1. Immunology and Inflammation
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Self-recognition drives the preferential accumulation of promiscuous CD4+ T-cells in aged mice

  1. Neha R Deshpande
  2. Heather L Parrish
  3. Michael S Kuhns  Is a corresponding author
  1. University of Arizona College of Medicine, United States
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Cite this article as: eLife 2015;4:e05949 doi: 10.7554/eLife.05949

Abstract

T-cell recognition of self and foreign peptide antigens presented in major histocompatibility complex molecules (pMHC) is essential for life-long immunity. How the ability of the CD4+ T-cell compartment to bind self- and foreign-pMHC changes over the lifespan remains a fundamental aspect of T-cell biology that is largely unexplored. We report that, while old mice (18–22 months) contain fewer CD4+ T-cells compared with adults (8–12 weeks), those that remain have a higher intrinsic affinity for self-pMHC, as measured by CD5 expression. Old mice also have more cells that bind individual or multiple distinct foreign-pMHCs, and the fold increase in pMHC-binding populations is directly related to their CD5 levels. These data demonstrate that the CD4+ T-cell compartment preferentially accumulates promiscuous constituents with age as a consequence of higher affinity T-cell receptor interactions with self-pMHC.

https://doi.org/10.7554/eLife.05949.001

eLife digest

The immune system's T cells help the body to recognize and destroy harmful pathogens, such as viruses and bacteria. T cells ‘remember’ immunity-inducing fragments, called antigens, from the pathogens they have encountered. This memory then allows the immune system to quickly fend off infections if those pathogens, or even related pathogens, invade again. Vaccines exploit the ability to form immunological memory by exposing the body to harmless forms of the pathogen, or even just particular antigens from it. This allows the T cells to learn how to identify the pathogen without any risk of illness.

Vaccines have been extremely successful and have helped to virtually eliminate some diseases. However, for reasons that are unclear, the immune systems of older adults become less functional, so vaccines often lose their effectiveness. Paradoxically, as people age T cells become more likely to attack the body's cells, causing autoimmune diseases like arthritis. Understanding what happens to aging T cells to cause these immune changes may help scientists design vaccines that remain effective as people age.

Little is known about what happens to a particular type of T cell—the CD4+ T cells—as people age, even though this population plays a critical role in providing other immune cells with detailed instructions on when and how to fight a pathogen. Now, Deshpande et al. show that CD4+ T cells undergo a remarkable set of changes in aging mice. Mice that are nearing the end of their natural lifespan have fewer CD4+ T cells than younger mice. However, those CD4+ T cells that remain are more likely than CD4+ T cells from younger mice to be able to recognize multiple antigens. This increase in the proportion of multitasking CD4+ T cells corresponds with an increased tendency of these cells to bind to the body's own cells. If similar changes occur in older people, this may help explain some age-related autoimmune diseases. Yet, the relationship between the increase in multitasking CD4+ T cells and the decrease in immune function with aging remains to be fully explored.

The challenge for scientists now is to determine how these age-related changes in CD4+ T cells affect immune responses to vaccines or pathogens in older individuals. One implication of this work is that CD4+ T cell responses may be too robust and out of balance with other arms of the immune system. This could even lead to conditions such as autoimmunity. Alternatively, while there may be more CD4+ T cells that can multitask by recognizing multiple antigens, their ability to respond appropriately to infections or vaccinations may be diminished. What is clear from the work of Deshpande et al. is that the rules that have been defined for immunity in adults change with aging. The rules that govern immunity in the elderly must be more clearly defined to realize the goal of designing immunotherapies, such as vaccines, that provide protection throughout the lifespan.

https://doi.org/10.7554/eLife.05949.002

Introduction

Each T-cell expresses a T-cell receptor (TCR) encoded by rearranged gene segments and non-germline nucleotides. Estimates of TCR diversity imply a repertoire that can bind a universe of self and foreign peptides embedded within self-major histocompatibility complex molecules (pMHC) (Davis and Bjorkman, 1988). Yet, this potential cannot be realized. Thymic development limits clonal representation to T-cells bearing TCRs within an affinity window for self-pMHC (Savage and Davis, 2001; Yin et al., 2012; Klein et al., 2014), while peripheral space physically constrains the number of T-cells present to recognize foreign-pMHC (Mason, 1998; Vrisekoop et al., 2014). Finally, time—with its age-associated changes in thymic expression of tissue-restricted antigens (TRAs), thymic architecture, antigen experience, and homeostasis—imposes an overarching pressure that limits the binding capacity of a repertoire for self- and foreign-pMHC to each constituent's prior history of TCR–pMHC interactions (Nikolich-Zugich, 2008; Surh and Sprent, 2008; Chinn et al., 2012; Griffith et al., 2012). How these pressures shape the capacity of the CD4+ T-cell compartment to bind pMHC over the lifespan remains largely unexplored.

Aging is associated with increased susceptibility to infections and decreased responsiveness to vaccines, suggesting that individual repertoires converge on a point where their diversity is insufficient to bind and/or mount a protective response to foreign-pMHC (Vazquez-Boland et al., 2001; Nichol, 2008; Nikolich-Zugich, 2008). Consistent with this idea, TCR diversity within both the CD4+ and CD8+ T-cell compartments contract from adult to old mice in parallel with thymic involution (Ahmed et al., 2009; Rudd et al., 2011; Britanova et al., 2014), and the number of CD8+ T-cells that bind distinct foreign class I pMHC in unprimed mice decreases over the lifespan (Yager et al., 2008; Rudd et al., 2011; Decman et al., 2012; Smithey et al., 2012). Here, we explored how aging impacts the number of naive and memory phenotype CD4+ T-cells available to bind pMHC, their relative affinity for self-pMHC, and their capacity to bind foreign-pMHC. We report that, while the absolute number of CD4+ T-cells decreases over time, those that remain have an increased affinity for self-pMHC and an increased capacity to bind foreign-pMHC.

Results

Unprimed old (18–22 months) C57BL/6 mice were found to have fewer CD4+ T-cells in their secondary lymphoid organs than adults (8–12 weeks) due to a loss of naive (CD44lo) T-cells, as expected given thymic involution (Figure 1A,B) (den Braber et al., 2012). The number of memory phenotype (CD44hi) CD4+ T-cells increased with aging (Figure 1C). This could be due to prior antigen experience and/or homeostatic proliferation (Nikolich-Zugich, 2008; Surh and Sprent, 2008).

The CD4+ T-cell compartment contracts but accumulates CD44hiCD5hi cells with aging.

