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Characterization of CD8+ T cell repertoire diversity and persistence in the influenza A virus model of localized, transient infection
Seminars in Immunology 16 (2004) 179–184
Characterization of CD8+ T cell repertoire diversity and persistence in the influenza A virus model of localized, transient infection Stephen J. Turner a,∗ , Katherine Kedzierska a , Nicole L. La Gruta a , Richard Webby b , Peter C. Doherty a,c a b
Department of Microbiology and Immunology, University of Melbourne, Parkville, Vic. 3010, Australia Department of Infectious Diseases, St. Jude Children’s Research Hospital, Memphis, TN 38105, Australia c Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, Australia
Abstract Influenza virus infection of C57BL/6 mice provides a well-characterized model for the study of acute CD8+ T cell responses and for the analysis of memory in the absence of antigen persistence. The advent of tetramer reagents and intracellular cytokine staining, coupled with techniques such as single cell RT–PCR and influenza reverse genetics, has enabled the detailed molecular dissection of different epitope-specific primary, memory and secondary immune CD8+ T cell responses. The approach offers novel insights into the factors determining the selection of immune repertoires, and their functional consequences for CD8+ T cell-mediated immunity. © 2004 Elsevier Ltd. All rights reserved. Keywords: CD8+ T cells; Influenza A virus; Repertoire diversity; Reverse genetics; T cell receptor
1. Introduction
2. Influenza A virus infection of B6 mice
The influenza A virus, C57Bl/6J (B6) mouse pneumonia model provides a well-developed experimental system for the analysis of CD8+ T cell repertoires. Technical approaches based on the use of peptide–MHC tetramers and intracellular cytokine staining facilitate the identification, isolation and characterisation of epitope-specific CD8 T cells. The non-persistent, localized nature of influenza A virus infection enables the kinetic comparison of CD8 T cells from different anatomical compartments, such as the regional lymph nodes, the lung and distal lymphoid and non-lymphoid sites. The diversity of this response also allows comparisons both within and between antigen-specific repertoires. The present review summarizes recent experimental analyses of CD8+ T cell repertoires specific for two different influenza virus peptide epitopes. The results establish the T cell repertoires that are expanded after virus infection vary in characteristic ways depending on the specific T cell receptor (TCR)–epitope interactions.
The enveloped influenza A viruses are classified in the orthomyxoviruses and have a segmented, negative sense RNA genome. Respiratory infection of B6 (H2b ) mice causes an acute pneumonia, with the virus being cleared by day 10 after infection. There is no evidence for the persistence of either viral RNA or antigen [1]. Experiments from our laboratory have focused on the A/PR8/34 (PR8, H1N1) and A/HKx31 (HKx31, H3N2) influenza strains, which share the same six internal genes (from PR8) but express different surface hemagglutinin (H) and neuraminidase (NA or N) proteins [2]. As all the influenza peptide epitopes recognized by CD8+ T cells in B6 mice are derived from the internal proteins, prime and challenge experiments with these two viruses allows the analysis secondary CD8+ T cell responses without the possible complication of cross-reactive neutralizing antibody [3–5]. A total of seven different epitopes [6] have been identified for H2Db and H2Kb with the most prominent being derived from the nucleoprotein (NP366–374 , H2Db ) [7,8], the acidic polymerase (PA224–233 , H2Db ) [3] and the basic polymerase subunit 1 (PB1703–711 , H2Kb ) [4]. During primary infection, the magnitude of the CD8+ T cell response to each of these determinants is roughly equivalent [4]. However. the Db NP366 -specific set dominates the
∗ Corresponding
author. Tel.: +61-3-83447968; fax: +61-3-83447990. E-mail address: [email protected] (S.J. Turner).
1044-5323/$ – see front matter © 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.smim.2004.02.005
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response after secondary challenge, constituting up to 80% of the influenza-specific CD8+ population [4,5,9]. The functional and phenotypic differences between Db NP366 - and Db PA224 -specific T cell populations are summarized in the following sections.
