During infection, CD8+ T cells initially expand then contract, leaving a small memory pool providing long lasting immunity. While it has been described that CD8+ T cell memory formation becomes defective in old age, the cellular mechanism is largely unknown. Autophagy is a major cellular lysosomal degradation pathway of bulk material, and levels are known to fall with age. In this study, we describe a novel role for autophagy in CD8+ T cell memory formation. Mice lacking the autophagy gene Atg7 in T cells failed to establish CD8+ T cell memory to influenza and MCMV infection. Interestingly, autophagy levels were diminished in CD8+ T cells from aged mice. We could rejuvenate CD8+ T cell responses in elderly mice in an autophagy dependent manner using the compound spermidine. This study reveals a cell intrinsic explanation for poor CD8+ T cell memory in the elderly and potentially offers novel immune modulators to improve aged immunity.https://doi.org/10.7554/eLife.03706.001
In the face of an infection, the immune system mounts an aggressive response by producing many copies of killer immune cells called CD8+ T cells that recognize and destroy any cells infected with the invading pathogen. The number of killer cells produced depends on the extent of the infection. Once the infection has been brought under control, most of the CD8+ T cells die off. The small numbers that are retained—called memory cells—‘remember’ the pathogen, so that if it invades the body again, they can help the immune system to respond more quickly and effectively.
Memory cells are also critical to the effectiveness of vaccines, many of which introduce a dead or weakened pathogen into the body. This does not cause an infection, but does allow the immune system to create memory cells that are able to fend off the same pathogen in the future. However, vaccines only work in individuals that are able to produce and maintain memory cells, which many older people are less able to do.
An important system that maintains cells, called autophagy, destroys and removes the ‘junk’ and toxic by products that all cells accumulate over time as a result of normal cell functions. Without autophagy, cells become less able to produce energy and they may die. Puleston et al. show that autophagy begins to fail in old mice, which prevents the formation of a proper memory response. In addition, mice that lack an important gene needed for autophagy are unable to produce memory cells after being infected with viruses such as influenza.
Puleston et al. found that boosting autophagy in older mice using a chemical called spermidine—which is also found naturally in many tissues—helped to restore the mice's ability to create and maintain memory cells. Spermidine-treated mice developed a stronger immunity to influenza after vaccination compared with other mice of a similar age. Further research is required to better understand how spermidine works to see if it could be developed into a drug that safely boosts the immune system of humans.https://doi.org/10.7554/eLife.03706.002
Upon successful clearance of a pathogen, the majority of short-lived effector T cells die and the remaining cells differentiate into a memory T cell population that provides long lasting immunity. While the cytokines, surface molecules, and signaling components involved in T cell memory formation have been extensively studied, the molecular pathways supporting these cell fate decisions are poorly understood. The T memory population is (1) quiescent, (2) long-lived and actively maintained, and (3) relies on mitochondrial respiration (Pearce and Pearce, 2013). Both reduced cell cycling and longevity of this stem cell-like population demand rigorous maintenance of the cytoplasm as debris cannot be diluted to daughter cells, reminiscent of true stem cells (Mortensen et al., 2011; Guan et al., 2013; Warr et al., 2013). Across mammalian cell types, clearance of debris and damaged organelles such as mitochondria is typically executed via autophagy (Choi et al., 2013).
A recent study showed that formation of the influenza-specific B cell memory pool requires autophagy (Chen et al., 2014). However, while the role of autophagy in the homeostasis of naïve T cells is well studied (Puleston and Simon, 2014), nothing is known about the requirement of autophagy in antigen-experienced T cells. The T cell memory pool has previously been shown to be controlled by PI3K/Akt and AMPK signaling as well as mTOR (mammalian Target Of Rapamycin) inhibition (Araki et al., 2009; Kim et al., 2012; Rolf et al., 2013), all of which also control autophagy (Jung et al., 2010). Indeed, T cell memory responses can be improved with the mTOR inhibitor rapamycin (Araki et al., 2009). Interestingly, rapamycin also rejuvenates HSCs in old mice (Chen et al., 2009). Neither of these studies addressed autophagy as a contributing mechanism.
Evidence for age-related declining levels of autophagy stems largely from lower organisms such as yeast, flies, and worms (Rubinsztein et al., 2011). A recent study showed that the polyamine spermidine induces autophagy and thereby prolongs life span in model organisms (Eisenberg et al., 2009). Our own work demonstrated decreased levels of autophagy in CD8+ T cells of old individuals (Phadwal et al., 2012).
In this study, investigating a mouse model lacking the essential autophagy gene Atg7 specifically in T cells, we find peripheral T cell lymphopenia, leading to proliferation and an activated phenotype within the CD8+ T cell compartment. While Atg7−/− T cells respond normally during the early stages of live viral challenge, a severely compromised memory CD8+ T cell compartment was found in response to influenza and murine cytomegalovirus (MCMV). Using bone marrow (BM) chimeras, we excluded that this is due the effects of lymphopenia; poor CD4+ T cell help; exhaustion, or altered cytokine receptor expression. Moreover, autophagy was found to be highest in antigen-specific CD8+ T cells when compared to naïve cells. Antigen-specific Atg7−/− CD8+ T cells also underwent more cell death at the time of memory formation, display compromised mitochondrial health, and increased expression of the glucose receptor GLUT1, a marker for glycolysis. Furthermore, recall CD8+ T cell responses to repeat immunizations and vaccination protocols were greatly diminished. This being reminiscent of the human ageing immune system (Haq and McElhaney, 2014), we confirmed reduced autophagy at the transcriptional and functional level in murine T cells from old mice. Importantly, we were able to restore the CD8+ T cell memory response in old mice with the autophagy-inducing compound spermidine, but not in autophagy-deficient mice. Finally, we found that spermidine induces autophagy independently of mTOR in T cells. Enhancing autophagy in an mTOR-independent manner may provide a safe way to improve vaccine responses in the elderly.
