Acid sphingomyelinase (Asm) and acid ceramidase (Ac) are parts of the sphingolipid metabolism. Asm hydrolyzes sphingomyelin to ceramide, which is further metabolized to sphingosine by Ac. Ceramide generates ceramide-enriched platforms that are involved in receptor clustering within cellular membranes. However, the impact of cell-intrinsic ceramide on T cell function is not well characterized. By using T cell-specific Asm- or Ac-deficient mice, with reduced or elevated ceramide levels in T cells, we identified ceramide to play a crucial role in T cell function in vitro and in vivo. T cell-specific ablation of Asm in Smpd1fl/fl/Cd4cre/+ (Asm/CD4cre) mice resulted in enhanced tumor progression associated with impaired T cell responses, whereas Asah1fl/fl/Cd4cre/+ (Ac/CD4cre) mice showed reduced tumor growth rates and elevated T cell activation compared to the respective controls upon tumor transplantation. Further in vitro analysis revealed that decreased ceramide content supports CD4+ regulatory T cell differentiation and interferes with cytotoxic activity of CD8+ T cells. In contrast, elevated ceramide concentration in CD8+ T cells from Ac/CD4cre mice was associated with enhanced cytotoxic activity. Strikingly, ceramide co-localized with the T cell receptor (TCR) and CD3 in the membrane of stimulated T cells and phosphorylation of TCR signaling molecules was elevated in Ac-deficient T cells. Hence, our results indicate that modulation of ceramide levels, by interfering with the Asm or Ac activity has an effect on T cell differentiation and function and might therefore represent a novel therapeutic strategy for the treatment of T cell-dependent diseases such as tumorigenesis.
The authors have used mouse genetics to show that acid sphingomyelinase mediated generation of ceramide promotes T cell activation and tumour control, whereas acid ceramidase reduces ceramide levels and impairs T cell activation and tumour control. The results also show that ceramide is polarised toward the immunological synapse. The work will be of relevance to those studying the role of lipids in signaling reactions generally and specifically to fields of T cell activation and tumour immunology.https://doi.org/10.7554/eLife.83073.sa0
Sphingolipids are structural components and bioactive molecules of cellular membranes with different functions in cellular processes. One important member of the sphingolipid family is ceramide. Ceramide has the ability to form ceramide-enriched platforms within the plasma membrane (Kolesnick et al., 2000). These microdomains contribute to receptor clustering and other protein interactions and are thereby involved in several signaling pathways and important cellular processes including proliferation, migration, differentiation, and apoptosis (Zhang et al., 2009).
The enzyme acid sphingomyelinase (Asm) generates ceramide by hydrolyzing sphingomyelin, whereas acid ceramidase (Ac) converts ceramide into sphingosine (Hannun and Obeid, 2018). Dysregulations in enzyme activity of the ceramide metabolism can lead to severe diseases. Specifically, mutations in the SMPD1 gene, encoding for Asm, resulting in loss of or reduced Asm activity, cause the lipid-storage disease Niemann-Pick type A and B (NPD) (Schuchman and Wasserstein, 2015). NPD type A patients suffer from severe neuronal symptoms, due to sphingomyelin accumulations in the central nervous system (Ohno, 1995). In contrast, elevated Asm activity is associated with the development of major depressive disorders (Kornhuber et al., 2005). Pharmacological inhibitors of Asm (functional inhibitors of Asm, FIASMA) are therefore used as antidepressant drugs (Beckmann et al., 2014). Loss of Ac activity leads to the development of Farber disease (FD). FD patients suffer from arthralgia, hepatosplenomegaly, and a general developmental delay (Yu et al., 2018).
In addition, alterations in the sphingolipid metabolism play an important role in other pathological disorders including different tumor entities (Ogretmen and Hannun, 2004). For instance, Asm-generated ceramide-enriched platforms are crucial for the CD95-mediated induction of apoptosis (Grassmé et al., 2003). Cancer cells may upregulate Ac expression, leading to reduced ceramide abundance and increased levels of pro-survival lipid sphingosine-1-phosphate (S-1-P) and thereby foster their survival (Morad and Cabot, 2013; Baran et al., 2007; Flowers et al., 2012). Therefore, targeting of Asm and Ac in experimental cancer therapies has shown anti-tumoral efficacy. For example, ionizing radiation induces the activity of Asm, leading to ceramide generation and apoptosis of cancer cells, but fails to do so in lymphoblasts from NPD patients, which lack Asm activity (Santana et al., 1996). In addition, Mauhin et al., 2021 demonstrated most recently, in a retrospective study, that there was an elevated incidence for cancer in NPD patients. We previously observed an enhanced tumor growth rate of transplanted tumor cells in Asm-deficient mice as compared to wildtype (WT) mice. Investigation of the tumor microvasculature identified apoptosis-resistant endothelial cells in Asm-deficient mice as a driver of elevated tumor growth (Garcia-Barros, 2003). In various cancer cell lines, Ac facilitates proliferation by the degradation of ceramide (Govindarajah et al., 2019). Pharmacological inhibition of Ac has been described to be effective for the treatment of patients suffering from colorectal cancer (Sakamoto et al., 2005).
Emphasizing the important role of ceramide in the modulation of tumorigenesis, recent studies by Ghosh et al. provided evidence that the application of exogenous C2 ceramide induces a strong anti-tumor response by increasing frequencies of cytotoxic CD8+ and IFN-γ-producing CD4+ T cells (Ghosh et al., 2020). Among other immune cells, T cells play a crucial role during tumor progression. In melanoma patients, the ratio of cytotoxic CD8+ T cells versus CD4+Foxp3+ regulatory T cells (Tregs) in the tumor microenvironment is predictive for the disease outcome (Jacobs et al., 2012). The infiltration of Tregs into the tumor tissue is considered as a critical step during tumorigenesis. We provided evidence that Neuropilin-1, highly expressed by Tregs (Bruder et al., 2004), regulates the migration of Tregs into VEGF-producing tumor tissue accompanied by elevated tumor progression (Hansen et al., 2012). Depletion of Tregs improved the anti-tumoral immune response of CD8+ T cells in colitis-associated colon cancer, emphasizing the important role of the T cell composition in tumorigenesis (Pastille et al., 2014).
Analysis of immune responses in Asm-deficient mice has shown an impaired cytotoxic activity of CD8+ T cells during LCMV infection (Herz et al., 2009). Moreover, Asm has been identified as a negative regulator of Treg development (Zhou et al., 2016). Asm-deficient or FIASMA-treated mice showed increased numbers of Tregs in comparison to WT animals (Hollmann et al., 2016). In accordance, we detected lower Treg frequencies in spleens of t-Asm/CD4cre mice, which overexpress Asm specifically in T cells (Hose et al., 2019). In CD4+ T cells, isolated from human peripheral blood, inhibition of Asm led to an impaired T cell receptor (TCR) signal transduction accompanied by reduced T cell proliferation and impaired CD4+ T helper (Th) cell differentiation (Bai et al., 2015). The role of Ac in T cell responses is largely unclear. Nevertheless, as mentioned above, several lines of evidence indicate that ceramide metabolism participates in the regulation of T cell responses.
Here, we demonstrate that elevated ceramide concentrations facilitate TCR signaling cascades and determine T cell activation and differentiation in vitro. Strikingly, transplantation of B16-F1 melanoma cells into Smpd1fl/fl/Cd4cre/+ (Asm/CD4cre) or Asah1fl/fl/Cd4cre/+ (Ac/CD4cre) mice, which exhibit decreased or increased ceramide levels in T cells, respectively, revealed that increased ceramide concentrations improve the anti-tumoral T cell response during melanoma progression.
