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. 2025 Jul 20;73(11):2273–2288. doi: 10.1002/glia.70067

Endoplasmic Reticulum Stress Amplifies Cytokine Responses in Astrocytes via a PERK/eIF2α/JAK1 Signaling Axis

Anirudhya Lahiri 1, Savannah G Sims 1, Jessica A Herstine 2,3, Alicia Meyer 1, Micah J Marshall 4, Ishrat Jahan 4, Subhodip Adhicary 4, Allison M Bradbury 2,3, Gordon P Meares 1,4,5,6,✉
PMCID: PMC12436993  PMID: 40685560

ABSTRACT

Aberrant activation of multiple cellular processes and signaling pathways is a hallmark of many neurological disorders. Understanding how these processes interact is crucial for elucidating the neuropathogenesis of these diseases. Among these, endoplasmic reticulum (ER) stress, activation of the unfolded protein response (UPR), and neuroinflammation are frequently implicated. Previously, we demonstrated that ER stress synergizes with tumor necrosis factor (TNF)‐α to amplify interleukin (IL)‐6 and C‐C motif chemokine ligand (CCL)20 production in astrocytes through a Janus kinase 1 (JAK1)‐dependent mechanism. Here, we expand on this finding by defining the scope and underlying mechanisms of this phenomenon. We show that ER stress and TNF‐α cooperatively enhance inflammatory gene expression in astrocytes via a signaling axis that requires both protein kinase R (PKR)‐like ER kinase (PERK) and JAK1. PERK‐mediated phosphorylation of eukaryotic translation initiation factor (eIF)2α suppresses protein translation, delaying the expression of negative regulators such as NF‐κB inhibitor (IκB)α and suppressor of cytokine signaling (SOCS)3 following TNF‐α or oncostatin M (OSM) stimulation, respectively. Pharmacological reversal of p‐eIF2α‐dependent translational suppression using the small molecule integrated stress response inhibitor (ISRIB) restored IκBα and SOCS3 expression and attenuated the ER stress‐induced enhancement of TNF‐α‐ or OSM‐driven inflammatory responses. Notably, astrocytes harboring a vanishing white matter‐associated EIF2B5 mutation revealed that translational attenuation alone is insufficient to amplify cytokine‐induced gene expression. Together, these findings identify a PERK/eIF2α/JAK1 signaling axis that sensitizes astrocytes to inflammatory cytokines, providing new mechanistic insights into the interactions between ER stress and neuroinflammation.

Keywords: glia, IL‐6, integrated stress response, JAK/STAT, neuroinflammation, unfolded protein response

Main Points

  • ER stress amplifies TNF‐α, OSM, and IL‐1β responses in astrocytes.

  • PERK and JAK1 signaling are required for the synergistic interaction between ER stress and inflammatory cytokines.

  • Translational suppression attenuates the synthesis of the negative feedback regulators IκBα and SOCS3.

  • Reversing translational suppression using ISRIB restores expression of IκBα and SOCS and mitigates inflammation.

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1. Introduction

Neuroinflammation and dysregulation of proteostasis are hallmarks of numerous neurological disorders and may contribute to disease progression and pathology (Wilson III et al. 2023). Cells exposed to misfolded proteins, oxidative stress, and other neuropathological insults activate adaptive mechanisms to restore homeostasis. Central to this response is the attenuation of global protein synthesis via the integrated stress response (ISR). The ISR is initiated by diverse stress signals, which activate stress‐selective kinases that phosphorylate eukaryotic initiation factor 2α (eIF2α). This phosphorylation suppresses translational initiation while promoting transcriptional reprogramming and selective mRNA translation to mitigate cellular stress (Costa‐Mattioli and Walter 2020). Endoplasmic reticulum (ER) stress, caused by an accumulation of misfolded proteins, is a potent trigger of the ISR. The ER stress sensor protein kinase R‐like ER kinase (PERK), activated by ER‐localized misfolded proteins, phosphorylates eIF2α, reducing protein synthesis by impairing the guanine nucleotide exchange activity of eIF2B, a critical regulator of translational initiation (Wek et al. 2023). PERK is part of the unfolded protein response (UPR), a broader ER stress response that also involves inositol‐requiring enzyme 1α (IRE1α) and activating transcription factor 6 (ATF6). The significance of this pathway is underscored by the mutations in EIF2B that cause vanishing white matter disease (VWM), a severe autosomal recessive leukoencephalopathy in which astrocytes are a key driver of pathology (van der Knaap et al. 2006; Dooves et al. 2016). In VWM, astrocytes fail to mature properly, become reactive, and negatively impact oligodendrocytes by exacerbating the loss of myelin and disrupting oligodendrocyte precursor cell (OPC) maturation (Dooves et al. 2016; Bugiani et al. 2018; de Waard and Bugiani 2020). Together, the UPR sensor proteins and downstream effectors not only signal for chaperone expression and transcriptional responses to counteract ER stress; they are also critical in maintaining homeostasis in the CNS (Vásquez et al. 2022; Sims et al. 2022). However, persistent or excessive activation of the UPR leads to cellular dysfunction and apoptosis (Hetz et al. 2020).

Concomitant with ER stress in many neurological diseases is neuroinflammation involving resident glial cells; infiltrating peripheral immune cells; and production of cytokines, chemokines, and reactive oxygen/nitrogen species. Astrocytes have emerged as key players in this process, capable of producing cytokines and chemokines including interleukin (IL)‐6, C‐C motif chemokine ligand (CCL)20, and C‐X‐C motif chemokine ligand (CXCL)10 (Giovannoni and Quintana 2020). We have previously reported that ER stress activates a PERK and Janus kinase (JAK) 1 pathway to drive inflammatory gene expression in astrocytes (Guthrie et al. 2016; Meares et al. 2014). JAK1, part of the JAK/STAT pathway, is a tyrosine kinase that mediates cytokine signaling downstream of receptors associated with glycoprotein 130 or the common γ‐chain, and interferon (IFN) receptors (Villarino et al. 2015; Philips et al. 2022; Stark et al. 2018). JAK1 signaling is indispensable for immunological function and cannot be compensated for by other JAK family members (Rodig et al. 1998). In addition to JAK signaling, cytokine responses and pathogen recognition involve the nuclear factor κB (NF‐κB) pathway. Tumor necrosis factor‐α (TNF‐α) activates NF‐κB via the IκB kinase (IKK) complex, leading to the degradation of NF‐κB inhibitor (IκBα) and nuclear translocation of NF‐κB subunits, typically a heterodimer of p50 and p65 (Taniguchi and Karin 2018). ER stress can indirectly activate NF‐κB by suppressing IκBα synthesis through eIF2α phosphorylation (Deng et al. 2004). Together, these pathways highlight the complex and interconnected molecular networks through which ER stress contributes to neuroinflammation in astrocytes and other glial cells, driving the production of pro‐inflammatory mediators that may exacerbate neuronal injury.