The absolute numbers of T-cells in unprimed adult (8–12 weeks) and old (18–22 months) mice are shown as (A) total CD4+ T-cells in secondary lymphoid organs, (B) CD4+ CD44lo (naïve) T-cells and (C) CD4+ CD44hi (memory phenotype) T-cells. Data are concatenated from three experiments, 4 mice/group. Horizontal bar indicates median (*p < 0.05, ***p < 0.0001; Mann–Whitney). (D) Relative fluorescent intensity (RFI) of CD5 expression on adult and old CD44hi and CD44lo CD4+ T-cells relative to CD5 expression on adult CD44lo CD4+ T-cells (dotted line). Data represent four experiments with 4 mice/group (***p < 0.0001, *p < 0.05; Mann–Whitney). (E) RFI of CD3 expression on adult and old CD44hi and CD44lo CD4+ T-cells relative to CD3 expression on adult CD44lo CD4+ T-cells (dotted line) (***p < 0.0001; Mann–Whitney). Results represent seven experiments with 4 mice/group. (F) Concatenated contour plots (4 mice) showing CD5 vs BrdU incorporation in unprimed adult and old total CD4+ T-cells. Percent BrdU+ of total CD4+ T-cells ± SEM is shown in the inset (*p < 0.05 Mann–Whitney adult compared to old). (G) Absolute numbers of CD4+ BrdU+ T-cells. Results are representative of two experiments with 4 mice/group.

https://doi.org/10.7554/eLife.05949.003

To assess steady-state TCR engagement, we measured CD5 expression, as a surrogate for the strength of tonic TCR–pMHC interactions (Azzam et al., 1998; Smith et al., 2001; Mandl et al., 2012, 2013; Persaud et al., 2014; Vrisekoop et al., 2014; Fulton et al., 2015); CD3 levels, which decrease upon TCR engagement (Valitutti et al., 1995); and BrdU incorporation to assess proliferation in unprimed mice. CD5 was higher on memory CD4+ T-cells in adult mice relative to adult naive T-cells, as expected (Mandl et al., 2013), while both naive and memory CD4+ T-cells in old mice had higher CD5 expression relative to adult naive cells (Figure 1D). An inverse relationship was observed between CD5 and CD3 levels, consistent with CD5 reflecting tonic TCR engagement (Figure 1E). Finally, cells with high CD5 expression incorporated the most BrdU in adult and old mice, consistent with tonic TCR interactions driving homeostatic proliferation (Figure 1F). A higher frequency of BrdU+ cells was observed in old mice compared with adults. However, since the total number of CD4+ T-cell drops in old mice this did not result in significantly more BrdU+CD4+ T-cells (Figure 1F,G). Altogether, the data indicate that the CD4+ T-cell compartment increases in clonal representation of constituents with higher intrinsic affinity for self-pMHC.

Age-related changes in the capacity of the CD4+ T-cell compartment to bind foreign-pMHC were evaluated via tetramer enrichment (all class II pMHC tetramer validation is shown in Figure 2—figure supplements 1, 2). I-Ab tetramers presenting an immunodominant peptide (aa 641–655) from West Nile Virus (WNV) envelope protein (E641:I-Ab) were used because WNV lethality increases over the lifespan of mice and humans, making it a useful model for investigating age-related defects in susceptibility to viral infection and vaccine efficacy (Brien et al., 2008, 2009; Uhrlaub et al., 2011; Suthar et al., 2013). Two-color tetramer enrichment (Nelson et al., 2015) revealed more cells binding E641:I-Ab in old mice than adults (Figure 2—figure supplement 3).

To determine if this is unique to E641:I-Ab, we also enumerated CD4+ T-cells with distinct recognition properties by using a tetramer made with a subdominant ovalbumin peptide (326–338) in I-Ab (OVA:I-Ab), and an allogeneic tetramer made with the moth cytochrome c peptide (88–103) bound to I-Ek (MCC:I-Ek) (Savage et al., 1999; Malherbe et al., 2004; Moon et al., 2007; Brien et al., 2008). OVA:I-Ab was considered to be subdominant because immunization with OVA elicited a smaller response than E641 in isolation and failed to mount a response upon co-immunization with E641 (Figure 2—figure supplements 2, 4). OVA:I-Ab monomer is also less SDS-stable than E641:I-Ab at room temperature (not shown), and pMHC stability is directly related to immunodominance (Lazarski et al., 2005). Alloreactive cells were enumerated because they are likely to be selected on a broader range of self-pMHC and represent a broader subset of the CD4+ T-cell compartment (Felix and Allen, 2007; Chu et al., 2009).

CD4+ T-cells bound to E641:I-Ab, OVA:I-Ab, and MCC:I-Ek were simultaneously enriched from individual animals using anti-His beads against the 6× His-tag on the alpha and beta subunits of each pMHC (Figure 2A–F and Figure 2—figure supplement 5). This yielded more E641-bound adult cells than the anti-PE/APC beads (Figure 2G and Figure 2—figure supplement 3E). Since tetramers cannot detect all CD4+ T-cells that respond to a given class II pMHC via weak TCR–pMHC interactions (Sabatino et al., 2011), the more avid His-tag enrichment is likely to detect T-cells that bind tetramers with lower avidity.

Figure 2 with 9 supplements see all
CD44lo and CD44hi CD4+ T-cells binding immunodominant, subdominant, and allogeneic pMHC increase with time.

Representative plots of CD4+ T-cells bound to (A and B) E641:I-Ab, (C and D) OVA:I-Ab, and (E and F) MCC:I-Ek tetramers in adult (top) and old (bottom) mice. Absolute number of CD4+ CD44lo (left Y-axis) and CD4+ CD44hi (right Y-axis) T-cells bound to (G) E641:I-Ab, (H) OVA:I-Ab, or (I) MCC:I-Ek tetramers only enumerated after dump tetramer analysis (‘Materials and methods’), or those binding (J) E641:I-Ab + OVA:I-Ab, (K) OVA:I-Ab + MCC:I-Ek, or (L) E64:I-Ab + MCC:I-Ek tetramers in combination enumerated after both dump and two-color tetramer analysis (‘Materials and methods’). Bars indicate median (*p < 0.05, **p < 0.005, ***p < 0.0001, ns = non-significant; Mann–Whitney). Fold change (Δ) in means between adult and old is shown. Results are from three experiments with 4 mice/group.

https://doi.org/10.7554/eLife.05949.004

More naive and memory cells were observed to bind a single pMHC specificity in old mice compared with adults when using dump tetramer gating (Figure 2G–I and Figure 2—figure supplements 5, 6) (Savage et al., 1999). This indicates that the increase in CD4+ T-cells binding E641:I-Ab is not unique. Rather, since CD4+ T-cells decline with aging, those that are left appear to bind foreign pMHC more promiscuously. Consistent with this interpretation, the number of naive cells binding OVA+MCC was higher in old mice compared with adults, as were the number of memory cells binding E641+OVA or OVA+MCC (Figure 2J–L and Figure 2—figure supplements 7–9). Altogether, these data provide evidence that the CD4+ T-cell compartment becomes polyspecific over time.

