Flot2 deletion enhances antitumor activity of T cells in murine tumor models. To investigate the role of Flot2 in T cell responses, we generated Flot2 global KO mice (i.e., Flot2–/– mice) by flanking the Flot2 coiled-coil domain (14) with loxP sites and then crossing these Flot2fl/fl mice with CMV-Cre mice (29) (Supplemental Figure 1; supplemental material available online with this article; https://doi.org/10.1172/jci.insight.182328DS1). B16F10 melanoma and MC38 colon adenocarcinoma, well-established in vivo models of T cell antitumor immunity (30–33), were first tested. In both the B16F10 and MC38 models, Flot2–/– mice exhibited delayed/reduced tumor growth compared with Flot2+/+ counterparts (Figure 1, A and B). Similar results were noted in mice of both sexes. Furthermore, Flot2–/– mice exhibited an increased frequency of CD4+ and CD8+ tumor-infiltrating lymphocytes (TILs) in the B16F10 melanoma model, specifically including Ki67+ proliferating effector CD4+ and CD8+ cells (Figure 1, C–J). The expression of TOX, a marker of functional exhaustion, was decreased in CD8+ TILs of Flot2–/– mice with MC38 tumors, whereas TIM-3 expression was similar to that in WT controls (Supplemental Figure 2, A–F). Total splenic IFN-γ production to melanoma TRP-2 peptide stimulation was also elevated in B16F10 tumor–bearing Flot2–/– mice compared with their Flot2+/+ counterparts, indicating an enhanced response to tumor antigen (Figure 1K). Taken together, these results indicate an augmented antitumor immune response in Flot2-deficient mice.

Flot2 deficiency potentiates the antitumor activity of both CD4+ and CD8+ T cells in vivo. (A and B) Tumor volume in Flot2+/+ or Flot2–/– mice injected with B16F10 (A) or MC38 (B) (n = 6–7 per group). (C–J) Flow cytometric analysis of tumor-infiltrating lymphocytes (TILs) in B16F10 tumor–bearing Flot2+/+ or Flot2–/– mice. Representative plots (C, E, and H) are shown. TCRβ+ (D), TCRβ+CD4+ (F), and TCRβ+CD8+ (G) populations within 7AAD–CD45+ population, and Ki67+ populations among 7AAD–CD45+TCRβ+CD4+CD44+CD62L– population (I) or 7AAD–CD45+TCRβ+CD8+CD44+CD62L– population (J), are depicted. (K) Splenocytes from B16F10 tumor–bearing Flot2+/+ or Flot2–/– mice were stimulated with 1 μg/mL of TRP-2 melanoma peptide for 24 hours and assayed for antigen-specific reactivity using an IFN-γ ELISPOT assay. Data are representative of 2 independent experiments. Data were analyzed by unpaired t test (D, F, G, and I–K) or 2-way ANOVA followed with Šidák’s multiple-comparison tests (A and B). Data are shown as mean ± SEM; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Next, we sought to examine whether Flot2 deficiency specifically within the T cell compartment is sufficient to confer enhanced antitumor immunity. To explore this, we generated mixed bone marrow chimeras by reconstituting lethally irradiated TCRα-deficient (TCRα–/–) recipient mice with a 1:5 ratio mixture of bone marrow cells from either Flot2+/+ or Flot2–/– donor mice and TCRα–/– mice, thereby generating mice with predominantly WT hematopoietic cells, except for a Flot2-deficient T cell compartment (34). Subsequently, these chimeras were inoculated with B16F10 tumors. Notably, TCRα–/– recipients reconstituted with Flot2–/– bone marrow exhibited a significant reduction in tumor volumes compared with those reconstituted with WT bone marrow (Supplemental Figure 2G). Furthermore, we observed increased proliferation marker Ki67 expression in both CD4+ and CD8+ TILs in the chimeras transferred with Flot2–/– bone marrow, along with an expansion of the CD44+IFN-γ+ population within CD8+ TILs (Supplemental Figure 2, H–J). These findings suggest that Flot2 deficiency specifically within T cells augments anticancer immune responses.

