Single-cell RNA sequencing reveals a landscape and targeted treatment of ferroptosis in retinal ischemia/reperfusion injury

ScRNA-seq yielded retinal cell profiling in mice with I/R injury

Single-cell transcriptome analysis was performed on retinal tissue of 8-week-old blank and retinal I/R mice to generate a comprehensive cell atlas of this I/R model. We then used 10× Genomics to generate a barcoded scRNA-seq library of the cell suspension samples. The sequencing data were processed using Cell Ranger software (version 3.1.0) to generate a matrix of unique molecular identifiers that was analyzed using Seurat R Package v3 [18]. scRNA-seq profiles passing quality control were corrected for technical 10× run batch effects using Harmony [19]. Unsupervised clustering of the Harmony-corrected data, followed by two-dimensional t-distributed stochastic neighbor embedding (tSNE), revealed 12 distinct molecular clusters, consistently clustering the various cell types into distinct regions.

We analyzed the distribution of the four cell lineages in the retina, including seven neuronal classes, Rod, Cone, cone bipolar cell (CBC), rod bipolar cell (RBC), amacrine cell (AC), horizontal cell (HC), and retinal ganglion cell (RGC), one glial class, macroglia (Mag), three immune classes, monocyte macrophage and microglia (Myeloid), Neutrophil, and T cell and dendritic cells (T&DC), and vascular endothelial cell (VEC), based on canonical markers and the most variable upregulated genes (Fig. 1A). Notably, we found that a group of Myeloid cells with high expression of ITGAM appeared during retinal I/R injury, including retina microglia, blood-derived macrophages and monocytes (Additional file 1: Fig. S1A). The number of cells and relative per-class cell types in the retinal I/R and blank groups are depicted in Additional file 1: Fig. S1B. Many clusters were differentially represented in the two groups. Myeloid, and T&DC subsets were over-represented in the I/R model and ROD, CBC, RBC, AC, RGC, and VEC subsets were underrepresented (Fig. 1B). Compared to the blank group, the I/R model had a markedly higher proportion of retinal cells in the Neutrophil and T&DC subsets and lower in the CBC, RBC, AC, Mag, RGC, and VEC subsets (p < 0.05; Fig. 1C). Four subsets (CONE, ROD, HC, and Myeloid) were similarly present in both groups (Additional file 1: Fig. S1B). scRNA-seq analysis revealed cell cluster differences between the groups.

Fig. 1figure 1

scRNA-seq reveals altered retinal heterogeneity in mice with I/R injury. A Clustering strategy of major retinal cell populations identifying 12 cell types (left) based on the scaled expression heatmap of canonical markers for each cluster (right). Color scheme is based on z-score distribution from − 2 (blue) to 2 (red). B Relative changes in cell ratios in different cluster between Blank and I/R groups. The numbers on the right indicate the Log2FC values of the cell ratios. C Violin plots showing the proportion of 8 clusters in retinal cells between Blank and I/R groups (n = 3/group). P value were calculated using a Wilcoxon rank-sum test. D t-SNE distribution showing I/R-upregulated DEGs numbers from 12 clusters. E GO and pathway enrichment analysis of I/R-upregulated DEGs in 12 clusters of the I/R model. P value was derived by a hypergeometric test

On condition of the exclusion of subsets of cells with a percentage of less than 0.1%, we conducted differentially expressed gene (DEG) analysis comparing the I/R and blank groups to further understand the gene changes in the retinal I/R model. tSNE is the number of upregulated DEG. Of these, over 400 were primarily expressed in the RGC and Myeloid subsets (Fig. 1D). Using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we showed that these upregulated genes were mainly associated with cell death regulation (e.g., apoptotic signaling pathway, ferroptosis, pyroptosis, necrosis, and neuronal death), oxidative stress, iron intake and transport, type II interferon signaling (IFNG), and the TNF and MAPK signaling pathways (Fig. 1E).

Taken together, we constructed an integrative transcriptional atlas containing multiple neuron and immune cell subpopulations and established a cellular profile to further understand the dynamic changes in immune cells and neurons during I/R.

