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. Author manuscript; available in PMC: 2026 Mar 24.
Published in final edited form as: Exp Eye Res. 2026 Mar 7;267:110957. doi: 10.1016/j.exer.2026.110957

GSK3β promotes p53/Nrf2-dependent expression of the stress response protein REDD2 in retinal Müller glia exposed to hyperlipidemic conditions

Ashley M VanCleave 1, Siddharth Sunilkumar 1, Allyson L Toro 1, Scot R Kimball 1, Michael D Dennis 1,2
PMCID: PMC13007010  NIHMSID: NIHMS2156207  PMID: 41802695

Abstract

The stress response proteins regulated in development and DNA damage (REDD)1 and REDD2 act as negative regulators of mechanistic target of rapamycin complex 1 (mTORC1). While the role of REDD1 in diabetes complications in the retina has been well-explored, the potential contribution of REDD2 has not been previously examined. In mice fed a pro-diabetogenic high-fat diet, REDD2 mRNA ribosome-association was increased in retinal Müller glia. Hyperlipidemic culture conditions also increased both REDD1 and REDD2 mRNA expression in human Müller cell cultures. Mechanistic studies identified key regulatory residues in REDD2 at P100 and K179/Y182 that were necessary for mTORC1 suppression. In Müller cells exposed to hyperlipidemic conditions, REDD1 and REDD2 mRNA expression were upregulated in coordination with markers of ER stress. However, chemical induction of ER stress with tunicamycin increased REDD1, but not REDD2. Rather, increased REDD2 mRNA expression in Müller cells exposed to hyperlipidemic conditions required the transcription factors p53 and nuclear factor erythroid 2-related factor 2 (Nrf2). Unlike the Nrf2-target heme oxygenase 1 (HO-1), the effect of Nrf2 on REDD2 was redox-independent, as REDD2 expression was insensitive to the antioxidant N-acetylcysteine, the Nrf2 agonist sulforaphane, or oxidant stress. Hyperlipidemic conditions attenuated the inhibitory phosphorylation of glycogen synthase kinase 3β (GSK3β) and GSK3β inhibition suppressed REDD2 mRNA expression under hyperlipidemic conditions. Expression of a constitutively active GSK3β variant also promoted REDD2 mRNA expression in a manner that required both p53 and Nrf2. The findings support that GSK3β promotes REDD2 mRNA transcription in Müller glia under hyperlipidemic conditions via activation of p53/Nrf2.

Keywords: DDIT4, DDIT4L, p53, Nrf2, GSK3β, hyperlipidemia

Graphical Abstract

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1. Introduction

Consumption of a high-fat diet contributes to the development of retinal complications, including diabetic retinopathy [1]. High-fat diets provide excess fatty acid substrates for de novo sphingolipid synthesis and consequently drive the local accumulation of sphingolipids. Several sphingolipid species, including ceramides, act not only as structural lipids, but also function as important bioactive signaling molecules. We previously demonstrated that feeding mice a diet high in saturated fats increases retinal sphingolipid content and down-regulates insulin receptor (IR)-mediated signaling within the retina [2]. Attenuated activation of pro-survival pathways downstream of IR signaling is an important mediator of diabetes-induced retinal complications [3]. IR-mediated signaling plays a key role in promoting cell growth and survival, in part through activation of the PI3K-Akt pathway and its downstream stimulation of mechanistic target of rapamycin complex 1 (mTORC1).

The stress response proteins regulated in development and DNA damage 1 (REDD1) and its paralog REDD2 act as dominant negative regulators of mTORC1 [4]. We previously demonstrated that REDD1 protein abundance is increased in the retina of mice fed a high-fat diet, in coordination with attenuated Akt phosphorylation [2]. Indeed, REDD1 has been implicated in visual function deficits in both diabetic laboratory rodents and in patients with type 2 diabetes [5]. Within the retina, REDD1 mRNA expression is dominant in Müller glia [6]. Müller glia are the principal macroglia of the retina, which provide critical homeostatic, metabolic, and structural support to the retinal vasculature and neuronal layers [7]. Prior studies demonstrated the role of REDD1-dependent changes in Akt/mTORC1 signaling in Müller cell gliosis and their secretion of growth factors and cytokines that drive retinal vascular permeability, inflammation, and neurodegeneration [6, 8–10]. While the role of REDD1 in diabetes complications in the retina has been well explored in recent years, the potential contribution of REDD2 has not been previously examined.

