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Article

TGF-β Regulates CD8+ T Cell Memory by Triggering mTORC1Weak-Mediated Activation of the Transcriptional FOXO1-TCF1-Eomes and Metabolic AMPK-ULK1-ATG7 Pathways

1
Research Unit, Saskatchewan Cancer Agency, 20 Campus Drive, Saskatoon, SK S7N 4H4, Canada
2
Division of Oncology, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
3
Department of Biochemistry, Microbiology and Immunology, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
4
Department of Laboratory Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi 563000, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to the work.
Cells 2026, 15(5), 471; https://doi.org/10.3390/cells15050471
Submission received: 7 January 2026 / Revised: 27 February 2026 / Accepted: 3 March 2026 / Published: 5 March 2026

Highlights

What are the main findings?
  • TGF-β functions as an antagonist of mTORC1 activation.
  • TGF-β regulates CD8+ T cell memory via the transcriptional FOXO1-TCF1-Eomes and metabolic AMPK-ULK1-ATG7 pathways.
What are the implications of the main findings?
  • The Smad-independent TGF-β signaling pathway plays an important role in controlling T cell immunity.
  • TGF-β-related signaling is a critical node to target for the development of novel vaccines for the treatment of cancer and infectious diseases.

Abstract

CD8+ memory T (TM) cells are essential for vaccine-induced protective immunity. While transforming growth factor beta (TGF-β) triggers CD8+ TM cell differentiation, the underlying molecular mechanism(s) has yet to be uncovered. We therefore used a well-established cell culture protocol to prepare TGF-β-triggered CD8+ TM cells derived from chicken ovalbumin (OVA)-specific T cell receptor (TCR) transgenic OTI mice, and systematically characterized them using Western blotting, confocal microscopy, flow cytometry and Seahorse assay analyses. We found that TGF-β/T cells exhibit a TM cell phenotype (CD62L+KLRG1) and display long-term survival upon adoptive transfer into mice. To elucidate the signaling circuitry underpinning the observed transcriptional and metabolic changes required to promote CD8+ TM cell differentiation, we measured the expression of several critical factors and found that TGF-β triggered weak mTORC1 (mTORC1Weak) signaling. mTORC1Weak signaling in turn led to an increase in the abundance of key transcriptional (TCF1, FOXO1 and Eomes) and metabolic (AMPK-α1, ATG7, ULK1, SIRT1, OPA1 and LAL) factors and an elevation in mitochondrial mass and reliance on fatty acid oxidation (FAO). Our data thus reveal for the first time that TGF-β regulates CD8+ T cell memory by triggering mTORC1Weak-mediated activation of the transcriptional FOXO1-TCF1-Eomes and metabolic AMPK-ULK1-ATG7 pathways. Given that induction of more qualified CD8+ TM cells is one of the ultimate goals of vaccination, our findings identify additional targets critical to TGF-β-induced T cell memory, which may greatly impact future vaccine development for the treatment of cancer and infectious diseases.

1. Introduction

CD8+ T cells are essential for combatting cancer and infectious diseases [1]. CD8+ T cell responses proceed through three programmed phases: T cell proliferation, contraction and memory [2]. In the T cell proliferation phase, naïve T cells differentiate into effector T (TE) cells, which rely on glycolysis to meet cellular ATP demands. This is followed by a contraction phase, during which the majority (90–95%) of TE cells die of activation-induced cell apoptosis. The surviving 5–10% of T cells then form a long-term memory T (TM) cell population, which uses fatty acid oxidation (FAO) to generate ATP during the memory phase, and it is this TM cell population that promptly responds to the same pathogen upon re-invasion to induce a potent and protective CD8+ T cell recall response [2]. One of the classic phenotypic markers used to distinguish long-lived CD8+ TM cells from short-lived TE cells is the expression of the TM cell marker CD62L relative to the TE cell marker killer cell lectin-like receptor subfamily G member-1 (KLRG1) [2]. The TM cell population further consists of CD44+CD62L effector memory T (TEM), CD44+CD62L+ central memory T (TCM) and CD44+CD62L+CD45RA+ stem cell-like memory T (TSCM) cell subsets [2]. Among these CD8+ T cell subsets, TCM cells circulate in the blood and patrol lymphoid tissues, while TEM cells traffic through the blood and non-lymphoid tissues to protect against pathogen invasion [3]. Recently, it has been reported that the TE cell marker KLRG1 is also expressed on TEM cells [4]. Unlike TCM cells, which exhibit lower glycolytic activity and utilize FAO to preserve energy homeostasis, TEM cells rely on both FAO and glycolysis but maintain a higher rate of aerobic glycolysis to support their immediate effector functions and their capacity to rapidly respond to secondary infection [5].
Mammalian target of rapamycin complex-1 (mTORC1) is a major, evolutionally conserved environmental and energy sensor that regulates immune cell proliferation, differentiation and metabolism [6]. We previously used modern state-of-the-art biotechnology and genetic and pharmacological tools to elucidate the core molecular pathways that govern distinct mTORC1 signaling strengths critical to T cell memory formation [7,8,9]. We demonstrated that the inflammatory cytokine IL-2 stimulated strong mTORC1 signaling (mTORC1Strong) and induced short-term CD8+ TE (IL-2/TE) cell differentiation by activating the transcriptional T-bet and metabolic cMyc-HIF-1α (hypoxia-inducible factor-1α) pathways to promote the maturation of the CD8+ TE phenotype and glycolytic metabolism, respectively [8,9]. In contrast, the pro-survival cytokines IL-7 and IL-15 stimulated weak mTORC1 signaling (mTORC1Weak) to promote long-lived CD8+ TM (IL-7/TM and IL-15/TM) cell formation by coordinately activating the transcriptional FOXO1 (forkhead box-O-1)-TCF1 (T cell factor-1)-ID3 (inhibitor of DNA binding-3)-Eomes and metabolic AMPK-α1 (AMP-activated protein kinase-α1)-ULK1 (Unc-51-like autophagy-activating kinase-1)-ATG7 (autophagy-related gene-7) pathways controlling the CD8+ TM phenotype and FAO metabolism, respectively [8,9].
Transforming growth factor beta (TGF-β) is an immunosuppressive cytokine that directly inhibits both innate and adaptive T cell immune responses [10] and indirectly suppresses T cell responses by TGF-β-induced immunosuppressive CD4+ regulatory T (Treg) cells [11]. In addition, TGF-β signaling has been reported to promote CD8+ TM cell differentiation in vitro and in vivo in a mouse infection model [12,13]. TGF-β exposure has also been found to upregulate the levels of TM cell transcription factor signaling ID3 [12], reduce the abundance of the TE cell phenotypic marker KLRG1 [14] and suppress the metabolic regulator c-Myc essential for glycolysis metabolism [15]. However, the underlying transcriptional and metabolic pathways by which TGF-β signaling induces CD8+ T cell memory formation are largely unknown.
In this study, we systematically characterized TGF-β-stimulated T (TGF-β/T) cells and IL-2-stimulated T (IL-2/T) cells (used as a control) prepared by using well-established protocols [8,9,16]. We found that IL-2/T cells became short-term CD62LKLRG1+ TE (IL-2/TE) cells, while TGF-β/T cells differentiated into long-lived CD62L+KLRG1 TM (TGF-β/TM) cells. To identify the molecular pathways that control the formation of TGF-β/TM cells, we used flow cytometry, molecular and biochemical analyses [8,9] to demonstrate that TGF-β indeed triggered mTORC1Weak signaling, induced upregulation of transcription regulators FOXO1, TCF1 and Eomes and metabolic regulators AMPK-α1, ULK1, ATG7, SIRT1 (silent information regulator of transcription-1), OPA1 (optic atrophy-1) and LAL (lysosomal acid lipase), and promoted mitochondrial biogenesis and FAO. Thus, our findings provide the first evidence that TGF-β indeed regulates CD8+ T cell memory by triggering our previously reported mTORC1Weak signaling-mediated activation of the transcriptional FOXO1-TCF1-Eomes and metabolic AMPK-α1-ULK1-ATG7 pathways [8,9].