This finding prompted us to generate T cell–specific Flot2-deficient mice through crossbreeding of Flot2fl/fl mice with CD4Cre mice (i.e., Flot2CD4 mice) in order to further explore the T cell–intrinsic role of Flot2 in anticancer immunity. Selective Flot2 deletion in T cells (Supplemental Figure 3, A–C) did not cause overt abnormalities in thymocyte development (Supplemental Figure 3, D–H). In the steady state, peripheral T cells in the lymph nodes of Flot2CD4 mice exhibited similar characteristics to those in Flot2WT mice. There was, however, a marginal decrease in total CD4+ T cell numbers, accompanied by an increase in the percentage of the CD44+CD62L– population, as well as enhanced expression of Nur77, T-bet, and LFA-1α within CD4+ T cells, suggesting a shift from naive to activated status (Supplemental Figure 3, I–N).

As above for Flot2–/– mice, Flot2CD4 mice were evaluated in the B16F10 melanoma and MC38 colon adenocarcinoma models. Consistent with the phenotypes of Flot2–/– mice, Flot2CD4 mice showed reduced growth of both B16F10 and MC38 tumors compared with Flot2WT controls (Figure 2, A and B). Flot2CD4 mice also showed elevated populations of CD4+ and CD8+ TILs, as well as increased Ki67+ proliferating effector CD4+ and CD8+ cells in the B16F10 melanoma model (Figure 2, C–H). Moreover, we observed heightened expression of IFN-γ and TNF-α effector cytokines in CD4+ T cells within the tumor-draining lymph nodes (dLN) of Flot2CD4 mice (Figure 2, I–K). However, no discernible difference was observed in CD8+ T cells within the dLN (Figure 2, L–N). Overall, these data demonstrate that specific Flot2 deficiency in T cells boosts antitumor responses of both CD4+ and CD8+ T cells in murine tumor models.

T cell–specific Flot2 deficiency potentiates the antitumor activity of both CD4+ and CD8+ T cells in vivo. (A and B) Tumor volume in Flot2WT or Flot2CD4 mice injected with B16F10 (A; n = 10 per group) or MC38 (B, n = 9 for Flot2WT and n = 14 for Flot2CD4). (C–H) Flow cytometric analysis of TILs. Representative plots (C and F) are shown. TCRβ+CD4+ (D) and TCRβ+CD8+ (E) populations among 7AAD–CD45.2+ population and Ki67+ populations among 7AAD–CD45.2+TCRβ+CD4+ population (G) or 7AAD–CD45.2+TCRβ+CD8+ population (H) in B16F10-bearing Flot2WT or Flot2CD4 mice are presented. (I–N) Flow cytometric analysis of tumor-draining lymph nodes (dLNs). Representative plots (I and L) are displayed. CD44+IFN-γ+ (J) and CD44+TNF-α+ (K) populations among 7AAD–CD45.2+TCRβ+CD4+ population and CD44+IFN-γ+ (M) and CD44+TNF-α+ (N) among 7AAD–CD45.2+TCRβ+CD8+ population in B16F10-bearing Flot2WT or Flot2CD4 mice are indicated. Data are representative of 2 independent experiments (A–N). Data were analyzed by unpaired t test (D, E, G, H, J, K, M, and N) or 2-way ANOVA followed with Šidák’s multiple-comparison tests (A and B). Data are shown as mean ± SEM; *P < 0.05; **P < 0.01; ***P < 0.001.

