Follicular helper T (Tfh) cells are the specialized CD4⁺ T cell subset that localize within B cell follicle to assist germinal center (GC) formation, plasma cell differentiation and high-affinity antibody production (Vinuesa et al., 2016; Crotty, 2011). Identified in the circulation and lymphoid organs post immune response (memory phase), CXCR5⁺ memory Tfh cells rapidly differentiate into mature effector Tfh cells and accelerate antibody response upon antigen re-exposure (Hale et al., 2013; He et al., 2013; MacLeod et al., 2011; Sage et al., 2014; Weber et al., 2012; Yu et al., 2022).

CXCR5-expressing CD45RA^- CD4⁺ T cells circulating in human blood (cTfh) provide important subjects to investigate memory Tfh cells since they have egressed from the site of the immune response at secondary lymphoid organs and can differentiate into effector Tfh cells upon antigen re-exposure (Tsai and Yu, 2014). Noticeably, cTfh cells are heterogenous and are often classified into subsets by distinct functional markers. For example, cTfh cells are classified into cTfh1 (CXCR3⁺CCR6^-), cTfh2 (CXCR3^-CCR6^-), and cTfh17 (CXCR3^-CCR6⁺) subsets based on the expression of chemokine receptors CXCR3 and CCR6 associated with Th1 and Th17, respectively. cTfh2 and cTfh17 cells were reported to demonstrate better B cell helper function than cTfh1 cells in culture (Morita et al., 2011). The increases in cTfh2 and cTfh17 frequencies in autoimmune diseases often correlated with excessive production of pathogenic autoantibodies (Zhao et al., 2018; Akiyama et al., 2015). On the other hand, infections such as HIV and malaria mainly induce the generation of cTfh1 cells (Niessl et al., 2020; Obeng-Adjei et al., 2015). In influenza vaccination, it is also the cTfh1 subset that correlates with the titers of protective antibodies (Bentebibel et al., 2013).

Besides the classification of cTfh into cTfh1, cTfh2, and cTfh17 subsets by the features of lineage polarization, cTfh cells are composed of CCR7^highPD-1^low ‘central memory (CM)-like’ (cTfh_CM) and CCR7^lowPD-1^high ‘effector memory (EM)-like’ (cTfh_EM) subsets (He et al., 2013), the latter also containing a more active ICOS⁺ population (Bentebibel et al., 2013; Spensieri et al., 2013; Herati et al., 2017). CCR7^high PD-1^low cTfh_CM cells are dominant in human blood cTfh cells whereas circulating CCR7^lowPD-1^high cTfh_EM cells are temporarily induced in immune response and generated from the precursor stage of Tfh differentiation at secondary lymphoid organs (He et al., 2013).

There is little knowledge on the difference of Tfh1, Tfh2, and Tfh17 cells in memory responses. In this study, we developed a method to induce antigen-specific Tfh1, Tfh2, and Tfh17-like (iTfh1, iTfh2, and iTfh17) mouse cells in vitro. iTfh1, iTfh2, and iTfh17 cells showed comparable B-helper function after the adoptive transfer into recipient mice followed by immediate immunization. In contrast, if transferred cells experienced an extended period of resting before re-immunization, iTfh17 cells were superior to iTfh1 and iTfh2 cells in sustaining antibody responses. In humans, cTfh17 cells represented ~20% cTfh_EM cells but accounted for >50% cTfh_CM cells which transcriptionally and phenotypically resemble central memory CD4⁺ T (T_CM) with better survival and proliferative potential than effector memory (T_EM) cells (Sallusto et al., 2004). In vaccine responses to hepatitis B virus (HBV), influenza, tetanus toxin or measles, the cTfh17 subset in vaccine-specific cTfh cells was preferentially maintained into memory phase and long-lived. Complementary results from mouse and human studies thus suggest Tfh17 cells are superior for memory maintenance, the ability to persist and to support humoral response upon antigen restimulation. Of note, this study includes many Tfh populations and their definitions and features were summarized to facilitate clarification (Table 1).