2. Materials and Methods

2.1. Mice, Antibodies and Reagents

In this study, the animal protocol (AUP#20180065) was approved by the Animal Use and Care Committee, University of Saskatchewan. C57BL/6 mice (B6, CD45.2+) were purchased from Charles River (Wilmington, MA, USA). B6.SJL-Ptprca Pepcb/BoyJ mice (B6.1, CD45.1+) and ovalbumin (OVA)-specific T cell receptor transgenic OTI mice on a B6 background were purchased from Jackson Laboratory (Bar Harbor, MA, USA). B6.1 mice were intercrossed with OTI mice to generate CD45.1+ B6.1/OTI mice in house at the University of Saskatchewan [8,9]. IL-2 and TGF-β recombinant proteins were purchased from Peprotech (Rocky Hill, NJ, USA). The following antibodies (Abs) were purchased from BioLegend (San Diego, CA, USA): Allophycocyanin (APC)-KLRG1, Brilliant Violet 421-CD62L, PE-CD44, PE-Cy5-CD8, FITC-CD45.1, APC-CD8, FITC-FOXO1 and FITC-TCF1. A PE-conjugated H-2Kb/OVA257–264 tetramer (PE-tetramer) was obtained from the Fred Hutchinson Cancer Research Center (Seattle, WA, USA). The following Abs were obtained from Cell Signaling Technology (Danvers, MA, USA): pS6 (S235/236), FOXO1, T-bet, TCF1, Eomes, cMyc, HIF-1α, pAMPK-α1 (T172), pULK1 (S555), ATG7, SIRT1, LAL, OPA1, β-actin and HRP-conjugated anti-rabbit IgG. The Easysep CD8+ T cell purification kit was acquired from StemCell Technologies (Vancouver, BC, Canada). DAPI (4′,6-diamidino-2-phenylindole) was purchased from ThermoFisher Scientific (Waltham, MA, USA). Fixation/permeabilization buffer was procured from BD (Franklin Lakes, NJ, USA). MitoTracker Green and Hoechst solution were purchased from Life Technologies Inc. (Carlsbad, CA, USA). Seahorse XF Mito Stress Test Kits were purchased from Agilent Technologies (Lexington, MA, USA).

2.2. Optimized Culture Protocol for IL-2/TE and TGF-β/TM Cell Preparation

CD8+ Tn cells were purified from the spleens of CD45.1+ B6.1/OTI mice using an Easysep CD8+ T cell purification kit. We then generated IL-2-stimulated effector T (IL-2/TE) cells by using our own established culture protocol [8,9] and TGF-β-stimulated memory T (TGF-β/TM) cells by making minor modifications to another culture protocol [16]. Briefly, CD8+ Tn cells were cultured in RPMI 1640 medium supplemented with 10% fetal bovine serum (FBS), 2-mercaptoethanol (2-ME, 50 µM) and ovalbumin (OVA)257–264 peptide (OVAI, SIINFEKL, 0.1 nM) in the presence of either IL-2 (100 U/mL) or IL-2 and TGF-β (10 ng/mL) (Peprotech, Rocky Hill, NJ, USA) for 3 days to yield IL-2/TE and TGF-β/TM cells, respectively. The activated CD8+ T cells were then cultured for another 2 days in the same medium lacking OVAI peptide to generate CD45.1+ IL-2/TE and TGF-β/TM cells. To ensure that our culture protocol was optimal, we performed two related experiments examining the effect of culture duration (3, 4 or 5 days) and TGF-β concentration (1, 3 or 10 ng/mL) on the relative abundance of factors critical to TGF-β/TM cell formation. Our results clearly indicate that culturing the TGF-β/TM cells for 5 days (Figure 1A) in media containing 10 ng/mL TGF-β (Figure 1B) resulted in the most significant reduction in pS6 (S235–236) levels and most pronounced upregulation in the abundance of the transcriptional FOXO1 and metabolic pAMPKα1 (T172) regulators. Thus, this culture protocol is indeed optimal for stimulating TGF-β-induced T cell memory.

