Katherine M. Andersh
Michael MacLean
Gareth R. Howell
Richard T. Libby- 1Department of Ophthalmology, Flaum Eye Institute, University of Rochester Medical Center, Rochester, NY, United States
- 2Neuroscience Graduate Program, University of Rochester Medical Center, Rochester, NY, United States
- 3The Center for Visual Sciences, University of Rochester, Rochester, NY, United States
- 4The Jackson Laboratory, Bar Harbor, ME, United States
- 5Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, NY, United States
Introduction: A growing body of literature suggests a role for neuroinflammation in retinal ganglion cell (RGC) death in glaucoma. For instance, deficiency of three proinflammatory cytokines, complement component 1, subcomponent q (C1q), interleukin 1 alpha (Il1a), and tumor necrosis factor (Tnf), resulted in significant protection of RGCs after glaucoma-relevant insults. While TNF and C1Q have been extensively investigated in glaucoma-relevant model systems, the role of IL1A in RGCs is not well defined.
Methods: Eyes of 2–4 month-old C57BL/6J mice or mice deficient in either Jun or Sarm1 were intravitreally injected with IL1A alone, TNF alone, or IL1A and TNF together. Retinal flat mounts were assessed for RGC survival using immunostaining of RBPMS. Bulk RNA-sequencing and differential expression analyses of retinal tissue was performed to determine molecular changes in response to IL1A, TNF, and IL1A combined with TNF within C57BL/6J and Sarm1 deficient mice.
Results: Intravitreal injection of IL1A did not result in RGC death at either 14 days or 12 weeks. Consistent with previous studies, TNF injection did not cause significant RGC loss at 14 days but did after 12 weeks. Together, IL1A+TNF resulted in a relatively rapid RGC death, driving significant loss 2 weeks after injection. We identified molecular changes which occur in response to IL1A and to combined IL1A+TNF treatment with limited changes identified in TNF alone treated eyes. Using mice deficient in Jun or Sarm1, we showed RGC loss after IL1A+TNF insult is JUN-independent and SARM1-dependent. Furthermore, RNA-seq analysis showed Sarm1 deficiency does not stop the neuroinflammatory response to IL1A+TNF.
Discussion: We identified a novel role of IL1A, we found that IL1A acted as a sensitizer to TNF-induced death. Co-injection of IL1A and TNF resulted in rapid RGC death, with significant RGC loss 14 days after injection. TNF+IL1A-induced RGC death did not depend on JUN activation and was rather SARM1 dependent. Also, RNA-seq analyses indicated that while Sarm1 deficiency protected from IL1A+TNF induced RGC loss it did not significantly alter microglia and astrocyte responses. Altogether, these findings indicate that IL1A potentiates SARM1-dependent TNF-induced RGC death in vivo.
Introduction
Glaucoma is a neurodegenerative disease characterized by retinal ganglion cell (RGC) death and irreversible loss of vision. Many studies in recent years have identified RGC intrinsic pathways required for RGC death after glaucoma-relevant insults (Syc-Mazurek and Libby, 2019). While these findings are promising, recent studies have implicated extrinsic signaling as key drivers of RGC injury in glaucoma. In fact, multiple studies have suggested a primary or direct role of microglia and astrocytes in glaucomatous neurodegeneration (Tezel, 2022; Miao et al., 2023).
Recent studies showed a direct neurotoxic role of neuroinflammation in glaucoma relevant RGC death, specifically through 3 neuroinflammatory molecules: C1qa, Tnf, and Il1a (Liddelow et al., 2017). These molecules were capable of indirectly driving RGC death via astrocyte activation in vitro (Liddelow et al., 2017), and deletion of C1qa, Tnf, and Il1a in vivo was sufficient to protect RGCs from mechanical optic nerve injury (optic nerve crush; ONC) (Liddelow et al., 2017; Guttenplan et al., 2020) and ocular hypertension (OHT) (Sterling et al., 2020). These studies show the role of neuroinflammatory signaling in driving glaucoma-relevant RGC death. In addition, in vitro application of TNF, IL1A and C1Q, can drive astrocyte activation (Liddelow et al., 2017). IL1A, TNF, and C1Q exposed astrocytes release neurotoxic lipids, which can kill RGCs (Guttenplan et al., 2021). These findings and others demonstrate the importance of these molecules in RGC degeneration after axonal insult (Kitaoka et al., 2006; Howell et al., 2011; Roh et al., 2012; Mac Nair et al., 2015). However, the direct neurotoxicity of these molecules in the absence of other insult(s) on the retina after intravitreal injection remains understudied.
C1Q and TNF have been extensively studied in the context of glaucoma, with C1q inhibition or deletion proving to be partially protective to RGCs (Howell et al., 2011). However, conflicting results implicating TNF in RGC degeneration have made it unclear whether it is protective or detrimental. TNF inhibition results in mild protection from OHT (Nakazawa et al., 2006; Roh et al., 2012), and deletion of Tnf leads to worsening RGC degeneration after ONC (Mac Nair et al., 2015). In the absence of other injuries, direct TNF application is known to drive approximately 15–20% RGC loss at a delayed rate following 8–12 weeks (Kitaoka et al., 2006; Mac Nair et al., 2015; Ko et al., 2020). These data suggest a complex and context-dependent role of TNF. IL1A is another key proinflammatory cytokine capable of being released from several cell types, including microglia (Hetier et al., 1988; Pinteaux et al., 2002; Todd et al., 2019), astrocytes (Friedman et al., 1996; Friedman, 2001; Lau and Yu, 2001; Moynagh, 2005), and Müller glia (Ueno et al., 2017). While IL1A was shown to be expressed in early stages of glaucoma in the DBA/2J glaucoma model (Howell et al., 2011), study of its function in the retina has been limited to retinal ischemia (Hangai et al., 1995) and uveitis (Rosenbaum et al., 1987; De Vos et al., 1994). Several studies assess the neurotoxic effects of IL1A in the central nervous system (Patel et al., 2003; Basu et al., 2004; Allan et al., 2005; Moynagh, 2005) though none have focused on the retina. It remains unknown if and how IL1A may act to drive RGC degeneration. Given the role of IL1A in RGC death after glaucoma-relevant insults learned from loss of function studies (Liddelow et al., 2017; Liddelow et al., 2017; Guttenplan et al., 2020; Sterling et al., 2020) it is important to understand the effects of IL1A on RGC survival. Here, we directly test the role of IL1A on RGCs to gain insight into the mechanisms of RGC death after cytokine insult in the absence of other injuries.