Such results could reflect age-related changes in thymic selection, homeostatic signals, or both. To evaluate the former, we enriched thymocytes from adult and old mice with E641:I-Ab, OVA:I-Ab, and MCC:I-Ek tetramers. The frequency of E641-bound CD4 single positive (SP) cells was higher for old thymocytes compared with the adults, while the frequency of OVA and MCC-bound CD4SPs did not differ (Figure 3 and Figure 3—figure supplement 1). CD4SPs binding two distinct tetramers were not detected amongst the small number of tetramer-enriched samples. This is not surprising given that dual binders average <10% of a peripheral population (Figure 2—figure supplement 6). Since thymic output remains constant as a function of size over time (Hale et al., 2006), the higher frequency of E641-bound CD4SP thymocytes in old mice suggests that more E641-binders leave the thymus of old mice than adults on a daily basis. However, mature CD4+ T-cells re-entering the thymus increase from ∼10% in adult mice to ∼20% in old mice (Hale et al., 2006). Our analysis cannot resolve CD4SPs from mature CD4+ T-cells, so the impact of recirculation on our analysis is unclear. Nevertheless, the data suggest that age-related changes in thymic selection impact the clonal representation and binding capacity of the CD4+ T-cell compartment.

Figure 3 with 1 supplement see all
Evidence for changes in selection of E641-binding CD4SP thymocytes with aging.

Frequencies of (A) E641:I-Ab+, (B) OVA:I-Ab+, and (C) MCC:I-Ek+ CD4 single positive (SP) thymocytes per 107 CD4SP thymocytes are shown. Horizontal bar indicates median (*p < 0.05 and ns = non-significant; Mann–Whitney). Each dot represents the results from 4–5 mice pooled/group as described in ‘Materials and methods’.

https://doi.org/10.7554/eLife.05949.014

Finally, we investigated how tonic TCR engagement relates to the capacity of the CD4+ T-cell compartment to bind foreign-pMHC (Mandl et al., 2013). CD5 levels on the tetramer-bound adult populations, relative to those on the total adult CD4+ T-cell population, directly correlated with the fold increase in the absolute number of these populations over time (Figure 4A,B). Steady-state BrdU incorporation for adult and old tetramer-bound CD4+ T-cells also mirrored the rank order (OVA>E641>MCC) of CD5 expression seen in both the naive and memory populations (Figure 4C,D). Thus, CD5 levels are predictive of the fold-increase in pMHC-specific CD4+ T-cell subsets with aging, suggesting a link between affinity for self-pMHC, homeostatic proliferation, and expansion over time.

CD5 levels on adult CD4+ T-cells correlate with expansion over time.

Correlation between CD5 RFI for adult CD4+ tetramer+ T-cells and fold change in tetramer+ cells between adult and old populations of (A) CD44lo and (B) CD44hi CD4+ T-cells are shown as labeled. Linear regression was calculated using GraphPad Prism 5. Steady-state in vivo proliferation was assessed by measuring percent BrdU incorporation in tetramer single+ (C) adult or (D) old CD4+ T-cells derived from unprimed mice after 6 days of BrdU exposure (*p < 0.05; ANOVA followed by Dunn's post-test comparison). Results represent two experiments with 4 mice/group.

https://doi.org/10.7554/eLife.05949.016

Discussion

Advances in the analysis of clonal representation, pMHC-binding capacity, and functionality within the T-cell repertoire are contributing to a broader understanding of the rules that govern its composition and function. While most studies focus on adult mouse or human T-cells, when immunity is at its peak, there is a growing appreciation that the pressures imposed by time on thymic selection and peripheral space result in a repertoire that continuously evolves in each individual. Here, we contribute to our basic understanding of T-cell biology by reporting that the size of the CD4+ T-cell compartment contracts with aging but, unlike CD8+ T-cells, the capacity of CD4+ T-cells to bind foreign-pMHC increases over the lifespan.

Thymic involution could contribute to these changes in multiple ways. A decrease in cortical thymic epithelial cells and changes in antigen processing could increase competition for positively selecting pMHC (Chinn et al., 2012; Klein et al., 2014), favoring higher TCR affinity for self-pMHC. In addition, decreased expression of TRAs on fewer medullary TECs (Chinn et al., 2012; Griffith et al., 2012) could lead to competition for negatively selecting pMHC with aging. Experimentally limiting thymic selection differentially impacts the CD4+ and CD8+ T-cell compartments, with CD4+ T-cells becoming more polyspecific and CD8+ T-cells becoming more pMHC focused (Huseby et al., 2005; Chu et al., 2009, 2010; Wang et al., 2009; Yin et al., 2012). Thus, age-related changes in the thymus would be expected to restrict negative selection and result in a CD4+ T-cell compartment with a broader binding capacity, as observed here. It is also noteworthy that T-cells can productively rearrange two TCRα subunits and express two TCRs that increase reactivity to self- and allo-pMHC (Ni et al., 2014). Whether T-cells expressing two TCRs increase over time remains unexplored.

Changes in peripheral space are also likely to contribute to the results reported here. A link between higher affinity for self-pMHC and residence within the CD4+ T-cell memory pool of adult mice was previously reported (Mandl et al., 2013). Here, we extended this observation to naive and memory CD4+ T-cells in old mice, indicating that affinity for self-pMHC influences clonal fitness over time. This would be akin to the affinity of TCR–pMHC interactions influencing clonal fitness within a polyclonal response to cognate antigens (Lanzavecchia and Sallusto, 2002; Gett et al., 2003; Malherbe et al., 2004). Indeed, CD5 levels on adult tetramer-binding memory subsets directly correlated with their fold expansion over the lifespan showing that CD5 levels have a clear predictive value when identifying populations with a long-term advantage for clonal representation within the CD4+ T-cell compartment.

Altogether, the data presented here suggest a more complex relationship between CD4+ T cells and immune senescence than has been reported for the CD8+ T cells. While an increase in binding capacity may compensate for a decrease in total CD4+ T cell numbers, the consequences of this increase remain unclear. Certainly, a population with a higher affinity for self-pMHC and broader binding capacity poses obvious risks that could explain the increase in age-related autoimmune diseases, such as rheumatoid arthritis and giant cell arteritis (Weyand et al., 2003; Mohan et al., 2011). Coupling functional analysis with the results presented here will be important to gain a better understanding of the functionality of the CD4+ T cell compartment over the lifespan.

Materials and methods

Mice

Old (18–22 months) male C57BL/6 mice were obtained from the National Institute of Aging breeding colony Bethesda, MD. Adult (8–12 weeks) male C57BL/6 mice were purchased from the Jackson Laboratory Bar Harbor, Maine. Mice were maintained under specific pathogen-free conditions in the animal facility at The University of Arizona. Experiments were conducted under guidelines and approval of the Institutional Animal Care and Use Committee of The University of Arizona.

Peptides, CFA, and immunizations

Synthetic peptides Env 641–655 (E641: PVGRLVTVNPFVSVA) and OVA 323–339 (OVA: ISQAVHAAHAEINEAGR) were purchased at >95% purity from 21st Century Biochemicals Marlborough, MA. Complete Freund's adjuvant (CFA) was purchased from Sigma–Aldrich St. Louis, MO. Mice were immunized with 50 µg peptide in 50 µl CFA on each side of the base of the tail.