REDD2 was originally identified as a hypoxia-inducible gene [11]. Since then, REDD2 was found to be transcriptionally upregulated in response to other cell stressors, including reactive oxygen species, osmotic stress, oxidized low-density lipoprotein, and radiation [12–15]. However, the signaling events that act to control REDD2 transcription remain poorly understood. Recently, the transcription factors X-box binding protein 1 (XBP1), nuclear factor erythroid 2-related factor 2 (Nrf2), and p53 were identified as regulators of REDD2 transcription [16–18]. XBP1 is a crucial mediator of the unfolded protein response (UPR) that allows cells to adapt to endoplasmic reticulum (ER) stress. An increase in ER stress markers has been previously localized to Müller glia in the retina of diabetic mice [19]. Additionally, Nrf2 and p53 were found to act cooperatively to promote REDD2 transcription in pancreatic β-cells under diabetogenic conditions [17]. The present study aimed to investigate the impact of diabetic conditions on REDD2 in retinal Müller glia. Overall, the results support a model wherein GSK3β promotes REDD2 mRNA transcription in Müller glia under hyperlipidemic conditions via activation of p53/Nrf2.

2. Materials and Methods

2.1. Animals

B6J.129(Cg)-Rpl22tm1.1Psam/SjJ RiboTag mice (The Jackson Laboratory) were crossed with C57BL/6-Tg(Pdgfra-cre)1Clc/J (The Jackson Laboratory) mice to achieve Müller glia-specific expression of an HA-tagged ribosomal protein Rpl22 variant [20]. At 6 weeks of age, male littermates were fed either a control diet (ENVIGO TD.08485; Envigo, Indianapolis, IN, USA) containing 13% kcal from fat, 63.3% from carbohydrates, and 19.1% from protein or a high-fat diet (ENVIGO TD.88137) containing 42% kcal from fat, 42% kcal from carbohydrates, and 15.2% from protein for 6 weeks. Diabetic phenotype was assessed with blood glucose levels >250mg/dL in fasted mice. All procedures were approved by the Penn State College of Medicine Institutional Animal Care and Use Committee.

2.2. Isolation of ribosome-associated mRNA

Ribosomes were isolated from retinal Müller glia as previously described [21]. Anti-HA beads (EZview; Sigma, St. Louis, MO, USA) were washed in immunoprecipitation buffer (50 mM Tris, pH 7.5) 100 mM KCl, 12 mM MgCl2, 1% Nonidet P-40) and blocked in 0.5% BSA. Retinas were homogenized in polysome buffer (50 mM Tris, pH 7.5, 100 mM KCl, 12 mM MgCl2, 1% Nonidet P-40, 1 mM DTT, 400 units/ml Promega RNasin, 0.5 mg/ml heparin, 100 μg/ml cycloheximide, 10 μl/ml protease inhibitor mixture) and centrifuged at 10,000 × g at 4°C for 10 min. Supernatants were collected and combined with anti-HA beads at 4°C for 16 h. The mixture was centrifuged at 8200 × g for 30 s, the bead pellet was collected, and washed with high-salt buffer (50 mm Tris, pH 7.5, 300 mM KCl, 12 mM MgCl2, 1% Nonidet P-40, 1 mM DTT, 100 μg/ml cycloheximide). RLT buffer (Qiagen, Hilden, Germany) was added to beads for processing, and mRNA was isolated using the RNeasy Micro kit (Qiagen).

2.3. Cell culture

MIO-M1 human Müller cells were obtained from the UCL Institute of Ophthalmology (London, UK). REDD1 deletion was achieved in MIO-M1 cells by CRISPR/Cas9, as previously described [2]. The p53−/− mouse embryonic fibroblast (MEF) cell line [22] was a gift from Dr. David J. Kwiatkowski (Harvard Medical School). All cells were cultured at 37 °C, in 5% CO2 on Genesee culture plates. MEF and HEK 293 cells (ATCC) were cultured in Dulbecco’s modified Eagle’s medium (DMEM, Thermo Fisher Scientific) containing 4.5 g/L glucose and supplemented with 10% fetal bovine serum and 1% penicillin-streptomycin. MIO-M1 cells were cultured in DMEM containing 1 g/L glucose and supplemented with 10% fetal bovine serum and 1% penicillin-streptomycin. In some studies, culture medium was supplemented with 60 μM ceramide 6 (Cer6, Sigma-Aldrich Corp.), 500 μM palmitate (Cayman Chemicals), 5 μM Tunicamycin (Sigma-Aldrich Corp.), 20 μM sulforaphane (Sigma-Aldric Corp.), 5 μM CHIR99021 (SelleckChem), 1 mM H2O2 (Sigma-Aldrich Corp.), or 10 mM N-acetyl cysteine (Sigma-Aldrich Corp.). To model hyperglycemic conditions, DMEM was supplemented with additional glucose to a final concentration of 30mM.

2.4. Western blotting

Proteins were collected in Laemmli buffer and heated at 100°C for 5 min. Proteins were separated in Criterion Precast 4 to 20% gels (Bio-Rad Laboratories), transferred to a polyvinylidene fluoride membrane (PVDF), blocked with 5% milk in Tris-buffered saline Tween-20 (TBS-T). The membrane was exposed to the appropriate antibodies (Supplemental Table S1). Antibody binding was visualized with enhanced chemiluminescence Clarity Reagent (Bio-Rad Laboratories) using a ProteinSimple Fluorchem E. Western blot bands were quantified by densitometry using ImageJ (National Institutes of Health).