Classification and differential expression gene (DEG) analysis of the retinal photoreceptor cells

We examined I/R-induced alterations in photoreceptor cells, because they are highly sensitive to I/R and lost shortly after it is induced [20]. We identified two clear photoreceptor clusters, the rods that selectively express rhodopsin and cones that express short- and medium-wavelength opsins (Additional file 1: Fig. S1D). Cone photoreceptors in both groups comprised four subclusters (SCs), SC0 to SC3 (Fig. 2A, B). Although the groups were similar in cones, they differed in their cone SC proportions (Fig. 2C). We observed that the proportion of SC0, which showed high expression of Opn1sw, Arr3, Opn1mw, and other cone signature genes, decreased in the I/R group (Fig. 2C, E). Notably, SC1 and SC3 were found almost exclusively in the I/R group (Fig. 2C). Higher Neutrophil-derived protein S100a8/a9 expression was confirmed in SC1, whereas SC3 was enriched for pro-inflammatory cytokine genes (Ilβ, Il1a) and ferroptosis-related genes (Fth1, Flt1, and Hmox1; Fig. 2D, E). Similarly, the rods were similar in the two groups and showed four distinct subclusters (Fig. 2F, G, Additional file 1: Fig. S1E). The percentage of SC2 and SC3 increased dramatically after I/R injury, particularly SC2 that was enriched in pro-inflammatory (S100a8 and Il1b) and iron intake and transport (Fth1, Flt1, and Hmox1) genes (Fig. 2H–J).

Fig. 2figure 2

I/R injury induced an expansion of photoreceptor subclusters with ferroptosis. A t-SNE distribution showing 4 subclusters in CONE. B t-SNE distribution showing groups (Blank and I/R) in CONE. C Bar plots showing cell abundances across CONE-SCs (n = 4) for the Blank and I/R groups. D Violin plots showing the proportion of CONE-SC3 in CONE between Blank and I/R groups (n = 3/group). P value were calculated using a Wilcoxon rank-sum test. E Heat map representing the scaled expression values of the top 10 genes defining each CONE-SCs. F t-SNE distribution showing 4 subclusters in ROD. G t-SNE distribution showing groups (Blank and I/R) in ROD. H Bar plots showing cell abundances across ROD-SCs (n = 4) for the Blank and I/R groups. I Violin plots showing the proportion of ROD-SC2 in ROD between Blank and I/R groups (n = 3/group). P value were calculated using a Wilcoxon rank-sum test. J Heat map representing the scaled expression values of the top 10 genes defining each ROD-SCs. K GO and pathway enrichment analysis of the CONE-SCs clustering DEGs. P value was derived by a hypergeometric test. L GO and pathway enrichment analysis of the ROD-SCs clustering DEGs. P value was derived by a hypergeometric test. M Violin plots showing the inflammatory response score between Blank and I/R groups among CONE (up) and ROD (down) clusters

We next explored the biological implications of the upregulated DEG through gene ontology (GO) and pathway analyses for each SC in the cone and rod photoreceptors. The commonly upregulated genes in cone-SC3 and rod-SC2 after I/R were enriched in apoptotic signaling pathways, ferroptosis, iron intake and transport, and cellular responses to stress (Fig. 2K, L). While the inflammation-related GO and pathway enrichment analysis showed highly expressions of TNF signaling pathway, NF-kappa B signaling pathway, inflammatory response, IL-17 signaling pathway and cellular response to IL-1 in cone-SC3 and rod-SC2 (Additional file 1: Fig. S1G, H). Next, we calculated the inflammatory response score in CONE and ROD, respectively, finding that the values of the I/R group were higher than those of the blank group in both cell types (Fig. 2M).

Hence, I/R-induced damage to the photoreceptor cells could be attributed to a reactive increase in specific SCs related to inflammation and ferroptosis.