Results

In vitro differentiation of induced Tfh1, Tfh2, and Tfh17-like (iTfh1, iTfh2, iTfh17) cells

The classification of Tfh1/2/17 cells based on the expression of CXCR3 and CCR6 markers was established by characterizing human blood memory Tfh cells (Morita et al., 2011). Such memory Tfh1/2/17 subsets in mice are low in numbers (Figure 1A), thus limiting functional characterization. We modified an established method that induces antigen-specific naive CD4⁺ T cells, such as OT-II T cells with transgenic TCR specific to ovalbumin (OVA), to differentiate into Tfh cells (iTfh) in vitro (Gao et al., 2020) and induced the individual differentiation into Tfh1/2/17 (iTfh1/2/17) in vitro. In addition to IL-6 and IL-21 in the iTfh differentiation method (Gao et al., 2020), Th1 (IL-12, anti-TGF-β, anti-IL-4), Th17 (TGF-β, anti-IFN-γ, anti-IL-4), and Th2 (IL-4, anti-IFN-γ, anti-TGF-β) polarization cultures were adopted for iTfh1/2/17 induction with lower IL-12, TGF-β or IL-4 concentrations for iTfh1/2/17 induction than those used for canonical iTh1, iTh17, or iTh2 induction (details in the method) (Read et al., 2019; Lu et al., 2011; Nurieva et al., 2008; Figure 1B). iTfh1/2/17 cells expressed higher Tfh-defining markers CXCR5, PD-1 and BCL6 than iTh0/1/2/17 cells (Figure 1C and D). The BCL6 expression in iTfh1/2/17 cells was lower than CD44⁺CXCR5^highPD-1^high GC-Tfh cells in immunized mice (Figure 1—figure supplement 1A, B). Tfh differentiation undergoes a step-by-step process, showing the generation of precursor Tfh cells expressing intermediate levels of BCL6 and subsequent maturation of GC-Tfh cells with the highest BCL6 expression (Vinuesa et al., 2016; Crotty, 2011). Memory cTfh cells largely originate from precursor Tfh cells and express low levels of BCL6 (He et al., 2013). Given that iTfh1/2/17 cells expressed BCL6 lower than that in GC-Tfh cells and resemble precursor Tfh cells, iTfh1/2/17 cells are suitable to study the function of memory cTfh cells. Importantly, iTfh1/2/17 cells differentially expressed transcription factors T-bet, GATA3 and RORγt (Figure 1E and F) and chemokine receptors CXCR3 and CCR6 (Figure 1G and H), as their counterpart human Tfh1/2/17 cells (Morita et al., 2011).

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To examine whether iTfh1/2/17 cells retain polarized phenotypes in vivo, we adoptively transferred each cell type individually into congenic CD28KO recipient mice, followed by the immunization of OVA in aluminium salt (OVA-Alum) (Figure 1I). After 7 days, iTfh1/2/17 cells showed the comparable ability of effector Tfh differentiation (Figure 1J and K) but maintain the distinction in CXCR3 and CCR6 expression aligning with their progenitors (Figure 1J and L). These results suggest that in vitro generated iTfh1/2/17 cells can be used to investigate the function of Tfh1/2/17 cells.

iTfh17 cells are superior in memory maintenance

To compare the function of Tfh1, Tfh2 and Tfh17 in vivo, we adoptively transferred each of OT-II naive T cell-derived iTfh1, iTfh2, or iTfh17 cells into congenic CD28KO recipient mice. T cells in CD28KO mice are defective in co-stimulation and unable to generate endogenous Tfh cells so antibody responses in CD28KO mice are dependent on transferred iTfh cells. After adoptive cell transfer, mice were immunized with OVA-Alum at day 0 (early immunization) or day 35 (late immunization) with the latter condition mimicking memory maintenance of Tfh1, Tfh2, and Tfh17 for extended in vivo resting (Figure 2A).

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On day 7 post the early immunization, OT-II iTfh1, iTfh2 and iTfh17 cells demonstrated largely comparable Tfh differentiation and the function in supporting the generation of germinal centre B (B_GC) cells and antibody-secreting B (B_ASC) cells (Figure 2B–G). A larger magnitude of B_GC cells supported by iTfh2 cells might be explained by the function of IL-4 in enhancing B_GC generation (Gaya et al., 2018). However, the outcome was very different in the scheme of late immunization whereby iTfh cells had experienced memory maintenance. After resting in vivo for 35 days, iTfh17 cells produced more than twofold of mature effector Tfh cells than those by iTfh1 or iTfh2 cells (Figure 2B and E), accompanied by ~twofold increase in B_GC differentiation in mice that had received iTfh17 cells than those had received iTfh1 or iTfh2 cells (Figure 2C and F). Although the trend of an increase in iTfh17-supported B_ASC differentiation didn’t reach statistical significance (Figure 2D and G), iTfh17 cells were superior to iTfh1 and iTfh2 cells in supporting the production of anti-NP IgG antibodies, after resting in vivo for 35 days before the immunization with antigen 4-Hydroxy-3-nitrophenyl (NP)-OVA (Figure 2H). Collectively, iTfh17 cells are superior to iTfh1 or iTfh2 cells in helping B cells, but only in the scheme with extended in vivo resting.