Materials and methods
Mice
Animals were fed chow and water ad libitum and housed on a 12-h light-to dark cycle. Roughly equal numbers of males and females were used for each experimental group. All mice included were 2–6 months of age. C57BL/6J, Sarm1 deficient (Jackson Laboratory, Stock # 018069), or Jun floxed (Junfl) (Behrens et al., 2002) mice were used. Floxed alleles of Jun were recombined in RGCs Six3-cre (The Jackson Laboratory, Stock# 019755) (Furuta et al., 2000). Six3-cre recombines in all retinal neurons (including RGCs) and retinal macroglia (retinal astrocytes and Muller cells) (Furuta et al., 2000; Rattner et al., 2013; Rattner et al., 2019). All experiments were conducted in adherence with the Association for Research in Vision and Ophthalmology’s statement on the use of animals in ophthalmic and vision research and were approved by the University of Rochester’s University Committee on Animal Resources.
Intravitreal injections
Mice were anesthetized with an intraperitoneal injection of 0.05 mL/10 g solution containing ketamine (20 mg/mL) and xylazine (2 mg/ mL). Eyes were sterilized with 50% betadine solution in phosphate buffered saline (PBS). The conjunctiva was cleared away with the bevel of a 30-gauge needle on the temporal side, and a small poke was made with the needle below the limbus and through the sclera. Vitreous was allowed to drain and was wicked away using a Kim wipe. If the eyes experienced an excessive bleed following the initial insertion of the needle, the eye was excluded from further injection and investigation. Hamilton syringes (Hamilton Company, 7,633–01) with blunt 33-gauge needles were used to perform intravitreal injections. The needle of the Hamilton syringe was inserted approximately 1 mm into the incision site at a 45° angle toward the optic nerve over a period of 30 s. Care was taken to avoid contacting the lens with the Hamilton needle. Before experiments were performed, it was established that eyes with observable lens damage due to intravitreal injection would be excluded from the study. Compounds were diluted in sterile PBS and injected slowly into the vitreous over 2 min to prevent a sudden pressure increase or leakage. 2 μL of IL1A alone (0.1 μg/μL, Peprotech, 200-01A), TNF alone (0.05 μg/μL, Sigma, T7539), or IL1A+TNF were injected. The amount of TNF used was based on our previous study that showed this amount resulted in RGC death (Mac Nair et al., 2015). To our knowledge, IL1A has not been used in intravitreal injections. The amount injected is approximately 25 times the ED50 provided by the supplier and 10 times higher than used in a recent intracisterna magna injections (Bretheau et al., 2022) when accounting for volume differences in the space injected (vitreal space and cerebrospinal fluid). After injection, the needle was held in place for 60 s to reduce drainage, and the needle was removed from the eye over the course of 30 s. The contralateral eye was injected with 2 μL of sterile PBS with identical methods to serve as an internal control. These methods were consistent across all lines and genotypes used.
Immunostaining and quantification
Immunohistochemistry was performed as previously described (Fernandes et al., 2012; Syc-Mazurek et al., 2017a; Syc-Mazurek et al., 2017b; Marola et al., 2020; Marola et al., 2022). Eyes were enucleated and fixed in 4% paraformaldehyde in 1X PBS at room temperature for 2 h. For whole mount assessment, retinas were dissected from the optic cup and blocked in 10% horse serum, 0.4% TritonX in 1X PBS overnight at 4°C. Retinas were incubated at 4°C for 72 h in primary antibody diluted in 10% horse serum, 0.4% TritonX in 1X PBS. Primary antibodies included: rabbit anti-pJUN (phosorylated JUN, Cell Signaling, 1:250; Cat# 9261S), rabbit cCASP3 (cleaved caspase 3, R&D, 1:500), rabbit anti-RBPMS (RNA binding protein, mRNA processing factor, GeneTex, 1:500; Cat# GTX118619), guinea pig anti-RBPMS (Phosphosolutions, 1:500; Cat# 1832-RBPMS), mouse anti-TUJ1 (class III beta-tubulin, BioLegend, 1:1,000; cat# 801201). Retinas were then washed and incubated overnight at 4°C in secondary antibody diluted in PBS (Alexa-fluor conjugated, Invitrogen and JacksonImmuno). Retinas were washed and mounted ganglion cell layer up in Fluorogel in TRIS buffer (Electron Microscopy Sciences). As previously described RBPMS+ and pJUN+ cells were quantified following collection of eight 40x fields per retina, and cCASP3+and RBPMS+ double positive cells were quantified using eight 20x fields per retina. Images were equally spaced 220 μm from the peripheral edge of the retina (with 2 images per quadrant) to gauge gross changes in RGC density following injection. For assessment of RGC density changes following injections, RBPMS+ TUJ1+ RGCs were quantified following collection of eight 40x fields per retina. Image quantification was performed using the cell-counter tool in ImageJ. A masked observer captured and manually quantified all images using these methods across groups and conditions.
