD3 complex indicate that CD3γε and CD3δε are clustered on one side of the TCR extracellular domain (Supplemental Fig. 1A, 1B) (1013). Furthermore, contacts between the DE-loop of the TCRα C region (Cα) and CD3δε influence TCR signaling (10). Additional work indicates that CD8 and CD4 are situated near CD3δε and CD3γε after coengagement of pMHC-I/II with the TCR, and that the overall architecture of the five-module assemblies is important for appropriate responses to pMHC-I/II (4, 6, 14). Finally, because the CD3 heterodimers and coreceptors are situated on one side of the TCR when assembled around pMHC-I/II, the Cα surface on the opposite side of the TCR is solvent accessible (Supplemental Fig. 1A, 1B) (4, 6, 1014). Given previous work suggesting that the C- and F-strands, which constitute the Cα surface, influence homotypic TCR interactions and responses to pMHC-II but do not clearly impact TCR interactions with the CD3 modules, we have proposed that there is a functional sidedness to the TCR (10, 11, 13).

The primary and tertiary structure of this exposed Cα surface is distinct from typical Ig domains, suggesting that it plays a unique role in T cell responses (15). Many activating immune receptors consist of one or more Ig domains wherein two β sheets are held together by a hydrophobic core. Indeed, the variable regions of TCRα and TCRβ (Vα and Vβ) are both Ig folds, as is the C region of TCRβ (Cβ); however, the Cα regions of mouse and human TCRs alike consist of an Ig-like fold that is missing its top β sheet and instead has two loosely associated top strands, the C- and F-strands, that form a flexible surface above a hydrophobic core (Supplemental Fig. 1A) (15, 16). The conservation of this unique Cα Ig-like domain in both human and mouse TCRs suggests that their solvent-exposed surfaces have been selected by evolution because they make an important contribution to T cell responses.

In this study, we asked, what is the fitness cost of mutating the unusual Cα surface for T cell development and function in vivo? Our goal was to determine how this region normally contributes to T cell biology. Accordingly, we generated TCR retrogenic and TCR transgenic (Tg) mice expressing either wild-type (WT) TCRs or a previously reported mutant thereof wherein two solvent-exposed residues in the Cα domain C-strand were mutated to acidic residues to alter the chemical nature of the Cα surface by imparting a net negative charge (N151D and K154E) to the C-strand, as described elsewhere (11). We observed an increase in the frequency of CD4 single-positive (SP) thymocytes, relative to CD4 CD8 double-positive (DP) thymocytes, in both the retrogenic and Tg mice. These differences were explained by increased positive selection, as determined using the Tg mice. We also observed increased thymic output in Tg mice expressing the C-stand mutant when compared with those expressing the WT TCR. Furthermore, we found that naive mutant TCR Tg T cells survived longer than their WT counterparts, and a higher frequency of mutant TCR Tg T cells proliferated in response to cognate pMHC-II. Altogether, our results provide evidence for higher tonic signaling in the mutant CD4+ T cells, from which we infer that the WT Cα surface has evolved to confer fitness to its host by regulating TCR signaling in response to weak interactions with pMHC-II.

M12 cell lines used as APCs for proximal signaling experiments that express OVA323–339 peptide tethered to I-Ab (OVA:I-Ab) or E641 tethered to I-Ab (E641:I-Ab) have been previously described (17). OT-IIα cDNAs were amplified by RT-PCR from OT-II Tg mice and cloned into pUC18 using 5′ primers targeting the Vα2 leader sequences and 3′ primers targeting the C-terminal end, including the stop codon, of the TCRα and TCRβ constant regions, as previously described (17, 18). OT-IIβ was similarly amplified by RT-PCR from cDNA. In this study, we used a 5′ primer that targeted the Vβ5 sequence immediately after the leader sequence as well as a 3′ primer targeting the C-terminal end of the Cβ2 region including the stop codon. The PCR product was cloned in-frame with sequence encoding the Vβ3 leader sequence in pUC18. The C4 (N170D and K173E, UniProt convention) mutations were introduced into the Cα domain by shuttling the 2B4 TCR Cα domain from the 2B4 TCR containing these mutations into the OT-II TCR by restriction enzyme cloning. After sequence verification in pUC18, the cDNAs were subcloned into the hCD2 minigene cassette using standard techniques (19).

Phoenix E cells were cultured in DMEM/10% FCS supplemented with l-Glu and penicillin/streptomycin. Cells were transfected using FuGENE 6 with previously reported WT 2B4αTCR constructs or the C4 (N151D and K154E), F4 (F189E and K196A), or DE1 (K171A and D174A) mutants (10). Virus was harvested for 2 d and concentrated using a 100-kDa Amicon Ultra spin concentrator. Concentrated supernatants were used for retroviral transduction.

To generate retrogenic mice we used 2B4β Tg mice crossed to B10.A.Rag2−/− mice as bone marrow donors (10). Mice were treated with 2 mg of 5-fluorouracil i.v., and bone marrow was harvested 5 d later. Hemopoietic stem cells were cultured overnight in IMDM, 5% FCS, penicillin/streptomycin, l-Glu, non-essential amino acid, pyruvate, 50 mM 2-ME containing stem cell factor, Flt3 ligand, and IL-11 cytokines at 10 ng/ml. Cells were spin infected with concentrated 2B4α WT, C4, F4, or DE1-loop mutant retrovirus in cytokine-deficient media with 4 mg/ml Polybrene at 32°C for 1.5 h. Cells were washed and cultured overnight, then injected into sublethally irradiated (450 rad) B10.A Rag2 knockout (KO) recipient mice at 6 wk of age. T cells were checked by tail bleeds at 4 wk posttransfer. Thymus and spleen were analyzed at 8 wk posttransfer on a Coulter flow cytometer. Mice were housed at Stanford University and used with approval of the Stanford University Committee on Animal Welfare. Note that retrogenic mice were made and analyzed in 2004–2005 and collected as .lmd files that cannot be read by current versions of FlowJo. For this reason, we have used percentages from previously analyzed data but not included flow plots. The data are intended to be preliminary and supportive of generating Tg mice.

