Preexisting memory CD4 T cells in naïve individuals confer robust immunity upon hepatitis B vaccination
Antigen recognition through the T cell receptor ( TCR ) is one of the key determinants of the adaptive immune response ( Rudolph et al . , 2006 ) . Antigen presentation via major histocompatibility complex ( MHC ) proteins , together with the right costimulatory and cytokine signals , are responsible for T cell activation ( Curtsinger and Mescher , 2010; Esensten et al . , 2016 ) . The TCR αβ heterodimer binds the peptide-MHC ( pMHC ) complex and confers the specificity of a T cell to an epitope . A highly diverse TCR repertoire ensures that an effective T cell response can be mounted against pathogen-derived peptides ( Turner et al . , 2009 ) . High TCRαβ diversity is generated through V ( D ) J recombination at the complementary-determining region 3 ( CDR3 ) of TCRα and TCRβ chains , accompanied with junctional deletions and insertions of nucleotides , further adding to the diversity ( Krangel , 2009 ) . Vaccines activate naïve T cells with high specificity to vaccine-derived peptides and induce T cell expansion and differentiation into effective and multifunctional T cells . This is followed by a contraction phase from which surviving cells constitute a long-lived memory T cell pool that allows for a quick and robust T cell response upon a second exposure to the pathogen ( Farber et al . , 2014 ) . However , previous studies have shown that a prior pathogen encounter is not a prerequisite for the formation of memory T cells and that CD4 T cells with a memory phenotype can be found in antigen-naïve individuals ( Su et al . , 2013 ) . The existence of memory-like CD4 T cells in naïve individuals ( Sewell , 2012 ) can be explained by molecular mimicry , as the encounter with environmentally derived peptides activates cross-reactive T cells due to the flexible nature of CD4 T cell recognition of the pMHC complex ( Wilson et al . , 2004 ) . Indeed , work that attempted to replicate the history of human pathogen exposure in mice has shown that sequential infections altered the immunological profile and remodeled the immune response to vaccination ( Reese et al . , 2016 ) . The existence of memory CD4 T cells specific to vaccine-derived peptides in unexposed individuals might confer an advantage in vaccine-induced immunity . In the present study , we used high-throughput sequencing to profile the memory CD4 TCRβ repertoire of healthy hepatitis B ( HB ) -naïve adults before and after administration of an HB vaccine to investigate the impact of preexisting memory CD4 T cells on the immune response to the vaccine . Based on anti-hepatitis B surface ( anti-HBs ) antibody titers over 365 days , vaccinees were grouped into early- , late- , and non-converters . Our data reveals that individuals with preexisting vaccine-specific CD4 T cell clonotypes in the memory CD4 compartment had earlier emergence of antibodies and mounted a more vigorous CD4 T cell response to the vaccine . Moreover , we identify a set of vaccine-specific TCRβ sequence patterns which can be used to predict TCR specificity and in turn , which individuals will have an early and more vigorous response to HB vaccine .
Out of 34 vaccinees , 21 vaccinees seroconverted ( an anti-HBs titer above 10 IU/ml was considered protective; Keating and Noble , 2003 ) at day 60 and were classified as early-converters; nine vaccinees seroconverted at day 180 or day 365 and were classified as late-converters; remaining four vaccinees had an anti-HBs antibody titer lower than 10 IU/ml at all time points following vaccination and were classified as non-converters ( Figure 1 and Figure 1—figure supplement 1A ) . Members of Herpesviridae family might alter immune responses to vaccines ( Furman et al . , 2015 ) . We found no significant differences in cytomegalovirus ( CMV ) , Epstein-Barr virus ( EBV ) , or herpes simplex virus ( HSV ) seropositivity between the three groups in our cohort ( Figure 1—figure supplement 1B ) . Early-converters were slightly younger than late-converters , and non-converters were notably younger than both early- and late-converters ( Figure 1—figure supplement 1C ) . A genomic DNA-based TCRβ sequence dataset of memory CD4 T cells isolated from peripheral blood was generated from a cohort of 33 healthy vaccinees ( see Materials and methods for details ) right before vaccination ( day 0 ) and 60 days after administration of the first dose of HB vaccine ( 30 days after administration of the second vaccine dose ) . Between 4 . 54 × 104 and 3 . 92 × 105 productive TCRβ sequence reads were obtained for each vaccinee at each time point ( Figure 2—figure supplement 1A ) . Between 30 , 000 and 90 , 000 unique TCRβ sequences were sequenced for each vaccinee at each time point ( Figure 2—figure supplement 1B ) . As expected , considering the extremely diverse memory CD4 T cell repertoire ( Klarenbeek et al . , 2010 ) , less than 20% of the TCRβ sequences is shared between the time points for each vaccinee ( Figure 2—figure supplement 1C ) . The diversity of the memory CD4 T cell repertoire of each vaccinee at the two time points was explored , but neither the breadth of the memory CD4 TCRβ repertoire nor the Shannon equitability index was found to have been impacted by the vaccine at day 60 ( Figure 2A ) . Peripheral blood mononuclear cells from day 60 were labeled with carboxyfluorescein succinimidyl ester ( CFSE ) , a dye that enables tracking of cell proliferation , and stimulated with a pool of peptides spanning HB surface antigen ( HBsAg ) . After day 7 of in vitro expansion , we sorted CFSElow CD4 T cells ( Becattini et al . , 2015 ) and extracted mRNA for quantitative assessment of HBsAg-specific TCRβ clonotypes by sequencing ( see Materials and methods for details ) . The establishment of a set of vaccine-specific TCRs enables their tracking within memory CD4 T cell repertoires from day 0 to day 60 , based on their CDR3β amino acid sequences . We detected a significant increase in the breadth of HBsAg-specific TCRβ sequences at day 60 post-vaccination compared to pre-vaccination ( mean increase = 107 . 