Single-cell analysis identifies Ifi27l2a as a novel gene regulator of microglial inflammation in the context of aging and stroke.

Single-cell analysis identifies Ifi27l2a as a novel gene regulator of microglial inflammation in the context of aging and stroke. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Single-cell analysis identifies Ifi27l2a as a novel gene regulator of microglial inflammation in the context of aging and stroke. Gab Seok Kim, Elisabeth Harmon, Manuel Gutierrez, Jessica Stephenson, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2557290/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Feb, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Microglia are key mediators of inflammatory responses within the brain, as they regulate pro-inflammatory responses while also limiting neuroinflammation via reparative phagocytosis. Thus, identifying genes that modulate microglial function may reveal novel therapeutic interventions for promoting better outcomes in diseases featuring extensive inflammation, such as stroke. To facilitate identification of potential mediators of inflammation, we performed single-cell RNA sequencing of aged mouse brains following stroke and found that Ifi27l2a was significantly up-regulated, particularly in microglia. The increased Ifi27l2a expression was further validated in microglial culture, stroke models with microglial depletion, and human autopsy samples. Ifi27l2a is known to be induced by interferons for viral host defense, however the role of Ifi27l2a in neurodegeneration is unknown. In vitro studies in cultured microglia demonstrated that Ifi27l2a overexpression causes neuroinflammation via reactive oxygen species. Interestingly, hemizygous deletion of Ifi27l2a significantly reduced gliosis in the thalamus following stroke, while also reducing neuroinflammation, indicating Ifi27l2a gene dosage is a critical mediator of neuroinflammation in ischemic stroke. Collectively, this study demonstrates that a novel gene, Ifi27l2a, regulates microglial function and neuroinflammation in the aged brain and following stroke. These findings suggest that Ifi27l2a may be a novel target for conferring cerebral protection post-stroke. Biological sciences/Neuroscience/Neuroimmunology Biological sciences/Neuroscience/Blood–brain barrier Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Main Microglia (MG) are resident macrophages in the central nervous system (CNS). Critically, MG feature extensive heterogeneity, with subtypes evident across different regions of the brain, across different developmental stages and ages, and between the sexes 1 , 2 . These various MG subtypes play a pivotal role in both initiating, and resolving inflammation, and act in coordination with other glial cells such as astrocytes, and oligodendrocytes. The MG response to inflammatory challenge and ischemic stroke is a crucial component for maintaining/restoring brain homeostasis, salvaging tissue, and minimizing brain damage 3 . However, MG in the aged brain are less effective at exhibiting proper immune responses than MG in younger animals and instead exhibit uncontrolled inflammatory responses 4 . This loss of competence contributes to the impairment of brain function and facilitates aging processes in the aged brain 5 , 6 . Selectively restoring MG functionality in older animals so that they mirror a less pro-inflammatory, more anti-inflammatory-like state may be an effective intervention to mitigate ischemic damage and facilitate improved functional recovery after stroke in aged mice. We performed scRNA-seq of young and aged brains of animals that underwent either sham surgery or permanent stroke. Using this unbiased approach, we discovered a gene, interferon alpha-inducible protein 27 like 2A ( Ifi27l2a) that was mildly upregulated in MG of the aged brain and significantly upregulated in MG following stroke, and even more elevated in the aged stroke brains. To the date, however, no specific role for Ifi27l2a in ischemic stroke has been described. Both interferons (IFN) and certain types of viral infection upregulate Ifi27l2a expression in the brain 7 , 8 . In non-glial cells Ifi27l2a protein enhances inflammation by blocking the action of nuclear receptors (NR4A) that normally act to promote expression of anti-inflammatory genes 9 , 10 . In the current study, we further demonstrate that reducing Ifi27l2a expression provides significant reduction of neuroinflammation and brain infarct following ischemic stroke. Together, these studies provide compelling new evidence that targeting Ifi27l2a expression or function may mitigate brain injury and inflammation following ischemic stroke. Results Ifi27l2a is highly upregulated after stroke in MG and aging significantly enhances this upregulation. To define the transcriptional signature across multiple cell types in the post-stroke brain, we performed scRNA-seq of young (3-month-old) and aged (20-month-old) male and female C57BL/6J mice subjected to permanent distal middle cerebral artery occlusion (pdMCAO) or sham surgeries (Table 1 ). The pdMCAO stroke model was used since it produces both primary injury (cortical infarct) and secondary injury in the thalamus 2-weeks post-stroke 11 . Since the cortex and thalamus also feature clear increases in microgliosis and astrogliosis following stroke, we included a brain region containing both peri-infarct cortex and thalamus for scRNA-seq study 11 . We evaluated differential gene expression (DGE) patterns, as an initial approach for determining how the molecular signature of cells within the young and aged brain change post stroke. To measure the effect of aging in stroked brains, we first integrated young stroke (AGGR2) and aged stroke (AGGR4) data into a single analysis (Seurat package 12 ) for analysis. Then, a single integrated analysis (data integration, PCA, UMAP and clustering, and DGE) was performed. Visualization of this merged dataset of 21,092 cells from the aged and young stroke mouse brain through dimension reduction by uniform manifold approximation and projection (UMAP) identified eight clusters of unique cell types based on gene expression differences. Identities were assigned to each of the eight clusters using the expression of conserved cell type markers, including microglia (MG, n = 7180) ( Trem2 ), oligodendrocytes (Oligo, n = 5149) ( Plp1 ), endothelial cells (EC, n = 3943) ( Cldn5 ), astrocytes (Astro, n = 1698) ( Aldoc ), lymphocytes (Lym, n = 1495) ( Plac8 ), epithelial cells (Epi, n = 1192) ( 1500015O10Rik ), vascular leptomeningeal cells (VLMC, n = 127) ( Dcn ) and vascular endothelial cells, venous (VECV, n = 89) ( Pglyrp1 ) (Fig. 1 a-b). Notably, the proportion of MG and Lym clusters were highly increased in the aged stroke brain, whereas the oligodendrocytes were reduced (Fig. 1 c). These findings are consistent with more extensive white matter injury in the aged stroke brain and correlate with increased MG-mediated neuroinflammation and lymphocyte infiltration. As we and others have demonstrated that MG are highly sensitive to inflammation and ischemic stress and act to regulate innate immunity in brains 3 , 13 , we focused our subsequent analysis on transcriptional changes within MG. Interestingly, our unbiased analyses of 21,092 cells (combined from young and aged stroke brains) showed that Ifi27l2a was the most highly upregulated gene in MG clusters in aged stroke, compared to young stroke (Table 2 ). The top five genes that were significantly upregulated in MG in the aged stroke brain included MG related genes ( Lgals3 , Lyz2 , Lgals3bp ) and another interferon-stimulated gene (ISG), Ifitm3 . Dot plots compared the expression level and percent of cells expressing the top five genes upregulated in aged stroke versus young stroke (Fig. 1 d). Within the MG cluster, there was a notable increase in the percentage of cells expressing Ifi27l2a between aged stroke and young stroke (62.6% vs 29.3%) (Fig. 1 d). Total normalized expression of Ifi27l2a from all cells showed increased Ifi27l2a expression in cells of aged stroke, compared to young stroke (Fig. 1 e). Ifi27l2a was more highly upregulated in MG of aged stroke brain, suggesting aging may act synergistically with ischemic stroke to promote Ifi27l2a expression in MG (Fig. 1 f). While most of the Ifi27l2a -expressing cells belonged to the MG cluster, Ifi27l2a expression was also detected in Lym and VLMC populations (Fig. 1 g). The VLMC showed increased Ifi27l2a expression with aged stroke, whereas stroke-induced Ifi27l2a expression in Lym was not markedly altered by aging. Other MG markers, such as Lgals3 , Ifitm3 and Lgals3bp , were also upregulated in MG and other cells following stroke (Fig. 1 h-j). In contrast, there was no synergistic effect of aging with stroke on C1qa expression, a MG marker gene (data not shown). As expected, a known marker of activated MG, Cst7 , was increased in aged stroke compared to young stroke brain ( Extended data Fig. 1 a), confirming that MG were more highly activated in aged stroke brains than in young stroke brains. In addition, we found significant upregulation of Apoe and Lyz2 , while Aif1 level appeared only slightly increased in MG in aged stroke compared to young stroke ( Extended Data Fig. 1 b-d). Taken together, the scRNA-seq data suggest an age-dependent upregulation of Ifi27l2a , which occurs predominantly in MG after stroke. scRNA-seq revealed that aging itself is sufficient to increase Ifi27l2a transcripts in MG. Following our finding that Ifi27l2a is upregulation following stroke in an age-dependent manner, we next sought to determine if aging alone impacts Ifi27l2a expression. Thus, we compared young and aged sham brains, integrating the young and aged sham operated samples (young sham - AGGR1, aged sham - AGGR3). Eight clusters were identified ( Extended data Fig. 2 a and 2 b), including oligodendrocytes (Oligo) ( Plp1 ), MG ( C1qa ), EC ( Cldn5 ), astrocytes (Astro) ( Gpr37l1 ), epithelial cells (Epi) ( Ttr ), lymphocytes (Lym) ( Nkg7 ), vascular smooth muscle cells, arterial (VSMCA) ( Des ), and B cells ( CD79a ). To determine how aging affects the transcriptional landscape in MGs, we compared the expression and percent of cells expressing the previously identified top five MG genes ( Ifi27l2a , Lgals3 , Ifitm3 , Lyz2 , and Lgals3bp ) in young and aged sham brains. All 5 genes that were upregulated in MG from aged stroke brain were also increased by aging alone ( Extended Fig. 2 c). Notably, Ifi27l2a transcript levels significantly increased with aging, as did Rps27rt . C1qa , on the other hand, was not dramatically altered between young and aged sham animals ( Extended data Fig. 2 d). We also confirmed the increased expression of Ifi27l2a in MG, Lym and B cell clusters in aged brains ( Extended data Fig. 3 a). The violin plots revealed modest upregulation of Ifi27l2a in MG in aged brain compared to young brains. Interestingly, we found significant age-dependent upregulation of ribosomal protein genes such as Rpl35 , Rps27rt , and Rps28 . This age-dependent upregulation of Rps27rt in all clusters, including MG and Lym ( Extended data Fig. 3 b), suggested aging-mediated changes in ribosomal complex composition in MG. Expression of two other genes associated with activated MG ( Aif1 and Il-1b ) were also modestly increased with aging ( Extended data Fig. 3 c-d). We repeated the same analyses comparing sham to stroke for aged ( Extended data Fig. 4 , 5 , 6) and young cohorts ( Extended data Fig. 7, 8 ). Together, these data suggest a synergistic effect of aging and stroke on Ifi27l2a expression. Disease-associated microglia (DAM) are present in the aged brain, and significantly increased following stroke. DAM are a recently discovered sub-population of MG found in the brains of various neurodegenerative diseases, such as AD, PD and ALS (REFs). We asked if DAMs are increased in the aged stroke brain. A recent study reported that homeostatic genes, such as C1qa, Ctss, Hexb , and Csf1r are not upregulated during the transition of MG into DAM, whereas other MG related genes ( Spp1, Cst7, Lpl , and Itgax ) are highly upregulated in DAM 14 . To determine whether a DAM-like MG subpopulation is increased in the aged or stroke brain, we compared the number and relative percentage of DAM in sham and stroke. The DAM subtype was defined by the elevated expression of Aif1, Spp1 , Cst7 , and Lpl among all MG (filter applied: Aif1 high and Spp1 high and Cst7 high and Lpl high , threshold by count). As expected, we did not detect DAM (0.0%) in young sham brains. However, we a small number of DAM in aged sham samples (0.9%) ( Extended data Fig. 9a ) shows that stroke increased the percent of DAM in both the young and aged brain (10.2% in young stroke vs 17.9% in aged stroke). These data show that MGs are converted to DAMs during aging, but are DAMs are significantly increased following stroke. Ifi27l2a is inversely correlated with DAM cell phenotype. We further analyzed our scRNA-seq data (aged sham and aged stroke) to determine whether Ifi27l2a plays a role in microglial activity, particularly in DAM. First, we examined whether Ifi27l2a expression correlated with expression of DAM-related markers, such as Lpl , Spp1 , Cst7 and Itgax . We subset MG into 4 different sub-clusters based on their levels of Ifi27l2a expression (normalized Ifi27l2a expression: 0.3–0.99, 1-1.99, 2-2.99, 3+). We consistently observed a negative correlation between Ifi27l2a and DAM related gene expression ( Lpl , Spp1 , Cst7 ) ( Extended data Fig. 9b ). Furthermore, segregating MG into either an Ifi27l2a “high” or “low” expressing cells followed by correlation analysis with known DAM genes and MG homoeostatic genes revealed a negative correlation between Ifi27l2a expression and phagocytosis/DAM related genes ( Lpl , Spp1 , Itgax , Cst7 , and Tyrobp ), but not homeostatic genes or other MG genes ( Extended data Fig. 9c ). Comparing the expression of DAM genes and homeostatic genes between “low” and “high” Ifi27l2a MG subpopulations revealed that DAM-related transcripts were significantly reduced in Ifi27l2a “high” MG. However, homeostatic genes ( Aif1, C1qc, Hexb , and Gapdh ) were either not changed or slightly increased ( Extended data Fig. 9c ). Furthermore, MG genes which are down-regulated in DAMs ( Csfr1, Olfml3, Trem119 , and P2ry13 ) were increased in Ifi27l2a “high” MG ( Extended data Fig. 9c ). Together, these data show a strong negative correlation between Ifi27l2a expression and a mature DAM transcriptional signature in MG. Regional Ifi27l2a expression with natural aging. While scRNA-seq showed that Ifi27l2a transcripts are enriched in MG and other cell types (e.g. Lym, VLMC) in both young and aged stroke brains, we lacked any data on whether there was a regional basis for these changes within the brain (e.g. within the primary injury in the cortex or within the secondary injury region occurring within the thalamus). The cortex and thalamus were extracted from the brains of naïve young (3 months, n = 4) and aged male mice (18–20 months, n = 4) to determine if there were regional differences in Ifi27l2a expression. Notably, Ifi27l2a mRNA was significantly upregulated in the aged thalamus (Fig. 2 a, p < 0.05 ). Ifi27l2a expression also approached upregulation in the cortex in aged brains ( p = 0.23). These findings agree with our earlier scRNA-seq finding and suggest normal aging increases Ifi27l2a expression in the brain. In addition, MG related genes Il-1b , Cst7 , and Tyrobp were markedly increased in either the thalamus or cortex of aged brains, further supporting an age-dependent increase in MG activation (Fig. 2 b-d). Transcripts for C1qb and Lpl , two genes which are known to be associated with microglia phagocytosis, were indistinguishable between the two stages (Fig. 2 e-f). These data indicate that Ifi27l2a is induced along with other genes associated with proinflammatory MG phenotype in the aged brain. Regional and temporal expression of Ifi27l2a in aged stroke brain. To provide regional and temporal expression of Ifi27l2a and other MG-related genes following stroke, we analyzed young and aged thalamus and cortex by qRT-PCR at 3 and 14 days post-stroke. As expected, Ifi27l2a was significantly elevated at three days (cortex) and two weeks (cortex and thalamus) after stroke, compared to sham (Fig. 2 i). We evaluated two other genes associated with MG activation ( Cst7 ) and reparative phagocytosis ( Tyrobp ), and which were found to be elevated in our scRNA-seq analysis. Both Cst7 and Tyrobp were increased in cortex and thalamus by two weeks post-stroke, but not by 3 days (Fig. 2 g-h). These findings suggest that Ifi27l2a expression is associated with the earlier phase of MG activation following stroke. The delayed expression in thalamus reflects the slower progression of the secondary injury mechanism. To provide spatial context to Ifi27l2a expression at the single-cell level, we profiled Ifi27l2a mRNA transcripts on mouse brain sections using single-molecule in situ hybridization (RNAscope). Probing for Ifi27l2a in aged sham and stroke brains revealed elevated transcripts in the peri-infarct area at 2 weeks post-stroke compared with sham-operated controls (Fig. 2 j-l). Combining RNAscope for Ifi27l2a with immunostaining for Iba1 confirmed that the majority of Ifi27l2a transcript is present in activated MG in the peri-infarct region of the aged brain (Fig. 2 m). MG represent the predominant source of Ifi27l2a expression