For the generation of OT-II TCR Tg mice, the hCD2-OT-IIα WT or C4 constructs were coinjected with hCD2-OT-IIβ constructs into C57BL/6 embryos at the University of Arizona’s Genetically Engineered Mouse Model Core facility. Founder mice were crossed to C57BL/6J Rag1KO mice (The Jackson Laboratory [Bar Harbor, ME], strain 002216, B6.129S7-Rag1tm1Mom/J) and then crossed to C57BL/6J Rag1KO CD45.1 congenic mice (a gift of the Nikolich-Zugich laboratory) to generate OT-II WT or C4 C57BL/6J CD45.1 Rag1KO mice. These mice were then backcrossed with C57BL/6J Rag1KO CD45.1 mice to generate hemizygous mice for analysis. C57BL/6J mice (strain 000664), used as recipients in adoptive transfer experiments, were purchased from The Jackson Laboratory. OT-II TCR Tg mice and recipient mice were maintained under specific pathogen-free conditions in the animal facility at the University of Arizona. Experiments were conducted under guidelines and approval of the Institutional Animal Care and Use Committee of The University of Arizona.

From male mice, brachial, axillary, and inguinal lymph nodes were pooled with spleens and CD4+ T cells were enriched using a CD4 T cell isolation kit (Miltenyi Biotec) and MACS separation columns (Miltenyi Biotec). Then, 1 × 105 Tag-it Violet (BioLegend)–labeled CD4+ T cells were retro-orbitally injected into male C57BL/6J mice recipient mice. Tag-it Violet (5 µM) staining was performed according to the manufacturer’s instructions. One day later, mice were immunized with 20 µg of OVA323–339 peptide (ISQAVHAAHAEINEAGR, purchased at >95% purity from 21st Century Biochemicals, Marlborough, MA) in CFA (Sigma-Aldrich, St. Louis, MO) on the back flank. At 60 h (proliferation analysis) or 6 d (differentiation analysis) postimmunization the draining lymph nodes (brachial, axillary, inguinal) were harvested and CD4 enriched prior to Ab staining and flow cytometry analysis.

T cells labeled with Tag-It Violet and subsequent dilution of fluorescent dye detected by flow cytometry were used to calculate the total number of daughter and undivided cells, the number of responding T cells (number of original T cells that divided due to stimulus), and the proliferative capacity (the average number of daughter cells generated per responder) as described similarly (20).

Enriched CD4+ T cells (5 × 104) from the OT-II strain generated in the Kuhns laboratory from WT mice (WTKL), the OT-II strains generated in the Kuhns laboratory from C4 mice (C4KL), or OT-II TCR Tg mice generated in the Carbone laboratory (WTCL) mice were cocultured with 1 × 105 transduced I-Ab+ M12 cells in triplicate in a 96-well round-bottom plate in RPMI 1640 with 5% FBS (Omega Scientific), penicillin/streptomycin + l-Glu (Cytiva), 10 ng/ml ciprofloxacin (Sigma-Aldrich), and 50 mM 2-ME (Fisher Scientific) in the presence of titrating amounts of OVA323–339 peptide starting at 10 µM OVA and a 1:3 titration. The supernatants were collected and assayed for IL-2 concentration by ELISA after 16 h of coculture at 37°C. Anti-mouse IL-2 (clone JES6-1A12, BioLegend) Ab was used to capture IL-2 from the supernatants, and biotin anti-mouse IL-2 (clone JES6-5H4, BioLegend) Ab was used as the secondary Ab. Streptavidin-HRP (BioLegend) and tetramethylbenzidine substrate (BioLegend) were also used.

Single-cell suspensions were blocked with anti-mouse FcRII mAb clone 2.4G2 hybridoma supernatants (American Type Culture Collection) and then stained for 30 min at 4°C with corresponding Abs. Staining thymocytes or splenocytes included anti-CD4 (RM4-5), CD8α (53-6.7), CCR7/CD197 (4B12), TCR Vα2 (B20.1), TCR Vβ5.1/5.2 (MR9-4), CD69 (H1.2F3), PD-1 (29F.1A12), CD5 (53-7.3), Ly6C (HK1.4), CD8β (YT5156.7.7), CD62L (MEL-14), Qa-2 (695H1-9-9), CD24 (M1/69), CD25 (PC61), CD44 (IM7), CD45.1 (A20), CD45.2 (104), and CD185/CXCR5 (L138D7) (all purchased from BioLegend). Staining for CCR7/CD197 was performed at 37°C 30 min prior to surface staining.

Cells were then stained using LIVE/DEAD Blue (Invitrogen) for 30 min at 4°C. Cells were fixed using 4% paraformaldehyde for 15 min at 4°C. Cells were washed before being stored at 4°C. When applicable, cells were permeabilized the following day using BD Biosciences Perm/Wash buffer for 30 min at 4°C. Cells were washed with Perm/Wash buffer twice before staining with rabbit anti-cleaved caspase-3 (Asp175) (Cell Signaling Technologies) at a 1:200 dilution for 30 min at room temperature and were detected with donkey anti-rabbit BV421 (BioLegend). Flow was performed on a Cytek Aurora (Cytek Biosciences) and analyzed with FlowJo v10 (Becton Dickinson).

Basal phosphorylation of the CD3ζζ module of the TCR–CD3 complex was measured by intracellular staining for p-CD3ζ. Naive WTKL, C4KL, or WTCL inguinal lymph nodes were harvested, immediately processed into single-cell suspensions, and fixed with 4% paraformaldehyde for 15 min at 37°C. The lymphocytes were then blocked with anti-mouse FcRII mAb clone 2.4G2 hybridoma supernatants (American Type Culture Collection) for 30 min on ice. Cells were stained with anti-CD4 (GK1.5, BioLegend) and fixed with 4% paraformaldehyde for 15 min at room temperature. Cells were washed twice with FACS buffer, pelleted at 350 × g for 5 min at room temperature, resuspended in 1 ml of True-Phos perm buffer (BioLegend), and incubated at −20°C for 2 h. They were then stained for 60 min with anti–p-CD3ζ (K25-407.69, BD Biosciences) at 37°C, washed, and analyzed on a LSR II (BD Biosciences) at the Flow Cytometry Shared Resource at The University of Arizona.

Analysis of p-CD3ζ levels after stimulation with OVA:I-Ab+ APCs was performed as per our recent publication (7). In brief, enriched naive CD4+ T cells were labeled with Tag-It Violet (BioLegend) whereas E641:I-Ab+ (null) or OVA:I-Ab+ (cognate) M12 cells, expressing tethered pMHC-II complexes, were labeled with CFSE (Thermo Fisher Scientific) according to the manufacturer’s instructions. M12 cells and naive CD4+ T cells were chilled on ice for 30 min, 5 × 105 cells of each cell type were mixed in 1.5-ml snap-cap tubes, and the cells were pelleted at 2000 rpm for 30 s at 4°C to force interactions. The supernatant was removed and the tubes were transferred to a 37°C water bath for 2 min to enable signaling. Fixation buffer (BioLegend) was then added for 15 min at 37°C. Cells were washed twice with FACS buffer, pelleted at 350 × g for 5 min at room temperature, resuspended in 1 ml of True-Phos perm buffer (BioLegend), and incubated at −20°C for 2 h. Cells were blocked with anti-mouse FcRII mAb clone 2.4G2 hybridoma supernatants (American Type Culture Collection) for 30 min, pelleted, and stained on ice for 60 min with anti–p-CD3ζ (K25-407.69, BD Biosciences). Finally, cells were washed twice with FACS buffer at 1000 × g for 5 min at room temperature and analyzed on a LSR II (BD Biosciences) at the Flow Cytometry Shared Resource at The University of Arizona. Then, 5 × 104 CD4+ T cell/M12 cell couples were collected per sample. Five thousand T cells coupled to APCs were collected per experiment (technical replicates), resulting in the concatenation of 15,000 coupled cells in total from the three independent biological replicates.