The selective advantage of iTfh17 cells in supporting Tfh differentiation and humoral immunity after an extended in vivo resting followed by immunization suggests that Tfh17 cells may outperform Tfh1 or Tfh2 cells to sustain Tfh memory. In resting mice, Tfh17 cells expressed higher CCR7 than that on Tfh1 or Tfh2 cells (Figures 1A and 2I), despite the highest expression of activation marker CD44 by Tfh17 cells (Figure 2J). CCR7⁺ marks T_CM cells that circulate in the blood and secondary lymphoid tissues and have longer survival and better proliferative capacity than CCR7^- T_EM cells (Sallusto et al., 2004; Bouneaud et al., 2005). We thus hypothesized that Tfh17 cells might carry certain features of T_CM cells suitable for memory maintenance.

Human cTfh_CM and cTfh_EM subsets phenotypically and functionally resemble T_CM and T_EM subsets respectively

Following the observation that iTfh17 cells showed a unique advantage in memory maintenance, we set to characterize the function of human Tfh17 cells in maintaining Tfh memory. We previously reported that human cTfh cells are composed of CCR7^highPD-1^low T_CM-like and CCR7^lowPD-1^high T_EM-like subsets with the latter indicating an active Tfh differentiation (He et al., 2013), but their function has not been formally compared. We first investigated the relationship between the two cTfh subsets and corresponding CD4⁺ T_CM and T_EM subsets by transcriptomic analysis using RNA sequencing (RNA-seq) (Figure 3A). As shown in an unsupervised multidimensional scaling (MDS) plot, cTfh_CM cells closely cluster with T_CM cells, and cTfh_EM cells fall between T_CM and T_EM cells on the major dimension1, implying that cTfh_EM cells are distinct from cTfh_CM and T_CM cells but also have effector programs different from T_EM cells (Figure 3B). Previous studies reported that cTfh cells predominantly show CCR7⁺ CM phenotype (Chevalier et al., 2011). Our transcriptomic analysis indeed suggests that cTfh_CM cells acquire a quiescent state hardly distinguishable from T_CM cells. In contrast, cTfh_EM cells’ transcriptomes are clearly separated from those of T_EM cells, presumably caused by the divergent effector function of Tfh cells as compared to other effector Th1, Th2, or Th17 cells. In line with this, the top 50 differentially expressed genes (DEG) indicate effector genes such as ZEB2 and TBX21 (Omilusik et al., 2015) were highly expressed in T_EM cells, intermediate levels in cTfh_EM cells, and lowest in cTfh_CM and T_CM cells (Figure 3C). In top 50 hallmark gene sets identified by gene set enrichment analysis (GSEA) between cTfh_EM vs cTfh_CM cells or T_EM vs T_CM cells, 37 gene sets were significantly enriched by both comparisons (NES discrepancy >2, Figure 3D), suggesting that the transcriptomic features and regulation between cTfh_EM vs cTfh_CM cells are overall similar to those between T_EM vs T_CM. Despite T_EM and cTfh_Em cells show distinct transcriptomes and locate separately in the MDS plot (Figure 3B), the key gene sets that are related to common effector T cell function (activation, effector differentiation, and cell cycle entry) were both positively enriched in comparisons between cTfh_EM vs cTfh_CM cells or T_EM vs T_CM cells (Figure 3E). Therefore, cTfh_CM and cTfh_EM cells resemble T_CM and T_EM cells at the transcriptomic levels respectively.

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We next compared cTfh_CM and cTfh_EM subsets for survival and stimulation-induced proliferation in culture, which were applied to characterize the difference between T_CM and T_EM cells (Sallusto et al., 2004). In non-stimulation culture for 3 days, T_CM and cTfh_CM cells retained ~50% viability while T_EM and cTfh_EM cells showed poorer survival of ~30% (Figure 3F and G). To measure the proliferative potential, all subsets were labeled with carboxyfluorescein succinimidyl ester (CFSE) and stimulated by anti-CD3/CD28 for 2.5 days. While the majority of T_EM or cTfh_EM cells underwent division once, most T_CM or cTfh_CM cells reached the second or third division, indicating a better proliferative potential (Figure 3H, I). Collectively, CCR7^highPD-1^low cTfh_CM and CCR7^lowPD-1^high cTfh_EM subsets showed not only transcriptomic profiles resembling their counterpart T_CM and T_EM cells but also functional characteristics of survival and proliferative capacity (Sallusto et al., 2004; Bouneaud et al., 2005).