There is abundant evidence that highlights bidirectional interactions between ER stress and inflammation (Sprenkle et al. 2017; Grootjans et al. 2016; Di Conza et al. 2023; Zhang and Kaufman 2008). For example, inflammatory cytokines such as TNF‐α, IL‐1β, and IFN‐γ induce ER stress (Lin et al. 2005; Xue et al. 2005; Cardozo et al. 2005), while ER stress alters inflammatory responses (Smith 2018). Importantly, these responses occur in a cell type‐dependent manner. In astrocytes, ER stress stimulates IL‐6 production via PERK signaling, whereas macrophages rely on IRE1α for a similar response (Sanchez et al. 2019; Keestra‐Gounder et al. 2016). In oligodendrocytes, IFN‐γ stimulates PERK activation to phosphorylate eIF2α, which suppresses IκBα translation leading to activation of NF‐κB. Importantly, the activation of NF‐κB mediates the protective effect of PERK in oligodendrocytes in the MS mouse model of experimental autoimmune encephalomyelitis (Lin et al. 2012; Lei et al. 2020). Furthermore, ER stress can synergistically augment gene expression induced by inflammatory stimuli, such as lipopolysaccharide (LPS), TNF‐α, IL‐1β, and IFN‐γ (Meares et al. 2014; Liu et al. 2012; Sims and Meares 2019; Miani et al. 2012). ER stress can also have immunosuppressive effects, particularly in the tumor microenvironment (Di Conza et al. 2023). Ultimately, the interactions between ER stress and inflammation are bidirectional, context‐dependent, and profoundly impact disparate conditions, including cancer, infections, autoimmunity, and neurodegeneration.

Along with other cytokines, TNF‐α is a pro‐inflammatory cytokine that has an important role in the CNS, particularly in glial cell activation. In astrocytes, TNF‐α is involved in initiating and amplifying neuroinflammation, which may contribute to the pathology of various conditions, including MS, Alzheimer's disease, and neural injury (Gonzalez Caldito 2023; Probert 2015). TNF‐α stimulates astrocytes to produce other pro‐inflammatory cytokines, chemokines, and reactive oxygen species. This inflammatory cascade can exacerbate neuronal damage, disrupt the blood–brain barrier, and impair synaptic function (Lee et al. 2023; Kim et al. 2022; Habbas et al. 2015). While TNF‐α has neuroprotective roles under certain conditions, its chronic production is often associated with maladaptive responses and neuroinflammation.

In this study, we investigated the transcriptional and translational programs activated by ER stress and TNF‐α in astrocytes. We identified a panel of genes synergistically induced by these stimuli and demonstrated that JAK1 and PERK signaling are essential for this response. Moreover, we showed that translational suppression of negative feedback regulators contributes to this enhanced gene expression. Using astrocytes harboring a VWM‐associated mutation in EIF2B5, we further revealed that translational suppression is necessary but not sufficient for heightened sensitivity to proinflammatory cytokines.

2. Materials and Methods

2.1. Animals

Wild‐type C57BL/6J, PERK floxed, and CAGG‐CreERTM mice were purchased from the Jackson Laboratory. The EIF2B5 I98M mice were previously obtained from the RIKEN BioResource Research Center and recovered from cryopreservation (Herstine et al. 2024). Mice were housed and bred under the care of the Office of Lab Animal Resources. Mice were on a 12/12 h light/dark cycle with food and water ad libitum. Tail biopsies were taken from 17 to 21 days‐old animals, and genomic DNA was isolated using the Wizard SV genomic DNA purification system (Promega). Genotyping was done by standard polymerase chain reaction (PCR) using platinum II hot start green PCR master mix (Invitrogen). The genotyping primers (Integrated DNA Technologies) were used to detect the presence of the Cre‐recombinase allele (forward primer: GCT AAC CAT GTT CAT GCC TTC; reverse primer: AGG CAA ATT TTG GTG TAC GG) and PERK floxed allele (forward primer: TTG CAC TCT GGC TTT CAC TC; reverse primer: AGG AGG AAG GTG GAA TTT GG). Genotyping the I98M model was conducted from pups (days 0–1 postnatal) as described previously (Herstine et al. 2024). Tail biopsies were collected, lysed in 180 μL NaOH (50 mM) for 45 min at 90°C, and then neutralized with 20 μL Tris–HCl (1 M). DNA was then quantified using the NanoDrop One MicroVolume and used in a custom TaqMan non‐human SNP assay (ThermoFisher, 4332077; custom assay ID: ANGZXZJ) to determine genotype by qPCR. Quantitative PCR was performed on the QuantStudio 3 Real‐Time PCR System, and cycling conditions were as follows: 60°C for 30 s (1 cycle), 95°C for 20 s (1 cycle), 95°C for 1 s, 60°C for 20 s (40 cycles), and finally 60°C for 30 s. All animal studies were conducted with approval from the institutional animal care and use committees and in accordance with the Guide for the Care and Use of Laboratory Animals.