Flow cytometry data were analyzed with FlowJo v10 software (Becton Dickinson) by gating on T cell and M12 cell couples, as described previously (7). Histograms of the p-CD3ζ intensity for the gated population were then generated and data expressing the gated populations as numbers of cells within intensity bins were exported from FlowJo into Microsoft Excel where the number of cells for each bin intensity value for OVA:I-Ab–stimulated cells was subtracted from E641:I-Ab–stimulated cells (negative control) on a bin-by-bin basis. This allowed us to enumerate the intensity differences per bin upon stimulation with the agonist pMHC-II over background. Mean intensity and SEM were calculated based on the background subtracted (OVA:I-Ab − E641:I-Ab) data. The data were then transferred to Prism 9 where we performed smoothing analysis with 500 nearest neighbors to smooth the line profile for graphing purposes. Those intensity bins with positive values were considered to contain cells that had responded to the OVA:I-Ab stimuli above background.

Before a T cell can contribute to immunity, its clonotypic TCR must engage self-pMHC well enough to signal positive selection in the thymus, but not so strongly as to signal negative selection. To evaluate the impact of the Cα surface on thymocyte development, we first made retrogenic mice expressing the well-characterized WT 2B4 TCR (I-Ek restricted) or 2B4 mutants bearing the previously described C4 mutation of the C-strand (N151D and K154E) or the F4 mutation of the F-strand (F189E and K196A) as per our prior work (see Supplemental Fig. 1A and 1B for spatial positioning and 1C for WT and mutation sequences) (11). Note that residues are numbered by UniProt convention. We also made mice bearing the DE1 mutation of the DE-loop (K171A and D174A), which mediates interactions with CD3δε on the opposite side of the TCR from the unusual Cα surface because, based on our prior work, we expected a different phenotype than that of the C- and F-strand mutants (10, 11). Our analysis showed that, 8 wk after bone marrow reconstitution, thymocytes expressing the WT and DE1 mutant TCRs were predominantly CD4+CD8+ DPs whereas those bearing the C4 and F4 mutant TCRs were predominantly CD4+ SP (Supplemental Fig. 1C). Curiously, the DE1 mutation did not impact thymocyte development compared with the WT despite mediating interactions with CD3δε that can impact signaling in response to agonist pMHC-II (10, 12). These data suggested that the TCR Cα surface plays a role in thymocyte selection. They did not, however, allow us to evaluate whether positive selection, negative selection, or both were being impacted.

To better study thymocytes and peripheral T cell phenotypes, we made TCR Tg mice expressing either the well-studied WT OT-II TCR (I-Ab restricted) or a variant bearing the C4 mutation (N170D and K173E) (18). We used the OT-II TCR for two reasons: 1) to ask whether the C4 mutation would impact thymocyte development similarly to the C4 mutant 2B4 TCR used in the retrogenic mice, and 2) to facilitate generation of TCR Tg mice, which could be made directly on the C57BL/6 background. The mice were first crossed to homozygosity on the C57BL/6.Rag1KO.CD45.1 background. We then generated hemizygous TCR Tg mice on this background, such that one copy would be intact for any endogenous gene or element that was disrupted by the transgene to mitigate the impact of transgene integration on our analysis. To distinguish our OT-II strains generated in the Kuhns laboratory from commercially available OT-II TCR Tg mice, we will refer to ours as WTKL and C4KL for brevity (Fig. 1A).

FIGURE 1.

The C4 mutation increases the ratio of SP/DP thymocytes. (A) Representative CD8 versus CD4 flow cytometry plots are shown for thymocytes from WTKL (left) and C4KL (right) OT-II TCR Tg mice after lymphocyte gating using side scatter versus forward scatter (FSC), FSC-height versus FSC-area doublet discriminator, and Live/Dead Blue (data not shown). Percentages are inset for each population. (B) The absolute numbers of thymocytes are shown. (C) DP (left) and CD4 SP (right) thymocyte counts are shown. (D) The ratio of CD4 SP counts to CD4+CD8+ DP counts are shown. Bars represent mean values ± SEM. Each dot represents a single mouse at 5–6 wk of age (male, n = 5; female, n = 5). An unpaired two-tailed t test was performed for (B)–(D), and exact p values are shown. C4KL, OT-II Tg C4KL; WTKL, OT-II Tg WTKL.

FIGURE 1.

The C4 mutation increases the ratio of SP/DP thymocytes. (A) Representative CD8 versus CD4 flow cytometry plots are shown for thymocytes from WTKL (left) and C4KL (right) OT-II TCR Tg mice after lymphocyte gating using side scatter versus forward scatter (FSC), FSC-height versus FSC-area doublet discriminator, and Live/Dead Blue (data not shown). Percentages are inset for each population. (B) The absolute numbers of thymocytes are shown. (C) DP (left) and CD4 SP (right) thymocyte counts are shown. (D) The ratio of CD4 SP counts to CD4+CD8+ DP counts are shown. Bars represent mean values ± SEM. Each dot represents a single mouse at 5–6 wk of age (male, n = 5; female, n = 5). An unpaired two-tailed t test was performed for (B)–(D), and exact p values are shown. C4KL, OT-II Tg C4KL; WTKL, OT-II Tg WTKL.

Close modal

First, we asked whether the C4KL TCR Tg mice phenocopied the 2B4 TCR-based retrogenic mice with regard to thymocyte development. The C4KL mutant mice had a higher percentage of SP thymocytes than did the WTKL mice, even though the WTKL mice had higher numbers of thymocytes overall (Fig. 1A, 1B). These differences were largely attributed to a higher number of DP cells in the WTKL mice compared with the C4KL mice, whereas the higher frequency of SP thymocytes in the C4KL mice corresponded to a higher absolute number of SP thymocytes compared with the WTKL mice (Fig. 1C). The net result was that the C4KL mice had a higher SP/DP thymocyte ratio than that for the WTKL mice (Fig. 1D), indicating that these mice did phenocopy the retrogenic mice.