Atg7flox/flox mice were bred with CD4-Cre mice to generate mice with defective autophagy in both CD4+ and CD8+ T lymphocytes (T-Atg7−/−). Successful excision and thereby absence of Atg7 mRNA and Atg7 protein was confirmed in purified T cells (Figure 1—figure supplement 1A and B, respectively). Using the imaging flow cytometer (ImageStream) to count LC3 puncta in CD4+ and CD8+ T cells (Phadwal et al., 2012), we demonstrated that functional autophagy was significantly diminished in Atg7−/− CD8+ T cells (Figure 1—figure supplement 1C with examples of ImageStream images in right panel). In addition, using a classical technique to detect lipidated LC3, we confirmed that basal autophagy was diminished in the presence and absence of the autophagy flux inhibitor Bafilomycin A (Figure 1—figure supplement 1D).
Previous reports have noted a number of changes to the naïve CD8+ T cell compartment in the absence of autophagy, with T cell lymphopenia, a consistent observation (Pua et al., 2007; Puleston and Simon, 2014). We set out to investigate if an altered naïve CD8+ T cell compartment exists in T-Atg7−/− mice. We confirmed observations from previous reports using similar autophagy-deficient mouse models (Pua et al., 2007, 2009) that thymic development of CD4+ and CD8+ T cells was normal in 6-week old T-Atg7−/− mice (Figure 1A). However, mice were lymphopenic for both CD4+ and CD8+ T cells in the lymph nodes and blood (Figure 1B,C). Moreover, Atg7−/− CD8+ T cells exhibited an activated phenotype with increased CD44 expression (Figure 1D) and decreased CD62L expression (Figure 1E), resembling a ‘virtual memory’ compartment (Akue et al., 2012). We observed similar frequencies of central effector memory CD62L+CD44hi, however, T-Atg7−/− mice accumulated CD8+ T cells with an effector memory phenotype (CD62L−CD44hi) (Figure 1—figure supplement 1E). Similarly, data from a mouse model in which another essential autophagy gene, Atg5, was deleted under the hematopoietic stem cell-specific promoter Vav, showed T cell lymphopenia and the expanded virtual memory T cell compartment (CD8+CD44+) suggesting this phenotype is not Atg7 specific (Figure 1—figure supplement 2A and B). Next, we established that proliferation was increased in the activated CD44hi CD8+ T cell compartment by Ki-67 staining (Figure 1F). The observed activated phenotype and increased cell turnover in Atg7−/− CD8+ T cells are likely driven by homeostatic proliferation in an attempt to fill the depleted T cell niche. Indeed, the expression of the homeostatic proliferation marker CD24 (Li et al., 2006) was found to be significantly increased on Atg7−/− CD8+ T cells (Figure 1G). To investigate whether lymphopenia drives this activated phenotype in the CD8+ T cell compartment, we generated 1:1 mixed bone marrow (BM) chimeras from CD45.2+ T-Atg7−/− BM mixed with CD45.1+ wild-type BM. Both BMs contributed equally to form the new hematological system (Figure 1—figure supplement 2C). Atg7−/− CD8+ T cells were still diminished even in the presence of a replete T cell niche, suggesting the survival defect previously described for autophagy-deficient T cells (Pua et al., 2007; Mortensen et al., 2010) is cell-intrinsic (Figure 1—figure supplement 2D). However, the activated Atg7−/− CD8+ T cell phenotype was no longer detected in BM chimeras as measured by the frequency of donor CD45.2+ CD8+ T cells found to be CD62L+ (Figure 1H) and CD44hi (Figure 1I). These data indicate that the observed homeostatic proliferation and the change in surface phenotype of Atg7−/− CD8+ T cells are driven by lymphopenia and are not cell-intrinsic.
Previous studies have shown a role for autophagy in naive T cell organelle homeostasis and survival (Pua et al., 2009; Jia and He, 2011). However, the importance of autophagy in CD8+ T cells responding to infection is unknown. To investigate this, we challenged T-Atg7−/− mice with influenza (PR8 strain) and MCMV. In T-Atg7−/− mice, we found normal expansion of the antigen-specific effector CD8+ T cell (CD8+ Teff) compartment using influenza-specific tetramers on day 10 (peak response) in the lungs (Figure 2A). However, due to the pre-existing lymphopenia observed in naïve mice, the absolute counts were diminished (Figure 2—figure supplement 1A). The CD8+ Teff response to MCMV in the blood on day 7 was also normal (Figure 2B) (Hutchinson et al., 2011). However, the ability of T-Atg7−/− mice to form memory CD8+ T cells (CD8+ Tmem) to both influenza and MCMV is severely compromised (Figure 2C,D). Performing serial bleeding on influenza infected mice over time, we demonstrated a catastrophic collapse of the antigen-specific CD8+ T cell pool at day 21, resulting in a failure to retain CD8+ Tmem in T-Atg7−/− mice (Figure 2E). Interestingly, the response to the ‘inflationary’ epitopes m38 and IE3 from MCMV is also compromised (Figure 2F). In response to these epitopes, wild-type CD8+ T cells continue to expand throughout MCMV chronic infection. However, Atg7−/− CD8+ T cells fail to inflate and instead undergo a dramatic contraction leading to a failure to form a MCMV-specific CD8+ T cell memory pool. This profound CD8+ T cell contraction in T-Atg7−/− mice is also observed in response to a conventional, non-inflating MCMV epitope (m45, Figure 2—figure supplement 1B). While viral titers against influenza in the lungs of wild-type and T-Atg7−/− mice were comparable at day 3 of infection, they were significantly higher on day 6 in T-Atg7−/− mice (Figure 2G). This is most likely due to the significantly lower absolute number of antigen-specific effector CD8+ T cells. As T-Atg7−/− mice survived influenza challenge, we expect that the virus is eventually cleared in all mice. In keeping with these findings, autophagy levels (CytoID) are significantly increased in the antigen-specific CD8+ T cell compartment compared to naïve T cells (CD44lo) in response to influenza in both spleen (Figure 2H) and lungs (Figure 2I), indicating autophagy is induced upon antigen stimulation in vivo.