Ferroptosis is involved in I/R-induced RGC damage

We identified the RGC based on the expression of Slc17a6, which encodes the transporter Vglut2, and Rbpms, which encodes an RNA-binding protein with multiple splicing. These markers were weakly expressed in other AC and HC clusters. Our analysis divided the RGC into two subclusters based on their canonical markers (Fig. 3A). SC0 was highly represented in the I/R group and SC1 in the blank group (Fig. 3B–D). Cells in SC0 expressed high levels of S100a8, S100a9, Cxcl2, Il1b, Flt1, and Hmox1, genes related to ferroptosis, iron uptake and transport, and immune response. Cells in SC1 expressed high levels of Tppp3, Calb2, and Cygb, genes related to neuron projection morphogenesis and extension and the apoptotic signaling pathway (Fig. 3E, F).

Fig. 3figure 3

I/R injury induced an expansion of RGC subclusters with ferroptosis. A t-SNE distribution showing 2 subclusters in RGC. B t-SNE distribution showing groups (Blank and I/R) in RGC. C Bar plots showing cell abundances across RGC-SCs (n = 2) for the Blank and I/R groups. D Violin plots showing the proportion of RGC-SCs in RGC between Blank and I/R groups (n = 3/group). P value were calculated using a Wilcoxon rank-sum test. E Heat map representing the scaled expression values of the top 10 genes defining each RGC-SCs. F GO and pathway enrichment analysis of the RGC-SCs clustering DEGs. P value was derived by a hypergeometric test. G Violin plots showing the expression of genes related to oxidative stress between Blank and I/R groups. H Violin plots showing the expression of genes related to regulated necrosis between Blank and I/R groups. I Violin plots showing the expression of genes related to ferroptosis between Blank and I/R groups

Next, we adopted a violin-plotted feature genes of well-established forms and several key events of RGC damage, including oxidative stress (Cyba, Fos, Gpx1, and Junb), regulated necrosis (Hsp90aa1, Sdcbp, Il1b, and Chmp4p), and ferroptosis (Fig. 3G, H). Interestingly, we found that ferroptosis genes (Fth1, Flt1, Gpx4, and Sat1) were specifically enriched in RGC in the I/R retina (Fig. 3I), indicating that RGC primarily experienced ferroptosis during I/R. These findings demonstrated that I/R retinas were characterized by the emergence of ferroptosis-sensitive RGC-SC0.

Retinal I/R led to ferroptosis-related changes in glial cells

Multiple glial cell types are activated during I/R. Macroglia, including astrocytes and Müller glia, undergo reactive gliosis after the retina and/or optic nerve is damaged, and interact with microglia to mediate the release of inflammatory cytokines. These cytokines were hypothesized detrimental or beneficial to the survival of RGC and their axon regeneration [20, 21]. We divided the macroglia into seven SCs (Additional file 1: Fig. S2A). The I/R mice had higher levels of SC1, SC2, SC3, and SC5, whereas the blank mice had larger proportions of SC0, SC4, and SC6 (Additional file 1: Fig. S2B–E). The known specific markers of Müller glia, Glul, Clu, and Dkk3, were upregulated in SC0. SC6 was classified as an astrocyte subcluster based on the expression of Gfap (Additional file 1: Fig. S2F). SC3 in the I/R group particularly stood out. Closer examination revealed significant enrichment in acute phase inflammation (Saa3, S100a8, S100a9, and Cxcl2) and ferroptosis (Fth1, Ftl1, and Hmox1) genes (Additional file 1: Fig. S2F). Furthermore, we found unique expression of some rod markers in SC1, including Rho and Gngt1, indicating that macroglia might play an important role in photoreceptor damage (Additional file 1: Fig. S2F, G).

GO analysis of DEG between the macroglia subclusters in I/R and blank retinas showed that SC3 was enriched in pathways, such as cell death (apoptosis signaling pathway, regulated necrosis, and ferroptosis), oxidative stress, iron uptake and transport, and immune response (MAPK pathway and response to interferon-gamma; Additional file 1: Fig. S2H). SC0, SC1, and SC4 were associated with neuronal system and neuron projection morphogenesis and extension (Additional file 1: Fig. S2H).