To analyze the impact of Asm activity on T cell function during tumorigenesis, we transplanted B16-F1 melanoma cells into Smpd1-deficient mice (Asm-KO) or control (Asm-WT) littermates. We observed significantly accelerated tumor growth rates in Asm-deficient mice compared to WT mice as previously described (Garcia-Barros, 2003; Figure 1A). Subsequently, we analyzed T cell frequencies in tumor draining lymph nodes (dLN) and tumors as well as the activation status of tumor-infiltrating lymphocytes (TILs). We detected lower frequencies of CD4+ and CD8+ T cells in dLNs but increased frequencies of Tregs in tumor bearing Asm-deficient mice compared to WT mice (Figure 1B). Furthermore, CD4+ and CD8+ TILs showed a reduced expression of IFN-γ and CD44 (Figure 1C), indicating a decreased T cell response in Asm-deficient mice during tumorigenesis. These results suggest that elevated tumor growth in Asm-deficient mice correlates with an insufficient T cell response.
Moreover, we investigated whether pharmacological inhibition of Asm also affects the T cell response during tumorigenesis in a similar way. Therefore, we treated tumor-bearing C57BL/6 mice with amitriptyline by daily intraperitoneal(i.p.) injection. Indeed, we detected enhanced tumor progression in amitriptyline-treated mice compared to tumor-bearing mice that received the vehicle. This was accompanied by reduced activation of TILs in terms of IFN-γ and CD44 expression in amitriptyline-treated C57BL/6 mice compared to PBS-treated mice (Figure 1—figure supplement 1A, B).
Next, we analyzed the effect of Asm deficiency on the Foxp3+ Treg subpopulation in vitro, since we observed elevated frequencies of Tregs in dLN and tumors of tumor-bearing Asm-deficient mice. In accordance with results from Hollmann et al., 2016 and our own study of Asm-overexpressing T cells (Hose et al., 2019), we detected elevated Treg frequencies in spleens of naïve Asm-KO mice as compared to controls (Figure 1D). Moreover, induction of Tregs in vitro revealed an improved capacity of CD4+CD25− T cells to differentiate into Tregs when Asm activity is absent (Figure 1E). In summary, these data provide evidence that ceramide generation by Asm activity in CD4+ T cells interferes with Treg differentiation.
Next, we asked whether the observed increase in relative numbers of Tregs contributes to the insufficient CD8+ T cell response accompanied by enhanced tumor growth in Asm-deficient mice. For this purpose, we depleted CD4+ T cells from Asm-deficient and Asm-WT mice and transplanted B16-F1 melanoma cells. Interestingly, depletion of CD4+ T cells reduced tumor growth in both Asm-WT and Asm-KO mice. Still, tumors of CD4+ T cell-depleted Asm-deficient mice showed higher tumor growth rates than CD4+ T cell-depleted Asm-WT mice (Figure 2A). Remarkably, depletion of CD4+ T cells in Asm-WT mice abolished tumor progression almost completely. Using flow cytometry analysis, we confirmed the successful depletion of CD4+ T cells in dLN and tumor tissue and observed an increase of CD8+ T cell frequencies and numbers, which was significantly less pronounced in dLNs and tumors of Asm-KO mice (Figure 2B). Strikingly, analysis of CD8+ TILs from Asm-deficient mice revealed reduced expression of activation-associated molecules like IFN-γ, CD44, and granzyme B as compared to Asm-WT mice after CD4+ T cell depletion (Figure 2C). These results indicate that Asm-deficiency interferes with CD8+ T cell responses in tumor-bearing mice independent of CD4+ T cells.
To gain further insights into the role of cell-intrinsic Asm activity in CD8+ T cells, we analyzed the phenotype and function of Asm-deficient CD8+ T cells in vitro. To exclude an impact of other Asm-deficient cells present in Asm-KO mice, we made use of Smpd1fl/fl/Cd4cre/+ (Asm/CD4cre) mice, which lack Asm expression specifically in T cells (Figure 3A, Figure 3—figure supplement 1A). This results in significantly reduced ceramide levels in unstimulated, as well as anti-CD3/anti-CD28 stimulated CD8+ and CD4+ T cells compared to T cells from WT littermates (Smpd1fl/fl/Cd4+/+) (Figure 3B, Figure 3—figure supplement 1B). Consistent with decreased T cell activation observed in tumor-bearing Asm-KO mice, in vitro stimulation of sorted CD8+ T cells from Asm/CD4cre mice led to reduced expression of early T cell activation-associated molecules. This was reflected by lower CD25, CD69, and CD44 expression among Asm-deficient CD8+ T cells compared to Asm-proficient CD8+ T cells after 24 hr of stimulation (Figure 3C). Moreover, co-cultivation of antigen-specific cytotoxic lymphocytes (CTLs), generated from Asm/CD4cre/OT-I mice, together with ovalbumin(OVA)-loaded target cells revealed a reduced killing capacity of Asm-deficient CD8+ T cells (Figure 3D). Well in line, CD8+ T cells from Asm/CD4cre mice showed reduced granzyme B expression in response to TCR stimulation (Figure 3E). Strikingly, this phenotype was partially rescued by the addition of exogenous C16 ceramide during stimulation (Figure 3F). Altogether, these data indicate that ceramide is important for effective CD8+ T cell responses, at least in vitro. In addition to the effect of ceramide on CD8+ T cell function, we detected a reduced capacity of CD4+ T cells from Asm/CD4cre mice to differentiate into Th1 cells, but to a higher extent into Tregs in vitro (Figure 1—figure supplement 1C, D), which is in line with our previous results from Asm-KO mice (Figure 1E).
To investigate whether T cell-specific Asm ablation has also an impact on T cell responses during tumorigenesis in vivo, we transplanted B16-F1 melanoma cells into Asm/CD4cre and WT mice and observed significantly higher tumor growth rates in Asm/CD4cre mice compared to control mice (Figure 4A). Again, we analyzed T cell frequencies and T cell activation in dLNs and TILs. In line with results from Asm-KO mice (Figure 1B), we detected elevated percentages of tumor-infiltrating Foxp3+ Tregs as well as reduced frequencies of CD4+ and CD8+ T cells in dLNs from Asm/CD4cre mice compared to control littermates (Figure 4B). Moreover, absolute cell numbers of intratumoral T cells were reduced in Asm/CD4cre mice compared to WT littermates. TILs from T cell-specific Asm-deficient mice showed decreased expression of IFN-γ and TNF-α, as well as granzyme B indicating a reduced anti-tumoral T cell response (Figure 4C). These results provide evidence that cell-intrinsic Asm activity has an impact on T cell responses in vitro and during ongoing immune responses in vivo.
The previous experiments indicate that ceramide generation by Asm activity is involved in T cell function. In order to elucidate the subcellular localization of ceramide, we performed fluorescence microscopy of CD8+ T cells stimulated with CD3/CD28 MACSiBead particles and stained for ceramide, CD3, and TCR-beta. Indeed, ceramide accumulates at the contact site between T cell and particle. Strikingly, ceramide co-localizes with CD3 (Figure 5A) and TCR beta, respectively (Figure 5B). This co-localization of TCR and ceramide suggests an involvement ceramide in TCR signaling.
To further validate the important role of ceramide in CD8+ T cell responses, we made use of Asah1fl/fl/Cd4cre/+ Ac/CD4cre mice. In these mice, T cells are deficient for Ac, the enzyme that catalyzes the hydrolysis of ceramide into sphingosine. As validated by qPCR, both CD8+ and CD4+ T cells lack Ac expression (Figure 6A, Figure 6—figure supplement 1A), resulting in elevated ceramide concentrations in unstimulated and anti-CD3/anti-CD28 T cells from Ac/CD4cre mice compared to control WT littermates (Asah1fl/fl/Cd4+/+) (Figure 6B, Figure 6—figure supplement 1B). Since we observed a co-localization between ceramide and CD3 and TCR-beta upon stimulation, respectively (Figure 5), we wondered whether elevated ceramide levels in Ac-deficient T cells might correlate with TCR signaling. Therefore, we isolated splenocytes from Ac/CD4cre and control mice and stimulated them with anti-CD3/anti-CD28 in vitro. Indeed, CD8+ and CD4+ T cells from Ac/CD4cre mice showed significantly elevated phosphorylation of the TCR signaling molecules ZAP70 and PLCγ compared to control CD8+ T cells (Figure 6C, Figure 6—figure supplement 1C). The elevated phosphorylation of ZAP70 was further confirmed by western blot analysis of isolated Ac-deficient CD8+ T cells (Figure 6D). Well in line with these data, stimulation of CD8+ T cells from Ac/CD4cre mice led to an increased expression of granzyme B compared to CD8+ T cells from control littermates (Figure 6E). Strikingly, CTLs from Ac/CD4cre/OT-I mice showed an improved killing capacity in comparison to control cells (Figure 6F). Although Ac ablation had no impact on Th1 differentiation in regard to IFN-γ expression, CD4+ T cells from Ac/CD4cre mice showed an enhanced expression of granzyme B under Th1-polarizing conditions in vitro (Figure 6—figure supplement 1D).