To exclude that a failure to maintain a CD8+ Tmem pool is caused by lymphopenia in T-Atg7−/− mice, we performed viral challenge experiments in 1:1 mixed BM chimeras, facilitating the observation of antigen-specific Atg7−/− CD8+ T cell responses in a replete T cell environment. Even in the context of a BM chimera, Atg7−/− CD8+ T cells fail to generate a CD8+ Tmem pool following influenza infection, suggesting this defect is cell intrinsic (Figure 3A). By using BM chimeras to observe antigen-specific Atg7−/− CD8+ T cell responses, we excluded a number of explanations as to why T-Atg7−/− mice fail to form CD8+ Tmem: (1) lymphopenia, (2) defective CD4+ T cell help, and (3) the excision of Atg7 in CD4-expressing antigen-presenting cells affecting CD8+ T cell priming. Furthermore, a defect in the frequency of memory precursor cells might also impact upon CD8+ Tmem formation in T-Atg7−/− mice. Mixed BM chimeras demonstrated that the frequency of short-lived effector (SLEC, CD127+KLRG1−) and memory precursor (MPEC, CD127−KLRG1+) CD8+ T cells was in fact normal in T-Atg7−/− mice (Figure 3B). We then tested whether the lack of memory response is due to exhaustion of autophagy-deficient antigen-specific CD8+ T cells. While in T-Atg7−/− mice, we found a sharp increase of antigen-specific CD8+ T cells co-expressing the exhaustion markers PD-1+ and TIM-3+; this was not found in the mixed BM chimeras. This indicates that without lymphopenia, exhaustion is not a hallmark of Atg7−/− CD8+ T cell responses and cannot explain the diminished CD8+ Tmem compartment (Figure 3C). We then sought to determine if altered expression of cytokine receptors crucial for CD8+ Tmem maintenance could explain the defective CD8+ Tmem compartment. However, both Il-7Rα (CD127) and Il-15Rα were normally expressed on Atg7−/− MCMV-specific CD8+ T cells (Figure 3D,E).
Finally, we tested whether autophagy compromises effector/memory differentiation and measured two transcription factors typically required during this differentiation. We found that the expression of IRF4, responsible for sustaining the expansion and differentiation of CD8+ Teff (Yao et al., 2013), and EOMES, a factor that promotes CD8+ Tmem formation (Intlekofer et al., 2005), behaved normally over time in Atg7−/− CD8+ T cells (Figure 3—figure supplement 1A and B).
To understand the mechanism that leads to the failure to maintain a memory compartment in the absence of autophagy, we next checked if Atg7−/− CD8+ T cells were undergoing more cell death than wild-type cells. While this is well described for naïve autophagy deficient T cells (Puleston and Simon, 2014), it had not been analyzed in antigen-specific T cells. As expected, in wild-type mice challenged with MCMV, we found highest levels of cell death among antigen-specific CD8+ T cells just after the peak of the effector phase on day 9, whereas in T-Atg7−/− mice, cell death was found to increase over time (Figure 4A). This could not be explained by a change in levels of the anti-apoptotic protein Bcl-2 (Figure 4—figure supplement 1A). The control of mitochondrial quality and reactive oxygen species (ROS) via mitophagy, the degradation of mitochondria, has been found to prevent cell death in T cells (Pua et al., 2009). In keeping with this, mitochondrial content (Figure 4B) and mitochondrial ROS (Figure 4C) were significantly increased in Atg7−/− antigen-specific CD8+ T cells. While this likely explains the increased cell death, as shown for other hematopoietic cells (Mortensen et al., 2010) and T cells (Pua et al., 2009), mitophagy is also thought to be essential for maintenance of healthy mitochondrial energy generation. This notion is consistent with our data in other autophagy-deficient hematopoietic cell types (macrophages and primary leukemic lines, submitted) demonstrating increased glycolytic enzymes by proteomic analysis, increased lactate production and decreased oxygen consumption using metabolic seahorse measurements. Indeed, studies by Pearce et al showed that formation of the CD8+ Tmem pool is accompanied by a switch to mitochondrial respiration (Pearce et al., 2009; Sukumar et al., 2013). However, in the physiological viral infection models used here, aiming to mimic human infection, the scarcity of antigen-specific CD8+ T cells prevented us from performing these metabolic measurements. In addition, due to the loss of CD8+ Tmem in the absence of Atg7 by day 30, any metabolic analysis was restricted to early time points when antigen-specific CD8+ T cells are still present in T-Atg7−/− mice. We resorted to the measurement of a surrogate marker of glycolysis, the glucose transporter GLUT-1 on antigen-specific CD8+ T cells by two different techniques, (a) the fluorescently labeled GLUT-1 binding domain of HTLV (human T cell leukemia virus), which specifically detects GLUT-1 (Manel et al., 2003; Kinet et al., 2007), and (b) a GLUT-1 antibody staining. As expected, GLUT-1 is upregulated on CD8+ Teff (day 9) and then downregulated on CD8+ Tmem (day 22) in wild-type mice as CD8+ T cells switch to mitochondrial respiration (Figure 4D). However, antigen-specific Atg7−/− CD8+ Teff expresses more GLUT-1 and downregulation does not occur to the same extent at the later time points compared to WT cells (day 22) (Figure 4D). This suggests that autophagy supports the metabolic switch during the differentiation from Teff to Tmem. This was confirmed using the GLUT-1 antibody (Figure 4—figure supplement 1B). However, treatment with the anti-diabetic drug metformin that induces mitochondrial β-oxidation metabolism in T cells (Pearce et al., 2009) did not rescue the memory T cell compartment in this model (data not shown).
We then tested whether T-Atg7−/− mice were able to mount a recall CD8+ T cell response to a secondary infection. We primed T-Atg7−/− mice with PR8 (H1N1) followed by heterologous challenge with the X31 strain of influenza (H3N2). By challenging with a heterologous virus strain expressing different surface antigens, it is possible to significantly diminish the influence of antibodies in mediating immunity to secondary infection. Thus, heterotypic immunity relies heavily on cross-reactive CD8+ T cell responses (Zweerink et al., 1977; Townsend et al., 1986), as opposed to homotypic immunity (for example PR8 primed, PR8 challenged) to which influenza-specific antibodies contribute (Townsend et al., 1986; Epstein and Price, 2010). While the wild-type mice mounted a fast and strong recall response upon X31 challenge in PR8-primed mice (PR8 + X31), this was drastically diminished in T-Atg7−/− mice in the lungs on day 5 (Figure 5A, absolute counts in Figure 5—figure supplement 1A). Even when three live virus immunizations were administered (PR8 primed, challenged with X31 then with PR8), T-Atg7−/− mice were unable to mount recall responses. Surprisingly, T-Atg7−/− mice survived the heterotypic viral challenges despite the vastly diminished numbers of secondary CD8+ Teff.