2.3. Flow Cytometry

CD8+ IL-2/TE and TGF-β/TM cell populations were incubated for 30 min on ice in the dark with a mixture of APC-KLRG1, PE-CD44 and Brilliant Violet 421-CD62L Abs (each at 1:100) in 200 µL of flow cytometry buffer (2% FBS and 0.1% sodium azide in PBS). Cell samples were then washed twice with the same buffer and analyzed by flow cytometry. The frequency of KLRG1+CD62L TE cells was measured initially. Cell samples were then gated KLRG and KLRG1+CD62L+ TM cell populations were isolated to quantitate CD44+CD62L TEM and CD44+CD62L+ TCM cell subsets, respectively. Flow cytometry analyses were performed on a Cytoflex Multicolour Flow cytometer (Beckman, San Diego, CA, USA). Data were analyzed with FlowJo 10 software (FlowJo, Ashland, OR, USA) [8,9].

2.4. T Cell Survival Analyses

To assess T cell survival, viable CD45.1+ IL-2/TE and TGF-β/TM cells (5 × 106 cells/mouse) were intravenously (i.v.) injected into CD45.2+ B6 mice. Mouse peripheral blood samples were then harvested 1, 7 and 15 days post injection and stained with PE-Cy5-CD8, FITC-CD45.1, PE-CD44 and BV421-CD62L Abs, and CD8+CD45.1+ IL-2/TE and TGF-β/TM cell abundance was quantified by flow cytometric analysis [8,9]. The CD8+CD45.1+ TGF-β/TM cells were then analyzed for TEM and TCM by measuring CD44 and CD62L expressions. To assess TM cell recall responses, recipient mice were challenged one month post adoptive T cell transfer by i.v. injection with 2000 CFUs of recombinant Listeria monocytogenes OVA (rLmOVA), and the abundance of PE-tetramer+ FITC-CD8+ T cells was quantified by flow cytometry 4 days after the rLmOVA boost [8,9].

2.5. Western Blotting

CD8+ IL-2/TE and TGF-β/TM cells were lysed in ice-cold RIPA buffer containing a protease and phosphatase inhibitor cocktail (Thermo Fisher Scientific, Waltham, MA, USA). Equal amounts of cell lysate (20 µg) were separated by SDS-PAGE and transferred onto PVDF membrane. The membrane was blocked with 5% BSA in PBS containing 0.05% Tween-20 (PBST) and incubated with various antibodies overnight at 4 °C. After washing with PBST for 10 min/wash for a total of 30 min, the membrane was incubated in secondary antibody for 1 h at room temperature. The membrane was then washed again as described above and imaged using a BioRad Chemidoc MP (Bio-Rad, Hercules, CA, USA). Band intensities were analyzed with Image J software (ImageJ.JS (https://ij.imjoy.io/), TreeStar, Ashland, OR, USA), and β-actin intensity was used as an internal reference control to normalize for differences in loading across lanes [8,9].

2.6. Confocal Microscopy

To visualize the intracellular localization of TCF1 or FOXO1, CD8+ IL-2/TE and TGF-β/TM cells were incubated with an APC-CD8 Ab at 4 °C for 30 min. T cells were then fixed and permeabilized in fixation/permeabilization buffer at 4 °C for 20 min, washed once with 1× permeabilization wash buffer, and incubated at 4 °C for 30 min with FITC-Abs against FOXO1 or TCF1 (1:100) in 1× permeabilization buffer. After 3 washes with 1× permeabilization wash buffer, an antifade mountant with DAPI was added and the cells were then deposited on microscope slides and coverslipped. Microscope slides were imaged by using the Zeiss LSM700 confocal microscope (Carl Zeiss, Oberkochen, BW, Germany). Confocal imaging was analyzed using ZEN 3.8 imaging software, as previously described [8,9].

2.7. Mitochondrial Analysis

To measure mitochondrial mass, IL-2/TE or TGF-β/TM cells were incubated with 50 nM MitoTracker Green (Life Technologies Inc., Carlsbad, CA, USA) for 15 min at 37 °C in the dark, washed three times with PBS and analyzed by flow cytometry. To directly visualize mitochondrial content, after staining with MitoTracker Green, IL-2/TE and TGF-β/TM cells were then incubated with Hoechst 33342 solution (5 µg/mL) for 5 min at 37 °C in the dark. Cells were then deposited on microscope slides, coverslipped and imaged using the Zeiss LSM700 confocal microscope (Carl Zeiss, Oberkochen, BW, Germany) [8,9].

2.8. Seahorse Assay

Mitochondrial respiration and glycolytic activity of IL-2/TE and TGF-β/TM cells were assessed by measuring the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) using a Seahorse XFp Analyzer (Agilent Technologies, Santa Clara, CA, USA), according to the manufacturer’s instructions. Cells were seeded onto XF8 cell culture microplates at 1.5 × 105 cells per well in assay medium supplemented with glucose (10 mM), sodium pyruvate (1 mM) and L-glutamine (2 mM). A mitochondrial stress test was conducted by measuring OCR (pmol/min) under basal conditions and following sequential injections of 1.5 µM oligomycin (port A), 2.5 µM FCCP (port B), and 0.5 µM rotenone and antimycin A (port C) into their respective ports, as previously described [8,9]. Data were analyzed by Seahorse Wave Desktop Software (v2.6.3; Agilent Technologies, Santa Clara, CA, USA).

2.9. Statistical Analysis

Results are expressed as mean values with standard deviation (SD). Statistical significance between groups was determined using Student’s t-test. All statistical analyses were performed with Prism 8 software (GraphPad, La Jolla, CA, USA) [8,9]. Probability values of p < 0.05 were considered statistically significant, and p < 0.01 was considered very statistically significant.