2.2. Primary Astrocytes Preparation

Primary astrocytes were prepared from postnatal day 0–1 male and female wild type C57BL/6, PERK‐CAGG‐CreERTM, or EIF2B5 mutant mice as previously described (Meares et al. 2012). The sex of the mice was not determined prior to use. In brief, pups were euthanized by decapitation, and the brains were collected into cold media. Meninges, cerebellum, and olfactory bulbs were removed, and cerebra were collected. Tissue was disrupted by trituration and filtered through a 100 μm cell strainer. Cells were centrifuged at 300 × g for 5 min, resuspended in fresh astrocyte medium (Dulbecco's Modified Eagle Medium [DMEM] with 10% fetal bovine serum [FBS], 16 mM 2‐[4‐(2‐hydroxyethyl)piperazin‐1‐yl] ethane sulfonic acid [HEPES], 1 × nonessential amino acids, 2 mM L‐glutamine, 100 units/mL penicillin, 100 μg/mL streptomycin, and 50 μg/mL gentamicin [Fisher Scientific]), and transferred onto T‐75 tissue culture flasks. The cultures were maintained for approximately 12–15 days at 37°C in a humidified 5% CO2/95% air atmosphere. One‐third of the media was changed every 3–4 days. To knockout PERK, 4‐hydroxy‐tamoxifen (2 μM) was given directly into the flasks 48 h prior to plating. Astrocytes were separated from microglia by shaking at 200 rpm for 2 h. Subsequently, astrocytes were trypsinized, washed, and seeded into 6‐well plates. Cells were cultured for 48–72 h before experimental treatments.

2.3. Antibodies and Reagents

Primary antibodies used were: Anti JAK1 (3344), P‐eIF2α (3398), eIF2α (5324), P‐STAT1 (9167), STAT1 (14994), P‐STAT3 (9145), STAT3 (12640), PERK (3192), IκBα (4814), A20 (5630), p65 (3033) from Cell Signaling; Glyceraldehyde 3‐phosphate dehydrogenase (GAPDH) (MAB374) and anti‐puromycin (MAB343) from Millipore Sigma; SOCS3 (ab16030) from Abcam. Cytokines used were: oncostatin (OSM) M, IL‐1β, and tumor necrosis factor (TNF)–α from R&D Systems. Thapsigargin, tunicamycin, and CCT020312 were from Millipore Sigma. Puromycin was from Fisher Scientific.

2.4. siRNA Transfections

Primary astrocytes were transfected with the indicated small interfering (si) RNA (50 pmol per 35 mm well) using Lipofectamine RNAiMAX (Life Technologies) according to the manufacturer's protocol. Cells were used for experiments 48–72 h after transfection. The siRNAs used in this study include siRNA silencer select Control, non‐targeting (siRNA ID 4390843) siRNA, Jak1 siRNA (siRNA ID s68537), Eif2ak3 (PERK) siRNA (siRNA ID), and P65 siRNA (siRNA ID: s72857).

2.5. Genome Editing

1321N1 human astrocytoma cell line stably expressing Cas9 nuclease was purchased from GeneCopoeia. Cells were cultured in DMEM with 10% FBS, 2 mM L‐glutamine, 100 units/mL penicillin, 100 μg/mL streptomycin, and 200 μg/mL hygromycin. Single guide RNAs (sgRNA) were designed by and purchased from Synthego. Cells were transfected in the absence of antibiotics using 50 pmol of sgRNA and Lipofectamine RNAiMAX. Knockout efficiency was determined by immunoblotting.

2.6. Quantitative RT‐PCR Analysis

RNA was isolated using 1 mL of TRIzol (Life Technologies) according to the manufacturer's protocol. RNA was quantified using a NanoDrop system (Thermo Scientific). For cDNA synthesis, 1 μg of RNA was mixed with oligo dT primer and incubated at 70°C for 5 min, followed immediately by 5 min on ice. A mix containing reaction buffer (Promega), Moloney murine leukemia virus reverse transcriptase, deoxynucleotide triphosphates (dNTP), and ribonuclease inhibitor (Promega) was added and incubated at 42°C for 1 h. The reaction was terminated by incubation at 95°C for 5 min. qPCR was performed using an ABI Step One Plus (Applied Biosystems). Reactions were carried out in 20 μL using Maxima Probe/ROX qPCR Master Mix and Taqman probe‐based primers (ThermoFisher). Data were analyzed using the ΔΔCt method and normalized to HPRT.

2.7. RNA Sequencing and Bioinformatics

Library preparation and RNA sequencing was conducted by Adera Health. RNA was assessed by Bioanalyzer and all RIN values were greater than 8. RNA was DNAase treated and depleted of ribosomal RNA (Ribo‐Zero, Illumina). Libraries were built using NEBNext Ultra II Directional kit as per manufacturer's protocol (New England Biolabs). The libraries were then quantified with Qubit and run on the Bioanalyzer using a High Sensitivity DNA chip to determine the average size. They were then pooled at an equimolar ratio and sequenced (paired‐end (PE) 150 bp) on a NovaSeq 6000. Analysis was performed using CLC Genomics Workbench (Qiagen). ShinyGO was used for Gene ontology (GO) enrichment analysis (Ge et al. 2020). Data visualization in Figure 1C was generated with assistance from ChatGPT using Python with the Seaborn and Matplotlib libraries.

FIGURE 1.

FIGURE 1

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ER stress and TNF‐α drive coordinated gene expression dependent on JAK1. (A) Primary murine astrocytes were transfected with control non‐targeting (NT) siRNA or JAK1 siRNA. After 48 h, the cells were treated with thapsigargin (thaps) (1 μM), TNF‐α (10 ng/mL), or both for 4 h followed by immunoblotting. (B) Astrocytes were treated as in (A) followed by RNAseq. The data in (B, C) are from the control siRNA group. Heatmap shows the top 1000 genes differentially expressed in the thaps + TNF‐α group, each column contains 3 biological replicates. (C) Top 20 genes showing synergistic induction by thaps + TNF‐α, values represent fold change from untreated. Synergy was defined as 1.5 times the additive values of thaps and TNF‐α alone. Synergy index is the thaps + TNF‐α value minus the synergy value (defined as (thaps alone + TNF‐α alone) × 1.5)). (D) Volcano plot of genes decreased or increased by JAK1 knockdown in the thaps + TNF‐α group. (E) Proportion of genes increased by thaps + TNF‐α dependent of JAK1. (F) Gene ontology (GO) terms for biological (green) and molecular process (yellow) based on JAK1‐dependent genes.