Using an established non-replicating pseudotyped influenza vaccination protocol (Powell et al., 2012), we next tested whether H1N1 vaccinated T-Atg7−/− mice could mount secondary CD8+ T responses to heterotypic viral challenge. Mice were vaccinated twice, 22 days apart then challenged with X31 influenza. Large numbers of influenza NP-specific CD8+ T cells were detected in the lungs of vaccinated wild-type mice 5 days post-challenge, but not in T-Atg7−/− mice (Figure 5B). When the CD8+ T cell kinetics to the vaccine regimen were followed over time in the blood of T-Atg7−/− mice, influenza-specific CD8+ T cells were detected at normal frequencies to primary immunization but the secondary ‘booster’ vaccine was unable to induce an increase in NP-specific CD8+ T cell frequency like it could in wild-type mice (Figure 5C). Similarly, vaccinated T-Atg7−/− mice failed to generate significant CD8+ T cell responses to viral challenge in the blood (Figure 5D). As before, all mice survived the live viral challenge (data not shown). In summary, these data indicate that autophagy is required for the CD8+ T cell recall response to either repeated immunizations with live virus or vaccination followed by live viral challenge. However, these results were not repeated in a mixed bone marrow chimera setting, making it difficult to exclude that lymphopenia, CD4+ T cell help or CD4-expressing antigen-presenting cells might be responsible for defective recall response in T-Atg7−/− mice.
We reasoned that a natural setting where these findings might be applicable is the aged organism, where reduced autophagy levels are found in many organs and cell types (Rubinsztein et al., 2011). Indeed, we have previously shown that autophagy levels are significantly reduced in the CD8+ T cells of aged healthy human donors (>65 years) as compared to young donors (<30 years) (Phadwal et al., 2012). Taking results presented here so far into account, we hypothesized that these low levels may contribute to the poor CD8+ Tmem formation and inefficient influenza vaccination observed in the elderly (Kapasi et al., 2002; Haynes et al., 2003; Kedzierska et al., 2012).
We addressed whether diminished CD8+ Tmem formation can be improved in the elderly by modulating autophagy. First, we showed that mRNA levels of essential autophagy genes are decreased in sorted CD8+ T cells from naïve old mice (2 years) as compared to young mice (8 weeks). The CD8+ CD44hi memory compartment is particularly affected (Figure 6A). CD8+ T cells from old mice also showed significantly decreased autophagic flux detected by counting LC3 spots in NP-specific CD8+ T cells from young and old mice both in the presence and absence of an autophagy flux inhibitor (Figure 6B,C). This was confirmed by using two flow cytometry based autophagy detection, also in NP-specific CD8+ T cells (Figure 6—figure supplement 1A and B).
Next, we chose the autophagy-inducing, naturally occurring compound spermidine to modulate autophagy in vivo, as it had been safely and effectively administered to mice previously (Eisenberg et al., 2009). We first confirmed that spermidine induces autophagy in T cells in vitro in a dose and time-dependent manner shown by increased levels of LC3-II (Figure 6D). Spermidine levels in the blood are known to decrease with age (Pucciarelli et al., 2012). To mimic this, we used the inhibitor of the natural spermidine synthesis pathway DFMO in the human Jurkat T cell line and found that autophagy levels detected by LC3 western blot significantly dropped in BafA treated samples and untreated samples (Figure 6E). Autophagy levels could be rescued by the addition of very low levels of spermidine in T cells (Figure 6E). As mTOR inhibition, such as achieved with rapamycin, is well known for its multiple side effects (Lamming et al., 2013), we confirmed that spermidine induces autophagy in T cells in an mTOR-independent manner. Rapamycin completely abolished the phosphorylation of S6K, a major target downstream of activated mTOR, whereas spermidine had no such effect (Figure 6F). Finally, we administered spermidine to old and young mice via the drinking water at concentrations known to induce autophagy (Eisenberg et al., 2009) during the influenza vaccination protocols as in Figure 5B–D. In response to first and second vaccination, and as observed in ageing humans, old mice do not mount a robust CD8+ T cell response as compared to young mice. Spermidine dramatically enhanced influenza-specific CD8+ T cell responses in old vaccinated wild-type mice but not in old vaccinated T-Atg7−/− mice as tracked over time in blood (Figure 6G). Similarly, the response to live influenza challenge in the blood was improved twofold to threefold (back to levels similar to young mice) when spermidine was administered to old mice, but not in the absence of autophagy (Figure 6H). In the lungs, the number of NP-specific CD8+ T cells responding to influenza challenge in vaccinated old mice were improved fivefold to sixfold in the presence of spermidine, but had little effect on the response of aged T-Atg7−/− mice (Figure 6I).
Hematopoietic and immune health both decline significantly with age (Beerman et al., 2010). With the ageing population, this has become a substantial health and socio-economic problem for the developed world. Our work sheds light on the cellular mechanisms of immune ageing and how to improve responses to vaccination in the elderly.
The naïve T cell compartment in the absence of several different essential autophagy genes has been extensively analysed (Puleston and Simon, 2014). These models uniformly demonstrated increased damaged mitochondria leading to cell death and peripheral lymphopenia. In this study, we show how this lymphopenia drives the remaining T cells to take on an activated/memory phenotype as they proliferate in an attempt to re-fill the T cell niche, often termed ‘virtual memory’ (Jia and He, 2011). Thus, we provide a link between lymphopenia and the formation of the ‘virtual memory’ compartment and highlight the significant changes in T cell surface phenotype that can occur in a lymphopenic environment. Interestingly, the virtual memory compartment is also a hallmark of the ageing adaptive immune system. This observed phenotype in naïve mice would have precluded a coherent analysis of antigen-activated T cells; however, the use of mixed BM chimeras crucially excluded a contribution of the skewed naïve repertoire to the CD8+ Tmem phenotype.