The results introduced above could be explained if the C4 mutant TCR increases the frequency of cells undergoing positive selection relative to the WT TCR. Alternatively, the frequency of thymocytes undergoing positive selection may be equivalent between the mutant and WTKL mice, but the C4KL TCR could cause an increased frequency of thymocytes to undergo negative selection. Finally, the results could be explained by an increase in both positive and negative selection.

To investigate the impact of the C4 mutation on positive selection we used gating strategies based on recent publications (2123). Initially, we gated on CD4+CD5hi thymocytes to analyze both SPs and DPs that had signaled through their TCRs (Fig. 2A). We then gated on TCRhiCCR7+ to restrict our analysis to thymocytes experiencing, or having completed, positive selection. Finally, we used CD69 expression to distinguish thymocytes actively experiencing TCR signaling, and thus presumably testing their TCR for positive selection, from those that were not. When we evaluated the CD4+CD5+CCR7+TCRhiCD69+/− populations for CD4 and CD8 expression, we found that the CD4+CD5+CCR7+TCRhiCD69+ population was downregulating CD8 but had not fully progressed to the CD4 SP population, supporting the idea that these cells were auditioning for positive selection (21, 24). In comparison, the CD4+CD5+CCR7+TCRhiCD69 cells had fully transitioned to a CD4hi SP stage, indicating that they had undergone positive selection (Fig. 2B).

FIGURE 2.

The C4 mutation leads to increased positive selection. (A) Representative gating scheme of OT-II Tg thymocytes (WTKL shown as an example) after lymphocyte gating using side scatter versus forward scatter (FSC), FSC-height versus FSC-area doublet discriminator, and Live/Dead Blue (data not shown). CD4+CD5hi WTKL thymocytes (left) were gated based on TCR and CCR7 expression (center) prior to gating based on CD69 expression (right). (B) CD8 versus CD4 expression is shown for CD4+CD5hiCCR7+TCRhi (Vβ5hi) CD69+ (left) and CD69 (right) subsets. (C) TCR Vβ5 histogram overlays (left), total cell counts (center), and percentage of parental populations (right) are shown for CD4+CD5hiCCR7+TCRhi (Vβ5hi) CD69+ gated WTKL and C4KL thymocytes subsets. (D) TCR Vβ5 histogram overlays (left), total cell counts (center), and percentage of parental populations are shown for CD4+CD5hiCCR7+TCRhi (Vβ5hi) CD69 gated WTKL and C4KL thymocytes subsets. (E) CD5 geometric MFI (gMFI) for CD4+CD5hiCCR7+TCRhi (Vβ5hi) CD69 (left, auditioning for selection) or CD69+ (right, positively selected) gated WTKL and C4KL thymocyte subsets. (F) Representative flow plot for cleaved caspase-3+ versus side scatter area (SSC-A) gating of CD4+CD5hiTCRhi WTKL thymocytes. (G) Total cell counts (center) and percentage of parental populations of CD4+CD5hiTCRhi cleaved caspase-3+ thymocytes are shown. For (C)–(E) and (G), an unpaired two-tailed t test was performed and exact p values are shown. Each dot represents a single mouse at 5–6 wk of age (male, n = 5; female, n = 5), and bars represent mean ± SEM. C4KL, OT-II Tg C4KL; WTKL, OT-II Tg WTKL.

FIGURE 2.

The C4 mutation leads to increased positive selection. (A) Representative gating scheme of OT-II Tg thymocytes (WTKL shown as an example) after lymphocyte gating using side scatter versus forward scatter (FSC), FSC-height versus FSC-area doublet discriminator, and Live/Dead Blue (data not shown). CD4+CD5hi WTKL thymocytes (left) were gated based on TCR and CCR7 expression (center) prior to gating based on CD69 expression (right). (B) CD8 versus CD4 expression is shown for CD4+CD5hiCCR7+TCRhi (Vβ5hi) CD69+ (left) and CD69 (right) subsets. (C) TCR Vβ5 histogram overlays (left), total cell counts (center), and percentage of parental populations (right) are shown for CD4+CD5hiCCR7+TCRhi (Vβ5hi) CD69+ gated WTKL and C4KL thymocytes subsets. (D) TCR Vβ5 histogram overlays (left), total cell counts (center), and percentage of parental populations are shown for CD4+CD5hiCCR7+TCRhi (Vβ5hi) CD69 gated WTKL and C4KL thymocytes subsets. (E) CD5 geometric MFI (gMFI) for CD4+CD5hiCCR7+TCRhi (Vβ5hi) CD69 (left, auditioning for selection) or CD69+ (right, positively selected) gated WTKL and C4KL thymocyte subsets. (F) Representative flow plot for cleaved caspase-3+ versus side scatter area (SSC-A) gating of CD4+CD5hiTCRhi WTKL thymocytes. (G) Total cell counts (center) and percentage of parental populations of CD4+CD5hiTCRhi cleaved caspase-3+ thymocytes are shown. For (C)–(E) and (G), an unpaired two-tailed t test was performed and exact p values are shown. Each dot represents a single mouse at 5–6 wk of age (male, n = 5; female, n = 5), and bars represent mean ± SEM. C4KL, OT-II Tg C4KL; WTKL, OT-II Tg WTKL.

Close modal

Using this gating we found that CD4+CD5+CCR7+TCRhiCD69+ thymocytes that are auditioning for positive selection had overlapping but slightly higher TCR expression in the C4KL mice compared with the WT mice (Fig. 2C). The absolute number of this thymocyte subset was higher in the C4KL mice compared with the WTKL mice; however, as a percentage of the parental CD4+CD5+CCR7+TCRhiCD69+/− population, the C4KL population was lower than the WTKL population. For the CD4+CD5+CCR7+TCRhiCD69 populations that had undergone positive selection, TCR levels were again overlapping but slightly higher in the C4KL mice (Fig. 2D). Both the absolute number and frequency of this positively selected subset was higher in the C4KL mice than in the WTKL mice. Analysis of CD5 expression levels (mean fluorescence intensity [MFI]), as a measure of TCR signal strength in response to the selecting ligands, indicated that the C4KL thymocytes were experiencing higher signaling than the WTKL thymocytes (Fig. 2E) (23). Taken together, these data suggest that a higher frequency of thymocytes undergo positive selection in the C4KL mice compared with the WTKL mice due to higher levels of TCR signaling.