In this study, we could confirm that Asm or Ac deficiency alters the ceramide concentrations in T cells. In consequence, T cells from Asm/CD4cre mice showed reduced activation and killing capacity in vitro and in vivo, whereas T cells from Ac/CD4cre mice revealed elevated phosphorylation of TCR signaling molecules and an improved killing capacity in vitro. To investigate whether the abundance of T cell synaptic ceramide is affected in Asm-deficient or Ac-deficient T cells, we isolated CD8+ T cells from respective mouse strains and analyzed the subcellular localization of ceramide (Figure 7A). By calculating the ratio of the ceramide signal in the synapse to the signal at the back of the cells, we elucidated the polarization of ceramide toward the stimulating beads. Indeed, synaptic ceramide signal in Ac-deficient T cells was highly elevated compared to Asm-deficient T cells (Figure 7B), emphasizing that ceramide is involved in TCR clustering and the interaction of T cells with antigen-presenting cells (APCs).
Since our data indicate an important role for cell-intrinsic ceramide in T cell activation in vitro, we next analyzed the effect of accumulating ceramide in T cells in vivo. Thus, we transplanted B16-F1 melanoma cells into Ac/CD4cre mice and control littermates. In contrast to Asm/CD4cre mice, Ac/CD4cre mice showed a significant reduction in tumor size compared to control mice (Figure 8A). Although mice did not differ regarding T cell frequencies or numbers (Figure 8B), we detected an elevated T cell activation in Ac/CD4cre tumor-bearing mice. This was reflected by increased IFN-γ and granzyme B expression of CD4+ and CD8+ TILs in comparison to control mice (Figure 8C). From these results, we conclude that enhancing cell-intrinsic ceramide by ablation of Ac activity promotes the T cell function, whereas reduced ceramide levels due to loss of Asm activity are accompanied by a decrease in the activity of T cells.
In the present study, we investigated the impact of cell-intrinsic Asm and Ac activity on the phenotype and function of CD4+ as well as CD8+ T cells in vitro, and during tumorigenesis in vivo. We identified a correlation between ceramide levels and T cell activity. Reduced ceramide content due to loss of Asm activity triggered Treg induction and interfered with effector T cell responses, whereas elevated ceramide concentrations induced by ablation of Ac expression resulted in enhanced T cell activation. Strikingly, cell-intrinsic ceramide levels also correlated with anti-tumoral immune responses and tumor growth in T cell-specific Asm-deficient or Ac-deficient mice.
Several studies already described Asm as regulator of CD4+ T cell function and differentiation (Zhou et al., 2016; Hollmann et al., 2016; Bai et al., 2015). Well in line, we demonstrated that cell-intrinsic Asm activity determines T cell activation and differentiation. However, the mechanism that triggers Asm activity in T cells is still controversial. Mueller et al., 2014 postulated that CD28 stimulation induces Asm activity in T cells, whereas co-stimulation of CD3 and CD28 does not. In contrast, Asm activation has been described in isolated human CD4+ T cells in response to CD3/CD28 co-stimulation (Bai et al., 2015), while Wiese et al. identified CD28 co-stimulation to be required for enhanced human CD4+Foxp3+ Treg frequencies upon Asm inhibition (Wiese et al., 2021). In accordance, we detected significantly elevated ceramide concentrations upon anti-CD3/anti-CD28 treatment of WT CD4+ T cells, which were substantially reduced in Asm-deficient T cells, suggesting that co-stimulation of CD3/CD28 is important for the induction of Asm activity in CD4+ T cells.
Others and we demonstrated that transplantation of melanoma cells into Asm-deficient mice results in accelerated tumor growth. As one underlying mechanism, apoptosis-resistant endothelial cells have been proposed (Garcia-Barros et al., 2004). Here, we provide evidence that Asm deficiency in T cells contributes to an impaired anti-tumoral immune response resulting in loss of tumor growth control. We detected elevated percentages of Foxp3+ Tregs accompanied with reduced expression of activation-associated molecules of effector T cells from tumor-bearing Asm-deficient mice, amitriptyline-treated mice, and importantly, in T cell-specific Asm-deficient mice, in contrast to the respective controls. These results indicate that the T cell-intrinsic Asm activity regulates T cell function and differentiation most likely via the generation of ceramide.
It is well established that Tregs infiltrate the tumor tissue and interfere with an effective local immune response (Hansen et al., 2012; Pastille et al., 2014; Jarnicki et al., 2006; Akeus et al., 2015). Moreover, a higher ratio of Tregs to CD8+ effector T cells correlates with poorer disease outcome in cancer (Sato et al., 2005; Gao et al., 2007; Angelova et al., 2015). To dissect whether enhanced Treg frequencies from Asm-deficient mice are responsible for the enhanced tumor growth, we depleted CD4+ T cells from tumor-bearing mice. Interestingly, CD4+ T cell depletion resulted in reduced tumor growth in both Asm-WT and Asm-KO mice. This is in line with studies by Ueha et al., who observed a reduction of tumor growth after CD4+ T cell depletion (Ueha et al., 2015). However, the tumor growth in Asm-deficient mice was still significantly enhanced compared to WT littermates after CD4+ T cell depletion. Subsequent analysis of CD8+ T cells revealed reduced activation of CD8+ T cells from tumor-bearing Asm-deficient mice. These results provide evidence that Asm activity has an impact not only on CD4+ T cell subsets but also on CD8+ T cell function during tumorigenesis. A reduced capacity to release cytotoxic granules by antigen-specific CD8+ T cells from LCMV-infected Asm-deficient mice has already been described by Herz et al., 2009. In accordance, we also observed decreased frequencies of granzyme B producing CD8+ TILs in tumor-bearing Asm-deficient mice, after CD4+ T cell depletion. Further analysis of CD8+ T cells from T cell-specific Asm-deficient mice (Asm/CD4cre) revealed a reduced activation upon stimulation in vitro compared to WT controls. Strikingly, Asm deficiency was associated with a lowered in vitro killing capacity of CD8+ CTLs, suggesting that the ceramide content could regulate cytotoxic CD8+ T cell function. Indeed, Asm-deficient CD8+ T cells with reduced ceramide concentrations showed an impaired granzyme B production. Interestingly, this phenotype could partially be rescued by the addition of C16 ceramide in vitro. Validating the impact of ceramide on CD8+ T cell responses, we used Ac/CD4cre mice with T cell-specific ablation of Ac expression resulting in increased ceramide concentrations in CD8+ T cells. Well in line with results from Asm-deficient CD8+ T cells, we demonstrated, at least to our knowledge, for the first time, that Ac-deficient CD8+ T cells show increased granzyme B expression upon stimulation and importantly, elevated in vitro killing activity. This phenotype correlated with a facilitated anti-tumoral T cell response leading to reduced tumor growth rates in Ac/CD4cre mice transplanted with B16-F1 melanoma cells in contrast to WT littermates. These results indicate that ceramide concentrations may determine T cell activity and function in vitro and in vivo. In previous studies, intracellular S-1-P has been shown to reduce anti-tumor functions of T cells (Chakraborty et al., 2019; Olesch et al., 2020). To exclude that the modulated anti-tumoral T cell response in Asm/CD4cre and Ac/CD4cre mice, respectively, is caused by altered S-1-P concentrations, we quantified its abundance in CD3/CD28 stimulated T cells. However, S-1-P concentrations were under the detection limit of 0.5 pmol per 1×106 cells (data not shown), emphasizing that indeed ceramide is more likely to modulate the anti-tumoral T cell response than S-1-P levels.