3. Functional diversity of influenza-specific T cells Virus-specific CD8+ T cell effector function can be mediated via cytotoxic T lymphocyte (CTL) activity, and/or the expression of cytokines such as interferon-gamma (IFN-␥) and Tumor Necrosis Factor (TNF-␣) [10]. Comparison of these influenza-specific CTLs shows that relatively more of the CD8+ Db PA224 + than the CD8+ Db NP366 + T cells make IFN-␥, TNF-␣ and IL-2 after in vitro peptide stimulation [4] (La Gruta et al., manuscript submitted). This greater functional capacity also correlates with a higher avidity peptide–MHC interaction (La Gruta et al., manuscript submitted). The link between TCR avidity and functional potential could reflect the magnitude of signal strength at the time of initial activation [11], though this is yet to be established. Given that there is diversity, an issue is whether these functionally-defined subsets are dominated by any one particular T cell clone or represent, in fact, a broad range of different T cell clones. This can potentially be approached by analysis of the clonally distributed TCRs in these responding lymphocyte populations.
4. Generation of TCR diversity Antigen specificity is determined by the clonally distributed TCR ␣ heterodimer [12]. Diversification of the TCR repertoire results from the random rearrangement of variable (V), diversity (D) and joining (J) genes for the TCR chain, and V- and J-gene segments for the TCR␣ chain. Regions of hypervariability found within the ␣ and  chains, called complementarity determining regions (CDR), fold in close proximity to each other and form the TCR antigen binding site. The CDR1 and CDR2 regions are encoded within the V-region, whereas the CDR3 region is at the junction of the V and J, and the V, D, and J regions of the ␣ and  chains, respectively. Due to the combinatorial nature of TCR gene rearrangement, imprecise joining and the addition of N-region nucleotides at the junctions of different gene segments, there is skewing of diversity towards the TCR chain CDR3 region. Functional and crystallographic analysis of the interaction between the MHC class I–peptide complex and the TCR indicates that peptide recognition is predominantly mediated via the CDR3 loop [13–16]. Many antigen-specific T cell responses are characterized by restrictions in TCR V-region usage and/or CDR3 loop length [17–19]. As the CDR3 length can influence the interaction of the specific TCR with its cognate MHC/peptide ligand, it can be used as a marker to follow antigen-specific responses.
5. Analysis of TCR repertoires The most common approach for studying antigen-specific T cell repertoires is use a combination of tetramers and TCR-specific antibodies to follow a particular TCRV bias [20,21]. A higher resolution approach is to use RT–PCR to measure the CDR3 length of antigen-specific TCRs [22,23]. This “spectratyping” protocol depends on the fact that the CDR3 lengths of na¨ıve T cells follow a Gaussian distribution [22–24], while antigen-induced selection results in the expansion of TCRs with skewed CDR3 profiles. Spectratyping allows rapid evaluation of antigen-specific TCRs within large T cell pools, but has the dual limitations that the amplification of cDNA from bulk T lymphocyte populations may introduce an element of bias, and that the variation within a particular CDR3 length is not measured. Sequencing the CDR3-region of single antigen-specific T cells overcomes these problems [25]. Single cell analysis also provides an absolute frequency of particular CDR3 usage. It was for these reasons we used the single cell RT–PCR strategy to probe the extent of TCR diversity within both the Db NP366 - and Db PA224 -specific T cell populations.
6. Influenza-specific TCR diversity While both NP366 and PA224 bind to H2Db , they induce different TCRV biases within their respective antigen-specific TCR repertoires. In the case of Db NP366 , approximately 30–50% of specific T cells express TCRBVS3 [5,26,27] (Kedzierska et al., manuscript in preparation), while some 30–60% of the Db PA224 -specific T cells express TCRBV7S1 [26,28]. Closer analysis of the sequence variation within each of these TCR biases shows that there are major differences in the structural composition of each CDR3 loop. The BV7S1 positive PA224–233 -specific T cells have CDR3 loop lengths of 5–7 amino acids and demonstrate a J-region BJ1S1 or BJ2S6 gene bias [28]. The BV8S3 NP366–373 -specific T cells have a longer modal CDR3 length of 9 amino acids and a J-region bias towards usage of the BJ2S2 gene segment [27] (Kedzierska et al., manuscript in preparation).