9% , 95% CI = 62 . 2–358 . 5% ) ( Figure 2B and Figure 2—figure supplement 1D ) . This increase far exceeded a baseline control of varicella-zoster virus ( VZV ) -specific TCRβ sequences established in an identical manner ( mean difference = 2 . 1% , 95% CI = −6 . 6% to 12 . 4% ) . The HBsAg-specific increase was found to be significant when compared to this VZV baseline ( Wilcoxon p-value 6 . 3e-05 ) . When considered across the different groups , the increase was found to be significantly different from the VZV baseline for the early-converters ( mean = 151 . 9% , 95% CI = 78 . 9–342 . 0% , Wilcoxon Bonferroni-corrected p-value 8 . 64e-5 ) and non-converters ( mean = 67 . 6% , 95% CI: 37 . 6–89 . 7% , Wilcoxon Bonferroni-corrected p-value 0 . 03 ) , but not for the late-converters ( mean = 18 . 8% , 95% CI = 3 . 6–41 . 8% , Wilcoxon Bonferroni-corrected p-value 0 . 257 ) . As HBsAg-specific TCRβ sequences were already detected in the memory CD4 T cell repertoire prior to vaccination , we sought to determine whether the vaccination induced an expansion of those sequences . Based on the frequency of vaccine-specific TCRβ sequences within the memory CD4 T cell repertoire , the data does not support a vaccine-induced expansion of preexisting vaccine-specific TCRβ sequences ( Figure 2—figure supplement 1E ) . Thus , although we see a rise in vaccine-specific TCRβ T cells from day 0 to day 60 , this cannot be attributed to an expansion of the vaccine-specific TCRβ clonotypes found at day 0 but rather the recruitment of new TCRβ clonotypes , as visualized for one vaccinee in Figure 2C . It makes sense to not only look at the difference in vaccine-specific TCRβ sequences between time points , but also explore whether there are differences in the proportion of HBsAg-specific clones in the memory repertoire between early-converters , late-converters , and non-converters after vaccination . In this case , to allow for a between-vaccinees comparison ( in contrast to the within-vaccinees time point comparison ) , we calculate the overlap coefficient , where HBsAg-specific sequences in the CD4 T cell memory repertoire are normalized by the number of HBsAg-specific TCRβ found for each vaccinee . From this analysis , it can be concluded that there is a difference in HBsAg-specific TCRβ at day 60 between the three groups ( Figure 2D ) ( ANOVA p-value = 0 . 00238 ) . A Wilcoxon test between early-converters and other vaccinees shows a significant p-value of 0 . 000473 , indicating that early-converters have a higher relative frequency of vaccine-specific TCRβ sequences present in their memory CD4 T cell repertoire at day 60 compared to vaccinees from the two other groups in the cohort . In summary , vaccine-specific TCRβ sequences increased in breadth following vaccination in early-converters and constituted a significantly higher proportion of the memory CD4 T cell compartment post-vaccination . To quantify the T cell response at the level of individual peptides that make up the HBsAg , a peptide matrix designed to cover 54 overlapping peptides of the HBsAg was used to extract peptide-specific T cells using a CD40L/CD154 activation-induced marker ( AIM ) assay ( see Materials and methods for details ) . The top six peptides for each individual were selected for an in vitro peptide-specific CD4 T cell expansion and sorting for TCR sequencing ( Supplementary file 2 and Figure 3—figure supplement 1 ) . In this manner , TCRβ sequences were identified for T cells reactive against 44 single HBsAg peptides . These were not uniformly distributed across the HBsAg amino acid sequence , with the most prominent epitopes covering the regions 1–15 , 129–144 , 149–164 , 161–176 , 181–200 , 213–228 . For each of those regions , more than 10 individuals had a strong T cell response and more than 150 unique TCRβ sequences could be identified ( Figure 3A ) . These peptide-specific TCRβ sequences can be utilized in a peptide-TCR interaction classifier to identify other TCRβ that are likely to react against same HBsAg epitopes , as it has been shown that similar TCRβ sequences tend to target the same epitopes ( De Neuter et al . , 2018; Meysman et al . , 2019 ) . These classifications were integrated into a model which outputs a ratio Rhbs , which represents the amount of HBsAg epitope-specific TCR sequences in an individual repertoire . The ratio is equal to the breadth of unique predicted HBsAg peptide-specific TCRβ divided by a normalization term for putative false positive predictions due to bystander activations in the training data set . The memory repertoire at day 60 shows that early-converters tend to have a higher breadth of putative HBsAg peptide-specific TCRβ , while late-converters tend to have relatively more putative false positives as per the normalization term ( Figure 3B ) . The ratio of these two terms Rhbs therefore shows a significant difference between early- and the late-converters at day 60 ( one-sided Wilcoxon-test p-value = 0 . 0313 , Figure 3C ) . Furthermore , searching for HBsAg peptide-specific clonotypes in the memory repertoires prior to vaccination ( day 0 ) results in a Rhbs with a similar difference ( one-sided Wilcoxon-test p-value = 0 . 0010 , Figure 3D ) . In this manner , the presence of HBsAg peptide-specific clonotypes as defined by the ratio Rhbs can be used as a classifier to distinguish early- from late-converters prior to vaccination ( Figure 3E ) , with an area under the curve ( AUC ) of 0 . 825 ( 95% CI: 0 . 657–0 . 