after stroke. Our analyses of stroked brains at post stroke day (PSD) 3 and PSD 14 revealed a significant increase in Ifi27l2a mRNA. To determine whether MG represented the predominant source for the increased Ifi27l2a expression, we used PLX5622 treatment to deplete MG in mice prior to inducing stroke. PLX5622 is a CSF1R antagonist that eliminates CNS-resident MG 15 . CSF1R mediated signaling is required for MG survival and proliferation 16 , 17 . Mice were treated with PLX5622 for seven days. On day 7 of administration of PLX5622, pdMCAO was performed. The PLX5622 diet was continued for 3 days after stroke surgery to prevent repopulation by MG. At PSD 3, brains were isolated and analyzed by qRT-PCR (ipsilateral hemisphere) and immunostaining (contralateral hemisphere). As a control, mice were fed normal diet (ND) for the same period (Fig. 3 a). Notably, Ifi27l2a mRNA level was significantly reduced by 86% in PLX-stroked brains (ipsilateral hemisphere), compared to ND-stroked brains (Fig. 3 b, p < 0.05). The effectiveness of PLX5622 to eliminate MG in brains was confirmed by Iba1 immunofluorescence (Fig. 3 c-d) in the contralateral hemisphere. PLX5622 treatment resulted in a profound decrease in the number of MG in brains (Fig. 3 d). Moreover, PLX5622 treatment significantly reduced Tmem119 expression in brains after stroke, compared to naïve or normal diet administered brains (Fig. 3 e, p < 0.05, compared to naïve and ND-stroke). These data indicate that the induction of Ifi27l2a after stroke is primarily dependent on the MG population in the brain. MG induce Ifi27l2a/IFI27L2 expression with inflammatory stimuli. We next used cultured MG to evaluate the potential for inflammatory mediators to promote Ifi27l2a expression. First, we used mouse primary MG collected from the mixed glial cell culture obtained from P2 pups. Primary MG were treated with TNF-α (20 ng/mL) and IFN-γ (20 ng/mL) for 24 hours (to measure mRNA level of Ifi27l2a ) and 48 hours (to measure protein level of Ifi27l2a by ELISA with cell lysate). Both mRNA (Fig. 3 f) and protein levels (Fig. 3 g) of Ifi27l2a were significantly increased with treatment. To determine whether these findings extended to a human in vitro MG model, we challenged human microglial cells (HMC3) by addition of pro-inflammatory cytokines (TNF-α [20 ng/mL] and IFN-γ [20 ng/mL]) in combination with oxygen/glucose deprivation (inflammation/OGD). This inflammatory challenge induced a significant upregulation of IFI27L2 mRNA in HMC3s (Fig. 3 h, n = 5–6, p < 0.05). We found that human IFI27L2 protein level was dramatically induced at 20 hours post inflammation/OGD (Stim), compared to control treatment (Control) (Fig. 3 i, representative of n = 4). Given these results, we next tested if IFI27L2 protein was increased in the brains of patients that featured neuroinflammation. Sections from the brains of deceased patients without neurological disease (n = 2, female) and from stroke patients (n = 3, female) who also demonstrated cerebral amyloid angiopathy (CAA) pathology and tauopathy, in which neuroinflammation (microgliosis) is prevalent. Immunohistochemistry showed significant IFI27L2 expression in the stroke brain samples but low expression in age-matched control samples (Fig. 3 j, representative of n = 2–3). Together, these data show the responsiveness of Ifi27l2a (murine) and IFI27L2 (human) to inflammatory stimulation and the presence of elevated IFI27L2 in brain of patients with multiple forms of neuroinflammatory disease. Differential expression of Ifi27l2a in subtypes of microglia (MG) and macrophage (MΦ) populations in the aged brains following stroke. Given the extensive heterogeneity evident within MG and MΦ, we subjected the aged scRNA-seq datasets to more granular analysis to determine if Ifi27l2a expression profiles correlated with different functional roles. We ultimately identified a total of 28 clusters from brain cells of aged sham and aged stroke mouse brains, eight clusters of which were assigned an MG or monocyte/MΦ identity based on the expression of conserved cell markers ( Extended data Fig. 10 ). Two MG homeostatic clusters were identified based on the expression of MG genes such as Siglech, Tmem119, Gpr34, P2ry12 , and Selplg . These MG were annotated as Siglech homeostatic MG and P2ry12 homeostatic MG. We also identified two different MG that appeared to be in an activated status ( Rag + activated MG and Tyrobp + activated MG). Two Monocyte-Macrophage populations were also identified. We also found the disease-associated MG (DAM) like cluster showing high expression of Lpl , Itgax , Cst7 , and Spp1 . Note that these genes also correlate with the microglial genes and lipid metabolism genes upregulated in DAMs in other neurodegenerative diseases, such as AD 14 , 18 . Since we found that stroke and aging increase the expression of Ifi27l2a in MG, and that Ifi27l2a expression is negatively correlated with DAM genes, we asked whether expression levels and degrees of Ifi27l2a gene induction from sham to stroke in DAM would be different from MG in other sub-clusters. We therefore compared the degree of Ifi27l2a gene induction among MG sub-clusters in aged sham versus stroke brains (Table 3 ). Among the non-homeostatic MG clusters, Ifi27l2a induction in DAM (1.7 fold) is lower than any of the other activated MG. Ifi27l2a expression is sufficient to promote MG activation. Given the induction of Ifi27l2a in MG in aged brains and following stroke, we sought to elucidate the functional role of Ifi27l2a in MG-mediated neuroinflammation. Changes in microglial morphology is an early, quantifiable sign of inflammation in MG and MG functionality. Thus, we asked if Ifi27l2a expression alone (without additional inflammatory mediators) could induce a pro-inflammatory morphology in MG. We infected a murine microglial cell line (Sim-A9 cells) with a lentivirus where the Cx3cx1 promoter drove the expression of Ifi27l2a and an eGFP reporter, or a lenti-eGFP control. At 5 days post-infection, quantification of cell morphology showed that induction of Ifi27l2a expression caused an increase in the percentage of cells with a small, rounded shape (to a more amoeboid morphology or de-ramification) compared to lenti-eGFP control (Fig. 4 a-b). Interestingly, MG with higher Ifi27l2a expression (using eGFP intensity as a surrogate maker) showed more dramatic morphological changes compared to cells that had low Ifi27l2a/eGFP expression (Fig. 4 c). These results provide direct evidence that Ifi27l2a alone can initiate MG activation, even in basal conditions (i.e. inflammatory stimuli are not required). Ifi27l2a induces ROS production. Earlier reports showed evidence for Ifi27l2a localization in mitochondria within non-CNS cells 19 . We also detected increased IFI27L2 in the peri-nuclear membrane and in mitochondria in HMC3 cells (not shown), leading us to question whether Ifi27l2a could mediate mitochondrial dysfunction in MG. Thus, we asked if Ifi27l2a expression alone could initiate the reactive oxygen species (ROS) generation in activated MG. We used CellROX Red and MitoSox. First, we utilized CellROX Red, a detector of most ROS species, to determine if Ifi27l2a expression induces ROS production in Sim-A9 cells in unstimulated conditions. Quantification by flow cytometry revealed that Ifi27l2a overexpression alone promotes a significant increase in ROS production (Fig. 4 d, as expressed in median fluorescence intensity, MFI, Ctrl: lenti-eGFP control, Ifi27l2a: lenti-Ifi27l2a-eGFP, n = 4, * p < 0.05). Next, we only analyzed GFP positive cells, representing those with successful transduction. The ROS level was greater in Ifi27l2a expressing cells compared to eGFP only control cells (Fig. 4 e, Ctrl: lenti-eGFP control, Ifi27l2a: lenti-Ifi27l2a-eGFP, n = 4, * p < 0.05). We checked more specifically if mitochondria contribute as an Ifi27l2a-induced ROS source using Mitosox dye (specific indicator of mitochondria-derived ROS). Ifi27l2a overexpression resulted in a significant increase in mitochondria generated ROS level (Fig. 4 f) and the percentage of Mitosox + cells (Fig. 4 g). The “no-virus” cells (No) showed negligible effect on ROS levels. These data indicate that Ifi27l2a expression alone can cause ROS generation in mitochondria in activated MG, implying a causative role of Ifi27l2a in mitochondrial dysfunction in MG. Ifi27l2a hemizygous deletion is protective from ischemic brain injury in mice. Given our finding that increased Ifi27l2a expression alone is sufficient to promote microglial activation, we asked if limiting Ifi27l2a expression could reduce microglial activation and brain injury following stroke. We used a permanent distal middle cerebral artery occlusion (pdMCAO) stroke model in WT and Ifi27l2a +/- (Het) mice (2–3 month old, male). At post-stroke day (PSD) 3, the infarct volume was significantly reduced in Het, compared to WT brain (Fig. 5 a-b, n = 5 or 6, * p < 0.05). The area of activated MG (Iba1) was also reduced in the primary injury region at PSD 14 (Fig. 5 c-d, n = 5 or 6, * p < 0.05). The pdMCAO model 20 is also a well-established model for evaluating secondary injury in stroke; significant gliosis develops in the ipsilateral thalamus several days after the primary injury. We and others have shown significant gliosis in the ipsilateral thalamus 1 or 2 weeks following stroke 11 , 21 , 22 . Therefore, to evaluate the role of Ifi27l2a in secondary thalamic injury, we examined thalamic gliosis in WT and Het mice (2–3 months old, male) at PSD 14. Evaluation of the ipsilateral thalamus revealed significant reduction in both microgliosis (Fig. 5 e-f, n = 6, * p < 0.05) and astrogliosis (Fig. 5 g-h, n = 6 ** p < 0.01) in Het mice compared with WT. Note that the reduced injury in Het mice is not due to developmental differences in MCA territory. Analysis of vascular territory between WT and full Ifi27l2a KO revealed no difference ( Extended Data Fig. 11 , n = 6, p = 0.19). Together, these findings indicate that reducing Ifi27l2a expression can reduce primary and secondary injury associated with ischemic stroke, likely through attenuation of the microglial-mediated inflammatory response. Discussion We used scRNA-seq to explore the effects of aging and stroke at the cellular level in the brain. As a result of these studies, we identified Ifi27l2a as a gene that demonstrated significant age-dependent upregulation in the post-stroke brain. This novel initial finding led to further study related specifically to where and when Ifi27l2a was upregulated in the brain and to the functional role of Ifi27l2a in aging, stroke, and other neurodegenerative conditions. From these studies, we now present the following major new findings: 1) Ifi27l2a is highly upregulated in MG following stroke, particularly in aged brain. 2) Ifi27l2a is mildly upregulated by aging alone in MG. 3) Upregulation of Ifi27l2a following stroke occurs predominantly in MG. 4) Ifi27l2a expression and upregulation following stroke varies by MG subtype. 5) Ifi27l2a expression is inversely correlated with gene markers of DAM cell phenotype. 6) Expression of Ifi27l2a alone promotes MG activation and mitochondrial ROS production. 7) Reducing Ifi27l2a expression provides reduced MG activation and ischemic injury in an ischemic stroke model. When considered as a whole, we now propose that inflammatory stress (caused by the aging process, ischemic stroke or other) initiates Ifi27l2a gene expression predominantly in MG, which then enhances and propagates inflammatory damage throughout the brain. Further, our data suggest that the level of Ifi27l2a expression in MG may serve as a molecular switch that triggers pro-inflammatory phenotypes and dampens reparative phenotypes in aging and following stroke. We discuss what is known about Ifi27l2a function and elaborate on our major findings below. Interferons and interferon mediated signaling were originally identified as antiviral 23 , anti-proliferative and immunomodulatory mechanisms 24 that were induced by viral infection. These pathways are most commonly known to play pivotal roles in host defense against viral infection. Accumulated evidence has also shown a critical role for interferon signaling (especially Type I IFN, α and β) in regulating neuro-inflammation in aging and diseased brains, such as in the AD and stroke brain 25 – 28 . However, how or if IFN signaling (e.g. Type I or Type II) modulates Ifi27l2a expression directly in stroke brain, especially in aged brain, has not been previously described. It has been shown that stimulation with IFNα and β, known activators of IFN type I signaling, can induce Ifi27l2a expression in cortical neurons 8 and adipocytes 29 . However, it was unclear whether canonical Type I (α, β) or Type II (γ) IFNs could induce Ifi27l2a expression in microglia in a dish or in damaged brain to induce inflammation. Moreover, analysis of the Ifi27l2a promoter region (human ortholog, Isg12b) failed to show interferon-stimulated response elements (ISREs), which are thought to be required for interferon stimulated gene induction 29 . These findings suggested an alternative, non-canonical interferon-independent pathway for Ifi27l2a regulation, such as by microRNA or signaling via other foreign DNA/RNA sensing receptors. Indeed, our scRNA-seq data supports the notion of an interferon-independent pathway. We observed that while Ifi27l2a expression is markedly upregulated in MG, other representative Isg ( Mx1 , Mx2 , Ifi family such as Ifi27 , Ifi35 , and Ifnb1 , etc.) known to be upregulated by IFN response, especially type I Interferons (IFNα and β), were not measurably changed in MG. These findings suggested that another pathway (e.g. an IFN I independent pathway or combined signaling with IFN response and other intrinsic cellular signaling caused by ischemic or hypoxic insults) might be involved in the acute/chronic Ifi27l2a induction in MG. Such a scenario could be explained by the existence of other molecular hubs that relay the downstream signals to ultimately induce Ifi27l2a expression in MG after stroke. This possibility is supported by our scRNA-seq data showing significant upregulation of interferon regulatory factor 7 (IRF7) in MG from aged brain following stroke, whereas other IRFs were not markedly changed (data not shown). Moreover, in the series of in vitro experiments with primary MG treated with pro-inflammatory cytokines, a positive correlation was found between Ifi27l2a and IRF7 , implying that IRF7 signaling may contribute to Ifi27l2a expression in activated MG. Interestingly, using TRANSFAC, a tool for transcriptional analysis, we found a putative IRF7 binding motif in the promoter of Ifi27l2a , suggesting that IRF7 may act as a key transcription factor to induce the Ifi27l2a gene expression in the inflammatory situation in microglia and other cells in brains. Further experiments will be required to specifically test the role and involvement of IRF7-mediated transcriptional regulation on Ifi27l2a expression. Outside of the CNS, a limited number of reports have suggested a role for Ifi27l2a in facilitating inflammation though its interaction with other cellular partner proteins. During conditions of inflammation, it was shown that the Ifi27l2a protein is rapidly expressed and interacts with nuclear receptor 4A (NR4A) family members. The NR4A family is thought to support expression of multiple genes involved in attenuating inflammation in various kinds of cells 30 – 32 . Binding between Ifi27l2a and NR4A in the nucleus results in the export of NR4A to the cytosol, and thus the removal of a driver of anti-inflammatory and cytoprotective gene expression 10 . This model of NR4A regulation could also explain the novel role of Ifi27l2a in MG after stroke. In support of this possibility, a separate study showed that MG-specific Nr4a1 knockout alone promoted inflammation and microglial activation as well as increased pathology in the experimental autoimmune encephalomyelitis mouse model (EAE) 33 . Interestingly, Nr4a1 was also shown to play a critical role in maintaining an anti-inflammatory state of macrophages via attenuating NF-kB mediated pro-inflammatory gene expression 34 . Moreover, it was revealed that if Nr4a1 is deleted in myeloid cells such as macrophages, more pro-inflammatory cytokines are produced 35 . It was recently shown that NR4A may also regulate phagocytosis via Mer tyrosine kinase (MerTK) gene expression in the cardiac repair process 36 . MerTK is a member of the MER/AXL/TYRO3 receptor kinase family, which is known to regulate phagocytic capacity in MG and MΦ. If other phagocytosis-related genes such as Axl and anti-inflammatory cytokines are also direct targets for NR4A, it is possible that lowering the expression level of Ifi27l2a might boost MG phagocytic capacity or promote phenotypical changes to DAM via promoting reparative phagocytosis related genes such as Axl . Indeed, our scRNA-seq data showed an inverse correlation between Ifi27l2a and Axl , indicating that lower Ifi27l2a expression may be a characteristic of the non-inflammatory MG phenotypes. We also found higher expression of Nr4a1 in DAM and one of the homeostatic MG clusters. Overall, our data support the novel working model that Ifi27l2a regulation of Nr4a1 contributes to the phenotypic polarization of microglia in natural aging and in brain pathology. If our model is correct, the interaction of Ifi27l2a and Nr4a1 would represent a novel therapeutic target for reducing brain