7. Generation of memory repertoires There are two main hypothesis relating to the relationship of how memory differentiation relates to repertoire diversity. The first is that the extent of TCR diversity is comparable for both primary, memory and secondary repertoires [20,22,23,25] (Fig. 1A). The second is that the antigen-specific TCR repertoire narrows sequentially during the transition from the effector stage through to memory, then narrows further after secondary challenge [21,29,30] (Fig. 1B). Overall, a progressive narrowing in TCR repertoire diversity would suggest that there is preferential se-
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Fig. 1. Shown are models of the evolution of CD8+ T cell repertoire diversity found in the primary, memory and secondary immune compartments. The first model (panel A) demonstrates that repertoire diversity is stable in the primary, memory and secondary CD8+ T cell repertoires. The repertoire selected during the primary response is mirrored in both the memory and secondary repertoires. The second model (panel B) suggests that there is narrowing of the CD8+ T cell repertoire in the transition from the primary response into memory. Upon re-challenge, diversity within the secondary CD8+ T cell repertoire narrows further. Our analysis of both the Db NP366 - and Db PA224 -specific repertories showed that the memory population mirrors the profile of selection in the primary response (panel C). While repertoire diversity is maintained after further challenge, there are alterations in the frequency of particular T cell clones. We hypothesize that this reflects stochastic selection of particular T cell clones from the memory pool.
lection and/or survival of specific T cells, perhaps of higher avidity or higher functional capacity [31,32]. Single cell analysis of the Db PA224 -specific BV7S1 repertoire supports the idea of stability, from the acute response through to long term memory [28]. Longitudinal analysis of primary, memory and secondary repertoires demonstrated that the same level of diversity was observed in each of these compartments. Interestingly, examination of the CDR3 amino acid sequences showed that the memory repertoire mirrored that found at the peak of the primary effector phase. While the extent of TCR diversity did not alter after secondary challenge, there were changes in the frequency of certain TCR signatures. For example, dominant TCRs found in the primary and memory repertoires were not necessarily prominent in the secondary repertoire. In other cases, TCR signatures found at low frequency in the primary and memory repertoires were dominant in the secondary repertoire. A similar phenomenon was observed when longitudinal TCR analysis was performed on the responding BV8S3 Db NP366 -specific CD8+ T cells. Overall, these data suggest that T cells selected during the primary response are stable into memory. While the majority of the secondary repertoire is derived from the circulation pool of antigen-specific CD8+ memory T cells, the
selection and subsequent expansion of a particular T cell following challenge is a stochastic event (Fig. 1C). Previous studies have demonstrated that selection of the primary immune repertoire from low frequency precursors is essentially random [33,34]. The alterations in frequency of particular TCR signatures for both the Db NP366 - and Db PA224 -specific T cells is likely to reflect chance encounter with antigen, rather than specific selection for dominant T cell specificities.
8. Factors determining the selection of “diverse” versus “restricted” repertoires The Db PA224 -specific subset is diverse, with approximately 15–20 different TCR signatures being found for each mouse. These estimates agree with other approximations using different model antigens [25]. Moreover, the Db PA224 -specific TCRs tended to be individual, and are legitimately described as a “private repertoire” [35]. In contrast, the Db NP366 -specific repertoire was more limited in extent, with only 5–10 different TCRs used per individual. Moreover, the Db NP366 -specific set was characterized by repeated TCRs that could be isolated from many mice. Such
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SGGANTGQL AGTGGGGGGGCA AGTGGGGGGGCT AGTGGTGGGGCA AGTGGTGGGGCG AGTGGGGGGGCG AGTGGGGGTGCA AGTGGGGGAGCA
M1 42% 28% 30% ---------
M2 72% ----22% 6% -----
M3 50% 25% ----25% -----
M4 29% ------58% --13%
SGGGNTGQL AGTGGGGGGGGA AGTGGAGGGGGT AGTGGAGGGGGC AGCGGGGGGGGA AGTGGGGGAGGA AGTGGGGGGGGG AGTGGGGGGGGC AGTGGGGGGGGT AGTGGTGGGGGC AGTGGAGGGGGG
M1 50% ------20% 9% 21% -------
M2 50% --------50% ---------
M3 ----20% ----57% ----23% ---
M4 100% -------------------
Fig. 2. The public CDR3 loops isolated from TCRBV8S3+ NP366 -specific CD8+ T cells are encoded by different nucleotide sequences. Shown are the amino acid sequences of the public CDR3 loop that can repeatedly isolated from different individual mice. The same CDR3 loop can be encoded by up to four different nucleotide sequences within the one individual mouse. This suggests that there is a strong selection for an appropriate CDR3 loop that is capable of binding the Db NP366 determinant.