994 ) in a leave-one-out cross-validation setting . A model in which age-matched vaccinees were included from early- and late-converters returned a similar receiver operating characteristic ( ROC ) curve , suggesting that this signal is not age-dependent ( Figure 3F ) . While Rhbs is able to differentiate between early- and late-converters , it seems to be worse at distinguishing non-converters . This is mainly due to a single non-converter vaccinee ( H21 ) with a high Rhbs , signifying a high number of putative HBsAg peptide-specific TCRβ in their memory repertoire . After showing evidence for the existence of vaccine-specific TCRβ sequences pre-vaccination and that individuals with a higher number of HBsAg peptide-specific clonotypes had earlier seroconversion , we attempted to link this observation to differences in vaccine-specific CD4 T cells responses using CD4 T cell assays . As TREG cells might suppress vaccine-induced immune responses ( Brezar et al . , 2016 ) , we used activation markers CD40L ( CD154 ) and 4-1BB ( CD137 ) to help delineate the conventional ( TCON ) and regulatory ( TREG ) phenotypes of activated CD4 T cells . In this scheme , after 6 hr of antigen stimulation , CD40L+4-1BB− can be used as a signature for antigen-specific CD4 TCON cells , as opposed to CD40L−4-1BB+ signature for antigen-specific CD4 TREG cells ( Elias et al . , 2020; Schoenbrunn et al . , 2012 ) . Additionally , we added CD25 and CD127 to better identify TREG cells ( Liu et al . , 2006; Seddiki et al . , 2006 ) and CXCR5 to further distinguish circulatory T follicular helper cells ( cTFH ) and circulatory T follicular regulatory cells ( cTFR ) ( Bentebibel et al . , 2011; Fonseca et al . , 2017 ) ( see Figure 4—figure supplement 1 for gating strategy ) . Using the converse expression of CD40L and 4-1BB , CD40L+4-1BB− and CD40L−4-1BB+ CD4 T cells have a CD25lowCD127high and CD25highCD127low phenotype , respectively ( Figure 4—figure supplement 2 ) , and validate their use for the distinction of activated TCON and TREG cells as described before ( Schoenbrunn et al . , 2012 ) . We detected a significant increase in the frequency of vaccine-specific CD40L+4-1BB− and CD40L−4-1BB+ memory CD4 T cells at day 60 in our cohort ( Figure 4A ) that correlated positively with the increase in antibody titer between day 0 and day 365 ( Figure 4B , Figure 4—figure supplement 3 ) . Upon a closer look , the induction of both signatures of vaccine-specific memory CD4 T cells was only true for early-converters ( Figure 4C , see Figure 4—figure supplement 4A for non-converters and Figure 4—figure supplement 4B for vaccine-specific CD4 T cells ) . Late-converters did not show a detectable memory CD4 T cell response . Although a subset of both early- and late-converters had detectable memory CD4 T cell responses prior to vaccination , we observed no significant differences in the frequencies of CD40L+4-1BB− and CD40L−4-1BB+ memory CD4 T cells between the two groups at day 0 ( Figure 4D ) . Collectively , flow cytometry data reveal that the expression of CD40L and 4-1BB in our ex vivo assay is consistent with our serological data and reflects the lack of seroconversion at day 60 in late-converters . However , it does not support the existence of more vaccine-specific memory CD4 T cells in early-converters prior to vaccination . Response groups used so far were established based on the dynamics of anti-HBs titers following vaccination . However , response groups can be defined based on the data of antigen specificity from the ex vivo CD4 T cell assay . Thus the frequency of CD40L+4-1BB− and CD40L−4-1BB+ memory CD4 T cells were used to define a low and high response group at three different times points ( days 60 , 180 , and 365 ) . For each time point , the same Rhbs metric was used in a leave-one-out cross-validation as before to differentiate between these novel response group definitions . Results indicate that the Rhbs metric is a good predictor for HBsAg-specific memory CD4 T cells with a TCON signature ( but not TREG signature ) identified at day 60 post-vaccination ( Figure 4E and F ) . However , the classifier is less performant for the prediction of CD4 T cell response at later time points . In order to detect any distinct signatures of early- and late-converters , we analyzed pre-vaccination flow cytometry data to examine major CD4 T cell subsets: TH , TREG , cTFH , and cTFR cells . Using manual gating in which regulatory T cells ( TREG ) were defined as viable CD3+CD4+CD8−CD25+CD127−CXCR5− and were further divided into CD45RA+ and CD45RA− TREG cells , we identified a significantly higher frequency of 4-1BB+ CD45RA− TREG cells in late-converters compared to early-converters ( Figure 5A and Figure 5—figure supplement 1 ) . TREG cells showed higher 4-1BB expression compared to TH , cTFH , and cTFR cells ( Figure 5B ) and within TREG subset , CD45RA− TREG cells showed significantly higher expression of 4-1BB , accompanied with a higher expression of CD25 , compared to CD45RA+ TREG cells ( Figure 5C ) . In this scheme , CD45RA− TREG can be divided into 4-1BB+CD25high and 4-1BB-CD25int subsets . It is worth noting here that no differences were detected in the frequency of CD45RA− or CD45RA+ TREG cells within CD4 T cell compartment between the two groups ( Figure 5D ) , and that it is the composition of TREG compartment that is distinct between the two groups ( Figure 5E ) . In summary , an expanded subset of 4-1BB+CD45RA− TREG cells pre-vaccination is a prominent feature of a delayed and modest immune response to HB vaccine in our cohort .
