Diffuse Traumatic Brain Injury Induced Stimulator of Interferons (STING) Signaling in Microglia Drives Cortical Neuroinflammation, Neuronal Dysfunction, and Impaired Cognition

Diffuse Traumatic Brain Injury Induced Stimulator of Interferons (STING) Signaling in Microglia Drives Cortical Neuroinflammation, Neuronal Dysfunction, and Impaired Cognition | 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 Research Article Diffuse Traumatic Brain Injury Induced Stimulator of Interferons (STING) Signaling in Microglia Drives Cortical Neuroinflammation, Neuronal Dysfunction, and Impaired Cognition Jonathan M. Packer, Samantha G. Giammo, Lynde M. Wangler, Amara C. Davis, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5960640/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Apr, 2025 Read the published version in Journal of Neuroinflammation → Version 1 posted 13 You are reading this latest preprint version Abstract Neuropsychiatric complications including depression and cognitive impairment develop, persist, and worsen in the years after traumatic brain injury (TBI), negatively affecting life and lifespan. Inflammatory responses mediated by microglia are associated with the transition from acute to chronic neuroinflammation after TBI. Moreover, type I interferon (IFN-I) signaling is a key mediator of inflammation during this transition. Thus, the purpose of this study was to determine the degree to which a microglia-specific knockout of the stimulator of interferons (STING) influenced TBI-induced neuroinflammation, neuronal dysfunction, and cognitive impairment. Here, microglial inducible STING knockout (CX₃CR1Cre/ERT2 x STING fl/fl ) mice were created and validated (mSTING -/- ). Diffuse brain injury (midline fluid percussion) in male and female mice increased STING expression in microglia, promoted microglial morphological restructuring, and induced robust cortical inflammation and pathology 7 days post injury (dpi). These TBI-associated responses were attenuated in mSTING -/- mice. Increased cortical astrogliosis and rod-shaped microglia induced by TBI were independent of mSTING -/- . 7 dpi, TBI induced 237 differentially expressed genes (DEG) in the cortex of functionally wildtype (STING +/+ ) associated with STING, NF- κB, and Interferon Alpha signaling and 85% were attenuated by mSTING -/- . Components of neuronal injury including reduced NeuN expression, increased cortical lipofuscin, and increased neurofilament light chain in plasma were increased by TBI and dependent on mSTING. TBI-associated cognitive tasks (novel object recognition/location, NOR/NOL) at 7 dpi were dependent on mSTING. Notably, the TBI-induced cognitive deficits in NOR/NOL and increased cortical inflammation 7 dpi were unaffected in global interferon-α/β receptor 1 knockout (IFNAR1) mice. In the final study, the RNA profile of neurons after TBI in STING +/+ and mSTING -/- mice was assessed 7 dpi by single nucleus RNA-sequencing. There was a TBI-dependent suppression of cortical neuronal homeostasis with reductions in CREB signaling, synaptogenesis, and oxytocin signaling and increases in cilium assembly and PTEN signaling. Overall, mSTING -/- prevented 50% of TBI-induced DEGs in cortical neurons. Collectively, ablation of STING in microglia attenuates TBI-induced IFN-dependent responses, cortical inflammation, neuronal dysfunction, neuronal pathology, and cognitive impairment. Microglia TBI Inflammation Cognitive Dysfunction Stimulator of Interferon Genes and Interferon Type I Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Neuropsychiatric complications including depression and cognitive decline develop and even worsen in the years following traumatic brain injury (TBI). These complications negatively affect quality of life and lifespan. On average, there are 2.4 million brain injuries per year in the United States alone [ 1 ]. TBI also increases the risk of dementia and progressive neurodegeneration [ 2 ]. Microglia, the innate immune cell of the central nervous system (CNS), are involved in chronic inflammation and progressive neurodegeneration after TBI [ 3 – 5 ]. For example, microglial activation is detected acutely, and evidence of this activation can persist months to years post-TBI in humans [ 6 – 9 ] Microglia and corresponding inflammation after TBI affects brain regions responsible for cognition and executive function, impairing information processing, memory, and executive function [ 3 – 5 ]. Thus, understanding the specific pathways induced in microglia after TBI that promote chronic inflammatory processes is a biologically relevant area of focus. Myriad reports indicate that TBI-induced chronic neuroinflammation and cognitive dysfunction in rodents are dependent on microglial responses [ 4 , 10 – 14 ]. We and others have reported that there is a pronounced shift in microglia RNA profiles from pro-inflammatory and NF-κB mediated genes towards a type 1 interferon (IFN-I) response at a subacute time point after TBI (7 days post injury, dpi) [ 11 , 12 , 15 ]. For instance, single-cell RNA sequencing (scRNA-seq) identified trauma associated microglia 7 dpi with a transcriptional signature that was enriched for IFN-I responses ( Ifitm3, Stat1, Irf7, Ifi27l2a ) [ 11 ]. Cortical RNA gene expression also showed the amplification of IFN-I responses 7 dpi [ 11 , 12 ]. Depletion of microglia prior to TBI using a CSF1R antagonist (PLX5622) attenuated neuroinflammation and ablated the IFN-I response to diffuse TBI. These reductions corresponded with improved cortical dendritic complexity, neuronal physiology, and cognition in novel object location and recognition tasks [ 11 ]. Notably, the subacute period after TBI (7 dpi) involved enhanced interferon responses and was worse with age. For instance, diffuse or penetrating TBI in aged mice amplified IFN-I genes ( Ifn-β, Irf7, Ifi204 , and Isg15 ) [ 16 , 17 ]. In addition, there was amplified IFN-I responses and enhanced gliosis and neuroinflammation in the cortex of aged mice after diffuse TBI [ 16 ]. Overall, IFN-I responses are dominant in the brain during the subacute period (7 dpi) after diffuse TBI. The shift in the inflammatory profile at the subacute period after TBI is pertinent and involves the stimulator of IFN genes (STING). STING is a stress-responsive endoplasmic reticulum protein. In the context of viral infection or injury, tissue damage increases cytosolic double-stranded DNA (dsDNA) and mitochondrial DNA (mtDNA) that are sensed by the cGAS-STING pathway [ 18 , 19 ]. STING promotes IFN-I responses that enhance transcription factors IRF3, and NF-κB [ 20 , 21 ] leading to a diverse array of IFN-I and NF-κB-mediated signaling [ 19 ]. Type-1 interferons (IFN-α/β) act on the interferon-α/β receptor 1 (IFNAR1) that is expressed by all cell types within the brain. After diffuse TBI, the microglial RNA profile 7 dpi (by snRNA-seq) indicates a STING-dependent production of IFN-I ( cGas, Tbk1, Sting1 ). In addition, genes associated with the IFNAR1 ( Ifnar2, Stat1 ) and interferon stimulated genes (ISGs) ( Mx1, Mx2, Oasl2) were also increased in microglia 7 dpi [ 22 ]. Consistent with this study, diffuse TBI (lateral fluid percussion injury (FPI)) increased the IFN response in both microglia and astrocytes 7 dpi [ 15 ]. In another study, diffuse TBI (midline FPI)-induced STING expression, microglial morphological restructuring, inflammatory, and IFN-related gene expression in the cortex ( Tnf, Cd68, Ccl2 , Irf7, Sting ) that was attenuated in global STING −/− mice and by a STING antagonist (chloroquine) [ 22 ]. Moreover, TBI-associated cognitive deficits (NOR/NOL) at 7 dpi were STING dependent [ 22 ]. Global reductions of STING signaling reduces inflammation, cognitive deficits, and neuronal dysfunction following TBI [ 22 , 23 ]. Furthermore, a recent study of penetrating TBI using controlled cortical impact (CCI) showed that mSTING −/− reduced the acute inflammatory response, lesion volume, and improved motor recovery 72 hours post injury [ 24 ]. Taken together, STING and IFN-I signaling are critical mediators of inflammation, neuronal dysfunction, and cognitive deficits after TBI. The purpose of this study was to determine the degree to which a microglia-specific knockout of STING influenced neuroinflammation, neuronal dysfunction, and cognitive impairment induced by diffuse TBI. We show novel data that the selective ablation of STING in microglia attenuates TBI-induced IFN-dependent responses, cortical inflammation, neuronal pathology and dysfunction, and cognitive impairment. Materials and Methods Mice: To generate inducible CX 3 CR1-STING -/- mice, CX 3 CR1Cre/ERT2 (Jax#:020940) and STING fl/fl (Jax#:035692) mice were purchased from The Jackson Laboratory and bred in-house. Heterozygous offspring were then backcrossed to generate Cre-ERT2 positive (CX 3 CR1Cre/ERT2-STING fl/fl ) and Cre-negative (STING fl/fl ) control mice. For genotyping, ear punches biopsies were taken following weaning (21d), and samples were genotyped by TransNetYX (Cordoba, TN). To induce recombination, Cre-ERT2 positive (CX 3 CR1Cre/ERT2-STING fl/fl ) and Cre-negative control mice (STING +/+ ) were administered 1.5 mg of tamoxifen in 150 ml of corn oil intraperitoneally (i.p.) daily for five days. Mice were allowed 30 days to reconstitute prior to experimental use. The result was a knockout of STING in microglia (CX 3 CR1-STING -/- or mSTING -/- ) or a functional STING wild type (STING +/+ ). For the global knockout IFNAR1 -/- mice, homozygous male and female IFNAR1 -/- mice were purchased from the Jackson Laboratory and bred in-house. Male and female mice were used in all experiments unless otherwise noted. These experiments, however, were not powered to make sex comparisons. Mice were group housed under a 12/12 light-dark cycle with ad libitum access to food and water. Mice were randomly assigned to groups with mixed treatment and injury groups in each cage. All procedures were performed in accordance with the National Institute of Health Guidelines for the Care and Use of Laboratory Animals, the Public Health Service’s Policy on Human Care and Use of Laboratory Animals, and the Guide for the Care and Use of Laboratory Animals and were approved by The Ohio State University Institutional Laboratory Animal Care and Use Committee. Midline Fluid Percussion Injury (mFPI): Mice were subjected to a midline diffuse TBI using a fluid percussion injury (FPI) apparatus as described previously [12, 22, 25]. Briefly, mice were anesthetized in an isoflurane chamber at 2-3% with a flow rate of 0.8 liters/min. After the surgical site was shaved, mice were secured to the stereotax (Stoelting Co., Cat# 51731) and maintained under anesthesia with a mask attachment (Stoelting Co., Cat# 51609M). The surgical site was prepared with aseptic technique, using alternating applications of iodine and 70% ethanol. Mice received a 3 mm craniectomy between the landmark sutures bregma and λ, and a rigid Luer-loc needle hub was secured over the craniectomy site. Following this procedure, mice were moved to a heated (37ºC) recovery cage and monitored until conscious (upright, responsive, and walking). After recovery, mice were briefly re-anesthetized in an isoflurane chamber at 5% (flow rate 0.8 liters/min) for 5 min. The Luer-loc hub was filled with saline, and the hub was attached to the injury device. Once a positive toe-pinch response was elicited (~30 s), a 10 ms pulse of saline (1.2 atm; 670-720 mV) was imposed on the dura. Immediately after the TBI, the Luer-loc hub was removed, dural integrity was confirmed. Next, wound clips (7 mm) were used to close the incision site and the time to self-right was determined (upright and responsive). Next, mice were moved to a heated cage overnight. In these studies, control mice were naïve and uninjured. Post-Op Care: Mice with TBI were monitored for 1 h post-injury and then allowed to recover overnight in a heated recovery cage with accessible food and hydrogel. The next day, mice were returned to their home cages. In these experiments, no analgesics were provided. Mice were weighed and monitored for lethargy (lack of movement) and infection (redness and pus around the incision site) daily throughout the experiments (7 days). Removal criteria included a loss of 20% of baseline bodyweight, sustained lethargy, paralysis, or surgical site infection. In this study, 5 mice were removed based on these criteria. Immunohistochemistry and Analysis: Mice were perfused with phosphate buffered saline (PBS) followed by 4% PFA. Brains were removed, post-fixed, and dehydrated in 30% sucrose. Brains were flash-frozen via isopentane, and then coronal sections (30 µm) were collected, washed, blocked, (0.1% Triton X, 5% BSA, and 5% NDS) and incubated with primary antibodies for rabbit anti-IBA1 (1:1000, Wako, Cat#019-19741, RRID:AB_839504), goat anti-IBA1 (1:500, Wako, #011-27991, RRID:AB_2935833), goat anti-GFAP (1:500, Abcam Cat#ab53554, RRID:AB_880202), rabbit anti-STING (1:200, Proteintech, #19851-1-AP, RRID:AB_10665370), or mouse anti-NeuN (1:500, Abcam, Cat#ab104225, RRID:AB_10711153). Next, sections were washed, incubated with an appropriate fluorochrome-conjugated secondary antibody (donkey anti-rabbit, anti-mouse, or anti-goat; AlexaFluor 488/594/647; Invitrogen) then mounted and cover-slipped with Fluoromount (Beckman Coulter, Inc., Fullerton, CA). Fluorescent labeling was imaged using an EVOS FL Auto 2 imaging system (Thermo Fisher, Waltham, MA). To determine percent area of IBA1 + , GFAP + , STING + , or NeuN + labeling, single channel images were converted to 8-bit TIFF format and constant thresholds were used to quantify positively labeled pixels (ImageJ Software). Rod morphology of IBA1 + microglia were quantified based on length-to-width ratios as previously described [12].Values from 4-6 images per mouse were averaged and used to calculate group averages and variance from each group. To determine the number of Lipofuscin + foci, 10 NeuN + cells were selected at random and foci were counted. Lipofuscin (autofluorescence) was detected at 455 nm excitation and 583 nm emission [26]. To determine co-localization of IBA1 + and STING + or Lipofuscin + and NeuN + single channel images were converted to 8-bit TIFF format and Just Another Co-localization Plugin (JaCoP) was used to determine the correlation coefficient (ImageJ Software). For colocalization, 4-6 images per mouse were taken using a Nikon Ti2 inverted motorized microscope. Images were taken at 10x magnification as 13 mm z stacks. Denoise.ai was used to reduce background and increase image intensity. Images were analyzed by an investigator blinded to treatment groups. NanoString and nCounter Analysis: NanoString nCounter tissue collection and analysis was performed as previously described [12, 16, 27]. Each experimental group was duplicated in separate experiments, yielding four total experimental groups, with six biological replicates per group. In brief, cortex was collected 7 dpi, flash frozen in liquid nitrogen, and stored -80°C. RNA was isolated using the TRI-Reagent and isopropanol protocol (Sigma-Aldrich). RNA quality and integrity were confirmed using a BioAnalyzer PicoAssay by Chip (Agilent). Gene expression was quantified using the nCounter NanoString neuroinflammation panel targeting 770 genes (https://nanostring.com/). This was performed by the Genomics Core facility at The Ohio State University. Technical normalization was performed to positive and negative controls. Cortical RNA was normalized to the housekeeping gene Csnk2a2. This housekeeping gene was selected based on strong correlation with total counts ( R 2 >0.8). Differential gene expression analyses were performed using the DESeq2 package in R Studio. Results were generated based on injury, genotype and sex (e.g., TBI-STING +/+ vs TBI-mSTING -/- ). Statistically significant genes had a threshold set to p -adj<0.05. Ingenuity Pathway Analysis (IPA, Qiagen) was used to identify canonical pathways associated with the significant genes compared to the respective control (Con-STING +/+ or Con-mSTING -/- ). Results from IPA are represented by z -score. Gene names and fold changes were submitted to compare expression patterns in our dataset to IPA’s database. IPA results for canonical pathways (p2) were considered significant. Upstream Regulators were further filtered for activation z -scores (positive or negative) that were associated with either increased or decreased signaling. Percoll Enrichment of Brain Myeloid Cells: CD11b + cells were enriched from whole brain homogenates as described [10, 25, 28]. In brief, brains were manually homogenized using Potter homogenizers, and resulting homogenates were pelleted at 600g for 6 min. Supernatants were removed and cell pellets were resuspended in 70% isotonic Percoll (GE-Healthcare, Catalog #45-001-747). A discontinuous isotonic Percoll density gradient was layered as follows: 50%, 35%, and 0% (PBS). Samples were pelleted for 20 min at 2000 g, and cells were collected from the interphase between the 70% and 50% Percoll layers. These cells were referred to as enriched brain CD11b + cells based on previous studies demonstrating that viable cells isolated by Percoll density gradient yields 90% CD11b + cells [28]. RNA Extraction and qPCR: Percoll-enriched myeloid cells were lysed, stored at -80°C, and total RNA was extracted using the Picopure RNA Isolation Kit (ThermoFisher, KIT0204). RNA was normalized by concentration and reverse-transcribed to cDNA. The Applied Biosystems Taqman Gene Expression assay-on-demand protocol and recommended probes