cTfh_CM cells are enriched with the cTfh17 subset whereas cTfh_EM cells are enriched with the cTfh1 subset

From a cohort of healthy donors (N=33, Table 2), we analyzed CCR7^highPD-1^low cTfh_CM and CCR7^lowPD-1^high cTfh_EM cells for the percentages of cTfh1/2/17 subsets based on CXCR3 and CCR6 expression. In agreement with the higher expression of CCR7 on mouse Tfh17 than that on Tfh1 or Tfh2 cells (Figure 2I), human cTfh_CM cells were dominated by the cTfh17 subset (mean = 51.44%), followed by the cTfh2 subset (mean = 16.19%) and the cTfh1 subset (mean = 12.17%) (Figure 4A), whereas cTfh_EM cells were dominated by the cTfh1 subset (mean = 34.06%,) (Figure 4B). The population of cTfh cells that expresses both CXCR3 and CCR6 has been reported and also presented in our samples. Due to the fact that CXCR3⁺CCR6⁺ cTfh cells were fewer than cTfh1, cTfh2, or cTfh17 cells and their ontogeny remains to be fully revealed (Morita et al., 2011), we did not include this population in the following analyses. To avoid the influence of individual variation of Tfh1/2/17 polarization due to different histories of immune exposure and examine whether there is an intrinsic difference of cTfh1/2/17 frequencies between cTfh_CM or cTfh_EM cells, the percentages of cTfh1/2/17 cells in cTfh_CM cells were normalized to those in cTfh_EM cells in each individual, which demonstrated the highest cTfh_CM/cTfh_EM ratio for cTfh17 (mean = 4.18), an intermediate ratio for cTfh2 (mean = 3.38), and the lowest ratio for cTfh1 (mean = 0.75) (Figure 4C). The highest ratio (>>1) for cTfh17 indicates cTfh_CM cells are highly enriched with the cTfh17 subset whereas the lowest ratio (<1) for cTfh1 indicates that cTfh_EM cells are enriched with the cTfh1 subset. We also measured the expression of hallmark transcription factors TBX21, GATA3, and RORC and cytokines IFN-γ, IL-4 and IL-17A that are selectively expressed in cTfh1/2/17 cells, respectively (Morita et al., 2011). These molecules for effector Th functions are abundantly expressed by T_EM cells but are downregulated in T_CM cells which enter into a resting state (Sallusto et al., 2004). Indeed, the expression of effector transcription factors and cytokines was consistently lower in cTfh_CM cells than those in cTfh_EM cells (Figure 4D and F). Notably, the ratios of expression (cTfh_CM/cTfh_EM) demonstrate modest reductions of 20–40% in cTfh17-related markers RORγt and IL-17A, in contrast to vast reductions of 70–80% in cTfh1-related markers T-bet and IFN-γ (Figure 4E and G). Such results of transcription factor and cytokine expression support the conclusion for an enrichment of the cTfh17 subset and a loss of the cTfh1 subset in cTfh_CM cells.

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Table 2

Cohort description	Number	Gender(female, male)	Age(median, range)	CorrespondingFigures
Healthy individuals for cTfh phenotyping	33	26/7	35 (21–71)	Figure 4A–C Figure 7D–E Figure 5—figure supplement 1A–C
Healthy individuals received HBV vaccines	38	8/29	19 (18–20)	Figure 5 Figure 7D–E Figure 5—figure supplement 1D–E Figure 5—figure supplement 2
Healthy individuals for measles and TT AIM assay	20	11/9	24 (18–32)	Figure 7D–E
Healthy children	18	14/4	6 (0.5–12)	Figure 7D–E
Cord blood	5	2/3	0 (0–0)	Figure 7D–E
Recovered Covid-19 patients	13	9/4	33 (23–52)	Figure 7—figure supplement 1A–C
Healthy individuals for qPCR and cytokine assay	14	9/5	42.5 (27-51)	Figure 4D–G Figure 7—figure supplement 1A

HBV antigen-specific cTfh17 cells are preferentially maintained in memory phase

cTfh_EM to cTfh_CM phenotype conversion occurs over the period of a few weeks when the antigen stimulation is discontinued (He et al., 2013). The enrichment of the cTfh17 subset in human cTfh_CM cells suggest the cTfh17 subset in cTfh_EM cells may persist longer than the cTfh1 or cTfh2 subsets. The phenomenon could also result from a biased cTfh_CM phenotype of cTfh17 cells generated even early in immune responses. To tease apart the cause, we next examined the phenotype of antigen-specific human cTfh cells over a period that expands both effector and memory phases after vaccination or infection.