3. Results and Discussion

3.1. TGF-β Stimulates the Formation of TGF-β/TM Cells with Long-Term Survival

We used our optimized cell culture protocol to prepare TGF-β-stimulated CD45.1+ TGF-β/T cells and IL-2-stimulated IL-2/T cells from naïve CD8+ T cells derived from CD45.1+ OTI mouse spleen (Figure 2A) [8,9]. To characterize their phenotypes, we first stained the IL-2/T and TGF-β/T cell populations with a cocktail of antibodies specific for the TE cell marker KLRG1 and the TM cell markers CD44 and CD62L and conducted flow cytometric analysis. We found that IL-2/T and TGF-β/T cell populations consisted of 97% and 10% KLRG1+CD62L TE cells, respectively (Figure 2B). We next assessed the enrichment of TM cell subsets within the IL-2/T and TGF-β/T cell populations. Since the TE cell marker KLRG1 was found to be expressed on TEM cells [4], we gated the 2% and 1% KLRG1+CD62L+ TM cells found in each population for further analysis of CD44 expression and found that they were all KLRG1+CD44+CD62L+ TCM cells (Figure 2B). We next gated the 89% KLRG1 (28% KLRGCD62L and 61% KLRG1CD62L+) T cell population to measure CD44 expression and found that the KLRG T cell population consisted of a similar amount of 49% CD44+CD62L TEM and 50% CD44+CD62L+ TCM cells, respectively (Figure 2B). Taken together, our data indicate that the IL-2-stimulated IL-2/T cells consisted almost entirely of KLRG1+CD62L TE cells and are indeed IL-2/TE cells, while TGF-β-stimulated TGF-β/T cells mainly consisted of TM cells (49% CD44+CD62L TEM, 50% CD44+CD62L+ TCM and 1% KLRG1+CD44+CD62L+ TCM cells) and may thus be classified as TGF-β/TM cells.
To further assess their in vivo survival, we adoptively transferred an equal number of viable CD45.1+ IL-2/TE and TGF-β/TM cells (5 × 106 cells/each mouse) into CD45.2+ B6 mice, and tracked their survival 1, 7 and 15 days post adoptive T cell injection by flow cytometric analysis of peripheral blood samples. Our data demonstrate that TGF-β/TM and IL-2/TE cells were found at similar percentages in peripheral blood 1 day post injection (Figure 2C), confirming that we had indeed injected a similar number of TGF-β/TM and IL-2/TE cells into B6 mice. However, we observed many more TGF-β/TM cells (1.58% and 1.43%) in peripheral blood when compared to IL-2/TE cells (0.20% and 0.12%) at the 7- and 15-day time points (Figure 2C), indicating that TGF-β/TM cells survive much longer than IL-2/TE cells in host B6 mice. Our data thus confirm that our TGF-β/T and IL-2/T cells are authentic, long- and short-lived CD62L+KLRG1 TM and CD62LKLRG1+ TE cells, respectively [8,9]. To further characterize the long-lived TM cells, we also analyzed the frequencies of the CD44+CD62L TEM and CD44+CD62L+ TCM subsets within the CD8+CD45.1+ T cell population in mouse peripheral blood 15 days post adoptive transfer of TGF-β/TM cells. Flow cytometry analyses demonstrated that TEM and TCM cells each represent roughly 50% of the total population (Figure 2C), indicating that both CD44+CD62L TEM and CD44+CD62L+ TCM cells exhibit similar survival profiles.
To further assess the competency of TM cells, we assayed recall response one month after adoptive transfer of IL-2/TE and TGF-β/TM cells by boosting the mice with the same adjuvant and measuring the response 4 days later. These analyses demonstrated that mice harboring TGF-β/TM cells exhibited an 8-fold-higher OVA-specific CD8+ T cell recall response than mice infused with IL-2/TE cells (Figure 2C) and thus corroborate the functional integrity of infused TM cells in recipient mice.

3.2. TGF-β Modulates mTORC1 Signaling

We recently demonstrated that IL-7 and IL-15 stimulate mTORC1Weak signaling to promote the differentiation and formation of CD8+ IL-7/TM and IL-15/TM cells [8,9]. To assess the relative strength of mTORC1 signaling triggered by TGF-β, we measured the abundance of the downstream target substrate ribosomal S6 protein by Western blot analysis of total TGF-β/TM and IL-2/TE cell lysates. Consistent with previous reports [8,9,16], we found that the abundance of phosphorylated S6 protein (pS6; Ser235/236) was significantly downregulated in TGF-β/TM cells relative to IL-2/TE cells (Figure 3A), which are known to harbor mTORC1Strong signaling [8,9]. Our data therefore indicate that TGF-β functions as an antagonist of mTORC1 activation, thereby triggering mTORC1Weak signaling in TGF-β/TM cells.

3.3. TGF-β Induces CD8+ TM Cell Formation via mTORC1Weak Signaling-Mediated Activation of the Transcriptional FOXO1-TCF1-Eomes Pathway

We next measured the abundance of transcription factors known to be downstream of mTORC1Weak (FOXO1, TCF1 and Eomes) and mTORC1Strong (T-bet) signaling. Consistent with our earlier findings of mTORC1Weak signaling, Western blot data demonstrated that the abundance of FOXO1, TCF1 and Eomes was elevated in TGF-β/TM cells while that of T-bet was reduced, with the reciprocal expression profile being observed in IL-2/TE cells (Figure 3A). These data collectively indicate that TGF-β indeed triggered mTORC1Weak signaling to promote TGF-β/TM cell formation via activation of the transcriptional FOXO1-TCF1-Eomes pathway controlling the CD62L+KLRG1 TM cell phenotype, while IL-2-stimulated mTORC1Strong signaling induces IL-2/TE cell differentiation via activation of the transcriptional T-bet pathway regulating the CD62LKLRG1+ TE cell phenotype and functional cytotoxicity [8,9].
It has been reported that FOXO1 and TCF1 must localize to the nucleus to exert their functional effects on TM cell formation [8,9]. Therefore, we also performed confocal microscopy analyses to visualize their subcellular localization and found that more FOXO1 and TCF1 protein was indeed localized to the nuclei of TGF-β/TM cells when compared with IL-2/TE cells (Figure 3B,C). Our results thus provide further evidence that the nuclear localization of FOXO1 and TCF1 is required to express the CD62L+KLRG1 TGF-β/TM cell phenotype.