In this study , we used high-throughput TCRβ repertoire profiling and ex vivo T cell assays to characterize memory CD4 T cell repertoires before and after immunization with HB vaccine , an adjuvanted subunit vaccine , and tracked vaccine-specific TCRβ clonotypes over two time points . As antigen-naïve adults were found to have an unexpected abundance of memory-phenotype CD4 T cells specific to viral antigens ( Su and Davis , 2013; Su et al . , 2013 ) , we sought to investigate the influence that preexisting memory CD4 T cells can have on vaccine-induced immunity . Commercially available HBV vaccines produce a robust and long-lasting anti-HBs response , and protection is provided by induction of an anti-HBs ( antibody against HBV surface antigen ) titer higher than 10 mIU/ml after a complete immunization schedule of three doses ( Meireles et al . , 2015 ) . However , 5–10% of healthy adult vaccinees fail to produce protective titers of anti-HBs and can be classified as non-responders ( Meireles et al . , 2015 ) . In our cohort , 13 vaccinees did not seroconvert by day 60 ( 30 days following administration of the second vaccine dose ) , as determined by antibody titer . Out of this group , nine vaccinees seroconverted by day 180 or day 365 , referred to here as late-converters , and four vaccinees did not seroconvert , referred to here as non-converters . A hallmark of adaptive immunity is a potential for memory immune responses to increase in both magnitude and quality upon repeated exposure to the antigen ( Sallusto et al . , 2010 ) . Our systems immunology data supports the theory that preexisting memory CD4 T cell TCRβ sequences specific to HBsAg , the antigenic component of the current HB vaccine , predict which individuals will mount an early and more vigorous immune response to the vaccine as evidenced by a higher fold change in anti-HBs antibody titer and a more significant induction of antigen-specific CD4 T cells . It is postulated that preexisting memory CD4 T cell clonotypes are generated due to the highly degenerate nature of T cell recognition of antigen/MHC and are cross-reactive to environmental antigens ( Sewell , 2012 ) . For example , preexisting memory CD4 T cells are well-established in unexposed HIV-seronegative individuals , although at a significantly lower magnitude than HIV-exposed seronegative individuals ( Campion et al . , 2014; Ritchie et al . , 2011 ) , and were likely primed by exposure to environmental triggers or the human microbiome . We and others have shown before that the TCRβ repertoire of CD4 T cells encodes the antigen exposure history of each individual and that antigen-specific TCRβ sequences could serve to automatically annotate the infection or exposure history ( DeWitt et al . , 2018; Emerson et al . , 2017; De Neuter et al . , 2019 ) . In this study , we show that similar principles can be used to study vaccine responsiveness . Specifically , the recruitment of novel vaccine-specific T cell clonotypes into memory compartment following vaccination can be tracked by examining the CD4 memory TCRβ repertoire over time . While we observed no increase in the frequency of the vaccine-specific memory T cells , as the time point may have missed the peak of the clonal expansion of effector CD4 T cells as was reported before ( Blom et al . , 2013; Kohler et al . , 2012; Pogorelyy et al . , 2018 ) , a significant rise in the number of unique vaccine-specific T cell clonotypes was detected . This observation is consistent with earlier studies of T cell immune repertoire that showed that antigen-specific TCRβ sequences do not always overlap with those sequences that increase in frequency after infection or vaccination ( DeWitt et al . , 2015 ) . More interestingly , individuals with the earlier and more robust response against the vaccine had a telltale antigen-specific signature in their memory TCRβ repertoire prior to vaccination , despite the lack of HBsAg antibodies and prior vaccination history . Detection of this vaccine-specific signature was possible due to the development of a novel predictive model that used epitope-specific TCRβ sequences from one set of individuals to make predictions about another . This is a non-trivial task as the MHC class II molecules vary between vaccinees , which in turn allows for great variation of the presented epitopes . However , we were able to cover the entire HBsAg and obtained a sufficient sample size to likely cover the most immunoprevalent epitopes . It can be presumed that we do not capture the full HBsAg T cell response , but obtain enough sequences which are representative for the response as a whole . In addition , a correction factor was needed to account for the occurrence of bystander-activated T cells within the original epitope-specific TCRβ sequences . Indeed , in those vaccinees without an early seroconversion ( at day 60 ) , putative vaccine-specific T cells might be induced due to bystander activation . This was supported by predictions using the TCRex tool ( Gielis et al . , 2019 ) , which matched these TCR sequences to common viral or other epitopes . It is of note that these TCRβ sequences are matched with CD8 T cell epitopes , while they originate from isolated CD4 T cells . This is likely due to the great similarity between the TCRβ sequences of CD4 and CD8 T cells as noted in prior research ( De Neuter et al . , 2018 ) . However , our in vitro antigen-specific data , using an assay that enables discrimination of TCON and TREG cells using the converse expression of the activation markers CD40L and 4-1BB ( Frentsch et al . , 2005; Schoenbrunn et al . , 2012 ) , failed to show a significant difference in preexisting antigen-specific CD4 T cells between early- and late-converters prior to vaccine administration . It is plausible that our activation proteins , CD40L and 4-1BB , might be unsuitable to detect preexisting memory CD4 T cells but this is unlikely as both proteins were used successfully in similar studies ( Bacher et al . , 2014a; Bacher et al . , 2014b ) . Another plausible explanation is that the signal is below the detection limit of the assay and that more sensitive techniques that require pre-enrichment of CD40L+ and 4-1BB+ T cells ( using magnetic beads ) ( Bacher et al . , 2013 ) or cultured ELISpot assay ( Reece et al . , 2004 ) are needed to capture preexisting vaccine-specific memory CD4 T cells directly from human peripheral blood . A similar disagreement between B cell receptor clonotype diversity underlying vaccine-induced response and a conventional B cell ELISpot assay was reported before following HB vaccination ( Galson et al . , 2016 ) . TREG cells represent about 5–10% of human CD4 T cell compartment and are identified by the constitutive surface expression of CD25 , also known as IL-2 receptor α subunit ( IL-2Ra ) , and the nuclear expression of forkhead family transcription