for each gene of interest was used for quantitative real-time PCR. Target genes including Tmem173 ( Sting ): Mm01158117_m1, H2-Eb1 : Mm00439221_m1, Irf7 : Mm00516791_g1, Cd68 : Mm03047343_m1, Tnf : Mm00443258_m1, and reference gene Gapdh : Mm99999915_g were determined using a QuantStudio 6 (Thermo Fisher) and data were analyzed using the comparative threshold method (ΔΔCt) with data expressed as fold-change from control. Novel Object Recognition (NOR) and Location (NOL): Novel object recognition (NOR) and novel object recognition (NOL) tasks were conducted as previously described [10, 11]. Briefly, these tests involved four 10 min phases each separated by 24 h: habituation (no objects), acclimation (2 objects), recognition (2 objects, with one new object), and location (2 objects, one new location). Discrimination index in the recognition and location trials was determined [(time novel -time familiar )/time total ] x100. Videos were analyzed by an investigator blinded to treatment groups. Plasma Neurofilament Analysis: Plasma neurofilament was assessed in duplicate using a Meso Scale Discovery R-PLEX Human Neurofilament L Assay (K1517XR-2) according to the manufacturer’s instructions and as described previously [29]. In brief, mice were euthanized, blood was collected and clarified at 6000 x g for 15 minutes, and plasma was frozen at −80°C until analysis. Neurofilament light chain (NF-L) was analyzed in plasma samples diluted two-fold. The concentration of neurofilament light chain (NF-L) (pg/ml) was determined using the MESO QuickPlex SQ 120 with reference to a standard curve. The standard curve was established using 8 provided calibrator standards (0-50,000 pg/mL). All samples were within the detection range of the standards. Nuclei Isolation: Nuclei were isolated for single nucleus RNA-sequencing as previously described [22]. In brief, each group ( n =3) was sacrificed simultaneously, then pooled. Each experimental group was duplicated in separate experiments, yielding four total experimental groups, with six biological replicates per group. Cortices were extracted then placed into 2 mL Dounce homogenizers with 1 mL of homogenization buffer. Cortices were homogenized, filtered using a 40 µM strainer and homogenates were clarified. Samples were resuspended in a PBS buffer with RNase Inhibitors (0.05 U/μL of Enzymatics RNAase-Inhibitor and Superase-Inhibitor) and re-pelleted. To remove myelin debris, samples were incubated with Myelin Removal Beads II (Miltenyi Biotec, #130-096-731) for 15 minutes at 4°C. Samples were washed (50% PBS and 50% PBS + 1% BSA) and re-pelleted. Supernatant was removed and samples were resuspended in 1 mL of wash buffer. Two LS columns (Miltenyi Biotec, Cat #130-042-401) were used to filter each of the samples, which were then pelleted and resuspended in 150 μL of wash buffer. Nuclei were counted with AO/PI (Logos Biosystems, #F23001) on a Luna-FL Cell Counter and fixed with a Nuclei Fixation Kit (Parse Biosciences, #SB1003) per the manufacturer’s instructions followed by rapid freezing at -80°C. Single-Nuclei Barcoding and Sub-library Generation: As previously described [22], The Parse Biosciences Whole Transcription Kit was used to barcode and generate eight separate sub-libraries with 12,500 nuclei per sub-library. DNA concentration was measured by Qubit 4 Fluorometer and a Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, #Q32851). A Bioanalyzer 2100 with a High Sensitivity DNA Assay chip was used to control quality of sub-libraries before samples were sequenced. Based on previous sequencing experiments, RNA was sequenced at a depth of 40,000 reads per nuclei using a NovaSeq S4 at the Advanced Genomics Core at The University of Michigan [22]. Single-Nuclei Sequencing Data Processing: Libraries were processed as previously described [22]. In brief, each fastq.gz file was downloaded and aligned to the Genome Reference Consortium Mouse Reference 39 (mm39) using the Parse Biosciences pipeline. Matrices were downloaded and manually filtered in RStudio using Seurat (v4.1.1). Low-quality nuclei and doublets were filtered using Seurat in R. Cell-type identification was done using previously established markers: endothelial cells ( Flt1 ), astrocytes ( Slc1a3 ), oligodendrocytes ( Mag ), microglia ( Csf1r ), and neurons ( Syt1 ). Differential gene expression was performed using the FindMarkers feature of Seurat with non-parametric Wilcoxon rank sum test. Pathway and master regulators analyses were performed with Ingenuity Pathway Analysis (IPA; Qiagen). Statistical Analysis: GraphPad Prism (Version 9; San Diego, CA) was used for analysis of variance (ANOVA) of histological and behavioral data. A Student’s t test was used as appropriate to determine differences between groups. Two-way ANOVA was used as appropriate to determine main effects and interactions between factors. Tukey’s test for multiple comparisonswas used for post-hoc analysis when main effects and/or interactions were determined. p<0 .05 was considered statistically significant. Statistical analysis for snRNA-sequencing using Seurat are described above. Outlier data values were determined using GraphPad Grubbs’ test with an Alpha value of 0.05 selected. Results TBI-induced STING expression in microglia was ablated by mSTING -/- . We previously reported that a global knockout of STING reduced TBI-associated neuroinflammation and cognitive impairment [22]. The objective here was to understand the cell specificity of STING signaling in microglia after diffuse TBI. First, a transgenic mouse line with an inducible knockout of STING in microglia was created (STING +/+ or mSTING -/- , Fig.1A). Next, STING +/+ and mSTING -/- mice were subjected to control or TBI (mFPI) and several parameters were evaluated 7 dpi (Fig.1B). For instance, time to self-right was assessed immediately after TBI. There were no differences between STING +/+ and mSTING -/- mice in self-righting times following TBI (Fig.1C). Next, Sting mRNA was determined in percoll-enriched microglia collected from the whole brain 7 dpi (Fig.1D). As expected, there was a main effect of genotype on Sting mRNA levels in microglia ( F 1,15 = 14.2, p <0.005 ) where mSTING -/- mice had the lowest expression of STING.Moreover, TBI increased STING mRNA in enriched microglia 7 dpi ( F 1,15 = 5.0, p <0.05), and this was ablated in mSTING -/- mice (Interaction, F 1,15 = 4.8, p <0.05). Post-hoc analysis confirmed TBI-STING +/+ mice had the highest expression of Sting in microglia compared to all other groups ( p <0.05). These mRNA data help validate the knockout of Sting in microglia. We have also reported that there was increased STING protein and morphological restructuring of microglia and astrocytes 7 dpi after diffuse TBI [22]. Thus, STING protein was assessed in the cortex 7 dpi (Fig.1E-F). Parallel to the mRNA data, TBI increased STING protein expression ( F 1,22 = 4.65, p <0.05) in the cortex 7 dpi, and this was influenced by genotype ( F 1,22 = 52.10, p <0.0001) with less STING protein expression in the mSTING -/- mice compared to STING +/+ mice (Fig.1E&F). Post-hoc analyses confirmed that TBI-STING +/+ mice had the highest levels of STING in the cortex compared to all other groups including the mSTING -/- mice ( p <0.001). Parallel to these data, STING expression was determined in IBA1 + microglia of the cortex 7 dpi. There was robust expression of STING 7 dpi in IBA1 + microglia of wild type (STING +/+ ) mice (Fig.1G&H). Specifically, 94% of IBA1 + microglia in the cortex expressed STING after TBI and this expression was reduced to 10% in the mSTING -/- mice ( p <0.001). Notably, there was non-microglia STING expression detected after TBI (Fig.1F). This increase of STING after TBI, however, was not apparent in cortical astrocytes (GFAP + ) or neurons (NeuN + ) (data not shown). These RNA and protein data validate that the mSTING -/- model is working as anticipated. Overall, Sting RNA and STING protein were increased in microglia 7 dpi, and both wereablated in microglia from the mSTING -/- mice. TBI-induced microglia reactivity 7 dpi was attenuated by mSTING -/- . Continuing with the influence of mSTING -/- on TBI responses (Fig.1A&B), cortical gliosis and microglial morphological restructuring was determined 7 dpi in male and female STING +/+ andmSTING -/- mice. As expected, there was a TBI-dependent increase in the percent area of GFAP + astrocytes ( F 1,25 = 33.56, p <0.0001, Fig.2A-B). This increase in cortical GFAP + expression 7 dpi was independent of mSTING(Fig.2A&B). For cortical microglia, there was a main effect of TBI on percent area of IBA1 + labeling ( F 1,25 = 55.46, p <0.0001, Fig.2C&D). This increase of cortical IBA1 + (percent area) after TBI was influenced by mSTING -/- (Interaction, F 1,25 = 9.30, p <0.05). Post-hoc analyses confirmed that TBI-STING +/+ mice had the highest IBA1 + percent area compared to all groups including the TBI-mSTING -/- mice ( p <0.05). These increases in IBA1 + expression are consistent with “reactive microglia” [30] detected after diffuse TBI [12, 25]. Another aspect of microglial restructuring post-TBI is increased rod-shaped microglia in the cortex [12, 31]. Here, rod-shaped microglia were increased 7 dpi in the medial cortex ( F 1, 24 = 11.84, p <0.005, Fig.2E&F). The increase in rod-shaped microglia, however, was independent of mSTING.Taken together, the reactive morphological profile of microglia 7 dpi was attenuated by mSTING -/- , but astrogliosis and rod-shaped microglia were unaffected. TBI-associated cortical inflammation was attenuated by mSTING -/- . Continuing with the assessment of the influence of mSTING -/- on TBI responses (Figs.1&2), cortical inflammation 7 dpi in male and female mice was assessed using NanoString nCounter neuroinflammation panel (770 genes). Genes that were differentially expressed (DEGs) between groups were determined using DESeq2 in R [32]. The first volcano plot (Fig.3A) shows the comparison between TBI-STING +/+ and Con-STING +/+ . There were 232 DEGs increased and 5 DEGs decreased after TBI in this comparison ( p -adj<0.05). Fig.3B shows the comparison between TBI-mSTING -/- versus Con-mSTING -/- . Here, there were 76 DEGs increased and no genes decreased by TBI in mSTING -/- mice ( p -adj<0.05). Fig.3C shows the comparison between TBI-mSTING -/- mice and TBI-STING +/+ . In this comparison, there were 2 DEGs increased and 82 DEGs decreased by mSTING -/- ( p -adj<0.05). As stated above, the TBI response between male and female mice was similar. To highlight this, the TBI comparison between male and female STING +/+ mice is shown (Fig.3D). Only two genes ( Kdm5d , Uty ) were differentially expressed after TBI in male and female mice. These DEGs were increased by TBI in males only and are Y-chromosome linked genes [33]. Thus, male and female data were collapsed and analyzed together.Overall, these volcano plots show that TBI induced gene expression in the cortex 7 dpi was robustly influenced by mSTING. These differences are highlighted in the Venn diagram and pie chart in Fig.3E. The Venn diagram represents DEGs that were uniquely increased in TBI-STING +/+ (173 DEGs), shared between the two groups (64) or unique to TBI-mSTING -/- (12). The pie chart shows the percentage of TBI-associated DEGs (249 total) that were attenuated by mSTING -/- (16%, reduced expression), prevented by mSTING -/- (70%, restoration to control levels), or not prevented by mSTING -/- (14%). The majority of the TBI-induced DEGs were attenuated or prevented by mSTING -/- . For instance, increased expression of myriad genes that were increased by TBI were either prevented ( Irf1, Ifi30, Ilra Irf8, Nfκb2) or attenuated ( Itbg5 , Itimt3 , Olfml3 ) by mSTING -/- (Fig.3F&G). Several inflammatory related DEGs were increased by TBI and this increase was either attenuated ( C1qb&c , Cd68 Cxcl10 ) or prevented ( Il1a, Cd14, Irak4 ) in the TBI-mSTING -/- mice (Fig.3F&G). There were also DEGs induced by TBI ( Tlr2 , Tlr4 , Irf7 , Lcn2 , and Sox10) that were not significantly attenuated or prevented by mSTING -/- (Fig.3H&I). Thus, not all inflammatory pathways 7 dpi relied on microglial STING. Overall, a majority of TBI-induced DEGs affected by TBI in the cortex 7 dpi were dependent on STING responses in microglia (86%) while 14% were independent of STING in microglia. Canonical pathways associated with inflammation and IFN signaling 7 dpi were attenuated by mSTING -/- . Continuing with the NanoString analysis,Ingenuity Pathway Analysis (IPA) was used to determine canonical pathways master regulators, and upstream regulators influenced by TBI or mSTING -/- . Canonical pathways induced by TBI and prevented by mSTING -/- are shown (Fig.4A). Pathways associated with interferon signaling (cGAS-STING Signaling, Interferon alpha/beta signaling, Interferon Gamma Signaling, Activation of IRF by Cytosolic Pattern Receptors) and neuroinflammation (Phagosome Formation, S100 Family Signaling, Pyroptosis Signaling, Macrophage Classical Activation, NF- κB Signaling, and iNOS Signaling) were all increased in TBI-STING +/+ mice ( p -adj<0.05). Moreover, all these pathways increased by TBI were prevented by mSTING -/- ( p -adj<0.05). Canonical pathways induced by TBI and unaffected mSTING -/- are also shown (Fig.4B). These mSTING independent pathways included Neutrophil Degranulation, Complement System, Autophagy, and TREM-1 signaling. Top master regulators induced by TBI and prevented by mSTING -/- are shown (Fig.4C-D). Master regulators associated with interferon signaling (STAT1, MYD88, IFNG) were increased by TBI while regulators associated with neuronal health (GLB1, NEU3, PTGER4, IRGM1) were decreased. Master regulators prevented by mSTING -/- include pathways associated with IFN-I (IFNG), neuroinflammation (C5AR1, TREM2, CCR2, IL1B) and neuronal health (LCP1, PTGER4). Next, upstream regulators induced by TBI and prevented by mSTING -/- are shown (Fig.4E-F). Upstream regulators induced by TBI and prevented by mSTING -/- included pathways associated with phagocytosis (NPC1) and neuroinflammation (IL1B). Taken together, TBI induces myriad inflammatory and interferon mediated genes that were dependent on STING in microglia. TBI-induced cognitive deficits 7 dpi were IFNAR1 in dependent. Our previous [22] and current data show that both global and microglia-selective STING knockouts reduce inflammation and support cognitive recovery after TBI. Another aspect of the cGAS-STING pathway is the interferon-α/β receptor 1 (IFNAR1), which is the primary receptor for type I interferons, alpha and beta [34-36]. These pathways were apparent in the NanoString analyses at 7 dpi in the cortex (Fig.4). Thus, we next examined components of cognition and inflammation in male global IFNAR1 -/- mice. These mice were subjected to control or TBI (mFPI) and cortical and hippocampal-mediated cognition was assessed 7 dpi using NOR/NOL (Fig.5A-F). There were no differences in total time exploring the objects between groups (Fig.5B). Fig.5C&D show there were TBI-induced deficits in NOR 6 dpi with reduced time exploring the novel object and impairments in the discrimination index (TBI, F 1,20 = 20.83, p <0.001), but these effects were independent of IFNAR1. These effects were mirrored in the NOL task 7 dpi (Fig.5E-G). Time spent with the object in the novel location and discrimination index were reduced by TBI (F 1,20 = 70.15, p <0.0001, Fig.5E-G), but again these effects were independent of IFNAR1. After completion of the NOR/NOL cognitive assessment in these mice, cortices were extracted 7 dpi for RNA analyses. TBI increased interferon receptor-related Irf7 expression, and this increase was dependent on IFNAR1(Interaction, F 1 , 20 , = p <0.0017, Fig.5H). Post-hoc analysis confirmed that Irf7 expression was highest in the TBI-WT group compared to all other groups including the TBI-IFNAR1 -/- group ( p <0.0001, Fig.5H). These Irf7 data are consistent with the global knockout of IFNAR1. Moreover, several genes associated with inflammation ( Tnf, Gfap, H2-eb1 ) were increased in the cortex 7 dpi (TBI, F 1,18 = 7.92, p <0.05, for each, Fig.6I-K). The increases in these mRNA levels in the cortex 7 dpi, however, were independent of IFNAR1. Collectively, TBI-associated cognitive deficits and inflammatory mRNA expression in the cortex 7 dpi were independent of IFNAR1. Neuronal injury and cognitive deficits 7 dpi were mSTING dependent. Our data show that mSTING (and not IFNAR1) was important for inflammation after diffuse TBI. Moreover , our previous single cell and single nuclei RNA-seq studies show reduced homeostasis of cortical neurons 7 dpi was dependent on microglia [11, 22]. Based on these data, neuronal health/injury was assessed 7 dpi. First, NeuN + signaling [37] and lipid debris (i.e., lipofuscin) in the cortex were assessed 7 dpi [26, 38] . For NeuN + labeling in the cortex 7 dpi, percent area of NeuN + was influenced by TBI and mSTING -/- (Interaction, F 1,24 = 9.68, p <0.005, Fig.6A&B). Post hoc analyses indicates that TBI-STING +/+ mice had the lowest NeuN + expression compared to all groups including the TBI-mSTING -/- mice ( p <0.05, Fig.6B). Lipofuscin accumulation in the brain with age, disease, or brain injury may also represent reduced homeostasis of neurons and glia [38-40]. There was auto-fluorescent lipid debris visible in the cortex 7 dpi, especially within NeuN+ cells (Fig.6C). Quantification indicates that there tended to be increased auto-fluorescent lipid debris in cortical neurons (NeuN + ) 7 dpi ( F 1,19 = 3.19, p =0.08, Fig.6D) that tended to be reduced by genotype ( F 1,19 = 3.93, p =0.06, Fig.6D). Thus, there was reduced NeuN + signaling and increased lipofuscin in cortical neurons 7 dpi that was attenuated by mSTING -/- . Next, neurofilament light chain (NF-L), a relevant biomarker of neural injury after TBI [40], was determined in the plasma of mice [29]. TBI increased NF-L protein (pg/ml) levels ( F 1,23 = 28.37, p <0.0001, Fig.6E), and this increase was influenced by mSTING -/- (Interaction, F 1,23 = 9.99, p <0.005). Post-hoc analyses confirmed TBI-STING +/+ mice had the highest average NF-L expression (~3,000 pg/ml) in the plasma compared to all groups including the TBI-mSTING -/- mice ( p <0.005). We interpret these results to indicate that TBI increased neuronal damage and dysfunction in the cortex 7 dpi that was dependent on STING in microglia. In a similar study, control and mSTING -/- mice were subjected to control or TBI (mFPI), and cortical and hippocampal mediated cognition was assessed 7 dpi using NOR/NOL (Fig.6F-K). There were no differences in total time exploring the objects between groups (Fig.6F). Fig.6G-H shows TBI-induced reductions in exploration of the novel object 6 dpi (TBI, F 1,39 = 24.53, p <0.0001). Time spent interacting with the novel object was influenced by TBI and mSTING -/- (Interaction, F 1,39 =12.01, p <0.005, Fig.6G-H). Post-hoc analyses confirmed that TBI-STING +/+ mice spent the least amount of time with the novel object compared to all other groups, including the mSTING -/- mice ( p <0.0001, Fig.6G&H). These effects and interactions were mirrored in the NOL task at 7 dpi (Fig.6I-K). Time spent interacting with the novel object was influenced by TBI and genotype (Interaction, F 1,43 =10.81, p <0.005, Fig.6J&K). Post-hoc analyses confirmed that TBI-STING +/+ mice spent the least amount of time with the novel object compared to all other groups, including the TBI-mSTING -/- mice ( p <0.05, Fig.6J&K). Overall, microglial STING signaling was critical for neuronal dysfunction and cognitive impairment following TBI. Single nucleus RNA-sequencing of cortical neurons 7 days after TBI.. We have reported that microglia and type I interferon responses were associated with reduced neuronal homeostasis in the cortex 7 dpi [22]. Here, we aimed to determine the degree to which this was dependent on STING signaling from microglia. Thus, single nucleus RNA-sequencing (snRNA-seq) was conducted in cortical samples after control or TBI (7 dpi) in male and female STING +/+ or mSTING -/- mice. Cortices were dissected, nuclei were isolated, fixed, and barcoded at 7 dpi (Fig.7A). Fig.7B shows that 89,320 nuclei were clustered into twenty distinct clusters. Clusters were identified based on gene expression of distinct markers (Fig.7C-E) ( Syt1 - neurons, Slc1a3 -astrocytes, Mag – oligodendrocytes, Flt1 – endothelia, and Csf1r –microglia). In line with previous work using snRNA-seq, 90% of cells detected in Fig.7D were neurons [22, 41, 42]. To delineate the neuronal profile with TBI and mSTING -/- 7 dpi, cortical neurons were subset and re-clustered (Fig.7F) using existing gene markers ( Slc17a7 , Cux1/2 , Rorb , Gad1/2 , Foxp2 , Adarb2 ) to classify the neuronal populations (Fig.7G&I). The distribution of cells based on the four experimental groups is shown (Fig.7H). Overall, there were approximately 80,000 nuclei collected from Syt1 + cortical neurons 7 dpi, and these nuclei were represented in all the experimental groups. Ablation of microglial STING attenuated the response to TBI in cortical neurons. Continuing with the snRNA-seq analyses of Syt1 + cortical neurons 7 dpi, the pie chart (Fig.8A) shows the distribution of specific neuronal profiles resolved. Consistent with our previous snRNA-seq experiments assessing cortical neurons [22], 36% of the Syt1 + nuclei corresponded to upper layer neurons ( Cux1/2 + ), 30% of the Syt1 + nuclei corresponded to layer 4 neurons ( Rorb + ), 21% of the Syt1 + nuclei corresponded to deep layer neurons ( Foxp2 + ), and 13% Syt1 + nuclei corresponded to inhibitory neurons ( Gad1/2 + ). These neuronal sub-clusters were used for analyses. Fig.8B highlights that TBI resulted in both increased and decreased mRNA expression in cortical neurons 7 dpi, with more overall suppression of gene expression. For upper layer neurons, there were 1,146 DEGs ( p -adj<0.05), with 697 increased and 449 decreased DEGs after TBI. Moreover, the influence of TBI on these upper layer neurons was 50% dependent on mSTING (600 DEGs, Fig.8C). For layer 4 neurons, there were 749 DEGs ( p -adj<0.05) with 227 increased and 522 decreased DEGs after TBI. The influence of TBI on layer 4 neurons was 45% dependent on mSTING (357 DEGs, Fig.8C). For deep layer neurons, there were 1104 DEGs ( p -adj<0.05) after TBI with 445 increased and 659 decreased DEGs. The influence of TBI on deep layer neurons was 47% dependent on mSTING (591 DEGs). Last, there were 241 DEGs ( p -adj<0.05) in the inhibitory neurons with 49 increased and 192 decreased. In inhibitory neurons, the influence of TBI was 64% dependent on mSTING for 154 DEGs ( p -adj<0.05, Fig.8C). Thus, there was a robust effect of TBI on cortical neurons 7 dpi and about 50% of the DEGs were prevented by mSTING -/- . Notably, both male and female mice were included in these snRNA-seq studies. Although these studies were not appropriately powered to make comparisons based on sex, we examined male and female mice within the TBI-STING +/+ group. The top DEGs are shown in the dot plot for male TBI versus female TBI functional wild type mice (Fig.8C). Xist was increased in female wild type TBI mice compared to males and this is an X linked gene [43]. Uty , Eif2s3y , Kdm5d , and Dxd3y were increased in male TBI mice compared to female TBI mice. These genes are all y-linked [33, 44, 45]. Thus, male and female snRNA-seq data were analyzed together. To visualize the significant DEGs in Fig8B&C, volcano plots are shown (Fig8E-J). For upper layer neurons (UL), the volcano plot shows the comparison between Con-STING +/+ and TBI-STING +/+ mice with 697 DEGs increased and 449 DEGs decreased ( p -adj<0.05, Fig.8E). For instance, there was a TBI associated reduction in two synaptic plasticity related genes, Arc and Homer1 . Fig.8F shows the comparison between Con-mSTING -/- and TBI-mSTING -/- mice.In this comparison, 1728 DEGs were increased by TBI and 1312 DEGs were decreased. Fig.8G shows comparison between TBI-mSTING -/- and TBI-STING +/+ mice. Here, there were 44 DEGs increased and 148 DEGs decreased. These data highlight a reduced influence of TBI on upper layer cortical neurons in the mSTING -/- mice compared to controls (STING +/+ mice). For instance, the reduction of Homer1 and Arc after TBI were prevented in the TBI-mSTING -/- group. For deep layer neurons (DL), the volcano plot shows comparison between Con-STING +/+ and TBI-STING +/+ mice with 445 DEGs increased and 659 DEGs decreased ( p -adj<0.05, Fig.8H). For instance, there was a TBI associated reduction in three synaptic plasticity related genes, Arc, Bdnf, and Homer1 . Reductions also evident in ApoE (lipid transport), Calm1 (calcium signaling), and Atg4a (autophagy). Fig.8I shows the comparison between Con-mSTING -/- and TBI-mSTING -/- mice.There were 924 DEGs increased and 1662 DEGs decreased. These data highlight that there was a reduced influence of TBI on deep layer cortical neurons in the mSTING -/- mice compared to controls (STING +/+ mice). For instance, the reduction of Atg4a and Homer1 after TBI were prevented in the TBI-mSTING -/- group (Fig.8J). Overall, TBI influenced the RNA profile of cortical neurons with a suppressive effect that was influenced by mSTING. Ablation of microglial STING attenuated TBI-induced imbalance in neuronal homeostasis of cortical neurons. Continuing with the snRNA-seq analyses of Syt1 + cortical neurons 7 dpi, DEGs ( p- adj<0.05) were analyzed in IPA for canonical pathways, master regulators and upstream regulators. Significant canonical pathways ( z score, -3.8 to 3.9) influenced by TBI are shown in upper layer (UL), layer 4 (L4), deep layer (DL) and inhibitory (IN) cortical neurons (Fig.9A). These pathways were conserved across the four neuronal subtypes. For example, TBI increased canonical pathways associated with neuronal restructuring (e.g., Cilium Assembly, VDR/RXR Activation, RHOGDI Signaling, Transcriptional Regulation by MECP2, and Netrin Signaling) and inhibition of growth (PTEN signaling). TBI also suppressed canonical pathways associated with neuronal homeostasis and metabolism (CREB Signaling, Synaptogenesis, S100 Family Signaling). These data are consistent with our previous work on the effects of TBI on neurons [22]. Next the significant canonical pathways induced by TBI and prevented by mSTING are shown in upper layer (UL), layer 4 (L4), deep layer (DL) and inhibitory (IN) cortical neurons (Fig.9B). Canonical pathways that were decreased following TBI and influenced by mSTING were associated with neuronal health (Oxytocin Signaling, Endothelin-1 Signaling, CREB Signaling, and Orexin Signaling). Canonical pathways that were increased by TBI associated with neuronal restructuring (Cilium Assembly) and inhibition of growth (PTEN) were also prevented by mSTING -/- (Fig.9B). Next, significant master regulators that were influenced by TBI are shown in upper layer (UL), layer 4 (L4), deep layer (DL) and inhibitory (IN) cortical neurons (Fig.9C). TBI increased DLGAP3, MYCBP2, RELN, CDK5 in upper layer and layer 4 neurons, and decreased CAMK, CREM, IL-4R, and GRM5. Master regulators reduced by TBI associated with neuronal homeostasis (e.g., CAM4K, CREM, IL4R, GRM5, ADORA2A) were prevented by mSTING, especially in deep layer neurons (Fig.9D). As such, deep layer neurons had the most master regulators prevented by mSTING -/- (7). Upper layer neurons had the most upstream regulators induced by TBI and prevented by mSTING -/- (7). These upstream regulators are associated with neuronal homeostasis (e.g., MECP2, MKNK1, CREB1, IL4R, CREM, ADORA2A, BDNF). These regulators were reduced by TBI, and this reduction was prevented by mSTING -/- (Fig.9F). Upstream regulators increased by TBI include HNRNPU, PTF1A, FMR1, and MAPT and decreased upstream regulators include BDNF, IL4R, CREM, and CREB1 (Fig.9E). These changes were prevented by mSTING, especially in upper layer cortical neurons (Fig.9F). Taken together, TBI reduced cortical neuronal homeostasis, and this was dependent on STING in microglia 7 dpi. Discussion We previously reported that a global knockout of the stimulator of interferons genes (STING) reduced chronic inflammation and cognitive impairment associated with diffuse TBI [ 22 ]. Thus, the aim of this study was to determine the degree to which a microglia-specific knockout of STING influenced neuroinflammation, neuronal dysfunction, and cognitive deficits induced by diffuse TBI. Here, TBI induced microglial morphological restructuring and cortical inflammation 7 dpi were mSTING dependent. In addition, neuronal injury and cognitive impairment 7 dpi were also dependent on mSTING. With snRNA-seq of cortical neurons after TBI, there were reductions in CREB signaling, synaptogenesis, and oxytocin signaling and increases in cilium assembly and PTEN signaling. These reductions in neuronal homeostasis were mSTING dependent. Collectively, ablation of STING in microglia attenuated TBI-induced IFN-dependent responses, cortical inflammation, cortical pathology, neuronal dysfunction, and cognitive impairment. One key finding of this study was that increased STING expression 7 days after TBI in the cortex was localized to IBA1 + microglia, and this increase in STING was ablated by microglial STING −/− . The increase in STING expression in the cortex after TBI is consistent with previous findings showing enhanced IFN-I responses after either diffuse [ 11 , 15 , 16 , 22 , 36 ] or penetrating TBI [ 23 , 24 , 35 , 46 ]. Moreover, studies of penetrating TBI induced by controlled cortical impact (CCI) indicate that STING is localized to IBA1 + microglia [ 23 , 24 , 46 ]. The extension here is that STING was localized to cortical microglia after diffuse TBI and this increase was ablated by a transgenic model of mSTING −/− . While STING induction was detected in other cell types including neurons and astrocytes after TBI [ 23 , 24 , 46 , 47 ], STING after diffuse TBI was localized in cortical microglia and undetectable in astrocytes and neurons. Assessment of mRNA from percoll enriched microglia paralleled these data with a TBI-dependent increase in STING mRNA 7 dpi and ablation by microglial STING −/− . These findings are also consistent with our previous reports using snRNA-seq that microglia, not neurons, expressed genes associated with the production of IFN-I after TBI [ 22 ]. These RNA and protein findings validate the targeted knock out of STING in microglia. Overall, TBI increased STING expression within IBA1 + microglia 7 dpi was ablated in mSTING −/− mice. Another relevant point is that TBI-induced microglial restructuring (IBA1 + percent area increase) 7 dpi was dependent on mSTING. Rod-shaped microglia and GFAP + astrocytes were also increased 7 dpi, but were independent of mSTING −/− . These data are similar to our previous reports where TBI-induced microglial restructuring was reduced by global STING −/− , but astrogliosis was unaffected [ 22 ]. In addition, another report showed that astrocytes were unresponsive to STING activation after TBI [ 16 ]. Rod-shaped microglia are detected in humans and rodents in the context of advanced age, neurodegeneration, and TBI [ 12 , 31 , 48 ], but their function is unclear. In a previous report, rod-shaped microglia were reduced in the cortex 7 dpi of global STING −/− mice [ 22 ]. Here, rod-shaped microglia were unaffected by mSTING −/− . One explanation for this difference is that rod-shaped microglia in the cortex 7 dpi are mSTING independent and may serve a neuroprotective role. For instance, these structurally unique and elongated microglia aligned with apical dendrites of damaged neurons in the cortex 7 dpi [ 12 ]. These cells were present 7 dpi in the cortex of mice with microglia depletion (PLX5622), which was associated with reduced neuroinflammation and cognitive improvement [ 11 ]. Furthermore, elimination of rod-shaped microglia using a TREM2 knock out in an ALS model increased neuronal hyperactivity, worsened motor deficits, and further reduced survival rates in mice [ 49 ]. Collectively, there were structurally divergent profiles of cortical glia 7 dpi and the reactive microglia profile was attenuated by mSTING −/− . Another point for discussion is the increased IFN-I and pro-inflammatory signaling in the cortex 7 dpi was dependent on microglial STING. For example, there were 232 genes detected in the NanoString panel (770 genes) associated with type I interferon signaling, inflammation, and antigen presentation 7 dpi. A majority of these TBI-associated genes were reduced (86%) by mSTING −/− . Notably, there were minimal sex differences detected in the cortical mRNA analyses with only two sex-linked genes ( Kdm5d and Uty ) [ 33 , 44 ] different between male and female TBI mice. Overall, TBI increased genes associated with IFN-I and inflammation in male and female mice, and these were reduced by mSTING −/− . Consistent with these DEGs, IPA canonical pathways and master regulator analyses showed myriad IFN-I and inflammatory pathways increased after TBI including activation of IRF, NFκB, and cGAS-STING. These increases in genes and pathways associated with IFN-I, inflammation, and microglial priming are consistent with previous reports 7 dpi [ 12 , 16 , 22 ]. Key pathways induced by TBI 7 dpi and prevented by mSTING −/− included cGAS-STING, NF-κB, and neuroinflammation signaling. Notably, some DEGs (35) and IPA pathways that were induced by TBI were unaffected by mSTING −/− . These DEGS were genes associated with the complement cascade ( C3, C4a ), astrocyte associated genes ( Aldh1l1, Gja1) and endothelia associated genes ( Blnk, Enpp6) . There were 12 total genes uniquely increased by TBI in mSTING −/− mice. A majority of these increased DEGs were neuronal ( Tubb3, Gria, Slc17a7, Rala, etc.) , and may represent improved neuroprotection following TBI in mSTING −/− mice. Thus, the inflammatory and IFN-I responses in the cortex 7 dpi were robustly influenced by STING in microglia. One notable finding of this study was that global IFNAR1 knockout did not reduce cortical inflammation or cognitive impairment 7 dpi. We and others have shown increased genes and pathways following diffuse and penetrating TBI related to the IFNAR1 pathway [ 11 , 15 – 17 , 22 – 24 , 35 , 36 ]. Presumably cGAS-STING activation in microglia after TBI increases Irf3 and corresponding IFN-I that would use the IFNAR1 [ 19 , 50 ]. Indeed, several studies show improvements in inflammation, cognition, and neurologic dysfunction following selective modulation of the IFNAR1 pathway with diffuse [ 36 ] and penetrating TBI [ 35 ]. Here, global IFNAR1 knockout did not reduce cortical inflammation or cognitive impairment 7 dpi. Global IFNAR1 knockout, however, reduced the induction of Irf7 7 dpi. One explanation is that the STING pathway also promotes NF-κB-mediated genes (e.g., IL-6 , TNF and IL-1 ) [ 20 , 21 ] and these pro-inflammatory cytokines are more responsible for the downstream effects on neurons and cognitive processes. For instance, the IL-1 receptor-1 (IL1-R1) is highly expressed on DG neurons of the hippocampus [ 41 , 51 ] and IL-1/IL-R1 responses are evident chronically after closed head TBI [ 52 ]. Another explanation is that