Myeloid activation is an early alteration during retinal I/R. Our previous study showed that the myeloid act as critical mediators, orchestrating neuroinflammation progression through pro-inflammatory cytokines [11]. Under stress, gliosis in retinal glia, such as macroglia, can be triggered by myeloid activation through increased cytokine levels [22]. Similarly, pathway-enrichment analysis with DEG obtained through unsupervised clustering analysis found apoptotic signaling pathways and the regulation of neuron death, driven in part by the upregulation of genes associated with ferroptosis, including Ptgs2 and Slc7a11. Genes involved in oxidative stress (e.g., Homx1 and Sod2) and iron uptake and transport (e.g., Atp6v1a, Atp6v0d1 and Fth1) were also upregulated (Fig. 4A and Additional file 1: Fig. S3A). The increased cell death pathways’ activities after I/R injury, particularly ferroptosis-related genes, demonstrated that I/R induced ferroptosis. We calculated the scores in Blank and I/R group to assess the extent of this phenomenon, finding that the latter exhibited higher inflammatory response score and ferroptosis score (Fig. 4B).

Fig. 4figure 4

I/R injury induced an expansion of Myeloid subclusters with ferroptosis. A GO and pathway enrichment analysis of the Myeloid cells clustering DEGs. P value was derived by a hypergeometric test. B Violin plots showing the inflammatory response score (up) and ferroptosis score (down) between Blank and I/R groups. C Heat map representing the scaled expression values of the top 10 genes defining each Myeloid subsets. D t-SNE distribution showing 4 subclusters in Myeloid. E t-SNE distribution showing groups (Blank and I/R) in Myeloid. F Bar plots showing cell abundances across Myeloid (n = 4) for the Blank and I/R groups. G Heat maps demonstrating up-regulated genes and pathways in Myeloid during retina I/R injury

For further study, myeloid were subdivided into 4 subgroups. C1qa and C1qb positive microglia, Ly6c2 (high) and Tgfbi (low) monocytes (Mo), Ly6c2 (high) and Tgfbi (high) mononuclear macrophage intermediates(intMoMp), and the remaining macrophages (Mp) were isolated (Fig. 4C, D and Additional file 1: Fig. S3B). By comparing cell proportions, we found that Mo and intMoMp were newly emerged cell types after retina I/R injury (Fig. 4E, F).

We then focused on the up-regulated genes and pathways in myeloid during retina I/R injury, and found that genes related to glial migration and activation increasing apparently, as well as the oxidative stress, iron death, and TNF pathways (Fig. 4G). Further analysis also showed that retina I/R led to rises in the inflammatory response scores and ferroptosis scores in myeloid (Additional file 1: Fig. S3C).

In summary, the glial cells mediate inflammation and ferroptosis during I/R through multiple mechanisms and interactions.

Aberrant cell–cell communication patterns may contribute to inflammatory tissue injury after inducing I/R

Cell-to-cell interactions orchestrate homeostasis and single-cell functions [23]. We explored intercellular signaling in I/R using CellChat, a tool that infers intercellular communication based on the expression of ligand–receptor pairs. Based on the pattern recognition method employed in CellChat, we first explored patterns shared by several cell populations to study how multiple cell groups and signaling pathways coordinated to function in normal retinal environment. The application of this analysis uncovered four outgoing (Fig. 5A) and four incoming (Fig. 5B) signaling patterns. A large portion of the outgoing retinal cell signaling was characterized by outgoing pattern #2 that represented multiple pathways, including TGFβ, FGF, IGF, and PSAP. Outgoing RGC signaling was characterized by outgoing pattern #3 that represented pathways, such as VEGF, IL2, and neurotrophin (NT; Fig. 5A). Target cell communication patterns (Fig. 5B) showed that incoming Mag signaling was dominated by incoming pattern #2 that included growth factor signaling (EGF, FGF, PDGF, VEGF, IGF), important for retinal lamination and photoreceptor development. Most incoming RGC signaling was characterized by incoming pattern #1, driven by the TGFb and Semaphorin 3 (SEMA3) pathways (Fig. 5B). These results showed that distinct retinal cell types (e.g., RGC and VEC) could rely on largely overlapping signaling networks. Certain cell types, such as glia and photoreceptor cells, simultaneously activated multiple growth signaling pathways, whereas immune cell types, such as T&DC and myeloid, relied on fewer signaling pathways.