Statistical analysis
The animal number is provided in each figure legend and, where appropriate, was determined by power analysis. Male and female mice were used for all experiments. Except the RNA-seq data, bar graphs represent means and error bars are standard error of the mean (SEM). For all experiments, mice were randomly chosen for experimental groups and the experimenter was masked to genotype and/or condition. Also, prior to injection, any animals with pre-existing abnormal eye phenotypes (e.g., displaced pupil, cataracts, abnormal size, missing eyes, etc.) were excluded from the study. For calculation of RBPMS+ and pJUN+ cells, pJUN+ cells and total RBPMS+ cells per image were assessed to determine both density of pJUN+ cells and percentage of RBPMS+ pJUN+ double positive RGCs. These data were then assessed for differences using a t-test. Quantification of cCASP3+ RBPMS+ double positive cells was done across all timepoints, separating out IL1A+TNF injected and PBS injected eyes per day, and assessed using a two-way ANOVA. For quantification of RGC density, RBPMS+ and TUJ1+ double positive cells were counted in all images per group and compared using a t-test for those passing the Shapiro Wilk normality test (IL1A+TNF versus PBS), or a Mann-Whitney non-parametric test for those failing the normality test as noted (TNF and IL1A versus PBS). These data were analyzed using GraphPad Prism 9 software. Following assessment, significance was noted using the following parameters: * = p < 0.05, ** = p < 0.01, *** = p < 0.001, **** = p < 0.0001. Roughly, equal numbers of male and female mice were used per experiment.
Murine RNA isolation and sequencing
Mouse eyes were harvested at 2 days following injection and retinas were freshly dissected in ice-cold PBS and frozen on dry ice and stored at −80°C prior to homogenization at the University of Rochester. Samples were shipped overnight to the Jackson Laboratory for RNA sequencing studies. Tissues were homogenized in MR1 buffer (Macherey-Nagel) using a Pellet Pestle Motor (Kimbal). Total RNA was isolated from tissue using the NucleoMag RNA Kit (Macherey-Nagel) and the KingFisher Flex purification system (ThermoFisher) as per the manufacturer’s protocol. An additional DNase treatment was done using the RNeasy Mini kit (Qiagen). RNA concentration and quality were assessed using the Nanodrop 8000 spectrophotometer (Thermo Scientific) and the RNA 6000 Nano Assay (Agilent Technologies). Libraries were constructed using the KAPA mRNA HyperPrep Kit (Roche Sequencing and Life Science), according to the manufacturer’s protocol. The quality and concentration of the libraries were assessed using the D5000 ScreenTape (Agilent Technologies) and Qubit dsDNA HS Assay (ThermoFisher), respectively, according to the manufacturers’ instructions. Libraries were sequenced 150 bp paired-end on an Illumina NovaSeq 6000 using the S4 Reagent Kit v1.5.
Murine RNA-seq data analysis
The resulting ∼40 M read pairs per sample were processed following standard quality control practices and high-quality read pairs were aligned to the mouse genome (mm10) using STAR 2.7.9a (Dobin et al., 2013; Wingett and Andrews, 2018). Read pair counts per gene were summed with the featureCounts function in subread 2.0.1 (Liao et al., 2013, 2014). Read counts were normalized using the trimmed mean of M values (TMM) method in edgeR 3.36.0 within the R environment 4.1.3 (Robinson et al., 2010; Robinson and Oshlack, 2010). Data was scaled using the limma v3.50.3 voom function and to control for repeated measures effects, the DuplicateCorrelation function was used to block on “mouse ID” (Ritchie et al., 2015). Linear models were utilized to identify differentially expressed genes fit by the predictors of the model: Sex and type of treatment (IL1, TNF, IL1+TNF, or PBS). For the RNA-seq data involving Sarm1 mice we also utilized the data generated for IL1, TNF, IL1+TNF treated eyes by incorporating a “batch” term into the linear model as written: Group (genotype and treatment combination) + Sex + Batch. Significant differentially expressed genes were determined by a cut-off of adjusted p-value < 0.05 and subjected to over representation analysis of KEGG pathways using the R package clusterProfiler v4.2.2 (Kanehisa and Goto, 2000; Yu et al., 2012). Significant differentially expressed genes with false-discovery rate (FDR) < 0.05 and corresponding log2 fold changes were used as input for ingenuity pathway analysis (IPA) upstream regulator analyses (QIAGEN Inc.) (Krämer et al., 2014). KEGG pathway maps were downloaded and colored by log2 fold change using the R package pathview v 1.34.0 (Luo and Brouwer, 2013). KEGG network graphs were generated using clusterProfiler v4.2.2 (Wu et al., 2021). Heatmaps were generated by using the average group log (counts per million mapped reads + 1) and scaling across each gene in which the scaled value = (original value-μ) / σ via pheatmap v1.0.12. Adjustments were made for multiple testing to control the FDR at 0.05 (Benjamini and Hochberg, 1995). Data will be made available through the Gene Expression Omnibus. A webtool is available for RNA-seq data exploration at: https://thejacksonlaboratory.shinyapps.io/IL1A_TNF/.
Results
IL1A+TNF in combination, but not alone, is sufficient to drive RGC death
Previous studies have shown that intravitreal injection of TNF drives approximately 15–20% loss of RGC (Kitaoka et al., 2006; Mac Nair et al., 2015; Ko et al., 2020), however, this death is only present 8–12 weeks following insult. Despite previous studies implicating IL1A in glaucomatous neurodegeneration, the in vivo role of IL1A in facilitating RGC death has not been assessed. To determine the direct neurotoxicity of IL1A on RGC viability, eyes of C57BL/6J mice were intravitreally injected with IL1A alone (0.1 μg/μL). While TNF (0.05 μg/μL) or IL1A injection alone did not cause significant RGC death 14 days post-injection (Ko et al., 2020), combined injection of IL1A+TNF did (Figures 1A−D). Twelve weeks after IL1A injection, there was no significant loss of RGCs compared to PBS-injected contralateral control eyes (Figure 1C). Twelve weeks was chosen as this is a timepoint where TNF insult had previously been reported to show RGC loss (Kitaoka et al., 2006; Mac Nair et al., 2015; Ko et al., 2020) and this confirmed in our study (Figure 1B). To determine if combined injection of IL1A+TNF resulted in increased RGC loss, ILA and TNF were injected together. Co-injection did not result in any increased cell death, compared to TNF injection alone 12 weeks post-injection (Figure 1D).