3.4. TGF-β Stimulates CD8+ TM Cell Formation via mTORC1Weak Signaling-Mediated Activation of the Metabolic AMPK-α1-ULK1-ATG7 Pathway

AMPK-α1 is a major, evolutionally conserved energy sensor that controls more than one hundred autogenic and mitochondrial respiratory proteins involved in almost all branches of catabolic metabolism [17]. Phosphorylated AMPK-α1 (pAMPK-α1, T172) activates ULK1 (pULK1, S555) and ATG7 [18] along with various metabolic regulators including SIRT1, OPA1 and LAL [19,20,21], which act in concert to increase mitochondrial mass and reliance on FAO metabolism [22] in support of CD8+ TM cell formation [8,9,16]. TE cells exhibit strong mTORC1 signaling, which instead activates the metabolic master regulator hypoxia-inducible factor (HIF)-1α to augment glycolytic flux and generate the ATP required for CD8+ TE cell functional activity [8,9]. To investigate which metabolic pathway TGF-β activates in TGF-β/TM cells, we performed Western blot analysis and demonstrated that the autophagy regulators pAMPK-α1 (T172), pULK1 (S555) and ATG7 as well as their downstream metabolic regulators SIRT1, OPA1 and LAL were all upregulated in TGF-β/TM cells, while cMyc and its downstream target HIF-1α were downregulated (Figure 4A). The reciprocal expression profile was observed for IL-2/TE cells (Figure 4A). Our data collectively indicate that TGF-β triggered mTORC1Weak signaling to activate the metabolic AMPK-α1-ULK1-ATG7 pathway and stimulate ATP production via FAO in TGF-β/TM cells.

3.5. TGF-β Promotes an Increase in Mitochondrial Content and FAO Metabolism in TGF-β/TM Cells

Mitochondria serve as bioenergetic and signaling organelles that play a crucial role in support of TM cell survival [23] by providing adequate oxidative phosphorylation (OXPHOS) potential to maintain spare respiratory capacity, which is essential for FAO [24,25]. Therefore, we used MitoTracker Green to specifically stain mitochondrial membranes in IL-2/TE and TGF-β/TM cells, and quantified and visualized organelle content by flow cytometry and confocal microscopy analyses, respectively [8,9]. Our data show that TGF-β promoted an increased mitochondrial mass in TGF-β/TM cells when compared to IL-2/TE cells (Figure 4B,C). To assess how TGF-β impacts energy metabolism in TM cells, we used the Seahorse assay to analyze the bioenergetic profiles of IL-2/TE and TGF-β/TM cells. Measurements were taken under baseline conditions and after the sequential application of specific OXPHOS inhibitors, as previously described [8,9]. These analyses demonstrated that TGF-β/TM cells displayed a low extracellular acidification rate (ECAR) (Figure 5A) and a high oxygen consumption rate (OCR) (Figure 5B,C), with the elevated OCR/ECAR indicating that TGF-β/TM cells rely on FAO metabolism to maintain energy homeostasis [8,9]. In contrast, IL-2/TE cells had a higher ECAR (Figure 5A) and a lower ratio of OCR/ECAR (Figure 5B), indicating that IL-2/TE cells rely on glycolytic metabolism to meet cellular ATP demands [8,9].
The signaling pathway of the TGF-β superfamily is conserved in both immune and non-immune cells [26]. Active TGF-β binds to its specific receptor TGF-βRII. Then, two TGF-βRIIs and two TGF-βRIs form a tetrameric receptor complex. TGF-βRII phosphorylates and activates TGF-βRI to regulate the downstream activity of two distinct signaling pathways [26]. First, TGF-β activate r-Smad2 proteins, which in turn interact with co-Smad4 to translocate into the nucleus to control target gene expression by interacting with various transcription factors and co-regulators. For example, TGF-β signaling triggers CD4+Foxp3+ Treg cell differentiation via activation of a Smad-dependent Smad3-Foxp3 pathway (Figure 6A) [27,28]. Second, TGF-β binding to its receptor also induces Smad-independent inhibition of the PI3K-AKT-mTORC1 pathway (Figure 6A), consistent with previous reports [8,9,16].
The “linear cell differentiation (LCD)” or “distinct signaling strengths” model was originally proposed by Sallusto’s group in 2000 and posits that strong and weak strengths of stimulatory signals control T cell differentiation into either short-lived TE or long-lived TM cells [29]. In 2009, Ahmed’s group provided the first evidence that treatment with rapamycin (Rapa), an mTORC1 inhibitor, promotes CD8+ TM cell differentiation [30]. This finding was further supported by evidence that Rapa induces T cell memory via a FOXO1-mediated transcriptional switch from T-bet to Eomes [31]. At the time, however, the molecular mechanism(s) underlying Rapa-dependent promotion of T cell memory was largely unknown. We previously demonstrated that treatment with the pro-survival cytokines IL-7 and IL-15 [8,9] or Rapa all induced mTORC1Weak signaling [2] to promote CD8+ TM cell formation via activation of the transcriptional FOXO1-TCF1-Eomes and metabolic AMPK-α1-ULK1-ATG7 pathways. In the current study, we further found that TGF-β also induced mTORC1Weak signaling to stimulate TM cell differentiation via activation of the above molecular pathways, thus providing another good example in support of the “distinct signaling strengths” model for TM cell differentiation [7].
Consistent with our previous findings [2,8,9], we show in this study that IL-2/TE cells exhibit strong mTORC1 signaling, which promotes CD8+ TE cell formation by activating the transcriptional T-bet and metabolic cMyc-HIF-1α pathways controlling the CD62LKLRG1+ phenotype and conferring the cytotoxic properties and reliance on glycolysis (Figure 6B). Interestingly, our study also demonstrates that TGF-β signaling functions as an antagonist of mTORC1 activation and induces its Smad-independent inhibition to trigger mTORC1Weak signaling. We thus provide the first evidence that TGF-β signaling promotes CD8+ TM cell formation by triggering our previously reported mTORC1Weak-mediated activation of the transcriptional FOXO1-TCF1-Eomes and the metabolic AMPK-α1-ULK1-ATG7 pathways, which act in concert to control the CD62L+KLRG1 phenotype and increase mitochondrial content and reliance on FAO to support the longevity and functionality of TGF-β/TM cells (Figure 6B) [2,8,9].
Exhausted CD8+ T (Tex) cells are often seen in response to chronic infection or in the tumor microenvironment under conditions of chronic antigenic stimulation. Tex cells are characterized by a dysfunctional phenotype and upregulation of inhibitory co-stimulatory molecules such as programmed death-1 (PD-1), lymphocyte activation gene-3 (LAG3) and T cell immunoglobulin- and mucin-containing protein-3 (TIM3). Immune checkpoint PD-1 blockade is known to reverse exhaustion in early progenitor exhausted T (Tpex) cells [32]. Similarly, TGF-β-dependent suppression of mTORC1 signaling in CD8+ Tpex cells has also been shown to reduce the formation of terminally exhausted Tex cells and prevent their death [16].