2.8. Western Blotting

Cells were washed twice with 1× Dulbecco's phosphate‐buffered saline (DPBS) (Gibco) and lysed with immunoprecipitation (IP) lysis buffer (20 mM Tris [pH 7.5], 150 mM NaCl, 2 mM EDTA, 2 mM EGTA, 0.5% NP‐40, and 1× phosphatase/protease inhibitor cocktail [Thermo Scientific]). Protein concentrations were determined using the bicinchoninic acid assay (BCA) assay (Thermo Scientific). Equal amounts of protein from each sample were solubilized in Laemmli sample buffer [2% Sodium Dodecyl Sulfate (SDS)] and heated for 5 min at 95°C. Proteins were separated by 8% or 10% SDS‐polyacrylamide gel electrophoresis and transferred to nitrocellulose membranes (Bio‐Rad). The membranes were blocked in 5% milk in TBST (20 mM Tris base, 137 mM NaCl, and 0.05% Tween‐20) followed by overnight incubation at 4°C with primary antibody diluted in 5% bovine serum albumin (BSA) (Fisher) or milk, according to the manufacturer's recommendation. Primary antibodies were diluted as follows: JAK1 1:2000, PERK 1:2000, IκBα 1:1000, p65 1:1000, A20 1:1000, P‐STAT1 1:3000, STAT1 1:3000, P‐STAT3 1:3000, STAT3 1:6000, GAPDH 1:120000, SOCS3 1:1000. Membranes were washed for 1 h with frequent changes to TBST. Membranes were incubated with horseradish peroxidase‐conjugated goat anti‐rabbit or goat anti‐mouse (1:3000 dilution, Jackson Immuno Research) secondary antibody diluted in 5% milk in TBST for 1 h at room temperature. Membranes were again washed for 1 h, and TBST was changed frequently. Proteins were detected by enhanced chemiluminescence (Thermo‐scientific). Immunoblots were imaged on ChemiDoc Touch imaging system (Bio‐Rad).

2.9. Protein Translation

Protein synthesis was estimated by measuring puromycin incorporation using a modified method based on Schmidt et al. (2009). Briefly, cells were incubated with puromycin (5 μg/mL) for 5 min, followed by washing in cold PBS and lysed with lysis buffer. Cell lysates were analyzed by Western blot using an anti‐puromycin antibody (Millipore) at 1:5000 dilution in 5% milk/TBST.

2.10. Statistical Analysis

All statistical analyses were performed using GraphPad Prism. An unpaired two‐tailed t‐test was used to compare two groups. A one‐way ANOVA was performed to compare more than two groups. Tukey's multiple comparison test was used for post hoc analysis. A two‐way ANOVA was performed to compare two independent variables. Tukey's multiple comparison test was used for post hoc analysis. Statistical significance is defined as p < 0.05. Data are represented as Mean ± standard deviation. Numerical p values are shown wherever applicable. RNA‐seq significance was determined using the Empirical Analysis of Differential Gene Expression (EDGE) test and significance was determined as a false discovery rate adjusted p value < 0.05.

3. Results

3.1. ER Stress and TNF‐α Drive a JAK1‐Dependent Transcriptional Program in Astrocytes

TNF‐α is a microglial and immune cell‐produced cytokine that alters the functional properties of astrocytes and is frequently implicated in neurological diseases (Lee et al. 2023; Sofroniew 2020; Prinz et al. 2019). Previously, we have shown that ER stress synergizes with TNF‐α to induce Il6 and Ccl20 gene expression in astrocytes in a JAK1‐dependent fashion (Sims and Meares 2019). To examine if other genes respond in a similar fashion, we transfected primary murine astrocytes with control (non‐targeting) or JAK1 siRNA to knock down JAK1. The astrocytes were then stimulated with thapsigargin (thaps) to induce ER stress, TNF‐α, or both stimuli together, and gene expression was measured by RNAseq after 4 h. As shown in Figure 1A, JAK1 was effectively knocked down and thaps induced ER stress, as shown by increased DNA damage‐inducible transcript 3 (Ddit3/CHOP) expression. We first analyzed the responses in the control siRNA transfected astrocytes. In general, ER stress and TNF‐α induced distinct gene expression programs and, when combined, these programs were substantially altered (Figure 1B). The gene expression pattern indicated that genes that were uniquely induced by either stimulus tended to also be increased in the combination‐treated group. Similarly, genes that were repressed tended to remain repressed. Collectively, the combination of ER stress and TNF‐α established a distinctive gene expression program in the astrocytes that was largely associated with stress and immune responses (Figure S1). We identified that many of the genes induced by either stimulus alone were substantially augmented in the combined treatment group, suggestive of a synergistic interaction. To examine and quantify this, we defined synergy as 1.5 times the additive fold change values of thaps and TNF‐α treatments alone. We identified over 200 genes that met this criterion (Table S1). As shown in Figure 1C, the top genes show strong synergistic induction. We also quantified the level of synergy using an index (based on fold change values from untreated) which is defined as the thaps + TNF‐α fold change values–((thaps alone + TNF‐α alone) × 1.5) (Figure 1C). Chemokines including Ccl20, Cxcl11, and Cxcl2 were among the genes with the highest level of synergy. We then examined which of the ER stress + TNF‐α induced genes were JAK1‐regulated by comparing gene expression between control and JAK1 siRNA transfected astrocytes. As shown in Figure 1D, numerous genes were regulated by JAK1, including those previously identified, such as Il6. Additionally, Jak1 was significantly reduced, confirming efficient knockdown (Figure 1D). We examined the proportion of genes that were increased dependent on JAK1 and identified that over 35% of the genes induced by the combination of ER stress and TNF‐α are JAK1‐dependent (Figure 1E). These genes were predominantly associated with immune responses (Figure 1F). Overall, these data demonstrate that ER stress and TNF‐α induced transcriptional programs modify one another and that JAK1 is a vital driver of this process. Furthermore, this was not unique to TNF‐α. IL‐1β also signals through a NF‐κB‐dependent pathway and synergizes with ER stress in a JAK1‐dependent fashion (Figure S2).

To begin to examine the mechanistic basis of this synergistic gene induction, we focused on a few representative genes (e.g., Il6 and Ccl20). We first confirmed that this effect was not an artifact of culturing astrocytes in serum, which has been suggested to promote an inflammatory state (Foo et al. 2011). For this, astrocytes were immunopurified (IP) using anti‐ATP1B2 (ACSA‐2) and cultured in defined serum‐free media (modified from Foo et al. 2011; Batiuk et al. 2017; Kantzer et al. 2017). As shown in Figure S3A, these cells express the astrocyte marker SOX9 and have low and variable levels of GFAP expression. Additionally, they have minimal expression of genes associated with inflammatory astrocytes when compared to neonatal astrocytes grown with serum (Figure S3B). As shown in Figure S3C, the combination of ER stress and TNF‐α synergized to drive Il6 and Ccl20 expression, consistent with the data in Figure 1 and our previous work (Sims and Meares 2019).