Fig. 5figure 5

Analysis of cell–cell communication patterns differences between Blank and I/R. Sankey plots showing the inferred outgoing communication patterns of secreting cells (A) and incoming communication patterns of target cells (B), which shows the correspondence between the inferred latent patterns and cell groups, as well as signaling pathways. The thickness of the flow indicates the contribution of the cell group or signaling pathway to each latent pattern. C Heatmap shows the role and importance of each cluster in IGF signaling network (up). Bar plots showing the relative contribution of each ligand–receptor pair in IGF signaling pathway (down). D Circle plot showing the inferred IGF signaling networks in Blank group. E Heatmap shows the role and importance of each cluster in NT signaling network (up). Bar plots showing the relative contribution of each ligand–receptor pair in NT signaling pathway (down). F Circle plot showing the inferred NT signaling networks between Blank and I/R groups. G Circle plot showing the inferred SEMA3 signaling networks between Blank and I/R groups. H Violin plots showing the expression of genes related to SEMA3 signaling between Blank and I/R groups. I Violin plots showing the expression of genes related to TNF signaling between Blank and I/R groups. J Circle plot showing the inferred CCL signaling networks in I/R group

Next, we explored the effects of I/R on intercellular interactions. Previous studies have shown that canonical IGF signaling activation was required for retinal lamination and photoreceptor development [24, 25]. Indeed, centrality analysis-specific signaling network identified RBC as the most prominent source of the Igf1 ligand (Fig. 5C), acting on Mag. IGF pathways were only active in the blank group (Fig. 5D, Additional file 1: Fig. S3D). NT signaling has multiple neuroprotective functions, including preventing retinal damage, with the Bdnf–Ntrk2 ligand–receptor pair being a major signaling driver (Fig. 5E). Our data revealed that NT signaling action on CBC was reduced in the I/R group, driven by Bdnf and Ntrk2 in RGC and CBC, respectively (Fig. 5F, Additional file 1: Fig. S3E). Next, we explored the signaling pathways activated by RGC. It was reported that the SEMA3 family was implicated in regulating developmental aspects of the visual system by affecting RGC maturation and guiding the RGC into the superior colliculus [26, 27]. VEC and RGC were the primary ligand sources in the SEMA3 signaling network, acting both in autocrine and paracrine manners (Fig. 5G, Additional file 1: Fig. S3F). Notably, we found that I/R reduced the expression of genes related to the SEMA3 signaling pathway, mainly between VEC and RGC (Fig. 5G, H). These results suggested that I/R might attenuate normal growth signaling among retinal cells, leading particularly to changes in the maturation and function of glial cells, CBC, and RGC, and the resulting retinal damage.

We also explored the influence of myeloid on intercellular interactions. The pattern recognition analysis found that myeloid dominantly drove CSF and TNF signaling, indicated by outgoing pattern #4 (Fig. 5A). CSF signaling is critical for myeloid cell proliferation [28], while TNF signaling is involved in cell death and inflammatory activation of myeloid [29]. Both could induce inflammatory tissue injury following I/R. Interestingly, the TNF signaling pathway output differed between the blank and I/R groups, with myeloid in the blank group and Neutrophil in the I/R group (Additional file 1: Fig. S3G). Tnf (a ligand) and Tnfrsf1a and Tnfrsf1b (its receptors) were increased in myeloid and Mag cells (Fig. 5I), suggesting that I/R induced TNF signaling pathway activation in glial cells. The CCL signaling pathway is important for myeloid activation and migration. This pathway was only present in the I/R group (Fig. 5J). Neutrophil and myeloid were the primary CCL sources acting on myeloid, with the Ccl3–Ccr1, Ccl3–Ccr5, and Ccl4–Ccr5 ligand–receptor pairs being the main signaling contributors (Additional file 1: Fig. S3H). We found that I/R increased the expression of Ccl3, Ccl4, Ccr1, and Ccr5, mainly in myeloid (Additional file 1: Fig. S3I).