inflammation. The other reported mechanism by which Ifi27l2a acts involves regulation of apoptosis. Studies in activated MG and other cells showed that Ifi27l2a can be shuttled to the mitochondria membrane, where it initiates a mitochondria-dependent apoptosis process 37 , 38 . Our study also supports this possibility wherein Ifi27l2a can act as an initiator for mitochondrial dysfunction by producing ROS. The mode of action of Ifi27l2a may also be regulated by its subcellular destination. With regard to the potential to trigger apoptosis and inflammation, we speculate that with more severe or prolonged MG activation, Ifi27l2a accumulation at the mitochondrial membrane might initially contribute to the MG inflammatory change, and then later trigger MG apoptosis. One intriguing hypothetical scenario is that high Ifi27l2a expression or mitochondrial targeting of Ifi27l2a contributes to the eventual termination of inflammatory MG. At this time, however, the potential role of Ifi27l2a in regulating apoptosis of MG after stroke has never been explored. Our comparison of young and aged non-stroke brains (shams) showed an age-dependent upregulation of Ifi27l2a in MG, Epi, and B-cell populations in the brain. Expression of Ifi27l2a in these cell populations went from undetectable expression in young brain to moderate expression in aged brain. How aging promotes increased Ifi27l2a expression in these clusters is unknown. Since Ifi27l2a is among the known interferon stimulated genes (Isg) that can be upregulated by IFN-mediated pathways (viral infection or by inflammatory pathways 39 , 40 ) chronic low-level activation of any of these pathways might promote the observed age-dependent increase in Ifi27l2a expression. However, given that the mice were housed in a specific pathogen free (SPF) facility, it is most likely that the increase we observed is due to low-level chronic inflammation that is known to exist in the aged brain 41 , 42 . Expression of Ifi27l2a differed among the MG sub-clusters in the basal level of Ifi27l2a expression in aged sham brain and degree of Ifi27l2a upregulation following ischemic stroke. Expression levels of Ifi27l2a in sham brain were low in homeostatic subclusters and resulted in less upregulation in the post-stroke brain compared with activated MG subclusters. The activated subclusters showed 2.1–3.5 fold higher Ifi27l2a expression compared with homeostatic subclusters following stroke. The greater expression level in activated MG suggests a potential role for Ifi27l2a in microglial activation and proliferation. Ifi27l2a expression in two other MG subclusters is discussed further below. Our data showed an inverse correlation between Ifi27l2a expression and reparative MG genes, which are now recognized as DAM genes. This clear relationship in aged stoke brain suggests that Ifi27l2a could also be a key determinant for inducing DAM phagocytic activity or DAM phenotypical changes from non-activated or activated MG. It was further notable that the inverse correlation held up with groups of genes that are related to maintaining MG homeostasis and the DAM phenotype. These findings suggest that Ifi27l2a expression level may contribute to expression of genes in MG related to reparative and phagocytic function. Future study will be required to determine if the reduced Ifi27l2a expression is causative versus merely correlative for this MG phenotype. In summary, using unsupervised scRNA-seq, we have found a significant increase in Ifi27l2a expression in MG following stroke, with particular upregulation in the aged stroke brain. Our data further show that mild Ifi27l2a upregulation even occurs with aging alone. We present evidence for a new model of MG phenotype regulation, wherein Ifi27l2a acts as a novel molecular regulator of microglial phenotypical changes and function. Based on the data we present here, we propose that elevated expression of Ifi27l2a contributes to a pro-inflammatory MG phenotype (producing more ROS and proinflammatory cytokines in MG) and reduced Ifi27l2a enables a non-inflammatory or phagocytic phenotype. Also we speculate that the functional role of Ifi27l2a is at least partly through negative regulation of Nr4a1-mediated gene transcription. In total, these findings suggest that targeting of Ifi27l2a expression or Ifi27l2a protein function in MG could be a novel strategy for regulating neuroinflammation in aging, stroke, or other neurodegenerative diseases to promote better functional recovery. Methods Animals. All procedures were performed in accordance with NIH guidelines for the care and use of laboratory animals and were approved by the Institutional Animal care and use committee of the University of Texas Health Science Center. Sperm from Ifi27l2a −/− KO mice [Ifi27l2atm1(KOMP)Vlcg] (REF) were obtained from the Diamond laboratory at Washington University in St. Louis and used for in vitro fertilization of WT (C57BL/6J) eggs (Genetically engineered rodent models core, Germ core, BCM). Resulting heterozygous Ifi27l2a +/− progeny were backcrossed to establish the Ifi27l2a −/− colony. Male and female mice in a C57BL/6J background (11–14 weeks old: young, 18–22 months old: aged) were used for all experiments. All animals were housed in the animal care facility at University of Texas Health Science Center and had ad libitum access to food and water and were maintained on a 12:12 light: dark schedule. Permanent distal middle cerebral artery occlusion (PDMCAO) model. C57BL/6J mice of both sexes were used for scRNA-seq at 11–14 weeks or 18–22 months of age. PDMCAO was induced by permanent ligation of the right distal middle cerebral artery (MCA) using a micro-coagulator (Accu-temp) 11 . Mice were anesthetized with isoflurane (4% induction and 2% maintenance in airflow) and body temperature was maintained at 37°C by feedback-controlled heating pad and rectal temperature probe. Bupivacaine (0.25% at 1ml/kg) was injected subcutaneously (s.c.), prior to any skin incision 43 . The distal MCA was accessed via a craniotomy and permanently occluded just proximal to the anterior and posterior branches by electrocoagulation. Sham controls were generated with same procedure without electro-coagulation of the MCA. For microglia depletion experiments, we used PLX5622, a CSF1R antagonist (REF). PLX5622 was provided by Plexxikon Inc. (Berkeley, CA) and formulated in AIN-76A standard chow at 1200 ppm by Research Diets Inc. PLX5622 was administrated for 7 days prior to the PDMCAO procedure and continued for 3 days after stroke. At 3 days after surgery, brains were isolated and ipsilateral hemisphere was used for RNA isolation and qRT-PCR analysis. The contralateral hemisphere was used for immunostaining. Brain sample preparation for single-cell RNA sequencing. We processed brains from young and aged mice subjected to either sham or PDMCAO surgeries (Table 1 ). 14 days post PDMCAO (or sham surgery), Anesthetized mice were transcardially perfused with heparinized PBS (10 U/mL). Brains were removed from the skull and sliced coronally into 3 mm-thick blocks (from a region spanning + 1 to -2 mm from bregma), covering the cortical infarction and secondary thalamic injury site 11 . The brain slice was then minced with a razor blade and subjected to the brain tissue dissociation protocol (Miltenyi Biotec, Gladbach, Germany). Minced tissue was then incubated a collagenase/dispase mixture (150 µL of 1 mg/mL in 2 mL) for 30 minutes at 37˚C in a gentleMACS Octo Dissociator (Miltenyi Biotec, Bergisch Gladbach, Germany) using the pre-installed program for adult brain dissociation. Myelin was removed using debris removal solution. Red blood cells were lysed and removed with red blood cell lysis solution. The final cell suspension was stained with trypan blue and live cells were counted using Countess II FL Automated Cell Counter (Thermo Fisher scientific, USA). GEM generation, library construction, and sequencing. The 10X Genomics Chromium™, Single-Cell RNA-Seq System (10X Genomics, Pleasanton, CA) was used to prepare cells for scRNA-seq. Brain single cell suspensions were processed to generate barcoded cDNA libraries using GEM gel bead, Chip kit, and library kits (10X Genomics, Pleasanton, CA) as per the manufacturer’s instructions. Cells were partitioned with beads containing reagents (primers and RT) required for generating 10X barcoded cDNA in individual cell using Chromium™ controller. The resulting cDNA libraries were sequenced with NextSeq500/550 Hi Output Kit v2.5 (75 Cycles, 20024906) on an Illumina NextSeq 500 System. Sequencing data processing and analysis. The cell ranger pipeline (10X genomics, Pleasanton, CA) was utilized to map the sequences to mouse reference genome (mm10), and to process barcode containing sequence data, aligning the read and generating feature barcode matrices that could be further processed by the Seurat package 12 using R. We also used cellranger aggr pipeline to combine outputs from multiple samples into one output file. AAGR1 (5,706 total cells analyzed) was a combined population consisting of “sham brains of young male and young female” mice. AAGR3 (5,174 total cells analyzed) was a combined population consisting of “sham brains of aged male and aged female” mice. AAGR2 (12,866 total cells analyzed) was a combined population consisting of “Stroke brains from young male and young female” mice. AAGR4 (total 8,226 cells analyzed) was a combined population consisting of “Stroke brains from aged male and aged female”. Reads were mapped to the mm10 murine transcriptome (10X genomics, Pleasanton, CA). We used Seurat 3.1 44 to analyze scRNA-seq data for clustering, and DEG identification between clusters and between the two groups. Briefly, log-normalization using NormalizeData was utilized. Feature counts for each cell were divided by total counts for the cell and multiplied by the scale factor (10,000). Then using log1p , data was natural log-transformed. The Uniform Manifold Approximation and Projection (UMAP) dimensional reduction technique (UMAP) was used for dimensional reduction and clustering was carried out using FindNeighbors and FindClusters with the resolution parameter either at 0.02 (generating 6–7 clusters) or at 1 (generating 25–27 clusters). Conserved cell type markers in each cluster were identified by using FindConservedMarkers. The name and level of genes that were differentially expressed in each cluster was determined using FindMarkers. Metadata and normalized read count data was extracted from Seurat objects and fed into Excel to further identify the critical genes (top 10 genes or top 50 genes) that were up- and down-regulated in each cluster and to find the correlation between levels of Ifi27l2a and other MG genes. Single molecule in situ hybridization (RNAscope). The RNAscope fluorescent multiplex assay (Advanced Cell Diagnostics, Newark, CA, USA) was performed according to manufacturer’s instructions with 2 week post-stroke brains of aged mice (18–20 months) and aged sham to probe Ifi27l2a transcripts in brain cells. The murine Ifi27l2a probe was designed by ACD Biosystems, based on their own criteria. Brain sections (PFA fixed, 30-µm thickness) from the 2-week post stroke brain and sham brains of aged mice (18–20 month old) were hybridized with Ifi27l2a probes for 2 hours at 40˚C. At the same time, ACD 3-plex positive control and negative control probes were incubated on one brain section to confirm signal specificity. The probes were amplified according to the manufacturer’s instructions and labeled with Opal-570 Red fluorophore (Akoya Biosciences, Marlborough, MA, USA). DAPI was used to label nuclei. Images were taken with a fluorescent microscope (Leica DMi8 fluorescence microscope system, Leica Biosystem, IL, USA) and a confocal microscope (Leica TCS SPE confocal system, Leica Biosystem, IL, USA). Multiple images were captured with the 10X objective covering the hemisphere and stitched to generate a single image (Leica LAS X software). HMC3 cell culture. Human microglial cell line 3 (HMC3) cells were purchased from ATCC (CRL-3304, USA) and cultured in Dulbecco's Modified Eagle's Medium (DMEM) (Thermo Fisher Scientific, Waltham, MA, USA) containing 10% fetal bovine serum, 20 ng/mL recombinant human M-CSF1 (Tonbo Biosciences, San Diego, CA, USA) and antibiotics (Pen/Step) in 5% CO 2 and 37ºC. Brain processing and immunostaining. For detecting Iba1 in PLX- or normal diet-treated mouse brains and gliosis (Iba1 and Gfap) in the thalamus following stroke, we performed immunostaining as previously described 11 . Cardiac perfusion with PBS, followed by 4% PFA (paraformaldehyde in PBS) were performed to clear the blood in brains. Perfused brains were then submerged in 30% sucrose in PBS for 24 hours at 4ºC prior to sectioning at 30 µm thickness (Micron HM 450, Thermo Fisher Scientific, Waltham, MA, U.S.A.). Sections corresponding to − 2 mm from bregma, which contain hippocampus and thalamus, were washed with PBS, incubated with blocking buffer (10% goat serum, 0.3% Trion X-100 in PBS), and then incubated overnight at 4ºC with the following primary antibodies: Rabbit anti-Iba1 antibody (1:200) (Wako Pure Chemical, Japan), mouse anti-GFAP antibody-cy3 (1:500) (Millipore Sigma, MO, USA). We used either donkey anti-rabbit IgG-Alexa 594 or 488 (1:200, Thermo Fisher Scientific, Waltham, MA, USA) to recognize rabbit anti-Iba1 antibody. Sections were incubated with DAPI (4′, 6-diamidino-2-phenylindole) to label nuclei. Images were obtained using a Leica TCS SPE confocal system and a Leica DMi8 fluorescence microscope system (Leica Biosystem, IL, USA). Images were captured using a 10X objective. Higher magnification images of selected regions were collected using 20X or 40X objectives. Image analysis was performed using Image J software (National Institutes of Health). Lentivirus infection and ROS measurement by flow cytometry . Control lentivirus (Cx3cr1-IRES-eGFP, initial titer-1.55×10 8 TU/ml) and Ifi27l2a expressing lentivirus (Cx3cr1-Ifi27l2a-IRES-eGFP, initial titer- 1.07×10 8 TU/ml) were generated (GeneCopoeia, Rockville, MD, USA) and these virus went through in-house quality control and validation. Sim-A9 cells, a microglia-like cell line, was transduced with control lentivirus (eGFP alone) or Ifi27l2a expressing lentivirus at 2 MOI using polybrene (Millipore Sigma, St. Louise, MO, USA). Five days after infection, cells were incubated with CellRox (Thermo Fisher Scientific, Waltham, MA, USA) for ROS detection or MitoSox (5 \(\mu\) M) (Thermo Fisher Scientific, Waltham, MA, USA) for mitochondrial derived ROS detection for 10 minutes at 37˚C. Cells were analyzed using a CytoFLEX S flow cytometer (Beckman Coulter Life Science, Indianapolis, IN, USA). For analysis, a gating strategy was applied first to remove debris using forward (FSC-A) and side scatter (SSC-A). Doublets were also excluded from analysis by FSC-height and width. CellRox Deep Red signal (excitation/emission; 644/665) was collected in the channel (BP 660/20) and the MitoSox Red signal (excitation/emission; 510/580 nm) in the channel (BP 585/42). Data were exported and analyzed with FlowJo software (FlowJo, Tree Star Inc., Ashland, OR, USA). The geometric mean of fluorescence intensities (MFI) and percentage of positive cells were calculated and expressed. Mouse Ifi27l2a ELISA. To check the intracellular levels of Ifi27l2a protein in primary microglia, the murine interferon alpha-inducible protein 27-like protein 2A (Ifi27l2a) was quantified by ELISA following the manufacturer’s recommendations (Abbexa, Cambridge, UK) after washing the cells with PBS two times and collecting lysates in RIPA lysis buffer. Real-Time quantitative RT-PCR. To validate the findings of scRNA-seq data, we performed qRT-PCR. Brains from naive young (3 mons) and aged mice (18–20 mons), or brains from sham and stroked mice (PSD 3 or PSD 14) were harvested and dissected to obtain both cortex and thalamus. For the PLX5672 treatment experiment, the ipsilateral hemisphere was collected instead. Total RNA was purified with TRIzol™ Reagent (Thermo Fisher Scientific, Waltham, MA, USA) using the RNeasy Mini Kit (Qiaqen, Germantown, MD, USA) according to the manufacturer’s instructions. Purity of RNA (> 1.7 at 260/280) and concentration of purified RNA were measured by Nano-drop Spectrometer and 1 µg of RNA was used to generate cDNA with iScript™ Reverse Transcription Supermix (Bio-Rad, Hercules, CA, USA). The SsoAdvanced Universal SYBR Green Supermix (Bio-Rad, Hercules, CA, USA) was used to detect newly amplified amplicons with a C1000 Touch Thermal Cycler CFX96 Real-Time System (Bio-Rad, Hercules, CA, USA). The PCR cycles were as follows: initial denaturation at 95˚C for 30 sec, followed by 40 reaction cycles of 95˚C for 5 sec, 56˚C for 10 sec, and 72˚C for 10 sec. To quantify relative gene expression, we used the ΔΔCt method using Ct values for the gene of interest normalized to GADPH. Data was expressed as fold change relative to control samples. Primer sequences are provided in Extended data Table 1 . Statistical data analysis. Statistical data analysis was performed using Prism 7.0.3 (GraphPad Software, San Diego, CA, USA) and R in Rstudio environment with p < 0.05 considered statistically significant. Data are presented as the mean ± standard error of the mean (SEM), and analyzed using an unpaired t-test (for two group comparisons) or a one-way ANOVA with Tukey post-hoc test for multiple comparisons. Declarations Acknowledgements This project was funded by UTH startups, NIH AG072488 to GSK, NIH R56NS120709 to SPM and the Huffington foundation. Author Contributions S.P.M., L.D.M. and G.S.K. conceived the experiments. G.S.K., E. H., J.M.S., M.C.G., A.B., A.C., J.L., A.D., Z.W., and T.W. performed the experiments. G.S.K., and S.P.M. analyzed the results. S.P.M., G.S.K., J.E.J., J.D.W. and L.D.M. discussed the results. G.S.K., E.H. and S.P.M. made the figures and wrote the manuscript. All authors reviewed the manuscript. References Hammond, T. R. et al. 