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Published in final edited form as: Glia. 2024 Mar 18;72(6):1067–1081. doi: 10.1002/glia.24514

ER-stress response in retinal Müller glia occurs significantly earlier than amyloid pathology in the Alzheimer’s mouse brain and retina

Sarah I Palko 1,#, Marc R Benoit 1,#, Annie Y Yao 1, Royce Mohan 1, Riqiang Yan 1,*
PMCID: PMC11006574  NIHMSID: NIHMS1971897  PMID: 38497356

Abstract

Alzheimer’s Disease (AD) pathogenesis is thought to begin up to 20 years before cognitive symptoms appear, suggesting the need for more sensitive diagnostic biomarkers of AD. In this report, we demonstrated pathological changes in retinal Müller glia significantly earlier than amyloid pathology in AD mouse models. By utilizing the knock-in NLGF mouse model, we surprisingly discovered an increase in reticulon 3 (RTN3) protein levels in the NLGF retina as early as postnatal day 30 (P30). Despite RTN3 being a canonically neuronal protein, this increase was noted in the retinal Müller glia, confirmed by immunohistochemical characterization. Further unbiased transcriptomic assays of the P30 NLGF retina revealed that retinal Müller glia were the most sensitive responding cells in this mouse retina, compared to other cell types including photoreceptor cells and ganglion neurons. Pathway analyses of differentially expressed genes in glia cells showed activation of ER stress response via the upregulation of unfolded protein response (UPR) proteins such as ATF4 and CHOP. Early elevation of RTN3 in response to challenges by toxic Aβ likely facilitated UPR. Altogether, these findings suggest that Müller glia act as a sentinel for AD pathology in the retina and should aid for both intervention and diagnosis.

Keywords: Alzheimer’s retina, Müller glia, RTN3, ER stress response, unfolded protein response, transcriptomic

Graphical Abstract

graphic file with name nihms-1971897-f0001.jpg

Retinal Muller glial response of NLGF mice at P30, a time point prior to plaque formation and cognitive impairment. Soluble amyloid beta (green), produced by RGCs (yellow) and other retinal neurons, is secreted into the extracellular space where it is detected and taken up by Mϋller glia (red). In response to amyloid beta, Mϋller glia activate the EIF2 pathway and increase transcription and translation of Atf4, Atf5, and Ddit3 (CHOP) (green arrows). RTN3 is in turn accumulated at the protein level in response to activation of this pathway. Increase in ATF and CHOP pathways lead to mitochondrial dysfunction and apoptotic signaling43, which can influence neighboring cells eventually leading to apoptosis of retinal neurons as seen in advanced stages of Alzheimer’s disease.

Introduction

Alzheimer’s disease (AD) is the leading cause of dementia and the most common neurodegenerative disease (Corriveau et al., 2017; McDade et al., 2021). The two main characteristics of the disease, amyloid beta (Aβ) plaques and neurofibrillary tangles, are thought to contribute to the eventual neurodegeneration seen in AD patients (Wilson et al., 2023; Young-Pearse et al., 2023). It has been shown that AD pathogenesis occurs up to 20 years before any cognitive symptoms become apparent in patients (Hampel et al., 2021; Jack et al., 2018; Rahman and Lendel, 2021), meaning that the ideal intervention for AD treatment is during this undiagnosed period of disease progression. Since 2003, one new disease-modifying drug Lecanemab has recently been approved for treatment of AD (van Dyck et al., 2023), highlighting the dire need for more earlier and effective intervention toward reducing amyloid pathology. Cognitive tests, brain PET scans, and various biomarkers such as Aβ levels are currently aiding in earlier diagnosis of AD (Elmaleh et al., 2019; Márquez and Yassa, 2019; West et al., 2021; Zetterberg and Blennow, 2021). However, the development for additional non- or minimal-invasive earlier detection methods for AD diagnosis are continuingly being explored. Considering the extensive investigations in Alzheimer’s brains, pathological changes occurred in the Alzheimer’s retinas remain scarce.

The retina is a direct extension of the central nervous system, meaning that pathological processes of neurodegeneration are likely conserved, and may pose as an indicator of disease progression in the brain (Byerly and Blackshaw, 2009). Not only does the retina offer a mirrored view of brain pathology, but it is also easily imaged and accessed using current ophthalmic technologies like fundoscopic imaging and optical coherence tomography (OCT). These imaging techniques offer a higher resolution than conventional brain imaging techniques, and are less expensive (De Groef and Cordeiro, 2018). Encouragingly, detecting minute changes in the human AD retina via these imaging techniques are being explored, including the finding of decreased vascular density (Cheung et al., 2015; Querques et al., 2019), increased Aβ burden (Koronyo et al., 2017), and retinal ganglion cell layer thinning (Lu et al., 2010; Moschos et al., 2012), associated with pathological consequences of AD in the retina. One important knowledge gap is whether and how pathological changes in the AD retina would differ from distinct pathologies seen in the brain.