Altogether, these findings revealed that specific intercellular interactions were affected by I/R. The reduced nerve growth and visual system development signaling and increased immune cell activation signaling might be the basis for inflammatory tissue injury after I/R.

Ferrostatin-1 directly reduced retinal ferroptosis and enhanced RGC survival after I/R

Since our scRNA-seq data showed that I/R causes multi-cell ferroptosis, we hypothesized that targeting ferroptosis could mitigate tissue damage caused by I/R. Therefore, we evaluated whether ferroptosis inhibitor (Ferrostatin-1, Fer-1) could reverse I/R-induced tissue injury and RGC death. Retinas exposed to I/R displayed a significantly thinner inner plexiform layer (IPL) 7 days after reperfusion than normal retinas. Damage to the retina, particularly to the IPL, was significantly ameliorated by the Fer-1 treatment (Fig. 6B). RGC apoptosis is another important indicator of functional retinal damage. Immunofluorescence staining of retinal markers confirmed that the RGC number in the I/R mice 7 days after reperfusion was smaller than in the blank mice. Intravitreal Fer-1 injections significantly decreased the severity of retinal damage and the extent of RGC death (Fig. 6C, D).

Fig. 6figure 6

Inhibiting ferroptosis attenuated I/R injury and RGC loss. A Representative H&E-stained images among groups. B Bar plots showing the mean thickness of IPL among groups (n = 9/group). C Immunofluorescence image labeling RGCs in retina with Tuj-1 (green) and Brn3a (red), and the merge image of two channels were shown above (scale bar = 50 μm). D Bar plots showing the RGC survival rate among groups (n = 5/group). The mRNA expression levels of Ptgs2 (E), Slc7a11 (F), and Gpx4 (G) in retina cells were measured with real-time quantitative PCR. Retina lysates were collected and the proteins were subjected to western blot analysis to detect the level of GPX4 (β-actin was used as a control) (H, I). J Flow cytometry histogram showing the expression of ROS in retinal tissue. K MFI graph showing the expression of ROS in retinal tissue (n = 3/group). L Level of 4-HNE in retina tissue of among groups (n = 4/group)

Next, we studied the neuroprotective mechanism of Fer-1. The disturbed expression of ferroptosis-related genes (Ptgs2, Slc7a11, and Gpx4) was confirmed by real-time PCR. Ptgs2 and Slc7a11 were significantly upregulated after I/R. Ptgs2 was markedly downregulated, and Slc7a11 and Gpx4 upregulated when Fer-1 treatment was included (Fig. 6E–G). The increased expression of Gpx4, induced by Fer-1, was also confirmed by western blot (Fig. 6H, I). Since ferroptosis is a regulated cell death process caused by the unbalanced ROS production and degradation inside the cells. We next explored the effects of Fer-1 on the reactive oxygen species (ROS) and found that the I/R-induced increased ROS levels in the retina were reversed by the Fer-1 treatment (Fig. 6J, K). Furthermore, the Fer-1 treatment reversed the I/R-induced increase in 4-HNE, a ferroptosis metabolite (Fig. 6L). Collectively, treatment with Ferrostatin-1 could reduce I/R-induced retinal injury.

Ferrostatin-1 inhibited inflammation and cell activation in vivo and in vitro

To investigate whether fer-1 could alleviate the activation of macroglia following retinal I/R, we used GFAP, a specific marker of macroglia. Immunofluorescence results shows the expression of GFAP was gradually increased after retinal I/R and reached a peak at day 7 by the enlarged GFAP-positive cell body and the extending synapses from NFL to ONL. Whereas fer-1 treatment significantly inhibited the upregulation of GFAP expression (Additional file 1: Fig. S3J).