Tetramers

Class II pMHC monomers were generated with baculovirus expression vectors, based on pAcGP67A (BD Pharmingen San Jose, CA), encoding acidic or basic leucine zippers (generous gift of KC Garcia) according to the approach of Teyton and colleagues (Scott et al., 1996). The full extracellular domains of I-Ek alpha and I-Ab alpha were expressed as fusions with the acidic leucine zipper, a BirA acceptor peptide, and a 6× his tag. The full I-Ab beta extracellular domain was expressed as fusions with the WNV Env 641–655 or OVA 326–338 peptides at the N-terminus, via a short linker similarly to Kappler and colleagues (Crawford et al., 1998), and at the C-terminus with the basic leucine zipper and a 6× his tag. I-Ek beta fused to moth MCC 88–103 was otherwise the same.

Baculovirus stocks were made in Sf9 cells and large-scale protein production was performed in Hi5 cells as previously described (Dukkipati et al., 2006). pMHC complexes were purified from media by affinity chromatography using Ni-NTA affinity resin (Qiagen Valencia, CA) followed by biotinylation with BirA (Avidity, Aurora, CO.) and size exclusion chromatography with a Superdex-200 column (GE Healthcare Life Sciences Pittsburgh, PA). Tetramers were created by mixing biotinylated peptide:I-Ab or I-Ek monomers with PE (Biolegend San Diego, CA)-, APC (Biolegend)-, or PerCPCy5.5 (eBiosciences San Diego, CA)-conjugated streptavidin at a molar ratio of 4:1 (Tetramer Concentration: 25 nM).

pMHCII tetramer-based enrichment and analysis

Tetramer enrichment and analysis was performed as described previously (Moon et al., 2007) with slight modifications. Inguinal, cervical, axillary, popliteal, mesenteric, and lumbar lymph nodes were harvested along with the spleen from individual mice. Single-cell suspensions of lymph node and spleens were depleted of red blood cells with ACK lysis buffer (Gibco Life Technologies Grand Island, NY) and Fc blocked (mAb 2.4G2 hybridoma supernatant + 2% mouse serum [Caltag Laboratories Burlingame, CA], 2% rat serum [Jackson Immuno Research Laboratories, INC West Grove, PA]) on ice for 20 min. Each tetramer was added at a final concentration of 25 nM and incubated at room temperature in the dark for 1 hr. Cells were washed in FACS buffer (PBS + 2% FBS, 0.1% NaN3) and resuspended in a final volume of 200 µl containing 25 µl of anti-PE and 25 µl of anti-APC microbeads (Miltenyi Biotec San Diego, CA) for two-color analysis of cells binding a single pMHC tetramers (Stetson et al., 2002; Obar et al., 2008; Nelson et al., 2015) or 50 µl of anti-His microbeads for simultaneous enrichment of cells binding three independent pMHC tetramers. After 30-min incubation at 4°C, cells were washed, resuspended in 3 ml FACS buffer and passed over a LS magnetic column at 4°C (Miltenyi Biotec) according to the manufacturer's instruction. The columns were removed from the magnetic field and bound cells were eluted by allowing 4 ml of FACS buffer to pass through the column by gravity at 4°C. A second elution was performed by pushing 4 ml of FACS buffer through the column with a plunger at 4°C. The tetramer-enriched ‘bound’ fraction and an aliquot of flow-thru, or ‘unbound’ fraction, were stained with a cocktail of flourochrome-labeled antibodies for 30 min at 4°C (anti-CD19 [eBiosciences], anti-CD8α [eBiosciences], anti-CD11c [eBiosciences], anti-F4/80 [Biolegend], anti-CD3 [eBiosciences], anti-CD4 [eBiosciences], anti-CD44 [eBiosciences], anti-CD5 [BD Pharmingen]). Cells were washed, and the samples were analyzed with a LSRII cytometer (Beckton Dickinson Franklin Lakes, NJ). Analysis was performed using FlowJo software (Treestar Ashland, OR). Gating was performed as shown in figure supplements.

Tetramers are composed of pMHC monomers and streptavidin (SA) conjugated to a fluorescent protein (FP). Two-color tetramer enrichment and gating for a single pMHC specificity was performed as a method for reducing false-positives in tetramer analysis (Stetson et al., 2002; Obar et al., 2008; Nelson et al., 2015). The operating principle followed here is that cells which bind to tetramers via TCR–pMHC interactions will fall on a diagonal, since binding should be proportional for each, while those that bind to the FP in a TCR-independent manner should fall off the diagonal (Figure 2—figure supplements 1, 3). The dump tetramer approach was used for samples in which E641:I-Ab, OVA:I-Ab, and MCC:I-Ek tetramers were used in a single sample for enrichment with anti-His beads (Savage et al., 1999; Newell et al., 2009). Here, cells bound to a tetramer of interest (e.g., E641:I-Ab) were gated and then those that also bound the other two tetramers (e.g., OVA:I-Ab and MCC:I-Ek) were excluded as a ‘dump’ to enumerate cells bound to one tetramer species only (Figure 2—figure supplement 5). The dumped cells could be false-positives binding SA, MHC, or the dump tetramer-associated FP nonspecifically; however, they could be bound via TCR–pMHC interactions. Importantly, the operating principles of both the dump and two-color methods were employed to enumerate cells binding two tetramers at once. Specifically, to enumerate cells bound to a specific combination (e.g., E641:I-Ab + OVA:I-Ab), those also binding the third tetramer (e.g., MCC:I-Ek) were dumped prior to enumerating cells bound to both tetramers of interest by two-color analysis. Combining the two approaches should enumerate cells binding tetramers via TCR–pMHC interactions and exclude dumped cells that bind SA, MHC, or the dump-associated FP and those excluded by two-color analysis that bind the FP associated with the tetramers of interest in a non-specific manner. Combining both approaches by sequential gating (Figure 2—figure supplement 5) yielded the numbers shown in Figure 2J–L. The same overall results were achieved if quadrant gating was used for two-color analysis after applying the dump gate (Figure 2—figure supplements 7–9).