Flot2 deficiency boosts the antibacterial responses of CD4+ and CD8+ T cells in vivo. To evaluate the role of Flot2 in regulating antibacterial immune responses in vivo, we next challenged mice with Listeria monocytogenes. Following infection, Flot2–/– mice showed elevated resistance to weight loss compared with Flot2+/+ mice (Figure 3A). Furthermore, both CD4+ and CD8+ T cells in Flot2–/– mice exhibited increased expression of Ki67 and TNF-α compared with Flot2+/+ mice (Figure 3, B–G), suggesting increased proliferation and effector function. Consistent with this, CD44+T-bet+, CD44+IFN-γ+, CD44–TNF-α+, and CD44+IL-2+ populations were all augmented in both CD4+ and CD8+ splenic T cells (Supplemental Figure 4). Given these findings, we next used Flot2CD4 mice to investigate whether T cell–specific Flot2 deficiency also improves the antibacterial T cell response. Notably, Flot2CD4 mice also showed less weight loss compared with Flot2WT after L. monocytogenes infection (Figure 3H). Quantification of the absolute number of T cells in the spleen of infected Flot2WT and Flot2CD4 mice revealed an increase in both CD4+ and CD8+ T cell numbers in Flot2CD4 mice (Figure 3I). Moreover, Flot2CD4 mice had increased TNF-α+IFN-γ+IL-2+ multifunctional CD4+ T cells, which play a crucial role in infection control (35, 36) (Figure 3, J and K). Consistent with findings in Flot2–/– mice, Flot2CD4 mice also exhibited heightened expression of Ki67 and TNF-α in both CD4+ and CD8+ splenic T cells (Figure 3, L–Q). These data collectively suggest that Flot2 deficiency augments the responses of both CD4+ and CD8+ T cells in the context of in vivo infection with L. monocytogenes.

Flot2 deficiency promotes CD4+ and CD8+ T cell responses against Listeria monocytogenes infection. (A) Weight loss in Flot2+/+ or Flot2–/– mice following Listeria monocytogenes infection (5,000 CFU per mouse) is presented as the mean percentage of initial weight (n = 4–5 per group). (B–G) Flow cytometric analysis of splenic T cells from Listeria-infected Flot2+/+ or Flot2–/– mice. Representative plots (B and E) are provided. CD44+Ki67+ (C) and TNF-α+ (D) populations within viable CD45+TCRβ+CD4+ population and CD44+Ki67+ (F) and TNF-α+ (G) populations within viable CD45+TCRβ+CD8+ population are shown. (H) Weight loss in Flot2WT or Flot2CD4 mice following L. monocytogenes infection (5,000 CFU per mouse) is presented as the mean percentage of initial weight (n = 5–6 per group). (I) Splenic CD4+ and CD8+ T cells numbers in infected Flot2WT or Flot2CD4 mice are depicted. (J–Q) Flow cytometric analysis of splenic T cells from L. monocytogenes–infected Flot2WT or Flot2CD4 mice. Representative plots (J, L, and O) are shown. TNF-α+IFN-γ+IL-2+ (K), CD44+Ki67+ (M), and TNF-α+ (N) populations within viable CD45+TCRβ+CD4+ population and CD44+Ki67+ (P) and TNF-α+ (Q) populations within viable CD45+TCRβ+CD8+ population are shown. Data are representative of 2 independent experiments (A–Q). Data were analyzed by unpaired t test (C, D, F, G, I, K, M, N, P, and Q) or 2-way ANOVA followed with Šidák’s multiple-comparison tests (A and H). Data are shown as mean ± SEM; *P < 0.05; **P < 0.01; ***P < 0.001.