there are reported confounds of IFNAR1 −/− . For instance, one report showed that global and microglia specific knockouts of IFNAR1 led to dysfunctional microglia with a “bubble” phagosome formation and increased accumulation of DNA-damaged neurons [ 53 ]. Another study showed that astrocytic IFNAR1 deletion in mice caused cognitive dysfunction and reduced synaptic plasticity [ 54 ]. Because of the potential confounds of these global IFNAR1 −/− mice, we conducted only limited studies with them and instead focused on mSTING −/− mice. Taken together, the interpretation is that ablating STING in microglia was more beneficial than targeting IFNAR1 because STING is upstream and thus affects both IFN-I and NF-κB mediated responses after diffuse TBI. Another relevant finding was the neuropathological influences of TBI (7 dpi) were dependent on STING in microglia. For example, there was reduced percent area labeling of NeuN + in the cortex 7 dpi, which was attenuated in TBI-mSTING mice. The interpretation is that reduced NeuN + labeling corresponds with more dysfunction or atypical neurons in the cortex after diffuse TBI. A similar TBI-induced reduction of NeuN in the cortex 7 dpi was detected in a weight drop model of TBI in mice (up to 6 months later) and associated with increase blood brain barrier permeability after TBI [ 37 ]. In the same study, the reduced NeuN + neurons were associated with reduced synaptic plasticity [ 37 ]. Parallel to this, lipofuscin (i.e., autofluorescent lipid debris) detected here in cortical neurons may also represent reduced homeostasis [ 55 ]. Indeed, several studies show increased lipofuscin in the brain with age or after TBI [ 26 , 38 ]. Moreover, increased lipofuscin after TBI in aged mice was associated with neuronal loss, glial activation, and oxidative stress [ 38 ]. Taken together, targeted mSTING deletion prevented inflammatory cytokine, chemokine, and IFN-I production that deleteriously affected neuronal homeostasis in the cortex. Consistent with the above data, we show novel data that the TBI-associated increase in plasma NF-L (7 dpi) was attenuated in the TBI-mSTING −/− mice. NF-L is a clinically validated biomarker for neuronal and axonal injury after moderate to severe TBI in humans [ 40 , 56 ]. Moreover, use of plasma NF-L as a biomarker reflecting the extent of underlying neuropathology in humans has been validating using MRI and cerebral microdialysis [ 40 ]. Thus, we interpret the data to show ablating STING in microglia was neuroprotective with less axonal and neuronal damage after diffuse TBI. Non-selectively inhibition of microglia after CNS injury may have off target effects that worsen recovery. For instance, minocycline reduced microglia activation in humans (by MRI) after TBI, but increased the neuronal damage marker, NF-L, in the plasma [ 57 ]. Furthermore, depletion of microglia prior to spinal cord injury worsened pathology by interfering with astrocytic dynamics [ 58 ]. Thus, inhibition of specific microglia pathways, like STING, are critical for addressing chronic neuroinflammation elicited by traumatic CNS injury while minimizing off target effects of treatment. Parallel with the evidence of increased neuronal injury 7 dpi, TBI reduced cortical/hippocampal dependent memory with reduced novel object/exploration 7 dpi. Here, novel data shows that these reductions in cognition after TBI were mSTING dependent. These data are consistent with previous studies of global STING −/− [ 22 ] and microglial elimination [ 11 ] showing that limiting inflammatory pathways in microglia improved behavioral and cognitive recovery after diffuse TBI. Taken together, TBI induced neuronal and cognitive dysfunction 7 dpi associated with increased NF-L, reduced NeuN + expression, and cognitive deficits were prevented by mSTING −/− . Consistent with our previous data [ 11 , 22 ] snRNA-seq analysis in the cortex 7 dpi shows suppression of neuronal pathways associated with metabolism and homeostasis (CREB Signaling in Neurons, Synaptogenesis, S100 Signaling, GPCR Mediated Nutrient Sensing, and Cholecystokinin Signaling). This pattern was conserved across all neuronal subtypes sampled, especially the excitatory neurons (DL, L4, and UL) indicating a shared pattern of cortical neuron suppression. Here, novel data shows that t extension was that STING ablation in microglia prevented these imbalances. For instance, approximately 50% of all DEGs influenced by TBI were prevented in microglial mSTING −/− mice. The mSTING dependent reversals of the TBI effects in upper layer (UL), layer 4 (L4), and deep layer (DL) neurons included canonical pathways (Cilium Assembly, RHODI, and Netrin Signaling) and master regulators (HNRNPU, PTF1A, FMR1, MAPT) associated with neuronal restructuring. These RNA data are consistent with the physiological neuronal restructuring and dendritic atrophy detected after TBI [ 11 ]. These physiological changes reported after TBI in mice were associated with cognitive dysfunction and depressive-like behavior [ 10 , 11 ]. In addition, the mSTING dependent reversals of the TBI effects in UL, L4, and DL neurons included canonical pathways (Oxytocin Signaling, GPCR Mediated Nutrient Sensing, CREB Signaling, S100 Family Signaling) and master regulators (MECP2, CREB1, IL4R, and BDNF) associated with neuronal homeostasis and metabolism. These pathways and master regulators increased following TBI are related to neuronal and synaptic remodeling, and likely represent the same cassette of genes previously reported to be associated with the Phosphatase and Tensin Homolog (PTEN) signaling [ 22 ]. PTEN is a master regulator of neuronal and dendritic morphological restructuring [ 59 ], and the increase in PTEN following traumatic CNS injuries is a potential target of intervention [ 60 , 61 ]. In summary, the reduced homeostasis of neurons in the cortex 7 dpi was associated with increased STING responses in microglia. A final point for discussion is that this study was not powered for sex comparisons. Nonetheless, male and female mice were used and there were similar patterns of responses following TBI. For instance, NanoString and single nucleus RNA-seq analyses revealed the same sex-linked genes ( Uty , Kdm5d ) were the top DEGs between male and female mice 7 dpi. Again, sex differences in TBI is an important issue and several reports indicate sexually dimorphic responses following TBI [ 62 – 65 ]. Nonetheless, STING and IFN-I responses to diffuse TBI were conserved in male and females 7 dpi. In conclusion, while sex differences are important aspects to interrogate with TBI, STING, and IFN-I responses after diffuse TBI were conserved in males and females. In summary, we show that diffuse TBI induced a STING response in microglia associated with IFN-I that impairs cortical neuronal homeostasis and cognition. The TBI-induced neuronal restructuring, neuronal damage, and snRNA-profiles were dependent on microglial STING. Targeted pharmacotherapies to reduce this microglial STING response may be beneficial in reducing neuroinflammation and corresponding neurocognitive complications following TBI. Declarations Funding Declaration: This research was supported by a National Institute of Neurological Disorders and Stroke (NINDS) R01 grant (NS118037 to JPG). JMP and ACD were supported by OSU Distinguished University Fellowships. LMW was supported by an NINDS T32 grant (NS105864). In addition, this work was supported by an NINDS P30 Core Grant (NS045758) to the Center for Brain and Spinal Cord Repair. Acknowledgements: . BioRender was used to construct Figure 8C. The authors thank Dr. Kim Green (University of California-Irvine) and his laboratory for their help with the protocol and initial pilot study for the analyses of neurofilament light chain (NF-L) in the plasma. The authors also thank Ryan Bullard, Braedan Oliver, Zoë Tapp-Poole, and Lauren Otto (The Ohio State University) for with their technical assistance on aspects on the project. Author Disclosures: The authors have no financial conflicts of interest to disclose. Data Availability: The data that support the findings of this study are available from the corresponding author upon reasonable request. Author Contributions: All authors contributed to the study’s conception and design. Material preparation and data collection were performed by JMP, SGG, LMW, ACD, and CEB. Experimental design and data analyses were performed by JMP and JPG. The manuscript was written by JMP and JPG and all authors were involved in editing. Funding acquisition, administration, and supervision were performed by JPG. All authors read and approved the final manuscript. Ethics Declaration: We affirm that this paper contains original data that have not been submitted elsewhere for publication and that all authors have read and approved the manuscript. All authors also report no financial conflicts of interest. All procedures were performed in accordance with the National Institute of Health Guidelines for the Care and Use of Laboratory Animals, the Public Health Service’s Policy on Human Care and Use of Laboratory Animals, and the Guide for the Care and Use of Laboratory Animals and were approved by The Ohio State University Institutional Laboratory Animal Care and Use Committee. References M. Faul, V. Coronado, Epidemiology of traumatic brain injury, Handb Clin Neurol 127 (2015) 3-13. O.N. Kokiko-Cochran, J.P. Godbout, The Inflammatory Continuum of Traumatic Brain Injury and Alzheimer's Disease, Front Immunol 9 (2018) 672. L.M. Wangler, J.P. Godbout, Microglia moonlighting after traumatic brain injury: aging and interferons influence chronic microglia reactivity, Trends Neurosci 46(11) (2023) 926-940. R.J. Henry, D.J. Loane, Targeting chronic and evolving neuroinflammation following traumatic brain injury to improve long-term outcomes: insights from microglial-depletion models, Neural Regen Res 16(5) (2021) 976-977. D.J. Loane, A. Kumar, B.A. Stoica, R. Cabatbat, A.I. Faden, Progressive neurodegeneration after experimental brain trauma: association with chronic microglial activation, J Neuropathol Exp Neurol 73(1) (2014) 14-29. A.F. Ramlackhansingh, D.J. Brooks, R.J. Greenwood, S.K. Bose, F.E. Turkheimer, K.M. Kinnunen, S. Gentleman, R.A. Heckemann, K. Gunanayagam, G. Gelosa, D.J. Sharp, Inflammation after trauma: microglial activation and traumatic brain injury, Ann Neurol 70(3) (2011) 374-83. J.M. Coughlin, Y. Wang, I. Minn, N. Bienko, E.B. Ambinder, X. Xu, M.E. Peters, J.W. Dougherty, M. Vranesic, S.M. Koo, H.H. Ahn, M. Lee, C. Cottrell, H.I. Sair, A. Sawa, C.A. Munro, C.J. Nowinski, R.F. Dannals, C.G. Lyketsos, M. Kassiou, G. Smith, B. Caffo, S. Mori, T.R. Guilarte, M.G. Pomper, Imaging of Glial Cell Activation and White Matter Integrity in Brains of Active and Recently Retired National Football League Players, JAMA Neurol 74(1) (2017) 67-74. J.M. Coughlin, Y. Wang, C.A. Munro, S. Ma, C. Yue, S. Chen, R. Airan, P.K. Kim, A.V. Adams, C. Garcia, C. Higgs, H.I. Sair, A. Sawa, G. Smith, C.G. Lyketsos, B. Caffo, M. Kassiou, T.R. Guilarte, M.G. Pomper, Neuroinflammation and brain atrophy in former NFL players: An in vivo multimodal imaging pilot study, Neurobiol Dis 74 (2015) 58-65. V.E. Johnson, J.E. Stewart, F.D. Begbie, J.Q. Trojanowski, D.H. Smith, W. Stewart, Inflammation and white matter degeneration persist for years after a single traumatic brain injury, Brain 136(Pt 1) (2013) 28-42. C.E. Bray, K.G. Witcher, D. Adekunle-Adegbite, M. Ouvina, M. Witzel, E. Hans, Z.M. Tapp, J. Packer, E. Goodman, F. Zhao, T. Chunchai, S. O'Neil, S.C. Chattipakorn, J. Sheridan, O.N. Kokiko-Cochran, C. Askwith, J.P. Godbout, Chronic Cortical Inflammation, Cognitive Impairment, and Immune Reactivity Associated with Diffuse Brain Injury Are Ameliorated by Forced Turnover of Microglia, J Neurosci 42(20) (2022) 4215-4228. K.G. Witcher, C.E. Bray, T. Chunchai, F. Zhao, S.M. O'Neil, A.J. Gordillo, W.A. Campbell, D.B. McKim, X. Liu, J.E. Dziabis, N. Quan, D.S. Eiferman, A.J. Fischer, O.N. Kokiko-Cochran, C. Askwith, J.P. Godbout, Traumatic Brain Injury Causes Chronic Cortical Inflammation and Neuronal Dysfunction Mediated by Microglia, J Neurosci 41(7) (2021) 1597-1616. K.G. Witcher, C.E. Bray, J.E. Dziabis, D.B. McKim, B.N. Benner, R.K. Rowe, O.N. Kokiko-Cochran, P.G. Popovich, J. Lifshitz, D.S. Eiferman, J.P. Godbout, Traumatic brain injury-induced neuronal damage in the somatosensory cortex causes formation of rod-shaped microglia that promote astrogliosis and persistent neuroinflammation, Glia 66(12) (2018) 2719-2736. R.J. Henry, R.M. Ritzel, J.P. Barrett, S.J. Doran, Y. Jiao, J.B. Leach, G.L. Szeto, J. Wu, B.A. Stoica, A.I. Faden, D.J. Loane, Microglial Depletion with CSF1R Inhibitor During Chronic Phase of Experimental Traumatic Brain Injury Reduces Neurodegeneration and Neurological Deficits, J Neurosci 40(14) (2020) 2960-2974. H. Gangal, J. Iannucci, Y. Huang, R. Chen, W. Purvines, W.T. Davis, A. Rivera, G. Johnson, X. Xie, S. Mukherjee, V. Vierkant, K. Mims, K. O'Neill, X. Wang, L.A. Shapiro, J. Wang, Traumatic Brain Injury Exacerbates Alcohol Consumption and Neuroinflammation with Decline in Cognition and Cholinergic Activity, bioRxiv (2024). B.P. Todd, M.S. Chimenti, Z. Luo, P.J. Ferguson, A.G. Bassuk, E.A. Newell, Traumatic brain injury results in unique microglial and astrocyte transcriptomes enriched for type I interferon response, J Neuroinflammation 18(1) (2021) 151. L.M. Wangler, C.E. Bray, J.M. Packer, Z.M. Tapp, A.C. Davis, S.M. O'Neil, K. Baetz, M. Ouvina, M. Witzel, J.P. Godbout, Amplified Gliosis and Interferon-Associated Inflammation in the Aging Brain following Diffuse Traumatic Brain Injury, J Neurosci 42(48) (2022) 9082-9096. J.P. Barrett, S.M. Knoblach, S. Bhattacharya, H. Gordish-Dressman, B.A. Stoica, D.J. Loane, Traumatic Brain Injury Induces cGAS Activation and Type I Interferon Signaling in Aged Mice, Front Immunol 12 (2021) 710608. H. Ishikawa, Z. Ma, G.N. Barber, STING regulates intracellular DNA-mediated, type I interferon-dependent innate immunity, Nature 461(7265) (2009) 788-92. A. Decout, J.D. Katz, S. Venkatraman, A. Ablasser, The cGAS-STING pathway as a therapeutic target in inflammatory diseases, Nat Rev Immunol 21(9) (2021) 548-569. T. Abe, G.N. Barber, Cytosolic-DNA-mediated, STING-dependent proinflammatory gene induction necessitates canonical NF-kappaB activation through TBK1, J Virol 88(10) (2014) 5328-41. S. Yum, M. Li, Y. Fang, Z.J. Chen, TBK1 recruitment to STING activates both IRF3 and NF-kappaB that mediate immune defense against tumors and viral infections, Proc Natl Acad Sci U S A 118(14) (2021). J.M. Packer, C.E. Bray, N.B. Beckman, L.M. Wangler, A.C. Davis, E.J. Goodman, N.E. Klingele, J.P. Godbout, Impaired cortical neuronal homeostasis and cognition after diffuse traumatic brain injury are dependent on microglia and type I interferon responses, Glia 72(2) (2024) 300-321. L.E. Fritsch, J. Ju, E.K. Gudenschwager Basso, E. Soliman, S. Paul, J. Chen, A.M. Kaloss, E.A. Kowalski, T.C. Tuhy, R.D. Somaiya, X. Wang, I.C. Allen, M.H. Theus, A.M. Pickrell, Type I Interferon Response Is Mediated by NLRX1-cGAS-STING Signaling in Brain Injury, Front Mol Neurosci 15 (2022) 852243. L.E. Fritsch, C. Kelly, J. Leonard, C. de Jager, X. Wei, S. Brindley, E.A. Harris, A.M. Kaloss, N. DeFoor, S. Paul, H. O'Malley, J. Ju, M.L. Olsen, M.H. Theus, A.M. Pickrell, STING-Dependent Signaling in Microglia or Peripheral Immune Cells Orchestrates the Early Inflammatory Response and Influences Brain Injury Outcome, J Neurosci 44(12) (2024). A.M. Fenn, J.C. Gensel, Y. Huang, P.G. Popovich, J. Lifshitz, J.P. Godbout, Immune activation promotes depression 1 month after diffuse brain injury: a role for primed microglia, Biol Psychiatry 76(7) (2014) 575-84. S.M. O'Neil, K.G. Witcher, D.B. McKim, J.P. Godbout, Forced turnover of aged microglia induces an intermediate phenotype but does not rebalance CNS environmental cues driving priming to immune challenge, Acta Neuropathol Commun 6(1) (2018) 129. Z.M. Tapp, S. Cornelius, A. Oberster, J.E. Kumar, R. Atluri, K.G. Witcher, B. Oliver, C. Bray, J. Velasquez, F. Zhao, J. Peng, J. Sheridan, C. Askwith, J.P. Godbout, O.N. Kokiko-Cochran, Sleep fragmentation engages stress-responsive circuitry, enhances inflammation and compromises hippocampal function following traumatic brain injury, Exp Neurol 353 (2022) 114058. E.S. Wohleb, A.M. Fenn, A.M. Pacenta, N.D. Powell, J.F. Sheridan, J.P. Godbout, Peripheral innate immune challenge exaggerated microglia activation, increased the number of inflammatory CNS macrophages, and prolonged social withdrawal in socially defeated mice, Psychoneuroendocrinology 37(9) (2012) 1491-505. K.M. Tran, S. Kawauchi, E.A. Kramar, N. Rezaie, H.Y. Liang, J.S. Sakr, A. Gomez-Arboledas, M.A. Arreola, C.D. Cunha, J. Phan, S. Wang, S. Collins, A. Walker, K.X. Shi, J. Neumann, G. Filimban, Z. Shi, G. Milinkeviciute, D.I. Javonillo, K. Tran, M. Gantuz, S. Forner, V. Swarup, A.J. Tenner, F.M. LaFerla, M.A. Wood, A. Mortazavi, G.R. MacGregor, K.N. Green, A Trem2(R47H) mouse model without cryptic splicing drives age- and disease-dependent tissue damage and synaptic loss in response to plaques, Mol Neurodegener 18(1) (2023) 12. R.C. Paolicelli, A. Sierra, B. Stevens, M.E. Tremblay, A. Aguzzi, B. Ajami, I. Amit, E. Audinat, I. Bechmann, M. Bennett, F. Bennett, A. Bessis, K. Biber, S. Bilbo, M. Blurton-Jones, E. Boddeke, D. Brites, B. Brone, G.C. Brown, O. Butovsky, M.J. Carson, B. Castellano, M. Colonna, S.A. Cowley, C. Cunningham, D. Davalos, P.L. De Jager, B. de