2.5. PCR analysis

Trizol (Invitrogen) was used to extract total RNA from cells or tissue. Next, 1,000 ng of extracted RNA was transcribed into cDNA using the high-capacity cDNA Reverse Transcription Kit (Applied Biosystems). QuantiTect SYBR Green master mix (Qiagen) was used to perform Quantitative real-time PCR (qRT-PCR) (QuantStudio 5 Real-Time PCR System, RRID: SCR_021123). Primer sequences are listed in Supplemental Table S2. Mean cycle threshold (CT) values were determined as previously described [23].

2.6. Transfection and site-directed mutagenesis

Cells were transfected using Lipofectamine 2000 (Life Technologies, Carlsbad, CA, USA) with the following plasmids: pCMV5 empty vector, pCMV-Myc-FLAG-REDD2 (Origene), pCMV-HA-REDD1 [24], pCMV-HA-GSK3β-S9A, or pRK7-HA-S6K1 (Addgene Plasmid #8984). The pCMV-Myc-FLAG-REDD2 plasmid variants were generated by site-directed mutagenesis (Agilent QuikChange Lightning Kit) using the appropriate primers (Supplemental Table S3). Mutant sequences were confirmed by sequencing.

2.7. Short hairpin RNA (shRNA) mRNA knockdown

For shRNA knockdown, lentiviral pLKO.1-puro plasmids were obtained from the Penn State College of Medicine shRNA Library Core (RRID: SCR_021123) (Supplemental Table S4). Lentivirus contained either TRC shRNA control, ATF4 shRNA, TP53 shRNA, Nrf2 shRNA, or GSK3β shRNA. Virus was prepared using the HEK293 FT system previously described [8, 25]. MIO-M1 cells were infected with virus for 72 h. Stable clones expressing the ATF4, Nrf2, TP53, or GSK3β shRNA were selected in media containing 2 mg/mL of puromycin. After 2 weeks of selection, knockdown was verified by western blotting and qRT-PCR.

2.8. Statistical analysis

Results are expressed as mean ± SD. Statistical analyses were performed using GraphPad Prism software with the Student t test or two-way ANOVA. A P value <0.05 was defined as statistically significant. Trend test and pairwise comparisons were conducted with the Tukey test for multiple comparisons. Descriptive statistics are provided in Supplemental Table S5.

3. Results

3.1. REDD1 and REDD2 mRNA expression were increased under hyperlipidemic conditions.

The relative expression of REDD1 and REDD2 was examined in rodent tissue (Supplemental Fig. S1A–B) and in publicly available human RNA sequencing datasets (Supplemental Fig. S1C–D). Whereas REDD1 was more widely expressed, REDD2 exhibited a more limited expression pattern, and in most tissues, including the retina, REDD1 expression was higher than that observed for REDD2. Analysis of human RNA sequencing data supported that retinal REDD2 mRNA expression was dominant in Müller glia (Supplemental Fig. 1E–F). To evaluate changes in REDD2 in Müller glia within the intact retina, we used a previously described RiboTag mouse that expresses an HA-tagged variant of the ribosomal protein Rpl22 specifically in Müller glia within the retina [20]. When RiboTag mice are fed a high-fat diet, fasting blood glucose concentrations are increased as compared to chow diet, supporting the development of insulin resistance and diabetes [21]. REDD2 mRNA ribosome association in the Müller glia was increased in mice fed a high-fat diet as compared to control chow (Fig. 1A).

Figure 1. REDD2 mRNA expression was increased in retinal Müller glia under hyperlipidemic conditions.

Figure 1.

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(A) RiboTag mice were fed either a high fat diet (HFD) or control diet (CD) for 6 weeks. Ribosomes were isolated from Müller glia by immunoprecipitating HA-Rpl22 from retinal lysates. Ribosome-associated REDD2 mRNA was analyzed by qRT-PCR. (B) Human MIO-M1 wild-type (WT) cells were exposed to cell culture media containing either vehicle (Veh) or 60 μM ceramide 6 (Cer6) for 17 h. REDD1 mRNA was analyzed by qRT-PCR. (C) CRISPR-Cas9 was used to generate an MIO-M1 cell line deficient for REDD1 (sgREDD1). MIO-M1 WT and sgREDD1 cells were exposed to cell culture media containing either Veh or Cer6 for up to 17 h. REDD1 and p70S6K phosphorylation at T389 were assessed by western blot. Representative blots are shown. Protein molecular mass in kDa is indicated on the right of blots. Relative phosphorylation of p70S6K1 was quantified. (D) REDD2 mRNA expression was analyzed 17 h after Cer6 exposure by qRT-PCR. (E) MIO-M1 WT cells were exposed to either 500 μM BSA-conjugated palmitate (Pal) or BSA alone for 8 h. (E) MIO-M1 WT cells were exposed to media containing either low glucose (LG, 5 mM) or high glucose (HG, 30 mM) for 17 h. Data are presented as means ± SD. *, p < 0.05 versus CD, Veh, BSA, or LG.