To investigate the impact of the C4 mutation on negative selection we analyzed cleaved caspase-3 activity in CD4+CD5+TCRhi thymocytes (Fig. 2F) (21). We observed reduced numbers of thymocytes undergoing negative selection, which constituted a lower frequency of the CD4+CD5+TCRhi parental population for the C4KL mice compared with the WTKL mice (Fig. 2G). These data indicate that increased negative selection does not contribute to the increased frequency of CD4 SP thymocytes in the C4KL mice.

The enhanced positive selection of thymocytes expressing the C4 mutant TCR described above predicts that there should be increased thymic output, resulting in an increase in recent thymic emigrants (RTEs). To test this prediction we used a CD24hiQa-2lo gating scheme to identify RTEs (Fig. 3A) (25). In this study, we added commercially available OT-II TCR Tg mice generated in the Carbone laboratory (TCR Tg homozygous, Rag2KO) to our analysis, denoted for the purposes of this study as WTCL for brevity (18). Based on the TCR expression hierarchy on mature CD4+ T cells, WTCL > C4KL > WTKL (Fig. 3B), we reasoned that the WTCL strain would help us distinguish between mutation-intrinsic and TCR expression differences for our analysis of peripheral CD4+ T cell phenotypes and function. We did not include the WTCL mice in our thymocyte analysis because we did not think they were appropriate controls, as differences in the transgene constructs, and the timing of transgene expression, could potentially alter thymocyte progression to the DP stages.

FIGURE 3.

The C4 mutation leads to increased recent thymic emigrants and peripheral CD4+ T cells. (A) CD24 versus Qa-2 expression to show gating for CD24hiQa-2lo recent thymic emigrants (RTEs) after gating on side scatter versus forward scatter (FSC), FSC-height versus FSC-area doublet discriminator, Live/Dead Blue, and Vβ5 versus CD4 (data not shown). A representative flow plot for WTKL CD4+ T cells is shown. (B) TCR Vβ5 levels are shown for WTKL, C4KL, and WTCL CD4+ T cells. (C) Frequency of peripheral CD4+ T cells that are RTEs (left) and their total numbers (right). (D) Total splenocyte counts (left) and CD4+ T cell counts in spleen (right) are shown for WTKL, C4KL, and WTCL mice. For (C) and (D), each dot represents a single mouse 5–6 wk of age (male, n = 5; female, n = 5), and bars represent mean ± SEM. A one-way ANOVA with Tukey’s posttest was performed, and exact p values are shown. C4KL, OT-II Tg C4KL; WTCL, OT-II Tg WTCL; WTKL, OT-II Tg WTKL.

FIGURE 3.

The C4 mutation leads to increased recent thymic emigrants and peripheral CD4+ T cells. (A) CD24 versus Qa-2 expression to show gating for CD24hiQa-2lo recent thymic emigrants (RTEs) after gating on side scatter versus forward scatter (FSC), FSC-height versus FSC-area doublet discriminator, Live/Dead Blue, and Vβ5 versus CD4 (data not shown). A representative flow plot for WTKL CD4+ T cells is shown. (B) TCR Vβ5 levels are shown for WTKL, C4KL, and WTCL CD4+ T cells. (C) Frequency of peripheral CD4+ T cells that are RTEs (left) and their total numbers (right). (D) Total splenocyte counts (left) and CD4+ T cell counts in spleen (right) are shown for WTKL, C4KL, and WTCL mice. For (C) and (D), each dot represents a single mouse 5–6 wk of age (male, n = 5; female, n = 5), and bars represent mean ± SEM. A one-way ANOVA with Tukey’s posttest was performed, and exact p values are shown. C4KL, OT-II Tg C4KL; WTCL, OT-II Tg WTCL; WTKL, OT-II Tg WTKL.

Close modal

Our analysis of CD24hiQa-2lo RTEs showed that the C4KL mice had ∼2-fold more RTEs than did either strain of WT mice (Fig. 3C). Interestingly, although we observed an equivalent number of splenocytes between the three mouse strains, the C4KL mice had nearly 5-fold the number of CD4+ T cells as the WTKL and WTCL mice (Fig. 3D). These data are consistent with increased positive selection in the C4KL mice.

The striking increase in mature peripheral CD4+ T cell numbers suggested that, in addition to thymic output, the CD4+ T cells in the C4KL mice may have increased homeostatic survival. Because homeostatic survival is mediated, in part, by weak tonic interactions between the TCR and self-pMHC-II, similarly to positive selection, we reasoned that the unusual Cα surface might have evolved to regulate the outcome of these weak interactions (2628).

To explore this further, we compared CD5 expression levels (MFI) as a measure of the tonic TCR signaling experienced by our CD4+ T cell populations (23). Using this measure alone, we observed no significant difference in CD5 levels between WTKL and C4KL CD4+ T cells, whereas the WTCL cells had significantly lower CD5 levels (Fig. 4A). We also used a CD5 versus Ly6C gating scheme because it was recently reported that this two-parameter analysis allows for detection of a broader range of tonic TCR signaling compared with single-parameter analysis of CD5 or Nur77 alone (29). Specifically, in that study, both CD5hiLy6Clo and Nur77hiLyc6Clo identified the same subset of OT-II TCR Tg CD4+ T cells experiencing the highest tonic signaling. Our analysis showed that the C4KL mice had a higher percentage of CD5hiLy6CloCD4+ T cells compared with the WTKL and WTCL mice, consistent with the idea that the C4 mutation impacts responses to weak TCR–pMHC-II interactions (Fig. 4A).

FIGURE 4.

The C4 mutation increases markers of tonic signaling and homeostatic survival. (A) CD5 geometric MFI (gMFI) for CD4+TCR+ (Vβ5) OT-II T cells (WTKL, C4KL, and WTCL) from the spleen are shown (left). CD5 versus Ly6C expression is shown for gating on CD5hiLy6C CD4+ T cells experiencing high tonic signaling (middle) after gating on side scatter versus forward scatter (FSC), FSC-height versus FSC-area doublet discriminator, Live/Dead Blue, and Vβ5 versus CD4 (data not shown). Representative WTKL CD4+ T cells are shown. The frequency of CD4+ T cells that are CD5hiLy6C are shown (right). (B) Histogram shows phosphorylation of CD3ζ (left) and gMFI (right) for the indicated populations ex vivo or upon stimulation with OVA:I-Ab+ APCs. (C) Quantification of Tag-it Violet–labeled WTKL-, C4KL-, or WTCL-labeled CD4+ T cells 2 wk after transfer into C57BL/6J recipients. (D) Enumeration of CD4+ T cells from spleens of WTKL and C4KL mice at the indicated ages. For (A)–(C), each dot represents an individual mouse and bars represent means ± SEM. One-way ANOVA and a Tukey’s posttest were performed, and exact p values are shown. For (D), multiple unpaired t tests with a false discovery rate with a two-stage step-up method (Benjamini, Krieger, and Yekutieli) were performed, and exact p values are shown. For weeks 5–6, 7–10, 11–14, and 15–20, WTKL (n = 17, 12, 4, and 7, respectively) and C4KL (n = 26, 10, 3, and 9, respectively) are shown.