3.2. PERK Is Required for ER Stress and TNF‐α Induced Gene Expression

We have previously shown that ER stress in astrocytes drives Il6 and Ccl20 expression dependent on PERK and JAK1 (Guthrie et al. 2016; Sims and Meares 2019). As shown in Figure S4, ER stress does not impact the stability of Il6 mRNA. Therefore, we expected that the synergistic interaction between ER stress and TNF‐α would require PERK. To test this, astrocytes were isolated and cultured from PERK floxed (PERKfl/fl) mice without or with CAGG‐CreER (PERKKO) and treated with 4‐OH tamoxifen in vitro to delete PERK (Figure 2A,B). We then treated the PERKfl/fl and PERKKO astrocytes with thaps, TNF‐α, or the combination for 4 h. As shown in Figure 2C, deletion of PERK significantly diminished the synergistic induction of Il6 and Ccl20. Additionally, we measured IL‐6 protein in the supernatant after 48 h, which revealed a similar synergistic induction of IL‐6 and that PERK is required under these conditions (Figure 2D). We then tested tunicamycin (tunic) as an alternative ER stress inducing agent. As shown in Figure 2E, the combination of tunic and TNF‐α enhanced Il6 expression but was moderate compared to thaps, while Ccl20 was strongly increased by the combination treatment. Both Il6 and Ccl20 were significantly reduced in the PERKKO astrocytes. The PERK‐dependent gene Ddit3 was increased by thaps or tunic and remained at similar levels in the ER stress + TNF‐α group. Ddit3 was significantly reduced in the PERKKO astrocytes (Figure 2C,E). The modest difference in responses between thaps and tunic may reflect differences in the mechanisms of action of these compounds. Thaps inhibits the sarcoendoplasmic reticulum calcium ATPase (SERCA) pump, increasing intracellular Ca2+ while tunic inhibits N‐linked glycosylation causing misfolded protein accumulation in the ER (Lytton et al. 1991; Heifetz et al. 1979). These data confirm that ER stress induced Il6 and Ccl20 expression requires PERK. However, it was unclear if ER stress is required for these effects or if PERK activation alone is sufficient. To test this, we used the small molecule PERK agonist, CCT020312 (CCT) (Stockwell et al. 2012) in wild type (WT) astrocytes. CCT alone increased Il6, Ccl20, and Ddit3 expression, consistent with PERK activation. The combination of CCT and TNF‐α led to enhanced expression of Il6 and Ccl20 (Figure 2F). These data indicate that PERK, in the absence of other ER stress‐induced pathways, can interact with TNF‐α‐induced signaling to drive enhanced inflammatory gene expression.

FIGURE 2.

FIGURE 2

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PERK drives synergy between ER stress and TNF‐α. Astrocytes were isolated from PERK fl/fl or PERK fl/fl × CAGG‐CreER and treated with 4‐OH tamoxifen (2 μM) to delete PERK. (A) Representative immunoblot from astrocytes treated without or with thaps (1 μM) for 4 h. (B) PERK expression was quantified from immunoblots of independent astrocyte preparations. N = 12/group. (C) Astrocytes were treated with thaps (1 μM), TNF‐α (10 ng/mL), or both for 4 h followed by qPCR. (D) Astrocytes were treated as in (C) for 48 h, IL‐6 was measured in the cell culture supernatant by ELISA. (E) Astrocytes were treated with tunicamycin (tunic) (5 μM), TNF‐α (10 ng/mL), or both for 4 h followed by qPCR. (F) Wild type Astrocytes were treated with CCT020312 (CCT) (10 μM), TNF‐α (10 ng/mL), or both for 4 h followed by qPCR. Data are means ± standard deviation of independent biological replicates.

To test if this synergy also occurs in human cells in a JAK1 and PERK dependent fashion, we used the human 1321N1 astrocytoma cell line stably expressing cas‐9. We delivered JAK1 guide RNA (gRNA) to delete JAK1. As shown in Figure 3A, we tested several guides and identified guide #2 that substantially reduced JAK1 levels and abrogated IFN‐γ‐induced STAT1 phosphorylation. We then compared the response of this JAK1 knockout cell line (non‐clonal pool) to control cells (non‐targeting gRNA). The combination of thaps and TNF‐α drove a synergistic induction of IL6 and CCL20 that was significantly reduced in the JAK1 knockout cells. Consistent with Figure 1A, JAK1 knockout had no impact on the ER stress‐induced expression of DDIT3 (Figure 3B). These data confirm that JAK1 is required for the combinatorial effects of ER stress and TNF‐α. Next, we deleted EIF2AK3, the gene encoding PERK, using the same Crispr‐based approach and confirmed that ER stress induced phosphorylation of eIF2α was abolished (Figure 3C). In line with the findings in murine astrocytes, PERK deletion significantly reduced IL6 and CCL20 expression in response to ER stress + TNF‐α. DDIT3 expression was also diminished, consistent with PERK deletion (Figure 3D). Overall, these data show that ER stress augments TNF‐α‐induced gene expression in both primary murine astrocytes and human astrocytoma cells through a PERK and JAK1 dependent pathway.

FIGURE 3.

FIGURE 3

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JAK1 and PERK are required to augment TNF‐α induced gene expression in human glioma cells. (A) 1321N1 cells stably expressing Cas9 were transfected with non‐targeting (NT) or JAK1 guide RNAs (gRNA) to establish non‐clonal cell lines. These cells were then treated with IFN‐γ (10 ng/mL) for 30 min followed by immunoblotting. (B) NT and JAK1 gRNA (#2) cells were treated with thaps (1 μM), TNF‐α (10 ng/mL), or both for 4 h followed by qPCR. (C) 1321N1 cells stably expressing Cas9 were transfected with NT or PERK gRNA to establish non‐clonal cell lines. These cells were then treated with thaps (1 μM) for the indicated times followed by immunoblotting. (D) NT and PERK gRNA cells were treated with thaps (1 μM), TNF‐α (10 ng/mL), or both for 4 h followed by qPCR. N = 4, data are means ± standard deviation.