Childhood HBV vaccination doesn’t always provide life-long protection with a proportion of vaccinees with antibody titers at an undetectable level in adulthood (Bruce et al., 2016). HBV boosting vaccination is recommended for high-risk populations such as medical practitioners including medical students in China. A cohort of medical students (N=38) with serum negative for anti-HBV surface antigen (HBVSA) antibody were recruited (Table 2). Peripheral blood mononuclear cells (PBMCs) were collected at day 7 before and day 7 and 28 after the immunization (Figure 5A). Antigen-induced marker (AIM) assay was used to examine HBV vaccine-specific T cells by culturing PBMCs with HBVSA for 18 hr and detecting the PD-L1⁺OX40⁺CD25⁺ cells as the antigen-specific population (Figure 5B). This method has been applied to characterize antigen-specific cTfh cells (Dan et al., 2016; Reiss et al., 2017). Such stimulation did not change the expression of CXCR3 and CCR6 on cTfh cells (Figure 5—figure supplement 1A–C), indicating that AIM assays are suitable to characterize antigen-specific cTfh1/2/17 cells. As reported (Reiss et al., 2017), a background in AIM assays exists in a small proportion of samples whereby PD-L1⁺OX40⁺CD25⁺ cells were detected in control cultures without antigen stimulation (Figure 5—figure supplement 1D). To specifically quantify antigen-specific response, we subtracted the value of antigen-stimulation culture by the background value from the control culture without antigen stimulation. Normalized values were then used to calculate the percentages of cTfh1, cTfh2, and cTfh17 cells (Figure 5—figure supplement 1E).

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In all subjects negative for HBVSA antigen and anti-HBVSA antibody, the average percentage of the cTfh17 subset in HBVSA-specific memory cTfh cells was 49.31%, whereas the average percentage of the cTfh1 subset was 15.7% (Figure 5C and D). In alignment with the results on total cTfh_CM cells (Figure 4), HBVSA-specific cTfh_CM cells were also enriched with the cTfh17 subset.

To tease apart whether the cTfh17 enrichment was caused by the biased generation or better maintenance, we then analysed PBMC samples collected at day 7 and day 28 after vaccination (Figure 5A). The cohort was divided into 4 groups based on vaccine responses measured by antibody titers (Figure 5—figure supplement 2A): early responders (titer >100 mIU at day7, titer = 1248 ± 324.4 mIU at day 28, N=11), late responders (titer <100 mIU at day 7 and >200 mIU at day 28, titer = 997.1 ± 289.7 mIU/ml at day 28, N=15), weak responders (50 mIU <titer < 200 mIU at day 28, titer = 107.9 ± 37.2 mIU at day 28, N=6) and non-responders (titer <50 mIU on day 28, titer = 17.28 ± 4.379 mIU at day 28, N=6) (Figure 5E). Tfh activation measured by a trend of increase in HBVSA-specific cTfh_EM cells by (2.84-fold, day –7 v.s. day 7, -value=0.074, not reaching statistical significance) was observed only in early responders but no other groups (Figure 5—figure supplement 2B, C). We next focused on the kinetics of HBVSA-specific cTfh subsets in early responders. At day 7 post vaccination, the percentages of three subsets in HBVSA-specific cTfh cells ranged from 20% to 30% and showed no significant difference (Figure 5—figure supplement 2D). Of note, the percentages of the cTfh17 subset significantly increased from ~30% to~50% from day 7–28 (p-value = 0.006). In contrast, the percentages of the cTfh1 subset dropped significantly from ~20% to~10% (p-value = 0.020). The percentages of cTfh2 remained largely unchanged (Figure 5F and G). As a result, cTfh17 cells dominated HBVSA-specific cTfh cells in the memory phase of day 28 post vaccination (Figure 5—figure supplement 2D). Therefore, the cTfh17 enrichment in cTfh_CM cells results from an advantage of cTfh17 cells in memory maintenance, rather than a biased phenotype to cTfh_CM cells. Significant changes in cTfh1 and cTfh17 percentages from day 7 to day 28 were selective in early responder group but not in three other groups (Figure 5G), and only observed in HBVSA-specific cTfh cells but not in total cTfh in early responders (Figure 5—figure supplement 2E), suggesting that the dynamic changes were specific to HBVSA-specific cTfh response.