To model hyperlipidemic conditions, human MIO-M1 Müller cell cultures were exposed to culture medium supplemented with the cell-permeable ceramide, Cer6. In cells exposed to elevated ceramide levels, REDD1 mRNA and protein were increased (Fig. 1B–C). The increase in REDD1 coincided with a decrease in mTORC1 activity, as assessed by phosphorylation of p70S6K1 at T389 (Fig. 1C). Notably, the suppressive effect of Cer6 on mTORC1 was not fully attenuated by REDD1 deletion. The observation supports that other negative regulators of mTORC1 may also be induced under hyperlipidemic conditions. Indeed, REDD2 mRNA expression was increased in cells exposed to medium supplemented with either Cer6 (Fig. 1D) or the saturated fatty acid palmitate (Fig. 1E). Thus, the expression of both REDD1 and REDD2 in Müller cells was sensitive to hyperlipidemic conditions. Notably, a more modest increase in REDD2 mRNA expression was also observed when Müller cells were exposed to hyperglycemic culture conditions (Fig. 1F).

3.2. Suppression of mTORC1 by REDD2 required regulatory residues conserved with REDD1.

Ceramides negatively regulate insulin action through the activation of PP2A and consequent suppression of Akt [26]. Similarly, REDD1 negatively regulates mTORC1 activity through the recruitment of PP2A and subsequent dephosphorylation of Akt [24]. Prior mutagenesis studies have identified P139, K219, and Y222 of REDD1, as key residues localized to a critical surface patch that mediates the suppressive effect of REDD1 on mTORC1 [27]. Additionally, E63 of REDD1 within the N-terminal domain was required for PP2A co-immunoprecipitation [24]. Sequence alignment of the human REDD1 and REDD2 proteins supported that all four regulatory sites critical in REDD1-mediated mTORC1 suppression were conserved in REDD2 (Fig. 2A). To determine if these residues in REDD2 contribute to mTORC1 inhibition, REDD2 E26A, P100A, and K179A/Y182A variants were generated by site-directed mutagenesis. Each Myc-REDD2 variant was co-transfected into HEK293 cells with a p70S6K1 reporter (Fig. 2B). Wild-type REDD1 or REDD2 attenuated phosphorylation of p70S6K1 at T389 (Fig. 2C). By contrast, the suppressive effect of the REDD2 K179A/Y182A and P100A variants on mTORC1 was reduced as compared to wild-type REDD2. However, the REDD2 E26A variant suppressed mTORC1 to a degree similar to that of wild-type REDD2. This observation supports that key functional differences in REDD1 and REDD2 are likely due to the differences in their N-terminal domain sequences.

Figure 2. Suppression of mTORC1 by REDD2 requires key regulatory residues that are conserved with REDD1.

Figure 2.

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(A) Alignment of human REDD1 and REDD2 amino acid sequences illustrating conservation of functional domain residues (black boxes). (B-C) HEK 293 cells were transiently co-transfected with either empty vector (EV), HA-tagged REDD1, or Myc-tagged REDD2 and HA-p70S6K. REDD2 variants included wild-type (WT), E26A, P100A, or K179A/Y182A. REDD1 and REDD2 protein abundance were evaluated by western blotting. As a marker of mTORC1 signaling, phosphorylation of p70S6K at T389 was evaluated by western blotting. Data are presented as means ± SD. *, p < 0.05 versus EV; #, p < 0.05 versus WT; nd, not detected.

3.3. ER stress did not promote REDD2 mRNA expression in Müller cells.

Prior studies support that hyperlipidemic conditions promote REDD1 mRNA expression via activation of ER stress and ATF4-dependent REDD1 transcription [28, 29]. We initially suspected that hyperlipidemic conditions may also act through ER stress to promote REDD2 transcription in Müller cells. In support of that possibility, the ER stress markers XBP1(s) and ATF3 were increased in Müller cells exposed to hyperlipidemic conditions (Fig. 3A–B). When ER stress was chemically induced by tunicamycin exposure, there was a similar increase in XBP1(s) and ATF3 (Fig. 3C–D). However, tunicamycin did not increase REDD2 mRNA expression (Fig. 3E), despite the expected increase in REDD1 (Fig. 3F). Consistent with the absence of an increase in REDD2 in Müller cells exposed to tunicamycin, REDD2 mRNA expression was moderately decreased by tunicamycin in HEK293 cells, whereas REDD1 and XBP1(s) were both increased (Fig. 3G–I). Further, knockdown of ATF4 promoted REDD2 mRNA expression in Müller cells, but suppressed REDD1 mRNA expression (Fig. 3J–L). Thus, unlike with REDD1, the increase in REDD2 mRNA expression under hyperlipidemic conditions was not likely a consequence of ER stress or ATF4.