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Stuart, T. et al. Comprehensive Integration of Single-Cell Data. Cell 177 , 1888–1902 e1821, doi: 10.1016/j.cell.2019.05.031 (2019). tables Table 1 scRNA-seq samples analyzed Young Aged Sample Sham (n = 2) Stroke (n = 4) Sham (n = 2) Stroke (n = 4) Name AGGR1 AGGR2 AGGR3 AGGR4 # of cells analyzed 5706 12866 5174 8226 Table 2. Identification of Ifi27l2a as a top gene that is upregulated in MG in aged stroke Table 3 Differential expression of Ifi27l2a in each MG sub-clusters in sham and stroke in aged brains MG sub-clusters Aged Sham (expression level) Aged Stroke (expression level) Average_FC Homeostatic MG_1-Siglech+ 1.419 2.489 1.856 Homeostatic MG_2-P2ry12+ 1.279 1.815 1.419 DAM like sub-cluster 2.762 4.910 1.777 MG_Activated_1 1.931 5.251 2.718 MG_Activated_2 2.272 6.276 2.761 MG_Progenitor 3.290 7.628 2.318 Additional Declarations There is NO Competing Interest. Supplementary Files Extendeddatafigurelegendsandtable02032023.docx Extended data figure legends and table Cite Share Download PDF Status: Published Journal Publication published 14 Feb, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2557290","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":175907651,"identity":"393e793d-84d5-4778-825a-99374447e253","order_by":0,"name":"Gab Seok 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18:56:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2557290/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2557290/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-56847-1","type":"published","date":"2025-02-14T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":33002847,"identity":"8169e066-1d04-407a-82e3-ead7602b04a8","added_by":"auto","created_at":"2023-02-15 22:52:29","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":474829,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003escRNA-seq identification of cell clusters and upregulation of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eIfi27l2a\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e in young and aged brains after stroke with distinct transcriptional signatures. (a)\u003c/strong\u003e UMAP plot shows the clusters in young and aged stroke (Seurat \u003cem\u003eFindClusters\u003c/em\u003e resolution at 0.02). MG; microglia, Oligo; oligodendrocytes, EC; endothelial cells, Astro; astrocytes, Lym; lymphocytes, Epi; epithelial cells, VLMC: vascular leptomeningeal cells, VECV; vascular endothelial cells, venous \u003cstrong\u003e(b) \u003c/strong\u003eFeature plot verifying clustering assignments by representative cell specific marker gene expression (Trem2; MG, Plp1; Oligo, Cldn5; EC, Aldoc; Astro, Plac8; Lym, 1500015l10Rik; Epi, Dcn; VLMC, Pglyrp1;VECV). \u003cstrong\u003e(c)\u003c/strong\u003e Pie plot showing the percentage of total for each cluster in young stroke and aged stroke. \u003cstrong\u003e(d)\u003c/strong\u003e \u003cem\u003eLgals3bp\u003c/em\u003e, \u003cem\u003eLyz2\u003c/em\u003e, \u003cem\u003eIfitm3\u003c/em\u003e, \u003cem\u003eLgals3\u003c/em\u003e, and \u003cem\u003eIfi27l2a\u003c/em\u003e were identified as the most highly expressed genes in aged stroke (red dot, aged stroke), compared to young stroke (blue dot, young stroke). Dot size indicates the percent of cells that express the respective gene in the cluster. \u003cstrong\u003e(e)\u003c/strong\u003e Normalized \u003cem\u003eIfi27l2a\u003c/em\u003e expression from total cell population in young stroke (12,708 cells) and aged stroke (8,165 cells). The overall expression of \u003cem\u003eIfi27l2a\u003c/em\u003e was greater in aged stroke. **** \u003cem\u003ep\u003c/em\u003e \u0026lt;0.0001 unpaired \u003cem\u003et\u003c/em\u003e-test. \u003cstrong\u003e(f)\u003c/strong\u003e Feature plots showing the distribution of \u003cem\u003eIfi27l2a\u003c/em\u003e, \u003cem\u003eIfitm3\u003c/em\u003e, and \u003cem\u003eC1qa\u003c/em\u003e in MG of young and aged stroke brains. Violin plots showed the increased expression of \u003cstrong\u003e(g)\u003c/strong\u003e \u003cem\u003eIfi27l2a,\u003c/em\u003e \u003cstrong\u003e(h)\u003c/strong\u003e \u003cem\u003eLgals3\u003c/em\u003e, \u003cstrong\u003e(i)\u003c/strong\u003e \u003cem\u003eIfitm3 \u003c/em\u003eand \u003cstrong\u003e(j)\u003c/strong\u003e \u003cem\u003eLgals3bp \u003c/em\u003eon cell type-specific in young and aged stroke (showing increased \u003cem\u003eIfi27l2a \u003c/em\u003eexpression in MG, Lym, and VLMC clusters in aged stroke samples).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2557290/v1/5d31b257b40d087d868b75a7.jpeg"},{"id":33002845,"identity":"00eebc8a-a26d-4997-a90b-eedbb55f8cc5","added_by":"auto","created_at":"2023-02-15 22:52:29","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":565097,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRegional increases of\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eIfi27l2a\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e expression in brain with normal aging and in post-stoke brains.\u003c/strong\u003e RNA was isolated from thalamus and cortex of young and aged brains for qRT-PCR analysis of \u003cstrong\u003e(a)\u003c/strong\u003e \u003cem\u003eIfi27l2a\u003c/em\u003e and other genes associated with MG phenotype: pro-inflammatory genes \u003cstrong\u003e(b)\u003c/strong\u003e \u003cem\u003eIL-1β\u003c/em\u003e, \u003cstrong\u003e(c)\u003c/strong\u003e \u003cem\u003eCst7\u003c/em\u003e and phagocytosis related genes \u003cstrong\u003e(d)\u003c/strong\u003e \u003cem\u003eTyrobp\u003c/em\u003e, \u003cstrong\u003e(e)\u003c/strong\u003e \u003cem\u003eC1qb,\u003c/em\u003e and \u003cstrong\u003e(f)\u003c/strong\u003e \u003cem\u003eLpl\u003c/em\u003e. Data presented as mean ± SEM (n = 4-6 mice per group). * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p\u0026lt; 0.001 by two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test. RNA was isolated from the cortex and thalamus of sham control or aged stroked mice at 3 days (3D) and 14 days (2W) after stroke for qRT-PCR analysis. Summary of fold change in expression for \u003cstrong\u003e(g)\u003c/strong\u003e\u003cem\u003e Cst7 \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(h)\u003c/strong\u003e\u003c/em\u003e \u003cem\u003eTyrobp, \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(i)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Ifi27l2a\u003c/em\u003e. Data presented as mean ± SEM (n = 4-6 mice per group). * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, compared to sham cortex (Sh-Cor) or Sham Thala (Sh-Thala), # \u0026lt;0.05, compared to 3D-Thala by two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test. RNAscope assay shows regional and MG-specific expression of \u003cem\u003eIfi27l2a\u003c/em\u003e in aged brain after stroke. \u003cstrong\u003e(j)\u003c/strong\u003e A representative stitched image showing \u003cem\u003eIfi27l2a\u003c/em\u003e transcripts (red dots) in the peri-infarct area of aged brain at 2 weeks after stroke. \u003cstrong\u003e(k, i) \u003c/strong\u003eHigher magnification comparing \u003cem\u003eIfi27l2a \u003c/em\u003eexpression in aged sham vs. aged stroke brain. Images representative of 4 mice, each group. Scale bar = 10 um. \u003cstrong\u003e(m)\u003c/strong\u003e Confocal imaging showing \u003cem\u003eIfi27l2a \u003c/em\u003emRNA expression as well as Iba1 immunofluorescence (marker for activated MG) from the peri-infarct region. Examples of MG expressing \u003cem\u003eIfi27l2a\u003c/em\u003e are indicated by solid white arrows. Scale bar = 10 um.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2557290/v1/f141626a09274614eda518ed.jpeg"},{"id":33003157,"identity":"300ec3ca-4f92-4bcc-ba86-a2979e5b63c4","added_by":"auto","created_at":"2023-02-15 23:08:29","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":616688,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMG represent the primary source of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eIfi27l2a\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e upregulation following stroke.\u003c/strong\u003e Depletion of brain MG with PLX5622 eliminates the stroke-induced increase of \u003cem\u003eIfi27l2a\u003c/em\u003e expression. Brain \u003cem\u003eIfi27l2a\u003c/em\u003e expression is reduced in PLX5622 treated mice after stroke. \u003cstrong\u003e(a)\u003c/strong\u003e Summary of experimental timeline and procedures. PLX5622 treatment is used to deplete the brain MG population. The brain hemisphere ipsilateral to the stroke was used for quantitative real-time PCR analysis, while the contralateral hemisphere was sliced for immunostaining to quantify MG depletion. Brains were evaluated at post-stroke day 3 (PSD 3). \u003cstrong\u003e(b) \u003c/strong\u003e\u003cem\u003eIfi27l2a\u003c/em\u003e expression was significantly reduced in PLX-treated mouse brains following stroke compared to ND-stroke. n=2, Naïve; n=3-4, PLX treated.\u003cstrong\u003e (c)\u003c/strong\u003e Representative images showing the significant reduction of Iba1 positive cells in PLX treated brains, compared to normal diet treated brains. \u0026nbsp;\u003cstrong\u003e(d)\u003c/strong\u003e The number of Iba1 positive cells after stroke is significantly reduced by PLX5622, compared to normal diet (n=2, Naïve; n=3-4, PLX treated). Data presented as mean ± SEM. **** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001 vs Naïve or ND-Stroke by one-way ANOVA with Bonferroni's multiple comparison test. \u003cstrong\u003e(e)\u003c/strong\u003eExpression of \u003cem\u003eTmem119\u003c/em\u003e from the ipsilateral hemisphere of stroke mice with PLX5622 treatment (PLX) or normal diet (ND). Data represents mean ± SEM (n=2 naïve, n=4 PLX or ND). * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01 vs ND-Stroke by one-way ANOVA with Bonferroni's multiple comparison test. \u0026nbsp;\u003cstrong\u003e(f-j)\u003c/strong\u003e Upregulation of \u003cem\u003eIfi27l2a\u003c/em\u003e/IFI27L2 in stimulated primary MG, human MG and diseased human brain. Mouse primary MG were treated with TNFα (20ng/ml) and IFNγ for 24 hours \u003cstrong\u003e(f)\u003c/strong\u003e and 48 hours \u003cstrong\u003e(g)\u003c/strong\u003e. \u003cem\u003eIfi27l2a\u003c/em\u003e mRNA were increased in stimulated MG for 24 hrs (n=6-7, *** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test). Intracellular Ifi27l2a protein was induced by proinflammatory cytokine treatment for 48 hrs (n=8-10, **** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001 two-tailed unpaired Student’s t-test). \u003cstrong\u003e(h)\u003c/strong\u003e HMC3 were treated with TNFα (20 ng/ml) and IFNγ (20 ng/ml) plus OGD (Stim). Induction of \u003cem\u003eIFI27L2\u003c/em\u003e mRNA in stimulated HMC3 cells were assessed by qRT-PCR (n=5-6, * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test.). \u003cstrong\u003e(i) \u003c/strong\u003eRepresentative images show expression of IFI27L2 in stressed human HMC. Scale bar = 20 µm. \u003cstrong\u003e(j)\u003c/strong\u003e Human IFI27L2 protein expression in age-matched control human brain and stroke brain collected from patients with confirmed CAA pathology and tauopathy. IFI27L2 positive cells were found in the stroke/CAA/tauopathy brain samples (n=3, female), but not in controls (n=2, female). Scale bar =100 µm.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2557290/v1/8f35e6bb9234f6027ae28c12.jpeg"},{"id":33003059,"identity":"840a8741-905a-4ae1-a4e0-ce1122aa075e","added_by":"auto","created_at":"2023-02-15 23:00:29","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":449751,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIfi27l2a is sufficient for microglial activation and ROS generation\u003c/strong\u003e. \u003cstrong\u003e(a)\u003c/strong\u003eOverexpression of Ifi27l2a by lentivirus changed the morphology at 5 days after infection\u003cstrong\u003e. (b)\u003c/strong\u003e The % of cells that changed their shapes was significantly increased in Ifi27l2a-lentivirus infected cells, compared to control-lentivirus infected cells (n=3, * p \u0026lt;0.05, two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test). scale bar=100\u003cstrong\u003e \u003c/strong\u003eµm \u003cstrong\u003e(c)\u003c/strong\u003e Representative images show that the cells that express Ifi27l2a (eGFP as an expression surrogate) changed their morphology to round and amoeboid shapes. Red arrows indicate cells that express Ifi27l2a and show a round morphology; Green arrow indicates a cell which does not express Ifi27l2a and remains in the intact morphology. scale bar=100\u003cstrong\u003e \u003c/strong\u003eµm. \u003cstrong\u003e(d) \u003c/strong\u003eIfi27l2a overexpression increased the intensity of CellRox dye in all cells (n=4, * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test). \u003cstrong\u003e(e) \u003c/strong\u003eIfi27l2a overexpression increased CellRox intensity within GFP expressing cells (n=4, * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test). Mitochondrial ROS levels (\u003cstrong\u003ef.\u003c/strong\u003e MFI, \u003cstrong\u003eg.\u003c/strong\u003e % of MitoSox+ cells) detected by Mitosox was increased in Ifi27l2a lentivirus infected cells, compared to control (n=3-6, * p\u0026lt;0.05, ** p\u0026lt;0.01, one-way ANOVA with Bonferroni's multiple comparison test).\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2557290/v1/21bd9768e151be05994df00f.jpeg"},{"id":33002846,"identity":"d6d5717c-21be-49c4-8ffe-8a9832a79c41","added_by":"auto","created_at":"2023-02-15 22:52:29","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":536471,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHemizygous deletion of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eIfi27l2a\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e is neuroprotective for ischemic stroke\u003c/strong\u003e. (\u003cstrong\u003ea, b\u003c/strong\u003e) Brain infarction at PSD 3 was significantly reduced in \u003cem\u003eIfi27l2a\u003c/em\u003e\u003csup\u003e+/-\u003c/sup\u003e (Het) compared to WT (n=6, * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test). (\u003cstrong\u003ec, d\u003c/strong\u003e) Ifi27l2a deletion (Het) significantly reduced microgliosis in the peri-infarct cortex at 14 days following stroke (n=5-6, * p\u0026lt;0.05).\u0026nbsp; Deletion of Ifi27l2a (Het) significantly reduced microgliosis (\u003cstrong\u003ee, f\u003c/strong\u003e) and astrogliosis (\u003cstrong\u003eg, h\u003c/strong\u003e) in the thalamus at 14 days post-stroke (n=6, * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, two-tailed unpaired Student’s \u003cem\u003et\u003c/em\u003e-test).\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2557290/v1/0718ba397389531a4d06c4f1.jpeg"},{"id":76345255,"identity":"b8af4663-1d3f-4ff8-a093-955555104b54","added_by":"auto","created_at":"2025-02-15 08:05:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4251644,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2557290/v1/e778a5c3-44f7-4802-b42d-fefa57b26f22.pdf"},{"id":33003384,"identity":"8016dba9-18f0-487b-816e-bb15826f245d","added_by":"auto","created_at":"2023-02-15 23:16:29","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3094893,"visible":true,"origin":"","legend":"\u003cp\u003eExtended data figure legends and table\u003c/p\u003e","description":"","filename":"Extendeddatafigurelegendsandtable02032023.docx","url":"https://assets-eu.researchsquare.com/files/rs-2557290/v1/b3581b971402a8d6314aab87.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Single-cell analysis identifies Ifi27l2a as a novel gene regulator of microglial inflammation in the context of aging and stroke.","fulltext":[{"header":"Main","content":"\u003cp\u003eMicroglia (MG) are resident macrophages in the central nervous system (CNS). Critically, MG feature extensive heterogeneity, with subtypes evident across different regions of the brain, across different developmental stages and ages, and between the sexes\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. These various MG subtypes play a pivotal role in both initiating, and resolving inflammation, and act in coordination with other glial cells such as astrocytes, and oligodendrocytes. The MG response to inflammatory challenge and ischemic stroke is a crucial component for maintaining/restoring brain homeostasis, salvaging tissue, and minimizing brain damage \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. However, MG in the aged brain are less effective at exhibiting proper immune responses than MG in younger animals and instead exhibit uncontrolled inflammatory responses \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. This loss of competence contributes to the impairment of brain function and facilitates aging processes in the aged brain \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Selectively restoring MG functionality in older animals so that they mirror a less pro-inflammatory, more anti-inflammatory-like state may be an effective intervention to mitigate ischemic damage and facilitate improved functional recovery after stroke in aged mice.