In this study, we showed a novel and essential link for autophagy in the formation of CD8+ Tmem to infection. The absence of autophagy also dramatically altered the ability of CD8+ T cells to respond to secondary infection. Interestingly, the severely depleted CD8+ T cell recall response did not prevent T-Atg7−/− mice from surviving a lethal secondary heterotypic influenza challenge. Influenza virus is typically controlled by both antibodies and cellular immunity. However, in a heterotypic challenge, the surface hemagglutinin and neuraminidase (recognized by antibodies) differ between the two heterotypic strains, while the viral internal proteins (presented by MHC class I to CD8+ T cells) remain the same, leaving the CD8+ T cells to provide protection (Rimmelzwaan et al., 2007). The unique protective role of CD8+ T cells in heterotypic immunity was described several decades ago in mice (Rimmelzwaan et al., 2007). The observation that the majority of CD8+ T cell epitopes are cross-reactive between subtypes and are located in the most conserved regions of the internal proteins (nucleoprotein and matrix protein) confirms their role. In humans, the evidence, typical for human studies, is sparse and more circumstantial. A study from 1983 by McMichael et al demonstrated that in experimentally infected individuals, virus-specific cytotoxicity inversely correlated with the extent of virus shedding in the absence of virus-specific antibodies for the strain that was used for infection (McMichael et al., 1983). More recently, Lalvani et al found higher frequencies of pre-existing T cells to conserved epitopes in individuals who developed less severe illness in the 2009 H1N1 flu pandemic in the absence of cross-protective antibodies (Sridhar et al., 2013). We would postulate therefore that the survival of the T-Atg7−/− mice after the secondary heterotypic challenge relies on the very few effector CD8+ T cells generated. These data also suggest that eliciting CD8+ T cell memory responses in influenza vaccination is highly desirable, particularly to protect from pandemic flu.
This also raises interesting questions as to why such robust secondary T cell responses have evolved when survival can be achieved with a fraction of what is observed normally in nature. Although no CD8+ Tmem cells can be detected by conventional tetramer technology 20–30 days post-immunization in T-Atg7−/− mice, some memory cells must remain below the detection limit at very low frequency. In addition, these Atg7−/− CD8+ T cells must maintain normal functional and proliferative capacity as they are detected at early time points after secondary immunization, characteristic of true memory T cell kinetics.
To explain how autophagy affects the maintenance of CD8+ Tmem cells, we addressed two alternative hypotheses experimentally: (1) accumulation of cellular damage affects the long-lived CD8+ Tmem in particular and (2) autophagy is required for the switch from glycolysis to mitochondrial respiration important for the survival of CD8+ Tmem cells. Regarding the first one, we show evidence for the accumulation of mitochondria and ROS in the absence of autophagy. However, a limitation of our study is, we did not test for accumulation of other organelles and protein aggregates. As for the second hypothesis, initial studies involved TRAF6 (TNFR-associated factor 6) in the regulation of CD8+ Tmem development by modulating fatty acid metabolism and thereby increasing mitochondrial respiration (Pearce et al., 2009; van der Windt et al., 2012). Interestingly, TRAF6, as an E3 ubiquitin ligase, has recently been shown to stabilize essential proteins in the autophagy pathway such as Ulk1 (Nazio et al., 2013) and Beclin-1 (Shi and Kehrl, 2010). We therefore hypothesize that TRAF6 controls metabolism via autophagy and propose three mechanisms contributing to autophagy's role in mitochondrial respiration: (1) through lipophagy, the degradation of lipids (Weidberg et al., 2009), autophagy provides the fatty acids that fuel the Krebs cycle with Acetyl-CoA though β-oxidation, (2) through degradation of glycolytic enzymes (Xiong et al., 2011), and (3) through mitophagy, autophagy provides mitochondrial quality control that is required for functional mitochondrial ATP generation. We provide evidence for the latter mechanism here. This suggests that autophagy is important in the control of metabolic pathways in T cells. Interestingly both the accumulation of damaged mitochondria/oxidative stress as well as a bias to preferentially use glycolysis are hallmarks of the ageing cell (Hipkiss, 2006).
In this study, we showed that autophagy levels are impaired in CD8+ T cells from aged mice. Using spermidine, we could dramatically improve the CD8+ T cell response to vaccination and infection in elderly mice in an autophagy-dependent manner. However, aged CD4+ T cells also undergo immune senescence. While inducing autophagy with spermidine in the CD8+ T cell compartment clearly contributes to the increased numbers of antigen-specific CD8+ T cells, the limitation of these experiments is that we cannot gauge the contribution of improved CD4+ T cell function to CD8+ T cell numbers. This will be included in future studies.
These results offer the first cell-intrinsic explanation as to why T cell memory is defective in old age. Spermidine is a pleiotropic compound and its major function has been described in yeast as an inhibitor of histone acetyl transferases, inducing epigenetic changes to autophagy-related gene expression (Eisenberg et al., 2009). We showed that spermidine operates independently of mTOR to induce autophagy. These findings offer the prospect of improving vaccine T cell responses in the elderly through spermidine in an mTOR-independent fashion. However, no other ways of inducing autophagy were tested here. We expect that fasting or other mTOR-independent drugs such as resveratrol (Morselli et al., 2009; Morselli et al., 2010) may also be beneficial for CD8+ Tmem maintenance. However, spermidine is significantly more attractive than previously published Tmem-boosting compounds such as metformin (Pearce et al., 2009) and rapamycin (Araki et al., 2009), that come with unwelcome side effects and toxicity in humans. The elucidation of the precise role of spermidine will be the subject of future work and will enable its development as a safe, readily administrable immune-modulating drug.
CD4-Cre mice (Lee et al., 2001) were from Adeline Hajjar (University of Washington) and crossed with Atg7flox/flox (Komatsu et al., 2005) to obtain T-Atg7−/− mice (CD4-Cre+ Atg7+/+) on a C57BL/6 background. Unless otherwise stated, all mice were 6–12 weeks of age at the start of each experiment and were age and sex matched. CD4-Cre− Atg7+/+ mice were used as wild-type controls and were littermates where possible. No phenotype was observed in CD4-Cre+ Atg7+/− mice. Old mice and young control mice were purchased from Charles River, UK. C57BL/6 SJL CD45.1 mice for bone marrow chimeras were purchased from Biomedical Services, Oxford. All mice were housed in Biomedical Services, Oxford and animal experiments were approved by the local ethical review committee and performed under UK project license (PPL 39/2809).