factor 3 ( Foxp3 ) , a lineage specification factor of TREG cells ( Rudensky , 2011 ) . Regulatory memory T cells play a role in the mitigation of tissue damage induced by effector memory T cells during protective immune responses , resulting in a selective advantage against pathogen-induced immunopathology ( Garner-Spitzer et al . , 2013; Lanteri et al . , 2009; Lin et al . , 2018; Lovelace and Maecker , 2018 ) . Several studies have identified CD4 TREG cells with specificity to pathogen-derived peptides in murine models and showed evidence for an induced expansion of TREG cells followed by an emergence and a long-term persistence of TREG cells with a memory phenotype and potent immunosuppressive properties ( Lin et al . , 2018; Sanchez et al . , 2012 ) . Blom et al . reported a significant and transient activation of TREG cells ( identified by upregulation of CD38 and Ki67 ) in humans 10 days after administration of live attenuated yellow fever virus 17D vaccine ( Blom et al . , 2013 ) . The induction of vaccine-specific TREG cells in our cohort is unexpected and the role it might play in vaccine-induced immunity warrants further investigation . The association of an expanded 4-1BB+ CD45RA− TREG subset with a delayed immune response to HB vaccine was not described before . Miyara et al . showed that blood contains two distinct subsets of stable and suppressive TREG cells: resting TREG , identified as FOXP3lowCD45RA+ CD4 T cells , and activated TREG , identified as FOXP3highCD45RA− CD4 T cells . They further noted that activated TREG cells constitute a minority subset within cord blood TREG cells and increase gradually with age ( Miyara et al . , 2009 ) . As activated TREG cells were shown to have an increased expression of proteins indicative of activation , including ICOS and HLA-DR ( Booth et al . , 2010; Ito et al . , 2008; Mason et al . , 2015; Miyara et al . , 2009; Mohr et al . , 2018 ) , it might be the case that an upregulation of 4-1BB is one more feature of this population or a subset thereof . Moreover , TREG cells in mice were shown to modulate TFH formation and germinal center ( GC ) B cell responses and to diminish antibody production in a CTLA-4 mediated suppression ( Wing et al . , 2014 ) . Interestingly , CD45RA− TREG cells were shown to be more rich in preformed CTLA-4 stored in intracellular vesicles compared to CD45RA+ TREG cells ( Miyara et al . , 2009 ) . 4-1BB was shown to be constitutively expressed by TREG cells ( McHugh et al . , 2002 ) and that 4-1BB+ TREG cells are functionally superior to 4-1BB− TREG cells in both contact-dependent and contact-independent immunosuppression ( Kachapati et al . , 2012 ) . 4-1BB+ TREG cells are the major producers of the alternatively spliced and soluble isoform of 4-1BB among T cells ( Kachapati et al . , 2012 ) . 4-1BB was shown before to be preferentially expressed on TREG cells compared with other non-regulatory CD4 T cell subsets ( McHugh et al . , 2002 ) and that 4-1BB-costimualtion induces the expansion of TREG cells both in vitro and in vivo ( Zheng et al . , 2004 ) . Moreover , agonistic anti-4-1BB mAbs have been shown to abrogate T cell-dependent antibody responses in vivo ( Mittler et al . , 1999 ) and to ameliorate experimental autoimmune encephalomyelitis by skewing the balance against TH17 differentiation in favor of TREG differentiation ( Kim et al . , 2011 ) . It is plausible that the expansion 4-1BB+CD45RA− TREG cells in late-converters is involved in the suppression of GC vaccine-specific TFH cells and the ensuing antibody response in our cohort , but this remains speculative and further research is warranted . It is enticing to speculate that the preexisting memory CD4 T cells result from the complex interplay between cellular immunity and the human microbiome . A role for the microbiota in modulating immunity to viral infection was suggested in 1960s ( Robinson and Pfeiffer , 2014 ) , and since then we gained better understanding of the impact of the various components of the microbiota including bacteria , fungi , protozoa , archaea , and viruses on the murine and human immune systems ( Winkler and Thackray , 2019 ) . Viral clearance of HB virus infection depends on the age of exposure and neonates and young children are less likely to spontaneously clear the virus ( Yuen et al . , 2018 ) . Han-Hsuan et al . have shown evidence in mice that this age dependency is mediated by gut microbiota that prepare the liver immunity system to clear HBV , possibly via a TLR4 signaling pathway ( Chou et al . , 2015 ) . In this study , young mice that have not reached an equilibrium in the gut microbiota exhibited prolonged HBsAg persistence , impaired anti-HBs antibody production , and limited Hepatitis B core antigen ( HBcAg ) -specific IFNγ+ splenocytes . More recently , Tingxin et al . provided evidence for a critical role of the commensal microbiota in supporting the differentiation of GC B cells , through follicular T helper ( TFH ) cells , to promote the anti-HBV humoral immunity ( Wu et al . , 2019 ) . Our study bears some intrinsic limitations . A major drawback is the restricted number of days at which TCRβ repertoire was profiled , as vaccine-specific perturbations within the repertoire may occur at different time points for early- , late- , and non-converters . Additionally , more in-depth characterization and functional studies on 4-1BB+CD45RA− TREG cells could have helped shed more light on the role they play in vaccine-induced immunity . Future studies in larger cohorts and with a more comprehensive TCRβ repertoire profiling and CD4 T cells immunophenotyping are required to validate our findings . In conclusion , our analysis of the memory CD4 T cell repertoire has uncovered a role for preexisting memory CD4 T cells in naïve individuals in mounting an earlier and more vigorous immune response to HB vaccine and argue for the utility of pre-vaccination TCRβ repertoire in the prediction of vaccine-induced immunity . Moreover , we identify a subset of 4-1BB+ memory TREG cells that is expanded in individuals with delayed immune response to the vaccine , which might further explain the heterogeneity of response to HB vaccine .