Figure 1. Intravitreal injection IL1A+TNF combined, but not alone, drives rapid RGC death. (A) Fourteen days after intravitreal application of IL1A or TNF alone, there was no loss of RGCs as judged by RBPMS+ RGCs. However, combined application of IL1A+TNF resulted in significant (P < 0.01) loss compared to PBS (control), IL1A, or TNF injection (PBS, n = 26, TNF, n = 9, IL1A, n = 7, IL1A+TNF, n = 10; **p < 0.01; ns, not significant). (B–D) The long-term effect of TNF, IL1A, and IL1A+TNF was investigated at 12 weeks post intravitreal injection. (B) At 12 weeks, TNF injection resulted in a significant loss of RBPMS+ RGCs compared to PBS-injected eyes (P < 0.001; n = 13 and 11, respectively). (C) In contrast, IL1A injection did not result in RGC loss compared to PBS injection (n = 8 for both conditions, P = 0.12). (D) However, the combined application of IL1A+TNF resulted in significant RGC loss compared to PBS (P < 0.0001; n = 10 for both conditions). (E) Cleaved caspase 3 (cCASP3) immunolabeling (red) was assessed in RGCs [colocalization with TUJ1+ cells (green)] at 1,3,5,7, and 10 days following IL1A+TNF or PBS application. cCASP3+TUJ1+ cell counts (per mm2) show a significant increase in cCASP3+TUJ1+ cells starting at around 3 days after injection and ending between 7 and 10 days (n ≥ 6 per group). Note: merged images in the bottom row indicate a zoomed-in section of the boxed area in the top row to highlight overlap. Box and whisker plots with min and max shown alongside all data points. Statistical information: (A) Kruskal Wallis Test with Dunn’s Multiple Comparisons Test, (B,C) Mann-Whitney U test, (D) Student’s t-test, (E) two-way ANOVA with Tukey’s Multiple Comparisons Test; NS, not significant; **p < 0.01, ***p < 0.001, ****p < 0.0001; error bars, SEM; scale bar = 50 μm.
To define the time window when RGCs die following IL1A+TNF injury, IL1A+TNF were injected into retinas, which were assessed for cleaved caspase 3 (cCASP3; a marker of dying cells). At 1,3,5,7, and 10 days. TUJ1+ cCASP3+ cells were present in the IL1A+TNF, but not PBS-injected eyes starting at 3 days and peaking between 5- and 7-days post-injection (TUJ1 labels RGCs in the ganglion cell layer; Figure 1E). These data show that IL1A or TNF alone are not capable of driving death at early timepoints, but together can mediate rapid RGC death.
IL1A+TNF facilitates increased neuroimmune transcriptional signatures and activation of cell-death pathways
The molecular pathways leading from TNF or IL1A+TNF insult to RGC death are unknown. It is possible these cytokines act directly on RGCs as receptors for both molecules are expressed on RGCs. It is also possible that the effect of these molecules is extrinsic to RGCs, perhaps through astrocytes, as suggested by the work of Liddelow et al. (2017), Guttenplan et al. (2020), and Guttenplan et al. (2021). To understand how IL1A and/or TNF drive RGC death, RNA-sequencing was performed on whole retinas isolated 2 days post intravitreal injection, the timepoint when RGC loss was first observed after IL1A+TNF injection. RNA-seq was performed on retinas injected with IL1A, TNF, or IL1A+TNF and contralateral control eyes injected with PBS. The results indicate that while IL1A or TNF alone induced significant transcriptional changes, the largest changes were observed in the IL1A+TNF group (Figures 2A−D). Overrepresentation analyses revealed key pathways affected in the combined treatment group included apoptosis, necroptosis, TNF signaling, Toll-receptor signaling, and NOD-like signaling (Figures 2E−G). Thus, the RNA-seq data revealed potential pathways important in cell signaling pathways intrinsic to RGCs and RGC extrinsic inflammatory and/or glial activation pathways. Note, when investigating the effects of TNF alone at 2, 14, and 35 days post-injection, few transcriptional changes were seen at 2 days compared to PBS controls and no significant changes at 14 or 35 days (Figure 2A, not shown).
Figure 2. IL1A+TNF injection alters neuroinflammatory and cell death-associated transcriptional signatures. (A) Bar chart summarizing the number of differentially expressed genes (DEGs) between the following groups from left to right: IL1A+TNF vs. PBS, IL1A vs. PBS, and TNF vs. PBS. Red bars represent DEGs with an FDR < 0.05, and dark blue bars are DEGs with an FDR < 0.01. (B–D) Volcano plots of differential expression between (B) TNF vs. PBS, (C) IL1A vs. PBS, and (D) IL1A+TNF vs. PBS. Genes with FDR < 0.05 are colored red. Top 10 genes by FDR are labeled. (E–G) Enrichment plots of enriched KEGG gene sets between: (E) TNF vs. PBS, (F) IL1A vs. PBS, and (G) IL1A+TNF vs. PBS. Lines between nodes reflect shared genes. Node size represents the number of DEGs in the gene set. The color is an illustration of the adjusted p-value for each gene set. Number of retinas per group: 31 PBS (15 female, 16 male), 8 TNF (4 female, 4 male), 9 IL1A (4 female, 5 male), and 10 IL1A+TNF (6 female, 4 male).
The transcriptional states of microglia and astrocytes have been suggested to be important for RGC loss in various disease models, particularly in association with neurotoxic cytokines (Liddelow et al., 2017; Guttenplan et al., 2020; Guttenplan et al., 2021). Genes associated with “A1” and “A2” astrocytes (Zhang et al., 2014; Liddelow et al., 2017; Figure 3A) were examined as well as several genes relevant to previously defined microglial disease-relevant states (Yang et al., 2021; Figure 3B). IL1A alone, but not TNF, resulted in a broad increase in astrocyte activation markers, while IL1A+TNF together was sufficient to facilitate increased expression in pan reactive, “A1,” and “A2” astrocyte markers. IL1A+TNF also led to an upregulation of gene signatures for interferon-responding microglia (IRM) and disease-associated microglia (DAM), further supporting their capability in driving glial activation 2 days post-injection.