3.6. Conclusions

Taken together, our study uncovered that TGF-β triggers mTORC1Weak signaling-mediated activation of the transcriptional FOXO1-TCF1-Eomes and metabolic AMPK-α1-ULK1-ATG7 pathways to induce CD8+ T cell memory. As such, our study identified additional targets, which may greatly impact vaccine development for the treatment of cancer and infectious diseases, given that one of the ultimate goals of vaccination is to induce more qualified CD8+ TM cells.

Author Contributions

J.X. designed the study and analyzed and interpreted the data. Z.W. and M.Y. performed experiments and prepared the figures. J.X. and Z.W. wrote the manuscript. S.C.L., J.Y. and J.H. jointly analyzed the data, prepared the discussion section and contributed to manuscript review and revisions. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Canadian Institutes of Health Research (CIHR) Project grant #419228 to J.X.

Institutional Review Board Statement

The approved animal study protocol (#20180065) was renewed by the Institutional Review Committee of the University of Saskatchewan on 16 January 2026.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries regarding the associated data or reagents can be made by contacting the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

AMPK-1αAMP-activated protein kinase-1α
APCAllophycocyanin
ATG7autophagy-related gene-7
ATPadenosine triphosphate
CPT1αcarnitine palmitoyl transferase-1α
DRP1dynamin-related protein-1
ECARextracellular acidification rate
ETCelectron transport chain
FAOfatty acid oxidation
FOXO1forkhead box-O-1
HIF-1αhypoxia-inducible factor-1α
ID2DNA binding-2
ID3DNA binding-3
KLRG1killer cell lectin-like receptor subfamily G member-1
LALlysosomal acid lipase
mTORC1mammalian target of rapamycin complex-1
OCRO2 consumption rate
OPA1optic atrophy-1
OVAovalbumin
OXPHOSoxidative phosphorylation
PI3Kphosphatidylinositol-3 kinase
SIRT1silent information regulator of transcription-1
SRCspare respiratory capacity
TCF1T cell factor-1
TEeffector T
TGF-βtransforming growth factor beta
TMmemory T
ULK1Unc-51-like autophagy-activating kinase-1
WTwild-type