Strooper, A. Denes, B.J.L. Eggen, U. Eyo, E. Galea, S. Garel, F. Ginhoux, C.K. Glass, O. Gokce, D. Gomez-Nicola, B. Gonzalez, S. Gordon, M.B. Graeber, A.D. Greenhalgh, P. Gressens, M. Greter, D.H. Gutmann, C. Haass, M.T. Heneka, F.L. Heppner, S. Hong, D.A. Hume, S. Jung, H. Kettenmann, J. Kipnis, R. Koyama, G. Lemke, M. Lynch, A. Majewska, M. Malcangio, T. Malm, R. Mancuso, T. Masuda, M. Matteoli, B.W. McColl, V.E. Miron, A.V. Molofsky, M. Monje, E. Mracsko, A. Nadjar, J.J. Neher, U. Neniskyte, H. Neumann, M. Noda, B. Peng, F. Peri, V.H. Perry, P.G. Popovich, C. Pridans, J. Priller, M. Prinz, D. Ragozzino, R.M. Ransohoff, M.W. Salter, A. Schaefer, D.P. Schafer, M. Schwartz, M. Simons, C.J. Smith, W.J. Streit, T.L. Tay, L.H. Tsai, A. Verkhratsky, R. von Bernhardi, H. Wake, V. Wittamer, S.A. Wolf, L.J. Wu, T. Wyss-Coray, Microglia states and nomenclature: A field at its crossroads, Neuron 110(21) (2022) 3458-3483. J.M. Ziebell, S.E. Taylor, T. Cao, J.L. Harrison, J. Lifshitz, Rod microglia: elongation, alignment, and coupling to form trains across the somatosensory cortex after experimental diffuse brain injury, J Neuroinflammation 9 (2012) 247. M.I. Love, W. Huber, S. Anders, Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2, Genome Biol 15(12) (2014) 550. M. Kosugi, M. Otani, Y. Kikkawa, Y. Itakura, K. Sakai, T. Ito, M. Toyoda, Y. Sekita, T. Kimura, Mutations of histone demethylase genes encoded by X and Y chromosomes, Kdm5c and Kdm5d, lead to noncompaction cardiomyopathy in mice, Biochem Biophys Res Commun (2020). A.J. Sadler, B.R. Williams, Interferon-inducible antiviral effectors, Nat Rev Immunol 8(7) (2008) 559-68. J.P. Barrett, R.J. Henry, K.A. Shirey, S.J. Doran, O.D. Makarevich, R.M. Ritzel, V.A. Meadows, S.N. Vogel, A.I. Faden, B.A. Stoica, D.J. Loane, Interferon-beta Plays a Detrimental Role in Experimental Traumatic Brain Injury by Enhancing Neuroinflammation That Drives Chronic Neurodegeneration, J Neurosci 40(11) (2020) 2357-2370. B.P. Todd, Z. Luo, N. Gilkes, M.S. Chimenti, Z. Peterson, M.R. Mix, J.T. Harty, T. Nickl-Jockschat, P.J. Ferguson, A.G. Bassuk, E.A. Newell, Selective neuroimmune modulation by type I interferon drives neuropathology and neurologic dysfunction following traumatic brain injury, Acta Neuropathol Commun 11(1) (2023) 134. C. Munoz-Ballester, D. Mahmutovic, Y. Rafiqzad, A. Korot, S. Robel, Mild Traumatic Brain Injury-Induced Disruption of the Blood-Brain Barrier Triggers an Atypical Neuronal Response, Front Cell Neurosci 16 (2022) 821885. R.M. Ritzel, Y. Li, Y. Jiao, Z. Lei, S.J. Doran, J. He, R.A. Shahror, R.J. Henry, R. Khan, C. Tan, S. Liu, B.A. Stoica, A.I. Faden, G. Szeto, D.J. Loane, J. Wu, Brain injury accelerates the onset of a reversible age-related microglial phenotype associated with inflammatory neurodegeneration, Sci Adv 9(10) (2023) eadd1101. S.M. O'Neil, E.E. Hans, S. Jiang, L.M. Wangler, J.P. Godbout, Astrocyte immunosenescence and deficits in interleukin 10 signaling in the aged brain disrupt the regulation of microglia following innate immune activation, Glia 70(5) (2022) 913-934. N.S.N. Graham, K.A. Zimmerman, F. Moro, A. Heslegrave, S.A. Maillard, A. Bernini, J.P. Miroz, C.K. Donat, M.Y. Lopez, N. Bourke, A.E. Jolly, E.J. Mallas, E. Soreq, M.H. Wilson, G. Fatania, D. Roi, M.C. Patel, E. Garbero, G. Nattino, C. Baciu, E. Fainardi, A. Chieregato, P. Gradisek, S. Magnoni, M. Oddo, H. Zetterberg, G. Bertolini, D.J. Sharp, Axonal marker neurofilament light predicts long-term outcomes and progressive neurodegeneration after traumatic brain injury, Sci Transl Med 13(613) (2021) eabg9922. E.J. Goodman, R.G. Biltz, J.M. Packer, D.J. DiSabato, S.P. Swanson, B. Oliver, N. Quan, J.F. Sheridan, J.P. Godbout, Enhanced fear memory after social defeat in mice is dependent on interleukin-1 receptor signaling in glutamatergic neurons, Mol Psychiatry (2024). E.J. Goodman, D.J. DiSabato, J.F. Sheridan, J.P. Godbout, Novel microglial transcriptional signatures promote social and cognitive deficits following repeated social defeat, Commun Biol 7(1) (2024) 1199. A. Loda, E. Heard, Xist RNA in action: Past, present, and future, PLoS Genet 15(9) (2019) e1008333. J. Xu, X. Deng, R. Watkins, C.M. Disteche, Sex-specific differences in expression of histone demethylases Utx and Uty in mouse brain and neurons, J Neurosci 28(17) (2008) 4521-7. H. Shen, A. Yanas, M.C. Owens, C. Zhang, C. Fritsch, C.M. Fare, K.E. Copley, J. Shorter, Y.E. Goldman, K.F. Liu, Sexually dimorphic RNA helicases DDX3X and DDX3Y differentially regulate RNA metabolism through phase separation, Mol Cell 82(14) (2022) 2588-2603 e9. A. Abdullah, M. Zhang, T. Frugier, S. Bedoui, J.M. Taylor, P.J. Crack, STING-mediated type-I interferons contribute to the neuroinflammatory process and detrimental effects following traumatic brain injury, J Neuroinflammation 15(1) (2018) 323. T. Sen, P. Saha, R. Gupta, L.M. Foley, T. Jiang, O.S. Abakumova, T.K. Hitchens, N. Sen, Aberrant ER Stress Induced Neuronal-IFNbeta Elicits White Matter Injury Due to Microglial Activation and T-Cell Infiltration after TBI, J Neurosci 40(2) (2020) 424-446. A.D. Bachstetter, E.T. Ighodaro, Y. Hassoun, D. Aldeiri, J.H. Neltner, E. Patel, E.L. Abner, P.T. Nelson, Rod-shaped microglia morphology is associated with aging in 2 human autopsy series, Neurobiol Aging 52 (2017) 98-105. M. Xie, A.S. Miller, P.N. Pallegar, A. Umpierre, Y. Liang, N. Wang, S. Zhang, N.K. Nagaraj, Z.C. Fogarty, N.B. Ghayal, B. Oskarsson, S. Zhao, J. Zheng, F. Qi, A. Nguyen, D.W. Dickson, L.J. Wu, Rod-shaped microglia interact with neuronal dendrites to regulate cortical excitability in TDP-43 related neurodegeneration, bioRxiv (2024). Y. Wang, X. Ning, P. Gao, S. Wu, M. Sha, M. Lv, X. Zhou, J. Gao, R. Fang, G. Meng, X. Su, Z. Jiang, Inflammasome Activation Triggers Caspase-1-Mediated Cleavage of cGAS to Regulate Responses to DNA Virus Infection, Immunity 46(3) (2017) 393-404. X. Liu, T. Yamashita, Q. Chen, N. Belevych, D.B. McKim, A.J. Tarr, V. Coppola, N. Nath, D.P. Nemeth, Z.W. Syed, J.F. Sheridan, J.P. Godbout, J. Zuo, N. Quan, Interleukin 1 type 1 receptor restore: a genetic mouse model for studying interleukin 1 receptor-mediated effects in specific cell types, J Neurosci 35(7) (2015) 2860-70. J.C. Vincent, C.N. Garnett, J.B. Watson, E.K. Higgins, T. Macheda, L. Sanders, K.N. Roberts, R.K. Shahidehpour, E.M. Blalock, N. Quan, A.D. Bachstetter, IL-1R1 signaling in TBI: assessing chronic impacts and neuroinflammatory dynamics in a mouse model of mild closed-head injury, J Neuroinflammation 20(1) (2023) 248. C.C. Escoubas, L.C. Dorman, P.T. Nguyen, C. Lagares-Linares, H. Nakajo, S.R. Anderson, J.J. Barron, S.D. Wade, B. Cuevas, I.D. Vainchtein, N.J. Silva, R. Guajardo, Y. Xiao, P.V. Lidsky, E.Y. Wang, B.M. Rivera, S.E. Taloma, D.K. Kim, E. Kaminskaya, H. Nakao-Inoue, B. Schwer, T.D. Arnold, A.B. Molofsky, C. Condello, R. Andino, T.J. Nowakowski, A.V. Molofsky, Type-I-interferon-responsive microglia shape cortical development and behavior, Cell 187(8) (2024) 1936-1954 e24. S. Hosseini, K. Michaelsen-Preusse, G. Grigoryan, C. Chhatbar, U. Kalinke, M. Korte, Type I Interferon Receptor Signaling in Astrocytes Regulates Hippocampal Synaptic Plasticity and Cognitive Function of the Healthy CNS, Cell Rep 31(7) (2020) 107666. L. Hashemzadeh-Bonehi, R.G. Phillips, N.J. Cairns, S. Mosaheb, J.R. Thorpe, Pin1 protein associates with neuronal lipofuscin: potential consequences in age-related neurodegeneration, Exp Neurol 199(2) (2006) 328-38. S. Richter, E. Czeiter, K. Amrein, A. Mikolic, J. Verheyden, K. Wang, A.I.R. Maas, E. Steyerberg, A. Buki, D.K. Menon, V.F.J. Newcombe, Prognostic Value of Serum Biomarkers in Patients With Moderate-Severe Traumatic Brain Injury, Differentiated by Marshall Computer Tomography Classification, J Neurotrauma 40(21-22) (2023) 2297-2310. G. Scott, H. Zetterberg, A. Jolly, J.H. Cole, S. De Simoni, P.O. Jenkins, C. Feeney, D.R. Owen, A. Lingford-Hughes, O. Howes, M.C. Patel, A.P. Goldstone, R.N. Gunn, K. Blennow, P.M. Matthews, D.J. Sharp, Minocycline reduces chronic microglial activation after brain trauma but increases neurodegeneration, Brain 141(2) (2018) 459-471. F.H. Brennan, Y. Li, C. Wang, A. Ma, Q. Guo, Y. Li, N. Pukos, W.A. Campbell, K.G. Witcher, Z. Guan, K.A. Kigerl, J.C.E. Hall, J.P. Godbout, A.J. Fischer, D.M. McTigue, Z. He, Q. Ma, P.G. Popovich, Microglia coordinate cellular interactions during spinal cord repair in mice, Nat Commun 13(1) (2022) 4096. K. Tariq, E. Cullen, S.A. Getz, A.K.S. Conching, A.R. Goyette, M.L. Prina, W. Wang, M. Li, M.C. Weston, B.W. Luikart, Disruption of mTORC1 rescues neuronal overgrowth and synapse function dysregulated by Pten loss, Cell Rep 41(5) (2022) 111574. R. Liu, X.Y. Liao, J.C. Tang, M.X. Pan, S.F. Chen, P.X. Lu, L.J. Lu, Z.F. Zhang, Y.Y. Zou, L.H. Bu, X.P. Qin, Q. Wan, BpV(pic) confers neuroprotection by inhibiting M1 microglial polarization and MCP-1 expression in rat traumatic brain injury, Mol Immunol 112 (2019) 30-39. M. Metcalfe, O. Steward, PTEN deletion in spinal pathways via retrograde transduction with AAV-RG enhances forelimb motor recovery after cervical spinal cord injury; Sex differences and late-onset pathophysiologies, Exp Neurol 370 (2023) 114551. S.J. Doran, R.M. Ritzel, E.P. Glaser, R.J. Henry, A.I. Faden, D.J. Loane, Sex Differences in Acute Neuroinflammation after Experimental Traumatic Brain Injury Are Mediated by Infiltrating Myeloid Cells, J Neurotrauma 36(7) (2019) 1040-1053. S. Villapol, D.J. Loane, M.P. Burns, Sexual dimorphism in the inflammatory response to traumatic brain injury, Glia 65(9) (2017) 1423-1438. N.J. Starkey, B. Duffy, K. Jones, A. Theadom, S. Barker-Collo, V. Feigin, B.R. Group, Sex differences in outcomes from mild traumatic brain injury eight years post-injury, PLoS One 17(5) (2022) e0269101. J. Iannucci, K. O'Neill, X. Wang, S. Mukherjee, J. Wang, L.A. Shapiro, Sex-Specific and Traumatic Brain Injury Effects on Dopamine Receptor Expression in the Hippocampus, Int J Mol Sci 24(22) (2023). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Apr, 2025 Read the published version in Journal of Neuroinflammation → Version 1 posted Editorial decision: Revision requested 08 Mar, 2025 Reviews received at journal 08 Mar, 2025 Reviews received at journal 05 Mar, 2025 Reviews received at journal 04 Mar, 2025 Reviewers agreed at journal 17 Feb, 2025 Reviewers agreed at journal 16 Feb, 2025 Reviewers agreed at journal 16 Feb, 2025 Reviewers agreed at journal 14 Feb, 2025 Reviewers agreed at journal 14 Feb, 2025 Reviewers invited by journal 14 Feb, 2025 Editor assigned by journal 13 Feb, 2025 Submission checks completed at journal 13 Feb, 2025 First submitted to journal 04 Feb, 2025 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-5960640","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":416434657,"identity":"014019ca-42c7-4336-9205-2b5b01525d1d","order_by":0,"name":"Jonathan M. Packer","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Jonathan","middleName":"M.","lastName":"Packer","suffix":""},{"id":416434658,"identity":"5ca291f7-b5e0-4144-a1ff-91b211ca61a7","order_by":1,"name":"Samantha G. Giammo","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Samantha","middleName":"G.","lastName":"Giammo","suffix":""},{"id":416434659,"identity":"41031709-27ff-4cec-bed3-b01b30828ab1","order_by":2,"name":"Lynde M. Wangler","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Lynde","middleName":"M.","lastName":"Wangler","suffix":""},{"id":416434660,"identity":"57c2b930-610f-406f-bf7a-39b41bf1881f","order_by":3,"name":"Amara C. Davis","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Amara","middleName":"C.","lastName":"Davis","suffix":""},{"id":416434661,"identity":"b5e80f1d-1e81-4111-9ae6-5bce66bcf4f1","order_by":4,"name":"Chelsea E. Bray","email":"","orcid":"","institution":"The Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Chelsea","middleName":"E.","lastName":"Bray","suffix":""},{"id":416434662,"identity":"295a66f9-a72d-4283-a1ec-8202ada1d7fa","order_by":5,"name":"Jonathan P. Godbout","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYBAC9gYgwQgi2A8wSINE+OFyB7BrAas+CCJ4EsBaJCQbiNYiwQDRYgBXiUtLe+/Bzx932OUxSDAfvF1QcbjO+Hj7M6kbNQxyfDcSsGvpOZcscfBMcjGDBFuy9YwzhyXMzpwxk845xmAsiUvLjBwDiYNtzIkNEm/MpHnbgFpu5LBJ5zYwJG7ArcX4x8G2eqCWHIgW4xnpz0Ba6nFpEZyRYwa05TBCi4FEghlIS4IBDi3SPGfMLM62HU9s40kD+SVdcsaZM8bWOcckDGeeeYBVCx97j/GNyrbqxH72w6AQs+bnb29/eDunxkae7zh2W+CADY0vgV/5KBgFo2AUjAK8AAAa9mEun7SsGgAAAABJRU5ErkJggg==","orcid":"","institution":"The Ohio State University","correspondingAuthor":true,"prefix":"","firstName":"Jonathan","middleName":"P.","lastName":"Godbout","suffix":""}],"badges":[],"createdAt":"2025-02-04 19:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5960640/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5960640/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12974-025-03451-1","type":"published","date":"2025-04-30T15:57:42+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":76468943,"identity":"a077af31-579e-49c7-8976-36f33f714bf1","added_by":"auto","created_at":"2025-02-17 12:43:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1027017,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTBI-induced STING expression in microglia was ablated by mSTING\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e-/-\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e. \u003c/strong\u003eA) To generate the inducible and microglia specific knockout of STING, C57BL/6- STING\u003csup\u003efl/fl \u003c/sup\u003e, mice were crossed with CX\u003csub\u003e3\u003c/sub\u003eCR1-Cre/ERT2 mice. Mice were backcrossed and genotyped to establish CX\u003csub\u003e3\u003c/sub\u003eCR1/STING\u003csup\u003efl/fl\u003c/sup\u003e mice (Cre\u003cstrong\u003e-\u003c/strong\u003eERT2\u003csup\u003e+\u003c/sup\u003e) and STING\u003csup\u003efl/fl\u003c/sup\u003e (Cre-ERT2\u003csup\u003eneg\u003c/sup\u003e) lines. Recombination was induced with tamoxifen (10 mg/ml in corn oil, i.p.) four weeks prior to experiments to generate CX\u003csub\u003e3\u003c/sub\u003eCR1/STING\u003csup\u003e-/-\u003c/sup\u003e (mSTING\u003csup\u003e-/-\u003c/sup\u003e) mice. B) Male and female functional wild type (STING\u003csup\u003e+/+\u003c/sup\u003e) and mSTING\u003csup\u003e-/-\u003c/sup\u003e mice were subjected to midline fluid percussion injury or left as uninjured controls. Several parameters were determined 7 dpi including determination of STING (RNA and protein) in microglia. C) Time to self-right for functional wild type (STING\u003csup\u003e+/+\u003c/sup\u003e) and CX\u003csub\u003e3\u003c/sub\u003eCR1/STING\u003csup\u003e-/-\u003c/sup\u003e (or mSTING\u003csup\u003e-/-\u003c/sup\u003e) mice immediately following TBI (n=9-14). D) \u003cem\u003eSting (Tmem117)\u003c/em\u003e RNA determined in percoll-enriched microglia collected from the whole brain 7 dpi (n=4-6). E) Representative images of STING\u003csup\u003e+\u003c/sup\u003e labeling (10x, 500 mm) in the cortex 7 dpi. Right panels show enlarged images of positive STING labeling in TBI-STING\u003csup\u003e+/+\u003c/sup\u003e and TBI-mSTING\u003csup\u003e-/-\u003c/sup\u003e mice. F) Percent-area of STING\u003csup\u003e+\u003c/sup\u003e labeling in the cortex 7 dpi (n=6-8). From the same experiment, G) Representative images of STING\u003csup\u003e+\u003c/sup\u003e and IBA1\u003csup\u003e+\u003c/sup\u003e labeling (n=6-8). G) Right panel shows percent of double labeled IBA1\u003csup\u003e+ \u003c/sup\u003eand STING\u003csup\u003e+ \u003c/sup\u003ecells 7 dpi in the cortex. Bars represent the mean ± SEM, and individual data points are provided. Means with (*) are significantly different from control groups (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) and means with (†) are significantly different from all other groups (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"Binder11.png","url":"https://assets-eu.researchsquare.com/files/rs-5960640/v1/85f5f22b92ac3aa803b149ce.png"},{"id":76466953,"identity":"adbf96a4-8bc8-46ee-ac1b-62967384d9cc","added_by":"auto","created_at":"2025-02-17 12:27:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1313938,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMicroglia reactivity 7 dpi was attenuated by mSTING\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e-/-\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e. \u003c/strong\u003eMale and female functional wild type (STING\u003csup\u003e+/+\u003c/sup\u003e) and CX\u003csub\u003e3\u003c/sub\u003eCR1/STING\u003csup\u003e-/-\u003c/sup\u003e (mSTING\u003csup\u003e-/-\u003c/sup\u003e) mice were subjected to midline fluid percussion injury or left as uninjured controls. A) Representative images of GFAP\u003csup\u003e+\u003c/sup\u003e labeling (10x) in the cortex 7 dpi. Insets show enlarged labeling and right panel shows pseudo-skeletonized GFAP\u003csup\u003e+\u003c/sup\u003e labeling (white). B) Percent-area of GFAP\u003csup\u003e+\u003c/sup\u003e labeling in the cortex 7 dpi (n=6-7). C) Representative images of IBA1\u003csup\u003e+\u003c/sup\u003e labeling (10x) in the lateral cortex 7 dpi. Insets show enlarged IBA1\u003csup\u003e+\u003c/sup\u003e labeling and right panel shows pseudo-skeletonized IBA1\u003csup\u003e+\u003c/sup\u003e labeling (white). D) Percent-area of IBA1\u003csup\u003e+\u003c/sup\u003e labeling in the cortex 7 dpi (n=6-7). E) Representative images of IBA1\u003csup\u003e+\u003c/sup\u003e labeling of rod-shaped microglia (10×) in the medial cortex 7 dpi. Insets show enlarged IBA1\u003csup\u003e+\u003c/sup\u003e labeling and right panel shows pseudo-skeletonized IBA1\u003csup\u003e+\u003c/sup\u003e labeling (white). F) Number of IBA1\u003csup\u003e+\u003c/sup\u003e rod microglia per 10× field in the medial cortex 7 dpi (n=6-7). Means with (*) are significantly different from control groups (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) and means with (^) are significantly different from TBI-STING\u003csup\u003e+/+\u003c/sup\u003e mice (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"Binder12.png","url":"https://assets-eu.researchsquare.com/files/rs-5960640/v1/0f56b6d85e0a3da8ea365bd5.png"},{"id":76466952,"identity":"ff0b0483-f570-435f-b0d4-0c00beacad75","added_by":"auto","created_at":"2025-02-17 12:27:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":183658,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTBI-associated cortical inflammation was attenuated by mSTING\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e-/-\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e.