To explore this, we investigated molecular changes in the retina using established mouse models, such as the NLGF mouse model (Saito et al., 2014) and 5xFAD mouse model (Eimer and Vassar, 2013); both developing amyloid pathology in mouse brains as early as two-month old, while developing amyloid pathology in mouse retina as late as 11-month old (Vandenabeele et al., 2021). Since tubular endoplasmic reticulum protein reticulon-3 (RTN3) was previously shown to be accumulated in AD mouse brains by surrounding amyloid plaques (Sharoar et al., 2016), we asked whether RTN3 expression and distribution in the retina would be altered in these AD retinas. Strikingly, elevated expression of RTN3 was found in the NLGF mouse retina as early as postnatal day 30 (P30), earlier than amyloid pathologies seen in the brain and much earlier than that in the retina. More interestingly, unlike the elevated expression of RTN3 in neurons in AD brains (He et al., 2004), elevated RTN3 expression in the NLGF mouse retinas was specific to Müller glia, the resident glial cell of the retina. We then utilized single-cell transcriptomics to explore how the retina was changing transcriptionally at this early time point and found robust and specific upregulation of the EIF2 and unfolded protein response (UPR) pathways within Müller glia. We further confirmed that components of these pathways were upregulated in a similar staining pattern to RTN3. These findings, taken together, indicate that Müller glia may be an initial sensor of Aβ accumulation, and orchestrate a cell-type specific ER stress response. The presence of ER-related biomarkers in asymptomatic AD retina appears to be not only a useful biomarker for monitoring AD pathogenesis but also a target for intervention to prevent pathological progression in the AD retina.

Results

Endoplasmic reticulum protein RTN3 is upregulated preceding plaque deposition in NLGF mouse retina

Neuronal RTN3 has been well characterized in AD for its role in the formation of dystrophic neurites (DNs) and for its interaction with BACE1, the enzyme responsible for cleaving amyloid precursor protein (APP) (Prior et al., 2010). RTN3 overexpression induces neuronal dystrophy and axonal disruptions (Hu et al., 2007). However, it is not understood whether this protein plays a similar role in the retina where manifestation of AD is evident through retinal neuron degeneration and late-stage plaque formation (den Haan et al., 2019; Lu et al., 2010; Vandenabeele et al., 2021).

To answer this question, we examined RTN3 protein levels in the NLGF mouse retina. Previous studies have shown that increased soluble Aβ in the NLGF mouse retina begins at P90, and dense plaques begin to appear around P365 (Vandenabeele et al., 2021). Since RTN3 accumulation normally occurs after plaque formation in the brain, we began to compare its expression at P365. We found that RTN3 protein levels were indeed increased in the P365 NLGF mouse retina in both its monomeric and dimeric forms (Figure 1A–C). Homo-dimerization of RTN3 can impact ER morphology, and increases in dimeric forms of RTN3 were previously noted in AD patients’ and AD mouse brains (Hu et al., 2007).

Figure 1: Increased expression of RTN3 in P365 and P30 NLGF retinas.

Figure 1:

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(A) Representative western blot of total RTN3 in WT and NLGF posterior cups at P365. Monomeric forms of RTN3 were detected at 25 kDa, and dimerized forms were detected at 50 kDa. (B) Quantification of monomeric RTN3 normalized to GAPDH in P365 WT and NLGF retinas (p=0.0245, n=4). (C) Quantification of RTN3 dimer normalized to GAPDH in P365 WT and NLGF retinas (p=0.0099, n=4). (D) Representative western blot of total RTN3 in P30 WT and NLGF posterior cups. (E) Quantification of monomeric RTN3 normalized to GAPDH in P30 WT and NLGF retinas (p=<0.0001, n=8). (F) Quantification of dimeric forms of RTN3 showing no significant changes in the P30 retina. (G) Immunohistochemical analysis of P30 WT and NLGF retinas revealed an increase in RTN3 in NLGF retinas that is colocalized with vimentin, an intermediate filament protein (scale bar = 50 μm). (H) Orthogonal z-stacks confirm colocalization of vimentin and RTN3 at 63X magnification (scale bar = 20 μm). (* p-value < 0.05, ** p-value < 0.005, *** p-value < 0.001) (GCL = ganglion cell layer, INL = inner nuclear layer, ONL = outer nuclear layer)

To determine how early this elevation occurs, we examined NLGF retina as early as P30, an age before any amyloid plaques in the brain. Remarkably, we also found a significant increase in monomeric forms of RTN3 in the P30 retina (Figure 1D and E), while changes of dimerized forms of RTN3 were not significantly (Figure 1F). The increase seen at P30 indicates an accumulation of RTN3 protein before signs of increased amyloid burden. To confirm that canonical AD-related pathology had not yet appeared in the P30 or P120 NLGF retina, we used immunohistochemical staining to probe for Aβ oligomers using the A11 and neuritic dystrophy with saposin-C antibodies, respectively (Sharoar et al., 2021). Consistent with previous reports (Vandenabeele et al., 2021), we did not observe Aβ accumulation or neuritic dystrophy in the ganglion cell layer (GCL) before the age of P365 (Supplemental Figure S1). In parallel with Aβ accumulation, retinal gliosis or reactive gliosis, marked by GFAP, was also obvious only at P365 (Supplemental Figure S1C). Together, we postulate that the increase in monomeric RTN3 protein levels at the 30-day time point suggests a potential cellular response to retinal Aβ or engineered mutant APP long before the dense plaque begins to form.

RTN3 upregulation is specific to Müller glia in the NLGF retina

To further characterize the cell-type specificity of RTN3 at P30 in the NLGF mouse retina, we conducted immunohistochemical staining of fixed retina sections using RTN3-specific antibodies validated by the use of RTN3-null samples (Shi et al., 2014). In human and rodent brains, RTN3 is predominantly expressed by neurons (Shi et al., 2017; Wojnacki et al., 2020). Basal expression of RTN3 in the WT retina was mainly restricted to the GCL, including both Müller end feet and the cell bodies of the RGCs (Figure 1G and H). To our surprise, increased RTN3 expression was more specific to retinal Müller glia rather than the expected ganglion neurons in the NLGF mouse retina (Figure 1G and H). We observed marked RTN3 expression throughout the ganglion cell layer, the inner plexiform layer, and the inner nuclear layer. Co-staining revealed specific colocalization with the glial marker, vimentin (Figure 1G). We confirmed expression of RTN3 in ganglion neurons as some colocalization of RTN3 and Thy1 was evident both in WT and NLGF (Supplemental Figure S2). However, the increase in RTN3 appeared to be specific to Müller glia (Figure 1H). Interestingly, increased RTN3 expression within P30 Müller glia not only preceded plaque accumulation but also notable gliosis (Supplemental Figure S1C).