Figure 3. IL1A+TNF induces transcripts associated with glial activation. Heatmaps of curated genes associated with astrocytes (A) and microglia (B). Average expression for the entire group is shown. Scaled and centered expression of the library-size and log normalized average expression value for each gene in each treatment group. * Denotes FDR < 0.05 for the selected gene in the treatment group when compared to the PBS group; numbers retinas per group: 31 PBS (15 female, 16 male), 8 TNF (4 female, 4 male), 9 IL1A (4 female, 5 male), and 10 IL1A+TNF (6 female, 4 male).
IL1A+TNF induced RGC death pathways
We were particularly interested in understanding molecular pathways following cytokine insults. Overrepresentation analysis showed the apoptosis pathway was significantly overrepresented in differentially expressed genes comparing IL1A+TNF with PBS retinas at 2 days after injection (Figure 4A). Previous work has shown that transcription factors can be critical mediators of RGC death after glaucoma-relevant injury (Fernandes et al., 2012; Fernandes et al., 2013; Syc-Mazurek et al., 2017a; Syc-Mazurek et al., 2017b; Syc-Mazurek et al., 2022). To identify putative master regulators of transcriptional changes identified in the IL1A+TNF group, we utilized the Upstream Regulator Analysis tool in Ingenuity Pathway Analysis (IPA). Upstream regulator analysis suggested the activation of several transcriptional regulators, including JUN (Figure 4B).
Figure 4. IL1A+TNF co-treatment induces cell-death and activation of JUN transcriptional signatures. (A) KEGG graph of the significantly enriched Apoptosis pathway within the DEGs comparing IL1A+TNF vs. PBS and is colored by the logFoldChange value for the expression of highlighted genes within the pathway comparing IL1A+ vs. PBS. (B) IPA upstream regulator analysis generated a mechanistic network for JUN using a strict cut-off for input DEGs identified between IL1A+TNF vs. PBS with FDR < 0.01 and LogFC > 0.5. Orange and blue indicate predicted activation and inhibition, respectively. Solid and dashed lines, respectively, indicate direct and indirect interactions. The yellow line suggests inconsistent with the state of downstream molecules. Gray indicates no effect predicted. Number of retinas used per group: 31, PBS (15 female, 16 male), 8 TNF (4 female, 4 male), 9 IL1A (4 female, 5 male), and 10 IL1A+TNF (6 female, 4 male).
While our bulk RNA-seq analyses are unable to distinguish cell-type specific alterations, it is well known that JUN is an important transcription factor involved in injury response in RGCs. Furthermore, JUN is important for RGC death after several glaucoma-relevant injuries, including OHT and ONC (Fernandes et al., 2012; Fernandes et al., 2013; Syc-Mazurek et al., 2017a,b). Given the enrichment of JUN in the upstream regulator analysis and its known importance in RGC death, we assessed whether JUN is activated (phosphorylated; pJUN) downstream of intravitreal IL1A+TNF insult in RGCs. Three days after IL1A+TNF injection, before peak RGC degeneration, pJUN was present in RBPMS+ cells, and absent in PBS injected eyes (Figure 5A). Thus, JUN is activated in RGCs after IL1A+TNF insult. To determine if JUN is required for RGC death, mice deficient in Jun in all retinal neurons (including RGCs) and retinal macroglia (astrocytes and Müller glia) were generated using floxed alleles of Jun (Behrens et al., 2002) (Junfl) recombined with Six3-cre (Furuta et al., 2000; Rattner et al., 2013; Rattner et al., 2019). Six3-cre+Junfl/fl and control mice (e.g., Six3-cre+Junfl/fl or Six3-cre–Junfl/+) were intravitreally injected with either IL1A+TNF or PBS. Contrary to the protective effects of the loss of Jun seen in other glaucoma-relevant injuries (Fernandes et al., 2013; Syc-Mazurek et al., 2017a,b; Marola et al., 2020), Six3-cre+Junfl/fl animals showed no protection to RGCs from IL1A+TNF insult (Figure 5B). These findings suggest that while JUN is activated after IL1A+TNF injury, RGC death is independent of Jun activation.
Figure 5. While JUN is activated following IL1A+TNF, Jun expression in RGCs and macroglia is not required for IL1A+TNF mediated degeneration. (A) Three days post IL1A+TNF injection, phosphorylated c-Jun (pJUN) is expressed in significantly more RBPMS+ RGCs compared than in control eyes injected with PBS (given as pJUN+ RGCs per mm2; PBS median, 5.0; IL1A+TNF median; 250.8; *p = 0.028, n = 4 per condition, Mann Whitney U test). This equates to approximately 8% of RGCs after IL1A+TNF injection and 0.2% of RGCs after PBS injection (*p = 0.028, n = 4 per condition, Mann Whitney U test). (B) Following IL1A+TNF injection, animals with Jun deleted in RGCs and macroglia had a loss of RGCs compared to PBS control eyes. (RBPMS+ RGCs per mm2± SEM: Control PBS, 3,782 ± 120; Control IL1A+TNF, 2,754, ± 159; Jun−/− PBS, 3,478 ± 141; Jun−/− IL1A+TNF, 2,739 ± 271.N ≥ 9 per group. Two-way ANOVA with Tukey’s Multiple Comparisons test, **p < 0.01, *p < 0.05).
In the CNS, previous studies identified SARM1 (sterile alpha and TIR motif containing protein 1) as a key regulator in axonal degeneration (Gerdts et al., 2015; Geisler et al., 2016; Gerdts et al., 2016; Fernandes et al., 2018). While deficiency of Sarm1 led to reduced axonal degeneration after glaucoma-relevant injury, it failed to protect RGCs somas from apoptosis and death (Fernandes et al., 2018). However, SARM1 has recently been linked to neuronal survival after TNF insult, with loss of Sarm1 conferring near complete protection to RGC somas following TNF injection (Ko et al., 2020). Therefore, to assess the potential role of SARM1 following the combined application of IL1A+TNF, eyes from Sarm1–/– and WT mice were injected IL1A+TNF and RGC density was quantified 14 days after injury. In line with the RGC protection seen in Sarm1–/– animals injected with TNF (Ko et al., 2020), we found that Sarm1 deficiency prevented the early IL1A+TNF-induced death (Figure 6).