A total of 34 healthy individuals ( 20-29 years: 10 , 30-39 years: 7 , 40-49 years: 16 , 50+ years: 1 ) without a history of HBV infection or previous HB vaccination were recruited in this study after obtaining written informed consent . Individuals were vaccinated with an HB vaccine by intramuscular ( m . deltoideus ) injection ( Engerix-B containing 20 μg dose of alum-adjuvanted HBsAg , GlaxoSmithKline ) on days 0 and 30 ( and on day 365 ) . At days 0 ( pre-vaccination ) , 60 , 180 , and 365 ( Figure 1A ) , peripheral blood samples were collected on spray-coated lithium heparin tubes , spray-coated K2EDTA ( dipotassium ethylenediamine tetra-acetic acid ) tubes , and serum tubes ( Becton Dickinson , NJ ) . Peripheral blood mononuclear cells ( PBMCs ) were isolated by Ficoll-Paque Plus gradient separation ( GE Healthcare , Chicago , IL ) . Cells were stored in 10% dimethyl sulfoxide in fetal bovine serum ( Thermo Fisher Scientific , Waltham , MA ) . After thawing and washing cryopreserved PBMC , cells were cultured in AIM-V medium that contained L-glutamine , streptomycin sulfate at 50 µg/ml , and gentamicin sulfate at 10 µg/ml ( Thermo Fisher Scientific , Waltham , MA ) and supplemented with 5% human serum ( One Lambda , Canoga Park , CA ) . Serum was separated and stored immediately at – 80°C until time of analysis . Anti-HBs antibody was titrated in serum from day 0 , 60 , 180 , and 365 using Roche Elecsys Anti-HBs antibody assay on an Elecsys 2010 analyzer ( Roche , Basel , Switzerland ) . An anti-HBs titer above 10 IU/ml was considered protective ( Keating and Noble , 2003 ) . Serum IgG antibodies to CMV , EBV viral-capsid antigen , and HSV-1 and -2 were determined using commercially available sandwich ELISA kits in accordance with the manufacturer’s instructions . A complete blood count including leukocyte differential was run on a hematology analyzer ( ABX MICROS 60 , Horiba , Kyoto , Japan ) . Total CD4 T cells were isolated by positive selection using CD4 magnetic microbeads ( Miltenyi Biotech , Bergisch Gladbach , Germany ) . Memory CD4 T cells were sorted after gating on single viable CD3+CD4+CD8−CD45RO+ cells . The following fluorochrome-labeled monoclonal antibodies were used for staining: CD3-PerCP ( BW264/56 ) ( Miltenyi Biotech ) , CD4-APC ( RPA-T4 ) , and CD45RO-PE ( UCHT1 ) ( both from Becton Dickinson , Franklin Lakes , NJ ) and CD8-Pacific Orange ( 3B5 ) ( from Thermo Fisher Scientific , Waltham , MA ) . Cells were stained at room temperature for 20 min and sorted with FACSAria II ( Becton Dickinson , Franklin Lakes , NJ ) . Sytox blue ( Thermo Fisher Scientific , Waltham , MA ) was used to exclude non-viable cells . A set of 15-mers peptides with an 11-amino acid overlap spanning the 226 amino acids along the small S protein of HBsAg , also designated as small HBs ( Shouval , 2003 ) , were synthesized by JPT Peptide Technologies ( Berlin , Germany ) . The set , composed of 54 single peptides ( see Supplementary file 1 ) , was used in a matrix-based strategy to map epitopes against which the immune response is directed as described before ( Precopio et al . , 2008 ) . The matrix layout enables efficient identification of epitopes within the antigen using a minimal number of cells . For this purpose , a matrix of 15 pools , 7 rows , and 8 columns , referred to as peptide matrix , was designed so that each peptide is in exactly one row-pool and one column-pool , thereby allowing for the identification of positive peptides at the intersection of positive pools . Matrix pools that induced a CD4 T cell response ( as determined by CD40L/CD154 assay described below ) which meets the threshold criteria for a positive response were considered in the deconvolution process . Top six single peptides were considered for peptide-specific T cell expansion and sorting . A master peptide pool is composed of all of the 54 single peptides and was used to identify and sort total vaccine-specific CD4 T cells . Each peptide was used at a final concentration of 2 µg/ml . VZV lysate was purchased from Microbix Biosystem ( Mississauga , Canada ) . Thawed PBMCs from each vaccinee were cultured in AIM-V medium that contained L-glutamine , streptomycin sulfate at 50 µg/ml , and gentamicin sulfate at 10 µg/ml ( GIBCO , Grand Island , NY ) and supplemented with 5% human serum ( One Lambda , Canoga Park , CA ) . Cells were stimulated for 6 hr with 2 μg/ml of each of the 15 peptide matrix pools in the presence of 1 µg/ml anti-CD40 antibody ( HB14 ) ( purchased from Miltenyi Biotec , Bergisch Gladbach , Germany ) and 1 μg/ml anti-CD28 antibody ( CD28 . 2 ) ( purchased from BD Biosciences , Franklin Lakes , NJ ) . Cells were stained using the following fluorochrome-labeled monoclonal antibodies: CD3-PerCP ( BW264/56 ) , CD4-APC ( REA623 ) , CD8-VioGreen ( REA734 ) , and CD40L-PE ( 5C8 ) ( purchased from Miltenyi Biotec , Bergisch Gladbach , Germany ) . Viability dye Sytox blue from Invitrogen ( Thermo Fisher Scientific , Waltham , MA ) was used to exclude non-viable cells . Data was acquired on FACSAria II using Diva Software , both from BD Biosciences ( Franklin Lakes , NJ ) , and analyzed on FlowJo software version 10 . 5 . 