References

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Figure 1. (A) Schematic diagram of the experimental design for the optimization of the in vitro preparation of IL-2/TE or TGF-β/TM cells from naïve cells purified from OTI mice. Cell lysates (CLs) were collected on day 3, 4 and 5 (upper). IL-2/TE day 5 and TGF-β/TM day 3, 4 and 5 CLs were then analyzed by Western blotting to quantify the abundance of proteins of interest (lower). (B) Schematic diagram of the experimental design for the optimization of TGF-β concentration (1, 3 and 10 ng/mL) for the in vitro preparation of IL-2/TE or TGF-β/TM cells from naïve cells purified from OTI mice (upper). IL-2/TE and TGF-β/TM CLs were prepared on day 5 and analyzed by Western blotting to quantify the abundance of proteins of interest (lower). For both panels A and B, the data reflect representative results from one of two independent experiments. Bar graphs depict the fold change in the abundance of each protein upon normalization to β-actin levels, which served as an internal loading control. Data are presented as the mean (n = 3) ± SD; * p < 0.05, ** p < 0.01 detected by Student’s t-test. NC denotes no change.
Figure 1. (A) Schematic diagram of the experimental design for the optimization of the in vitro preparation of IL-2/TE or TGF-β/TM cells from naïve cells purified from OTI mice. Cell lysates (CLs) were collected on day 3, 4 and 5 (upper). IL-2/TE day 5 and TGF-β/TM day 3, 4 and 5 CLs were then analyzed by Western blotting to quantify the abundance of proteins of interest (lower). (B) Schematic diagram of the experimental design for the optimization of TGF-β concentration (1, 3 and 10 ng/mL) for the in vitro preparation of IL-2/TE or TGF-β/TM cells from naïve cells purified from OTI mice (upper). IL-2/TE and TGF-β/TM CLs were prepared on day 5 and analyzed by Western blotting to quantify the abundance of proteins of interest (lower). For both panels A and B, the data reflect representative results from one of two independent experiments. Bar graphs depict the fold change in the abundance of each protein upon normalization to β-actin levels, which served as an internal loading control. Data are presented as the mean (n = 3) ± SD; * p < 0.05, ** p < 0.01 detected by Student’s t-test. NC denotes no change.
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Figure 2. TGF-β stimulates the differentiation of CD8+ TM cells by upregulating CD62L and downregulating KLRG1 expression to promote survival. (A) Schematic diagram of the experimental protocol used for the in vitro preparation of IL-2/TE or TGF-β/TM cells from naïve cells purified from CD45.1+/2+ WT OTI mice. (B) IL-2/TE and TGF-β/TM cells were stained with anti-CD62L, KLRG1 and CD44 antibodies for flow cytometry analysis. The first set of representative flow cytometry plots showed 97% and 10% KLRG1+CD62L TE cells in IL-2/T and TGF-β/T cell populations, respectively. We then gated KLRG1+CD62L+ TM cells in IL-2/T and TGF-β/T cell populations and gated KLRG1 T cells in TGF-β/T cell population for measuring CD44 and CD62L expression in the second set of flow cytometry plots. (C) IL-2/TE or TGF-β/TM cells were i.v. injected into B6 (CD45.2+) mice, and their relative abundance was detected by flow cytometry 1, 7 and 15 days post injection. Flow cytometry scatter plots and bar graphs show the percentage of donor CD8+ CD45.1+ T cells expressed relative to the number of total host CD8+ T cells. The donor CD8+ CD45.1+ cells were then analyzed for TEM and TCM by measuring CD44 and CD62L expression. The recipient mice were re-challenged by i.v. injection with rLmOVA one month after adoptive T cell transfer. Flow cytometric analysis of PE-tetramer+ and FITC-CD8+ T cell abundance was performed on day 4 after the rLmOVA boost. Flow cytometry scatter plots and bar graphs show the percentage of tetramer+CD8+ T cells. These representative data reflect results from one of two independent experiments. Data are presented as the mean (n = 3) ± SD. ** p < 0.01 by Student’s t-test.
Figure 2. TGF-β stimulates the differentiation of CD8+ TM cells by upregulating CD62L and downregulating KLRG1 expression to promote survival. (A) Schematic diagram of the experimental protocol used for the in vitro preparation of IL-2/TE or TGF-β/TM cells from naïve cells purified from CD45.1+/2+ WT OTI mice. (B) IL-2/TE and TGF-β/TM cells were stained with anti-CD62L, KLRG1 and CD44 antibodies for flow cytometry analysis. The first set of representative flow cytometry plots showed 97% and 10% KLRG1+CD62L TE cells in IL-2/T and TGF-β/T cell populations, respectively. We then gated KLRG1+CD62L+ TM cells in IL-2/T and TGF-β/T cell populations and gated KLRG1 T cells in TGF-β/T cell population for measuring CD44 and CD62L expression in the second set of flow cytometry plots. (C) IL-2/TE or TGF-β/TM cells were i.v. injected into B6 (CD45.2+) mice, and their relative abundance was detected by flow cytometry 1, 7 and 15 days post injection. Flow cytometry scatter plots and bar graphs show the percentage of donor CD8+ CD45.1+ T cells expressed relative to the number of total host CD8+ T cells. The donor CD8+ CD45.1+ cells were then analyzed for TEM and TCM by measuring CD44 and CD62L expression. The recipient mice were re-challenged by i.v. injection with rLmOVA one month after adoptive T cell transfer. Flow cytometric analysis of PE-tetramer+ and FITC-CD8+ T cell abundance was performed on day 4 after the rLmOVA boost. Flow cytometry scatter plots and bar graphs show the percentage of tetramer+CD8+ T cells. These representative data reflect results from one of two independent experiments. Data are presented as the mean (n = 3) ± SD. ** p < 0.01 by Student’s t-test.
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Figure 3. TGF-β stimulates CD8+ TM cell differentiation via mTORC1weak signaling, which activates the transcriptional FOXO1-TCF1-Eomes pathway. (A) Lysates of IL-2/TE and TGF-β/TM cells were analyzed by Western blotting to quantify the abundance of proteins of interest. Bar graphs represent the fold change in each protein normalized to β-actin levels. Data are presented as the mean (n = 3) ± SD; * p < 0.05, ** p < 0.01 by Student’s t-test. (B,C) IL-2/TE and TGF-β/TM cells were permeabilized and incubated with antibodies against CD8 (red) and FOXO1 (green) or TCF1 (green). DAPI (blue) was used to counterstain nuclei, and the subcellular localization of FOXO1 (B) or TCF1 (C) was visualized by confocal microscopy using a 40× objective lens magnification. These data reflect results representative of two independent experiments.
Figure 3. TGF-β stimulates CD8+ TM cell differentiation via mTORC1weak signaling, which activates the transcriptional FOXO1-TCF1-Eomes pathway. (A) Lysates of IL-2/TE and TGF-β/TM cells were analyzed by Western blotting to quantify the abundance of proteins of interest. Bar graphs represent the fold change in each protein normalized to β-actin levels. Data are presented as the mean (n = 3) ± SD; * p < 0.05, ** p < 0.01 by Student’s t-test. (B,C) IL-2/TE and TGF-β/TM cells were permeabilized and incubated with antibodies against CD8 (red) and FOXO1 (green) or TCF1 (green). DAPI (blue) was used to counterstain nuclei, and the subcellular localization of FOXO1 (B) or TCF1 (C) was visualized by confocal microscopy using a 40× objective lens magnification. These data reflect results representative of two independent experiments.
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Figure 4. TGF-β stimulates CD8+ TM cell differentiation via mTORC1weak signaling, which activates the metabolic AMPK-α1-ULK1-ATG7 pathway and increases mitochondrial content. (A) Lysates of IL-2/TE and TGF-β/TM cells were analyzed by Western blotting to quantify the abundance of proteins of interest. Bar graphs represent the fold change in each protein normalized to β-actin levels. Data are presented as the mean (n = 3) ± SD. * p < 0.05, ** p < 0.01 by Student’s t-test. (B) IL-2/TE and TGF-β/TM cells were stained with MitoTracker Green and analyzed by flow cytometry to measure mitochondrial content. Data from two independent experiments were quantified and expressed as the relative fold change in mean fluorescence intensity (MFI). Data are presented as the mean ± SD. * p < 0.05 by Student’s t-test. (C) IL-2/TE and TGF-β/TM cells were stained with MitoTracker Green and Hoechst 33342 solution (blue) and imaged by confocal microscopy to directly visualize mitochondria. A 40× objective lens magnification was used, and representative data from one of two independent experiments are shown.
Figure 4. TGF-β stimulates CD8+ TM cell differentiation via mTORC1weak signaling, which activates the metabolic AMPK-α1-ULK1-ATG7 pathway and increases mitochondrial content. (A) Lysates of IL-2/TE and TGF-β/TM cells were analyzed by Western blotting to quantify the abundance of proteins of interest. Bar graphs represent the fold change in each protein normalized to β-actin levels. Data are presented as the mean (n = 3) ± SD. * p < 0.05, ** p < 0.01 by Student’s t-test. (B) IL-2/TE and TGF-β/TM cells were stained with MitoTracker Green and analyzed by flow cytometry to measure mitochondrial content. Data from two independent experiments were quantified and expressed as the relative fold change in mean fluorescence intensity (MFI). Data are presented as the mean ± SD. * p < 0.05 by Student’s t-test. (C) IL-2/TE and TGF-β/TM cells were stained with MitoTracker Green and Hoechst 33342 solution (blue) and imaged by confocal microscopy to directly visualize mitochondria. A 40× objective lens magnification was used, and representative data from one of two independent experiments are shown.
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Figure 5. TGF-β-stimulated CD8+ TM cells have substantial mitochondrial spare respiratory capacity (SRC) and rely on FAO. (A) ECAR and (B) the OCR/ECAR ratio of IL-2/TE and TGF-β/TM cells were analyzed by Seahorse assay. (C) Line tracing of the OCR profile measured in real time and in response to the indicated mitochondrial inhibitors. Vertical dotted lines indicate the times when oligomycin (1.5 µM), FCCP (2.5 µM), and rotenone and antimycin A (0.5 µM) were added sequentially. These representative data reflect results from one of two independent experiments. Data are presented as the mean (n = 3) ± SD. ** p < 0.01 by Student’s t-test.
Figure 5. TGF-β-stimulated CD8+ TM cells have substantial mitochondrial spare respiratory capacity (SRC) and rely on FAO. (A) ECAR and (B) the OCR/ECAR ratio of IL-2/TE and TGF-β/TM cells were analyzed by Seahorse assay. (C) Line tracing of the OCR profile measured in real time and in response to the indicated mitochondrial inhibitors. Vertical dotted lines indicate the times when oligomycin (1.5 µM), FCCP (2.5 µM), and rotenone and antimycin A (0.5 µM) were added sequentially. These representative data reflect results from one of two independent experiments. Data are presented as the mean (n = 3) ± SD. ** p < 0.01 by Student’s t-test.
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Figure 6. TGF-β signaling regulates the expression of various autophagic and mitochondrial respiratory molecules in T cell memory. (A) Schematic diagram illustrating that TGF-β binds to its receptor to activate a Smad-dependent pathway that regulates CD4+ Treg cell differentiation. TGF-β binding to its receptor also triggers Smad-independent suppression of the PI3K-AKT-mTOR pathway (up arrow: upregulation; down arrow: downregulation). (B) Schematic diagram showing that TGF-β promotes CD8+ TM cell formation by triggering mTORC1Weak signaling to activate the transcriptional FOXO1-TCF1-Eomes and metabolic AMPK-1α-ULK1-ATG7 pathways in TGF-β/TM cells. Stronger mTORC1 signaling such as that observed upon IL-2 stimulation induces CD8+ TE cell differentiation by activation of the transcriptional T-bet and metabolic cMyc-HIF-1α pathways.
Figure 6. TGF-β signaling regulates the expression of various autophagic and mitochondrial respiratory molecules in T cell memory. (A) Schematic diagram illustrating that TGF-β binds to its receptor to activate a Smad-dependent pathway that regulates CD4+ Treg cell differentiation. TGF-β binding to its receptor also triggers Smad-independent suppression of the PI3K-AKT-mTOR pathway (up arrow: upregulation; down arrow: downregulation). (B) Schematic diagram showing that TGF-β promotes CD8+ TM cell formation by triggering mTORC1Weak signaling to activate the transcriptional FOXO1-TCF1-Eomes and metabolic AMPK-1α-ULK1-ATG7 pathways in TGF-β/TM cells. Stronger mTORC1 signaling such as that observed upon IL-2 stimulation induces CD8+ TE cell differentiation by activation of the transcriptional T-bet and metabolic cMyc-HIF-1α pathways.
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MDPI and ACS Style