Our results demonstrate that ablation of Ac in CD8+ T cells from Ac/CD4cre mice led to a facilitated phosphorylation of ZAP-70 and PLCγ suggesting that ceramide, most likely as ceramide-enriched platforms in the plasma membrane, modulates the TCR signaling pathway. In accordance Bai and colleagues observed reduced phosphorylation of different TCR signaling molecules in stimulated human CD4+ T cells in the presence of the Asm inhibitor imipramine (Bai et al., 2015), further suggesting that TCR signaling is affected by ceramide. In addition, one might speculate about a positive feedback regulation between ceramide and T cell activation since TCR stimulation of CD4+ as well as CD8+ T cells resulted in elevated ceramide concentration, which in turn seems to strengthen the TCR signaling cascade.
By using fluorescence microscopy, we were able to reveal a co-localization of ceramide and TCR in stimulated CD8+ T cells. Strikingly, synaptic ceramide in CD8+ T cells from Ac/CD4cre mice was highly elevated compared to that of Asm-deficient CD8+ T cells. These results indicate that Asm and Ac activity in T cells not only effect the overall cellular ceramide content but also ceramide levels within the immunological synapse, supporting our hypothesis that the ceramide level is involved in the strength of TCR-induced signaling pathway. Although our results clearly demonstrated the impact of Asm and Ac activity on the ceramide content and T cell function, we could not exclude that other enzymes of the sphingolipid pathways may contribute to increased or decreased ceramide levels. For instance, ceramide could also be synthesized by the neutral sphingomyelinase 2, which was proposed to be required for the immune synapse polarization of TCR signaling components in human Jurkat T cells (Börtlein et al., 2018). Interestingly, blocking its enzymatic activity interferes with the polarized release of exosomes from multivesicular bodies produced by T cell clones (Mittelbrunn et al., 2011), emphasizing an important and diverse role of synaptic ceramide in T cell function. However, ablation of Asm resulted in lower cellular and synaptic ceramide levels associated with impaired CD8+ T cell function, suggesting that other sphingomyelinases are not able to fully compensate for Asm deficiency in T cells.
Overall, our study provides evidence that the cell-intrinsic ceramide content is regulated by the activity of Asm and Ac and associated with CD4+ as well as CD8+ T cell function in vitro and in vivo. Thereby, the sphingolipid metabolism represents a potential therapeutic target for improving anti-tumoral T cell responses during tumorigenesis. However, the use of drugs modulating ceramide generating enzymes like amitriptyline or other FIASMAs should be carefully reflected in cancer patients. Nevertheless, genetic engineering of T cells by manipulating the expression of sphingolipid metabolizing enzymes and using them for cancer therapy could be a potential approach for cancer therapy.
All mice were on C57BL/6 background and maintained under specific pathogen-free conditions at the Animal Facility of University Hospital Essen. Female C57BL/6 mice were purchased from Envigo Laboratories (Envigo CRS GmbH, Rossdorf, Germany).
Asm-KO (Smpd1tm1Esc) mice has been described previously (Horinouchi et al., 1995). Floxed Smpd1 (Smpd1tm1a(EUCOMM)Wtsi) and Asah1 (Asah1tm1.1Jhkh) mice (Gulbins et al., 2013) were crossed to Cd4cre mice and for some experiments additionally to OTI mice (Hogquist et al., 1994) expressing a transgenic TCR recognizing ovalbumin peptide 257–264 (kindly provided by Tetyana Yevsa, Hannover Medical School, Germany). All animal experiments were carried out in accordance with the guidelines of the German Animal Protection Law and were approved by the state authority for nature, environment, and customer protection, North Rhine-Westphalia, Germany.
B16-F1 (CRL-6323) melanoma cells were cultured in Iscove's Modified Dulbecco's Medium(IMDM) supplemented with 10% heat-inactivated fetal calf serum (FCS), 25 µM β-mercaptoethanol, and antibiotics [100 U/ml penicillin, 0.1 mg/ml streptomycin](IMDM complete). Cells were maintained in a humidified 5% CO2 atmosphere at 37°C. Cells were stored in liquid nitrogen and passaged twice before transplantation. Mycoplasma testing was performed every other month by PCR in in vitro propagated cultures.
Tumor cells were harvested and washed twice with PBS. 5×105 tumor cells in a volume of 100-µl PBS were injected subcutaneously (s.c.) into the right flank of experimental animals. Tumor volume was calculated using the formula V = (W2 × L)/2 (Faustino-Rocha et al., 2013) based on caliper measurements once tumors have established.
B16-F1 melanoma cells were injected s.c. into 8–12-week-old C57BL/6 mice, following mice received 20-mg amitriptyline/kg bodyweight in 100-µl PBS via daily i.p. injection over a period of 13 days.
Single-cell suspensions of splenocytes were generated by rinsing spleens with erythrocyte lysis buffer and washing with PBS supplemented with 2% FCS and 2 mM EDTA. T cells were isolated from splenocytes either by using the CD4+ or CD8+ T cell isolation kit (Miltenyi Biotec, Bergisch Gladbach, Germany) according to the manufacturer’s recommendation alone or followed by anti-CD4, anti-CD25, anti-CD8 staining, and cell sorting using an Aria II Cell Sorter (BD Biosciences, Heidelberg, Germany). T cells were stimulated with 1 μg/ml anti-CD3 plate-bound and 1 μg/ml anti-CD28 soluble (both BD Biosciences, Heidelberg, Germany) in IMDM complete culture medium. For exogenous ceramide administration in vitro C16 ceramide (Avanti Polar Lipids, Birmingham, USA) solved in 100% EtOH was sonicated for 10 min. The final concentration used for in vitro T cell culture was 5 µM.
dLN were pestled through a 70-μm cell strainer and washed with PBS containing 2-mM EDTA and 2% FCS. Tumors were homogenized and pestled through a 70-μm cell strainer and washed with IMDM complete culture medium.
For Treg differentiation (iTreg), CD4+CD25− T cells were stimulated with anti-CD3/anti-CD28 as described above in the presence of 20 ng/ml IL-2 (eBioscience, ThermoFisher Scientific, Langenselbold, Germany) and 5 ng/ml TGF-β1 (R&D Systems, Bio-Techne, Wiesbaden, Germany) for 72 hr.
For the generation of antigen-specific CTLs, splenic CD8+ T cells from Asm/CD4cre/OT-I, Ac/CD4cre/OT-I mice or the respective littermate controls were cultivated in the presence of irradiated splenocytes, 1 µg/ml OVA-peptide 257–264, 10 ng/ml IL-2, and 20 ng/ml IL-12 for 6 days. As control, cells were stimulated without OVA-peptide 257–264 (non-CTLs). At day 3, cells were split, and fresh IMDM complete culture medium supplemented with 10 ng/ml IL-2 was added. CTLs and non-CTLs were isolated from the culture and incubated with OVA-peptide 257–264 loaded Carboxyfluoresceinsuccinimidylesterhigh(CFSEhigh)-labeled (2.5 µM CFSE) target and unloaded CFSElow-labeled (0.25 µM CFSE) control cells (both splenocytes from WT mice) for 2 or 4 hr. Frequencies of target and control populations were analyzed using flow cytometry. Specific killing was calculated as described before (Barber et al., 2003) using the formula: specific killing [%]=100−([(CTLtarget/CTLcontrol)/(non-CTLtarget/non-CTLcontrol)] × 100).