3 ( Tree Star , Inc , Ashland , OR ) . Fluorescence-minus-one controls were performed in pilot studies . Gates for CD40L+CD4 T cells were set using cells left unstimulated . Thawed PBMCs were labeled with CFSE ( Invitrogen , Carlsbad , CA ) and cultured in AIM-V medium that contained L-glutamine , streptomycin sulfate at 50 µg/ml , and gentamicin sulfate at 10 µg/ml ( GIBCO , Grand Island , NY ) and supplemented with 5% human serum ( One Lambda , Canoga Park , CA ) . Cells were stimulated for 7 days with 2 µg/ml of selected single peptides in addition to the master peptides pool . Cells were also stimulated with 4 µg/ml of a VZV lysate and used as a baseline control . Cells were stained using the following fluorochrome-labeled monoclonal antibodies: CD3-PerCP ( BW264/56 ) , CD4-APC ( REA623 ) , and CD8-VioGreen ( REA734 ) ( purchased from Miltenyi Biotec , Bergisch Gladbach , Germany ) . Viability dye Sytox blue from Invitrogen ( Thermo Fisher Scientific , Waltham , MA ) was used to exclude non-viable cells . Single viable CFSElow CD3+ CD8− CD4+ T cells were sorted into 96-well PCR plates containing DNA/RNA Shield ( Zymo Research , Irvine , CA ) using FACSAria II and Diva Software ( BD Biosciences , Franklin Lakes , NJ ) . For each of the selected single peptides , 500 cells were sorted in two technical replicates . For the master peptide pool and VZV lysate , 1000 cells were sorted in two technical replicates . Plates were immediately centrifuged and kept at –20°C before TCR cDNA library preparation and sequencing . DNA was extracted from sorted memory CD4 T cells using Quick-DNA Microprep kit ( Zymo Research , Irvine , CA ) . ImmunoSEQ hsTCRB sequencing kit ( Adaptive Biotechnologies , Seattle , WA ) was used to profile TCRβ repertoire following the manufacturer’s protocol . After quality control using Fragment Analyzer ( Agilent , Santa Clara , CA ) , libraries were pooled with equal volumes . The concentration of the final pool was measured with the Qubit dsDNA HS Assay kit ( Thermo Fisher Scientific , Waltham , MA ) . The final pool was processed to be sequenced on the Miseq and NextSeq platforms ( Illumina , San Diego , CA ) . Memory CD4 T cells of one of the vaccinees ( H42 , a non-converter ) was not sequenced due to a capacity issue . RNA was extracted from each of the two technical replicates of sorted CFSElow CD4 T cells using Quick-RNA Microprep kit ( Zymo Research , Irvine , CA ) . Without measuring the resulting RNA concentration , an RNA-based library preparation was used . The QIAseq Immune Repertoire RNA Library kit ( Qiagen , Venlo , The Netherlands ) amplifies TCRα , -β , -γ , and -δ chains . After quality control using Fragment Analyzer ( Agilent , Santa Clara , CA ) , concentration was measured with the Qubit dsDNA HS Assay kit ( Thermo Fisher Scientific , Waltham , MA ) and pools were equimolarly pooled and prepared for sequencing on the NextSeq platform ( Illumina , San Diego , CA ) . TCRβ clonotypes were identified as previously described ( De Neuter et al . , 2019 ) where a unique TCRβ clonotype is defined as a unique combination of a V gene , CDR3 amino acid sequence , and J gene . All memory CD4 T cell DNA-based TCRβ sequencing reads were annotated using the immunoSEQ analyzer ( v2 ) from Adaptive Biotechnologies . All small bulk RNA-based TCR sequencing reads were annotated using the MiXCR tool ( v3 . 0 . 7 ) from the FASTQ files . As all RNA-based TCR sequencing experiments featured two technical replicates , only those TCR sequences that occurred in both replicates were retained and their counts were summed . Tracking of vaccine-specific TCRβ clonotypes is based on exact TCRβ CDR3 amino acid matches to remove any bias introduced by the different VDJ annotation pipelines . Non-HBsAg TCR annotations were done with the TCRex web tool ( Gielis et al . , 2019 ) on the July 24 , 2019 , using version 0 . 3 . 0 . Breadth of the TCR sequences is defined as the number of unique TCR clonotypes belonging to a given set , divided by the total number of unique clonotypes in a repertoire . Inference of similar epitope binding between two TCR sequences is defined according to the Hamming distance ( d ) calculated on the CDR3 amino acid sequence with a cutoff c = 1 , as supported by prior research where it was shown that it was equivalent to the performance of more complex methods such as TCRdist ( Dash et al . , 2017 ) or k-mer clustering when applied to TCRβ chains only ( De Neuter et al . , 2018; Valkiers et al . , 2021 ) . All scripts used in this analysis are available via GitHub ( https://github . com/pmeysman/HepBTCR , copy archived at swh:1:rev:bdda21dde671ac2e424e85bd270efafa719d4cb4 , Meysman , 2022 ) . From the single peptide data generated in the epitope mapping experiments , we aimed to create a predictive model to enumerate the HBs response from full TCRβ repertoire data . This approach allows for predictions that are epitope-specific rather than simply vaccine-specific . This model was applied in a leave-one-out cross-validation so that vaccine-specific TCRβ sequences from a vaccinee are not used to make predictions for the same vaccinee . While the predictive model is derived from epitope-specific data , it cannot be guaranteed that some of the expanded CD4 T cells detected in the in vitro assay are not due to bystander activation . Vaccine-specific TCRβ sequences of vaccinees who did not respond to the vaccine at day 60 ( late-converters and non-converters ) are expected to be more enriched in cells triggered to expand due to bystander activation . Indeed , running the set of vaccine-specific TCRβ sequences through the TCRex webtool ( Gielis et al . , 2019 ) reveals that several TCRs are predicted to be highly similar to those reactive to the CMV NLVPMVATV epitope ( enrichment p-value < 0 . 001 when compared to the TCRex background repertoire ) and the Mart-1 variant ELAGIGILTV epitope ( p-value < 0 . 