Figure 6. Loss of Sarm1 expression was sufficient to prevent IL1A+TNF induced death. Sarm1 deficient animals no RGCs loss 14 days after IL1A+TNF injection compared to PBS injected eyes (n = 6 per group; p > 0.05). In contrast, wild-type animals injected had significant RGC loss 14 days after IL1A+TNF, but not in PBS controls (n = 10 PBS, 9 IL1A+TNF; p < 0.0001, ****). Two-way ANOVA with Tukey’s Multiple Comparisons test was used for all comparisons; scale bar = 50 μm. Box and whisker plots of RBPMS+ RGCs per mm2 with min and max shown.
Loss of Sarm1 does not prevent IL1A+TNF-induced glial activation transcriptional signatures
To gain insight into the molecular mechanism of SARM1 in RGC death after IL1A+TNF insult RNA-Seq was performed on WT IL1A+TNF, WT PBS, Sarm1–/– IL1A+TNF, and Sarm1–/– PBS retinas 2 days after injections. We included samples from Figure 2 in this analysis to allow us to compare to TNF and IL1A sole treatments by including a batch term in the model. Sarm1 deficiency without insult only resulted in 8 genes being differentially expressed in uninjured eyes: Sarm1, Slc46a1, Dynlt1b, Fam57a, Vsp53, Tlcd2, ENSMUSG00000079733, and the pseudogene Tmem181b.ps (Figures 7A,B). There was differential expression of genes associated with synaptic changes, calcium signaling, MAPK signaling, and glial responses between Sarm1 deficient and control retinas (Figures 7C−H) after IL1A+TNF insult. Yet, Sarm1 deficient animals had similar levels of astrocyte activation (Figure 8A) and microglial response (Figure 8B) 2 days after IL1A+TNF insult. While the apoptosis pathway was still enriched and Jun was also predicted upstream regulator in IL1A+TNF treated Sarm1–/– eyes (Figures 7D, 9). Therefore, while Sarm1 deficiency can prevent early IL1A+TNF induced RGC loss, it is not necessary for IL1A+TNF mediated Jun and glial activation.
Figure 7. Sarm1 deficiency significantly alters synapse-associated transcripts after IL1A+TNF insult. (A) Bar chart summarizing the number of differentially expressed genes (DEGs) between the following groups from left to right: IL1A+TNF vs. PBS in WT eyes, IL1A+TNF vs. PBS in Sarm1–/– eyes, Sarm1–/– retinas vs. WT retinas, IL1A+TNF treated Sarm1–/– vs. IL1A+TNF WT eyes, and the Genotype by Treatment interaction effect. Red bars represent DEGs with an FDR < 0.05 and dark blue bars are DEGs with an FDR < 0.01. (B,C,E,G) Volcano plots of differential expression between (B) Sarm1–/– retinas vs. WT retinas, (C) IL1A+TNF vs. PBS treatment in Sarm1–/– retinas, (E) IL1A+TNF treated Sarm1–/– vs. IL1A+TNF treated WT eyes, and (G) Genotype by Treatment, genes with FDR < 0.05 are colored red and top 10 genes by FDR are labeled. (D,F,H) Enrichment plots of enriched KEGG gene sets between: (D) IL1A+TNF vs. PBS treatment in Sarm1–/– retinas, (F) IL1A+TNF treated Sarm1–/– vs. IL1A+TNF treated WT eyes, and (H) Genotype by Treatment. Lines between nodes reflect shared genes and node size represents the number of DEGs in the gene set. The color is an illustration of the adjusted p-value for each gene set. Retinas used by treatment: PBS, 36 WT (17 female, 19 male) and 6 Sarm1–/– (3 female, 3 male); IL1A+TNF, 16 WT (9 female, 7 male) and 6 Sarm1–/– eyes (3 female, 3 male).
Figure 8. Sarm1 deficiency does not reduce glial activation driven by IL1A+TNF. Heatmaps of curated genes associated with astrocytes (A) and microglia (B). Average expression for the entire group is shown. Scaled and centered expression of the library-size and log normalized average expression value for each gene in each treatment group is shown. * Denotes FDR < 0.05 for the selected gene in the treatment group when compared to the PBS in WT eyes or PBS in Sarm1–/– eyes. Retinas used by treatment: PBS, 36 WT (17 female, 19 male) and 6 Sarm1–/– (3 female, 3 male); IL1A+TNF, 16 WT (9 female, 7 male) and 6 Sarm1–/– eyes (3 female, 3 male).
Figure 9. Sarm1 deficiency does not reduce IL1A+TNF induced activation of JUN transcriptional signatures. (A) KEGG graph of the significantly enriched Apoptosis pathway within the DEGs comparing IL1A+TNF vs. PBS in Sarm1–/– retinas and is colored by the logFoldChange value for the expression of highlighted genes within the pathway comparing IL1A+ vs. PBS in Sarm1–/– retinas. (B) IPA upstream regulator analysis generated a mechanistic network for JUN using a strict cut-off for input DEGs identified between IL1A+TNF vs. PBS in Sarm1–/– retinas with FDR < 0.01 and LogFC > 0.5. Orange and blue indicate predicted activation and inhibition, respectively. Solid and dashed lines, respectively, indicate direct and indirect interactions. The yellow line suggests inconsistent with the state of downstream molecules. Gray indicates no effect predicted. Number of retinas used per group: 6 PBS treated Sarm1–/– (3 female, 3 male), and 6 IL1A+TNF treated Sarm1–/– (3 female, 3 male).
Discussion
Neuroinflammation has been extensively linked to RGC cell death and glaucomatous neurodegeneration (Howell et al., 2011; Howell et al., 2014; Soto and Howell, 2014; Harder et al., 2017; Williams et al., 2019). Recent studies have shown that combined deficiency of the neuroinflammatory-related molecules Tnf, C1q, and Il1a prevented RGC death after ONC (Liddelow et al., 2017; Guttenplan et al., 2020) and lessened RGC death after an OHT injury (Sterling et al., 2020). While TNF and C1Q have been studied extensively in glaucoma-relevant pathogenesis, IL1A has not been assessed for its neurotoxic capabilities to RGCs in vivo.