Anti-CD4, anti-CD8, anti-IFN-γ, anti-CD25, anti-CD44 (BD Biosciences, Heidelberg Germany), anti-CD8, anti-Foxp3, anti-TNF-α, anti-CD69 (eBioscience, ThermoFisher Scientific, Langenselbold, Germany), anti-p-PLCγ, anti-p-ZAP70 (Cell Signaling, Frankfurt am Main, Germany), anti-Granzyme B (Invitrogen, ThermoFisher Scientific, Langenselbold, Germany), and anti-ZAP70 (BioLegend, San Diego, USA) were used as fluorescein isothiocyanate (FITC), pacific blue, phycoerythrin (PE), allophycocyanin, AlexaFluor488, AlexaFluor647, PE-cyanin 7, or peridinin-chlorophyll protein conjugates. Dead cells were identified by staining with the fixable viability dye eFluor 780 (eBioscience, ThermoFisher Scientific, Langenselbold, Germany). Intracellular staining for Foxp3 and Granzyme B was performed with the Foxp3 staining kit (eBiocience, ThermoFisher Scientific, Langenselbold, Germany) according to the manufacturer’s protocol. IFN-γ and TNF-α expression were measured by stimulating cells with 10 ng/ml phorbol 12-myristate 13-acetate and 100-μg/ml ionomycin (both Sigma-Aldrich, München, Germany) for 4 hr in the presence of 5-μg/ml Brefeldin A (Sigma-Aldrich, München. Germany), followed by treatment with 2% paraformaldehyde and 0.1% IGEPAL CA-630 (Sigma-Aldrich, München, Germany), and staining with the respective antibody for 30 min at 4°C. Flow cytometric analyses were performed with an LSR II and a Canto II instrument using DIVA software (BD Biosciences, Heidelberg Germany).
Cell suspensions were subjected to lipid extraction using 1.5-ml methanol/chloroform (2:1, v:v) as described (Gulbins et al., 2018). The extraction solvent contained C17 ceramide (C17 Cer) and d7-S-1-P (both Avanti Polar Lipids, Alabaster, USA) as internal standards. Chromatographic separations were achieved on a 1290 Infinity II HPLC (Agilent Technologies, Waldbronn, Germany) equipped with a Poroshell 120 EC-C8 column (3.0×150 mm, 2.7 µm; Agilent Technologies). MS/MS analyses were carried out using a 6495 triple-quadrupole mass spectrometer (Agilent Technologies) operating in the positive electrospray ionization mode (ESI+) (Naser et al., 2020). The following mass transitions were recorded (qualifier product ions in parentheses): m/z 380.3 → 264.3 (82.1) for S-1-P, m/z 387.3 → 271.3 (82.1) for d7-S-1-P, m/z 520.5 → 264.3 (282.3) for C16 Cer, m/z 534.5 → 264.3 (282.3) for C17 Cer, m/z 548.5 → 264.3 (282.3) for C18 Cer, m/z 576.6 → 264.3 (282.3) for C20 Cer, m/z 604.6 → 264.3 (282.3) for C22 Cer, m/z 630.6 → 264.3 (282.3) for C24:1 Cer, and m/z 632.6 → 264.3 (282.3) for C24 Cer. Peak areas of Cer subspecies, as determined with MassHunter software (Agilent Technologies), were normalized to those of the internal standard (C17 Cer) followed by external calibration in the range of 1 fmol–50 pmol on column. S-1-P was directly quantified via its deuterated internal standard d7-S-1-P (0.125 pmol on column). Determined ceramide and S-1-P amounts were normalized to cell count.
For analyzing phosphorylation of TCR signaling molecules by flow cytometry, 5×105 splenocytes were left unstimulated or stimulated with 1 μg/ml anti-CD3 and 1 μg/ml anti-CD28 for 5 or 10 min, treated with Cytofix/Cytoperm (BD Biosciences, Heidelberg Germany) for 1 hr, and stained with the respective antibodies for 30 min at 4°C. For western blot analysis isolated T cells were stimulated for 5 min, washed with PBS, collected in lysis buffer, and incubated on ice for 20 min. Afterward, cells were centrifuged for 5 min at 1200 rpm, the supernatant was collected, and protein concentrations were determined as described by Lowry and Randall, 1951. 30 µg of total protein were diluted in sodium dodecyl sulfate (SDS)-buffer, denatured at 95 °C for 5 min and subjected to SDS polyacrylamide gel electrophoresis. Separated proteins were transferred to a Polyvinylidendifluorid(PVDF) membrane using the Trans-Blot Turbo RTA Transfer Kit (Bio-Rad Laboratories, Feldkirchen, Germany) according to the manufacturer’s recommendations. The PVDF membrane was blocked with 5% BSA in TBS-T for 1 hr at room temperature. Primary antibodies against p-ZAP70 (Cell Signaling, Frankfurt am Main, Germany, 1:1000) and β-actin (Sigma-Aldrich, Saint Louis, USA, 1:2000) were incubated over night at 4°C. Secondary anti-rabbit IgG antibody (Sigma-Aldrich, Saint Louis, USA, 1:10,000) was incubated for 1 hr at room temperature. Blots were developed using SuperSignal West Femto Maximum Sensitivity Substrate (Thermo Scientific), and signals were detected with a Fusion FX System (Vilber, Eberhardzell, Germany).
Isolated CD8+ T cells were plated in ibidi µ-slides (Ibidi, Gräfelfing, Germany) and stimulated with CD3/CD28 MACSiBead particles (Miltenyi Biotec, Bergisch Gladbach, Germany) in a 1:1 ratio for 2 hr at room temperature. Afterward, cells were fixed with 4% PFA, blocked with 1% BSA in PBS for 30 min, and stained with anti-ceramide antibody (LSBio, Seattle, USA, 1:20 in 1% BSA in PBS) for 1 hr. Secondary anti-mouse IgM antibody (BioLegend, San Diego, USA, PE-conjugated, 1:1000) and anti-CD3 (BioLegend, San Diego, USA, FITC-conjugated) or anti-TCR beta (Invitrogen, Carlsbad, USA, FITC-conjugated, 1:50) antibodies were diluted in 1% BSA in PBS and incubated for 30 min at room temperature. Stained cells were mounted using fluorescence mounting medium (Dako, California, USA) and visualized with a Biorevo BZ-9000 fluorescence microscope (Keyence, Itasca Illinois, USA). For quantification, the ceramide signal was measured in the synapse and in the back of the cell and calculated using following formula: Fluorescence intensity = Integrated Density – (Area of Selected Cell × Mean Fluorescence of Background readings).
For depletion of CD4+ T cells during tumorigenesis, 200-μg anti-mouse CD4-depleting antibody (clone GK1.5; BioXcell, Lebanon, USA) was injected intraperitoneal on days –1, 3, 6, 9, and 12 after tumor cell transplantation.
RNA was isolated using the NucleoSpin RNA XS Kit (Macherey-Nagel, Düren, Germany) according to the manufacturer’s instructions. 100 ng of RNA was reversed transcribed using M-MLV reverse transcriptase (Promega, Mannheim, Germany) with dNTPs (Bio-Budget, Krefeld, Germany), Oligo-dT mixed with Random Hexamer primers (both Invitrogen, Frederick Maryland, USA). Quantitative real-time PCR was performed using the Fast SYBR Green Master Mix (Thermo Fisher Scientific, Braunschweig, Germany) and a 7500 Fast Real-Time PCR System (Thermo Fisher Scientific, Darmstadt, Germany). Samples were measured as technical duplicates. Expression levels were normalized against ribosomal protein S9 (RPS9). Following primer sequences were used: Asm (Smpd1) CTG TCA GCC GTG TCC TCT TCC TTA, GGG CCC AGT CCT TTC AAC AG, Ac (Asah1) TTC TCA CCT GGG TCC TAG CC, TAT GGT GTG CCA CGG AAC TG, RPS9 CTG GAC GAG GGC AAG ATG AAG C, TGA CGT TGG CGG ATG AGC ACA.
Statistical analyses were calculated using Graph Pad Prism Software (Graph Pad Software, La Jolla, CA). To test for Gaussian distribution, D’Agostino-Pearson omnibus and Shapiro-Wilk normality tests were used. If data passed normality testing, paired or unpaired Student’s t-test was performed, otherwise Mann-Whitney U-test was used for unpaired data. Differences between two or more groups with different factors were calculated using two-way ANOVA followed by Sidak’s post-test. Statistical significance was set at the levels of *p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001.
Source Data files have been provided for figures 1-8 and supplemental figures.