Figure 3. ER stress did not promote REDD2 mRNA expression.

Figure 3.

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(A-B) MIO-M1 cells were exposed to culture media containing 60 μM ceramide 6 (Cer6) or vehicle (Veh) for 17 h. As markers of ER stress, XBP1 spliced and ATF3 mRNA expression were assessed by qRT-PCR. (C-F) MIO-M1 cells were exposed to culture media containing 2 μM tunicamycin for 4 h. XBP1 spliced, ATF3, REDD2, and REDD1 mRNA expression were assessed by qRT-PCR. (G-I) HEK 293 cells were exposed to culture media containing 2 μM tunicamycin for 4 h. REDD2, REDD1, and XBP1 spliced expression were assessed by qRT-PCR. (J-L) ATF4 mRNA was knocked down in MIO-M1 cells by stable expression of an shRNA (shATF4). REDD2, REDD1, and ATF4 mRNA expression were examined in wild-type (WT) versus shATF4 MIO-M1 cells by qRT-PCR. Data are presented as means ± SD, *, p < 0.05 versus Veh; #, p < 0.05 versus WT.

3.4. Hyperlipidemic conditions required p53 to promote REDD2 mRNA expression.

To investigate the role of p53 in promoting REDD2 mRNA expression under hyperlipidemic conditions, p53 was suppressed in Müller cells by stable expression of an shRNA (Fig. 4A). In cells exposed to hyperlipidemic conditions, p53 knockdown partially attenuated the increase in REDD2 mRNA expression, but not REDD1 (Fig. 4B–C). Similarly, p53-deficient MEF did not exhibit an increase in REDD2 mRNA expression upon exposure to Cer6, whereas the increase in REDD1 was similar to wild-type MEF (Fig. 4D–F). Altogether, this data support that p53 is necessary for hyperlipidemic conditions to promote expression of REDD2, but not REDD1.

Figure 4. Increased REDD2 mRNA expression in response to hyperlipidemic conditions was p53-dependent.

Figure 4.

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(A-C) Expression of p53 was knocked down in MIO-M1 cells by stable expression of an shRNA (shTP53) versus an shRNA control (shCTL). p53 protein was assessed by western blotting. Representative western blots are shown. Protein molecular mass in kDa is indicated on the right of blots. (B-C) shCTL and shTP53 MIO-M1 cells were exposed to cell culture media containing either vehicle (Veh) or 60 μM ceramide 6 (Cer6) for 17 h. REDD2 and REDD1 mRNA expression were assessed by qRT-PCR. (D) p53 protein was assessed by western blotting in wild-type (WT) and p53 knockout (KO) MEF. (E-F) WT and p53 KO MEF were exposed to culture media containing either Veh or 60 μM Cer6 for 17 h. REDD2 and REDD1 mRNA expression were assessed by qRT-PCR. Data are presented as means ± SD, *p < 0.05 versus Veh; # p < 0.05 versus shCTL or WT.

3.5. Nrf2 was necessary for enhanced REDD2 mRNA expression upon exposure to hyperlipidemic conditions.

To examine whether Nrf2 acts cooperatively with p53 to regulate REDD2 mRNA expression in Müller glia, a Nrf2 knockdown MIO-M1 cell line was generated by stable shRNA expression (Fig. 5A). To validate the model, control and Nrf2-deficient Müller cells were exposed to the Nrf2 inducer sulforaphane. Sulforaphane upregulated levels of the Nrf2 target heme oxygenase 1 (HO-1) in control cells, whereas Nrf2 knockdown prevented the effect (Fig. 5B–C). Surprisingly, partial Nrf2 mRNA knockdown was sufficient to fully prevent sulforaphane-induced HO-1, which potentially reflects the existence of 14 Nrf2 mRNA transcript variants (NM_006164.5) with distinct roles in mediating Nrf2 activity. Interestingly, sulforaphane did not increase REDD2 mRNA expression (Fig. 5D). To further explore whether REDD2 was regulated by oxidative stress, Müller cells were exposed to the oxidant hydrogen peroxide. Whereas HO-1 expression was increased by hydrogen peroxide (Fig. 5E), REDD2 mRNA expression was not (Fig. 5F). Further, the antioxidant N-acetyl cysteine (NAC) prevented an increase in HO-1 expression in Müller cells exposed to hyperlipidemic conditions (Fig. 5G), but neither the increase in REDD2 nor REDD1 mRNA expression under hyperlipidemic conditions were suppressed by NAC (Fig. 5H–I). The observation supports that REDD2 mRNA expression in Müller cells may be insensitive to changes in redox conditions. However, in response to hyperlipidemic conditions, Nrf2 knockdown attenuated REDD2 mRNA expression, but not REDD1 (Fig. 5J–K). Altogether, this data support that Nrf2 influences REDD2 mRNA expression independently of the oxidative stress response, and that the transcription factor contributes to upregulation of REDD2 mRNA expression under hyperlipidemic conditions.