The following antibodies were used for flow cytometry (antibody clone in brackets): CD8 (Ly2) PE/PE-CY7; CD8 (53-6.7) FITC/eF450/PE-Cy7; CD4 (GK1.5) PE/FITC/APC; TCRβ (H57-597) FITC/PE/PE-Cy7/APC; CD3 (145-2C11) eF450/APC; CD62L (MEL-14) FITC/PE-Cy7; CD44 (IM7) FITC/PE-Cy7; KLRG1 (2F1) FITC/PE-Cy7; IRF4 (3E4) FITC; EOMES (Dan11mag) PE-Cy7; CD127 (A7R34) FITC/PE/eF450; Ki-67 (SolA15) eF450; CD24 (M1/69) APC; CD16/32 (93) purified Fc block; CD45.2 (104) eF450; all from eBioscience (San Diego, CA, USA). PD-1 (29F.1A12) PE-Cy7; PD-1 (RMP1-30) PE; CD45.2 (104) PE-Cy7; TIM-3 (B8.2C12) PE/APC; Bcl-2 (BCL/10C4) PE; all from Biolegend (San Diego, CA, USA). Glut1 (q) PerCP; IL-15Rα (BAF551) biotinylated; both from R&D Systems (Minneapolis, USA).
For surface staining, cells were suspended in PBS, 2% FCS, 5 mM EDTA and stained at 4°C. Anti-CD16/32 (Fc Block, eBioscience) was generally added to antibody mix to minimize non-specific staining. LIVE/DEAD Fixable Violet Dead Cell Stain Kit (Life Technologies) was used prior to surface staining to exclude dead cells. For cytoplasmic intracellular staining (Bcl-2), cells were stained for surface antibodies then fixed in IC fixation buffer before permeabilisation with perm buffer (eBioscience). Cells were then suspended in perm buffer at RT for antibody staining. For nuclear targets (IRF, EOMES, Ki-67), after surface staining cells were fixed and permeabilised with FoxP3 Fixation/Permeabilisation kit (eBioscience) before resuspension in perm buffer for intracellular staining at RT.
Absolute cell counts were performed on peripheral blood taken from the lateral tail vein of live animals, collected in heparin-coated tubes (Microvette 300, Sarstedt [Nümbrecht, Germany]) to avoid coagulation. Cell counts were calculated with BD TruCount tubes (BD Bioscience, NJ, USA) according to the manufacturer's instructions.
Tetramers were generated as previously described (Altman et al., 1996) and MHC-Class I monomers stored at −80°C. Biotinylated monomers were tetramerized with Streptavidin PE or APC at the right concentration to achieve 1:1 ratio with biotin binding sites and added in 1/10th volumes waiting 10 min between additions. Tetramerized complexes were stored at 4°C. Peptide sequences for MCMV tetramers were as follows: m45 985HGIRNASFI993, H-2Db-restricted; m38 316SSPPMFRV323, H-2Kb-restricted; IE3 416RALEYKNL423, H-2Kb-restricted. The peptide sequence for the influenza tetramer was as follows: NP 366ASNENMETM374, H-2Db-restricted. Cells were always stained with tetramers prior to surface antibody staining in PBS, 2% FCS at 37°C for 15 min. Tracking tetramer-positive cells over time in the blood was performed by serially bleeding the lateral tail vein. After erythrocyte lysis with red cell lysis buffer (eBioscience), remaining white cells were stained with tetramer and surface antibodies as described above.
Autophagy detection by flow cytometry was measured using the CytoID Autophagy Detection Kit (Enzo Life Science, Exeter, UK). Splenocytes and cells isolated from the lung were first stained with CytoID according to the manufacturer's instructions, prior to tetramer and surface antibody staining. Autophagy was also measured using flow cytometry by quantifying LC3-II mean fluorescence intensity using the FlowCellect Autophagy LC3 Antibody-based Assay Kit (FCCH100171, Merk-Millipore, MA, USA) according to the manufacture's instructions and always following cell surface antibody staining. Use of this kit includes a step where cytosolic LC3-I is washed from the cell, leaving only membrane bound LC3-II prior to staining.
For apoptosis detection, splenocytes were stained with m45-tetramer and surface antibody as described above and then stained with LIVE/DEAD Fixable Violet Dead Cell Stain Kit. Cells were finally stained with Annexin V PE-Cy7 (eBioscience) in Annexin V binding buffer at room temperature. Apoptotic cells were determined as LIVE/DEAD cell dye negative (live cells), Annexin V positive.
GLUT-1 was measured through binding to its ligand, the receptor binding domain (RBD) of a recombinant glycoprotein from the human T lymphotrophic virus (HTLV) fused to eGFP (HRBD-eGFP) (Montel-Hagen et al., 2008).
For mitochondrial mass analysis, cells were stained with MitoTracker Green (Life Technologies, Carlsbad, CA, USA) at 150 nM in PBS, 2% FCS for 30 min at 37°C after tetramer and surface antibody staining. To measure mitochondrial superoxide production, MitoSOX Red (Life Technologies) was used at final concentration of 5 µM from a 5 mM stock in PBS, 2% FCS for 30 min at 37°C following tetramer and cell surface staining. All flow cytometry experiments were performed on a Cyan flow cytometer (Beckman Coulter, Brea, CA, USA).
BM cells were extracted from a single 8-week old wild-type, T-Atg7−/− (both CD45.2+), and C57BL/6 SJL mouse expressing CD45.1. After erythrocyte lysis, 3 × 106 wild-type or T-Atg7−/− BM cells were added to 3 × 106 CD45.1+ BM cells (1:1 CD45.2+:CD45.1+) in a total volume of 200 µl PBS. The 1:1 BM mix was injected i.v 2 hr after lethal irradiation (450 cGy twice, 4 hr apart) to C57BL/6 SJL CD45.1+ recipients (total of 6 × 106 BM cells per mouse in 200 µl). After 8 weeks of reconstitution, mixed BM chimera was immunized with MCMV or PR8 influenza, or left unimmunized. WT and T-Atg7−/− mice were always used as controls.