FIGURE 4.

The C4 mutation increases markers of tonic signaling and homeostatic survival. (A) CD5 geometric MFI (gMFI) for CD4+TCR+ (Vβ5) OT-II T cells (WTKL, C4KL, and WTCL) from the spleen are shown (left). CD5 versus Ly6C expression is shown for gating on CD5hiLy6C CD4+ T cells experiencing high tonic signaling (middle) after gating on side scatter versus forward scatter (FSC), FSC-height versus FSC-area doublet discriminator, Live/Dead Blue, and Vβ5 versus CD4 (data not shown). Representative WTKL CD4+ T cells are shown. The frequency of CD4+ T cells that are CD5hiLy6C are shown (right). (B) Histogram shows phosphorylation of CD3ζ (left) and gMFI (right) for the indicated populations ex vivo or upon stimulation with OVA:I-Ab+ APCs. (C) Quantification of Tag-it Violet–labeled WTKL-, C4KL-, or WTCL-labeled CD4+ T cells 2 wk after transfer into C57BL/6J recipients. (D) Enumeration of CD4+ T cells from spleens of WTKL and C4KL mice at the indicated ages. For (A)–(C), each dot represents an individual mouse and bars represent means ± SEM. One-way ANOVA and a Tukey’s posttest were performed, and exact p values are shown. For (D), multiple unpaired t tests with a false discovery rate with a two-stage step-up method (Benjamini, Krieger, and Yekutieli) were performed, and exact p values are shown. For weeks 5–6, 7–10, 11–14, and 15–20, WTKL (n = 17, 12, 4, and 7, respectively) and C4KL (n = 26, 10, 3, and 9, respectively) are shown.

Close modal

Next, we asked whether we could detect increased basal phosphorylation of the TCR–CD3 complex CD3ζ subunit (p-CD3ζ), as this has also been related to tonic signaling. We did not detect any differences between the strains; however, a prior study reported that tonic signaling through the OT-II TCR was so weak that p-CD3ζ could not be detected, which limits our ability to make strong conclusions about this analysis (Fig. 4B) (30).

Finally, we tested directly whether the C4 mutation leads to increased homeostatic proliferation or survival. Specifically, we transferred Tag-It Violet–labeled WTKL, C4KL, and WTCL TCRs into C57BL/6 mice and, after 2 wk, enumerated the surviving cells and evaluated their Tag-It Violet levels for evidence of dye dilution as a result of homeostatic proliferation. We recovered 2- to 10-fold more C4KL CD4+ T cells than WTKL or WTCL CD4+ T cells but found no evidence of proliferation (Fig. 4C). Taken together, the data in (Fig. 4A and 4C support the idea that the C4 mutation makes CD4+ T cells more sensitive to weak TCR–pMHC-II interactions, resulting in increased homeostatic survival.

Given that both thymic output and homeostatic survival were increased in the C4KL mice, we asked whether homeostasis was completely dysregulated in the C4KL mice or whether their CD4+ T cell populations would plateau over time. Accordingly, we enumerated the total number of CD4+ T cells in the lymph nodes and spleens of the C4KL and WTKL mice at 5–6, 7–10, 11–14, and 15–20 wk of age. We found that the C4KL mice had higher CD4+ T cell numbers at each time point compared with the WTKL mice, and peaked later, but that the numbers ultimately plateaued (Fig. 4D). These data indicate that increased thymic output and homeostatic survival caused by the C4 mutation led to partial dysregulation of peripheral CD4+ T cell homeostasis.

To determine whether the C4 mutation impacts CD4+ T cell responses to agonist pMHC-II, we first asked whether the mutation impacted phosphorylation of CD3ζ (p-CD3ζ) upon T cell coupling to APCs expressing OVA:I-Ab. We observed small differences in p-CD3ζ levels (WTKL < C4KL < WTCL; (Fig. 5A) that we could not confidently attribute to the C4 mutation as they correlated with differences in TCR surface expression (Fig. 3B).

FIGURE 5.

The C4 mutation does not impair CD4+ T cell in vivo proliferation or differentiation. (A) Histogram of p-CD3ζ MFI in OT-II T cells (WTKL, C4KL, and WTCL) is shown after stimulation with OVA:I-Ab+ APCs (left). Means ± SEM of p-CD3ζ intensity from T cells coupled to APCs are shown for the concatenated results from three independent experiments (right). (B) Representative curve for IL-2 production by OT-II T cells (WTKL, C4KL, and WTCL) in response to a titration of OVA peptide presented by I-Ab+ APCs (left). Area under the curve (AUC) analysis for the dose response is shown as a measure of the response magnitude (center). The average response to a low dose (41 nM) of peptide is shown as a measure of sensitivity (right). (C) Left to right, Representative in vivo proliferation of WTKL, C4KL, and WTCL CD4+ T cells in C57BL/6 recipient mice after immunization with OVA peptide in CFA, as measured by Tag-it Violet dye dilution. The number of divided cells, the calculated number of responders that would generate the daughter cell population (see Materials and Methods), the average number of daughter cells per responder (proliferative capacity, see Materials and Methods), and the number of undivided cells are shown. Tag-it Violet cells were identified after forward scatter (FSC) versus side scatter, FSC-height versus FSC-area doublet discriminator, Live/Dead, CD4+CD8, Vα2+Vβ5+, and CD45.1 (only for WTKL and C4KL) or CD45.2 for WTCL. Each dot represents a recipient mouse (n = 9). Bars equal means ± SEM. (D) Representative CD45.1 versus CD45.2 expression on WT CD4+ T cells 6 d after immunization of recipient C57BL/6 mice showing that most cells after FSC versus side scatter, FSC-height versus FSC-area doublet discriminator, Live/Dead, CD4+CD8, Vα2+Vβ5+, and CD44hi gating are derived from the CD45.1+ adoptively transferred population. (E) Representative gating of adoptively transferred WTKL, C4KL, and WTKL CD4+ T cells 6 d after immunization of C57BL/6 recipient mice for Th1 (CXCR5loPD-1lo), Tfh (CXCR5intPD-1int), and GC-Tfh (CXCR5hiPD-1hi) populations after pregating on FSC versus side scatter, FSC-height versus FSC-area doublet discriminator, Live/Dead, CD4+CD8, Vα2+Vβ5+, and CD44hi (left). The percent of adoptively transferred populations differentiated to Th1, Tfh, and GC-Tfh are shown (middle), and the absolute number of adoptively transferred cells enumerated on day 6 are shown (right). For (A)–(E), exact p values generated by one-way ANOVA with a Tukey’s posttest are shown. C4KL, OT-II Tg C4KL; WTCL, OT-II Tg WTCL; WTKL, OT-II Tg WTKL.