\u003c/strong\u003e A) Male and female functional wild type (STING\u003csup\u003e+/+\u003c/sup\u003e) and CX\u003csub\u003e3\u003c/sub\u003eCR1/STING\u003csup\u003e-/-\u003c/sup\u003e (mSTING\u003csup\u003e-/-\u003c/sup\u003e) mice were subjected to midline fluid percussion injury or left as uninjured controls. Cortices were collected 7 dpi and mRNA expression was determined using NanoString nCounter analyses (n=6). A) Volcano plot of DEGs in the cortex of TBI-STING\u003csup\u003e+/+ \u003c/sup\u003eversus Con-STING\u003csup\u003e+/+ \u003c/sup\u003emice. B) Volcano plot of DEGs in the cortex of TBI-mSTING\u003csup\u003e-/- \u003c/sup\u003eversus Con-mSTING\u003csup\u003e-/-\u003c/sup\u003emice. C) Volcano plot of DEGs in the cortex of TBI-mSTING\u003csup\u003e-/- \u003c/sup\u003eversus TBI-STING\u003csup\u003e+/+ \u003c/sup\u003emice. Red dots represent genes significantly increased with |log2FoldChange| \u0026gt; 0 and \u003cem\u003ep-adj\u003c/em\u003e\u0026lt;0.05. Blue dots represent genes significantly decreased with |log2FoldChange| \u0026gt; 0 and\u003cem\u003e p-ad \u003c/em\u003e\u0026lt;0.05. Triangles represent the highest DEGs within any volcano plot. D) Volcano plot of DEGs in the cortex of male TBI–STING\u003csup\u003e+/+ \u003c/sup\u003eversus female TBI- STING\u003csup\u003e+/+ \u003c/sup\u003emice. E) Percent of genes significantly affected by TBI (TBI-STING\u003csup\u003e+/+\u003c/sup\u003e vs Con-STING\u003csup\u003e+/+\u003c/sup\u003e) that were attenuated, prevented or not prevented in mSTING\u003csup\u003e-/-\u003c/sup\u003e mice. DEGs that were F) attenuated, G) prevented, H) not prevented, or I) exacerbated are shown in respective heat maps (Fig.3F-I).\u003c/p\u003e","description":"","filename":"Binder13.png","url":"https://assets-eu.researchsquare.com/files/rs-5960640/v1/9d816797888b724d5d23d701.png"},{"id":76467360,"identity":"a112a29f-4e5b-406a-9026-151e05c4b112","added_by":"auto","created_at":"2025-02-17 12:35:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":104545,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCanonical pathways associated with inflammation and IFN signaling 7 dpi were attenuated by mSTING\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e-/-\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e. \u003c/strong\u003eContinuing with the NanoString experiment outlined in Fig.3, Ingenuity Pathway Analysis (IPA) assessed canonical pathways, master regulators, and upstream regulators influenced by TBI and mSTING\u003csup\u003e-/- \u003c/sup\u003e(\u003cem\u003ez\u003c/em\u003e-score). A) Heat map of IPA canonical pathways induced by TBI. B) Heat map of IPA canonical pathways induced by TBI and prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e. C) Heat maps of activated or inhibited master regulators by TBI. D) Heat map of activated or inhibited master regulators by TBI and prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e. E) Heat map of activated or inhibited IPA upstream regulators induced by TBI. F) Heat map of IPA upstream regulators induced by TBI and prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e. Values were significant with a \u003cem\u003ep\u003c/em\u003e-adj \u0026lt;0.05.\u003c/p\u003e","description":"","filename":"Binder14.png","url":"https://assets-eu.researchsquare.com/files/rs-5960640/v1/2e9f110993c8d6e7ed6edbaf.png"},{"id":76466959,"identity":"e2e4b31e-3e81-427b-a2ec-e6bc152fe469","added_by":"auto","created_at":"2025-02-17 12:27:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":93882,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTBI-induced cognitive deficits 7 dpi were IFNAR1 independent\u003c/strong\u003e. A) Wildtype (IFNAR1\u003csup\u003e+/+\u003c/sup\u003e)\u003csup\u003e \u003c/sup\u003eand global IFNAR1 knockout (IFNAR1\u003csup\u003e-/-\u003c/sup\u003e) male mice were subjected to midline fluid percussion injury (TBI) or left as uninjured controls.\u003cstrong\u003e \u003c/strong\u003eCognition (novel object recognition (NOR) and location (NOL)) and cortical inflammation were assessed 7 dpi (n=5-6). B) Total exploration time (seconds) of the objects in NOR. C) Percent time exploring the novel object and D) Discrimination index of time exploring the novel object. E) Total exploration time (seconds) of the objects in NOL. F) Percent time exploring the object in the novel location. G) Discrimination index of time exploring the object in the novel location. From the same mice, mRNA levels of H) \u003cem\u003eIrf7\u003c/em\u003e, I) \u003cem\u003eGfap\u003c/em\u003e, J) \u003cem\u003eH2-Eb1\u003c/em\u003e, and K) \u003cem\u003eTnf\u003c/em\u003e were determined from the cortex (n=5-6). Bars represent the mean ± SEM, and individual data points are provided. Means with (*) are significantly different from control groups (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) and means with (†) are significantly different from all other groups (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"Binder15.png","url":"https://assets-eu.researchsquare.com/files/rs-5960640/v1/12c045197ea7e9f2668a6ab9.png"},{"id":76466956,"identity":"fd76db14-0234-4377-b1e7-06f9f9acdfc2","added_by":"auto","created_at":"2025-02-17 12:27:34","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1903577,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTBI-induced neuronal injury and cognitive deficits 7 dpi were mSTING dependent.\u003c/strong\u003e A)\u003cstrong\u003e \u003c/strong\u003eMale and female functional wild type (STING\u003csup\u003e+/+\u003c/sup\u003e) and CX\u003csub\u003e3\u003c/sub\u003eCR1/STING\u003csup\u003e-/-\u003c/sup\u003e (mSTING\u003csup\u003e-/-\u003c/sup\u003e) mice were subjected to midline fluid percussion injury or left as uninjured controls. Several parameters of neuronal injury were assessed in the cortex and plasma 7 dpi. A) Representative images of NeuN\u003csup\u003e+\u003c/sup\u003e labeling (10x) in the cortex 7 dpi. White box represents location where inset was selected. Right panel shows enlarged labeling from inset. B) Percent-area of NeuN\u003csup\u003e+\u003c/sup\u003e labeling per 10x field in the medial cortex 7 dpi (n=6-8). C) Representative images of lipofuscin autofluorescence and NeuN\u003csup\u003e+ \u003c/sup\u003elabeling\u003csup\u003e \u003c/sup\u003ein the lateral cortex 7 dpi. Insets show enlarged images of lipofuscin auto-fluorescence in NeuN\u003csup\u003e+\u003c/sup\u003e cells. D) Quantification of lipofuscin foci in NeuN\u003csup\u003e+\u003c/sup\u003e neurons in the lateral cortex 7 dpi. E) Neurofilament light chain protein (NF-L) was determined in the plasma 7 dpi (n=6-8). In a separate study, cognition was determined using the novel object recognition (NOR) and location (NOL) tests (n=12-16). F) Total exploration time (seconds) of the objects in NOR. G) Percent time exploring the novel object. H) Discrimination index of time exploring the novel object. I) Total exploration time (seconds) of the objects in NOL. J) Percent time exploring the object in the novel location. F) Discrimination index of time exploring the object in the novel location. Bars represent the mean ± SEM and individual data points are provided. Means with (*) are significantly different from control groups (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Means with (^) tend to be different from control groups (\u003cem\u003ep\u003c/em\u003e=0.06-0.1).\u003c/p\u003e","description":"","filename":"Binder16.png","url":"https://assets-eu.researchsquare.com/files/rs-5960640/v1/d4fe9a97466718bdcc3d2c26.png"},{"id":76467361,"identity":"e8ef5b7d-db1e-4755-b35c-fb7232ccd692","added_by":"auto","created_at":"2025-02-17 12:35:34","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":633313,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSingle nucleus RNA-sequencing of cortical neurons 7 days after TBI. \u003c/strong\u003eA)\u003cstrong\u003e \u003c/strong\u003eMale and female functional wild type (STING\u003csup\u003e+/+\u003c/sup\u003e) and CX\u003csub\u003e3\u003c/sub\u003eCR1/STING\u003csup\u003e-/-\u003c/sup\u003e (mSTING\u003csup\u003e-/-\u003c/sup\u003e) mice were subjected to midline fluid percussion injury or left as uninjured controls. At 7 dpi, mice were sacrificed, and cortices were dissected, pooled (3 males, 3 females per group), and nuclei were collected. RNA profiles of collected nuclei were determined 7 dpi using snRNA-sequencing. Clustering and differential expression were determined using Seurat in R. B) UMAP plots indicate 19 distinct clusters of cortical cells based on identity genes. C\u0026amp;E) Clusters were identified based on established gene expression: neurons (\u003cem\u003eSyt1\u003c/em\u003e), oligodendrocytes (\u003cem\u003eMag\u003c/em\u003e), microglia (\u003cem\u003eCsf1r\u003c/em\u003e), astrocytes (\u003cem\u003eSlc1a3\u003c/em\u003e) and endothelia (\u003cem\u003eFlt1\u003c/em\u003e). Dot plot figure shows gene expression of identifying genes for clusters. D) Representative percentage of each cell type. Next, neurons (\u003cem\u003eSty1\u003c/em\u003e+) were subset and re-clustered. F) The UMAP plot shows that 14 clusters of cortical neurons identified. G\u0026amp;I) Dot plot figure shows gene expression of identifying genes for clusters based established gene expression: upper layer neurons (\u003cem\u003eCux2\u003c/em\u003e), layer 4 neurons (\u003cem\u003eRorb\u003c/em\u003e), deep layer neurons (\u003cem\u003eFoxp2\u003c/em\u003e), and inhibitory neurons (\u003cem\u003eGad1\u003c/em\u003e). H) The UMAP plot shows the distribution of cortical neuron clusters between the experimental groups.\u003c/p\u003e","description":"","filename":"Binder17.png","url":"https://assets-eu.researchsquare.com/files/rs-5960640/v1/011bd7e3493f907486db1f64.png"},{"id":76466960,"identity":"608d23ae-15ba-4d79-9548-96afd16a186d","added_by":"auto","created_at":"2025-02-17 12:27:34","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":280443,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAblation of microglial STING attenuated the response to TBI in cortical neurons. \u003c/strong\u003eA) Continuing with the snRNA-seq experiment outlined in Fig.7, the pie chart shows the percentages of different Sty1+ neurons. B) The number of DEGs increased or decreased by TBI (TBI-STING\u003csup\u003e+/+\u003c/sup\u003e vs Con-STING\u003csup\u003e+/+\u003c/sup\u003e) for each cortical neuron cluster are shown. C) The percentage and number of DEGs induced by TBI and prevented by mSTING-/- (TBI-STING\u003csup\u003e+/+\u003c/sup\u003e vs TBI–mSTING\u003csup\u003e-/-\u003c/sup\u003e) in each neuronal cluster. D) Dot plot shows the top DEGs between male and female TBI-STING\u003csup\u003e+/+ \u003c/sup\u003emice. E) Volcano plot of DEGs in the upper layer (UL) neurons of TBI-STING\u003csup\u003e+/+\u003c/sup\u003e vs Con-TBI\u003csup\u003e+/+\u003c/sup\u003e. F) Volcano plot of DEGs in the upper layer (UL) neurons of TBI-mSTING\u003csup\u003e-/- \u003c/sup\u003evs Con- mSTING\u003csup\u003e-/-\u003c/sup\u003e. G) Volcano plot of DEGs in the upper layer (UL) neurons of TBI-mSTING\u003csup\u003e-/-\u003c/sup\u003e vs TBI-STING\u003csup\u003e+/+\u003c/sup\u003e. H) Volcano plot of DEGs in the deep layer (DL) neurons of TBI-STING\u003csup\u003e+/+\u003c/sup\u003e vs Con-TBI\u003csup\u003e+/+\u003c/sup\u003e. I) Volcano plot of DEGs in the deep layer (DL) neurons of TBI-mSTING\u003csup\u003e-/- \u003c/sup\u003evs Con-mSTING\u003csup\u003e-/-\u003c/sup\u003e. J) Volcano plot of DEGs in the deep layer (DL) neurons of TBI-mSTING\u003csup\u003e-/ -\u003c/sup\u003evs TBI-STING\u003csup\u003e+/+\u003c/sup\u003e. Red dots represent genes significantly increased with |log2FoldChange| \u0026gt; 0 and \u003cem\u003ep\u003c/em\u003e-adj \u0026lt;0.05. Blue dots represent genes significantly decreased with |log2FoldChange| \u0026gt; 0 and \u003cem\u003ep\u003c/em\u003e-adj \u0026lt;0.05. Values were significant with a \u003cem\u003ep\u003c/em\u003e-adj \u0026lt;0.05\u003c/p\u003e","description":"","filename":"Binder18.png","url":"https://assets-eu.researchsquare.com/files/rs-5960640/v1/350397d89ba6495e579a4a8f.png"},{"id":76466958,"identity":"88e38975-5319-433a-8f77-f8c4af8842bc","added_by":"auto","created_at":"2025-02-17 12:27:34","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":116505,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAblation of microglial STING attenuated TBI-induced imbalance in neuronal homeostasis of cortical neurons. \u003c/strong\u003eContinuing with the snRNA-seq experiment outlined in Figs.7\u0026amp;8. Ingenuity Pathway Analysis (IPA) assessed canonical pathways, master regulators, and upstream regulators influenced by TBI and mSTING\u003csup\u003e-/- \u003c/sup\u003ein upper layer neurons (UL), layer 4 neurons (L4), deep layer neurons (DL), and inhibitory neurons (IN). A) Heat map of IPA canonical pathways induced by TBI (TBI vs Con-STING\u003csup\u003e+/+\u003c/sup\u003e) are shown. B) Heat map of IPA canonical pathways induced by TBI and prevented by mSTING\u003csup\u003e-/- \u003c/sup\u003eare shown. C) Heat maps of activated or inhibited IPA master regulators by TBI (TBI vs Con-STING\u003csup\u003e+/+\u003c/sup\u003e). D) Heat map of activated or inhibited IPA master regulators by TBI and prevented by mSTING\u003csup\u003e-/- \u003c/sup\u003eare shown. E) Heat map of activated or inhibited IPA upstream regulators induced by TBI are shown. Values were significant with a \u003cem\u003ep\u003c/em\u003e-adj \u0026lt;0.05.\u003c/p\u003e","description":"","filename":"Binder19.png","url":"https://assets-eu.researchsquare.com/files/rs-5960640/v1/ede8d5d4cda2bae4a1d06534.png"},{"id":81988164,"identity":"5cc71863-dfb2-4834-93ac-be15c8d9aa23","added_by":"auto","created_at":"2025-05-05 16:08:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6965874,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5960640/v1/8c8221d1-3cbe-4b26-a098-2028ca881551.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Diffuse Traumatic Brain Injury Induced Stimulator of Interferons (STING) Signaling in Microglia Drives Cortical Neuroinflammation, Neuronal Dysfunction, and Impaired Cognition","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNeuropsychiatric complications including depression and cognitive decline develop and even worsen in the years following traumatic brain injury (TBI). These complications negatively affect quality of life and lifespan. On average, there are 2.4\u0026nbsp;million brain injuries per year in the United States alone [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. TBI also increases the risk of dementia and progressive neurodegeneration [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Microglia, the innate immune cell of the central nervous system (CNS), are involved in chronic inflammation and progressive neurodegeneration after TBI [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. For example, microglial activation is detected acutely, and evidence of this activation can persist months to years post-TBI in humans [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] Microglia and corresponding inflammation after TBI affects brain regions responsible for cognition and executive function, impairing information processing, memory, and executive function [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Thus, understanding the specific pathways induced in microglia after TBI that promote chronic inflammatory processes is a biologically relevant area of focus.\u003c/p\u003e \u003cp\u003eMyriad reports indicate that TBI-induced chronic neuroinflammation and cognitive dysfunction in rodents are dependent on microglial responses [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR11 CR12 CR13\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. We and others have reported that there is a pronounced shift in microglia RNA profiles from pro-inflammatory and NF-κB mediated genes towards a type 1 interferon (IFN-I) response at a subacute time point after TBI (7 days post injury, dpi) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. For instance, single-cell RNA sequencing (scRNA-seq) identified trauma associated microglia 7 dpi with a transcriptional signature that was enriched for IFN-I responses (\u003cem\u003eIfitm3, Stat1, Irf7, Ifi27l2a\u003c/em\u003e) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Cortical RNA gene expression also showed the amplification of IFN-I responses 7 dpi [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Depletion of microglia prior to TBI using a CSF1R antagonist (PLX5622) attenuated neuroinflammation and ablated the IFN-I response to diffuse TBI. These reductions corresponded with improved cortical dendritic complexity, neuronal physiology, and cognition in novel object location and recognition tasks [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Notably, the subacute period after TBI (7 dpi) involved enhanced interferon responses and was worse with age. For instance, diffuse or penetrating TBI in aged mice amplified IFN-I genes (\u003cem\u003eIfn-β, Irf7, Ifi204\u003c/em\u003e, and \u003cem\u003eIsg15\u003c/em\u003e) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In addition, there was amplified IFN-I responses and enhanced gliosis and neuroinflammation in the cortex of aged mice after diffuse TBI [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Overall, IFN-I responses are dominant in the brain during the subacute period (7 dpi) after diffuse TBI.