Thymocyte preparation

Thymi from old and adult mice were harvested in 1 ml of un-supplemented RPMI. Thymi from 4–5 old mice were pooled in order to take into account the drop in the total number of thymocytes in old mice due to thymic involution and to increase the total number of cells for the tetramer enrichment processing. Thymi were incubated with 3 ml of Accutase (eBiosciences) at 37°C for 30 min to achieve optimal cell detachment. Single cell suspension of thymocytes was depleted of red blood cells with ACK lysis buffer. The total number of thymocytes in old mice was 10-fold lower (∼2 × 107) than adults (∼2 × 108) due to thymic involution. The adult samples were then normalized for comparison by pooling 2 × 107 thymocytes from 4 to 5 adult mice. Thymocytes were Fc blocked on ice for 20 min. Cells were stained with E641:I-Ab–PerCP-Cy5.5, OVA:I-Ab–PE-Cy7, MCC:I-Ek–PE and each of these tetramers in a common FP (APC). Each tetramer was added at a final concentration of 25 nM. Tetramer enrichment was carried out as described above. The tetramer enriched ‘bound’ fraction and an aliquot of flow-thru, or ‘unbound’ fraction were stained with cocktail of flourochrome-labeled antibodies for 30 min at 4°C (anti-CD19, anti-CD8α, anti-CD11c, anti-F4/80, anti-CD3, anti-CD4, anti-CD5). Cells were washed and the samples were analyzed with a LSRII cytometer (Beckton Dickinson). Analysis was performed using FlowJo software (Treestar) as shown in Figure 3—figure supplement 1. The single color specificities of two of the tetramers (e.g., OVA and MCC) were used as dump tetramers prior to two-color analysis of the third tetramer (e.g., E641).

Hybridoma cell lines

TCR negative 58αβ hybridomas cells were transduced with retroviral vectors encoding the OT II, 5c.c7 or 2B4 TCR, full-length CD3 subunits, and CD4 according to previously described protocols (Kuhns and Davis, 2007).

In vivo proliferation assay

BrdU was administered to mice through drinking water at the concentration of 1 mg/ml + 1% glucose. Spleen and lymph nodes were harvested on day 6. Post-tetramer enrichment, cells were stained with cell surface antibodies (anti-CD3, anti-CD4, anti-CD19, anti-CD8α, anti-CD11c, anti-F4/80, anti-CD44, and anti-CD5) followed by intracellular anti-BrdU (BD Pharmingen) antibody according to BrdU flow kit protocol (BD Biosciences).

Statistical analysis

Mean fluorescent intensity of cell surface antibodies and intra-cellular antibodies were obtained from FlowJo software (Treestar). Statistical analyses were performed using the Mann–Whitney t-test for non-parametric data, ANOVA followed by Dunn's post-test for multiple comparisons of non-parametric data or linear regression for analyzing correlation. All statistical analysis was performed using GraphPad Prism software.

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Decision letter

  1. Satyajit Rath
    Reviewing Editor; National Institute of Immunology, India

eLife posts the editorial decision letter and author response on a selection of the published articles (subject to the approval of the authors). An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent (see review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.

Thank you for sending your work entitled “Affinity for self drives the preferential accumulation of promiscuous CD4+ T cells over the lifespan” for consideration at eLife. Your article has been favorably evaluated by Tadatsugu Taniguchi (Senior editor) and three reviewers, one of whom is a member of our Board of Reviewing Editors.

The Reviewing editor and the other reviewers discussed their comments before we reached this decision, and the Reviewing editor has assembled the following comments to help you prepare a revised submission.

1) The manuscript demonstrates that the specificity (and perhaps self-pMHC affinity) landscape of the TCR repertoire shows interesting aging-related changes in the CD4 T cell compartment that are distinct from those reported for the CD8 T cell compartment (Decman et al., 2012). The findings are correlative at this point with no data implicating any mechanisms by which these distinctions arise, and they require greater rigor in both data and interpretation.

2) The TCR specificity of the tetramer binding, the assay upon which all the results depend, must be established with greater rigor than at present. While the data in Figure 3 are reasonably convincing in this regard, the data in Figure 4 are not. Without double staining with the same tetramer labeled with two different fluorochromes, it is harder to assess the validity of the staining in Figure 4. Except for 4B, the tetramer-binding cells are poorly resolved from the background. A control to show that no events are in the CD3+ CD8+ gate is absent. The data suggest that, for any antigenic peptide, equal numbers of precursors are available in the naive and the memory CD4 T cell compartments. These issues raise the concern that the detected cells are not binding the tetramers by their TCRs. About one third of the E641:I-Ab-specific cells also bind to OVA323-339:I-Ab in young adults, not to mention old mice. This is an extraordinarily high number since peptides that bind to the same MHCII molecule need to share at least a couple of TCR contact amino acids to cross-react on the same TCR (Birnbaum et al., 2014). Since core nonamer sequences are not defined for either E641 or OVA323-339, it is not clear if they share any such TCR contact amino acids. The specificity concern is exacerbated by the fact that the cells that bind E641:I-Ab and OVA323-339:I-Ab do not undergo clonal expansion after immunization with E641. It is therefore essential to perform additional experiments with the resolving power of Figure 3 to provide convincing evidence that the tetramer binding being detected, particularly by ‘polyspecific’ CD4 T cells, is indeed via their TCRs.

3) It would be important to address directly the contribution of differences created during thymic selection versus those created during peripheral residence to the distinctions of naive CD4 T cell repertories between young and aged mice, such as data on repertoires of maturing thymocytes between young and aged mice, for example.

4) CD5 levels are interpreted throughout as indicators of self-pMHC affinity of TCRs. It would be important to have at least some data providing independent indications supporting this interpretation.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Thank you for sending your work entitled “Affinity for self drives the preferential accumulation of promiscuous CD4+ T cells over the lifespan” for consideration at eLife. Your revised manuscript was further evaluated by Tadatsugu Taniguchi (Senior Editor) and two reviewers, one of whom is a member of our Board of Reviewing Editors (BRE). Please find below the comments, which were assembled by the BRE member, and the offer we can make at this stage.

While the reviewers all find your work interesting, the revised manuscript does not substantively address all the four major concerns raised in the first review. Therefore, it does not cross the enthusiasm threshold for publication in eLife as a full article.

The first concern is that it would be useful to have some indication of the mechanisms by which TCR repertoire modifications during aging differ between CD4 and CD8 compartments. While the difficulty of providing this is acknowledged, it remains the case that the revised manuscript does not provide any additional data addressing such mechanistic possibilities, reducing cross-disciplinary impact of the manuscript. The second concern is that the seemingly high frequencies of polyreactivity the authors obtain in their analysis of CD4 T cell repertoires necessitate a stringent-ER identification of target-specific TCRs and/or some independent evidence (if not explanation) for high-frequency polyspecificity. This issue has been addressed, albeit mostly via plausible arguments rather than additional data. The third concern is regarding the thymic and/or peripheral origin of the reported repertoire differences. The authors have indeed provided very interesting data for this issue, and have directly and substantively addressed the concern, improving the significance of the findings in the manuscript. The fourth concern is regarding the use of CD5 levels as a surrogate marker for self pMHC-affinity of TCRs. While the revised manuscript makes a case for this by plausible arguments, the relationship still remains a hypothesis, albeit a reasonable one.

Under these circumstances, particularly in light of the lack of mechanistic insights, the scope of the impact of the manuscript is limited for its publication as a full eLife research article.