FIGURE 5.

The C4 mutation does not impair CD4+ T cell in vivo proliferation or differentiation. (A) Histogram of p-CD3ζ MFI in OT-II T cells (WTKL, C4KL, and WTCL) is shown after stimulation with OVA:I-Ab+ APCs (left). Means ± SEM of p-CD3ζ intensity from T cells coupled to APCs are shown for the concatenated results from three independent experiments (right). (B) Representative curve for IL-2 production by OT-II T cells (WTKL, C4KL, and WTCL) in response to a titration of OVA peptide presented by I-Ab+ APCs (left). Area under the curve (AUC) analysis for the dose response is shown as a measure of the response magnitude (center). The average response to a low dose (41 nM) of peptide is shown as a measure of sensitivity (right). (C) Left to right, Representative in vivo proliferation of WTKL, C4KL, and WTCL CD4+ T cells in C57BL/6 recipient mice after immunization with OVA peptide in CFA, as measured by Tag-it Violet dye dilution. The number of divided cells, the calculated number of responders that would generate the daughter cell population (see Materials and Methods), the average number of daughter cells per responder (proliferative capacity, see Materials and Methods), and the number of undivided cells are shown. Tag-it Violet cells were identified after forward scatter (FSC) versus side scatter, FSC-height versus FSC-area doublet discriminator, Live/Dead, CD4+CD8, Vα2+Vβ5+, and CD45.1 (only for WTKL and C4KL) or CD45.2 for WTCL. Each dot represents a recipient mouse (n = 9). Bars equal means ± SEM. (D) Representative CD45.1 versus CD45.2 expression on WT CD4+ T cells 6 d after immunization of recipient C57BL/6 mice showing that most cells after FSC versus side scatter, FSC-height versus FSC-area doublet discriminator, Live/Dead, CD4+CD8, Vα2+Vβ5+, and CD44hi gating are derived from the CD45.1+ adoptively transferred population. (E) Representative gating of adoptively transferred WTKL, C4KL, and WTKL CD4+ T cells 6 d after immunization of C57BL/6 recipient mice for Th1 (CXCR5loPD-1lo), Tfh (CXCR5intPD-1int), and GC-Tfh (CXCR5hiPD-1hi) populations after pregating on FSC versus side scatter, FSC-height versus FSC-area doublet discriminator, Live/Dead, CD4+CD8, Vα2+Vβ5+, and CD44hi (left). The percent of adoptively transferred populations differentiated to Th1, Tfh, and GC-Tfh are shown (middle), and the absolute number of adoptively transferred cells enumerated on day 6 are shown (right). For (A)–(E), exact p values generated by one-way ANOVA with a Tukey’s posttest are shown. C4KL, OT-II Tg C4KL; WTCL, OT-II Tg WTCL; WTKL, OT-II Tg WTKL.

Close modal

Next, we evaluated IL-2 production by our panel of CD4+ T cells when cultured with APCs in the presence of a titration of OVA peptide. Across the titration range, the WTKL T cells made slightly more IL-2 than did the C4KL and WTCL T cells at the highest peptide concentrations, and slightly lower levels at the lowest peptide concentrations (Fig. 5B). These differences were not sufficient to lead to overall differences in the response magnitude, as quantified by the area under the curve for the overall response to the peptide range. However, at the lowest peptide concentration tested, we found IL-2 production (WTKL < C4KL ≤ WTCL) to generally mirror TCR expression such that we could not confidently attribute differences in sensitivity to the C4 mutation. Taken together, we could not assign a defect in in vitro responses to agonist pMHC-II to the C4 mutation.

To investigate how the C4 mutation impacts CD4+ T cells responses to agonist pMHC-II in vivo, we monitored proliferation in response to immunization with cognate peptide Ag. Specifically, we adoptively transferred Tag-It Violet–labeled WTKL, C4KL, or WTCL CD4+ T cells into C57BL/6J recipients, immunized the recipient mice with OVA in CFA, and quantified proliferation by Tag-It Violet dye dilution at 60 h postimmunization (Fig. 5C). Enumeration of the daughter cells allowed us to back-calculate the number of cells that would have had to respond to generate that number of daughter cells, as well as the average number of daughter cells that result from each responder (20). Our data indicate that the C4 mutation resulted in more CD4+ T cells that responded to the cognate pMHC-II by proliferating upon immunization. It did not, however, appear to impact the average number of daughter cells made by any given responder when compared with the WTKL and WTCL CD4+ T cells. Interestingly, we also observed more undivided cells in the C4KL population at 60 h compared with the WT populations. We think this is likely to reflect the increased survival between the populations, in which case the increased number of responders in the C4KL population might, in part, reflect enhanced survival of the transferred population prior to immunization. Overall, the mutation did not appear to have a major impact on proliferative responses to agonist pMHC-II, which is consistent with the IL-2 data above.

Because TCR signal strength has been shown to influence CD4+ T cell differentiation, we next asked whether the C4 mutation influences CD4+ T cell differentiation on day 6 postimmunization as per prior work (31). To identify the transferred WTKL and C4KL CD4+ T cells, we took advantage of their clonotypic TCR Vα2 and Vβ5 expression as well as the congenic CD45.1 marker. Given that >97% of the Vα2+Vβ5+CD44hiCD4+ T cells in recipient mice received WTKL CD4+ T cells derived from the adoptively transferred population, we also used Vα2+Vβ5+CD44hi gating to identify the WTCL CD4+ T cells because they did not express CD45.1 (Fig. 5D). For all strains, we then used CXCR5 versus PD-1 expression to identify Th1, Tfh, and germinal center–Tfh (GC-Tfh) CD4+ T cells. As previously reported, the WTKL and WTCL OT-II TCRs directed differentiation that heavily favored the Tfh phenotype, and this was also true for CD4+ T cells bearing the C4 TCR (Fig. 5E) (31). Small differences were observed between the frequencies of effector populations, but we could not confidently attribute these differences to the C4 mutation over strain-specific differences such as TCR levels. Finally, it is notable that by day 6 postimmunization, the number of transferred cells was equivalent for the WTKL, C4KL, and WTCL CD4+ T cells, indicating that the differences in proliferation observed at 60 h did not translate into more effector cells at day 6. These data indicate that the C4 mutation did not dramatically influence the responses of monoclonal populations of CD4+ T cells against their cognate ligand.

