Autophagy regulates Müller glial cell inflammatory activation
Purpose. Immune privilege in the eye is a compilation of anti-inflammatory mechanisms that protect vision from the damaging sequelae of intense immune responses.  Although the breakdown of privilege can lead to ocular disease, little is known about how these mechanisms are regulated. Since retinal Müller glial cells and autophagy also have anti-inflammatory properties, we tested the idea that Müller cells utilize autophagy to support immune privilege.  Methods. The essential autophagy regulator Atg5 was deleted in retinal Muller cells using a tamoxifen inducible GlastCre ERT X Atg5f/f strain.  Intraocular inflammation was induced by intravitreal injection of LPS and monitored by H&E staining, immunofluorescent confocal microscopy, and flow cytometry.  scRNA-seq was performed on retinal Müller cells isolated from control and Atg5-deficient mice.  Additionally, markers of Müller cell gliosis and function were assessed by western blotting and cytokines were detected by Luminex cytokine/chemokine arrays. In cultured Müller cells siRNA knockdown techniques were used to examine the role of autophagy in regulation of LPS-induced inflammatory pathways.  Results. We observed increased and prolonged intraocular inflammation when Müller cells were autophagy (Atg5) deficient.  Müller cell gliosis (as measured by Gfap expression) was significantly increased and inflammation was sustained over 5 days post-LPS injection compared to control.  The retinae with Atg5-deficient Müller cells also contained increased inflammatory mediators and neuroprotective molecules.  Gene expression analysis revealed a heterogeneous response to LPS in Müller glial cell population that revealed 2 states of activation.  The normal retinae contain Müller cells in both a basal and an activated state, while autophagy deficient retinae (Atg5i?Müller) contained only activated Müller cells.  Analysis of gliosis markers Gfap and Lcn2 confirmed this heterogeneity showing that in control eyes basal and activated (gliotic) Müller glia were observed; however, with autophagy deficiency nearly all Müller cells were gliotic.  Interestingly, activated cells were largely indistinguishable between autophagy sufficient and deficient Müller cells. In cultured Müller cells, siRNA knockdown of autophagy genes resulted in heightened mTOR activation, increased Gfap expression, and upregulated cytokine/chemokine production.  Conclusions.  Autophagy deficiency in Müller cells leads to enhanced intraocular inflammation though activation of the mTOR pathway. Our data suggests that autophagy defines a novel perspective on Müller glial heterogeneity based on their activation state.  Thus, autophagy restrains cellular activation and inflammation, supporting immune privilege by preventing excessive and potentially destructive immune responses. Overall design: Single cell suspensions were generated from pooled isolated retinas for each group (n=6) with a Papain Dissociation kit using the protocol provided. The final cell pellet was resuspended in PBS (pH7.4) with 0.1% BSA and cell viability assessed using Trypan blue staining. Only samples with >85% viability were used. Single-cell RNA sequencing (scRNA-seq) was performed using the 10X Genomics platform and reagents (3'v3.1) according to the manufacturer's instructions. Resulting libraries were sequenced on an Illumina NovaSeq 6000 at the McDonnell Genome Institute at Washington University School of Medicine. Raw fastq files were processed and mapped to the mouse genome (mm10) using CellRanger (v6.0.0). Further analysis was performed using Seurat (v5.2.1) in R. The full code for this analysis is available at https://github.com/p-ruzycki/Atg5KO_LPS. Briefly, raw count matrices from Atg5f/f and Atg5i?Muller samples were imported and merged for comparative analysis. Quality control was performed by filtering out cells with mitochondrial content =25% and cells with fewer than 500 detected genes. Normalization and variance stabilization were conducted using the LogNormalize method in Seurat, and the top 2,000 most variable genes were identified. The dataset was then scaled, and dimensionality reduction was performed using Principal Component Analysis (PCA), retaining the first 11 principal components (PCs) based on an elbow plot. Clustering was performed at multiple resolutions, and a resolution of 1.0 was selected for downstream analysis. Cell types were identified based on FindMarkers results and known marker gene expression, and visualization was conducted using Uniform Manifold Approximation and Projection (UMAP) in Seurat. A subset of non-neuronal cell populations (including Müller glia, myeloid cells, and vascular endothelial cells) was re-clustered and filtered for residual contaminating retinal neurons using Seurat preprocessing steps and reannotated based on FindMarkers results and known marker genes. Further sub setting was performed to isolate Müller glia cells, and these were re-clustered to examine subpopulation structures. Two differential expression analyses (DEA) were performed using Seurat: (1) comparison between Atg5f/f and Atg5i?Muller in Müller glia (Cluster 1) using the FindMarkers function, where genes with adjusted p-value (p_adj) < 0.05 and log2 fold change (log2FC) = ±1.0 were considered significantly differentially expressed, and (2) comparison between Müller glia subpopulations, where Cluster 2 was compared to Cluster 1 using the same statistical criteria. Volcano plots were generated using ggplot2 (v3.5.1) and ggrepel (v0.9.6) to visualize differentially expressed genes, highlighting selected genes with distinct colors and labeling them using geom_text_repel, with threshold lines indicating statistical significance. Pathway enrichment analysis was conducted using Gene Set Enrichment Analysis (GSEA, v4.3.3), where pathways were considered significantly enriched if they had a normalized enrichment score (NES) =2 (upregulated) or =-2 (downregulated) with an FDR q-value =0.05. Enrichment results were visualized using dot plots, and gene sets were obtained from MSigDB (Molecular Signatures Database).