TCR activation induces enhanced response in Flot2-deficient CD4+ but not CD8+ T cells. After confirming that Flot2 deficiency enhances effector T cell responses in vivo in both tumor and infection models, we investigated this phenomenon mechanistically, using reductionist in vitro approaches. Purified naive CD4+ and CD8+ T cells from Flot2WT or Flot2CD4 mice were stimulated with increasing concentrations of plate-bound αCD3, along with a fixed concentration of soluble αCD28 (1 μg/mL), modeling TCR stimulation and costimulation exclusively. Following stimulation, both Flot2WT and Flot2CD4 CD4+ T cells showed a concentration-dependent increase in CellTrace Violet– (CTV–; i.e., proliferated), Ki67+, T-bet+, and CD25+ populations, confirming T cell activation in line with the strength of TCR stimulation (Figure 4, A–D, and Supplemental Figure 5A). Flot2CD4 CD4+ T cells exhibited heightened proliferation (CTV– and Ki67+) and T-bet and CD25 expression compared with Flot2WT across various concentrations of αCD3 (Figure 4, A–D, and Supplemental Figure 5A). Remarkably, Flot2 deficiency augmented CD4+ T cell proliferation even at very low concentrations of αCD3 (0.0625 μg/mL) (Figure 4A) and increased expression of the early T cell activation marker (CD25) at low concentrations of αCD3 (0.125 μg/mL) (Figure 4D), highlighting enhanced T cell responsiveness to weak TCR stimulation. By contrast, Flot2-deficient CD8+ T cells did not experience increased cell proliferation or early activation compared with WT controls (Figure 4, E–H, and Supplemental Figure 5B). Collectively, these findings indicate that Flot2 deficiency renders CD4+ T cells more responsive to weak TCR stimulation in the presence of both TCR stimulation and costimulation, whereas Flot2-deficient CD8+ T cells may rely on supplemental factors, potentially available in vivo, for their boosted activation.

Flot2CD4 CD4+ T cells, but not Flot2CD4 CD8+ T cells, showed enhanced T cell responses during in vitro T cell stimulation. (A–D) Naive CD4+ T cells were purified and stimulated in vitro for 72 hours with varying doses of plate-bound αCD3, alongside a fixed dose of soluble αCD28 (1 μg/mL), followed by flow cytometric analysis to assess cell proliferation and activation. CTV– (A), Ki67+ (B), T-bet+ (C), and CD25+ (D) populations within viable TCRβ+CD4+ population are shown. (E–H) Naive CD8+ T cells were purified and stimulated in vitro for 72 hours with varying doses of plate-bound αCD3, alongside a fixed dose of soluble αCD28 (1 μg/mL), followed by flow cytometric analysis to assess cell proliferation and activation. CTV– (E), Ki67+ (F), Granzyme B+ (G), and CD25+ (H) populations within viable TCRβ+CD8+ population are shown. Data are representative of 2 independent experiments (A–H). Data were analyzed by 1-way ANOVA followed with Šidák’s multiple-comparison tests (A–H). Data are shown as mean ± SEM; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Deletion of Flot2 in CD4+ T cells promotes Th1 cell differentiation. During T cell activation, naive CD4+ T cells have the potential to differentiate into various Th cell subsets, characterized by distinct transcription factors, cytokines, and functions (37–39). The determination of cell fate during differentiation is influenced by both TCR signal strength and the cytokine milieu, with recent findings suggesting an association between strong TCR signals and Th1 differentiation (40–42). Since in vitro stimulated Flot2-deficient CD4+ T cells express higher levels of CD25 and T-bet (Figure 4, C and D), indicative of strong TCR signal strength, we investigated the effect of Flot2 deficiency on Th differentiation. Initially, naive CD4+ T cells were differentiated in vitro using Th1 polarizing medium and varying concentration of plate-bound αCD3. Both Flot2WT and Flot2CD4 CD4+ T cells exhibited concentration-dependent induction of Th1 polarization and proliferation (Figure 5). Notably, Flot2CD4 CD4+ T cells displayed a significant increase in T-bet+IFN-γ+ and CD44+TNF-α+ populations compared with Flot2WT CD4+ T cells across various concentrations of αCD3, even at very low concentrations (Figure 5, A–D). Furthermore, Th1 cell proliferation of Flot2CD4 CD4+ T cells was also robustly induced at low concentrations of αCD3, likely due to their increased sensitivity to TCR stimulation (Figure 5, E and F).