\u003c/p\u003e \u003cp\u003eThe shift in the inflammatory profile at the subacute period after TBI is pertinent and involves the stimulator of IFN genes (STING). STING is a stress-responsive endoplasmic reticulum protein. In the context of viral infection or injury, tissue damage increases cytosolic double-stranded DNA (dsDNA) and mitochondrial DNA (mtDNA) that are sensed by the cGAS-STING pathway [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. STING promotes IFN-I responses that enhance transcription factors IRF3, and NF-κB [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] leading to a diverse array of IFN-I and NF-κB-mediated signaling [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Type-1 interferons (IFN-α/β) act on the interferon-α/β receptor 1 (IFNAR1) that is expressed by all cell types within the brain. After diffuse TBI, the microglial RNA profile 7 dpi (by snRNA-seq) indicates a STING-dependent production of IFN-I (\u003cem\u003ecGas, Tbk1, Sting1\u003c/em\u003e). In addition, genes associated with the IFNAR1 (\u003cem\u003eIfnar2, Stat1\u003c/em\u003e) and interferon stimulated genes (ISGs) (\u003cem\u003eMx1, Mx2, Oasl2)\u003c/em\u003e were also increased in microglia 7 dpi [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Consistent with this study, diffuse TBI (lateral fluid percussion injury (FPI)) increased the IFN response in both microglia and astrocytes 7 dpi [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In another study, diffuse TBI (midline FPI)-induced STING expression, microglial morphological restructuring, inflammatory, and IFN-related gene expression in the cortex (\u003cem\u003eTnf, Cd68, Ccl2\u003c/em\u003e, \u003cem\u003eIrf7, Sting\u003c/em\u003e) that was attenuated in global STING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice and by a STING antagonist (chloroquine) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Moreover, TBI-associated cognitive deficits (NOR/NOL) at 7 dpi were STING dependent [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Global reductions of STING signaling reduces inflammation, cognitive deficits, and neuronal dysfunction following TBI [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Furthermore, a recent study of penetrating TBI using controlled cortical impact (CCI) showed that mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e reduced the acute inflammatory response, lesion volume, and improved motor recovery 72 hours post injury [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Taken together, STING and IFN-I signaling are critical mediators of inflammation, neuronal dysfunction, and cognitive deficits after TBI.\u003c/p\u003e \u003cp\u003eThe purpose of this study was to determine the degree to which a microglia-specific knockout of STING influenced neuroinflammation, neuronal dysfunction, and cognitive impairment induced by diffuse TBI. We show novel data that the selective ablation of STING in microglia attenuates TBI-induced IFN-dependent responses, cortical inflammation, neuronal pathology and dysfunction, and cognitive impairment.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cem\u003eMice:\u0026nbsp;\u003c/em\u003eTo generate inducible CX\u003csub\u003e3\u003c/sub\u003eCR1-STING\u003csup\u003e-/-\u003c/sup\u003e mice, CX\u003csub\u003e3\u003c/sub\u003eCR1Cre/ERT2 (Jax#:020940) and STING\u003csup\u003efl/fl\u003c/sup\u003e (Jax#:035692) mice were purchased from The Jackson Laboratory and bred in-house. Heterozygous offspring were then backcrossed to generate Cre-ERT2 positive (CX\u003csub\u003e3\u003c/sub\u003eCR1Cre/ERT2-STING\u003csup\u003efl/fl\u003c/sup\u003e) and Cre-negative (STING\u003csup\u003efl/fl\u003c/sup\u003e) control mice. For genotyping, ear punches biopsies were taken following weaning (21d), and samples were genotyped by TransNetYX (Cordoba, TN). To induce recombination, Cre-ERT2 positive (CX\u003csub\u003e3\u003c/sub\u003eCR1Cre/ERT2-STING\u003csup\u003efl/fl\u003c/sup\u003e) and Cre-negative control mice (STING\u003csup\u003e+/+\u003c/sup\u003e) were administered 1.5 mg of tamoxifen in 150\u0026nbsp;ml of corn oil intraperitoneally (i.p.) daily for five days. Mice were allowed 30 days to reconstitute prior to experimental use. The result was a knockout of STING in microglia (CX\u003csub\u003e3\u003c/sub\u003eCR1-STING\u003csup\u003e-/-\u003c/sup\u003e or mSTING\u003csup\u003e-/-\u003c/sup\u003e) or a functional STING wild type (STING\u003csup\u003e+/+\u003c/sup\u003e). For the global knockout IFNAR1\u003csup\u003e-/-\u003c/sup\u003e mice, homozygous male and female IFNAR1\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emice were purchased from the Jackson Laboratory and bred in-house. Male and female mice were used in all experiments unless otherwise noted. These experiments, however, were not powered to make sex comparisons. Mice were group housed under a 12/12 light-dark cycle with \u003cem\u003ead libitum\u003c/em\u003e access to food and water. Mice were randomly assigned to groups with mixed treatment and injury groups in each cage. All procedures were performed in accordance with the National Institute of Health Guidelines for the Care and Use of Laboratory Animals, the Public Health Service’s Policy on Human Care and Use of Laboratory Animals, and the Guide for the Care and Use of Laboratory Animals and were approved by The Ohio State University Institutional Laboratory Animal Care and Use Committee.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMidline Fluid Percussion Injury (mFPI):\u003c/em\u003e Mice were subjected to a midline diffuse TBI using a fluid percussion injury (FPI) apparatus as described previously [12, 22, 25]. Briefly, mice were anesthetized in an isoflurane chamber at 2-3% with a flow rate of 0.8 liters/min. After the surgical site was shaved, mice were secured to the stereotax (Stoelting Co., Cat# 51731) and maintained under anesthesia with a mask attachment (Stoelting Co., Cat# 51609M). The surgical site was prepared with aseptic technique, using alternating applications of iodine and 70% ethanol. Mice received a 3 mm craniectomy between the landmark sutures bregma and λ, and a rigid Luer-loc needle hub was secured over the craniectomy site. Following this procedure, mice were moved to a heated (37ºC) recovery cage and monitored until conscious (upright, responsive, and walking). After recovery, mice were briefly re-anesthetized in an isoflurane chamber at 5% (flow rate 0.8 liters/min) for 5 min. The Luer-loc hub was filled with saline, and the hub was attached to the injury device. Once a positive toe-pinch response was elicited (~30 s), a 10 ms pulse of saline (1.2 atm; 670-720 mV) was imposed on the dura. Immediately after the TBI, the Luer-loc hub was removed, dural integrity was confirmed. Next, wound clips (7 mm) were used to close the incision site and the time to self-right was determined (upright and responsive). Next, mice were moved to a heated cage overnight. In these studies, control mice were naïve and uninjured.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePost-Op Care:\u0026nbsp;\u003c/em\u003eMice with TBI were monitored for 1 h post-injury and then allowed to recover overnight in a heated recovery cage with accessible food and hydrogel. The next day, mice were returned to their home cages. In these experiments, no analgesics were provided. Mice were weighed and monitored for lethargy (lack of movement) and infection (redness and pus around the incision site) daily throughout the experiments (7 days). Removal criteria included a loss of 20% of baseline bodyweight, sustained lethargy, paralysis, or surgical site infection. In this study, 5 mice were removed based on these criteria.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eImmunohistochemistry and Analysis:\u0026nbsp;\u003c/em\u003eMice were perfused with phosphate buffered saline (PBS) followed by 4% PFA. Brains were removed, post-fixed, and dehydrated in 30% sucrose. Brains were flash-frozen via isopentane, and then coronal sections (30 µm) were collected, washed, blocked, (0.1% Triton X, 5% BSA, and 5% NDS) and incubated with primary antibodies for rabbit anti-IBA1 (1:1000, Wako, Cat#019-19741, RRID:AB_839504), goat anti-IBA1 (1:500, Wako, #011-27991, RRID:AB_2935833), goat anti-GFAP (1:500, Abcam Cat#ab53554, RRID:AB_880202), rabbit anti-STING (1:200, Proteintech, #19851-1-AP, RRID:AB_10665370), or mouse anti-NeuN (1:500, Abcam, Cat#ab104225, RRID:AB_10711153). Next, sections were washed, incubated with an appropriate fluorochrome-conjugated secondary antibody (donkey anti-rabbit, anti-mouse, or anti-goat; AlexaFluor 488/594/647; Invitrogen) then mounted and cover-slipped with Fluoromount (Beckman Coulter, Inc., Fullerton, CA). Fluorescent labeling was imaged using an EVOS FL Auto 2 imaging system (Thermo Fisher, Waltham, MA). To determine percent area of IBA1\u003csup\u003e+\u003c/sup\u003e , GFAP\u003csup\u003e+\u003c/sup\u003e, STING\u003csup\u003e+\u003c/sup\u003e, or NeuN\u003csup\u003e+\u003c/sup\u003e labeling, single channel images were converted to 8-bit TIFF format and constant thresholds were used to quantify positively labeled pixels (ImageJ Software). Rod morphology of IBA1\u003csup\u003e+\u0026nbsp;\u003c/sup\u003emicroglia were quantified based on length-to-width ratios as previously described [12].Values from 4-6 images per mouse were averaged and used to calculate group averages and variance from each group. To determine the number of Lipofuscin\u003csup\u003e+\u003c/sup\u003e foci, 10 NeuN\u003csup\u003e+\u0026nbsp;\u003c/sup\u003ecells were selected at random and foci were counted. Lipofuscin (autofluorescence) was detected at 455 nm excitation and 583 nm emission [26]. To determine co-localization of IBA1\u003csup\u003e+\u003c/sup\u003e and STING\u003csup\u003e+\u003c/sup\u003e or Lipofuscin\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eand NeuN\u003csup\u003e+\u003c/sup\u003e single channel images were converted to 8-bit TIFF format and Just Another Co-localization Plugin (JaCoP) was used to determine the correlation coefficient (ImageJ Software). For colocalization, 4-6 images per mouse were taken using a Nikon Ti2 inverted motorized microscope. Images were taken at 10x magnification as 13\u0026nbsp;mm z stacks. Denoise.ai was used to reduce background and increase image intensity. Images were analyzed by an investigator blinded to treatment groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNanoString and nCounter Analysis:\u003c/em\u003eNanoString nCounter tissue collection and analysis was performed as previously described [12, 16, 27].\u0026nbsp;Each experimental group was duplicated in separate experiments, yielding four total experimental groups, with six biological replicates per group.\u0026nbsp;In brief, cortex was collected 7 dpi, flash frozen in liquid nitrogen, and stored -80°C. RNA was isolated using the TRI-Reagent and isopropanol protocol (Sigma-Aldrich). RNA quality and integrity were confirmed using a BioAnalyzer PicoAssay by Chip (Agilent). Gene expression was quantified using the nCounter NanoString neuroinflammation panel targeting 770 genes (https://nanostring.com/). This was performed by the Genomics Core facility at The Ohio State University. Technical normalization was performed to positive and negative controls. Cortical RNA was normalized to the housekeeping gene Csnk2a2. This housekeeping gene was selected based on strong correlation with total counts (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026gt;0.8). Differential gene expression analyses were performed using the DESeq2 package in R Studio. Results were generated based on injury, genotype and sex (e.g., TBI-STING\u003csup\u003e+/+\u003c/sup\u003e vs TBI-mSTING\u003csup\u003e-/-\u003c/sup\u003e). Statistically significant genes had a threshold set to \u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05. Ingenuity Pathway Analysis (IPA, Qiagen) was used to identify canonical pathways associated with the significant genes compared to the respective control (Con-STING\u003csup\u003e+/+\u003c/sup\u003e or Con-mSTING\u003csup\u003e-/-\u003c/sup\u003e). Results from IPA are represented by\u003cem\u003e\u0026nbsp;z\u003c/em\u003e-score.\u0026nbsp;Gene names and fold changes were submitted to compare expression patterns in our dataset to IPA’s database. IPA results for canonical pathways \u003cem\u003e(p\u0026lt;\u003c/em\u003e0.05; composite \u003cem\u003ez\u003c/em\u003e-score\u0026gt;2) were considered significant. Upstream Regulators were further filtered for activation \u003cem\u003ez\u003c/em\u003e-scores (positive or negative) that were associated with either increased or decreased signaling.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePercoll Enrichment of Brain Myeloid Cells:\u003c/em\u003e CD11b\u003csup\u003e+\u003c/sup\u003e cells were enriched from whole brain homogenates as described [10, 25, 28]. In brief, brains were manually homogenized using Potter homogenizers, and resulting homogenates were pelleted at 600g for 6 min. Supernatants were removed and cell pellets were resuspended in 70% isotonic Percoll (GE-Healthcare, Catalog #45-001-747). A discontinuous isotonic Percoll density gradient was layered as follows: 50%, 35%, and 0% (PBS). Samples were pelleted for 20 min at 2000 g, and cells were collected from the interphase between the 70% and 50% Percoll layers. These cells were referred to as enriched brain CD11b\u003csup\u003e+\u003c/sup\u003e cells based on previous studies demonstrating that viable cells isolated by Percoll density gradient yields 90% CD11b\u003csup\u003e+\u003c/sup\u003e cells [28].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRNA Extraction and qPCR:\u003c/em\u003e Percoll-enriched myeloid cells were lysed, stored at -80°C, and total RNA was extracted using the Picopure RNA Isolation Kit (ThermoFisher, KIT0204). RNA was normalized by concentration and reverse-transcribed to cDNA. The Applied Biosystems Taqman Gene Expression assay-on-demand protocol and recommended probes for each gene of interest was used for quantitative real-time PCR. Target genes including \u003cem\u003eTmem173\u003c/em\u003e (\u003cem\u003eSting\u003c/em\u003e): Mm01158117_m1, \u003cem\u003eH2-Eb1\u003c/em\u003e: Mm00439221_m1, \u003cem\u003eIrf7\u003c/em\u003e: Mm00516791_g1, \u003cem\u003eCd68\u003c/em\u003e: Mm03047343_m1, \u003cem\u003eTnf\u003c/em\u003e: Mm00443258_m1, and reference gene \u003cem\u003eGapdh\u003c/em\u003e: Mm99999915_g were determined using a QuantStudio 6 (Thermo Fisher) and data were analyzed using the comparative threshold method (ΔΔCt) with data expressed as fold-change from control.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNovel Object Recognition (NOR) and Location (NOL):\u003c/em\u003e Novel object recognition (NOR) and novel object recognition (NOL) tasks were conducted as previously described [10, 11]. Briefly,\u0026nbsp;these tests involved four 10 min phases each separated by 24 h: habituation (no objects), acclimation (2 objects), recognition (2 objects, with one new object), and location (2 objects, one new location). Discrimination index in the recognition and location trials was determined [(time\u003csub\u003enovel\u003c/sub\u003e-time\u003csub\u003efamiliar\u003c/sub\u003e)/time\u003csub\u003etotal\u003c/sub\u003e] x100.\u0026nbsp;Videos were analyzed by an investigator blinded to treatment groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePlasma Neurofilament Analysis:\u003c/em\u003e Plasma neurofilament was assessed in duplicate using a Meso Scale Discovery R-PLEX Human Neurofilament L Assay (K1517XR-2) according to the manufacturer’s instructions and as described previously [29]. In brief, mice were euthanized, blood was collected and clarified at 6000 x g for 15 minutes, and plasma was frozen at −80°C until analysis. Neurofilament light chain (NF-L) was analyzed in plasma samples diluted two-fold. The concentration of neurofilament light chain (NF-L) (pg/ml) was determined using the MESO QuickPlex SQ 120 with reference to a standard curve. The standard curve was established using 8 provided calibrator standards (0-50,000 pg/mL). All samples were within the detection range of the standards.