Figure 5. Nrf2 was necessary for a redox-independent increase in REDD2 mRNA expression upon exposure to hyperlipidemic conditions.

Figure 5.

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(A) Nrf2 was knocked down in MIO-M1 cells by stable expression of an shRNA targeting the Nrf2 mRNA (shNrf2). Control cells expressed a scramble shRNA (shCTL). Nrf2 mRNA expression was assessed by qRT-PCR. (B) Cells were exposed to culture media containing 20 μM of the Nrf2 activator sulforaphane (Sulf) or vehicle (Veh) for 17 h. Protein abundance of Nrf2 and the Nrf2 target gene HO-1 [6] was assessed by western blotting. Representative blots are shown. Protein molecular mass in kDa is indicated on the right of blots. Non-specific (ns) bands are indicated. (C) Quantification of HO-1 protein in panel B. (D) MIO-M1 cells were exposed to Sulf or Veh for 17 h. REDD2 mRNA expression was assessed by qRT-PCR. (E-F) MIO-M1 cells were exposed culture media supplemented with 1 mM of the oxidant hydrogen peroxide (HP) or Veh for 3 h. HO-1 and REDD2 mRNA expression were determined by qRT-PCR. (G-K) MIO-M1 cells were exposed to culture media containing Veh, 60 μM ceramide 6 (Cer6), or Cer6 + 10 mM N-acetylcysteine (NAC) for 17 h. HO-1, REDD2, and REDD1 mRNA expression were assessed by qRT-PCR. (H-I) MIO-M1 shCTL and shNRF2 cells were exposed to culture media containing Veh or Cer6. REDD2 and REDD1 mRNA expression were assessed by qRT-PCR. Data are presented as means ± SD, *, p < 0.05 versus Veh; #, p < 0.05 versus shCTL; $, p < 0.05 versus Cer6 alone.

3.6. Inhibition of GSK3β attenuates Cer6 induced REDD2 transcription.

The kinase GSK3β acts to regulate the activity of both p53 and Nrf2 [30, 31]. In Müller cells exposed to hyperlipidemic conditions, the inhibitory phosphorylation of GSK3β at S9 was reduced (Fig. 6A). In Müller cells exposed to hyperlipidemic conditions, the GSK3β inhibitor CHIR99021 suppressed Cer6-induced expression of REDD2, but not REDD1 (Fig. 6B–C). To further explore regulation of REDD2, GSK3β-deficient Müller cells were generated by shRNA expression (Fig. 6D). GSK3β knockdown decreased basal REDD2 as compared to control cells (Fig. 6E). Moreover, GSK3β knockdown prevented the increase in REDD2 in cells exposed to hyperlipidemic conditions. GSK3β knockdown did not suppress the increase in REDD1 mRNA expression upon exposure to hyperlipidemic conditions (Fig. 6F). Finally, expression of a constitutively active GSK3β S9A variant promoted REDD2 mRNA expression in Müller cells, and the effect was prevented by knockdown of either Nrf2 or p53 (Fig. 6G). The observation supports that the increase in REDD2 mRNA expression mediated by GSK3β requires both Nrf2 and p53.

Figure 6. GSK3β mediated increased REDD2 mRNA expression in response to hyperlipidemic conditions.

Figure 6.

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(A) MIO-M1 cells were exposed to culture media containing 60 μM ceramide 6 (Cer6) for 0–8 h. GSK3β phosphorylation at S9 was assessed by western blotting. Representative blots are shown and protein molecular mass in kDa is indicated on the right of each blot. (B-C) MIO-M1 cells that were exposed to culture media containing vehicle (Veh), Cer6, or Cer6 + 5 μM CHIR99021 (CHIR). REDD2 and REDD1 mRNA expression were assessed by qRT-PCR. (D) GSK3β was knocked down in MIO-M1 cells by stable expression of an shRNA (shGSK3β). Control cells expressed a scramble shRNA (shCTL). Knockdown was confirmed by western blotting. (E-F) Control and GSK3β-deficient cells were exposed to culture media containing either Veh or Cer6 for 17 h. (G) Nrf2 or p53 were knocked down in MIO-M1 cells by stable expression of shRNAs (shNrf2 or shTP53, respectively). Cells were transfected to express either an empty vector (EV) control or constitutively active GSK3β (caGSK3β) for 48 h. Data are presented as means ± SD, *, p < 0.05 versus time 0 or Veh; #, p < 0.05 versus shCTL; $, p < 0.05 versus Cer6 alone.