However, the findings in the manuscript concerning the re-shaping of the CD4 T cell repertoire in aging mice are novel and of great interest and, therefore, deserve rapid publication.

Under these circumstances, it is recommended that the manuscript be re-written as a ‘Short Report’. This is no doubt a challenge, since limits for a short report involve a 2000-word text limit and a four-item main display limit (http://elifesciences.org/category/short-report). Nonetheless, we hope that you will undertake this to get these interesting and provocative findings published in eLife.

https://doi.org/10.7554/eLife.05949.017

Author response

1) The manuscript demonstrates that the specificity (and perhaps self-pMHC affinity) landscape of the TCR repertoire shows interesting aging-related changes in the CD4 T cell compartment that are distinct from those reported for the CD8 T cell compartment (Decman et al., 2012). The findings are correlative at this point with no data implicating any mechanisms by which these distinctions arise, and they require greater rigor in both data and interpretation.

We thank the reviewers for their constructive comments and critical input. Indeed, several studies have described a decrease in the numbers of CD8 T cells specific for foreign class I pMHC with aging. These include a decline in CD8 T cells specific for peptide epitopes from ovalbumin, vaccinia virus, influenza, HSV-1, LCMV (Decman et al., 2012; Rudd et al., 2011; Smithey et al., 2012; Yager et al., 2008), and WNV (Janko Nikolich-Zugich, personal communication). In contrast, age-related changes in the capacity of the CD4 T cell compartment to bind foreign-pMHC have been largely unexplored. Our results show a significant increase in CD4 T cells that bind foreign-pMHC over time, even though the absolute number of CD4 T cells declines. Aging thus inversely impacts the CD4 and CD8 T cell compartments. We consider this to represent an important advance in our fundamental understanding of T cell biology. Although the mechanistic basis for these changes will benefit from further elaboration in future studies, here we establish a mechanistic link between tonic TCR interactions with self-pMHC, steady state proliferation in vivo (Figure 6 and 7), and the increase in binding capacity observed in this study (Figure 3 and 4). We have also now added analysis of thymocytes in response to major point #3 (Figure 5). These data support the notion that both thymic and peripheral pressures contribute to age-related changes in the binding capacity of the CD4 T cell compartment.

2) The TCR specificity of the tetramer binding, the assay upon which all the results depend, must be established with greater rigor than at present. While the data in Figure 3 are reasonably convincing in this regard, the data in Figure 4 are not. Without double staining with the same tetramer labeled with two different fluorochromes, it is harder to assess the validity of the staining in Figure 4. Except for 4B, the tetramer-binding cells are poorly resolved from the background. A control to show that no events are in the CD3+ CD8+ gate is absent. The data suggest that, for any antigenic peptide, equal numbers of precursors are available in the naive and the memory CD4 T cell compartments. These issues raise the concern that the detected cells are not binding the tetramers by their TCRs. About one third of the E641:I-Ab-specific cells also bind to OVA323-339:I-Ab in young adults, not to mention old mice. This is an extraordinarily high number since peptides that bind to the same MHCII molecule need to share at least a couple of TCR contact amino acids to cross-react on the same TCR (Birnbaum et al., 2014). Since core nonamer sequences are not defined for either E641 or OVA323-339, it is not clear if they share any such TCR contact amino acids. The specificity concern is exacerbated by the fact that the cells that bind E641:I-Ab and OVA323-339:I-Ab do not undergo clonal expansion after immunization with E641. It is therefore essential to perform additional experiments with the resolving power of Figure 3 to provide convincing evidence that the tetramer binding being detected, particularly by ‘polyspecific’ CD4 T cells, is indeed via their TCRs.

We agree with the reviewers that tetramers require great care in both their use and data interpretation. With this in mind, our experiments were conducted with an extensive panel of dump antibodies as well as the two main published protocols for stringency in tetramer-based analysis: (i) dump tetramers (Newell et al., 2009; Savage et al., 1999), or (ii) two-color tetramers (Nelson et al., 2015; Obar et al., 2008; Stetson et al., 2002). Each strategy has pros and cons. Dump tetramers gate out false-positive cells bound to some component of a tetramer – be it streptavidin (SA), the MHC, or the fluorescent protein (FP) used for the dump tetramer– in a TCR-independent manner. This method also excludes cells bound to two different tetramers (the dump and subject tetramers) in a TCR-specific manner, either because they express one TCR that binds both pMHC, or two TCRs that individually bind two distinct pMHC. The two-color approach selectively analyzes cells binding the same tetramer made with two different FPs on a diagonal, since tetramer binding is proportional to the affinity of TCR-pMHC interactions and the differently colored tetramers should bind a specific cell equivalently. This approach lowers the limit of detection for low affinity cells, since tetramers of both colors are competing for limited TCR space on a T cell, but it excludes from analysis those cells that bind exclusively to one of the two FPs as false-positives. Cells bound to SA, the MHC, or shared motifs between FPs (as could occur with the structurally related phycobiliproteins PE and APC) in a TCR-independent manner are included in the analysis as false-positives.

For Figure 4G-4I we applied a sequential gating scheme (now Figure 4–figure supplement 5) to enumerate those cells that bind one tetramer exclusively (e.g. E641-only) after dumping out those cells that also bind the other tetramers (e.g. OVA and MCC) (Figure 4G-4I). Figure 4–figure supplement 6 has now been added to show how sequential gating impacts enumeration of the tetramer-bound populations under consideration. Theoretically, for the reasons outlined above, using two dump tetramers to enumerate the tetramer-only populations should be at least as stringent as the two-color approach.

A key point of emphasis is that we employed both the dump and two-color tetramer protocols to enumerate the ‘polyspecific’ CD4 T cells in question (e.g. E641+OVA). We realize from the Reviewer’s comments that our sequential gating scheme may not illustrate this point as well as a quadrant gate, and thus may cause confusion, even though it operationally achieves the same goal. Figure 4–figure supplements 8-10 have now been added to better illustrate the application of two-color staining, using quadrant gates, before and after the use of a dump tetramer (e.g. MCC) to identify cells binding strictly to two tetramers (e.g. E641+OVA). The numbers of ‘polyspecifc’ cells enumerated by two-color staining pre- and post-dump are also shown in these figure supplements. The derived numbers differ slightly from those obtained with our sequential gating scheme, shown in Figure 4J-4L, but the overall results and conclusions remain the same. We have also revised the text to better describe the logic behind our tetramer analysis (subsections “WNV-specific CD4+ T cells increase over time”, “Enumeration of CD4+ T cells binding multiple pMHC from the same mice” and “The CD4+ T cell compartment becomes more promiscuous for foreign pMHC over time”). Importantly, since the two-color approach is inherent within our analysis of the polyspecific cells in Figure 4J-4L, and applied after a dump tetramer, we consider the resolving power of these experiments to be at least equal to that of Figure 3.