repeat sequences (SGGSNTGQL and SGGANTGQL) were also shown for Db NP366 -specific hybridomas in a previous study [27], and indeed represent a “public” repertoire [35]. The factors that determine the selection of “public” versus “private” repertoires are not clear. The same EBV-specific TCR combination is repeatedly isolated from different individuals expressing HLA-B8 [18]. Interestingly, these EBV-specific T cells are also cross-reactive with the HLA-B4220 alloantigen. People who are both HLA-B8 and B4402 positive no longer express this TCR “public” specificity and in fact have a rather diversified EBV-specific repertoire [36]. Thymic selection may be modifying the diversity of this EBV-specific repertoire. A likely scenario is that “public” repertoires result from the preferential selection of TCRs with the appropriate structural confirmation for antigen recognition [13,14]. Supporting this idea is the fact that the same CDR3 loop amino acid sequence can be encoded by distinct nucleotide sequences [18,36–38]. We analyzed “public” TCR sequences observed for the influenza-specific Db NP366 response and identified up to 10 different nucleotide sequences, with one to four of these being present within any one individual (Fig. 2 and Kedzierska et al., manuscript in preparation). In most cases such variation was a result of N-region diversity. Why the Db NP366 -specific response induces such a “public” TCR repertoire is unclear. Perhaps the answer lies in the rather featureless shape of the Db NP366 epitope (Kedzierska et al., manuscript in preparation), analogous to the “vanilla” peptide of the influenza matrix epitope that binds to HLA-A2 [14].
9. Reverse genetics: a new technique for the manipulation of influenza-specific CD8 T cell responses The use of plasmids for the generation of infectious influenza virions [39] enables the site-directed mutagenesis of particular gene segments, a strategy we have used to dissect the influenza-specific CD8+ T cell responses after infection [40]. Point mutations were made at position 5 in both NP366–374 and PA224–233 , with the consequence that the modified peptides no longer bind H2Db [40]. Infection of mice with these mutant viruses established three important points. 1. There was a clear, protective role for both the Db NP366 and Db PA224 -specific T cell populations during the course of infection. Both single (NP− or PA− ) and double (NP− PA− ) mutant viruses showed increased virulence in Ig−/− mice. This was somewhat of a surprise for the Db PA224 -specific set, as there is evidence that Db PA224 may not be expressed on lung epithelium and would not, therefore, be a predicted target for viral clearance [41]. While the mechanism of protection is yet to be determined, it is clear that selection of epitopes for vaccine strategies needs to be done with care. It may not be sufficient to simply determine whether or not a response is dominant. 2. Influenza epitope-specific CTL responses seem to be regulated independent of each other. The CD8+ Db NP366 + set dominates the influenza-specific secondary response,
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perhaps because these T cells in some way compromise the Db PA224 -specific population. This could reflect down-modulation of the Db PA224 -specific response, either by competition for antigen presenting cells (APCs) or by killing off professional APCs [42]. This seems unlikely, however, as little evidence was found for an increased response to Db PA224 in mice infected with the NP− virus. 3. The reverse genetic system is a powerful technique that allows manipulation of the responding CD8 T cell repertoires. This in turn facilitates the delineation of the relationship between diverse profiles of antigen recognition and the functional consequence of the TCR–epitope interaction.
10. Conclusions Respiratory challenge with the influenza A viruses provides a well-characterized system for the analysis of CD8+ T cell response in a localized, transient infectious process. The model is safe to use in both laboratories and animal facilities, and is readily exploited to explore new questions and technologies. Though it is likely that a great deal remains to be learned about CD8+ T cell response to acute infection, the use of approaches involving mutant viruses, single cell sorting and RT–PCR is providing a spectrum of new findings and insights. The ultimate aim is to exploit such models to identify markers of immunity (functional and molecular) that are appropriates correlates of protective cell-mediated immunity, particularly in humans. We need to understand better, for example, why it is that the CD8 T cell numbers generated after vaccination do not always correlate with the extent of effective protection. The more that is learned about the relationships between the quality of CTL responses and protection, the more rapidly we are likely to proceed with the development of novel vaccine strategies.
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This work is supported by the NH&MRC (Burnet Fellowship awarded to P.C.D.), by USPHS grants AI29579 and CA21765 and by the American Lebanese Syrian Associated Charities (ALSAC).