Flot2 ablation promotes CD4+ T cell differentiation into Th1 upon weak TCR stimulation. (A–F) Naive CD4+ T cells were purified and differentiated toward the Th1 subtype in vitro using Th1 polarizing conditions, followed by flow cytometric analysis to assess Th1 polarization, cytokine production, and cell proliferation. Representative plots (A, C, and E) are shown. T-bet+IFN-γ+ (B), CD44+TNF-α+ (D), and CTV– (F) populations within viable TCRβ+CD4+ population are shown. Data are representative of 3 independent experiments (A–F). Data were analyzed by 1-way ANOVA followed with Šidák’s multiple-comparison tests (B, D, and F). Data are shown as mean ± SEM; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Next, we evaluated differentiation into other Th subsets using Th2, Th17, or Treg polarizing conditions. In contrast to Th1 differentiation, Flot2CD4 CD4+ T cells showed no difference in Th2 proliferation, evidenced by the CTV– population, and a decrease in IL-4+GATA3+ populations at sufficient TCR stimulation (Supplemental Figure 6, A–D). Similarly, no difference was observed in Th17 differentiation (Supplemental Figure 6, E and F). However, Flot2CD4 CD4+ T cells showed augmented differentiation into Foxp3+ Treg populations selectively upon weak TCR stimulation (Supplemental Figure 6, G and H). Given that Treg differentiation tends to favor low-abundance, high-affinity antigens (43), this finding may reflect the increased reactivity of Flot2CD4 CD4+ T cells to the low abundance of αCD3 compared with Flot2WT CD4+ T cells. On the basis of these findings, we conclude that Flot2-deficient CD4+ T cells are inclined toward Th1 and Treg differentiation even at very low concentrations of αCD3, likely due to their hypersensitivity to weak TCR stimulation.

Flot2 ablation decreases TCR triggering threshold in CD4+ T cells. Given the heightened proliferation, activation, and Th1 differentiation observed in Flot2-deficient CD4+ T cells, we hypothesized an augmentation in TCR signaling in CD4+ T cells upon Flot2 ablation. To test this, we stimulated purified naive CD4+ T cells from Flot2WT or Flot2CD4 mice with varying concentrations of plate-bound αCD3 in vitro and analyzed them after 3 hours or 24 hours to observe early-phase T cell activation. Flot2CD4 CD4+ T cells exhibited elevated expression of Nur77, a marker of TCR signal strength, particularly at low concentrations of αCD3 (Figure 6, A and B). Additionally, the early T cell activation marker CD69 was increased in Flot2CD4 CD4+ T cells compared with Flot2WT CD4+ T cells (Figure 6, A and C). Conversely, Flot2CD4 CD8+ T cells did not exhibit enhanced expression of Nur77 and CD69, further emphasizing the necessity of additional factors for the Flot2-dependent activation phenotype in CD8+ T cells (Supplemental Figure 7, A–C). We next investigated earlier phases of TCR signaling by profiling phosphorylation of TCR signaling molecules after 3 minutes of in vitro stimulation. Notably, early phosphorylation of ZAP70 and ERK1/2 induced by TCR triggering was enhanced in Flot2CD4 CD4+ T cells compared with Flot2WT CD4+ T cells under weak stimulation (Figure 6, D–F). Meanwhile, the phosphorylation of Lck at Y505, an inactivating phosphorylation, showed no difference between the 2 genotypes (Figure 6, D and G). Altogether, these data show enhanced signaling and early activation of Flot2CD4 CD4+ T cells compared with Flot2WT CD4+ T cells upon suboptimal stimulation, indicating that Flot2 ablation lowers the TCR triggering threshold.