Treg-cell depletion promotes chemokine production and accumulation of CXCR3 (+) conventional T cells in intestinal tumorsEuropean Journal of Immunology 45:1654–1666.https://doi.org/10.1002/eji.201445058
Cutting edge: rapid in vivo killing by memory CD8 T cellsJournal of Immunology 171:27–31.https://doi.org/10.4049/jimmunol.171.1.27
Inhibition of acid sphingomyelinase by tricyclic antidepressants and analogonsFrontiers in Physiology 5:1–14.https://doi.org/10.3389/fphys.2014.00331
Neuropilin-1: a surface marker of regulatory T cellsEuropean Journal of Immunology 34:623–630.https://doi.org/10.1002/eji.200324799
C6-Ceramide and targeted inhibition of acid ceramidase induce synergistic decreases in breast cancer cell growthBreast Cancer Research and Treatment 133:447–458.https://doi.org/10.1007/s10549-011-1768-8
Pkcζ mediated anti-proliferative effect of C2 ceramide on neutralization of the tumor microenvironment and melanoma regressionCancer Immunology, Immunotherapy 69:611–627.https://doi.org/10.1007/s00262-020-02492-0
Sphingolipids and acid ceramidase as therapeutic targets in cancer therapyCritical Reviews in Oncology/Hematology 138:104–111.https://doi.org/10.1016/j.critrevonc.2019.03.018
Antidepressants act by inducing autophagy controlled by sphingomyelin-ceramideMolecular Psychiatry 23:2324–2346.https://doi.org/10.1038/s41380-018-0090-9
Sphingolipids and their metabolism in physiology and diseaseNature Reviews. Molecular Cell Biology 19:175–191.https://doi.org/10.1038/nrm.2017.107
Neuropilin 1 deficiency on CD4+Foxp3+ regulatory T cells impairs mouse melanoma growthThe Journal of Experimental Medicine 209:2001–2016.https://doi.org/10.1084/jem.20111497
Compartmentalization of ceramide signaling: physical foundations and biological effectsJournal of Cellular Physiology 184:285–300.https://doi.org/10.1002/1097-4652(200009)184:3<285::AID-JCP2>3.0.CO;2-3
High activity of acid sphingomyelinase in major depressionJournal of Neural Transmission 112:1583–1590.https://doi.org/10.1007/s00702-005-0374-5
Protein measurement byt the folin reagentThe Journal of Biological Chemistry 1:1–11.
Prevalence of cancer in acid sphingomyelinase deficiencyJournal of Clinical Medicine 10:21.https://doi.org/10.3390/jcm10215029
Biologically active sphingolipids in cancer pathogenesis and treatmentNature Reviews. Cancer 4:604–616.https://doi.org/10.1038/nrc1411
S1PR4 ablation reduces tumor growth and improves chemotherapy via CD8+ T cell expansionThe Journal of Clinical Investigation 130:5461–5476.https://doi.org/10.1172/JCI136928
An individual patient data meta-analysis of adjuvant therapy with carmofur in patients with curatively resected colon cancerJapanese Journal of Clinical Oncology 35:536–544.https://doi.org/10.1093/jjco/hyi147
Inhibition of acid sphingomyelinase increases regulatory T cells in humansBrain Communications 3:fcab020.https://doi.org/10.1093/braincomms/fcab020
Acid ceramidase deficiency: farber disease and SMA-PMEOrphanet Journal of Rare Diseases 13:121.https://doi.org/10.1186/s13023-018-0845-z
Ceramide-Enriched membrane domains -- structure and functionBiochimica et Biophysica Acta 1788:178–183.https://doi.org/10.1016/j.bbamem.2008.07.030
Acid sphingomyelinase (ASM) is a negative regulator of regulatory T cell (Treg) developmentCellular Physiology and Biochemistry 39:985–995.https://doi.org/10.1159/000447806
Michael L DustinReviewing Editor; University of Oxford, United Kingdom
Tony NgSenior Editor; King's College London, United Kingdom
In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.
[Editors' note: this paper was reviewed by Review Commons.]https://doi.org/10.7554/eLife.83073.sa1
1) There needs to be a quantification of S1P in T cells in response to ASM or AC knockouts in T cells in Figures2A and 6A, as intracellular S1P has been shown to reduce anti-tumor functions of T cells in previous studies.
We thank the reviewer for this helpful comment. Indeed, we have now analysed S1P levels in Asm- and Ac-deficient T cells. However, S1P concentrations were under detection limit and therefore not included in the revised manuscript, but we included the information about non-detectable S1P levels in the Discussion section of the revised manuscript
2) The tumor volume measurements were performed within 13-18 days of post-injection of cells in mice. These studies are too short and need to be evaluated at around 21-30 days to evaluate whether observed defects in T cells are sustained in a time-dependent fashion.
We agree that analysis of our experiments at later time points would be interesting to see how T cell responses develop over time. Therefore, we repeated tumor transplantation into Acflox/flox/CD4cre mice to evaluate tumor growth and T cell responses over an extended period of time. However, for animal welfare reasons, we again had to sacrifice the mice on day 18 after transplantation since tumors have become too large.
3) The mechanisms that are involved in the regulation of anti-tumor functions of T cells by ASM versus AC are not very clear. Although TCR signaling is implicated, the mechanistic aspects of the data are weak.
We hypothesize that the clustering of ceramide facilitates the polarization of TCR molecules and thereby foster the intracellular downstream signalling cascade. Indeed, microscopy of T cells revealed a co-localization of TCR β and ceramide upon stimulation with CD3/CD28 MACSiBeads. We have included these new data in Figure 5 of the revised manuscript. Moreover, we could confirm and have included new data on a facilitated phosphorylation of Zap70 in ceramide enriched T cells from Acflox/flox/CD4cre mice analysed by Western Blot (Figure 6D of the revised manuscript), suggesting that an increase in ceramide-enriched platforms contribute to elevated TCR clustering and signalling
4) The subcellular localization of ceramide in the plasma membrane/TCR synapsis needs to be examined and shown to strengthen the major point of the study.
We thank the reviewer for this helpful suggestion. We performed fluorescence microscopy of CD8+ T cells stimulated with CD3/CD28 MACSiBead Particles and stained for CD3, TCR β and ceramide. Indeed, ceramide accumulates at the contact site with the particle and co-localizes with CD3 and the TCR. We included representative images in Figure 5 of the revised manuscript.
1) The effects of ASM or AC deletions on TCR signaling in T cells should be shown by Western blotting and/or immunofluorescence in addition to the flow cytometry-based assays (for detecting p-AKT, pZAP70, and p-PLC (these need to be examined in Figure 2F as in 6B). PKC-theta should be added in this panel also.
Analysis of phospho-TCR signalling molecules by flow cytometry is a well-established method and has been already been published by us and many other authors (for example, Hose et al., Front Immunol 2019, 10: 1225; Morelli et al., Cell Reports 2020, 30: 3448-65; Hong et al., Cell 2020, 180: 847-61; Balyan et al., Immunology 2018, 156: 384-401). Moreover, reduced phosphorylation of TCR signalling molecules upon Asm inhibition has already been shown by Western Blot analysis in a previous study (Bai, et al., Cell Death Dis. 2015,6(7):e1828.). Nevertheless, as a proof of concept we confirmed our results on elevated p-ZAP70 in Ac-proficient CD8+ T cells by western blot analysis as an example and included it in Figure 6 of the revised manuscript.
2) The list of references contain too many review articles, and it seems that it is missing many recent publications describing the roles and mechanisms of ceramide or S1P in the regulation of anti-tumor functions of T cells.
We thank the reviewer for this recommendation and have now included more primary and recent publications on the topic in the revised manuscript.
Figure 1: Data inconsistency: The tumor growth in control mice varies considerably between experiments (e.g. Figure 1a WT d13 700mm3 vs Figure 1d and WT/PBS d13 200mm3) why is this the case? While the impact of tumor control in Asm deficient mice is overall convincing the analysis of the functional defect of Asm deficient T cells is superficial. Analysis of additional cytokines (TNF, IL2) would be important. IFN needs be depicted as % positive rather than MFI and representative FACS plots would further strengthen the data. Same applies to Ki67 and CD44.