influenza virus-specific cTfh cells show cTfh1 signatures in effector phase but cTfh17 signatures in memory phase

Single-cell RNA-seq (scRNA-seq) paired with TCR sequencing facilitates the characterization of the phenotype and function of antigen-specific T cell clones in an immune response. We took the advantage of this new technology to analyze the characteristics of influenza haemagglutinin (HA)-specific CD4⁺ T clones in a published dataset of scRNA/TCR-seq from four healthy individuals with influenza vaccination (Meckiff et al., 2020). We compared HA-specific T cell clones before the vaccination (memory phase) and day 12 after the vaccination (effector phase; Figure 6A). HA-specific CD4⁺ T cells before and after the vaccination were pooled to generate unsupervised clustering, in which CXCR5-expressing clusters 2–5 were enriched of cTfh cells, in which a total of twelve major CD4⁺ T clones (clonal abundance ≥10) were identified (Figure 6B). To investigate Tfh subsets-associated features in HA-specific clonal cTfh cells, we applied cTfh1 or cTfh17 signature gene sets derived from bulk RNA-seq for cTfh1/2/17 cells (Figure 6—figure supplement 1A; Yost et al., 2019) in clonal cTfh cells. The scores of cTfh1 signature were higher in clonal cTfh cells in the effector phase than those in the memory phase (p-value = 0.041); by contrast, the scores of cTfh17 signature were lower in the effector phase than in the memory phase (p-value = 0.002) (Figure 6C and D). The divergence of cTfh1 and cTfh17 signatures between the effector and memory phases was consistent in individual donors (Figure 6—figure supplement 1B) and at the level measured by 12 major clones (Figure 6E and F). Therefore, we conclude that the advantage of cTfh17 cells in memory maintenance is consistently observed among different cohorts with different types of vaccines.

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cTfh17 cells are long-lived and accumulate with aging

Our previous experiments have demonstrated that antigen-specific mouse Tfh17 cells and vaccine-specific human Tfh17 cells are superior to Tfh1 and Tfh2 cells in maintaining Tfh memory for a period of about one month (HBV) or less than one year (influenza vaccine). We next ask whether Tfh17 cells can persist for even longer periods, such as years. In a cohort of adults (N=20, Table 2), we examined cTfh cells specific to vaccines for tetanus toxoid and measles, both administrated in childhood (Figure 7A). Given that community transmission of tetanus and measles is very rare (Huang et al., 2018), cTfh cells specific to tetanus toxoid and measles in adults were likely induced many years ago by childhood vaccination (Van Damme et al., 2019; Nanan et al., 2000; Locci et al., 2013). The average percentages of the cTfh17 subset in vaccine-specific memory cTfh cells were 55.22% and 45.07% for tetanus toxoid and measles respectively, which were more than twofold higher than the cTfh2 percentages and more than threefold higher than the cTfh1 percentages (Figure 7B and C). These results suggest cTfh17 cells may maintain Tfh memory for more than a decade. We also asked whether the cTfh17 dominance in memory phase was also applied to cTfh cells induced by SARS-CoV-2 infection. We examined convalescent patients with Covid-19 showing SARS-CoV-2-specific IgG antibodies (N=13, Figure 7—figure supplement 1A and Table 2). Similar to vaccine-specific cTfh cells, the cTfh17 percentages in SARS-CoV-2-specific cTfh cells were much higher than the cTfh1 or cTfh2 percentages (mean, 59.03% v.s. 12.87% or 7.73%) (Figure 7—figure supplement 1B, C).

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If antigen-specific cTfh17 cells are long-lived and superior to cTfh1 and cTfh2 cells for persistence, we would expect a preferential accumulation of cTfh17 cells over cTfh1 or cTfh2 cells along with aging. By pooling results of cTfh characterization from cord blood, children, young and middle-aged adults and the elderly (Table 2), we indeed observed that the cTfh17 percentages in total cTfh cells positively correlated with biological ages whereas the percentages of cTfh1 or cTfh2 subsets showed negative correlations (p-value <0.001) (Figure 7D and E). In conclusion, Tfh17 cells are superior to Tfh1 and Tfh2 cells in Tfh memory maintenance, a phenomenon consistently observed in vaccination, infection and natural antigen exposure.

iTfh17 cells are superior in survival and differentiation into GC-Tfh cells after resting