Flot2 ablation sensitizes TCR triggering threshold in CD4+ T cells. (A–C) Naive CD4+ T cells were stimulated in vitro for 3 hours (B) or 24 hours (C) with varying doses of plate-bound αCD3, alongside a fixed dose of soluble αCD28 (1 μg/mL), followed by FACS. Representative plots (A) show Nur77+ (B) and CD69+ (C) populations within viable TCRβ+CD4+ population. (D–G) Western blot of the phosphorylation of TCR signaling molecules in naive CD4+ T cells stimulated with varying doses of plate-bound αCD3 for 3 minutes. Representative blots (D) and quantifications of pZAP70 (E), pERK1/2 (F), and pLck (Y505) (G), normalized to their respective total protein levels (ZAP70, ERK1/2, and Lck), are shown. (H and I) scRNA-Seq was performed on naive CD4+ T cells following a 3-hour stimulation with varying concentrations of plate-bound αCD3. A fixed dose of soluble αCD28 (1 μg/mL) was provided under the conditions of 0.25 or 1 μg/mL of plate-bound αCD3. Unsupervised T cell clusters were annotated as 5 distinguishable functional states on a UMAP plot (H), and the effect of stimulation dose was projected onto the UMAP (I). (J) Distribution of Flot2WT or Flot2CD4 CD4+ T cells in each cluster. Red arrows indicate the priming clusters for each genotype. (K) Occupancy of Flot2WT or Flot2CD4 genotype in each T cell cluster, analyzed by total or each stimulatory condition. (L) Volcano plots of spliced RNA in naive, priming, and activated clusters. (M) Expression level of spliced RNA related to cellular proliferation in the naive cluster. Data are pooled from 3 (A–C), 5 (E), 8 (F), or 7 (G) independent experiments. Data were analyzed by 1-way ANOVA followed with Šidák’s multiple-comparison tests (B, C, and E–G), χ2 analysis (K), or Wilcoxon ranked-sum test (M). Data are shown as mean ± SEM; *P < 0.05; **P < 0.01; ****P < 0.0001.

To gain a more comprehensive understanding of the role of Flot2 in CD4+ T cells during T cell activation, we next performed scRNA-Seq on naive Flot2WT or Flot2CD4 CD4+ T cells after in vitro stimulation with varying concentrations of αCD3 antibody–mediated TCR stimulation: no (0 μg/mL), weak (0.25 μg/mL), or strong (1 μg/mL) stimulation for 3 hours. Clustering the results using the Leiden algorithm revealed 5 distinct functional states based on expression of marker genes — naive, intermediate, priming, preactivated, and activated — as visualized using Uniform Manifold Approximation and Projection (UMAP) (Figure 6H and Supplemental Figure 7D). These clusters aligned well with previously reported gene sets related to early T cell activation (44) and hallmark genes of T cell activation (Nr4a1, Myc, Cd69, Il2ra), and naive status (Tcf7, Ccr7, Cd4, Sell) (Supplemental Figure 7, E–G). The integration of stimulation concentrations into the UMAP plot revealed that cells from the 0 μg/mL group were mostly in the naive cluster and cells from the 1 μg/mL group were mostly in the activated cluster, validating our analysis (Figure 6I). Notably, naive CD4+ T cells exposed to weak stimulation (0.25 μg/mL) were distributed across diverse clusters spanning from naive to activated states, indicating that reducing the αCD3 concentration led to increased heterogeneity in the transcriptomic profile during T cell activation (Figure 6I). Interestingly, the distribution of the 2 genotypes significantly differed across activation clusters, with Flot2CD4 CD4+ T cells showing a significantly lower frequency in the priming cluster (red arrow) compared with Flot2WT CD4+ T cells (Figure 6, J and K). By contrast, Flot2CD4 CD4+ T cells demonstrated a higher occupancy in the activated cluster following weak stimulation (0.25 μg/mL) compared with Flot2WT CD4+ T cells, consistent with flow cytometric analysis following in vitro stimulation (Figure 6, B and K).