\u003c/p\u003e\n\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\n\u003cp\u003eWe performed scRNA-seq of young and aged brains of animals that underwent either sham surgery or permanent stroke. Using this unbiased approach, we discovered a gene, interferon \u003cem\u003ealpha-inducible protein 27 like 2A\u003c/em\u003e (\u003cem\u003eIfi27l2a)\u003c/em\u003e that was mildly upregulated in MG of the aged brain and significantly upregulated in MG following stroke, and even more elevated in the aged stroke brains. To the date, however, no specific role for \u003cem\u003eIfi27l2a\u003c/em\u003e in ischemic stroke has been described.\u003c/p\u003e\n\u003cp\u003eBoth interferons (IFN) and certain types of viral infection upregulate \u003cem\u003eIfi27l2a\u003c/em\u003e expression in the brain \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In non-glial cells Ifi27l2a protein enhances inflammation by blocking the action of nuclear receptors (NR4A) that normally act to promote expression of anti-inflammatory genes \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In the current study, we further demonstrate that reducing \u003cem\u003eIfi27l2a\u003c/em\u003e expression provides significant reduction of neuroinflammation and brain infarct following ischemic stroke. Together, these studies provide compelling new evidence that targeting Ifi27l2a expression or function may mitigate brain injury and inflammation following ischemic stroke.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eIfi27l2a\u003c/span\u003e \u003cb\u003eis highly upregulated after stroke in MG and aging significantly enhances this upregulation.\u003c/b\u003e To define the transcriptional signature across multiple cell types in the post-stroke brain, we performed scRNA-seq of young (3-month-old) and aged (20-month-old) male and female C57BL/6J mice subjected to permanent distal middle cerebral artery occlusion (pdMCAO) or sham surgeries (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The pdMCAO stroke model was used since it produces both primary injury (cortical infarct) and secondary injury in the thalamus 2-weeks post-stroke \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Since the cortex and thalamus also feature clear increases in microgliosis and astrogliosis following stroke, we included a brain region containing both peri-infarct cortex and thalamus for scRNA-seq study \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe evaluated differential gene expression (DGE) patterns, as an initial approach for determining how the molecular signature of cells within the young and aged brain change post stroke. To measure the effect of aging in stroked brains, we first integrated young stroke (AGGR2) and aged stroke (AGGR4) data into a single analysis (Seurat package \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e) for analysis. Then, a single integrated analysis (data integration, PCA, UMAP and clustering, and DGE) was performed. Visualization of this merged dataset of 21,092 cells from the aged and young stroke mouse brain through dimension reduction by uniform manifold approximation and projection (UMAP) identified eight clusters of unique cell types based on gene expression differences. Identities were assigned to each of the eight clusters using the expression of conserved cell type markers, including microglia (MG, n\u0026thinsp;=\u0026thinsp;7180) (\u003cem\u003eTrem2\u003c/em\u003e), oligodendrocytes (Oligo, n\u0026thinsp;=\u0026thinsp;5149) (\u003cem\u003ePlp1\u003c/em\u003e), endothelial cells (EC, n\u0026thinsp;=\u0026thinsp;3943) (\u003cem\u003eCldn5\u003c/em\u003e), astrocytes (Astro, n\u0026thinsp;=\u0026thinsp;1698) (\u003cem\u003eAldoc\u003c/em\u003e), lymphocytes (Lym, n\u0026thinsp;=\u0026thinsp;1495) (\u003cem\u003ePlac8\u003c/em\u003e), epithelial cells (Epi, n\u0026thinsp;=\u0026thinsp;1192) (\u003cem\u003e1500015O10Rik\u003c/em\u003e), vascular leptomeningeal cells (VLMC, n\u0026thinsp;=\u0026thinsp;127) (\u003cem\u003eDcn\u003c/em\u003e) and vascular endothelial cells, venous (VECV, n\u0026thinsp;=\u0026thinsp;89) (\u003cem\u003ePglyrp1\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea-b). Notably, the proportion of MG and Lym clusters were highly increased in the aged stroke brain, whereas the oligodendrocytes were reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). These findings are consistent with more extensive white matter injury in the aged stroke brain and correlate with increased MG-mediated neuroinflammation and lymphocyte infiltration. As we and others have demonstrated that MG are highly sensitive to inflammation and ischemic stress and act to regulate innate immunity in brains \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, we focused our subsequent analysis on transcriptional changes within MG.\u003c/p\u003e \u003cp\u003eInterestingly, our unbiased analyses of 21,092 cells (combined from young and aged stroke brains) showed that \u003cem\u003eIfi27l2a\u003c/em\u003e was the most highly upregulated gene in MG clusters in aged stroke, compared to young stroke (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The top five genes that were significantly upregulated in MG in the aged stroke brain included MG related genes (\u003cem\u003eLgals3\u003c/em\u003e, \u003cem\u003eLyz2\u003c/em\u003e, \u003cem\u003eLgals3bp\u003c/em\u003e) and another interferon-stimulated gene (ISG), \u003cem\u003eIfitm3\u003c/em\u003e. Dot plots compared the expression level and percent of cells expressing the top five genes upregulated in aged stroke versus young stroke (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Within the MG cluster, there was a notable increase in the percentage of cells expressing \u003cem\u003eIfi27l2a\u003c/em\u003e between aged stroke and young stroke (62.6% vs 29.3%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Total normalized expression of \u003cem\u003eIfi27l2a\u003c/em\u003e from all cells showed increased \u003cem\u003eIfi27l2a\u003c/em\u003e expression in cells of aged stroke, compared to young stroke (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). \u003cem\u003eIfi27l2a\u003c/em\u003e was more highly upregulated in MG of aged stroke brain, suggesting aging may act synergistically with ischemic stroke to promote \u003cem\u003eIfi27l2a\u003c/em\u003e expression in MG (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef). While most of the \u003cem\u003eIfi27l2a\u003c/em\u003e-expressing cells belonged to the MG cluster, \u003cem\u003eIfi27l2a\u003c/em\u003e expression was also detected in Lym and VLMC populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg). The VLMC showed increased \u003cem\u003eIfi27l2a\u003c/em\u003e expression with aged stroke, whereas stroke-induced \u003cem\u003eIfi27l2a\u003c/em\u003e expression in Lym was not markedly altered by aging. Other MG markers, such as \u003cem\u003eLgals3\u003c/em\u003e, \u003cem\u003eIfitm3\u003c/em\u003e and \u003cem\u003eLgals3bp\u003c/em\u003e, were also upregulated in MG and other cells following stroke (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh-j). In contrast, there was no synergistic effect of aging with stroke on \u003cem\u003eC1qa\u003c/em\u003e expression, a MG marker gene (data not shown). As expected, a known marker of activated MG, \u003cem\u003eCst7\u003c/em\u003e, was increased in aged stroke compared to young stroke brain (\u003cb\u003eExtended data\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea), confirming that MG were more highly activated in aged stroke brains than in young stroke brains. In addition, we found significant upregulation of \u003cem\u003eApoe\u003c/em\u003e and \u003cem\u003eLyz2\u003c/em\u003e, while \u003cem\u003eAif1\u003c/em\u003e level appeared only slightly increased in MG in aged stroke compared to young stroke (\u003cb\u003eExtended Data\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb-d). Taken together, the scRNA-seq data suggest an age-dependent upregulation of \u003cem\u003eIfi27l2a\u003c/em\u003e, which occurs predominantly in MG after stroke.\u003c/p\u003e \u003cp\u003e \u003cb\u003escRNA-seq revealed that aging itself is sufficient to increase\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eIfi27l2a\u003c/span\u003e \u003cb\u003etranscripts in MG.\u003c/b\u003e Following our finding that \u003cem\u003eIfi27l2a\u003c/em\u003e is upregulation following stroke in an age-dependent manner, we next sought to determine if aging alone impacts \u003cem\u003eIfi27l2a\u003c/em\u003e expression. Thus, we compared young and aged sham brains, integrating the young and aged sham operated samples (young sham - AGGR1, aged sham - AGGR3). Eight clusters were identified (\u003cb\u003eExtended data\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), including oligodendrocytes (Oligo) (\u003cem\u003ePlp1\u003c/em\u003e), MG (\u003cem\u003eC1qa\u003c/em\u003e), EC (\u003cem\u003eCldn5\u003c/em\u003e), astrocytes (Astro) (\u003cem\u003eGpr37l1\u003c/em\u003e), epithelial cells (Epi) (\u003cem\u003eTtr\u003c/em\u003e), lymphocytes (Lym) (\u003cem\u003eNkg7\u003c/em\u003e), vascular smooth muscle cells, arterial (VSMCA) (\u003cem\u003eDes\u003c/em\u003e), and B cells (\u003cem\u003eCD79a\u003c/em\u003e). To determine how aging affects the transcriptional landscape in MGs, we compared the expression and percent of cells expressing the previously identified top five MG genes (\u003cem\u003eIfi27l2a\u003c/em\u003e, \u003cem\u003eLgals3\u003c/em\u003e, \u003cem\u003eIfitm3\u003c/em\u003e, \u003cem\u003eLyz2\u003c/em\u003e, and \u003cem\u003eLgals3bp\u003c/em\u003e) in young and aged sham brains. All 5 genes that were upregulated in MG from aged stroke brain were also increased by aging alone (\u003cb\u003eExtended\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Notably, \u003cem\u003eIfi27l2a\u003c/em\u003e transcript levels significantly increased with aging, as did \u003cem\u003eRps27rt\u003c/em\u003e. \u003cem\u003eC1qa\u003c/em\u003e, on the other hand, was not dramatically altered between young and aged sham animals (\u003cb\u003eExtended data\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). We also confirmed the increased expression of \u003cem\u003eIfi27l2a\u003c/em\u003e in MG, Lym and B cell clusters in aged brains (\u003cb\u003eExtended data\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). The violin plots revealed modest upregulation of \u003cem\u003eIfi27l2a\u003c/em\u003e in MG in aged brain compared to young brains. Interestingly, we found significant age-dependent upregulation of ribosomal protein genes such as \u003cem\u003eRpl35\u003c/em\u003e, \u003cem\u003eRps27rt\u003c/em\u003e, and \u003cem\u003eRps28\u003c/em\u003e. This age-dependent upregulation of \u003cem\u003eRps27rt\u003c/em\u003e in all clusters, including MG and Lym (\u003cb\u003eExtended data\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), suggested aging-mediated changes in ribosomal complex composition in MG. Expression of two other genes associated with activated MG (\u003cem\u003eAif1 and Il-1b\u003c/em\u003e) were also modestly increased with aging (\u003cb\u003eExtended data\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec-d). We repeated the same analyses comparing sham to stroke for aged (\u003cb\u003eExtended data\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, 6) and young cohorts (\u003cb\u003eExtended data Fig.\u0026nbsp;7, 8\u003c/b\u003e). Together, these data suggest a synergistic effect of aging and stroke on \u003cem\u003eIfi27l2a\u003c/em\u003e expression.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eDisease-associated microglia (DAM) are present in the aged brain, and significantly increased following stroke.\u003c/span\u003e DAM are a recently discovered sub-population of MG found in the brains of various neurodegenerative diseases, such as AD, PD and ALS (REFs). We asked if DAMs are increased in the aged stroke brain. A recent study reported that homeostatic genes, such as \u003cem\u003eC1qa, Ctss, Hexb\u003c/em\u003e, and \u003cem\u003eCsf1r\u003c/em\u003e are not upregulated during the transition of MG into DAM, whereas other MG related genes (\u003cem\u003eSpp1, Cst7, Lpl\u003c/em\u003e, and \u003cem\u003eItgax\u003c/em\u003e) are highly upregulated in DAM \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. To determine whether a DAM-like MG subpopulation is increased in the aged or stroke brain, we compared the number and relative percentage of DAM in sham and stroke. The DAM subtype was defined by the elevated expression of \u003cem\u003eAif1, Spp1\u003c/em\u003e, \u003cem\u003eCst7\u003c/em\u003e, and \u003cem\u003eLpl\u003c/em\u003e among all MG (filter applied: \u003cem\u003eAif1\u003c/em\u003e \u003csup\u003e\u003cem\u003ehigh\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eSpp1\u003c/em\u003e \u003csup\u003e\u003cem\u003ehigh\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eCst7\u003c/em\u003e \u003csup\u003e\u003cem\u003ehigh\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eLpl\u003c/em\u003e \u003csup\u003e\u003cem\u003ehigh\u003c/em\u003e\u003c/sup\u003e, threshold by count). As expected, we did not detect DAM (0.0%) in young sham brains. However, we a small number of DAM in aged sham samples (0.9%) (\u003cb\u003eExtended data Fig.\u0026nbsp;9a\u003c/b\u003e) shows that stroke increased the percent of DAM in both the young and aged brain (10.2% in young stroke vs 17.9% in aged stroke). These data show that MGs are converted to DAMs during aging, but are DAMs are significantly increased following stroke.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eIfi27l2a is inversely correlated with DAM cell phenotype.\u003c/span\u003e We further analyzed our scRNA-seq data (aged sham and aged stroke) to determine whether \u003cem\u003eIfi27l2a\u003c/em\u003e plays a role in microglial activity, particularly in DAM. First, we examined whether \u003cem\u003eIfi27l2a\u003c/em\u003e expression correlated with expression of DAM-related markers, such as \u003cem\u003eLpl\u003c/em\u003e, \u003cem\u003eSpp1\u003c/em\u003e, \u003cem\u003eCst7\u003c/em\u003e and \u003cem\u003eItgax\u003c/em\u003e. We subset MG into 4 different sub-clusters based on their levels of \u003cem\u003eIfi27l2a\u003c/em\u003e expression (normalized \u003cem\u003eIfi27l2a\u003c/em\u003e expression: 0.3\u0026ndash;0.99, 1-1.99, 2-2.99, 3+). We consistently observed a negative correlation between \u003cem\u003eIfi27l2a\u003c/em\u003e and DAM related gene expression (\u003cem\u003eLpl\u003c/em\u003e, \u003cem\u003eSpp1\u003c/em\u003e, \u003cem\u003eCst7\u003c/em\u003e) (\u003cb\u003eExtended data Fig.\u0026nbsp;9b\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, segregating MG into either an \u003cem\u003eIfi27l2a\u003c/em\u003e \u0026ldquo;high\u0026rdquo; or \u0026ldquo;low\u0026rdquo; expressing cells followed by correlation analysis with known DAM genes and MG homoeostatic genes revealed a negative correlation between \u003cem\u003eIfi27l2a\u003c/em\u003e expression and phagocytosis/DAM related genes (\u003cem\u003eLpl\u003c/em\u003e, \u003cem\u003eSpp1\u003c/em\u003e, \u003cem\u003eItgax\u003c/em\u003e, \u003cem\u003eCst7\u003c/em\u003e, and \u003cem\u003eTyrobp\u003c/em\u003e), but not homeostatic genes or other MG genes (\u003cb\u003eExtended data Fig.\u0026nbsp;9c\u003c/b\u003e). Comparing the expression of DAM genes and homeostatic genes between \u0026ldquo;low\u0026rdquo; and \u0026ldquo;high\u0026rdquo; Ifi27l2a MG subpopulations revealed that DAM-related transcripts were significantly reduced in \u003cem\u003eIfi27l2a\u003c/em\u003e \u0026ldquo;high\u0026rdquo; MG. However, homeostatic genes (\u003cem\u003eAif1, C1qc, Hexb\u003c/em\u003e, and \u003cem\u003eGapdh\u003c/em\u003e) were either not changed or slightly increased (\u003cb\u003eExtended data Fig.\u0026nbsp;9c\u003c/b\u003e). Furthermore, MG genes which are down-regulated in DAMs (\u003cem\u003eCsfr1, Olfml3, Trem119\u003c/em\u003e, and \u003cem\u003eP2ry13\u003c/em\u003e) were increased in \u003cem\u003eIfi27l2a\u003c/em\u003e \u0026ldquo;high\u0026rdquo; MG (\u003cb\u003eExtended data Fig.\u0026nbsp;9c\u003c/b\u003e). Together, these data show a strong negative correlation between \u003cem\u003eIfi27l2a\u003c/em\u003e expression and a mature DAM transcriptional signature in MG.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eRegional Ifi27l2a expression with natural aging.\u003c/span\u003e While scRNA-seq showed that \u003cem\u003eIfi27l2a\u003c/em\u003e transcripts are enriched in MG and other cell types (e.g. Lym, VLMC) in both young and aged stroke brains, we lacked any data on whether there was a regional basis for these changes within the brain (e.g. within the primary injury in the cortex or within the secondary injury region occurring within the thalamus). The cortex and thalamus were extracted from the brains of na\u0026iuml;ve young (3 months, n\u0026thinsp;=\u0026thinsp;4) and aged male mice (18\u0026ndash;20 months, n\u0026thinsp;=\u0026thinsp;4) to determine if there were regional differences in \u003cem\u003eIfi27l2a\u003c/em\u003e expression. Notably, \u003cem\u003eIfi27l2a\u003c/em\u003e mRNA was significantly upregulated in the aged thalamus (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, p\u0026thinsp;\u003cb\u003e\u0026lt;\u0026thinsp;0.05\u003c/b\u003e). \u003cem\u003eIfi27l2a\u003c/em\u003e expression also approached upregulation in the cortex in aged brains (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.23). These findings agree with our earlier scRNA-seq finding and suggest normal aging increases \u003cem\u003eIfi27l2a\u003c/em\u003e expression in the brain. In addition, MG related genes \u003cem\u003eIl-1b\u003c/em\u003e, \u003cem\u003eCst7\u003c/em\u003e, and \u003cem\u003eTyrobp\u003c/em\u003e were markedly increased in either the thalamus or cortex of aged brains, further supporting an age-dependent increase in MG activation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb-d). Transcripts for \u003cem\u003eC1qb\u003c/em\u003e and \u003cem\u003eLpl\u003c/em\u003e, two genes which are known to be associated with microglia phagocytosis, were indistinguishable between the two stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee-f). These data indicate that \u003cem\u003eIfi27l2a\u003c/em\u003e is induced along with other genes associated with proinflammatory MG phenotype in the aged brain.