Mice were immunized i.v. with 1 × 106 p.f.u MCMV in 100 µl (Smith strain ATCC: VR194). Unimmunized controls were injected with 100 µl PBS i.v. For influenza infections, mice were administered intra-nasally with either A/PR/8/34 (PR8, H1N1 Cambridge) influenza or X31 (H3N2) influenza at the stated dose in 50 µl viral dilution media (VDM; DMEM, 0.1% BSA, 10 mM HEPES, 100 U/ml penicillin, 100 µg/ml streptomycin, and 2 mM glutamine; all from Sigma, St Louis, MO, USA). Mice were anaesthetized with isofluorane and droplets of VDM-containing virus were applied to the nares until the total 50 µl was inhaled. Unimmunized mice were always used as controls (50 µl of VDM alone). For influenza vaccination, mice were immunized intra-nasally with 32 HAU pseudotyped H1N1 influenza (S-Flu) (Powell et al., 2012), using the influenza infection protocol described above, and challenged with 32 HAU X31. Unvaccinated and fully naïve mice were used as controls in all influenza vaccine experiments. In unvaccinated mice that received X31 challenge, a combination of weight loss and clinical score was used as a humane endpoint.
Cells were purified with a MoFlo cell sorter (Beckman Coulter) by their surface markers. RNA was extracted using RNeasy Kit (Qiagen, Hilden, Germany) and quantified using a Nanodrop spectrophotometer (Thermo Scientific, Waltham, MA, USA). RNA was reverse transcribed (RT) using a High Capacity RNA to cDNA kit (Applied Biosystems (AB), Foster City, CA, USA). Resulting cDNA was stored at −20°C. Real-time quantitative PCR using comparative Ct method (ΔΔCt) was utilized to evaluate gene expression using validated TaqMan probes (AB) on a 7500 Fast Real-time PCR machine (AB). Conditions: (1) 50°C, 2 min; (2) 95°C, 10 min; (3) 95°C 15 s; (4) 60°C 1 min; 40 cycles of 3–4. The assay IDs for the primers of the analyzed genes are as follows: Mm00504340_m1 (Atg5), Mm00512209_m1 (Atg7), Mm01264428_m1 (Atg9), Mm00470550_m1 (Atg10), Mm00503201_m1 (Atg12), Mm0051717_m1 (beclin1), Mm00458724_m1 (Map1lc3a), Mm01545399_m1 (hprt), Mm99999915_g1 (gapdh).
ImageStream (Amnis imaging flow cytometer, MA, USA) has previously been used to determine autophagic flux (Phadwal et al., 2012). To determine LC3 spot count, we stained cells for LC3-II (following cell surface staining) using the FlowCellect Autophagy LC3 Antibody-based Assay Kit (FCCH100171, Merk-Millipore) according to the manufacture's instructions. Before LC3 detection, to assess autophagic flux, cells were incubated for 2 hr with the autophagy flux inhibitor provided by the kit specified and according to the manufacturer's instructions. LC3 spot count was quantified using Ideas software (Amnis), which contains a specialised objective spot counting feature. Images collected were all at ×60 magnification.
3 × 106 Jurkat cells (human CD4+ T cell line) or 5 × 106 purified primary CD8+ T cells were lysed on ice using 100 μl 1 × NP-40 Lysis Buffer. Protein concentration in supernatant was measured using BCA Protein Assay Kit (PI-23227, Thermo Scientific), and reducing Laemmli Sample Buffer was added to make protein samples for SDS-PAGE. Proteins of 30–50 μg per lane were separated on 16% SDS-PAGE and transferred to PVDF membrane (IPFL00010, Millipore, MA, USA). After blocking with 5% skim milk, the membrane was blotted using the following primary antibodies: LC3 (L8918, Sigma) (1:1000), GAPDH (MAB374, Millipore) (1:10,000), pS6 (2211, Cell Signaling Technology, Danvers, MA, USA) (1:5000). For S6 blotting, membranes were blotted with anti-pS6 first, then stripped for re-blot using primary antibody against S6 (2217, Cell Signaling Technologies) (1:1000). IRDye secondary antibodies were bought from LI-COR (Lincoln, NE, USA): (926-32,211, 926-68,020) (1:15,000). For the purification of primary CD8+ T cells, cells were negatively selected from splenocytes using the CD8+ T cell Isolation kit (130-104-075, Miltenyi, Bergisch Gladbach, Germany) according to the manufacturer's instructions.
Determination of the 50% tissue culture infective dose (TCID50) was performed on MDCK-SIAT1 cells in a 96-well flat-bottom plate performed by serial dilution of lung homogenates onto 3 × 104 MDCK-SIAT1 cells followed by incubation for 72 hr at 37°C. Virus was then detected by hemagglutination, where 50 µl 1% (vol/vol) human erythrocytes (adjusted so that a 1:2 dilution gave an optical density at 600 nm) was added to 50 µl of the serially diluted lung homogenates/MDCK-SIAT1 supernatant in a 96-well V-bottom plate. Hemagglutination was analyzed by the loss of teardrop formation after tilting the plate. TCID50 was calculated as described by Reed and Muench (1938).
All data were presented as mean ± s.e.m. p values were determined using either a Mann–Whitney U-test or two-tailed Student's t test using GraphPad Prism software. Significant statistical differences are indicated in the figure legends or on the graphs themselves.
Mice were administered spermidine in the drinking water 21 days prior to immunization through to the experimental endpoint. Spermidine was added at a concentration of 5 mM from a 1 M aqueous stock. Spermidine-containing drinking water was replenished every 2–3 days.
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Beth LevineReviewing Editor; UT Southwestern Medical School, United States
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 “Autophagy as a critical regulator of CD8+ T cell memory and a route to improved vaccination in the elderly” for consideration at eLife. Your article has been favorably evaluated by Tadatsugu Taniguchi (Senior editor), a member of the Board of Reviewing Editors, and 2 expert reviewers in your field.
The Reviewing editor and the 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.
The reviewers and Reviewing editor all feel that, overall, this is an interesting, well-performed study addressing the role of autophagy and ageing effects on autophagy in viral-specific CD8 memory T cells. We think that this study has important potential implications for understanding the role of autophagy in a crucial basic aspect of immunology, T cell memory, and, as pointed out by the authors, has potential clinical implications for improving vaccine responses in the elderly.