In the NLGF mouse model, the humanized mutant App gene is expressed via the endogenous promoter (Saito et al., 2014). Therefore, we can’t exclude the potential effect of low levels of mutant APP produced by Müller glia on RTN3 expression. To address this point, we utilized the 5xFAD AD mouse model to probe for RTN3 expression. Transgenic 5xFAD mice express mutant App driven by a Thy1 promoter (Oakley et al., 2006); thus only Thy1-expressing cells, namely RGCs, should express mutated APP. We chose a timepoint (P120) that precedes plaque formation in this model (Lim et al., 2020; Zhang et al., 2021). By comparing the P120 NLGF retina and P120 5xFAD retina, we demonstrated that RTN3 expression was also upregulated in Müller glia proceeding plaque accumulation in the 5xFAD model (Supplemental Figure S3). RTN3 expression colocalized with vimentin (the Mϋller glia marker), indicating that Mϋller glia would also be an early responsive cell type in a neuron-specific APP overexpression model.

Early transcriptomic changes in the NLGF Müller glia

Our RTN3 staining result reveals that Müller glia are more sensitive to mutant APP or Aβ in the NLGF retina at P30, even well before cerebral amyloid plaque accumulation. To determine what other molecular changes are occurring transcriptionally within Müller glia, we turned to unbiased single cell RNA sequencing (scRNAseq). We used dissociated cells from two P30 wildtype (WT) retinas (one male and one female) and two P30 NLGF retinas (one male and one female) for this experiment. Expression of mutant App in NLGF knock-in retinas was confirmed based on cDNA sequencing reads to validate accurate genotypes (Supplemental Figure S4A). We integrated and clustered the four independent datasets as shown by UMAP clustering (Figure 2A), and annotated cell types based on canonical retinal cell markers with expected representation of each retinal cell type (Supplemental Figure S4B). The number of reads and dead cells as represented by mitochondrial gene content were comparable between all four samples (Supplemental Figure S4C).

Figure 2: Single-cell RNA sequencing of P30 retinas reveals Rtn3 is primarily expressed by retinal glia, and glia and rods are altered transcriptionally in P30 Alzheimer’s mouse model.

Figure 2:

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(A) UMAP plots of P30 retinas from WT and NLGF mice. Expected retinal cell types are represented. (B) Expression of Rtn3 by cell type. Violin plots are showing normalized expression and numbers indicate average normalized expression by cell type. (C) Rtn3 expression overlaid on UMAP plots showing expression is highest within the glia cluster. (D) Expression of Rtn3 is unchanged between WT and NLGF within the glia cluster. (E) Table showing number of significantly differentially expressed genes (DEGs) by cell type between WT and NLGF across different comparisons. Common DEGs represent genes that are consistently significantly differentially expressed across male, female, and combined comparisons. (F) Volcano plot showing DEGs within rods. WT versus NLGF differentially expressed genes are shown in gray and common DEGs are labeled in red. (G) Volcano plot showing DEGs within glia. WT versus NLGF differentially expressed genes are shown in gray and common DEGs are labeled in orange.

Since we observed RTN3 protein accumulation in the Müller glia in the NLGF mouse retina, we asked whether Rtn3 was expressed by Müller glia and if this protein accumulation was due to upregulated Rtn3 transcription in NLGF mice. We showed that Rtn3 was abundantly expressed by glia, even more than neuronal cell types including RGCs (Figure 2B and C). Our comparative analysis showed no obvious changes in Rtn3 expression between WT and NLGF glia (Figure 2D). This data suggests that the increase in RTN3, observed in Figure 1, was the result of protein accumulation and not a change in transcriptional regulation.

Further analysis of differential expressed genes (DEGs) was conducted by comparing male WT versus male NLGF, female WT versus female NLGF, and both WT versus both NLGF. To ensure specificity, only DEGs common to all three comparisons were investigated, termed ‘common DEGs’ (Figure 2E, Supplemental Table S1). Although neuronal cell types, like RGCs, are canonically expected to respond to Aβ production, we detected more transcriptional changes within glia (18 common DEGs) vs 7 common DEGs within rods or 0 in RGCs (Figure 2E). DEGs were also shown by volcano plot (Figure 2F) and violin plots (Supplemental Figure S4D–F). Specifically, significantly altered genes were Sag, Pde6g and Rcvrn, known to act in the phototransduction pathway (Brennenstuhl et al., 2015; Chen et al., 1995; Zhang and Lu, 2000), implying that changes to rod physiology in the NLGF mouse retina likely occurs earlier than expected. Upregulated genes within the glia cluster, such as Atf4, Ddit3 (CHOP), Eif2s2, Herpud1, Cebpg, and Nupr1, were components known in the unfolded protein response (UPR) and ER stress pathways (Figure 2G).