001 ) , which supports the notion that some of these TCRβ sequences might not be specific to HBsAg . This set of vaccine-specific TCRβ sequences can thus be used to make predictions about possible TCRβ sequences due to bystander activation of CD4 T cells , that is , common TCRβ sequences that might be present as false positives . The final output of the model is thus a ratio , Rhbs , for any repertoire repi describing a set of TCRβ sequences trepi:Rhbs ( trepi ) = ∑pep=154x ∈ trepiminy ∈tpep dx , y§amp;lt;c/tpep x ∈trepiminy ∈tbystander dx , y§amp;lt;c/tbystander with tpep as the set of TCRβ sequences occurring in both biological replicates for a single sample and a single peptide ( pep ) from the HBsAg epitope mapping experiment , and tbystander as the set of TCRβ sequences occurring in both biological replicates of the master peptide pool in any of the non-responding samples . Thus , the ratio signifies the number of TCR clonotypes predicted to be reactive against one of the HBsAg peptides , normalized by a count of putative false positive predictions from bystander T cells . Thawed PBMCs from each vaccinee were cultured in AIM-V medium that contained L-glutamine , streptomycin sulfate at 50 µg/ml , and gentamicin sulfate at 10 µg/ml ( GIBCO , Grand Island , NY ) and supplemented with 5% human serum ( One Lambda , Canoga Park , CA ) . Cells were stimulated for 6 hr with 2 μg/ml of a master peptide pool representing the full length of the small surface envelope protein of HB , in the presence of 1 µg/ml anti-CD40 antibody ( HB14 ) ( purchased from Miltenyi Biotec , Bergisch Gladbach , Germany ) and 1 μg/ml anti-CD28 antibody ( CD28 . 2 ) ( purchased from BD Biosciences , Franklin Lakes , NJ ) . Cells were stained using the following fluorochrome-labeled monoclonal antibodies: CD3-BV510 ( SK7 ) , CD4-PerCP/Cy5 . 5 ( RPA-T4 ) , CD8-APC/Cy7 ( SK1 ) , CD45RA-AF488 ( HI100 ) , CD25-BV421 ( M-A251 ) , CD127-BV785 ( A019D5 ) , and CD137-PE ( 4-1BB ) ( purchased from BioLegend , San Diego , CA ) , CXCR5 ( CD185 ) -PE-eFluor 610 ( MU5UBEE ) ( from eBioscience , Thermo Fisher Scientific , Waltham , MA ) and CD40L-APC ( 5C8 ) ( purchased from Miltenyi Biotec , Bergisch Gladbach , Germany ) . Fixable viability dye Zombie NIR from BioLegend ( San Diego , CA ) was used to exclude non-viable cells . Data was acquired on FACSAria II using Diva Software , both from BD Biosciences ( Franklin Lakes , NJ ) , and analyzed on FlowJo software version 10 . 5 . 3 ( Tree Star , Inc , Ashland , OR ) using gating strategy shown in Figure 4—figure supplement 1A . Fluorescence-minus-one controls were performed in pilot studies . Gates for CD40L+ and 4-1BB+ CD4 T cells ( Figure 4—figure supplement 1B ) were set using cells left unstimulated ( negative control contained DMSO at the same concentration used to solve peptide pools ) . In order to account for background expression of CD40L and 4-1BB on CD4 T cells , responses in cells left unstimulated were subtracted from the responses to peptides , and when peptides-specific CD40L+ or 4-1BB+ CD4 T cells were not significantly higher than those detected for cells left unstimulated ( using one-sided Fisher’s exact test ) , values were mutated to zero . The two-sided Fisher’s exact test was used to evaluate the significance of relationship between early/late-converters and CMV , EBV , or HSV seropositivity . For the visualization of marker expression , TCRβ counts and cell frequencies between time points or groups of vaccinees , ggplot2 ( v3 . 3 . 2 ) , ggpubr ( v0 . 2 . 5 ) , and rstatix ( v0 . 7 . 0 ) packages in R were used . The Wilcoxon rank sum test and the Wilcoxon signed-rank test were used to compare two or more groups , with unpaired and paired analysis as necessary . Bonferroni correction was applied when multiple comparisons were made . The nonparametric Spearman’s rank-order correlation was used to test for correlation . We used the following convention for symbols indicating statistical significance; ns p > 0 . 05 , *p ≤ 0 . 05 , **p ≤ 0 . 01 , ***p ≤ 0 . 001 , ****p ≤ 0 . 0001 .
Antigen recognition through the T cell receptor ( TCR ) αβ heterodimer is one of the primary determinants of the adaptive immune response . Vaccines activate naïve T cells with high specificity to expand and differentiate into memory T cells . However , antigen-specific memory CD4 T cells exist in unexposed antigen-naïve hosts . In this study , we use high-throughput sequencing of memory CD4 TCRβ repertoire and machine learning to show that individuals with preexisting vaccine-reactive memory CD4 T cell clonotypes elicited earlier and higher antibody titers and mounted a more robust CD4 T cell response to hepatitis B vaccine . In addition , integration of TCRβ sequence patterns into a hepatitis B epitope-specific annotation model can predict which individuals will have an early and more vigorous vaccine-elicited immunity . Thus , the presence of preexisting memory T cell clonotypes has a significant impact on immunity and can be used to predict immune responses to vaccination .
Immune cells called CD4 T cells help the body build immunity to infections caused by bacteria and viruses , or after vaccination . Receptor proteins on the outside of the cells recognize pathogens , foreign molecules called antigens , or vaccine antigens . Vaccine antigens are usually inactivated bacteria or viruses , or fragments of these pathogens . After recognizing an antigen , CD4 T cells develop into memory CD4 T cells ready to defend against future infections with the pathogen . People who have never been exposed to a pathogen , or have never been vaccinated against it , may nevertheless have preexisting memory cells ready to defend against it . This happens because CD4 T cells can recognize multiple targets , which enables the immune system to be ready to defend against both new and familiar pathogens . Elias , Meysman , Bartholomeus et al . wanted to find out whether having preexisting memory CD4 T cells confers an advantage for vaccine-induced immunity . Thirty-four people who were never exposed to hepatitis B or vaccinated against it participated in the study . These individuals provided blood samples before vaccination , with 2 doses of the hepatitis B vaccine , and at 3 time points afterward . Using next generation immune sequencing and machine learning techniques , Elias et al . analyzed the individuals’ memory CD4 T cells before and after vaccination . The experiments showed that preexisting memory CD4 T cells may determine vaccination outcomes , and people with more preexisting memory cells develop quicker and stronger immunity after vaccination against hepatitis B . This information may help scientists to better understand how people develop immunity to pathogens . It may guide them develop better vaccines or predict who will develop immunity after vaccination .