The tertiary structure of the αβTCR Cα domain, composed of the C- and F-strands, is conserved in mice and humans but deviates from the C-type Ig domains found in Abs or γδTCRs, suggesting that it confers an evolutionary fitness advantage with regard to the function of CD4+ and CD8+ T cells (32). In this study, we evaluated the fitness cost of acquiring mutations in this region for CD4+ T cell development and homeostasis. Based on the phenotype of our mutant mice, we infer that the WT Cα surface of αβTCRs plays a role in regulating CD4+ T cell development and homeostasis in response to self-pMHC-II.

The data presented in this study contribute to our understanding of the features that shape the αβT cell repertoire by ensuring that mature CD4+ T cells are capable of distinguishing self-Ags from foreign peptide Ags presented in MHC-II. They indicate that, for a monoclonal population of thymocytes expressing the MHC-II–restricted OT-II TCR, mutating the C-strand results in enhanced positive selection without impacting negative selection, suggesting that the mutation increases sensitivity to weak TCR–pMHC-II interactions. This conclusion is supported by phenotypic evidence that mature CD4+ T cells expressing the mutant TCR experience higher tonic signaling in response to self-pMHC-II and data showing they have increased homeostatic survival. We therefore infer from the phenotype of our mutant retrogenic and Tg mice that a key function of the unique Cα domain surface is to regulate sensitivity to weak interactions with self-pMHC-II. It is likely that the Cα domain similarly regulates CD8+ T cell development and homeostasis, although confirming this will require future studies. Likewise, elucidating how the Cα domain impacts the composition and size of polyclonal CD4+ and CD8+ T cell repertoires will require analysis with more sophisticated mouse models.

One caveat of note is that we observed distinct expression levels for the WTKL, C4KL, and WTCL Tg TCRs evaluated in this study (WTKL < C4KL < WTCL). We cannot fully rule out that the overlapping but distinct TCR expression between the WTKL and C4KL thymocytes influenced their phenotypes; however, because two distinct pMHC-II–restricted TCRs (i.e., 2B4 and OT-II) bearing the C4 mutation yielded phenotypes with an increased SP/DP ratio when compared with their counterparts in two different mouse model systems (i.e., retrogenic and Tg TCR mice), the simplest interpretation of our data is that the thymocyte phenotype is largely mutation intrinsic. Similarly, given that the C4 TCR expression was intermediate to the WTKL and WTCL expression in naive CD4+ T cells, differences in TCR expression are unlikely to account for the increased homeostatic survival and responder frequency to immunization observed in the periphery for the C4KL T cells, relative to the WTKL and WTCL populations.

Prior work indicated that the unusual Cα surface is available to mediate protein–protein interactions, including homotypic TCR interactions that are impaired by the C-strand mutation of the Cα surface studied in the present study (1012). It is therefore notable that the F-strand is flanked by putative N-linked glycosylation sites in mice and humans whereas the human αβTCR has an additional glycosylation site in the middle of the C-strand (32). These sites might always be glycosylated, which could sterically hinder the proposed protein interactions (33). Yet, for other proteins, varying glycosylation has been reported to regulate the activity of specific function-mediating surfaces. For example, Ab glycosylation in the Fc region is reported to alter their affinity for Fc receptors and thus serve as a mechanism to tune biological activity (34). It is therefore worth considering that differential glycosylation of the Cα surface may allow for regulation of TCR dimerization, or interactions with other proteins, to fine-tune signaling in response to weak TCR interactions with pMHC-II. Although future work is required to explore this idea, the data presented in the present study suggest that such regulation could aid in controlling thymic output and homeostatic survival of clonotypes in the periphery to regulate the size and diversity of the αβT cell repertoire.

In closing, this study contributes to our understanding of CD4+ T cell biology by providing insights into the relationship between a uniquely evolved structural feature of the TCR, the Cα domain, and the ability of CD4+ T cells to distinguish self- from foreign-pMHC-II and respond accordingly. Although early debates about the nature of TCR triggering considered whether TCR–CD3 clustering or conformational changes in the TCR–CD3 complex led to signal initiation, work in recent years has shown that the assembly of TCR–CD3–CD4/8 receptor complexes around pMHC-I/II generates signals in response to single agonist pMHC-I/II and involve conformational changes (1, 3540). The data presented in this study help answer how the unusual Cα region contributes to TCR-directed responses by providing evidence that it has evolved to help the αβTCR mediate the unique function of responding to weak self-pMHC-II by setting a threshold below which TCR–pMHC-II interactions do not mediate positive selection or homeostatic survival.

We thank Mark M. Davis for providing critical feedback and use of the retrogenic mouse data. We thank J. Nikolich-Žugich for providing Rag1KO CD45.1 C57BL/6J mice and Eric Huseby for providing the hCD2 cassette. We also thank Dominik Schenten, Koenraad Van Doorslaer, and members of the Kuhns laboratory for critical feedback on the manuscript. We particularly thank Mark Lee for technical assistance, advice, and thoughtful discussions.

This work was supported by National Institutes of Health/Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases Grant R01 AI101053.

The online version of this article contains supplemental material.

Abbreviations used in this article:

     
  • C4KL

    OT-II strain generated in the Kuhns laboratory from C4 mice

  •  
  • DP

    double-positive

  •  
  • E641:I-Ab

    E641 tethered to I-Ab

  •  
  • GC

    germinal center

  •  
  • hCD2

    human CD2

  •  
  • KO

    knockout

  •  
  • MFI

    mean fluorescence intensity

  •  
  • OVA:I-Ab

    OVA323–339 peptide tethered to I-Ab

  •  
  • pMHC-I

    peptide Ags presented by class I MHC molecules

  •  
  • pMHC-II

    peptide Ags presented by class II MHC molecules

  •  
  • RTE

    recent thymic emigrant

  •  
  • SP

    single-positive

  •  
  • Tfh

    T follicular helper

  •  
  • Tg

    transgenic

  •  
  • WT

    wild-type

  •  
  • WTCL

    OT-II TCR Tg mice generated in the Carbone laboratory

  •  
  • WTKL

    OT-II strain generated in the Kuhns laboratory from WT mice

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M.S.K. has disclosed an outside interest in Module Therapeutics to The University of Arizona. Conflicts of interest resulting from this interest are being managed by The University of Arizona in accordance with their policies. The other authors have no financial conflicts of interest.

Supplementary data