Intravitreal injection of TNF results in approximately 15–20% loss of RGCs, however, the loss of RGCs appears only around 8–12 weeks following injection (Kitaoka et al., 2006; Mac Nair et al., 2015; Ko et al., 2020). IL1A has been assessed for its ability to drive neuroinflammation in the brain (Shaftel et al., 2008; Spulber et al., 2009), but to our knowledge, its effect on the retina in vivo has never been tested. To determine the direct neurotoxicity of IL1A and the combinatorial effects of IL1A+TNF, the eyes of B6 mice were intravitreally injected with IL1A alone, TNF alone, or IL1A+TNF. Consistent with previous studies (Nakazawa et al., 2006; Mac Nair et al., 2015), TNF injection failed to kill RGCs by 14 days following insult but did result in RGC loss 12 weeks post-injection. In addition, IL1A alone did not result in any loss of RGCs at any time point assessed out to 12 weeks (the latest time point examined). However, in eyes receiving a combined injection of IL1A+ TNF, there was a significant decrease in RGC density at 14 days (∼20%) compared to control eyes, with RGCs dying mainly between 3 and 7 days. Interestingly, at 12 weeks, the amount of death remained ∼20%, suggesting IL1A acted as a sensitizer for TNF-induced RGC death, accelerating RGC death, but did not drive RGC death on its own.
The molecular pathways leading from TNF or IL1A+TNF insult to RGC death is unknown. These cytokines could act directly on RGCs as their receptors are expressed on RGCs. As Liddelow et al. (2017), Guttenplan et al. (2020), and Guttenplan et al. (2021) have suggested, it is possible that TNF and IL1A act on astrocytes, which in turn release a neurotoxic substance. To gain insight into this question, RNA-seq on whole retinas was performed 2 days following either TNF, IL1A, or IL1A+TNF insult. This time point was chosen to identify primary changes after cytokine insult. Only around 50 genes had significant changes in their expression after TNF insult alone. Also, surprisingly, TNF injection did not result in any significant gene expression changes at either 14 or 35 days. Thus, these experiments did not shed any insight on why TNF induces a delayed RGC death. In contrast to TNF, intravitreal injection of either IL1A alone or IL1A+TNF led to significant transcriptional changes relative to PBS controls (2,000+ and 8,000+ genes, respectively). Pathway analysis revealed several interesting pathways to be upregulated, suggesting possible mechanisms for IL1A+TNF-induced RGC death. These included both apoptosis and necroptosis, as well as TNF, NOD-like, and Toll-like receptor signaling pathways. These findings demonstrated the early capability of these cytokines to drive both RGC death and immune-related signaling changes by 2 days.
We were particularly interested in whether glial activation occurred prior to or coincidently with RGC death after IL1A and IL1A+TNF injections. In OHT models of glaucoma, glial activation occurs before RGC loss (Howell et al., 2011; Howell et al., 2012). After mechanical axon injury to RGCs, our group showed using RNA-seq data that proinflammatory signaling and glial activation in the retina might be secondary to activation of pro-death pathways in RGCs after acute axonal injury (Syc-Mazurek et al., 2022). However, Liddelow and colleagues have shown that cytokine signaling kills RGCs, assumed to be acting through astrocytes (Liddelow et al., 2017; Guttenplan et al., 2021). Our RNA-seq data here showed that marker genes for astrocyte and microglial responses were upregulated. For microglia, expression changes showed clear upregulation of both IRM and DAM microglial responses. There were also significant changes in genes that are important in astrocyte activation. Upregulation of genes thought important in astrocytic states associated with pathology were present, including genes marking A1, A2, and pan reactive astrocytes. Interestingly, unlike previous in vitro findings (Liddelow et al., 2017), IL1A+TNF insult appeared to mediate not just A1, but also A2 signatures, suggesting that in vivo these cytokines do not act solely in an A1-mediated neurotoxic manner. However, because we performed bulk RNA-seq, we do not know if these marker genes were upregulated in distinct cell (sub) populations. Together, these data show that both microglia and astrocytes are activated at the onset of RGC injury and are consistent with an important role for glia in IL1A+TNF-induced RGC death.
Along with the role of neuroinflammatory signaling in IL1A+TNF-induced RGC death, we were also interested in understanding cell signaling pathways within RGCs that lead to RGC death after IL1A+TNF insult. The RNA-seq analysis showed that cell death pathways, including apoptosis and necroptosis, were overrepresented. It was particularly interesting that upstream regulator analysis of the differentially regulated transcripts identified the transcription factor JUN. JUN is important in RGC death after axonal injury and in ocular hypertensive eyes (Fernandes et al., 2012; Fernandes et al., 2013; Syc-Mazurek et al., 2017a,b; Syc-Mazurek et al., 2022).