Next, using RNA velocity analysis, we examined if Flot2 deficiency affected T cell activation trajectories following in vitro stimulation. Our observations revealed nearly overlapping RNA velocity UMAP space between Flot2WT and Flot2CD4 CD4+ T cells, indicating that both groups undergo similar major transcriptional changes during the early stages of activation, regardless of Flot2 expression (Supplemental Figure 7, H–J). Although Flot2WT and Flot2CD4 CD4+ T cells displayed similar transcriptomic changes throughout activation, our analysis revealed increased spliced RNA expression of genes associated with cellular proliferation in Flot2CD4 CD4+ T cells (Figure 6, L and M). Specifically, even in the naive state, Flot2CD4 CD4+ T cells demonstrated higher expression levels of spliced Ppia, Cd52, and Malat1 (Figure 6M). These genes are known to positively regulate T cell proliferation and activation as well as to enhance cytotoxic T cell differentiation and cytokine production (45–50). This suggests that while gene expression alterations remain consistent, differences in isoform usage may contribute to variations in T cell activation between Flot2WT and Flot2CD4 CD4+ T cells.

Collectively, these findings suggest that Flot2 deficiency lowers the TCR triggering threshold in CD4+ T cells, resulting in enhanced TCR signaling and activation, particularly in response to weak TCR stimulation. Flot2 deficiency does not alter the intrinsic activation trajectory of CD4+ T cells but appears to alter the occupancy of a priming state, promoting the progression from the naive to the fully activated state upon weak stimulation.

Flot2 controls TCR nanoclustering on the plasma membrane of naive CD4+ T cells. Receptor clustering is pivotal for setting thresholds in various signaling pathways (51, 52). While TCRs form nanoclusters and their clustering is crucial for TCR signaling regulation (7–9, 53–56), the mechanisms governing TCR nanoclustering remain unclear. Based on our findings demonstrating a role of Flot2 in regulating TCR signaling initiation, we hypothesized that Flot2 may also regulate TCR nanoclustering. Utilizing super-resolution imaging, we examined TCR nanoclusters in steady-state naive CD4+ T cells from Flot2WT or Flot2CD4 mice, identifying them with CD3ε or TCRβ markers as previously described (9, 57). Notably, we found that naive Flot2CD4 CD4+ T cells exhibited a higher number of CD3ε+ TCR nanoclusters in the steady state (Figure 7, A–C). Associated with this was a reduction in cluster size, as measured using volumetric space (voxel) analysis (Figure 7D). This increased number of small clusters resulted in a pattern of scattered TCR clusters on the membrane, giving the appearance of greater overall coverage (Figure 7A). Consistent with CD3ε+ nanocluster analysis, there was an increase in the number of TCRβ+ nanoclusters of smaller sizes (Figure 7, E–H). Convex hull geometry analysis further confirmed reduced volume, surface, the largest length, and the largest width of the convex hull of the cluster in Flot2CD4 naive CD4+ T cells compared with Flot2WT counterparts (Supplemental Figure 8). In summary, these results suggest that Flot2 ablation regulates TCR nanoclustering by promoting the formation of an increased number of small clusters on the plasma membrane of naive CD4+ T cells.

Flot2 ablation increases the number of surface TCR nanoclusters with a smaller size on naive CD4+ T cells. (A–H) dSTORM analysis of TCR nanoclustering in Flot2WT and Flot2CD4 naive CD4+ T cells. Clustering images of CD3ε molecules (A and B) or TCRβ molecules (E and F) are shown. Number of clusters and voxel of CD3ε (C and D) or TCRβ (G and H) molecules after quantification using Huygens Cluster Analyzer are depicted. Scale bars: 1 μm. Data are representative of 4 (A–D) or 2 (E–H) independent experiments. Data were analyzed by unpaired t test (C, D, G, and H). Data are shown as mean ± SEM; *P < 0.05; **P < 0.01.