We reasoned that the advantage of Tfh17 cells in supporting humoral responses after delayed immunization might be attributed to several non-exclusive reasons: (1) Tfh17 can survive better; (2) Tfh17 cells can maintain stronger potential to differentiate into GC-Tfh cells after resting, and (3) Tfh17-derived GC-Tfh cells can gain better B cell helper function. Firstly, to test whether Tfh17 cells can better survive than Tfh1/2 cells, we transferred either OT-II iTfh1, iTfh2 or iTfh17 cells into CD28KO mice and counted the numbers of transferred cells in the spleen after 1 day and 35 days (Figure 8A). While the numbers of transferred iTfh1/2/17 cells were comparable on day1, the numbers of transferred iTfh17 cells were significantly higher than iTfh1 cells on day35 (Figure 8B–C), suggesting that iTfh17 cells had superior survival capacity over iTfh1 but not iTfh2 cells.

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Secondly, to test whether Tfh17 cells may maintain better potential to differentiate into GC-Tfh cells after resting, we transferred either OT-II iTfh1, iTfh2 or iTfh17 cells into CD28KO mice together with NP-specific B1-8 cells, followed by an immediate NP-OVA immunization at day 1 or a delayed NP-OVA immunization to examine the formation of GC-Tfh cells (Figure 8D). In the immediate immunization, iTfh1/2/17 cells expanded and differentiated into GC-Tfh in comparable manners after immunization (Figure 8E–G). However, in the delayed immunization (day 35), iTfh17 cells showed higher expansion than iTfh1 but not iTfh2 cells (Figure 8E). Furthermore, iTfh17 cells differentiated into more GC-Tfh cells than both iTfh1 and iTfh2 cells (Figure 8F–G). These results suggest that iTfh17 cells maintained a better potential to generated GC-Tfh cells compared to Tfh1 or Tfh2 cells, in addition to a better survival than iTfh1 cells.

Finally, to compare the B cell helper function between iTfh1/2/17-derived GC-Tfh cells on per cell basis, we sorted iTfh1/2/17-derived CXCR5^hi PD-1^hi GC-Tfh cells in the same experiment as in ‘(2)’ and measured the expressions of key functional genes in GC-Tfh cells including Pdcd1, Cxcr5, Icos, Cd40lg, Il21, and Bcl6. In the delayed immunization, we found no significant differences in these gene expression among iTfh1/2/17-derived GC-Tfh cells, despite of better B_GC and B_ASC responses in the iTfh17 group (Figure 8—figure supplement 1A–B). In summary, our results suggested that the superior immunological memory maintenance of iTfh17 cells was attributed to their better survival capacity and better maintenance of the potential to differentiate into GC-Tfh cells, rather than better B cell helper function on per cell basis than that of iTfh1 or iTfh2 cells.

Furthermore, we measured the expressions of Ifng and Il4 in iTfh1/2/17 derived GC-Tfh cells and demonstrated iTfh1 and iTfh2-derived GC-Tfh cells showed featured of increased Ifng and Il4 respectively, as their counterpart Th1 and Th2 cells (Figure 8—figure supplement 1C). In agreement with polarized cytokine profiles, we detected that iTfh1 cells promoted isotype switching to IgG2a/IgG3 while iTfh2 cells promoted isotype switching to IgG1/IgE (Figure 8—figure supplement 1D). These results suggest iTfh1/2 cells retained polarised cytokine profiles that promote specific class-switch recombination after antigen re-exposure.

Sequencing data have been deposited in GEO under the accession code GSE167309.

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Author details

1. Xin Gao

   1. Immunology and Infectious Disease Division, John Curtin School of Medical Research, The Australian National University, Canberra, Australia
   2. China-Australia Centre for Personalised Immunology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Investigation, Writing – original draft, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5927-2241

2. Kaiming Luo

   China-Australia Centre for Personalised Immunology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

   Contribution

   Data curation, Formal analysis

   Competing interests

   No competing interests declared

3. Diya Wang

   Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Fourth Military Medical University, Xi'an, China

   Contribution

   Data curation, Methodology

   Competing interests

   No competing interests declared

4. Yunbo Wei

   Laboratory of Immunology for Environment and Health, Shandong Analysis and Test Center, Qilu University of Technology, Shandong Academy of Sciences, Jinan, China

   Contribution

   Data curation, Methodology

   Competing interests

   No competing interests declared

5. Yin Yao

   Department of Otolaryngology-Head and Neck Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

   Contribution

   Data curation, Formal analysis, Methodology

   Competing interests

   No competing interests declared

6. Jun Deng

   China-Australia Centre for Personalised Immunology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