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Characterization of CD8+ T cell repertoire diversity and persistence in the influenza A virus model of localized, transient infection Stephen J. Turner a,∗ , Katherine Kedzierska a , Nicole L. La Gruta a , Richard Webby b , Peter C. Doherty a,c a b
Department of Microbiology and Immunology, University of Melbourne, Parkville, Vic. 3010, Australia Department of Infectious Diseases, St. Jude Children’s Research Hospital, Memphis, TN 38105, Australia c Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, Australia
Abstract Influenza virus infection of C57BL/6 mice provides a well-characterized model for the study of acute CD8+ T cell responses and for the analysis of memory in the absence of antigen persistence. The advent of tetramer reagents and intracellular cytokine staining, coupled with techniques such as single cell RT–PCR and influenza reverse genetics, has enabled the detailed molecular dissection of different epitope-specific primary, memory and secondary immune CD8+ T cell responses. The approach offers novel insights into the factors determining the selection of immune repertoires, and their functional consequences for CD8+ T cell-mediated immunity. © 2004 Elsevier Ltd. All rights reserved. Keywords: CD8+ T cells; Influenza A virus; Repertoire diversity; Reverse genetics; T cell receptor
1. Introduction
2. Influenza A virus infection of B6 mice
The influenza A virus, C57Bl/6J (B6) mouse pneumonia model provides a well-developed experimental system for the analysis of CD8+ T cell repertoires. Technical approaches based on the use of peptide–MHC tetramers and intracellular cytokine staining facilitate the identification, isolation and characterisation of epitope-specific CD8 T cells. The non-persistent, localized nature of influenza A virus infection enables the kinetic comparison of CD8 T cells from different anatomical compartments, such as the regional lymph nodes, the lung and distal lymphoid and non-lymphoid sites. The diversity of this response also allows comparisons both within and between antigen-specific repertoires. The present review summarizes recent experimental analyses of CD8+ T cell repertoires specific for two different influenza virus peptide epitopes. The results establish the T cell repertoires that are expanded after virus infection vary in characteristic ways depending on the specific T cell receptor (TCR)–epitope interactions.
The enveloped influenza A viruses are classified in the orthomyxoviruses and have a segmented, negative sense RNA genome. Respiratory infection of B6 (H2b ) mice causes an acute pneumonia, with the virus being cleared by day 10 after infection. There is no evidence for the persistence of either viral RNA or antigen [1]. Experiments from our laboratory have focused on the A/PR8/34 (PR8, H1N1) and A/HKx31 (HKx31, H3N2) influenza strains, which share the same six internal genes (from PR8) but express different surface hemagglutinin (H) and neuraminidase (NA or N) proteins [2]. As all the influenza peptide epitopes recognized by CD8+ T cells in B6 mice are derived from the internal proteins, prime and challenge experiments with these two viruses allows the analysis secondary CD8+ T cell responses without the possible complication of cross-reactive neutralizing antibody [3–5]. A total of seven different epitopes [6] have been identified for H2Db and H2Kb with the most prominent being derived from the nucleoprotein (NP366–374 , H2Db ) [7,8], the acidic polymerase (PA224–233 , H2Db ) [3] and the basic polymerase subunit 1 (PB1703–711 , H2Kb ) [4]. During primary infection, the magnitude of the CD8+ T cell response to each of these determinants is roughly equivalent [4]. However. the Db NP366 -specific set dominates the
∗ Corresponding
author. Tel.: +61-3-83447968; fax: +61-3-83447990. E-mail address: [email protected] (S.J. Turner).
1044-5323/$ – see front matter © 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.smim.2004.02.005
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response after secondary challenge, constituting up to 80% of the influenza-specific CD8+ population [4,5,9]. The functional and phenotypic differences between Db NP366 - and Db PA224 -specific T cell populations are summarized in the following sections.