3.3. ER Stress Amplifies Cytokine‐Induced Gene Expression by Suppressing Negative Feedback Mechanisms

The data from the current study and our previous findings suggest that p‐eIF2α induced translational suppression may be a mechanism by which ER stress enhances inflammatory gene expression. TNF‐α induces the degradation of the inhibitory protein IκBα, enabling NF‐κB to translocate to the nucleus and activate gene expression. Crucially, TNF‐α also drives negative feedback mechanisms to resynthesize IκBα, which helps terminate the pathway and prevent excessive inflammation (Taniguchi and Karin 2018). We hypothesized that ER stress may interfere with this negative feedback mechanism. To test this, we treated astrocytes with TNF‐α without or with thaps from 15 min–4 h. Within 15 min following TNF‐α, IκBα was degraded and was resynthesized by 1 h. Under ER stress, the resynthesis of IκBα was significantly delayed, while an additional negative regulator of NF‐κB, A20, was minimally impacted (Figure 4A,B). These data suggest that prolonged NF‐κB activation may contribute to the enhancement of gene expression. As expected, knockdown of the NF‐κB p65 subunit significantly reduced the combination effects of ER stress and TNF‐α on Il6 and Ccl20 expression, confirming the essential role of NF‐κB (Figure 4C). As shown in Figure 4D, p65 was effectively knocked down without impacting the induction of ER stress as assessed by CHOP expression. We then tested if reversing ER stress‐induced translational suppression using the small molecule eIF2B agonist, ISR inhibitor (ISRIB) (Zyryanova et al. 2021; Sidrauski et al. 2013), could rescue IκBα expression. As shown in Figure 4E, the combination of thaps + TNF‐α stimulated the degradation and delayed resynthesis of IκBα. Treatment with ISRIB had no effect on the degradation of IκBα but restored the timing of resynthesis to that of TNF‐α alone. The delayed resynthesis of IκBα was also reversed by knockdown of PERK (Figure S5). Consistent with restored regulation of this pathway, ISRIB prevented the enhanced gene expression observed with the combination of ER stress and TNF‐α (Figure 4F). These data indicate that ER stress enhances TNF‐α‐induced gene expression by interfering with negative feedback mechanisms that require protein synthesis.

FIGURE 4.

FIGURE 4

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Translational suppression facilitates synergy between ER stress and TNF‐α. (A) Astrocytes were treated with TNF‐α (10 ng/mL) without or with thaps (1 μM) for the indicated times followed by immunoblotting. (B) Quantification of IκBα from (A). N = 4, p value determined by repeated measures ANOVA. (C) Astrocytes were transfected with non‐targeting (NT) siRNA or p65 siRNA. After 48 h, the cells were treated with thaps (1 μM), TNF‐α (10 ng/mL), or both for 4 h followed by qPCR for IL‐6. (D) Astrocytes were treated as in (C) followed by immunoblotting. (E) Astrocytes were treated with TNF‐α (10 ng/mL) and thaps (1 μM) for the indicated times without or with ISRIB (0.5 μM) followed by immunoblotting. (F) Astrocytes were treated with thaps (1 μM), TNF‐α (10 ng/mL), or both for 4 h without or with ISRIB (0.5 μM)followed by qPCR. Vehicle or ISRIB was added 30 min prior to additional treatments. Data are means ± standard deviation of independent biological replicates.

To test if this mechanism extends beyond NF‐κB activating cytokines, we used the IL‐6 family cytokine oncostatin M (OSM) that signals through the JAK/STAT pathway. This pathway induces the expression of suppressors of cytokine signaling (SOCS) proteins as a negative feedback mechanism (Yoshimura et al. 2007). These proteins constrain neuroinflammation and inflammatory responses by astrocytes (Qin et al. 2008; Baker et al. 2009). As shown in Figure 5A, OSM stimulated the activation‐associated phosphorylation of STAT3 at tyrosine 705. OSM also increased SOCS3 expression, in line with previous work (Baker et al. 2008). ER stress, initiated by thaps or tunic, significantly reduced the OSM‐induced expression of SOCS3 while modestly enhancing STAT3 phosphorylation (Figure 5A,B). Additionally, ER stress and OSM strongly synergized to drive IL‐6 expression (Figure 5C). Similar to IκBα, ISRIB could rescue the expression of SOCS3 under conditions of ER stress (Figure 5D). Moreover, ISRIB suppressed the synergistic induction of Il6 by ER stress and OSM (Figure 5E). Collectively, these data show that ER stress suppresses the cytokine‐induced synthesis of negative regulatory proteins, which contributes to increased inflammatory gene expression.

FIGURE 5.

FIGURE 5

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ER stress suppresses translation of SOCS3 and synergizes with OSM to drive IL‐6 expression. (A) Astrocytes were treated with OSM (2.5 ng/mL) without or with thaps (1 μM) or tunic (5 μM) for 4 h followed by immunoblotting. (B) Quantification of SOCS3 from (A). (C) Astrocytes were treated with thaps (1 μM), OSM (2.5 ng/mL), or both for 4 h followed by qPCR for IL‐6. (D) Astrocytes were treated with OSM (2.5 ng/mL), thaps (1 μM), and ISRIB (0.5 μM) as indicated for 4 h followed by immunoblotting. (E) Astrocytes were treated with OSM (2.5 ng/mL) and thaps (1 μM) without or with ISRIB (0.5 μM) for 4 h followed qPCR for IL‐6. Vehicle or ISRIB was added 30 min prior to additional treatments. Data are means ± standard deviation of independent biological replicates.