   Contribution

   Data curation, Methodology

   Competing interests

   No competing interests declared

7. Yang Yang

   Frazer Institute, Faculty of Medicine, University of Queensland, Brisbane, Australia

   Contribution

   Methodology

   Competing interests

   No competing interests declared

8. Qunxiong Zeng

   1. China-Australia Centre for Personalised Immunology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
   2. Department of Rheumatology, Shanghai Institute of Rheumatology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

   Contribution

   Data curation

   Competing interests

   No competing interests declared

9. Xiaoru Dong

   Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Fourth Military Medical University, Xi'an, China

   Contribution

   Data curation

   Competing interests

   No competing interests declared

10. Le Xiong

    Department of Rheumatology, Shanghai Institute of Rheumatology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

    Contribution

    Data curation

    Competing interests

    No competing interests declared

11. Dongcheng Gong

    China-Australia Centre for Personalised Immunology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

    Contribution

    Data curation

    Competing interests

    No competing interests declared

12. Lin Lin

    Department of Laboratory Medicine, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

    Contribution

    Resources

    Competing interests

    No competing interests declared

13. Kai Pohl

    Immunology and Infectious Disease Division, John Curtin School of Medical Research, The Australian National University, Canberra, Australia

    Contribution

    Data curation

    Competing interests

    No competing interests declared

14. Shaoling Liu

    Shanghai Children's Medical Centre, Shanghai Jiao Tong University, Shanghai, China

    Contribution

    Data curation

    Competing interests

    No competing interests declared

15. Yu Liu

    Shanghai Children's Medical Centre, Shanghai Jiao Tong University, Shanghai, China

    Contribution

    Data curation

    Competing interests

    No competing interests declared

16. Lu Liu

    Obstetrics and Gynecology Hospital of Fudan University (Shanghai Red House Obstetrics and Gynecology Hospital), Shanghai, China

    Contribution

    Data curation

    Competing interests

    No competing interests declared

17. Thi HO Nguyen

    Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia

    Contribution

    Validation

    Competing interests

    No competing interests declared

18. Lilith F Allen

    Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia

    Contribution

    Validation

    Competing interests

    No competing interests declared

19. Katherine Kedzierska

    Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia

    Contribution

    Resources, Validation

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-6141-335X

20. Yanliang Jin

    Shanghai Children's Medical Centre, Shanghai Jiao Tong University, Shanghai, China

    Contribution

    Resources, Data curation

    Competing interests

    No competing interests declared

21. Mei-Rong Du

    Obstetrics and Gynecology Hospital of Fudan University (Shanghai Red House Obstetrics and Gynecology Hospital), Shanghai, China

    Contribution

    Resources, Data curation

    Competing interests

    No competing interests declared

22. Wanping Chen

    Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Fourth Military Medical University, Xi'an, China

    Contribution

    Resources, Data curation

    Competing interests

    No competing interests declared

23. Liangjing Lu

    Department of Rheumatology, Shanghai Institute of Rheumatology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

    Contribution

    Resources, Funding acquisition

    Competing interests

    No competing interests declared

24. Nan Shen

    1. China-Australia Centre for Personalised Immunology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
    2. Department of Rheumatology, Shanghai Institute of Rheumatology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

    Contribution

    Resources, Data curation, Methodology

    Competing interests

    No competing interests declared

25. Zheng Liu

    Department of Otolaryngology-Head and Neck Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

    Contribution

    Resources, Supervision, Funding acquisition

    Competing interests

    No competing interests declared

26. Ian A Cockburn

    Immunology and Infectious Disease Division, John Curtin School of Medical Research, The Australian National University, Canberra, Australia

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition

    For correspondence

    ian.cockburn@anu.edu.au

    Competing interests

    No competing interests declared

27. Wenjing Luo

    Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Fourth Military Medical University, Xi'an, China

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition, Project administration

    For correspondence

    luowenj@fmmu.edu.cn

    Competing interests

    No competing interests declared

28. Di Yu

    1. Immunology and Infectious Disease Division, John Curtin School of Medical Research, The Australian National University, Canberra, Australia
    2. Frazer Institute, Faculty of Medicine, University of Queensland, Brisbane, Australia
    3. Ian Frazer Centre for Children’s Immunotherapy Research, Children’s Health Research Centre, Faculty of Medicine, University of Queensland, Brisbane, Australia

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing – original draft, Project administration, Writing – review and editing

    For correspondence

    di.yu@uq.edu.au

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-1721-8922

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