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eRegional and temporal expression of Ifi27l2a in aged stroke brain.\u003c/span\u003e To provide regional and temporal expression of \u003cem\u003eIfi27l2a\u003c/em\u003e and other MG-related genes following stroke, we analyzed young and aged thalamus and cortex by qRT-PCR at 3 and 14 days post-stroke. As expected, \u003cem\u003eIfi27l2a\u003c/em\u003e was significantly elevated at three days (cortex) and two weeks (cortex and thalamus) after stroke, compared to sham (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ei). We evaluated two other genes associated with MG activation (\u003cem\u003eCst7\u003c/em\u003e) and reparative phagocytosis (\u003cem\u003eTyrobp\u003c/em\u003e), and which were found to be elevated in our scRNA-seq analysis. Both \u003cem\u003eCst7\u003c/em\u003e and \u003cem\u003eTyrobp\u003c/em\u003e were increased in cortex and thalamus by two weeks post-stroke, but not by 3 days (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg-h). These findings suggest that \u003cem\u003eIfi27l2a\u003c/em\u003e expression is associated with the earlier phase of MG activation following stroke. The delayed expression in thalamus reflects the slower progression of the secondary injury mechanism.\u003c/p\u003e \u003cp\u003eTo provide spatial context to \u003cem\u003eIfi27l2a\u003c/em\u003e expression at the single-cell level, we profiled \u003cem\u003eIfi27l2a\u003c/em\u003e mRNA transcripts on mouse brain sections using single-molecule \u003cem\u003ein situ\u003c/em\u003e hybridization (RNAscope). Probing for \u003cem\u003eIfi27l2a\u003c/em\u003e in aged sham and stroke brains revealed elevated transcripts in the peri-infarct area at 2 weeks post-stroke compared with sham-operated controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ej-l). Combining RNAscope for \u003cem\u003eIfi27l2a\u003c/em\u003e with immunostaining for Iba1 confirmed that the majority of \u003cem\u003eIfi27l2a\u003c/em\u003e transcript is present in activated MG in the peri-infarct region of the aged brain (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003em).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eMG represent the predominant source of Ifi27l2a expression after stroke.\u003c/span\u003e Our analyses of stroked brains at post stroke day (PSD) 3 and PSD 14 revealed a significant increase in \u003cem\u003eIfi27l2a\u003c/em\u003e mRNA. To determine whether MG represented the predominant source for the increased \u003cem\u003eIfi27l2a\u003c/em\u003e expression, we used PLX5622 treatment to deplete MG in mice prior to inducing stroke. PLX5622 is a CSF1R antagonist that eliminates CNS-resident MG \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. CSF1R mediated signaling is required for MG survival and proliferation \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Mice were treated with PLX5622 for seven days. On day 7 of administration of PLX5622, pdMCAO was performed. The PLX5622 diet was continued for 3 days after stroke surgery to prevent repopulation by MG. At PSD 3, brains were isolated and analyzed by qRT-PCR (ipsilateral hemisphere) and immunostaining (contralateral hemisphere). As a control, mice were fed normal diet (ND) for the same period (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Notably, \u003cem\u003eIfi27l2a\u003c/em\u003e mRNA level was significantly reduced by 86% in PLX-stroked brains (ipsilateral hemisphere), compared to ND-stroked brains (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The effectiveness of PLX5622 to eliminate MG in brains was confirmed by Iba1 immunofluorescence (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec-d) in the contralateral hemisphere. PLX5622 treatment resulted in a profound decrease in the number of MG in brains (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed). Moreover, PLX5622 treatment significantly reduced \u003cem\u003eTmem119\u003c/em\u003e expression in brains after stroke, compared to na\u0026iuml;ve or normal diet administered brains (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, compared to na\u0026iuml;ve and ND-stroke). These data indicate that the induction of \u003cem\u003eIfi27l2a\u003c/em\u003e after stroke is primarily dependent on the MG population in the brain.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eMG induce Ifi27l2a/IFI27L2 expression with inflammatory stimuli.\u003c/span\u003e We next used cultured MG to evaluate the potential for inflammatory mediators to promote Ifi27l2a expression. First, we used mouse primary MG collected from the mixed glial cell culture obtained from P2 pups. Primary MG were treated with TNF-α (20 ng/mL) and IFN-γ (20 ng/mL) for 24 hours (to measure mRNA level of \u003cem\u003eIfi27l2a\u003c/em\u003e) and 48 hours (to measure protein level of Ifi27l2a by ELISA with cell lysate). Both mRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef) and protein levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg) of Ifi27l2a were significantly increased with treatment.\u003c/p\u003e \u003cp\u003eTo determine whether these findings extended to a human \u003cem\u003ein vitro\u003c/em\u003e MG model, we challenged human microglial cells (HMC3) by addition of pro-inflammatory cytokines (TNF-α [20 ng/mL] and IFN-γ [20 ng/mL]) in combination with oxygen/glucose deprivation (inflammation/OGD). This inflammatory challenge induced a significant upregulation of \u003cem\u003eIFI27L2\u003c/em\u003e mRNA in HMC3s (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh, n\u0026thinsp;=\u0026thinsp;5\u0026ndash;6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). We found that human IFI27L2 protein level was dramatically induced at 20 hours post inflammation/OGD (Stim), compared to control treatment (Control) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ei, representative of n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e \u003cp\u003eGiven these results, we next tested if IFI27L2 protein was increased in the brains of patients that featured neuroinflammation. Sections from the brains of deceased patients without neurological disease (n\u0026thinsp;=\u0026thinsp;2, female) and from stroke patients (n\u0026thinsp;=\u0026thinsp;3, female) who also demonstrated cerebral amyloid angiopathy (CAA) pathology and tauopathy, in which neuroinflammation (microgliosis) is prevalent. Immunohistochemistry showed significant IFI27L2 expression in the stroke brain samples but low expression in age-matched control samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ej, representative of n\u0026thinsp;=\u0026thinsp;2\u0026ndash;3). Together, these data show the responsiveness of Ifi27l2a (murine) and IFI27L2 (human) to inflammatory stimulation and the presence of elevated IFI27L2 in brain of patients with multiple forms of neuroinflammatory disease.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eDifferential expression of Ifi27l2a in subtypes of microglia (MG) and macrophage (MΦ) populations in the aged brains following stroke.\u003c/span\u003e Given the extensive heterogeneity evident within MG and MΦ, we subjected the aged scRNA-seq datasets to more granular analysis to determine if \u003cem\u003eIfi27l2a\u003c/em\u003e expression profiles correlated with different functional roles. We ultimately identified a total of 28 clusters from brain cells of aged sham and aged stroke mouse brains, eight clusters of which were assigned an MG or monocyte/MΦ identity based on the expression of conserved cell markers (\u003cb\u003eExtended data Fig.\u0026nbsp;10\u003c/b\u003e). Two MG homeostatic clusters were identified based on the expression of MG genes such as \u003cem\u003eSiglech, Tmem119, Gpr34, P2ry12\u003c/em\u003e, and \u003cem\u003eSelplg\u003c/em\u003e. These MG were annotated as \u003cem\u003eSiglech\u003c/em\u003e homeostatic MG and \u003cem\u003eP2ry12\u003c/em\u003e homeostatic MG. We also identified two different MG that appeared to be in an activated status (\u003cem\u003eRag\u003c/em\u003e\u0026thinsp;+\u0026thinsp;activated MG and \u003cem\u003eTyrobp\u003c/em\u003e\u0026thinsp;+\u0026thinsp;activated MG). Two Monocyte-Macrophage populations were also identified. We also found the disease-associated MG (DAM) like cluster showing high expression of \u003cem\u003eLpl\u003c/em\u003e, \u003cem\u003eItgax\u003c/em\u003e, \u003cem\u003eCst7\u003c/em\u003e, and \u003cem\u003eSpp1\u003c/em\u003e. Note that these genes also correlate with the microglial genes and lipid metabolism genes upregulated in DAMs in other neurodegenerative diseases, such as AD \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Since we found that stroke and aging increase the expression of \u003cem\u003eIfi27l2a\u003c/em\u003e in MG, and that \u003cem\u003eIfi27l2a\u003c/em\u003e expression is negatively correlated with DAM genes, we asked whether expression levels and degrees of \u003cem\u003eIfi27l2a\u003c/em\u003e gene induction from sham to stroke in DAM would be different from MG in other sub-clusters. We therefore compared the degree of \u003cem\u003eIfi27l2a\u003c/em\u003e gene induction among MG sub-clusters in aged sham versus stroke brains (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the non-homeostatic MG clusters, \u003cem\u003eIfi27l2a\u003c/em\u003e induction in DAM (1.7 fold) is lower than any of the other activated MG.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIfi27l2a expression is sufficient to promote MG activation.\u003c/b\u003e Given the induction of \u003cem\u003eIfi27l2a\u003c/em\u003e in MG in aged brains and following stroke, we sought to elucidate the functional role of Ifi27l2a in MG-mediated neuroinflammation. Changes in microglial morphology is an early, quantifiable sign of inflammation in MG and MG functionality. Thus, we asked if Ifi27l2a expression alone (without additional inflammatory mediators) could induce a pro-inflammatory morphology in MG. We infected a murine microglial cell line (Sim-A9 cells) with a lentivirus where the Cx3cx1 promoter drove the expression of \u003cem\u003eIfi27l2a\u003c/em\u003e and an eGFP reporter, or a lenti-eGFP control. At 5 days post-infection, quantification of cell morphology showed that induction of Ifi27l2a expression caused an increase in the percentage of cells with a small, rounded shape (to a more amoeboid morphology or de-ramification) compared to lenti-eGFP control (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-b). Interestingly, MG with higher Ifi27l2a expression (using eGFP intensity as a surrogate maker) showed more dramatic morphological changes compared to cells that had low Ifi27l2a/eGFP expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). These results provide direct evidence that Ifi27l2a alone can initiate MG activation, even in basal conditions (i.e. inflammatory stimuli are not required).\u003c/p\u003e \u003cp\u003e \u003cb\u003eIfi27l2a induces ROS production.\u003c/b\u003e Earlier reports showed evidence for Ifi27l2a localization in mitochondria within non-CNS cells \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. We also detected increased IFI27L2 in the peri-nuclear membrane and in mitochondria in HMC3 cells (not shown), leading us to question whether Ifi27l2a could mediate mitochondrial dysfunction in MG. Thus, we asked if Ifi27l2a expression alone could initiate the reactive oxygen species (ROS) generation in activated MG. We used CellROX Red and MitoSox. First, we utilized CellROX Red, a detector of most ROS species, to determine if Ifi27l2a expression induces ROS production in Sim-A9 cells in unstimulated conditions. Quantification by flow cytometry revealed that Ifi27l2a overexpression alone promotes a significant increase in ROS production (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, as expressed in median fluorescence intensity, MFI, Ctrl: lenti-eGFP control, Ifi27l2a: lenti-Ifi27l2a-eGFP, n\u0026thinsp;=\u0026thinsp;4, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Next, we only analyzed GFP positive cells, representing those with successful transduction. The ROS level was greater in Ifi27l2a expressing cells compared to eGFP only control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee, Ctrl: lenti-eGFP control, Ifi27l2a: lenti-Ifi27l2a-eGFP, n\u0026thinsp;=\u0026thinsp;4, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eWe checked more specifically if mitochondria contribute as an Ifi27l2a-induced ROS source using Mitosox dye (specific indicator of mitochondria-derived ROS). Ifi27l2a overexpression resulted in a significant increase in mitochondria generated ROS level (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef) and the percentage of Mitosox\u0026thinsp;+\u0026thinsp;cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg). The \u0026ldquo;no-virus\u0026rdquo; cells (No) showed negligible effect on ROS levels. These data indicate that Ifi27l2a expression alone can cause ROS generation in mitochondria in activated MG, implying a causative role of Ifi27l2a in mitochondrial dysfunction in MG.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIfi27l2a hemizygous deletion is protective from ischemic brain injury in mice.\u003c/b\u003e Given our finding that increased Ifi27l2a expression alone is sufficient to promote microglial activation, we asked if limiting Ifi27l2a expression could reduce microglial activation and brain injury following stroke. We used a permanent distal middle cerebral artery occlusion (pdMCAO) stroke model in WT and Ifi27l2a +/- (Het) mice (2\u0026ndash;3 month old, male). At post-stroke day (PSD) 3, the infarct volume was significantly reduced in Het, compared to WT brain (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-b, n\u0026thinsp;=\u0026thinsp;5 or 6, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The area of activated MG (Iba1) was also reduced in the primary injury region at PSD 14 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec-d, n\u0026thinsp;=\u0026thinsp;5 or 6, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The pdMCAO model \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e is also a well-established model for evaluating secondary injury in stroke; significant gliosis develops in the ipsilateral thalamus several days after the primary injury. We and others have shown significant gliosis in the ipsilateral thalamus 1 or 2 weeks following stroke \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Therefore, to evaluate the role of Ifi27l2a in secondary thalamic injury, we examined thalamic gliosis in WT and Het mice (2\u0026ndash;3 months old, male) at PSD 14. Evaluation of the ipsilateral thalamus revealed significant reduction in both microgliosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee-f, n\u0026thinsp;=\u0026thinsp;6, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and astrogliosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eg-h, n\u0026thinsp;=\u0026thinsp;6 ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) in Het mice compared with WT. Note that the reduced injury in Het mice is not due to developmental differences in MCA territory. Analysis of vascular territory between WT and full \u003cem\u003eIfi27l2a\u003c/em\u003e KO revealed no difference (\u003cb\u003eExtended Data Fig.\u0026nbsp;11\u003c/b\u003e, n\u0026thinsp;=\u0026thinsp;6, p\u0026thinsp;=\u0026thinsp;0.19). Together, these findings indicate that reducing Ifi27l2a expression can reduce primary and secondary injury associated with ischemic stroke, likely through attenuation of the microglial-mediated inflammatory response.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe used scRNA-seq to explore the effects of aging and stroke at the cellular level in the brain. As a result of these studies, we identified \u003cem\u003eIfi27l2a\u003c/em\u003e as a gene that demonstrated significant age-dependent upregulation in the post-stroke brain. This novel initial finding led to further study related specifically to where and when \u003cem\u003eIfi27l2a\u003c/em\u003e was upregulated in the brain and to the functional role of Ifi27l2a in aging, stroke, and other neurodegenerative conditions. From these studies, we now present the following major new findings: 1) \u003cem\u003eIfi27l2a\u003c/em\u003e is highly upregulated in MG following stroke, particularly in aged brain. 2) \u003cem\u003eIfi27l2a\u003c/em\u003e is mildly upregulated by aging alone in MG. 3) Upregulation of \u003cem\u003eIfi27l2a\u003c/em\u003e following stroke occurs predominantly in MG. 4) \u003cem\u003eIfi27l2a\u003c/em\u003e expression and upregulation following stroke varies by MG subtype. 