Müller glia elicit early ER stress response in P30 NLGF mouse retinas

Since the retina harbors multiple glial subtypes, we wanted to determine specifically which glial subtype had these genes upregulated and if this upregulation would explain our observation of increased RTN3 in Müller glia. We performed sub-clustering of retinal glia (Figure 3A, inset), and identified three distinct clusters based on the expression of Müller glia (Rlbp1-high, Dbi-high, Cd44+ and Uba3+), astrocytes (Rlbp1-, Sned1-high, Slc38a3-high, Clk1-high and Macf1-high), and microglia (P2ry12+, Cx3cr1+ and Tmem119+) (Supplemental figure S5A–B). By using the same differential gene expression approach as Figure 2, genes responding to ER stress were again significantly upregulated, but only within the Müller glia sub-cluster (Figure 3B and C), although Rtn3 is expressed by astrocytes (Supplemental figure S5A). This confirms that the DEGs observed in the P30 NLGF mouse retina were specific to Müller glia.

Figure 3: Sub-clustering of glial cells reveals transcriptomic changes to NLGF retina are specific to Mϋller glia.

Figure 3:

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(A) UMAP plot of glia cluster (inset) reveals it consists of Mϋller glia, astrocytes, and microglia. (B) Table and volcano plot showing significant differentially expressed genes by glial subtype. Müller glia are the only cell type transcriptionally changing between WT and NLGF. Common DEGs are labeled in blue. (C) Violin plots of individual genes in the EIF2-ATF4 signaling pathway show activation of the pathway in NLGF Müller glia. (D) Pathway analysis of common DEGs within Mϋller glia shows activation of EIF2 signaling, unfolded protein response, p38 MAPK signaling and ER stress pathway. (E) A composite score of 214 ER stress response genes (scores > 0 represent transcriptional levels above background) are specifically increasing in glial cells (p-value = 1×10−16 for comparing WT versus NLGF glia).

We further conducted Ingenuity Pathway Analysis (Qiagen) based on the altered DEGs within Müller glia, and identified EIF2 signaling, unfolded protein response (UPR), p38 MAPK signaling and the ER stress pathway as being significantly activated (Figure 3D). Considering the published observation that overexpression of RTN3 in HeLa cells leads to increased expression of Ddit3 (CHOP) (Kuang et al., 2005; Wan et al., 2007), we inferred that that elevation of RTN3 protein likely occurs first, and then triggers expression of ER stress response genes.

Considering the highly stringent conditions utilized in identifying DEGs, we also tested whether ER stress in the NLGF retina was restricted to glia or other cell types if conditions were relaxed. To this purpose, we generated a composite score of 214 ER stress markers as previously characterized (Chow et al., 2015), with a score > 0 representing upregulation compared to background gene expression within each cell type (Figure 3E). Only the NLGF glia cluster was significantly upregulating the ER stress response based on this gene set (p-value = 1×10−16). This data further demonstrates Müller glia as the only responding cell type at this time point.

The single-cell sequencing data was also useful to determine whether Müller glia produce Aβ. We, therefore, analyzed App and Bace1 expression levels by cell type within the retina and showed that Müller glia express low levels of App and negligible Bace1 (Supplemental Figure S5B). Compared to endothelial cells and RGCs, Müller glia are unlikely the major source for toxic Aβ due to undetectable expression of Bace1, which is required for Aβ generation (Hampel et al., 2020). This was also in line with the result from 5xFAD mouse model (Supplemental Figure S3). Elevated RTN3 in Müller glia is likely the consequence of extracellular Aβ in a non-cell autonomous manner, and oligomeric Aβ was shown to induce expression of RTN3 (Hu et al., 2007).

The EIF2 pathway is upregulated at the protein level in Müller glia

Genes such as Atf4 and Ddit3 (CHOP) are known to be regulated through the PERK arm of the ER stress pathway (Liu et al., 2015). Phosphorylation of PERK and EIF2α proteins during cellular stress results in activation and increased expression of ATF4 and CHOP at the protein level, facilitating two key features of AD retinal pathology: mitochondrial dysfunction and apoptosis (Liu and Zhu, 2017; Obulesu and Lakshmi, 2014).

To determine whether the increase in Atf4 and Ddit3 (CHOP) transcripts would translate to altered protein levels of ATF4 and CHOP, we performed immunohistochemistry on P30 retinas from WT and NLGF mice. CHOP expression was minimal in the P30 WT retina with some sparse staining in the GCL (Figure 4A and C). In the NLGF mouse retina, CHOP expression was evident in the GCL, INL and ONL (Figure 4B and D). CHOP expression colocalized with the intermediate filament protein, vimentin, similar to RTN3 expression seen in Figure 1H. The enlarged view also showed colocalization of RTN3 and CHOP in Müller glial filaments in the P30 NLGF retina but this colocalization was not observed in the WT retina (Supplemental Figure S6). This Mϋller glia-specific expression of CHOP is supportive to our RNA sequencing data, and confirms that activation of the UPR pathway is occurring in P30 NLGF mouse retina.

Figure 4: EIF2 pathway regulator CHOP is upregulated at the protein level in P30 NLGF Mϋller glia.

Figure 4:

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Immunohistochemical analysis of WT (A and C) and NLGF (B and D) P30 retinas revealed an increase in CHOP in NLGF retinal Mϋller glia. 20X confocal images show sparse expression of CHOP in WT P30 retinas that does not colocalize with the Mϋller glia marker, vimentin. In NLGF retinas, increase in CHOP is evident throughout retinal layers and colocalizes with vimentin. Scale bar = 50 μm for 20X images and 20 μm for 63X images. (Vim = vimentin, GluL = glutamine synthetase, GCL = ganglion cell layer, INL = inner nuclear layer, ONL = outer nuclear layer).