4. Discussion

The studies herein examined changes in REDD2 in response to diabetic conditions. Single-cell sequencing data supported that both REDD1 and REDD2 mRNA expression in the retina was dominant in Müller glia. Indeed, REDD2 mRNA ribosome-association was increased in Müller glia when mice were fed a pro-diabetogenic diet high in saturated fats. We previously reported that when laboratory mice consume a high-fat diet, retinal sphingolipids content, including ceramide levels, are increased in coordination with an increase in REDD1 [2]. When we used a cell-permeable ceramide to model sphingolipid-mediated signaling in human Müller cell cultures, we found that both REDD1 and REDD2 mRNA expression were increased. The data herein suggest that both REDD1 and REDD2 are likely important for Müller cell signaling changes in the context of diabetes and obesity. The studies herein support a working model wherein hyperlipidemic conditions act to promote REDD2 mRNA expression in Müller glia via GSK3β activation and the transcription factors p53 and Nrf2 (Fig. 7).

Figure 7. Working model for enhanced REDD2 and REDD1 transcription in Müller glia exposed to hyperlipidemic conditions.

Figure 7.

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Increased REDD1 mRNA expression under hyperlipidemic conditions is regulated by activation of the eIF2α kinase PERK and the transcription factor ATF4. By contrast, REDD2 mRNA expression in Müller cells is not altered by ER stress. Rather, hyperlipidemic conditions activate GSK3β in Müller cells, which promotes p53/Nrf2-dependent REDD2 mRNA expression. Unlike the redox-sensitive Nrf2-target gene HO-1, increased REDD2 mRNA expression in response to hyperlipidemic conditions is independent of oxidative stress. Graphic created with Biorender.com. GC, ganglion cells; BP, bipolar cells; MG, Müller glia; PR, photoreceptors; RPE, retinal pigmented epithelium.

Unlike prior reports for REDD1 [28], the data herein do not support that the increase in REDD2 mRNA expression in Müller cells in response to hyperlipidemic conditions is a consequence of ER stress. In a mouse model of colorectal cancer, the ER stress-sensitive transcription factor XBP1 promotes REDD2 mRNA expression [16]. In support of that observation, the increase in REDD1 and REDD2 mRNA expression in Müller cells exposed to hyperlipidemic conditions was observed in coordination with XBP1 activation. However, when ER stress was induced by tunicamycin, both XBP1 activation and REDD1 mRNA expression were increased, but REDD2 mRNA expression was not. The differential response in REDD1 versus REDD2 to cell stressors is supported by several prior reports [13, 17, 32]. We also suspected that the change in REDD2 in response to a high-fat diet could be due to variation in levels of stress hormones, cytokines, or growth factors. Circulating glucocorticoid levels are increased by a high-fat diet [33]; however, only REDD1 is responsive to glucocorticoids, and not REDD2 [34]. Moreover, prior reports support that REDD2 mRNA expression is decreased in response to TGF-β and negatively correlates with levels of TNFα [35, 36]. Consistent with those findings, REDD1 mRNA expression was increased in Müller cells exposed to either TGF-β or TNFα, but REDD2 mRNA expression was not (Supplemental Fig. S2).

Hyperlipidemic conditions promoted REDD2 mRNA expression in Müller cells through the cooperative regulation of p53 and Nrf2. Indeed, the REDD2 promoter includes binding domains for both p53 (−90/−81) and Nrf2 (−349/−340) [17]. Surprisingly, the effect of Nrf2 on REDD2 was redox-independent, as antioxidant supplementation prevented increased expression of the Nrf2-target gene HO-1 in response to hyperlipidemic conditions, but was not sufficient to block the increase in REDD2 mRNA expression. Furthermore, HO-1 was induced by either sulforaphane or hydrogen peroxide, whereas REDD2 mRNA expression was not. The observation conflicts with the previous finding in monocytes, where REDD2 was sensitive to oxidative stress [13]. Thus, there may be cell- or tissue-type specific pathways that act to regulate REDD2. The discordant Nrf2-dependent changes in HO-1 and REDD2 in Müller cells were reminiscent of the prior observation that thioredoxin is a p53-activated Nrf2 target gene, whereas HO-1 is a p53-repressed Nrf2 target gene [37]. Indeed, the direct binding of p53 and Nrf2 selectively promotes the transcription of specific gene targets, while leading to the translational repression of others [38]. The studies here extend on the prior discovery by demonstrating that the p53/Nrf2-mediated increase in REDD2 mRNA expression is controlled by GSK3β. GSK3β increases p53 activity through direct phosphorylation of p53 at S33 [39]. By contrast, GSK3β directly phosphorylates Nrf2 to inhibit the transcription of redox-sensitive phase II genes, including HO-1 [40]. Indeed, we previously demonstrated that GSK3 inhibition promotes Nrf2 activity in the retina of diabetic mice [25]. The data support the possibility that REDD2 is among a group of target genes that are selectively expressed in response to GSK3β-dependent activation of p53/Nrf2 in diabetes.