5) \u003cem\u003eIfi27l2a\u003c/em\u003e expression is inversely correlated with gene markers of DAM cell phenotype. 6) Expression of Ifi27l2a alone promotes MG activation and mitochondrial ROS production. 7) Reducing Ifi27l2a expression provides reduced MG activation and ischemic injury in an ischemic stroke model. When considered as a whole, we now propose that inflammatory stress (caused by the aging process, ischemic stroke or other) initiates \u003cem\u003eIfi27l2a\u003c/em\u003e gene expression predominantly in MG, which then enhances and propagates inflammatory damage throughout the brain. Further, our data suggest that the level of Ifi27l2a expression in MG may serve as a molecular switch that triggers pro-inflammatory phenotypes and dampens reparative phenotypes in aging and following stroke. We discuss what is known about Ifi27l2a function and elaborate on our major findings below.\u003c/p\u003e\n\u003cp\u003eInterferons and interferon mediated signaling were originally identified as antiviral \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, anti-proliferative and immunomodulatory mechanisms \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e that were induced by viral infection. These pathways are most commonly known to play pivotal roles in host defense against viral infection. Accumulated evidence has also shown a critical role for interferon signaling (especially Type I IFN, \u0026alpha; and \u0026beta;) in regulating neuro-inflammation in aging and diseased brains, such as in the AD and stroke brain \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eHowever, how or if IFN signaling (e.g. Type I or Type II) modulates \u003cem\u003eIfi27l2a\u003c/em\u003e expression directly in stroke brain, especially in aged brain, has not been previously described. It has been shown that stimulation with IFN\u0026alpha; and \u0026beta;, known activators of IFN type I signaling, can induce \u003cem\u003eIfi27l2a\u003c/em\u003e expression in cortical neurons \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e and adipocytes \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. However, it was unclear whether canonical Type I (\u0026alpha;, \u0026beta;) or Type II (\u0026gamma;) IFNs could induce Ifi27l2a expression in microglia in a dish or in damaged brain to induce inflammation. Moreover, analysis of the \u003cem\u003eIfi27l2a\u003c/em\u003e promoter region (human ortholog, Isg12b) failed to show interferon-stimulated response elements (ISREs), which are thought to be required for interferon stimulated gene induction \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. These findings suggested an alternative, non-canonical interferon-independent pathway for \u003cem\u003eIfi27l2a\u003c/em\u003e regulation, such as by microRNA or signaling via other foreign DNA/RNA sensing receptors. Indeed, our scRNA-seq data supports the notion of an interferon-independent pathway. We observed that while \u003cem\u003eIfi27l2a\u003c/em\u003e expression is markedly upregulated in MG, other representative Isg (\u003cem\u003eMx1\u003c/em\u003e, \u003cem\u003eMx2\u003c/em\u003e, Ifi family such as \u003cem\u003eIfi27\u003c/em\u003e, \u003cem\u003eIfi35\u003c/em\u003e, and \u003cem\u003eIfnb1\u003c/em\u003e, etc.) known to be upregulated by IFN response, especially type I Interferons (IFN\u0026alpha; and \u0026beta;), were not measurably changed in MG. These findings suggested that another pathway (e.g. an IFN I independent pathway or combined signaling with IFN response and other intrinsic cellular signaling caused by ischemic or hypoxic insults) might be involved in the acute/chronic \u003cem\u003eIfi27l2a\u003c/em\u003e induction in MG. Such a scenario could be explained by the existence of other molecular hubs that relay the downstream signals to ultimately induce \u003cem\u003eIfi27l2a\u003c/em\u003e expression in MG after stroke. This possibility is supported by our scRNA-seq data showing significant upregulation of interferon regulatory factor 7 (IRF7) in MG from aged brain following stroke, whereas other IRFs were not markedly changed (data not shown). Moreover, in the series of \u003cem\u003ein vitro\u003c/em\u003e experiments with primary MG treated with pro-inflammatory cytokines, a positive correlation was found between \u003cem\u003eIfi27l2a\u003c/em\u003e and \u003cem\u003eIRF7\u003c/em\u003e, implying that IRF7 signaling may contribute to Ifi27l2a expression in activated MG. Interestingly, using TRANSFAC, a tool for transcriptional analysis, we found a putative IRF7 binding motif in the promoter of \u003cem\u003eIfi27l2a\u003c/em\u003e, suggesting that IRF7 may act as a key transcription factor to induce the \u003cem\u003eIfi27l2a\u003c/em\u003e gene expression in the inflammatory situation in microglia and other cells in brains. Further experiments will be required to specifically test the role and involvement of IRF7-mediated transcriptional regulation on \u003cem\u003eIfi27l2a\u003c/em\u003e expression.\u003c/p\u003e\n\u003cp\u003eOutside of the CNS, a limited number of reports have suggested a role for Ifi27l2a in facilitating inflammation though its interaction with other cellular partner proteins. During conditions of inflammation, it was shown that the Ifi27l2a protein is rapidly expressed and interacts with nuclear receptor 4A (NR4A) family members. The NR4A family is thought to support expression of multiple genes involved in attenuating inflammation in various kinds of cells \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Binding between Ifi27l2a and NR4A in the nucleus results in the export of NR4A to the cytosol, and thus the removal of a driver of anti-inflammatory and cytoprotective gene expression \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. This model of NR4A regulation could also explain the novel role of Ifi27l2a in MG after stroke. In support of this possibility, a separate study showed that MG-specific \u003cem\u003eNr4a1\u003c/em\u003e knockout alone promoted inflammation and microglial activation as well as increased pathology in the experimental autoimmune encephalomyelitis mouse model (EAE) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Interestingly, \u003cem\u003eNr4a1\u003c/em\u003e was also shown to play a critical role in maintaining an anti-inflammatory state of macrophages via attenuating NF-kB mediated pro-inflammatory gene expression \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Moreover, it was revealed that if \u003cem\u003eNr4a1\u003c/em\u003e is deleted in myeloid cells such as macrophages, more pro-inflammatory cytokines are produced \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. It was recently shown that NR4A may also regulate phagocytosis via Mer tyrosine kinase (MerTK) gene expression in the cardiac repair process \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. MerTK is a member of the MER/AXL/TYRO3 receptor kinase family, which is known to regulate phagocytic capacity in MG and M\u0026Phi;. If other phagocytosis-related genes such as \u003cem\u003eAxl\u003c/em\u003e and anti-inflammatory cytokines are also direct targets for NR4A, it is possible that lowering the expression level of Ifi27l2a might boost MG phagocytic capacity or promote phenotypical changes to DAM via promoting reparative phagocytosis related genes such as \u003cem\u003eAxl\u003c/em\u003e. Indeed, our scRNA-seq data showed an inverse correlation between \u003cem\u003eIfi27l2a\u003c/em\u003e and \u003cem\u003eAxl\u003c/em\u003e, indicating that lower \u003cem\u003eIfi27l2a\u003c/em\u003e expression may be a characteristic of the non-inflammatory MG phenotypes. We also found higher expression of \u003cem\u003eNr4a1\u003c/em\u003e in DAM and one of the homeostatic MG clusters. Overall, our data support the novel working model that Ifi27l2a regulation of Nr4a1 contributes to the phenotypic polarization of microglia in natural aging and in brain pathology. If our model is correct, the interaction of Ifi27l2a and Nr4a1 would represent a novel therapeutic target for reducing brain inflammation.\u003c/p\u003e\n\u003cp\u003eThe other reported mechanism by which Ifi27l2a acts involves regulation of apoptosis. Studies in activated MG and other cells showed that Ifi27l2a can be shuttled to the mitochondria membrane, where it initiates a mitochondria-dependent apoptosis process \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Our study also supports this possibility wherein Ifi27l2a can act as an initiator for mitochondrial dysfunction by producing ROS. The mode of action of Ifi27l2a may also be regulated by its subcellular destination. With regard to the potential to trigger apoptosis and inflammation, we speculate that with more severe or prolonged MG activation, Ifi27l2a accumulation at the mitochondrial membrane might initially contribute to the MG inflammatory change, and then later trigger MG apoptosis. One intriguing hypothetical scenario is that high Ifi27l2a expression or mitochondrial targeting of Ifi27l2a contributes to the eventual termination of inflammatory MG. At this time, however, the potential role of Ifi27l2a in regulating apoptosis of MG after stroke has never been explored.\u003c/p\u003e\n\u003cp\u003eOur comparison of young and aged non-stroke brains (shams) showed an age-dependent upregulation of \u003cem\u003eIfi27l2a\u003c/em\u003e in MG, Epi, and B-cell populations in the brain. Expression of \u003cem\u003eIfi27l2a\u003c/em\u003e in these cell populations went from undetectable expression in young brain to moderate expression in aged brain. How aging promotes increased \u003cem\u003eIfi27l2a\u003c/em\u003e expression in these clusters is unknown. Since \u003cem\u003eIfi27l2a\u003c/em\u003e is among the known interferon stimulated genes (Isg) that can be upregulated by IFN-mediated pathways (viral infection or by inflammatory pathways \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e) chronic low-level activation of any of these pathways might promote the observed age-dependent increase in Ifi27l2a expression. However, given that the mice were housed in a specific pathogen free (SPF) facility, it is most likely that the increase we observed is due to low-level chronic inflammation that is known to exist in the aged brain \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eExpression of \u003cem\u003eIfi27l2a\u003c/em\u003e differed among the MG sub-clusters in the basal level of \u003cem\u003eIfi27l2a\u003c/em\u003e expression in aged sham brain and degree of \u003cem\u003eIfi27l2a\u003c/em\u003e upregulation following ischemic stroke. Expression levels of \u003cem\u003eIfi27l2a\u003c/em\u003e in sham brain were low in homeostatic subclusters and resulted in less upregulation in the post-stroke brain compared with activated MG subclusters. The activated subclusters showed 2.1\u0026ndash;3.5 fold higher \u003cem\u003eIfi27l2a\u003c/em\u003e expression compared with homeostatic subclusters following stroke. The greater expression level in activated MG suggests a potential role for \u003cem\u003eIfi27l2a\u003c/em\u003e in microglial activation and proliferation. \u003cem\u003eIfi27l2a\u003c/em\u003e expression in two other MG subclusters is discussed further below. Our data showed an inverse correlation between \u003cem\u003eIfi27l2a\u003c/em\u003e expression and reparative MG genes, which are now recognized as DAM genes. This clear relationship in aged stoke brain suggests that Ifi27l2a could also be a key determinant for inducing DAM phagocytic activity or DAM phenotypical changes from non-activated or activated MG. It was further notable that the inverse correlation held up with groups of genes that are related to maintaining MG homeostasis and the DAM phenotype. These findings suggest that \u003cem\u003eIfi27l2a\u003c/em\u003e expression level may contribute to expression of genes in MG related to reparative and phagocytic function. Future study will be required to determine if the reduced \u003cem\u003eIfi27l2a\u003c/em\u003e expression is causative versus merely correlative for this MG phenotype.\u003c/p\u003e\n\u003cp\u003eIn summary, using unsupervised scRNA-seq, we have found a significant increase in \u003cem\u003eIfi27l2a\u003c/em\u003e expression in MG following stroke, with particular upregulation in the aged stroke brain. Our data further show that mild \u003cem\u003eIfi27l2a\u003c/em\u003e upregulation even occurs with aging alone. We present evidence for a new model of MG phenotype regulation, wherein Ifi27l2a acts as a novel molecular regulator of microglial phenotypical changes and function. Based on the data we present here, we propose that elevated expression of Ifi27l2a contributes to a pro-inflammatory MG phenotype (producing more ROS and proinflammatory cytokines in MG) and reduced Ifi27l2a enables a non-inflammatory or phagocytic phenotype. Also we speculate that the functional role of Ifi27l2a is at least partly through negative regulation of Nr4a1-mediated gene transcription. In total, these findings suggest that targeting of \u003cem\u003eIfi27l2a\u003c/em\u003e expression or Ifi27l2a protein function in MG could be a novel strategy for regulating neuroinflammation in aging, stroke, or other neurodegenerative diseases to promote better functional recovery.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eAnimals.\u003c/strong\u003e All procedures were performed in accordance with NIH guidelines for the care and use of laboratory animals and were approved by the Institutional Animal care and use committee of the University of Texas Health Science Center. Sperm from \u003cem\u003eIfi27l2a\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;/\u0026minus;\u003c/em\u003e\u003c/sup\u003e KO mice [Ifi27l2atm1(KOMP)Vlcg] (REF) were obtained from the Diamond laboratory at Washington University in St. Louis and used for \u003cem\u003ein vitro\u003c/em\u003e fertilization of WT (C57BL/6J) eggs (Genetically engineered rodent models core, Germ core, BCM). Resulting heterozygous \u003cem\u003eIfi27l2a\u003c/em\u003e\u003csup\u003e\u003cem\u003e+/\u0026minus;\u003c/em\u003e\u003c/sup\u003e progeny were backcrossed to establish the \u003cem\u003eIfi27l2a\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;/\u0026minus;\u003c/em\u003e\u003c/sup\u003e colony. Male and female mice in a C57BL/6J background (11\u0026ndash;14 weeks old: young, 18\u0026ndash;22 months old: aged) were used for all experiments. All animals were housed in the animal care facility at University of Texas Health Science Center and had \u003cem\u003ead libitum\u003c/em\u003e access to food and water and were maintained on a 12:12 light: dark schedule.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePermanent distal middle cerebral artery occlusion (PDMCAO) model.\u003c/strong\u003e C57BL/6J mice of both sexes were used for scRNA-seq at 11\u0026ndash;14 weeks or 18\u0026ndash;22 months of age. PDMCAO was induced by permanent ligation of the right distal middle cerebral artery (MCA) using a micro-coagulator (Accu-temp)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Mice were anesthetized with isoflurane (4% induction and 2% maintenance in airflow) and body temperature was maintained at 37\u0026deg;C by feedback-controlled heating pad and rectal temperature probe. Bupivacaine (0.25% at 1ml/kg) was injected subcutaneously (s.c.), prior to any skin incision \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. The distal MCA was accessed via a craniotomy and permanently occluded just proximal to the anterior and posterior branches by electrocoagulation. Sham controls were generated with same procedure without electro-coagulation of the MCA.\u003c/p\u003e\n\u003cp\u003eFor microglia depletion experiments, we used PLX5622, a CSF1R antagonist (REF). PLX5622 was provided by Plexxikon Inc. (Berkeley, CA) and formulated in AIN-76A standard chow at 1200 ppm by Research Diets Inc. PLX5622 was administrated for 7 days prior to the PDMCAO procedure and continued for 3 days after stroke. At 3 days after surgery, brains were isolated and ipsilateral hemisphere was used for RNA isolation and qRT-PCR analysis. The contralateral hemisphere was used for immunostaining.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBrain sample preparation for single-cell RNA sequencing.\u003c/strong\u003e We processed brains from young and aged mice subjected to either sham or PDMCAO surgeries (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). 14 days post PDMCAO (or sham surgery), Anesthetized mice were transcardially perfused with heparinized PBS (10 U/mL). Brains were removed from the skull and sliced coronally into 3 mm-thick blocks (from a region spanning\u0026thinsp;+\u0026thinsp;1 to -2 mm from bregma), covering the cortical infarction and secondary thalamic injury site \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The brain slice was then minced with a razor blade and subjected to the brain tissue dissociation protocol (Miltenyi Biotec, Gladbach, Germany). Minced tissue was then incubated a collagenase/dispase mixture (150 \u0026micro;L of 1 mg/mL in 2 mL) for 30 minutes at 37˚C in a gentleMACS Octo Dissociator (Miltenyi Biotec, Bergisch Gladbach, Germany) using the pre-installed program for adult brain dissociation. Myelin was removed using debris removal solution. Red blood cells were lysed and removed with red blood cell lysis solution. The final cell suspension was stained with trypan blue and live cells were counted using Countess II FL Automated Cell Counter (Thermo Fisher scientific, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGEM generation, library construction, and sequencing.