3. Functional diversity of influenza-specific T cells Virus-specific CD8+ T cell effector function can be mediated via cytotoxic T lymphocyte (CTL) activity, and/or the expression of cytokines such as interferon-gamma (IFN-␥) and Tumor Necrosis Factor (TNF-␣) [10]. Comparison of these influenza-specific CTLs shows that relatively more of the CD8+ Db PA224 + than the CD8+ Db NP366 + T cells make IFN-␥, TNF-␣ and IL-2 after in vitro peptide stimulation [4] (La Gruta et al., manuscript submitted). This greater functional capacity also correlates with a higher avidity peptide–MHC interaction (La Gruta et al., manuscript submitted). The link between TCR avidity and functional potential could reflect the magnitude of signal strength at the time of initial activation [11], though this is yet to be established. Given that there is diversity, an issue is whether these functionally-defined subsets are dominated by any one particular T cell clone or represent, in fact, a broad range of different T cell clones. This can potentially be approached by analysis of the clonally distributed TCRs in these responding lymphocyte populations.
4. Generation of TCR diversity Antigen specificity is determined by the clonally distributed TCR ␣ heterodimer [12]. Diversification of the TCR repertoire results from the random rearrangement of variable (V), diversity (D) and joining (J) genes for the TCR chain, and V- and J-gene segments for the TCR␣ chain. Regions of hypervariability found within the ␣ and  chains, called complementarity determining regions (CDR), fold in close proximity to each other and form the TCR antigen binding site. The CDR1 and CDR2 regions are encoded within the V-region, whereas the CDR3 region is at the junction of the V and J, and the V, D, and J regions of the ␣ and  chains, respectively. Due to the combinatorial nature of TCR gene rearrangement, imprecise joining and the addition of N-region nucleotides at the junctions of different gene segments, there is skewing of diversity towards the TCR chain CDR3 region. Functional and crystallographic analysis of the interaction between the MHC class I–peptide complex and the TCR indicates that peptide recognition is predominantly mediated via the CDR3 loop [13–16]. Many antigen-specific T cell responses are characterized by restrictions in TCR V-region usage and/or CDR3 loop length [17–19]. As the CDR3 length can influence the interaction of the specific TCR with its cognate MHC/peptide ligand, it can be used as a marker to follow antigen-specific responses.
5. Analysis of TCR repertoires The most common approach for studying antigen-specific T cell repertoires is use a combination of tetramers and TCR-specific antibodies to follow a particular TCRV bias [20,21]. A higher resolution approach is to use RT–PCR to measure the CDR3 length of antigen-specific TCRs [22,23]. This “spectratyping” protocol depends on the fact that the CDR3 lengths of na¨ıve T cells follow a Gaussian distribution [22–24], while antigen-induced selection results in the expansion of TCRs with skewed CDR3 profiles. Spectratyping allows rapid evaluation of antigen-specific TCRs within large T cell pools, but has the dual limitations that the amplification of cDNA from bulk T lymphocyte populations may introduce an element of bias, and that the variation within a particular CDR3 length is not measured. Sequencing the CDR3-region of single antigen-specific T cells overcomes these problems [25]. Single cell analysis also provides an absolute frequency of particular CDR3 usage. It was for these reasons we used the single cell RT–PCR strategy to probe the extent of TCR diversity within both the Db NP366 - and Db PA224 -specific T cell populations.
6. Influenza-specific TCR diversity While both NP366 and PA224 bind to H2Db , they induce different TCRV biases within their respective antigen-specific TCR repertoires. In the case of Db NP366 , approximately 30–50% of specific T cells express TCRBVS3 [5,26,27] (Kedzierska et al., manuscript in preparation), while some 30–60% of the Db PA224 -specific T cells express TCRBV7S1 [26,28]. Closer analysis of the sequence variation within each of these TCR biases shows that there are major differences in the structural composition of each CDR3 loop. The BV7S1 positive PA224–233 -specific T cells have CDR3 loop lengths of 5–7 amino acids and demonstrate a J-region BJ1S1 or BJ2S6 gene bias [28]. The BV8S3 NP366–373 -specific T cells have a longer modal CDR3 length of 9 amino acids and a J-region bias towards usage of the BJ2S2 gene segment [27] (Kedzierska et al., manuscript in preparation).