We agree that tumor growth shows variation between the different experiments. One reason for that might be genetic differences between the WT controls used in the experiments. In Figure 1A WT mice are non-transgenic littermates from our in-house AsmKO breeding (AsmKO heterozygous x AsmKO heterozygous), whereas commercial available C57BL/6JOlaHsd mice from Envigo were used for amitriptyline treatment in Figure 1 of the original manuscript, now shown in the Supplemental Figure 1. Data for IFNγ and CD44 are now depicted as % in Figure 1 of the revised manuscript. Examples for representative FACS plots on IFNγ and CD44 expressing TILs are included in Figure 2 and an example for the gating strategy of CD4 and CD8 T cells used for all experiments is shown in Figure 4 of the revised manuscript.
Figure 2: The authors switch between Asm KO to Asm inhibition without providing further explanation (e.g. Figure 2E and F the only use the inhibition model). The authors should clarify this in the text. Could the phenotype of Asm deficiency be rescued by addition of ceramide species in vitro? This could establish a mechanistic link between ceramide abundance and T cell function. Asm and Ac expression should be shown on a protein level (if possible) or at least on an mRNA level over time following activation. (E) intracellular cytokine staining and representative FACS plots would strengthen the data. (F) This data is not convincing. How were pos cells gated given the minimal shift in staining?
We are grateful for these helpful comments. We agree that switching between Asm KO and Asm inhibition was confusing in the initial manuscript. Moreover, data on the impact of Asm inhibition on CD4 T cells in vitro has already been published by others (Bai et al., Cell Death Dis. 2015,6(7):e1828). Therefore, we have now excluded the in vitro data on Asm inhibition from the revised manuscript. In order to analyse whether the phenotype of Asm deficiency can be rescued by the addition of ceramide, we isolated CD8+ T cells from Asmflox/flox/CD4cre and WT mice and stimulated them in presence or absence of C16 ceramide and evaluated the expression of granzyme B. Indeed, addition of C16 ceramide partially rescued granzyme B expression of Asm-deficient CD8+ T cells. The data are included in Figure 3F of the revised manuscript. Using RT-qPCR, we analysed the expression of Asm and Ac in T cells on mRNA level. We included the data in the revised manuscript in Figure 3A for CD8+ T cells and Supplemental Figure S2 for CD4+ T cells from Asmflox/flox/CD4cre and WT mice and in Figure 6A for CD8+ T cells and Supplemental Figure S3 for CD4+ T cells from Acflox/flox/CD4cre and WT mice. In addition, we now included the gating and FMOs for FACS analysis of TCR signalling in Figure 6C and Supplemental Figure S3 of the revised manuscript.
Figure 3: The authors should harmonize what they mean by "activation" among figures and use the same markers/molecules in every figure (e.g. IFN not shown in Figure 3, but shown in Figure 1, also applies to Figure 4,5 and 6). Otherwise, the comparison between different figures/conditions/models (e.g. CD4+ T cell depletion) is not feasible. (B) Absolute numbers of CD4 and CD8 T cells need to be shown. (c) Ki67 levels should be shown as % positive and supported by representative FACS plots.
We thank the reviewer for these recommendation. Unfortunately, we do not have analysed every marker/ molecule in all different models. However, since the main topic of our study is the impact of the sphingolipid metabolism on cytotoxic T cell function, we now mainly focused on IFNγ and granzyme B expression. Regarding absolute CD8+ T cell numbers, we agree with the reviewer and included respective data in Figure 2B of the revised manuscript. However, since CD4+ T cells are depleted, we could have only added absolute numbers of the control groups.
Figure 4: (B) Gzmb levels should be shown as % positive and supported by representative FACS plots. (C) The proliferation assay shows that the KO and WT cells proliferate similarly once they enter cell cycle. The main difference is that in Asm KO T cells a larger fraction does not enter cell cycle. It would strengthen the manuscript to elucidate why this is the case. The authors should temper their conclusions. Arguing that Asm is "essential" for T cell activation seems exaggerated based on the provided data.
We thank the reviewer for these helpful comments. In the revised manuscript we now show granzyme B expression as % and included representative FACS plot (Figure 3E). We agree with the reviewer that it would be interesting to elucidate why a larger fraction of AsmKO CD4+ T cells did not enter the cell cycle. However, the main focus of our study was the impact of the sphingolipid metabolism on T cell responses during tumorigenesis and its cytotoxic activity. Therefore, we have decided to exclude data on CD4+ T cell proliferation from the revised manuscript. We apologize for the exaggerated wording and have carefully adjusted corresponding statements in the revised manuscript.
Figure 5: (A) Absolute CD4, Treg cell and CD8 T cell numbers need to be shown to optimally interpret the data. Parental gating of the FACS plots should be shown/indicated. (B) Cytokine response and Gzmb expression should be shown as % positive rather than MFI. Based on the FACS plot the differences are likely more impressive than the MFIs suggest. (C) tumor growth WT control on d14 about 200mm3, this is not consistent with Figure 1a.
We agree with the reviewers suggestions and now included absolute numbers and the FACS gating strategy in Figure 4B in the revised manuscript. Moreover, we additionally show % of cytokine and granzyme B expression (Figure 4C). As mentioned above, differences in tumor growth curves are likely due to the use of different WT controls in the individual experiments. Data shown in Figure 1A are from non–transgenic WT littermates of our in-house AsmKO breeding (AsmKO heterozygous x AsmKO heterozygous), whereas WT controls in Figure 4 are littermates of Asmflox/floxCD4cre mice that do not express the cre recombinase.
Figure 6: Since the paper talks about T cell function in general and since this is a completely new mouse model (Acflox/flox/CD4Cre) and the first time this enzyme has been studied in T cells, the authors should show the phenotype and characterization of CD4+ T cells as well, and not only CD8+ T cells (Figures 6A-D). (B) This data is not convincing. How were pos cells gated given the minimal shift in staining? (C) Gzmb should be shown as % positive and representative FACS plots should be added. (E) Tumor growth curve at d18 does not match with the tumor size at day of sacrifize shown in the adjacent bar graph. Absolute numbers of CD4, Treg cells and CD8 T cells in tumors should be shown.
We are grateful for these helpful suggestions. We have now included data on Ac-deficient CD4+ T cells in Supplemental Figure S3 of the revised manuscript. As mentioned above, we have added the FACS gating and FMOs plots for the analysis of TCR signalling in the new Figure 6C. Moreover, we now additionally show % of granzyme B-expressing T cells and representative FACS plots in Figure 6E of the revised manuscript. We agree and apologize that the way the tumor size was presented for Acflox/flox/CD4cre mice is misleading. Therefore, we have now only included data of mice sacrificed 18 days post transplantation and added absolute numbers of tumor-infiltrating T cells in Figure 7B in the revised manuscript.
Discussion line 496: "the sphingolipid metabolism represents a potential therapeutic target for improving anti-tumoral T cell responses during tumorigenesis". If would great if the authors speculated more about how this could be done; how could a target inhibition of T cell be achieved? Maybe engineering CD4+, CD8+ and Tregs by manipulating the expression of these sphingolipid metabolizing enzymes and using them for tumor therapy could be a potential approach.
We have now discussed this issue in more details in the revised manuscript.
1. Authors further argue that TCR signalling is affected in Asm KO and Ac KO cells. Data provided are not fully convincing. First, a strong stimulation by aCD3/aCD28 antibodies is used and in the most cases differences between WT and mutant cells is minor (Figure 2, Figure 6). Indeed, the use of antibodies with high affinity/avidity to the receptors may hide the real impact of changes on early TCR signalling events.
We agree with the reviewer that effects on phosphorylation of TCR signalling molecules seems not to be tremendous, but differences are significant after stimulation with aCD3/aCD28. Although differences in early TCR signalling events might be even stronger after a milder form of stimulation, we decided to use the same stimulation protocol for all of our analysis in the manuscript to make the data comparable.