Additionally, we examined the protein expression of ATF4, a key mediator of CHOP upregulation (Rozpędek et al., 2016). In the WT mouse, ATF4 expression was punctate and sparse throughout the GCL (Figure 5A and C). ATF4 expression was elevated in P30 NLGF retina throughout the GCL and INL, and its expression was punctate and colocalized with another Mϋller glial specific marker, glutamine synthetase, which is a transport protein involved in glutamate uptake (Figure 5B and D).

Figure 5: EIF2 pathway regulator ATF4 is upregulated at the protein level in P30 NLGF Mϋller glia.

Figure 5:

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Immunohistochemical analysis of WT (A and C) and NLGF (B and D) P30 retinas revealed an increase in ATF4 in NLGF retinal Mϋller glia. In WT retina, ATF4 labeling is weak. In NLGF retinas, ATF4 expression colocalizes with GluL and is seen throughout the GCL and INL. Scale bar = 50 μm for 20X images and 20 μm for 63X images. (Vim = vimentin, GluL = glutamine synthetase, GCL = ganglion cell layer, INL = inner nuclear layer, ONL = outer nuclear layer).

To investigate whether upregulation of the UPR pathway via CHOP and ATF4 expression is occurring independent of the gliotic response, we examined the expression of GFAP and Aβ in P30 WT and NLGF retinas. Mϋller glia do not express GFAP in normal physiological conditions but upregulate both GFAP and vimentin during retinal gliosis. In the P30 NLGF retina, GFAP expression remained exclusive to astrocytes in the GCL. We also did not observe a difference in 6E10 staining (detecting both APP and Aβ) between P30 WT and NLGF retina (Supplemental Figure S7), indicating that the upregulation of CHOP and ATF4 is an early event in the NLGF retina. These findings, taken together, indicate that the mounted ER stress response in Mϋller glia likely occurs prior to the astrocytosis and retinal functional impairments.

Since we observed an increase in RTN3, CHOP, and ATF4 in the NLGF mouse model at P30, we then aimed to ask whether upregulation of RTN3 alone is sufficient to induce upregulation of CHOP and ATF4. To determine whether RTN3 expression alone can induce UPR protein upregulation, we transfected a construct overexpressing RTN3 into HEK-293 and immortalized human Müller glia. We found, via western blotting, that ATF4 expression was significantly increased by overexpressed RTN3 in HEK 293 cells (Figure 6), in line with previous report (Kuang et al., 2005). On the western blot, the elevation of CHOP was not evident (Supplemental Figure S8), likely related to the overall low expression of CHOP in HEK-293 cells. While immortalized human Müller glia was highly sensitive to lipofectamine-mediated transfection, we managed to show that overexpression of RTN3 was sufficient to induce ATF4 expression in immortalized Müller glia (Supplemental Figure S9). We showed that Müller cells had reduced expression of ATF4, but a dramatic increase in ATF4 expression was noted when the Myc-tagged RTN3 was present. These findings, taken together, support that elevated RTN3 levels would induce the expression of ER stress proteins.

Figure 6: Overexpression of RTN3 in human HEK-293 cells causes increase in ATF4 expression.

Figure 6:

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HEK-293 cells were transfected with empty vector (V) or RTN3 expression construct (R3) for 48 hrs and protein lysates were subjected to western blotting analyses. RTN3 expression was detected at 25kDa (endogenous) and 28kDa (transgene with a Myc-fusion tag at its C-terminus) by RTN3 mouse monoclonal antibody (RTN3-Ms in A). ATF4 expression was detected at 39kDa (B). Loading controls were used to normalize expression and two-tailed t-tests were performed (C, P= > 0.0001, D, P= 0.0346).

Discussion

In this study, we aimed to characterize retinal changes in relation to cerebral amyloid plaque formation using the NLGF KI AD mouse model. Using protein assays and bioinformatic approaches, we found elevated expression of reticulon 3 protein (RTN3) and activation of the ER stress pathway occurred as early as P30 (Figure 1A–F), while retinal amyloid pathology was not detected until P365 (Supplemental Figure S1) (Vandenabeele et al., 2021).

The increase in RTN3 expression was specific to Müller glia (Figure 1G–H), a novel discovery considering RTN3 is predominantly expressed by neurons and barely detectable in glial cells in the brain (Shi et al., 2017). It has been previously demonstrated that the role of RTN3 in AD pathology is neuronal, including the accumulation of RTN3-immunoactive dystrophic neurites, and negative modulation of neuronal BACE1 (Prior et al., 2010; Sharoar et al., 2021). We have previously shown that treatment of cultured primary neurons with oligomeric Aβ induces accumulation of RTN3 (Hu et al., 2007). In line with this, the accumulation of RTN3 observe in Müller glia is likely in response to extracellular Aβ. The elevation of RTN3 in a glial cell type, rather than ganglion neurons, was a surprise finding, indicating a differential effects of tubular ER proteins in brains vs retinas.

To further understand the molecular changes associated with early accumulation of RTN3 in Müller glia, we turned to unbiased single-cell RNA sequencing (scRNAseq) of P30 WT and NLGF mouse retinas. First, it showed that RNA expression of Rtn3 was high in indeed Müller glia, providing a logical validation that RTN3 may have a unique role in Müller glia. Second, we found no alteration in Rtn3 transcript levels between WT and NLGF, indicating that elevation of RTN3 protein is regulated post-translationally. Third, transcriptional changes in the P30 NLGF retina occurred predominantly within Müller glia, revealing that Müller glia are the most sensitive cell type to respond to early amyloid toxicity. Notably, App gene expression and APP processing genes were lower in Müller glia than retinal neurons (Supplemental Figure S5B), suggesting that Müller glial transcriptional changes are a non-cell-autonomous response to extracellular Aβ. This is supported by the accumulation of RTN3 in Müller glia in P120 5xFAD mice (Supplemental Figure S3), a mouse model with RGC-specific overexpression of App. Fourth, the transcriptional changes in P30 NLGF Müller glia are related to PERK signaling [Atf4, Atf5, Ddit3 (CHOP), Eif2s2] and UPR pathways [Atf4, Ddit3 (CHOP), Cebpg]. Using a composite score of ER stress markers, we demonstrate that upregulation of these cellular pathways occurs exclusively in Müller glia (see graphic illustration). This suggests Müller glia are orchestrating an early ER stress response to accumulating toxic Aβ. Lastly, we conducted immunohistochemical characterization that confirms upregulation of Atf4 and Ddit3 (CHOP) transcription leading to protein accumulation within Müller glia.