REDD1 and REDD2 act similarly as dominant negative regulators of mTORC1 [4]. Hyperlipidemic conditions promoted the expression of both REDD1 and REDD2, suggesting that REDD2 acts as an additional check on Müller cell mTORC1 signaling in the context of lipotoxicity. Suppression of mTORC1 by REDD1 or REDD2 is mediated upstream of the tuberous sclerosis complex (TSC)1/2, as a functional TSC1/2 complex is required for the effect [4]. TSC1/2 acts as a GTPase-activating protein (GAP) for the small GTPase Rheb, and Rheb-GTP serves as an essential activator of mTORC1 [41]. We previously demonstrated that REDD1 promotes the recruitment of PP2A to selectively dephosphorylate Akt [24]. Akt directly phosphorylates TSC2 to inhibit its GAP activity [42]. Thus, REDD1 inhibits mTORC1 by promoting the dephosphorylation of Akt, reduced Akt-dependent inhibition of TSC2 GAP activity, and a reduction in Rheb-GTP.

Structural analysis of the functional domains in REDD1 identified a critical surface patch that mediates mTORC1 inhibition [27]. The obligate surface patch on REDD1 maps to two non-contiguous amino acid sequences that are well-conserved with REDD2. Consistent with the observation that P139 and K219/Y222 of REDD1 are required for its suppressive effect on mTORC1 [27], we found that the corresponding substitutions in REDD2 of P100A and K179A/Y182A impaired mTORC1 inhibition. Prior studies support that P139 and K219/Y222 of REDD1 are required for REDD1 to interact with Akt [24]. This observation suggests that REDD2 acts to repress mTORC1 through a similar mechanism to REDD1. On the other hand, a major difference between the REDD1 and REDD2 primary sequences is the absence of 42 N-terminal residues of REDD1 from REDD2. In addition to the conserved surface patch, the N-terminal E63 site of REDD1 has also been implicated in mTORC1 inhibition [24]. Unlike wild-type REDD1, the REDD1 E63A variant fails to bind PP2A [24]. Interestingly, E26 of REDD2 aligned with E63 of REDD1, but unlike REDD1 E63A [24], the REDD2 E26A variant retained its ability to suppress mTORC1. One possibility is that REDD2 does not act via recruitment of PP2A, but rather an alternative phosphatase. However, it is important to point out that the conservation of the remaining N-terminal residues in REDD2 with REDD1 is much lower than in other parts of the protein, thus the REDD2 E26A and REDD1 E63A substitutions may not be functionally equivalent.

The bioactive sphingolipids ceramide, sphingosine-1-phosphate, sphingosine, and ceramide-1-phosphate are important mediators of retinal disease (reviewed in [43]). Indeed, ceramide levels are increased in the vitreous of people living with type 2 diabetes [44]. Pre-clinical studies support that such an increase in intravitreal ceramide levels is sufficient to drive Müller cell gliosis and visual function deficits in rodents [45]. The studies herein demonstrate that elevated ceramide levels increase levels of both REDD1 and REDD2 in retinal Müller glia. The role of Müller glial REDD1 mRNA expression in retinal complications caused by diabetes is well-established [5, 9], and REDD1-targeted therapies have shown promise in improving best corrected visual acuity in patients with diabetic macular edema [46]. However, the potential role of REDD2 in diabetes-induced retinal complications has been essentially ignored. Notably, REDD2 is increased in a murine model of optic nerve crush, where REDD2 knockdown improves light responsiveness by restoring mTORC1 activity [47]. Overall, the results support that GSK3β-dependent activation of Nrf2/p53 promotes REDD2 mRNA expression in retinal Müller glia exposed to hyperlipidemic conditions. Thus, therapeutic interventions targeting this new GSK3β-p53/Nrf2-REDD2 signaling axis may be beneficial in retinal disease.

Supplementary Material

1

Highlights-.

  • High-fat diet increased REDD2 mRNA ribosome-association in retinal Müller glia.

  • Hyperlipidemic conditions promoted REDD2 and REDD1 mRNA expression.

  • Unlike REDD1, REDD2 mRNA expression was not sensitive to ER stress.

  • REDD2 mRNA expression was increased by p53/Nrf2-dependent GSK3β signaling.

Acknowledgement

This research was supported by the National Institutes of Health grants R01 EY029702 & EY032879 (to M.D.D.) and a Children’s Miracle Network Trainee Research Grant (to S.S.). Graphic for working model was generated with Biorender.com.

Footnotes

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Declaration of Competing Interest

The authors declare no conflicts of interest.

Data availability

All primary data supporting the findings of this study are presented within the manuscript or in the supplemental information. Unedited western blot images are available at doi.org/10.6084/m9.figshare.31029397.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS2156207-supplement-1.pdf (518KB, pdf)

Data Availability Statement

All primary data supporting the findings of this study are presented within the manuscript or in the supplemental information. Unedited western blot images are available at doi.org/10.6084/m9.figshare.31029397.

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