7. Generation of memory repertoires There are two main hypothesis relating to the relationship of how memory differentiation relates to repertoire diversity. The first is that the extent of TCR diversity is comparable for both primary, memory and secondary repertoires [20,22,23,25] (Fig. 1A). The second is that the antigen-specific TCR repertoire narrows sequentially during the transition from the effector stage through to memory, then narrows further after secondary challenge [21,29,30] (Fig. 1B). Overall, a progressive narrowing in TCR repertoire diversity would suggest that there is preferential se-
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Fig. 1. Shown are models of the evolution of CD8+ T cell repertoire diversity found in the primary, memory and secondary immune compartments. The first model (panel A) demonstrates that repertoire diversity is stable in the primary, memory and secondary CD8+ T cell repertoires. The repertoire selected during the primary response is mirrored in both the memory and secondary repertoires. The second model (panel B) suggests that there is narrowing of the CD8+ T cell repertoire in the transition from the primary response into memory. Upon re-challenge, diversity within the secondary CD8+ T cell repertoire narrows further. Our analysis of both the Db NP366 - and Db PA224 -specific repertories showed that the memory population mirrors the profile of selection in the primary response (panel C). While repertoire diversity is maintained after further challenge, there are alterations in the frequency of particular T cell clones. We hypothesize that this reflects stochastic selection of particular T cell clones from the memory pool.
lection and/or survival of specific T cells, perhaps of higher avidity or higher functional capacity [31,32]. Single cell analysis of the Db PA224 -specific BV7S1 repertoire supports the idea of stability, from the acute response through to long term memory [28]. Longitudinal analysis of primary, memory and secondary repertoires demonstrated that the same level of diversity was observed in each of these compartments. Interestingly, examination of the CDR3 amino acid sequences showed that the memory repertoire mirrored that found at the peak of the primary effector phase. While the extent of TCR diversity did not alter after secondary challenge, there were changes in the frequency of certain TCR signatures. For example, dominant TCRs found in the primary and memory repertoires were not necessarily prominent in the secondary repertoire. In other cases, TCR signatures found at low frequency in the primary and memory repertoires were dominant in the secondary repertoire. A similar phenomenon was observed when longitudinal TCR analysis was performed on the responding BV8S3 Db NP366 -specific CD8+ T cells. Overall, these data suggest that T cells selected during the primary response are stable into memory. While the majority of the secondary repertoire is derived from the circulation pool of antigen-specific CD8+ memory T cells, the
selection and subsequent expansion of a particular T cell following challenge is a stochastic event (Fig. 1C). Previous studies have demonstrated that selection of the primary immune repertoire from low frequency precursors is essentially random [33,34]. The alterations in frequency of particular TCR signatures for both the Db NP366 - and Db PA224 -specific T cells is likely to reflect chance encounter with antigen, rather than specific selection for dominant T cell specificities.
8. Factors determining the selection of “diverse” versus “restricted” repertoires The Db PA224 -specific subset is diverse, with approximately 15–20 different TCR signatures being found for each mouse. These estimates agree with other approximations using different model antigens [25]. Moreover, the Db PA224 -specific TCRs tended to be individual, and are legitimately described as a “private repertoire” [35]. In contrast, the Db NP366 -specific repertoire was more limited in extent, with only 5–10 different TCRs used per individual. Moreover, the Db NP366 -specific set was characterized by repeated TCRs that could be isolated from many mice. Such
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SGGANTGQL AGTGGGGGGGCA AGTGGGGGGGCT AGTGGTGGGGCA AGTGGTGGGGCG AGTGGGGGGGCG AGTGGGGGTGCA AGTGGGGGAGCA
M1 42% 28% 30% ---------
M2 72% ----22% 6% -----
M3 50% 25% ----25% -----
M4 29% ------58% --13%
SGGGNTGQL AGTGGGGGGGGA AGTGGAGGGGGT AGTGGAGGGGGC AGCGGGGGGGGA AGTGGGGGAGGA AGTGGGGGGGGG AGTGGGGGGGGC AGTGGGGGGGGT AGTGGTGGGGGC AGTGGAGGGGGG
M1 50% ------20% 9% 21% -------
M2 50% --------50% ---------
M3 ----20% ----57% ----23% ---
M4 100% -------------------
Fig. 2. The public CDR3 loops isolated from TCRBV8S3+ NP366 -specific CD8+ T cells are encoded by different nucleotide sequences. Shown are the amino acid sequences of the public CDR3 loop that can repeatedly isolated from different individual mice. The same CDR3 loop can be encoded by up to four different nucleotide sequences within the one individual mouse. This suggests that there is a strong selection for an appropriate CDR3 loop that is capable of binding the Db NP366 determinant.