2. Flow cytometry is used exclusively to show changes in phosphorylation of signalling molecules (ZAP70, Akt, PLCg, p38). Why ZAP70, Akt and PLCg are tested for Ac part and PLCg and p38 in the Asm section? Histograms are shown and the difference between control (WT, positive) and amitriptyline-treated T cells is very subtle. Negative control is not shown. In the graph, authors present % of cells with phosphorylated protein from the total number of protein-positive cells. This value strongly depends on setting of the value, which represents phoshoprotein positivity. For Ac mutant T cells, authors even use relative values in the graphs. Presented histograms again do not show well-distinguishable difference. However, it is unclear why authors use relative % values for data which represent ratiometric values. Presenting all measured and processed values in the Supplementary Data may help to resolve this issue. Still, the changes are small, and I am not sure if altered TCR signalling can explain well-documented effect of ceramide levels on T cell function in vivo and in vitro.
We totally agree with the reviewers’ opinion and apologize for the measurement of different signalling molecules for the Asm and Ac section. Since the section on Asm inhibition by amitriptyline was rather confusing (see comments of reviewer #2) and the impact of Asm inhibition on TCR signalling has already been shown in detail for CD4+ T cells by others (Bai et al., Cell Death Dis. 2015,6(7):e1828) we excluded these data from the revised manuscript. For Ac-deficient T cells we added the FACS gating and FMOs (Figure 6C and Supplemental Figure S3) and performed exemplary western blot analysis for p-ZAP70 (Figure 6D) to further strengthen these data. Moreover, we now present % instead of relative values in the revised manuscript.
3. Immunobloting can further support presented flow cytometry data related to TCR-induced signalling (phosphorylation of signalling molecules).
As mentioned above, we additionally performed western blot analysis to support the flow cytometry data.
4. As described above, the effect on early TCR signalling is inconclusive (in the current form of the manuscript). Please, revise the sentence in the Abstract: 'Mechanistically, our results indicate that ceramide levels, regulated by Asm and Ac activity, correlate with the phosphorylation of TCR signaling molecules in T cells.'It is not clear if authors mean that TCR signalling induces ceramide levels (well-supported by presented data) or that TCR signalling is affected by altered ceramide levels (less-well supported by the data).
We agree with the reviewer that our data provide evidence for an increase in ceramide after TCR activation. Nevertheless, unstimulated T cells deficient for Asm or Ac already showed differences in the ceramide levels (Figure 3B and 6B of the revised manuscript) and our new data provide evidence for co-localization of the TCR and ceramide upon stimulation (Figure 5 of the revised manuscript).
Therefore, one might speculate about an influence of ceramide levels on TCR signalling, which in turn further affects the ceramide levels. We have carefully rewritten this aspect in the Abstract and discussed this issue in the revised manuscript.
5. Ceramide levels: There is dramatic difference between values presented for ceramide in WT cells in Figure 2 and Figure 6. Please, comment on the difference. Adding all relevant numbers into a table would be very useful.
We agree that ceramide levels of WT cells shown in Figure 2 and Figure 6 of the original manuscript are different. However, ceramide concentration shown in the Figure 2 of the original manuscript derived from CD4+ T cells, whereas concentration shown in Figure 6 were measured in CD8+ T cells. We have now analysed ceramide contents in CD4+ T cells as well as CD8+ T cells isolated from both Asmflox/flox/CD4cre and Acflox/flox/CD4cre mice included the new data in Figures 3, 6 and Supplemental Figures S2 and S3 of the revised manuscript.
6. Changes in ceramide levels may influence levels of other lipids, e.g., sphingolipids,
glycosphingolipids, cholesterol, some specific glycerophospholipids (PS, PI). Do authors have any data about other lipids in Asm and Ac KO cells?
We agree with the reviewer that analysis of other lipids in AsmKO and AcKO T cells would be interesting. However, the focus of this study was on the effects of Asm deficiency and Ac deficiency on ceramide levels and the resulting phenotypic changes of T cells. Therefore, we do not have analysed other lipids yet. Nevertheless, in response to the suggestion of reviewer #1 we analysed S1P levels of Asm- and Ac-deficient T cells, but concentrations were under detection limit.
1. On 2-3 places, overstatement can be found: e.g., line 272 impaired -> reduced; line 453 diminished -> reduced/lowered
We have now carefully rephrased the respective statements.
2. Typo? Line 303: CD4+ T cells -> Tregs (not sure)
We thank the reviewer for this comment and specified our statement.
3. Figure 5B, granzyme B panel: The word 'Tumors'below the graph is confusing.
We apologize for this confusion. We have now corrected the Figure in the revised manuscript.https://doi.org/10.7554/eLife.83073.sa2
- Astrid M Westendorf
- Katrin Anne Becker
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
We kindly thank Sina Luppus for excellent technical assistance and Witold Bartosik and Christian Fehring for cell sorting. Moreover, we thank Daniel Herrmann for the help with the HPLC-MS analyses of ceramides. This work was supported by the Deutsche Forschungsgemeinschaft (DFG - GRK2098 to AMW, JB, KAB, EG and WH, and GRK1949 to AMW, JB, and WH).
All experiments were performed in strict accordance with the guidelines of the German Animal Protection Law and approved by the State Agency for Nature, Environment, and Consumer Protection (LANUV), North Rhine-Westphalia, Germany (Az 84-02.04.2015.A367, Az 84-02.04.2016.A506, Az 84-02.04.2017.A024).
- Tony Ng, King's College London, United Kingdom
- Michael L Dustin, University of Oxford, United Kingdom
© 2022, Hose, Günther et al.
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Age-associated DNA methylation in blood cells convey information on health status. However, the mechanisms that drive these changes in circulating cells and their relationships to gene regulation are unknown. We identified age-associated DNA methylation sites in six purified blood-borne immune cell types (naive B, naive CD4+ and CD8+ T cells, granulocytes, monocytes, and NK cells) collected from healthy individuals interspersed over a wide age range. Of the thousands of age-associated sites, only 350 sites were differentially methylated in the same direction in all cell types and validated in an independent longitudinal cohort. Genes close to age-associated hypomethylated sites were enriched for collagen biosynthesis and complement cascade pathways, while genes close to hypermethylated sites mapped to neuronal pathways. In silico analyses showed that in most cell types, the age-associated hypo- and hypermethylated sites were enriched for ARNT (HIF1β) and REST transcription factor (TF) motifs, respectively, which are both master regulators of hypoxia response. To conclude, despite spatial heterogeneity, there is a commonality in the putative regulatory role with respect to TF motifs and histone modifications at and around these sites. These features suggest that DNA methylation changes in healthy aging may be adaptive responses to fluctuations of oxygen availability.
Infection with Influenza A virus (IAV) causes the well-known symptoms of the flu, including fever, loss of appetite, and excessive sleepiness. These responses, mediated by the brain, will normally disappear once the virus is cleared from the system, but a severe respiratory virus infection may cause long-lasting neurological disturbances. These include encephalitis lethargica and narcolepsy. The mechanisms behind such long lasting changes are unknown. The hypothalamus is a central regulator of the homeostatic response during a viral challenge. To gain insight into the neuronal and non-neuronal molecular changes during an IAV infection, we intranasally infected mice with an H1N1 virus and extracted the brain at different time points. Using single-nucleus RNA sequencing (snRNA-seq) of the hypothalamus, we identify transcriptional effects in all identified cell populations. The snRNA-seq data showed the most pronounced transcriptional response at 3 days past infection, with a strong downregulation of genes across all cell types. General immune processes were mainly impacted in microglia, the brain resident immune cells, where we found increased numbers of cells expressing pro-inflammatory gene networks. In addition, we found that most neuronal cell populations downregulated genes contributing to the energy homeostasis in mitochondria and protein translation in the cytosol, indicating potential reduced cellular and neuronal activity. This might be a preventive mechanism in neuronal cells to avoid intracellular viral replication and attack by phagocytosing cells. The change of microglia gene activity suggest that this is complemented by a shift in microglia activity to provide increased surveillance of their surroundings.