The data clearly indicate that ER stress‐induced suppression of protein translation is necessary to enhance TNF‐α and OSM‐induced gene expression. However, it was unknown if this was sufficient to enhance cytokine‐induced gene expression. To address this, we isolated astrocytes from mice that carry a VWM‐associated mutation in EIF2B5 (I98M). This mutation reduces the guanine nucleotide exchange activity of EIF2, mimicking the effects of p‐eIF2α and leading to neurological dysfunction and white matter degeneration in mice homozygous for this mutation, while heterozygous mice are unaffected (Terumitsu‐Tsujita et al. 2020). These defects can be rescued by targeted expression of WT EIF2B5 in astrocytes (Herstine et al. 2024). We isolated astrocytes that were WT, heterozygous for the I98M mutation (WT/I98M), or homozygous (I98M/I98M). Astrocytes were stimulated with TNF‐α, OSM, or IL‐1β. These cytokines induced Il6 and Ccl20 to varying degrees and this was unaffected by the I98M mutation. Ddit3 expression was also similar between the WT and mutant cells indicating there was not ER stress under these conditions (Figure 6A). Additionally, there was no difference between WT and I98M/I98M astrocytes in the levels or kinetics of IκBα, P‐STAT3, or SOCS3 in response to cytokines (Figure 6B,C). These data suggest that disruption of EIF2B5 function is insufficient to augment cytokine responses; however, these cells were cultured with serum and high levels of glucose. Recent work has shown that sugar phosphates, such as the glycolytic metabolite fructose‐6‐phosphate, are direct agonists of eIF2B (Hao et al. 2021). This raised the possibility that culturing these cells under nutrient‐rich conditions may overcome the effects of the mutation in EIF2B5. To account for this, we cultured the cells without glucose or serum for 48 h prior to treatment with cytokines. As shown in Figure 6D, protein synthesis is diminished in the mutant astrocytes as measured by puromycin incorporation, while cytokine signaling appeared to remain intact based on OSM‐induced phosphorylation of STAT3. Cytokine‐induced gene expression showed no alterations in the cells with the homozygous I98M mutation even under these nutrient‐deprived conditions (Figure 6E). These data suggest that disruption of translation is necessary but not sufficient to drive enhanced cytokine‐induced gene expression in astrocytes and that PERK and JAK1‐dependent signals are also required.

FIGURE 6.

FIGURE 6

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Translational suppression is not sufficient to augment cytokine induced gene expression. (A) Astrocytes from EIF2B5 wild type (WT), heterozygous (WT/I98M), or homozygous (I98M/I98M) mice were treated with TNF‐α (10 ng/mL), OSM (2.5 ng/mL), or IL‐1β (500 pg/mL) for 4 h followed by qPCR. (B) EIF2B5 WT or I98M/I98M astrocytes were treated with TNF‐α (10 ng/mL) for the indicated times followed by immunoblotting. (C) EIF2B5 WT or I98M/I98M astrocytes were treated with OSM (2.5 ng/mL) for the indicated times followed by immunoblotting. (D, E) EIF2B5 WT/I98M or I98M/I98M astrocytes were cultured without serum or glucose for 48 h then stimulated with cytokines as in (A), followed by immunoblotting (D) or qPCR (E). Data are means ± standard deviation of independent biological replicates.

4. Discussion

Our findings indicate that transcriptional and translational programs stimulated by ER stress and cytokines work in coordination to maximize inflammatory gene expression in astrocytes. This process requires JAK1, which we have shown previously is critical in the PERK dependent inflammatory response to ER stress (Meares et al. 2014). However, JAK1 does not impact PERK mediated phosphorylation of eIF2α and subsequent suppression of protein translation (Sims and Meares 2019). Thus, PERK appears as a vital signaling node that drives both JAK1‐dependent gene expression and attenuation of translation. This led us to ask how suppression of protein translation could impact transcription of inflammatory genes. Cytokines such as TNF‐α and OSM activate signaling pathways that include the upregulation of inhibitory proteins, which play a key role in negatively regulating the pathway and preventing overactivation. Our findings indicate that ER stress induced translational suppression impairs this negative regulation and likely prolongs the activity of key transcription factors driving gene expression. This provides a mechanistic link between translational control and inflammatory gene expression, as summarized in Figure 7.

FIGURE 7.

FIGURE 7

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Summary schematic of the PERK/eIF2α/JAK1 Signaling Axis that augments inflammatory gene expression in astrocytes. ER stress drives PERK activation that enhances cytokine induced transcriptional programs through a JAK1‐dependent mechanism. PERK also phosphorylates eIF2α to suppress protein translation, which leads to reduced or delayed synthesis of the negative regulatory proteins IκBα and SOCS3. Attenuated production of IκBα or SOCS3 further enhances the ER stress/cytokine induced inflammatory gene expression. ISRIB restores the expression of IκBα or SOCS3 and reduces inflammatory gene expression induced by the combination of ER stress and TNF‐α or OSM. Created in BioRender. Meares, G. (2025) https://BioRender.com/ilmw72d.

Previous work in oligodendrocytes has demonstrated that PERK drives NF‐κB activation to promote cell survival by diminishing synthesis of IκBα in vitro and in vivo (Lin et al. 2012; Lei et al. 2020). While PERK activation in both oligodendrocytes and astrocytes promotes NF‐κB signaling, the functional outcomes appear different (i.e., survival vs. inflammation). However, it is possible that PERK may drive a similar survival response in astrocytes, as we have shown that deletion of PERK sensitizes astrocytes to ER stress‐induced caspase 3 activation (Guthrie et al. 2016). Additionally, considering the emerging evidence that oligodendrocyte lineage cells can have inflammatory functions (Kirby et al. 2019; Boccazzi et al. 2021; Madsen et al. 2020), it is possible that PERK and NF‐κB may also drive inflammatory gene expression in these cells.

Using astrocytes with mutated EIF2B5, we identified that impairment of translation alone is insufficient to enhance the responsiveness to inflammatory cytokines. Importantly, the astrocytes were isolated from 1‐day‐old pups, a timepoint prior to the activation of UPR pathways in the EIF2B5 mutant mice (Terumitsu‐Tsujita et al. 2020). Consistent with this, there was no increase of Ddit3 expression under the conditions we tested. These findings further support the premise that PERK activation is vital not only for driving eIF2α phosphorylation but also for establishing a transcriptional program that promotes inflammatory gene expression. However, because IκBα and SOCS3 levels were unaffected in astrocytes carrying the EIF2B5 mutation, we cannot exclude the possibility that translational suppression never reached the threshold necessary to trigger a synergistic response. Considering that the synergy between ER stress and TNF‐α required translation suppression, it is likely that this effect is not unique to ER stress and is generalizable to the ISR. We are currently testing if this is the case. Linking phosphorylation of eIF2α to enhanced inflammatory responses could be beneficial in physiological contexts. For example, viral infections in which PKR would phosphorylate eIF2α may help to strengthen the inflammatory response to combat these pathogens. However, aberrant activation of the UPR, as in many neurological diseases, could be a detrimental amplifier of neuroinflammation. Additionally, PERK activation in astrocytes has been shown to impair synaptogenic support for neurons (Smith et al. 2020). Together, this suggests a reactive state in which astrocytes could lose support for neurons and become hyperresponsive to inflammatory cytokines. These astrocytes would produce IL‐6 and a host of chemokines that could exacerbate the neuroinflammatory environment. As shown in Figures 4 and 5, production of Il6 and Ccl20 is dramatically reduced by ISRIB. It is currently unknown how widespread the effects of ISRIB are on astrocytes but raises the possibility that ISRIB may reverse this PERK‐induced activation state. The functional outcome of astrocytic PERK activation is still largely unknown but appears context‐dependent. We have shown that astrocytic PERK is protective in a murine model of ischemic stroke (Lahiri et al. 2023), yet this pathway is detrimental in a model of prion disease (Smith et al. 2020).