Previous studies have shown that inflammatory activation of IBA-1 positive cells was the main cause of function loss and RGC death. We have shown that I/R induced upregulation of inflammatory pathways and ferroptosis in IBA-1 positive cells. The cell–cell interactions demonstrated that I/R enhanced the migration and inflammatory activation of myeloid, as shown by the overactivation of the CCL and TNF pathways. We explored Fer-1 effects on inflammation and IBA-1 positive cells activation to further verify its protective effects against I/R damage. Notably, Fer-1 treatment significantly downregulated the mRNA levels of genes involved in IBA-1 positive cells activation and the inflammatory response, including cytokines (Il-1β, Il-6, and TNF-α) and chemokines (CCL3 and CCL4) (Fig. 7A–E). Immunostaining showed that the I/R-induced IBA-1 (a microglial activation marker) positive cells was remarkably attenuated by Fer-1 (Fig. 7F, G). The increase of CD11b+ cells in I/R and their decrease after Fer-1 treatment were also validated by flow cytometry (Fig. 7I, J). Notably, Fer-1 treatment reduced the ROS levels in the retinal CD11b+ cells (Fig. 7H). These results suggested that ferroptosis inhibition by Fer-1 protected against I/R-induced retinal injury by inhibiting IBA-1 positive cells activation and the inflammatory response in vivo.

Fig. 7figure 7

Inhibiting ferroptosis inhibited inflammatory response and cell activation in vivo and vitro. The mRNA expression levels of Il1b (A), Il6 (B), Tnfa (C), Ccl3 (D) and Ccl4 (E) in retina cells were measured with real-time quantitative PCR. F Immunofluorescence image labeling activated microglia with Iba1(red) is shown. Cell nucleuses were stained with DAPI (blue). G Statistical analysis of the proportion of IBA1+ cells among groups (n = 5/group). H Flow cytometry histogram (left) and MFI graph (right) showing the expression of ROS in retinal IBA1+ cells (n = 5/group). I Flow cytometry histogram showing the expression of CD11b+ cells in retinal tissue. J Statistical analysis of the proportion of CD11b+ microglia among groups (n = 3/group). K Primary retinal microglia lysates were collected and the proteins were subjected to western blot analysis to detect the level of GPX4 (β-actin was used as a control) among groups (n = 3/group). L Flow cytometry histogram (left) and MFI graph (right) showing the expression of ROS in purified microglia (n = 5/group). The mRNA expression levels of Il1b (M), Il6 (N), Tnfa (O), Ccl3 (P) and Ccl4 (Q) in microglia were measured with real-time quantitative PCR

Next, we tested whether Fer-1 had similar effects on microglia in vitro. We used flow cytometry to sort primary microglia to > 70% purity (Additional file 1: Fig. S4A, B). CCK8 assays assessed Fer-1 cytotoxicity in microglia. We found that Fer-1 showed no substantial cytotoxicity at concentrations ≤ 15 µg/ml (Additional file 1: Fig. S3K). Similarly, we examined the expression of GPX4 in vitro. Western blot showed that Fer-1 treatment could markedly up-regulate the expression of GPX4 in microglia after OGD/R (Fig. 7K). We then tested ROS release in primary microglia in vitro and found its level in the OGD/R group significantly higher than the blank group or following treatment with Fer-1 (1 µg/ml; Fig. 7L). In addition, OGD/R induced an increase in inflammatory genes Il-1β, Il-6, and TNF-α in microglia, which was reversed by treatment with fer-1 (Fig. 7M–O). Meanwhile, Fer-1 inhibited the OGD/R-induced upregulation of CCL3 and CCL4 (Fig. 7P, Q). Collectively, these results suggested that Fer-1 effectively alleviated microglia oxidative stress and inflammatory response in vivo and in vitro.

留言 (0)

沒有登入
gif