repeat sequences (SGGSNTGQL and SGGANTGQL) were also shown for Db NP366 -specific hybridomas in a previous study [27], and indeed represent a “public” repertoire [35]. The factors that determine the selection of “public” versus “private” repertoires are not clear. The same EBV-specific TCR combination is repeatedly isolated from different individuals expressing HLA-B8 [18]. Interestingly, these EBV-specific T cells are also cross-reactive with the HLA-B4220 alloantigen. People who are both HLA-B8 and B4402 positive no longer express this TCR “public” specificity and in fact have a rather diversified EBV-specific repertoire [36]. Thymic selection may be modifying the diversity of this EBV-specific repertoire. A likely scenario is that “public” repertoires result from the preferential selection of TCRs with the appropriate structural confirmation for antigen recognition [13,14]. Supporting this idea is the fact that the same CDR3 loop amino acid sequence can be encoded by distinct nucleotide sequences [18,36–38]. We analyzed “public” TCR sequences observed for the influenza-specific Db NP366 response and identified up to 10 different nucleotide sequences, with one to four of these being present within any one individual (Fig. 2 and Kedzierska et al., manuscript in preparation). In most cases such variation was a result of N-region diversity. Why the Db NP366 -specific response induces such a “public” TCR repertoire is unclear. Perhaps the answer lies in the rather featureless shape of the Db NP366 epitope (Kedzierska et al., manuscript in preparation), analogous to the “vanilla” peptide of the influenza matrix epitope that binds to HLA-A2 [14].
9. Reverse genetics: a new technique for the manipulation of influenza-specific CD8 T cell responses The use of plasmids for the generation of infectious influenza virions [39] enables the site-directed mutagenesis of particular gene segments, a strategy we have used to dissect the influenza-specific CD8+ T cell responses after infection [40]. Point mutations were made at position 5 in both NP366–374 and PA224–233 , with the consequence that the modified peptides no longer bind H2Db [40]. Infection of mice with these mutant viruses established three important points. 1. There was a clear, protective role for both the Db NP366 and Db PA224 -specific T cell populations during the course of infection. Both single (NP− or PA− ) and double (NP− PA− ) mutant viruses showed increased virulence in Ig−/− mice. This was somewhat of a surprise for the Db PA224 -specific set, as there is evidence that Db PA224 may not be expressed on lung epithelium and would not, therefore, be a predicted target for viral clearance [41]. While the mechanism of protection is yet to be determined, it is clear that selection of epitopes for vaccine strategies needs to be done with care. It may not be sufficient to simply determine whether or not a response is dominant. 2. Influenza epitope-specific CTL responses seem to be regulated independent of each other. The CD8+ Db NP366 + set dominates the influenza-specific secondary response,
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perhaps because these T cells in some way compromise the Db PA224 -specific population. This could reflect down-modulation of the Db PA224 -specific response, either by competition for antigen presenting cells (APCs) or by killing off professional APCs [42]. This seems unlikely, however, as little evidence was found for an increased response to Db PA224 in mice infected with the NP− virus. 3. The reverse genetic system is a powerful technique that allows manipulation of the responding CD8 T cell repertoires. This in turn facilitates the delineation of the relationship between diverse profiles of antigen recognition and the functional consequence of the TCR–epitope interaction.
10. Conclusions Respiratory challenge with the influenza A viruses provides a well-characterized system for the analysis of CD8+ T cell response in a localized, transient infectious process. The model is safe to use in both laboratories and animal facilities, and is readily exploited to explore new questions and technologies. Though it is likely that a great deal remains to be learned about CD8+ T cell response to acute infection, the use of approaches involving mutant viruses, single cell sorting and RT–PCR is providing a spectrum of new findings and insights. The ultimate aim is to exploit such models to identify markers of immunity (functional and molecular) that are appropriates correlates of protective cell-mediated immunity, particularly in humans. We need to understand better, for example, why it is that the CD8 T cell numbers generated after vaccination do not always correlate with the extent of effective protection. The more that is learned about the relationships between the quality of CTL responses and protection, the more rapidly we are likely to proceed with the development of novel vaccine strategies.
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This work is supported by the NH&MRC (Burnet Fellowship awarded to P.C.D.), by USPHS grants AI29579 and CA21765 and by the American Lebanese Syrian Associated Charities (ALSAC).
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