We are also providing data to the reviewers from additional control experiments, which we performed with TCR negative hybridomas, in order to ensure that the stringency employed in Figure 4 provides resolving power equal to Figure 3. Here we used TCR negative 58α-β- cells to model the two-color approach used in Figure 3, the dump approach used in Figure 4G-4I, and the use of both for polyspecific cells in Figure 4J-4L.

TCR negative 58α-β- cells were incubated with E641 tetramers made with PE and APC, as in Figure 3B, to model false-positive cells binding to both tetramers versus one or the other. A large number of events were collected since our tetramers are not generally “sticky” (Author response image 1A and 1B). We enumerated 222 false positive cells on the diagonal (of a total of 464 false-positives) per 500,000 cells collected. In the same experiment, 58α-β- cells were incubated with E641-APC, OVA-PerCP-Cy5.5, and MCC-PE tetramers as in Figure 4. We enumerated 225 per 500,000 E641-bound cells without excluding cells binding OVA or MCC (Author response image 1C) and 126 per 500,000 E641-bound cells after excluded cells bound to OVA and MCC (Author response image 1D) as per the dump approach applied to E641-only cells in Figure 4G. Both approaches reduce the number of false-positive cells enumerated in these experiments by a similar magnitude, suggesting to us that the analysis in Figures 3B and 4G-4I are at least comparable in stringency.

Author response image 1

Exclusion of false-positive cells by two-color and dump tetramer analysis modeled with TCR negative T cell hybridoma. TCR negative 58α-β- cells were incubated with E641: I-Ab tetramer in two color as in Figure 3 or with E641: I-Ab, OVA: I-Ab and MCC: I-Ek tetramers with single color as in Figure 4. Contour plot showing our (A) live 58α-β- cells; (B) 58α-β- cells incubated with E641: I-Ab (APC) and (PE) for two-color analysis; or 58α-β- cells staining positive for E641: I-Ab tetramer (C) pre and (D) post dump of cells bound to OVA: I-Ab and MCC: I-Ek. Percent and number (of 500,000 58α-β- cells) of cells bound to E641: I-Ab tetramer are shown in inset.

https://doi.org/10.7554/eLife.05949.019

In Author response image 2, we then combined the operating principles of both approaches to model our analysis of polyspecific cells that bind two distinct specificities (Figure 4J-4L). In Author response image 2A we show two-color analysis of false-positive 58α-β- cells binding E641, OVA, or both (39 of 500,000) after incubation with E641-APC, OVA-PerCP-Cy5.5, and MCC-PE tetramers as in Figure 4. Author response image 2B then shows that the false positive cells binding both have largely been eliminated after those bound to MCC have been excluded as a dump (2 per 500,000). We interpret these data as evidence that combining both methods provides at least as much resolving power as that of Figure 3.

Author response image 2

Dump tetramer and two-color analysis excludes the bulk of false positives from the analysis. TCR negative 58α-β- cells were incubated with E641: I-Ab, OVA: I-Ab and MCC: I-Ek tetramers as in Figure 4. Contour plot showing 58α-β- cells staining with E641: I-Ab (APC) and OVA: IAb (PerCP- Cy5.5) pre and post using dump (MCC: I-Ek) tetramer (A-B) Quadrant gate as in Nelson, et al., 2015. 500,000 58α-β- events are displayed. Percent and number of within the quadrant gates are shown in inset.

https://doi.org/10.7554/eLife.05949.020

Additional responses to Point #2 are as follows:

A) Figure 4–figure supplement 6 has been added to address the Reviewers’s comment that “About one third of the E641:I-Ab-specific cells also bind to OVA323-339:I-Ab in young adults, not to mention old mice.” ∼5-7% of the total population of cells binding E641 also bind OVA in the adult or old mice if we use MCC as a dump. 14-20% bind OVA and E641 if we include triple binders. These could bind both pMHC with a single TCR. Or, this percentage is within the range of cells expressing two TCR alpha chains that could bind to two distinct tetramers via two distinct TCRs. Also, particularly without the dump tetramer, some of these cells are likely to be non-specific binders.

B) “A control to show that no events are in the CD3+ CD8+ gate is absent.”

Our anti-CD8 mAb was included in our panel of dump mAbs, as in other studies (Obar et al., 2008; Savage et al., 1999), so it is difficult to confidently resolve CD8 T cells from the remainder of the cell populations we are dumping from our analysis. These were dumped since the literature suggests there should be some CD8 T cells binding class II pMHC, particularly the allo-pMHC, and we have no idea how age-associated changes in homeostatic or thymic pressures might impact MHC restriction (Hansen et al., 2013; Huseby et al., 2005; Robey et al., 1991). We have added specificity data, shown in Figure 4–figure supplement 1, to complement the specificity controls already shown in the manuscript in order to further validate our reagents.

C) “…the same MHCII molecule need to share at least a couple of TCR contact amino acids to cross-react on the same TCR (Birnbaum et al., 2014).”

The reviewers make an important point that we have considered. Table 1 has now been added to show the E641 and OVA peptides with the predicted core nonamer sequences and putative TCR contact residues (P2, P5, and P8) (Nelson et al., 2015; Zhu et al., 2003). Both peptides contain small hydrophobic side chains at P2 (Val and Ala, respectively) and polar residues at P5 (Asn and Glu, respectively). This suggests some weak similarities between TCR contact residues of the two peptides that may hint at a mechanistic basis for the cross reactivity we observe.

The study cited above does not rule out the possibility of polyspecific cells that bind two distinct, or at least more distantly related pMHC in a TCR-dependent manner. Indeed, they pointed out that examples exist in the literature for TCRs recognizing non-homologous peptides (Birnbaum et al., 2014). Furthermore, TCRs have been described that focus more on the MHC than the peptide and even cross-react with class I MHC after selection with a single class II pMHC (Huseby et al., 2005). In addition, Jenkins and colleagues showed CD4 SP thymocytes binding both 2W:I-Ab and IgM:I-Ab or 2W:I-Ab and FliC:I-Ab tetramers under conditions of limiting negative selection (Chu et al., 2010). By our assessment (not shown), the putative core nonamers of the former share hydrophobic residues at P2 (Trp and Val) and P5 (Leu and Ala) that vary in size, as do the latter at P5 (Leu and Ile) and P8 (Trp and Leu). We think it is therefore possible that exceptions to the requirement of shared TCR contacts for cross reactivity become more frequent under conditions of limiting negative selection with aging. Also, since ∼10% of peripheral T cells express dual TCRs (which represent > 40% of alloreactive cells), the possibility exists that our polyspecific cells may be recognizing multiple pMHC via dual TCRs (Ni et al., 2014). We think this is an important and exciting future direction that extends beyond what can be reasonably explored in one study.

3) It would be important to address directly the contribution of differences created during thymic selection versus those created during peripheral residence to the distinctions of naive CD4 T cell repertories between young and aged mice, such as data on repertoires of maturing thymocytes between young and aged mice, for example.