To determine the downstream signaling events following IL1A+TNF insult before RGC death, we assessed animals injected with IL1A+TNF at 3 days for phosphorylated-c-jun (pJUN), a known transcription factor involved in RGC death following a variety of insults. At this time point, JUN is significantly elevated in IL1A+TNF injected retinas compared to PBS controls, with approximately 8–10% of RGCs expressing pJUN (Figure 6A). These findings indicated that JUN signaling is occurring downstream of IL1A+TNF insult. However, to assess whether Jun is required for RGC death after this insult, we recombined Junfl alleles using Six3-cre to target RGCs and macroglia. Interestingly, loss of Jun in Six3-cre+ Junfl animals failed to prevent RGC death after IL1A+TNF injection (Figure 5). These findings contrast with other glaucoma relevant insults showing protection to RGCs following loss of Jun (Syc-Mazurek et al., 2017a,b), suggesting a Jun independent mechanism of RGC death following extrinsic application of IL1A+TNF. The RNA-seq pathway analysis also identified necroptosis as a potential cell death pathway acutely activated following IL1A+TNF. SARM1 is involved in necroptosis (Summers et al., 2014; Ko et al., 2020). Furthermore, SARM1 has recently been linked to neuronal survival after TNF insult, and, importantly, SARM1 is known to be involved in axonal and degeneration after axonal insult (Gerdts et al., 2015; Geisler et al., 2016; Gerdts et al., 2016; Fernandes et al., 2018), a key component of glaucomatous neurodegeneration. Ko and colleagues recently also found that Sarm1–/– mice showed no RGC somal or axonal loss following TNF injection (Ko et al., 2020), suggesting SARM1 may play a key role in RGC somal death after a neurotoxic insult. Not surprisingly, Sarm1–/– mice showed no loss of RGCs following IL1A+TNF (Figure 7), supporting the role of SARM1 in the soma after neurotoxic cytokine insult. Interestingly, SARM1, while typically described as a modulator of NAD+ metabolism and axon integrity, is also known as Myd88-5, which is a bottleneck molecule downstream in IL1A signaling (Wang et al., 2018). Our findings would also support SARM1’s role in initiating downstream mechanisms following exposure to IL1A+TNF. It will be important to determine if SARM1 continues to protect RGCs at later time points.
RNA-seq analysis was performed on Sarm1 deficient mice 2 days following IL1A+TNF insult. This analysis was done to gain insight into where in the cell signaling process SARM1 was acting. When assessing the differences in gene expression IL1A+TNF treated eyes across genotypes, most of the differentially expressed genes fell under synaptic signaling pathways, with the largest genotype effect seen in Sarm1 expression itself (Figures 7C−H). These data underscore that RGC death in control eyes treated with IL1A+TNF starts at 3 days post-injury, and changes to synaptic structure likely occur before overt neuronal loss and is seemingly modulated by SARM1 deficiency. In line with this, and in contrast to WT-treated eyes, SARM1-deficient eyes displayed an increased expression of Nrf1, previously implicated in the survival of developing RGCs and regulates mitochondrial function (Kiyama et al., 2018).
When comparing astrocyte activation markers, there appears to be a subtle but significant reduction in A1, but not A2 transcripts, in Sarm1–/– treated eyes (Figure 8A). When assessing changes in microglial-associated transcripts, we saw similar levels of IRM and DAM transcript upregulation in both WT and Sarm1–/– eyes after IL1A+TNF (Figure 8B). These results indicate that there are unique transcriptional differences (∼2,000 genes) following IL1A+TNF when cell death is prevented via loss of Sarm1, relative to WT eyes, but the majority of IL1A+TNF associated changes still occur ( > 8,000 genes), (Figure 7C). In fact, the apoptosis pathway was still enriched and JUN was also still a predicted upstream regulator (Figure 9) in IL1A+TNF treated Sarm1 deficient eyes. As we utilized bulk RNA-sequencing for this first study we are unable to discern if these changes are occurring within RGCs specifically or in other cell-types such as astrocytes or microglia. Future work is required to delineate the cell-type specific changes in response to IL1A+TNF insult by approaches such as spatial transcriptomics and/or single cell RNA-sequencing.
Overall, these findings demonstrated the direct neurotoxic role of IL1A+TNF to retinal ganglion cells in vivo. We determined that RGC loss after IL1A+TNF is present by 14 days, and that the loss is JUN-independent and SARM1 dependent. This is an intriguing result. As discussed above, JUN has been shown to be critical for axonal or ocular hypertensive-induced somal loss. Also, ocular hypertension-induced RGC death has been shown to involve SARM1 (Zeng et al., 2024; Zhang et al., 2024) and IL1A, TNF, and C1Q Thus, more work is needed in order to understand who these results integrate into our understanding of glaucomatous neurodegeneration. For instance, the precise molecular signaling cascade(s) within RGCs that is critical for RGC death after a glaucomatous insult needs to be defined.
Data availability statement
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE318351, accession GSE318351.
Ethics statement
The animal study was approved by University of Rochester’s University Committee on Animal Resources. The study was conducted in accordance with the local legislation and institutional requirements.
Author contributions
KA: Writing – original draft, Writing – review & editing. MM: Writing – original draft, Writing – review & editing. GH: Writing – original draft, Writing – review & editing. RL: Writing – original draft, Writing – review & editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the BrightFocus Foundation (RL), National Eye Institute EY027701 (RL, GH), EY035093 (RL, GH), EY018606 (RL), an unrestricted grant from the Research to Prevent Blindness to the Department of Ophthalmology at the University of Rochester. KA was also supported by the Center for Visual Science Training Grant T32-EY007125 (KA) and the Neuroscience Graduate Program at the University of Rochester. GH was also extremely grateful for the support of the Diana Davis Spencer Foundation. The funding agencies had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.
Acknowledgments
We gratefully acknowledge the contribution of the Genome Technologies Scientific Service at The Jackson Laboratory for expert assistance with the work described in this publication.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
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Keywords: glaucoma, interleukin 1, neuroinflammation, opticneuropathy, proinflammatory cytokines
Citation: Andersh KM, MacLean M, Howell GR and Libby RT (2026) IL1A enhances TNF-induced retinal ganglion cell death. Front. Aging Neurosci. 18:1754881. doi: 10.3389/fnagi.2026.1754881
Received: 26 November 2025; Revised: 14 January 2026; Accepted: 20 January 2026;
Published: 05 February 2026.
Edited by:
Paul T. Massa, Upstate Medical University, United StatesReviewed by:
Chen Ding, Boston Children’s Hospital and Harvard Medical School, United StatesColleen McDowell, University of Wisconsin-Madison, United States
Copyright © 2026 Andersh, MacLean, Howell and Libby. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Gareth R. Howell, Z2FyZXRoLmhvd2VsbEBqYXgub3Jn; Richard T. Libby, cmljaGFyZF9saWJieUB1cm1jLnJvY2hlc3Rlci5lZHU=
†These authors have contributed equally to this work