Transcriptomic analysis (Figure 1) highlighted widespread changes in astrocyte gene expression in response to TNF‐α and ER stress. However, under these conditions, protein translation is also suppressed. It is unknown which of these transcripts are translated into a functional protein. We have previously shown that astrocytes produce protein for IL‐6, CXCL10, CXCL1, CCL20, and other chemokines under ER stressed conditions (Guthrie et al. 2016; Meares et al. 2014). This indicates that astrocytes remain capable of producing inflammatory proteins even under p‐eIF2α conditions that attenuate the expression of other proteins, including IκBα and SOCS3. The differential translation of these proteins is likely due, in part, to the structure of the 5′ untranslated region of the mRNAs (Wek et al. 2023). Additionally, the continued translation of cytokines and chemokines is consistent with previous work showing that shorter lived proteins are less likely to be translationally suppressed by eIF2α phosphorylation (Schneider et al. 2020). We are currently conducting unbiased proteomics to comprehensively determine the proteins that are translated by astrocytes under inflammatory ISR conditions. Our findings are consistent with previous work showing that ER stress suppresses IκBα synthesis to drive NF‐κB activation (Deng et al. 2004; Lei et al. 2020; Wu et al. 2004). It has also been reported that ER stress enhances the pancreatic β‐cell response to IL‐1β through an IRE1/XBP1 dependent mechanism (Miani et al. 2012) and IRE1 has been shown to be involved in PERK‐dependent activation of NF‐kB (Tam et al. 2012). It is unknown whether IRE1 has a role in enhancing TNF‐α‐induced gene expression in astrocytes. However, previous work has shown that IRE1 activation in astrocytes promotes neuroinflammation in a mouse model of multiple sclerosis (Wheeler et al. 2019). These data indicate that ER stress pathways may integrate with inflammatory pathways through multiple mechanisms in astrocytes. We identified that ER stress augments inflammatory gene expression through suppression of negative regulators like IκBα or SOCS3. The observed enhancement of TNF‐α‐ and OSM‐induced gene expression likely extends to other cytokines. For example, IL‐1, which signals via NF‐κB, is also augmented by ER stress in a JAK1‐dependent fashion, indicating a similar mechanism for that identified for TNF‐α. SOCS proteins are induced by a variety of JAK/STAT‐activating cytokines, including those in the IL‐6 family and interferons. Thus, translational suppression mediated by ER stress could profoundly influence immunological functions by reducing SOCS protein levels.

In summary, our study elucidates a central mechanism by which ER stress enhances cytokine‐induced gene expression in astrocytes via a PERK/p‐eIF2α/JAK1 pathway. This mechanism integrates JAK1‐mediated transcriptional regulation with p‐eIF2α‐driven translational suppression of negative feedback regulators, highlighting an important interaction between ER stress and cytokine signaling in shaping inflammatory responses. This may be a mechanism that contributes to chronic or excessive inflammation in neurological diseases.

Author Contributions

A.L.: experimental design, data collection, analysis, figure generation, manuscript writing and editing; S.G.S, A.M., and I.J.: data collection, analysis, figure generation; M.J.M. and S.A. data collection, analysis, figure generation and manuscript editing; J.A.H. and A.M.B: contributed materials, intellectual content, and manuscript editing. G.P.M: experimental design, data collection, analysis, figure generation, manuscript writing and editing, and project management.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1: Supporting Information.

GLIA-73-2273-s002.docx (15.5KB, docx)

Figure S1: Supporting Information.

GLIA-73-2273-s006.tif (586.4KB, tif)

Figure S2: Supporting Information.

GLIA-73-2273-s004.tif (591.2KB, tif)

Figure S3: Supporting Information.

GLIA-73-2273-s007.tif (1,005.4KB, tif)

Figure S4: Supporting Information.

GLIA-73-2273-s001.tif (512.5KB, tif)

Figure S5: Supporting Information.

GLIA-73-2273-s005.tif (634.4KB, tif)

Table S1: Supporting Information.

GLIA-73-2273-s003.docx (37.4KB, docx)

Acknowledgments

This work is supported by NIH grants NS099304 (to G.P.M.), NS113482 (to S.G.S.) and NS139538 (to J.A.H.). Additional support was provided by The Columbus Foundation (to A.M.B.). We thank Basant Ahmed and Katilyn Simmons for critical evaluation of the manuscript.

Lahiri, A. , Sims S. G., Herstine J. A., et al. 2025. “Endoplasmic Reticulum Stress Amplifies Cytokine Responses in Astrocytes via a PERK/eIF2α/JAK1 Signaling Axis.” Glia 73, no. 11: 2273–2288. 10.1002/glia.70067.

Funding: This work is supported by NIH grants NS099304 (to G.P.M.), NS113482 (to S.G.S.) and NS139538 (to J.A.H.). Additional support was provided by The Columbus Foundation (to A.M.B.).

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Associated Data

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

Supplementary Materials

Data S1: Supporting Information.

GLIA-73-2273-s002.docx (15.5KB, docx)

Figure S1: Supporting Information.

GLIA-73-2273-s006.tif (586.4KB, tif)

Figure S2: Supporting Information.

GLIA-73-2273-s004.tif (591.2KB, tif)

Figure S3: Supporting Information.

GLIA-73-2273-s007.tif (1,005.4KB, tif)

Figure S4: Supporting Information.

GLIA-73-2273-s001.tif (512.5KB, tif)

Figure S5: Supporting Information.

GLIA-73-2273-s005.tif (634.4KB, tif)

Table S1: Supporting Information.

GLIA-73-2273-s003.docx (37.4KB, docx)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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