We agree that this line of inquiry is important for a deeper mechanistic understanding of our findings. To address this comment, we first analyzed the relationship between CD5 expression on adult and old peripheral T cells versus CD4 SP thymocytes (now shown in Figure 1–figure supplement 1). CD5 levels are higher on both adult and old CD4 SP thymocytes than on total adult CD4 T cells, but not different from each other. No clear connection can be made with these data and our previous results.

We also performed anti-His tag-based tetramer enrichment of adult and old thymocytes with E641, OVA, and MCC tetramers (now shown in Figure 5 and Figure 5–figure supplement 1). In consideration of the Reviewers’ comments, each tetramer had a unique color (E641 = PerCpCy5.5; OVA = PE-Cy7; MCC = PE) and all tetramers also had a common color (APC). Here we dumped the unique colors of two of the tetramers (e.g. OVA and MCC) and then enumerated those cells that bind the remaining tetramer in two colors (e.g. E641). Since old mice had ten-fold fewer (∼2X107) total thymocytes than adult mice (∼2X108), thymocytes from 4-5 old mice were pooled for tetramer enrichment. This was repeated with two data sets representing 4 mice/group and one representing 5/group from a total of three experiments. For the adults in each experiment, an aliquot of 2X107 cells from individual mice were pooled to equalize our tetramer enrichment samples between the adult and old populations.

More E641-binding CD4 SP thymocytes were enumerated from equivalent numbers of thymocytes from old mice compared to adults, indicating that the percentage of E641-bound CD4 SP is higher in old mice. The number of tetramer bound cells for OVA and MCC were not significantly different between adult and old in our sample size. The numbers of tetramer bound cells were so low that we are not surprised we did not detect cells binding two distinct tetramers, given their relatively low frequency in the periphery. Since Fink and colleagues have reported that thymic output is consistent over time relative to thymic size (Hale et al., 2006), the implication is that on a daily basis a higher number of E641 binders leave the thymus in old mice compared with the adult to take up residence in the periphery. Clearly, this is an important direction for further elaboration in future studies.

4) CD5 levels are interpreted throughout as indicators of self-pMHC affinity of TCRs. It would be important to have at least some data providing independent indications supporting this interpretation.

We agree with the reviewers on this point as this was the motivation for the data shown in Figure 1F and Figure 2A. First we assessed relative TCR levels, since TCR down regulation occurs upon TCR engagement, and demonstrated that they are inversely correlated with relative CD5 levels (Figure 1F). We also assessed BrdU incorporation, which is dependent on TCR engagement, and showed higher BrdU incorporation occurred in cells with higher CD5 levels (Figure 2A). The data in these figures were presented to complement the studies we referenced in the text (Azzam et al., 1998; Mandl et al., 2012; Mandl et al., 2013; Persaud et al., 2014; Smith et al., 2001). Such work is also consistent with a recent study from Jameson and colleagues (Fulton et al., 2015). We think the sum of the data in these bodies of work provide sufficient justification for our use of CD5 expression as a surrogate measure of tonic TCR interactions for self-pMHC.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

[…] While the reviewers all find your work interesting, the revised manuscript does not substantively address all the four major concerns raised in the first review. Therefore, it does not cross the enthusiasm threshold for publication in eLife as a full article. […]Under these circumstances, it is recommended that the manuscript be re-written as a ‘Short Report’.

We thank all involved individuals for their time and effort spent evaluating our work, as well as your offer to condense our key findings into a Short Report. Our manuscript now contains the following:

Figure 1: The broad characterization of naive and memory phenotype CD4 T cells regarding absolute numbers, CD5 expression, TCR down regulation, and steady-state proliferation (BrdU) (previously Figure 1 and 2). These data show that the CD4 T cell repertoire contracts in absolute number with aging, shifts in composition towards cells with a memory phenotype, and accumulates an increased frequency of constituents with higher CD5 levels that proliferate.

Figure 2: The enumeration of tetramer specific cells that bind only one tetramer, and those that bind two tetramers (previously Figure 3 and 4). These data demonstrate that a higher number of CD4 T cells bind to one or two individual pMHC within the contracting CD4 T cell repertoire of old mice compared with adults.

Figure 3: The enumeration of tetramer specific thymocytes. These data provide evidence that age-related changes in thymic selection serve as a potential mechanistic basis for changes in peripheral binding capacity (previously Figure 5).

Figure 4: Present the link between CD5 expression (as a measure of affinity for tonic TCR-pMHC interactions) and fold expansion of tetramer-bound cells over time (previously Figure 6E and 6F), as well as the relationship between CD5 levels and steady state proliferation (previously Figure 7). These data provide evidence that peripheral pressures (i.e. homeostatic proliferation driven by tonic TCR-pMHC interactions) serve as a potential mechanistic basis for changes in peripheral binding capacity that re-shape the aging CD4 T cell repertoire.

https://doi.org/10.7554/eLife.05949.018

Article and author information

Author details

  1. Neha R Deshpande

    1. Department of Immunobiology, University of Arizona College of Medicine, Tucson, United States
    2. Arizona Center on Aging, University of Arizona College of Medicine, Tucson, United States
    Contribution
    NRD, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article, Contributed unpublished essential data or reagents
    Competing interests
    The authors declare that no competing interests exist.
  2. Heather L Parrish

    Department of Immunobiology, University of Arizona College of Medicine, Tucson, United States
    Contribution
    HLP, Acquisition of data, Contributed unpublished essential data or reagents
    Competing interests
    The authors declare that no competing interests exist.
  3. Michael S Kuhns

    1. Department of Immunobiology, University of Arizona College of Medicine, Tucson, United States
    2. Arizona Center on Aging, University of Arizona College of Medicine, Tucson, United States
    3. BIO-5 Institute, University of Arizona College of Medicine, Tucson, United States
    Contribution
    MSK, Conception and design, Analysis and interpretation of data, Drafting or revising the article, Contributed unpublished essential data or reagents
    For correspondence
    mkuhns@email.arizona.edu
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (NIH) (BAA-NIAID-DAIT-NIHAI2010085)

  • Michael S Kuhns

Pew Charitable Trusts

  • Michael S Kuhns

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Janko Nikolich-Zugich, Dominik Schenten, Megan Smithey, Jennifer Uhrlaub, Caleb Glassman, and Sing Sing Way for critical comment and feedback on the manuscript. We also thank Mark Lee for thoughtful comments and technical assistance, as well as members of the Frelinger, Wu and Schenten labs for critical discussions. MSK is a Pew Scholar in Biomedical Sciences, supported by the Pew Charitable Trusts. This work was supported by the BAA-NIAID-DAIT-NIHAI2010085 (MSK).

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#08-102) of the University of Arizona.

Reviewing Editor

  1. Satyajit Rath, National Institute of Immunology, India

Publication history

  1. Received: December 8, 2014
  2. Accepted: June 24, 2015
  3. Version of Record published: July 14, 2015 (version 1)

Copyright

© 2015, Deshpande et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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