In several different age-related retinal diseases such as macular degeneration (AMD), retinitis pigmentosa (RP), glaucoma, and diabetic retinopathy (DR), the unfolded protein response (UPR) in retinal neurons has been extensively investigated (McLaughlin et al., 2022). Recently, Müller glia, which spans the entire thickness of the neural retina between the inner and outer limiting membranes (Reichenbach and Bringmann, 2020), is shown to act as a sentinel for metabolic disruption like high glucose (diabetic retinopathy), impeded lipid metabolism (AMD) (Palko et al., 2022), and oxidative stress/mitochondrial dysfunction (glaucoma) (Wax and Tezel, 2002). Their responsiveness to pathological stimuli, while neuroprotective in acute phases, often becomes detrimental to neuronal survival after chronic activation. Specifically, Müller glia have been shown to directly influence RGC survival in diabetic retinopathy through ATF4 and CHOP upregulation and release of apoptotic factors (Wu et al., 2012; Zhong et al., 2012). In both human AD and AD mouse models, the noted pathological event in the retina is RGC dysfunction and death (La Morgia et al., 2017; Moncaster et al., 2022). Though degeneration of these cells has been studied extensively, the mechanism by which they die has not yet been elucidated. Given their degeneration precedes retinal plaque formation, this is an important question in understanding the pathogenesis of AD in the retina. Our findings suggest that Müller glia mount an early ER stress response through the PERK arm of the UPR pathway. Interestingly, we not only observed increase of PERK specific proteins like CHOP and ATF4, but also found increased accumulation of RTN3, a tubular ER protein that has been shown to drive ER stress via intracellular calcium modulation (Kuang et al., 2005). Overexpression of RTN3 has been shown to directly induce ATF4 and CHOP expression; its binding to heat shock protein family A (Hsp70) can induce ER dysfunction (Yang et al., 2021).

Consistent with our results, a recent study (Chucair-Elliott et al., 2022) showed that Müller glia activate the CHOP/ATF4 pathway under stress conditions. Chucair-Elliott et al. found that retina stress from optic nerve crush leads to a Müller glia translatomic response that includes upregulated expression of Ddit3 (CHOP) and Atf4. The DEGs (including Ddit3 (CHOP) and Atf4) were found to be enriched in biological processes following a myriad of stress conditions: regulation of DNA-templated transcription in response to stress, response to starvation, response to wounding, positive regulation of cytokine production, neuron death, and response to molecule of bacterial origin (Chucair-Elliott et al., 2022). We also noted that Atf4 gene was significantly more abundant in Müller glia than astrocytes in P30 mouse retinas (Supplemental Figure S12). These findings support the idea that CHOP/ATF4 upregulation are part of a Müller glia response to stress, such as those undergone by the NLGF retina seen in our study.

In the brain, Aβ-mediated ER stress and maladaptive UPR is mostly shown to occur in neurons (Abisambra et al., 2013; Katayama et al., 2004), though ER stress in astrocytes has recently gained attention (Martin-Jiménez et al., 2017; Sims et al., 2022). ER stress induction in astrocytes mainly occurs via the UPR pathway and is likely a result of uptake of aggregated Aβ after amyloid deposition. In early AD mouse models, molecular changes in astrocytes are limited to increased expression of inflammatory response genes, reduced expression of neuronal support genes and cholesterol biosynthesis genes in astrocytes of AD mice compared to WT controls (Preman et al., 2021). Our results clearly show glial responsive profiles in the retina that are distinct from that in the brain.

Whether the early response in Müller glia causes protection or impairment to the AD retina in the long-term remains to be established. However, our scRNAseq results revealed small reduction of gene expression involved in photoreceptor functions. We speculate that an early non-gliotic response of Müller glia is likely to transmit signal to rod cells, although this hypothesis remained to be attested. Our findings offer insight into how the Müller glia may play a larger role in retinal neuron pathology than previously thought and offer opportunity to explore how Müller glia are proactively responding to toxic Aβ, even before astrocytes in the brain. If Müller glia are responding to extracellular Aβ to reduce survival of RGCs prior to amyloid plaque formation via UPR pathways, it is important to develop therapeutic strategy for targeting early homeostasis of Müller glia to reduce damage in the AD retina.

Materials and Methods

Animal Breeding and maintenance

APPNLGF mice were obtained from the RIKEN Center for Brain Science, Wako, Japan. 5xFAD mice were purchased from Jackson Laboratory (stock # 34840). All mice in the study were maintained and used according to protocols approved by the Institutional Animal Care and Use Committee of the University of Connecticut. Presence of the NLGF knock-in mutation in App were confirmed using the grep function on fastq files produced from the single cell RNA sequencing experiments.