Wu, Z.; Yu, M.; Leary, S.C.; Yuan, J.; Huang, J.; Xiang, J. TGF-β Regulates CD8+ T Cell Memory by Triggering mTORC1Weak-Mediated Activation of the Transcriptional FOXO1-TCF1-Eomes and Metabolic AMPK-ULK1-ATG7 Pathways. Cells 2026, 15, 471. https://doi.org/10.3390/cells15050471

AMA Style

Wu Z, Yu M, Leary SC, Yuan J, Huang J, Xiang J. TGF-β Regulates CD8+ T Cell Memory by Triggering mTORC1Weak-Mediated Activation of the Transcriptional FOXO1-TCF1-Eomes and Metabolic AMPK-ULK1-ATG7 Pathways. Cells. 2026; 15(5):471. https://doi.org/10.3390/cells15050471

Chicago/Turabian Style

Wu, Zhaojia, Michelle Yu, Scot C Leary, Jianbo Yuan, Junqiong Huang, and Jim Xiang. 2026. "TGF-β Regulates CD8+ T Cell Memory by Triggering mTORC1Weak-Mediated Activation of the Transcriptional FOXO1-TCF1-Eomes and Metabolic AMPK-ULK1-ATG7 Pathways" Cells 15, no. 5: 471. https://doi.org/10.3390/cells15050471

APA Style

Wu, Z., Yu, M., Leary, S. C., Yuan, J., Huang, J., & Xiang, J. (2026). TGF-β Regulates CD8+ T Cell Memory by Triggering mTORC1Weak-Mediated Activation of the Transcriptional FOXO1-TCF1-Eomes and Metabolic AMPK-ULK1-ATG7 Pathways. Cells, 15(5), 471. https://doi.org/10.3390/cells15050471

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