\u003c/strong\u003e The 10X Genomics Chromium\u0026trade;, Single-Cell RNA-Seq System (10X Genomics, Pleasanton, CA) was used to prepare cells for scRNA-seq.\u0026nbsp;Brain single cell suspensions were processed to generate barcoded cDNA libraries using GEM gel bead, Chip kit, and library kits (10X Genomics, Pleasanton, CA) as per the manufacturer\u0026rsquo;s instructions. Cells were partitioned with beads containing reagents (primers and RT) required for generating 10X barcoded cDNA in individual cell using Chromium\u0026trade; controller. The resulting cDNA libraries were sequenced with NextSeq500/550 Hi Output Kit v2.5 (75 Cycles, 20024906) on an Illumina NextSeq 500 System.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSequencing data processing and analysis.\u003c/strong\u003e The cell ranger pipeline (10X genomics, Pleasanton, CA) was utilized to map the sequences to mouse reference genome (mm10), and to process barcode containing sequence data, aligning the read and generating feature barcode matrices that could be further processed by the Seurat package \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e using R. We also used \u003cem\u003ecellranger aggr\u003c/em\u003e pipeline to combine outputs from multiple samples into one output file. AAGR1 (5,706 total cells analyzed) was a combined population consisting of \u0026ldquo;sham brains of young male and young female\u0026rdquo; mice. AAGR3 (5,174 total cells analyzed) was a combined population consisting of \u0026ldquo;sham brains of aged male and aged female\u0026rdquo; mice. AAGR2 (12,866 total cells analyzed) was a combined population consisting of \u0026ldquo;Stroke brains from young male and young female\u0026rdquo; mice. AAGR4 (total 8,226 cells analyzed) was a combined population consisting of \u0026ldquo;Stroke brains from aged male and aged female\u0026rdquo;. Reads were mapped to the mm10 murine transcriptome (10X genomics, Pleasanton, CA). We used Seurat 3.1 \u003csup\u003e44\u003c/sup\u003e to analyze scRNA-seq data for clustering, and DEG identification between clusters and between the two groups. Briefly, log-normalization using \u003cem\u003eNormalizeData\u003c/em\u003e was utilized. Feature counts for each cell were divided by total counts for the cell and multiplied by the scale factor (10,000). Then using \u003cem\u003elog1p\u003c/em\u003e, data was natural log-transformed. The Uniform Manifold Approximation and Projection (UMAP) dimensional reduction technique (UMAP) was used for dimensional reduction and clustering was carried out using \u003cem\u003eFindNeighbors\u003c/em\u003e and \u003cem\u003eFindClusters\u003c/em\u003e with the resolution parameter either at 0.02 (generating 6\u0026ndash;7 clusters) or at 1 (generating 25\u0026ndash;27 clusters). Conserved cell type markers in each cluster were identified by using \u003cem\u003eFindConservedMarkers.\u003c/em\u003e The name and level of genes that were differentially expressed in each cluster was determined using \u003cem\u003eFindMarkers.\u003c/em\u003e Metadata and normalized read count data was extracted from Seurat objects and fed into Excel to further identify the critical genes (top 10 genes or top 50 genes) that were up- and down-regulated in each cluster and to find the correlation between levels of \u003cem\u003eIfi27l2a\u003c/em\u003e and other MG genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle molecule\u003c/strong\u003e \u003cspan class=\"BoldItalic\"\u003ein situ\u003c/span\u003e \u003cstrong\u003ehybridization (RNAscope).\u003c/strong\u003e The RNAscope fluorescent multiplex assay (Advanced Cell Diagnostics, Newark, CA, USA) was performed according to manufacturer\u0026rsquo;s instructions with 2 week post-stroke brains of aged mice (18\u0026ndash;20 months) and aged sham to probe \u003cem\u003eIfi27l2a\u003c/em\u003e transcripts in brain cells. The murine \u003cem\u003eIfi27l2a\u003c/em\u003e probe was designed by ACD Biosystems, based on their own criteria. Brain sections (PFA fixed, 30-\u0026micro;m thickness) from the 2-week post stroke brain and sham brains of aged mice (18\u0026ndash;20 month old) were hybridized with \u003cem\u003eIfi27l2a\u003c/em\u003e probes for 2 hours at 40˚C. At the same time, ACD 3-plex positive control and negative control probes were incubated on one brain section to confirm signal specificity. The probes were amplified according to the manufacturer\u0026rsquo;s instructions and labeled with Opal-570 Red fluorophore (Akoya Biosciences, Marlborough, MA, USA). DAPI was used to label nuclei. Images were taken with a fluorescent microscope (Leica DMi8 fluorescence microscope system, Leica Biosystem, IL, USA) and a confocal microscope (Leica TCS SPE confocal system, Leica Biosystem, IL, USA). Multiple images were captured with the 10X objective covering the hemisphere and stitched to generate a single image (Leica LAS X software).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHMC3 cell culture.\u003c/strong\u003e Human microglial cell line 3 (HMC3) cells were purchased from ATCC (CRL-3304, USA) and cultured in Dulbecco's Modified Eagle's Medium (DMEM) (Thermo Fisher Scientific, Waltham, MA, USA) containing 10% fetal bovine serum, 20 ng/mL recombinant human M-CSF1 (Tonbo Biosciences, San Diego, CA, USA) and antibiotics (Pen/Step) in 5% CO\u003csub\u003e2\u003c/sub\u003e and 37\u0026ordm;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBrain processing and immunostaining.\u003c/strong\u003e For detecting Iba1 in PLX- or normal diet-treated mouse brains and gliosis (Iba1 and Gfap) in the thalamus following stroke, we performed immunostaining as previously described \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Cardiac perfusion with PBS, followed by 4% PFA (paraformaldehyde in PBS) were performed to clear the blood in brains. Perfused brains were then submerged in 30% sucrose in PBS for 24 hours at 4\u0026ordm;C prior to sectioning at 30 \u0026micro;m thickness (Micron HM 450, Thermo Fisher Scientific, Waltham, MA, U.S.A.). Sections corresponding to \u0026minus;\u0026thinsp;2 mm from bregma, which contain hippocampus and thalamus, were washed with PBS, incubated with blocking buffer (10% goat serum, 0.3% Trion X-100 in PBS), and then incubated overnight at 4\u0026ordm;C with the following primary antibodies: Rabbit anti-Iba1 antibody (1:200) (Wako Pure Chemical, Japan), mouse anti-GFAP antibody-cy3 (1:500) (Millipore Sigma, MO, USA). We used either donkey anti-rabbit IgG-Alexa 594 or 488 (1:200, Thermo Fisher Scientific, Waltham, MA, USA) to recognize rabbit anti-Iba1 antibody. Sections were incubated with DAPI (4\u0026prime;, 6-diamidino-2-phenylindole) to label nuclei. Images were obtained using a Leica TCS SPE confocal system and a Leica DMi8 fluorescence microscope system (Leica Biosystem, IL, USA). Images were captured using a 10X objective. Higher magnification images of selected regions were collected using 20X or 40X objectives. Image analysis was performed using Image J software (National Institutes of Health).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLentivirus infection and ROS measurement by flow cytometry\u003c/strong\u003e. Control lentivirus (Cx3cr1-IRES-eGFP, initial titer-1.55\u0026times;10\u003csup\u003e8\u003c/sup\u003e TU/ml) and Ifi27l2a expressing lentivirus (Cx3cr1-Ifi27l2a-IRES-eGFP, initial titer- 1.07\u0026times;10\u003csup\u003e8\u003c/sup\u003e TU/ml) were generated (GeneCopoeia, Rockville, MD, USA) and these virus went through in-house quality control and validation. Sim-A9 cells, a microglia-like cell line, was transduced with control lentivirus (eGFP alone) or Ifi27l2a expressing lentivirus at 2 MOI using polybrene (Millipore Sigma, St. Louise, MO, USA). Five days after infection, cells were incubated with CellRox (Thermo Fisher Scientific, Waltham, MA, USA) for ROS detection or MitoSox (5 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\mu\\)\u003c/span\u003e\u003c/span\u003eM) (Thermo Fisher Scientific, Waltham, MA, USA) for mitochondrial derived ROS detection for 10 minutes at 37˚C. Cells were analyzed using a CytoFLEX S flow cytometer (Beckman Coulter Life Science, Indianapolis, IN, USA). For analysis, a gating strategy was applied first to remove debris using forward (FSC-A) and side scatter (SSC-A). Doublets were also excluded from analysis by FSC-height and width. CellRox Deep Red signal (excitation/emission; 644/665) was collected in the channel (BP 660/20) and the MitoSox Red signal (excitation/emission; 510/580 nm) in the channel (BP 585/42). Data were exported and analyzed with FlowJo software (FlowJo, Tree Star Inc., Ashland, OR, USA). The geometric mean of fluorescence intensities (MFI) and percentage of positive cells were calculated and expressed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMouse Ifi27l2a ELISA.\u003c/strong\u003e To check the intracellular levels of Ifi27l2a protein in primary microglia, the murine interferon alpha-inducible protein 27-like protein 2A (Ifi27l2a) was quantified by ELISA following the manufacturer\u0026rsquo;s recommendations (Abbexa, Cambridge, UK) after washing the cells with PBS two times and collecting lysates in RIPA lysis buffer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReal-Time quantitative RT-PCR.\u003c/strong\u003e To validate the findings of scRNA-seq data, we performed qRT-PCR. Brains from naive young (3 mons) and aged mice (18\u0026ndash;20 mons), or brains from sham and stroked mice (PSD 3 or PSD 14) were harvested and dissected to obtain both cortex and thalamus. For the PLX5672 treatment experiment, the ipsilateral hemisphere was collected instead. Total RNA was purified with TRIzol\u0026trade; Reagent (Thermo Fisher Scientific, Waltham, MA, USA) using the RNeasy Mini Kit (Qiaqen, Germantown, MD, USA) according to the manufacturer\u0026rsquo;s instructions. Purity of RNA (\u0026gt;\u0026thinsp;1.7 at 260/280) and concentration of purified RNA were measured by Nano-drop Spectrometer and 1 \u0026micro;g of RNA was used to generate cDNA with iScript\u0026trade; Reverse Transcription Supermix (Bio-Rad, Hercules, CA, USA). The SsoAdvanced Universal SYBR Green Supermix (Bio-Rad, Hercules, CA, USA) was used to detect newly amplified amplicons with a C1000 Touch Thermal Cycler CFX96 Real-Time System (Bio-Rad, Hercules, CA, USA). The PCR cycles were as follows: initial denaturation at 95˚C for 30 sec, followed by 40 reaction cycles of 95˚C for 5 sec, 56˚C for 10 sec, and 72˚C for 10 sec. To quantify relative gene expression, we used the \u0026Delta;\u0026Delta;Ct method using Ct values for the gene of interest normalized to GADPH. Data was expressed as fold change relative to control samples. Primer sequences are provided in \u003cstrong\u003eExtended data\u003c/strong\u003e Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical data analysis.\u003c/strong\u003e Statistical data analysis was performed using Prism 7.0.3 (GraphPad Software, San Diego, CA, USA) and R in Rstudio environment with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant. Data are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM), and analyzed using an unpaired t-test (for two group comparisons) or a one-way ANOVA with Tukey post-hoc test for multiple comparisons.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded by UTH startups, NIH AG072488 to GSK, NIH R56NS120709 to SPM and the Huffington foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.P.M., L.D.M. and G.S.K. conceived the experiments. G.S.K., E. H., J.M.S., M.C.G., A.B., A.C., J.L., A.D., Z.W., and T.W. performed the experiments. G.S.K., and S.P.M. analyzed the results. S.P.M., G.S.K., J.E.J., J.D.W. and L.D.M. discussed the results. G.S.K., E.H. and S.P.M. made the figures and wrote the manuscript. 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\u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003escRNA-seq samples analyzed\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eYoung\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAged\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSham (n = 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStroke (n = 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSham (n = 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStroke (n = 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eName\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAGGR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAGGR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAGGR3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAGGR4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e# of cells analyzed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8226\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Identification of Ifi27l2a as a top gene that is upregulated in MG in aged stroke\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDifferential expression of \u003cem\u003eIfi27l2a\u003c/em\u003e in each MG sub-clusters in sham and stroke in aged brains\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMG sub-clusters\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAged Sham (expression level)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAged Stroke (expression level)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAverage_FC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHomeostatic MG_1-Siglech+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.856\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHomeostatic MG_2-P2ry12+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.815\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.419\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDAM like sub-cluster\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.762\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.910\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.777\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMG_Activated_1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.718\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMG_Activated_2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.761\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMG_Progenitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.318\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-2557290/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2557290/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicroglia are key mediators of inflammatory responses within the brain, as they regulate pro-inflammatory responses while also limiting neuroinflammation via reparative phagocytosis. Thus, identifying genes that modulate microglial function may reveal novel therapeutic interventions for promoting better outcomes in diseases featuring extensive inflammation, such as stroke. To facilitate identification of potential mediators of inflammation, we performed single-cell RNA sequencing of aged mouse brains following stroke and found that \u003cem\u003eIfi27l2a\u003c/em\u003e was significantly up-regulated, particularly in microglia. The increased \u003cem\u003eIfi27l2a\u003c/em\u003e expression was further validated in microglial culture, stroke models with microglial depletion, and human autopsy samples. Ifi27l2a is known to be induced by interferons for viral host defense, however the role of Ifi27l2a in neurodegeneration is unknown. \u003cem\u003eIn vitro \u003c/em\u003estudies in cultured microglia demonstrated that Ifi27l2a overexpression causes neuroinflammation via reactive oxygen species. Interestingly, hemizygous deletion of Ifi27l2a significantly reduced gliosis in the thalamus following stroke, while also reducing neuroinflammation, indicating Ifi27l2a gene dosage is a critical mediator of neuroinflammation in ischemic stroke. Collectively, this study demonstrates that a novel gene, Ifi27l2a, regulates microglial function and neuroinflammation in the aged brain and following stroke. These findings suggest that Ifi27l2a may be a novel target for conferring cerebral protection post-stroke.\u003c/p\u003e","manuscriptTitle":"Single-cell analysis identifies Ifi27l2a as a novel gene regulator of microglial inflammation in the context of aging and stroke.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-02-15 22:52:24","doi":"10.21203/rs.3.rs-2557290/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"48315fad-643a-446a-8994-514cf5de7d3f","owner":[],"postedDate":"February 15th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":19197041,"name":"Biological sciences/Neuroscience/Neuroimmunology"},{"id":19197042,"name":"Biological sciences/Neuroscience/Blood\u0026#x2013;brain barrier"}],"tags":[],"updatedAt":"2025-02-15T08:05:15+00:00","versionOfRecord":{"articleIdentity":"rs-2557290","link":"https://doi.org/10.1038/s41467-025-56847-1","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-02-14 05:00:00","publishedOnDateReadable":"February 14th, 2025"},"versionCreatedAt":"2023-02-15 22:52:24","video":"","vorDoi":"10.1038/s41467-025-56847-1","vorDoiUrl":"https://doi.org/10.1038/s41467-025-56847-1","workflowStages":[]},"version":"v1","identity":"rs-2557290","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2557290","identity":"rs-2557290","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}