Western Blotting

The anterior ocular tissues were carefully separated from the posterior eye cups and the latter tissue was employed for protein extraction. We performed separate extractions for each western blot analysis. Posterior cups were minced on ice in RIPA buffer containing complete protease inhibitors. The homogenates were subjected to three freeze/thaw cycles to extract protein and spun at 14,000 × g for 5 minutes at 4°C supernatants were collected, and protein concentrations were measured with the bicinchoninic acid protein assay reagent (Thermo Scientific, Grand Island, NY, USA). Equal amounts of protein samples were resolved on 4–12% NuPage Bis-Tris gels purchased from Invitrogen. Following incubation with the indicated primary antibody, an appropriate horseradish peroxidase-conjugated secondary antibody was added. Immunoreactivity was detected by chemiluminescence using SuperSignal West PICO reagent (Thermo Scientific). Image-J software was used to quantify the mean gray value for a fixed area of each protein band28.

Immunohistochemistry

Eyes were enucleated from WT and homozygous NLGF mice and flash frozen on dry ice. Eyes were stored at −80 degrees C or suspended in OTC for tissue sectioning. 12 μm cryosections were air dried for 30 minutes at room temperature, fixed with 4% paraformaldehyde/PBS for 15 minutes, and then washed three times for 5 minutes with PBS. Samples were blocked in 5% goat serum/.05% Triton X for 1 hour at room temperature. Samples were probed with primary antibodies (Table 1) diluted in 5% goat serum overnight at 4°C. After three washes with PBS for 15 minutes, slides were then incubated with secondary antibodies for 1 hour at room temperature (RT). DAPI nuclei stain was added, and images were examined and captured with a Leica SP5 and a Ziess LSM880 confocal microscope. Non-specific immunofluorescence by secondary antibody only in fixed mouse retina sections was presented (Supplemental Figure S10). Autofluorescence of mouse retina sections was also shown (Supplemental Figure S11), with significant autofluorescence in the inner segments (IS) and outer segments (OS) of photoreceptors.

Table 1.

Antibodies used for western blotting (WB) and immunofluorescence staining (IF).

Antibodies RRID Company/Catalog Number Clone/Isotype Species Dilution Incubation Figure Reference
ATF4 AB_2058600 ProteinTech/ 10835–1-AP Polyclonal IgG Rabbit 1:200 IF: O/N @ 4 degrees Figure 5
Figure 6
Figure S8 (B)
A11 AB_2536236 Thermofisher/ AHB0052 Polyclonal IgG Rabbit 1:200 IF: O/N @ 4 degrees Figure S1 (A)
CHOP AB_298023 Abcam/ ab11419 Monoclonal IgG Mouse 1:200 IF: O/N @ 4 degrees Figure 4
Figure S7
cMyc AB_627268 Santa Cruz/ sc-40 monoclonal IgG1 Mouse 1:200 IF: O/N @ 4 degrees Figure S9
GAPDH AB_2107426 Calbiochem/ CB1001 Monoclonal IgG Mouse 1:1000 WB: O/N @ 4 degrees Figure 1 (A,D)
Figure S8 (B)
GFAP AB_2532994 Thermoscientific/ 13–0300 Monoclonal IgG Rat 1:500 IF: O/N @ 4 degrees Figure S6
GFAP AB_561049 Cell Signaling/ 3670 Monoclonal IgG Mouse 1:500 IF: O/N @ 4 degrees Figure S1 (C)
Glutamine Synthetase AB_2110656 Millipore/ MAB302 Monoclonal IgG Mouse 1:200 IF: O/N @ 4 degrees Figure 5
RTN3 See reference See reference (Shi et al., 2017) Monoclonal IgG Mouse 1:1000 IF/WB: O/N @ 4 degrees Figure 1 (A,B,G,H)
Figure S3
Figure S8 (A)
RTN3 See reference See reference (Shi et al., 2017) Polyclonal IgG Rabbit 1:1000 IF: O/N @ 4 degrees Figure S2
Figure S7
Saposin AB_1128802 SantaCruz/ sc-100584 Monoclonal IgG Mouse 1:200 IF: O/N @ 4 degrees Figure S1 (A)
Thy1 AB_11213488 Millipore/ MAB1406 Monoclonal IgG Rat 1:200 IF: O/N @ 4 degrees Figure S2 (A,B,C,D)
Vimentin AB_10562134 Abcam/ ab92547 Polyclonal IgG Rabbit 1:200 IF: O/N @ 4 degrees Figure 1 (G,H)
Figure S3
Figure 4
6E10 2564652 Biolegend/ 803003 Monoclonal IgG Mouse 1:500 IF: O/N @ 4 degrees Figure S6
Alexa 594 Anti-Mouse N/A Thermofisher/ A11032 Goat 1:500 IF: 1 hr @ RT Figure 1 (G,H)
Figure 4
Figure 5
Figure 6
Figure S1
Figure S3
Figure S7
Figure S9
Alexa 594 Anti-Rabbit N/A Thermofisher/ A11012 Goat 1:500 IF: 1 hr @ RT Figure S1
Figure S9
Alexa 594 Anti-Rat N/A Thermofisher/ Goat 1:500 IF: 1 hr @ RT Figure S2
Figure S6
Alexa 568 Anti-Mouse N/A Thermofisher/ A11031 Goat 1:500 IF: 1 hr @ RT Figure S10
Alexa 568 Anti-Rabbit N/A Thermofisher/ A11036 Goat 1:500 IF: 1 hr @ RT Figure S10
Alexa 488 Anti-Rabbit N/A Thermofisher/ A11008 Goat 1:500 IF: 1 hr @ RT Figure 1 (G,H)
Figure 4
Figure 5
Figure 6
Figure S3
Figure S7
Figure S9
Alexa 488 Anti-Mouse N/A Thermofisher/ A28175 Goat 1:500 IF: 1 hr @ RT Figure S2
Figure S6
Figure S9
Anti-Mouse HRP Conjugated N/A Thermofisher/ 31430 Goat 1:1000 WB: 2 hr @ RT Figure 1
Figure S8
Anti-Rabbit HRP Conjugated N/A Thermofisher/ 31460 Goat 1:1000 WB: 2 hr @ RT Figure 1
Figure S8
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Retinal Dissociation