The reviewers have made several suggestions to further improve the manuscript. We are enclosing a list of the major points. Some of the points request further text explanations or modifications of the data analysis. Other points suggest a need for some additional data; however, as a general principle, given the overall enthusiasm for the work and the editorial policies of eLife, if these points cannot be quickly addressed by new experimental data, we ask that you revise the text (Discussion) to acknowledge the limitations of the present study.
One exception to this principle is point #8; although we recognize that your lab has previously published studies using the BDS feature to measure autophagic flux in lymphocytes, we do believe that, prior to publication, this assay should be confirmed by at least one additional autophagic flux assay to more convincingly demonstrate a defect in autophagic flux in T/Atg7-/- cells. Another exception is point #9; the LC3 assays in Figure 6D and 6E are performed in the same cells; the difference in the blots for control cells suggests a technical problem that should be resolved prior to publication.
1) The authors have not directly examined the effects of memory CD8 T cells on viral clearance and/or protection against pathological lung damage during influenza virus. If the authors have data in the adoptive transfer experiments in Figure 3 evaluate the functions of wild-type and Atg7-/- memory T on viral clearance and/or lung damage, such data should be included in the manuscript. If they have not collected such data in their experiments, they should acknowledge this limitation.
2) The authors use a model of heterotypic immunity against influenza to avoid a model in which antibody-mediated responses are involved in protection against viral challenge. However, it is notable that mouse survival is not affected by autophagy deficiency in T cells. The reviewers ask whether the authors have tried to use higher titers of the viruses or lethal strains such as those described before (Virology 2011, 412:36-45). If antibodies are the main effectors against influenza and CD8 T cells are not sufficient or required for the protection against influenza challenge, this should be clarified by the authors. In addition, the authors should more fully discuss the data on the role of human CD8 T cell responses in protection against influenza challenge after vaccines. The argument that the findings in mice may have relevance to diminished vaccine responses to flu vaccines in elderly relies on the relevance of CD8 T cell memory responses to vaccine efficacy. The final paragraph mentions briefly that CD8 T cell responses are an important correlate of vaccine protection; however, this should be discussed more extensively in light of the lack of in-depth experimental evidence in this study in the mouse for a role of memory CD8 T cells in protection against disease caused by viral challenge.
3) T/Atg7-/- mice show defects in T cell development and a reduction of CD4 and CD8 T cells in the spleen and lymph nodes (J. Immunol. 182:4046-4055 and Figure 2). In Figure 1, the authors should show the percentage and total numbers of antigen-specific CD8 T cells among all cells in the lung, not just among gated CD8 T cells. The authors conclude that there is “normal expansion of the antigen-specific effector CD8+ T cell compartment”. However, a general lymphopenia in CD4 and CD8 T cells in these mice should be clearly presented in Figure 1, although a comparable fold of CD8 expansion was observed.
4) The reviewers feel that the interpretation of data in Figure 5 is complicated by lymphopenia in T/Atg7-/- mice as well as autophagy deficiency in the CD4 T cell compartment. This point needs to be addressed in the authors' response.
5) In Figure 6, the authors should consider immunodeficiency in aged CD4 T cells (Wakikawa et al., Exp Gerontol 34, 231-242; Cheung et al., Exp Gerontol 18, 451-460). Spermidine would target all cells types in vivo, including CD4+ T helper cells. The experiments performed do not distinguish between these possibilities.
6) The knockout of essential genes from the autophagic cascade entails a major cellular dysfunction due to accumulating, dysfunctional mitochondria (and perhaps other organelles and protein aggregates). Hence, the phenotype of Atg7 knockout cells is not just the result of autophagy inhibition but rather that of accumulating damage. This problem should be discussed. It would be even better to include some of the data that are mentioned as “not shown” with regard to the phenotype of mice lacking Atg5 in T cells.
7) The authors only use one autophagy inducer, spermidine, in their experiments. Hence, it is still possible that autophagy would be only one of the spermidine effects (knowing that spermidine that might mediate additional metabolic effects on polyamine metabolism) that accounts for the improvement of CD8 memory T cells. The paper would be more complete, if the authors used other autophagy inducers (such as resveratrol, fasting etc). At a minimum, the current limitation should be discussed.
8) Autophagic flux is only measured by the 'BDS feature', namely the co-localization of a lysosomal marker and LC3, measured by means of the Amnis Imagestream system. It is important to confirm these measurements (and in particular the efficiency of the ATG7 knockout) by immunoblot detection of the LC3 lipidation in the absence and presence of autophagy inhibitors.
9) The controls in Figure 6d and 6e look very different with regard to the proportion of LC3-I and LC3-II. This could be due to several different factors, including differences in basal autophagy conditions (density, nutritional factors) or sample processing (i.e. freeze-thawing samples will result in degradation of LC3-I which is more labile). The discrepancy in experimental conditions that results in such a notable discrepancy in the proportion of LC3-I and LC3-II in controls of the same cell type in different figures should be resolved.https://doi.org/10.7554/eLife.03706.016
- Daniel J Puleston
- Hanlin Zhang
- Timothy J Powell
- Elina Lipina
- Alexander S Watson
- Vincenzo Cerundolo
- Alain RM Townsend
- Daniel J Puleston
- Paul Klenerman
- Daniel J Puleston
- Alexander S Watson
- Alexander S Watson
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
The study was funded by the MRC Human Immunology Unit and the Wellcome Trust. The Chinese Scholarship Council is gratefully acknowledged for the stipend and fees of HZ; the Lady Tata fund for AW's stipend and fees; and TJP is funded by the Townsend-Jeantet Trust (registered charity no. 1011770) and the MRC Human Immunology Unit. Thanks also goes to Rosanna McEwen-Smith for assistance in setting up the influenza studies.
Animal experimentation: Animal experiments were approved by the local ethical review committee and performed under the project licence (PPL 39/2809) issued by the UK home office.
- Beth Levine, Reviewing Editor, UT Southwestern Medical School, United States
- Received: June 18, 2014
- Accepted: October 16, 2014
- Version of Record published: November 11, 2014 (version 1)
© 2014, Puleston 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.