Four P30 retinas, one WT male, one WT female, one NLGF male and one NLGF female WT were extracted according to the published procedure (Fadl et al., 2020). Briefly, the retinas were dissected in fresh and cold 1X HBSS and individually transferred to a 5 ml polypropylene round-bottom tube containing 1 ml of digestion solution. The individual retinas were then incubated at 8 °C for 40 min followed by a second incubation at 28 °C for 10 min. After the incubation steps, the retina should have remained morphologically intact. Mechanical trituration of the retina was performed in 700 μl of prewarmed (10 min at 28 °C) inactivation solution. Trituration was stopped when the retina was visibly dissociated, and 700 μl of ice-cold washing solution was layered under the cell suspension. Cell suspensions were centrifuged using a swing-bucket rotor at 200 ×g for 5 min at 4 °C. After the supernatant was removed, the cells were resuspended in 500 μl of DPBS containing 0.04% BSA and passed through a 40 μm cell strainer.

Single Cell RNA Sequencing

Single cell suspensions from retinal dissociation were counted and loaded onto a droplet-based 10x Chromium controller to perform single cell partitioning and barcoding. Raw sequencing from the NovaSeq6000 was aligned and annotated using the CellRanger v3.1.0 pipeline. During FASTQ generation, reads with more than 1 mismatch in the 8bp i7 index were excluded. During alignment using STAR (Dobin et al., 2013), only reads with MAPQ scores greater than 255 aligned to annotated transcripts were retained. Reads containing bases with Q30 scores below 3 were also excluded. After alignment, cell barcodes were filtered up to 1 mismatch against a whitelist of 737,500 barcodes provided by 10X Genomics. Barcodes associated with cells were distinguished from ambient mRNA using an adaptively computed UMI threshold. The raw counts matrix was filtered using cutoff values of mitochondrial transcripts below 25% and between 500 and 7,500 unique features.

Dimensionality reduction and clustering

Data analyses also considered guidance as discussed (Wang et al., 2022). The expression profiles of each cell using the 2000 most variable genes as measured by dispersion (Satija et al., 2015; Zheng et al., 2017) were used for neighborhood graph generation and dimensionality reduction with UMAP (McInnes et al., 2020). Clustering was performed on this neighborhood graph using the Leiden community detection algorithm (Traag et al., 2019). Because the experiments consisted of multiple samples, the neighborhood graph was batch-corrected using the batch correction software BBKNN (Polański et al., 2020) and integrated using reciprocal principal component analysis (rPCA). Clustering, cell type annotation, sub-clustering, and differential expression were performed ad hoc on a per-cluster basis using the Seurat v4.0 R toolkit (Hao et al., 2021).

Statistical analysis

Results with statistical significance are expressed as Mean ± SEM with *p < 0.05, **p < 0.01, ***p< 0.001 using Student’s t-test. The statistical calculation was using GraphPad Prism 6.0 software (GraphPad Software, San Diego). Differential gene expression between conditions in single-cell RNAseq data set was analyzed using the Wilcoxon Rank Sum Test with Bonferroni-corrected p-values within the Seurat v4.0 R toolkit. Statistical analysis comparing gene set scores was completed using a differential expression test (Welch t-test) with Bonferroni-corrected p-values. Qiagen Ingenuity Pathway Analysis (IPA) was utilized for glial and rod differential gene sets against the mouse transcriptome.

Supplementary Material

Supinfo1
Tab S1
Tab S2
Supinfo2

Significance:

This study provides the first evidence that Müller glia is the first to sense the challenge of abnormal production β-amyloid peptide in the Alzheimer’s retina, an event significantly earlier than amyloid deposition in the retina. Mechanistic study reveals that the first change is elevated level of Müller glia tubular endoplasmic reticulum protein reticulon-3 (RTN3), a protein previously shown to be abnormally accumulated in neurons and dystrophic neurites of AD brains. This is the first study to reveal differential glial responses between the retina and brain, and changes in Müller glia should be monitored for AD pathological progression. To maintain homeostasis of Müller glia may protect retinal degeneration in AD.

Acknowledgement:

We sincerely thank members of the Yan lab for the discussion during the study. This work is supported by grants AG025493, RF1AG058261, NS074256, and AG046929 from the National Institutes of Health to R Yan. Dr. Yan’s lab is also supported by the Cure Alzheimer’s Fund. Dr. Mohan is supported by R21EY028699. A Yao is a receipt of F30 award (1F30AG081134-01) from NIH and 2022 Kalman AFAR Scholarship.

Sequencing data availability:

Sequencing data is available through the gene expression omnibus at GSE254524.

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Associated Data

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

Supplementary Materials

Supinfo1
NIHMS1971897-supplement-Supinfo1.mhtml (3MB, mhtml)
Tab S1
NIHMS1971897-supplement-Tab_S1.xlsx (40.2KB, xlsx)
Tab S2
NIHMS1971897-supplement-Tab_S2.xlsx (18KB, xlsx)
Supinfo2
NIHMS1971897-supplement-Supinfo2.docx (19.3MB, docx)

Data Availability Statement

Sequencing data is available through the gene expression omnibus at GSE254524.

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