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNuclei Isolation:\u003c/em\u003e Nuclei were isolated for single nucleus RNA-sequencing as previously described [22]. In brief, each group (\u003cem\u003en\u003c/em\u003e=3) was sacrificed simultaneously, then pooled. Each experimental group was duplicated in separate experiments, yielding four total experimental groups, with six biological replicates per group. Cortices were extracted then placed into 2 mL Dounce homogenizers with 1 mL of homogenization buffer. Cortices were homogenized, filtered using a 40\u0026nbsp;µM strainer and homogenates were clarified. Samples were resuspended in a PBS buffer with RNase Inhibitors (0.05 U/μL of Enzymatics RNAase-Inhibitor and Superase-Inhibitor) and re-pelleted. To remove myelin debris, samples were incubated with Myelin Removal Beads II (Miltenyi Biotec, #130-096-731) for 15 minutes at 4°C. Samples were washed (50% PBS and 50% PBS + 1% BSA) and re-pelleted. Supernatant was removed and samples were resuspended in 1 mL of wash buffer. Two LS columns (Miltenyi Biotec, Cat #130-042-401) were used to filter each of the samples, which were then pelleted and resuspended in 150 μL of wash buffer. Nuclei were counted with AO/PI (Logos Biosystems, #F23001) on a Luna-FL Cell Counter and fixed with a Nuclei Fixation Kit (Parse Biosciences, #SB1003) per the manufacturer’s instructions followed by rapid freezing at -80°C.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSingle-Nuclei Barcoding and Sub-library Generation:\u003c/em\u003e As previously described [22], The Parse Biosciences Whole Transcription Kit was used to barcode and generate eight separate sub-libraries with 12,500 nuclei per sub-library. DNA concentration was measured by Qubit 4 Fluorometer and a Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, #Q32851). A Bioanalyzer 2100 with a High Sensitivity DNA Assay chip was used to control quality of sub-libraries before samples were sequenced. Based on previous sequencing experiments, RNA was sequenced at a depth of 40,000 reads per nuclei using a NovaSeq S4 at the Advanced Genomics Core at The University of Michigan [22].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSingle-Nuclei Sequencing Data Processing:\u003c/em\u003e Libraries were processed as previously described [22]. In brief, each fastq.gz file was downloaded and aligned to the Genome Reference Consortium Mouse Reference 39 (mm39) using the Parse Biosciences pipeline. Matrices were downloaded and manually filtered in RStudio using Seurat (v4.1.1). Low-quality nuclei and doublets were filtered using Seurat in R. Cell-type identification was done using previously established markers: endothelial cells (\u003cem\u003eFlt1\u003c/em\u003e), astrocytes (\u003cem\u003eSlc1a3\u003c/em\u003e), oligodendrocytes (\u003cem\u003eMag\u003c/em\u003e), microglia (\u003cem\u003eCsf1r\u003c/em\u003e), and neurons (\u003cem\u003eSyt1\u003c/em\u003e). Differential gene expression was performed using the FindMarkers feature of Seurat with non-parametric Wilcoxon rank sum test. Pathway and master regulators analyses were performed with Ingenuity Pathway Analysis (IPA; Qiagen).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical Analysis:\u003c/em\u003e GraphPad Prism (Version 9; San Diego, CA) was used for analysis of variance (ANOVA) of histological and behavioral data. A Student’s t test was used as appropriate to determine differences between groups. Two-way ANOVA was used as appropriate to determine main effects and interactions between factors. Tukey’s test for multiple comparisonswas used for \u003cem\u003epost-hoc\u003c/em\u003e analysis when main effects and/or interactions were determined. \u003cem\u003ep\u0026lt;0\u003c/em\u003e.05 was considered statistically significant. Statistical analysis for snRNA-sequencing using Seurat are described above. Outlier data values were determined using GraphPad Grubbs’ test with an Alpha value of 0.05 selected.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eTBI-induced STING expression in microglia was ablated by mSTING\u003csup\u003e-/-\u003c/sup\u003e.\u0026nbsp;\u003c/strong\u003eWe previously reported that a global knockout of STING reduced TBI-associated neuroinflammation and cognitive impairment\u0026nbsp;[22].\u0026nbsp;The objective here was to understand the cell specificity of STING signaling in microglia after diffuse TBI. First, a transgenic mouse line with an inducible knockout of STING in microglia was created (STING\u003csup\u003e+/+\u0026nbsp;\u003c/sup\u003eor mSTING\u003csup\u003e-/-\u003c/sup\u003e, Fig.1A). Next, STING\u003csup\u003e+/+\u003c/sup\u003e and mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emice\u0026nbsp;were subjected to control or TBI (mFPI) and several parameters were evaluated 7 dpi (Fig.1B). \u0026nbsp;For instance, time to self-right was assessed immediately after TBI. There were no differences between STING\u003csup\u003e+/+\u0026nbsp;\u003c/sup\u003eand mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emice in self-righting times following TBI (Fig.1C). Next, \u003cem\u003eSting\u003c/em\u003e mRNA was determined in percoll-enriched microglia collected from the whole brain 7 dpi (Fig.1D). As expected, there was a main effect of genotype on \u003cem\u003eSting\u003c/em\u003e mRNA levels in microglia (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,15\u0026nbsp;\u003c/sub\u003e= 14.2, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.005\u003cstrong\u003e)\u0026nbsp;\u003c/strong\u003ewhere mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emice had the lowest expression of STING.Moreover, TBI increased STING mRNA in enriched microglia 7 dpi (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,15\u0026nbsp;\u003c/sub\u003e= 5.0, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05), and this was ablated in mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emice (Interaction, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,15\u003c/sub\u003e = 4.8, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Post-hoc analysis confirmed TBI-STING\u003csup\u003e+/+\u003c/sup\u003e mice had the highest expression of \u003cem\u003eSting\u003c/em\u003e in microglia compared to all other groups (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). These mRNA data help validate the knockout of \u003cem\u003eSting\u003c/em\u003e in microglia.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe have also reported that there was increased STING protein and morphological restructuring of microglia and astrocytes 7 dpi after diffuse TBI\u0026nbsp;[22].\u0026nbsp;Thus, STING protein was assessed in the cortex 7 dpi (Fig.1E-F). Parallel to the mRNA data, TBI increased STING protein expression (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,22\u0026nbsp;\u003c/sub\u003e= 4.65, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) in the cortex 7 dpi, and this was influenced by genotype (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,22\u0026nbsp;\u003c/sub\u003e= 52.10,\u003cem\u003e\u0026nbsp;p\u003c/em\u003e\u0026lt;0.0001) with less STING protein expression in the\u0026nbsp;mSTING\u003csup\u003e-/-\u003c/sup\u003e mice\u0026nbsp;compared to\u0026nbsp;STING\u003csup\u003e+/+\u0026nbsp;\u003c/sup\u003emice (Fig.1E\u0026amp;F). Post-hoc analyses confirmed that TBI-STING\u003csup\u003e+/+\u0026nbsp;\u003c/sup\u003emice had the highest levels of STING in the cortex compared to all other groups including the\u0026nbsp;mSTING\u003csup\u003e-/-\u003c/sup\u003e mice (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001).\u0026nbsp;Parallel to these data, STING expression was determined in IBA1\u003csup\u003e+\u003c/sup\u003e microglia of the cortex 7 dpi. There was robust expression of STING 7 dpi in IBA1\u003csup\u003e+\u003c/sup\u003e microglia of wild type (STING\u003csup\u003e+/+\u003c/sup\u003e) mice (Fig.1G\u0026amp;H). Specifically, 94% of IBA1\u003csup\u003e+\u003c/sup\u003e microglia in the cortex expressed STING after TBI and this expression was reduced to 10% in the\u0026nbsp;mSTING\u003csup\u003e-/-\u003c/sup\u003e mice (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). Notably, there was non-microglia STING expression detected after TBI (Fig.1F). This increase of STING after TBI, however, was not apparent in cortical astrocytes (GFAP\u003csup\u003e+\u003c/sup\u003e) or neurons (NeuN\u003csup\u003e+\u003c/sup\u003e) (data not shown). These RNA and protein data validate that the\u0026nbsp;mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emodel is working as anticipated. Overall, \u003cem\u003eSting\u003c/em\u003e RNA and STING protein were increased in microglia 7 dpi, and both wereablated in microglia from the\u0026nbsp;mSTING\u003csup\u003e-/-\u003c/sup\u003e mice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTBI-induced microglia reactivity 7 dpi was attenuated by\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;mSTING\u003csup\u003e-/-\u003c/sup\u003e.\u0026nbsp;\u003c/strong\u003eContinuing with the influence of mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003eon TBI responses (Fig.1A\u0026amp;B), cortical gliosis and microglial morphological restructuring was determined 7 dpi in male and female STING\u003csup\u003e+/+\u003c/sup\u003e andmSTING\u003csup\u003e-/-\u003c/sup\u003e mice. As expected, there was a TBI-dependent increase in the percent area of GFAP\u003csup\u003e+\u003c/sup\u003e astrocytes (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,25\u003c/sub\u003e = 33.56, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, Fig.2A-B). This increase in cortical GFAP\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eexpression 7 dpi was independent of mSTING(Fig.2A\u0026amp;B). For cortical microglia, there was a main effect of TBI on percent area of IBA1\u003csup\u003e+\u0026nbsp;\u003c/sup\u003elabeling (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,25\u0026nbsp;\u003c/sub\u003e= 55.46, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, Fig.2C\u0026amp;D). This increase of cortical IBA1\u003csup\u003e+\u003c/sup\u003e (percent area) after TBI was influenced by mSTING\u003csup\u003e-/-\u003c/sup\u003e (Interaction, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,25\u0026nbsp;\u003c/sub\u003e= 9.30, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Post-hoc analyses confirmed that TBI-STING\u003csup\u003e+/+\u003c/sup\u003e mice had the highest IBA1\u003csup\u003e+\u003c/sup\u003e percent area compared to all groups including the TBI-mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emice (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05).\u0026nbsp;These increases in IBA1\u003csup\u003e+\u003c/sup\u003e expression are consistent with \u0026ldquo;reactive microglia\u0026rdquo;\u0026nbsp;[30]\u0026nbsp;detected after diffuse TBI\u0026nbsp;[12, 25]. Another aspect of microglial restructuring post-TBI is increased rod-shaped microglia in the cortex\u0026nbsp;[12, 31]. Here, rod-shaped microglia were increased 7 dpi in the medial cortex (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 24\u0026nbsp;\u003c/sub\u003e= 11.84, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.005,\u0026nbsp;Fig.2E\u0026amp;F). The increase in rod-shaped microglia, however, was independent of mSTING.Taken together, the reactive morphological profile of microglia 7 dpi was attenuated by mSTING\u003csup\u003e-/-\u003c/sup\u003e, but astrogliosis and rod-shaped microglia were unaffected.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTBI-associated cortical inflammation was attenuated by mSTING\u003csup\u003e-/-\u003c/sup\u003e.\u0026nbsp;\u003c/strong\u003eContinuing with the assessment of the influence of mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003eon TBI responses (Figs.1\u0026amp;2), cortical inflammation 7 dpi in male and female mice was assessed using NanoString nCounter neuroinflammation panel (770 genes). Genes that were differentially expressed (DEGs) between groups were determined using DESeq2 in R [32]. The first volcano plot (Fig.3A) shows the comparison between TBI-STING\u003csup\u003e+/+\u003c/sup\u003e and Con-STING\u003csup\u003e+/+\u003c/sup\u003e. There were 232 DEGs increased and 5 DEGs decreased after\u0026nbsp;TBI in this comparison\u0026nbsp;(\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05). Fig.3B shows the comparison between\u0026nbsp;TBI-mSTING\u003csup\u003e-/-\u003c/sup\u003e versus Con-mSTING\u003csup\u003e-/-\u003c/sup\u003e. Here, there were 76 DEGs increased and no genes decreased by TBI in mSTING\u003csup\u003e-/-\u003c/sup\u003e mice (\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05). Fig.3C shows the\u0026nbsp;comparison between TBI-mSTING\u003csup\u003e\u0026nbsp;-/-\u003c/sup\u003e mice and TBI-STING\u003csup\u003e+/+\u003c/sup\u003e. In this comparison, there were 2 DEGs increased and 82 DEGs decreased by mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003e(\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05). As stated above, the TBI response between male and female mice was similar. To highlight this,\u0026nbsp;the TBI comparison between male and female STING\u003csup\u003e+/+\u003c/sup\u003e mice is shown (Fig.3D). Only two genes (\u003cem\u003eKdm5d\u003c/em\u003e, \u003cem\u003eUty\u003c/em\u003e) were differentially expressed after TBI in male and female mice. These DEGs were increased by TBI in males only and are Y-chromosome linked genes\u0026nbsp;[33]. Thus, male and female data were collapsed and analyzed together.Overall, these volcano plots show that TBI induced gene expression in the cortex 7 dpi was robustly influenced by mSTING.\u003c/p\u003e\n\u003cp\u003eThese differences are highlighted in the Venn diagram and pie chart in Fig.3E. The Venn diagram represents DEGs that were uniquely increased in TBI-STING\u003csup\u003e+/+\u003c/sup\u003e (173 DEGs), shared between the two groups (64) or unique to TBI-mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003e(12). The pie chart shows the percentage of TBI-associated DEGs (249 total) that were attenuated by mSTING\u003csup\u003e-/-\u003c/sup\u003e (16%, reduced expression), prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e (70%, restoration to control levels), or not prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e (14%). The majority of the TBI-induced DEGs were attenuated or prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e. For instance, increased expression of myriad genes that were increased by TBI were either prevented (\u003cem\u003eIrf1, Ifi30, Ilra Irf8, Nf\u0026kappa;b2)\u003c/em\u003e or attenuated (\u003cem\u003eItbg5\u003c/em\u003e, \u003cem\u003eItimt3\u003c/em\u003e, \u003cem\u003eOlfml3\u003c/em\u003e) by mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003e(Fig.3F\u0026amp;G). Several inflammatory related DEGs were increased by TBI and this increase was either attenuated (\u003cem\u003eC1qb\u0026amp;c\u003c/em\u003e, \u003cem\u003eCd68\u003c/em\u003e \u003cem\u003eCxcl10\u003c/em\u003e) or prevented (\u003cem\u003eIl1a, Cd14, Irak4\u003c/em\u003e) in the TBI-mSTING\u003csup\u003e-/-\u003c/sup\u003e mice (Fig.3F\u0026amp;G). There were also DEGs induced by TBI (\u003cem\u003eTlr2\u003c/em\u003e, \u003cem\u003eTlr4\u003c/em\u003e, \u003cem\u003eIrf7\u003c/em\u003e, \u003cem\u003eLcn2\u003c/em\u003e, \u003cem\u003eand Sox10)\u003c/em\u003e that were not significantly attenuated or prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e (Fig.3H\u0026amp;I). Thus, not all inflammatory pathways 7 dpi relied on microglial STING. Overall, a majority of TBI-induced DEGs affected by TBI in the cortex 7 dpi were dependent on STING responses in microglia (86%) while 14% were independent of STING in microglia.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCanonical pathways associated with inflammation and IFN signaling 7 dpi were attenuated by mSTING\u003csup\u003e-/-\u003c/sup\u003e.\u0026nbsp;\u003c/strong\u003eContinuing with the NanoString analysis,Ingenuity Pathway Analysis (IPA) was used to determine canonical pathways master regulators, and upstream regulators influenced by TBI or mSTING\u003csup\u003e-/-\u003c/sup\u003e. Canonical pathways induced by TBI and prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e are shown (Fig.4A). Pathways associated with interferon signaling (cGAS-STING Signaling, Interferon alpha/beta signaling, Interferon Gamma Signaling, Activation of IRF by Cytosolic Pattern Receptors) and neuroinflammation (Phagosome Formation, S100 Family Signaling, Pyroptosis Signaling, Macrophage Classical Activation, NF- \u0026kappa;B Signaling, and iNOS Signaling) were all increased in TBI-STING\u003csup\u003e+/+\u0026nbsp;\u003c/sup\u003emice (\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05). Moreover, all these pathways increased by TBI were prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e (\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05). Canonical pathways induced by TBI and unaffected mSTING\u003csup\u003e-/-\u003c/sup\u003e are also shown (Fig.4B). These mSTING independent pathways included Neutrophil Degranulation, Complement System, Autophagy, and TREM-1 signaling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTop master regulators induced by TBI and prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e are shown (Fig.4C-D). Master regulators associated with interferon signaling (STAT1, MYD88, IFNG) were increased by TBI while regulators associated with neuronal health (GLB1, NEU3, PTGER4, IRGM1) were decreased. Master regulators prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e include pathways associated with IFN-I (IFNG), neuroinflammation (C5AR1, TREM2, CCR2, IL1B) and neuronal health (LCP1, PTGER4). Next, upstream regulators induced by TBI and prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e are shown (Fig.4E-F). Upstream regulators induced by TBI and prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e included pathways associated with phagocytosis (NPC1) and neuroinflammation (IL1B). Taken together, TBI induces myriad inflammatory and interferon mediated genes that were dependent on STING in microglia.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTBI-induced cognitive deficits 7 dpi were IFNAR1 in\u003c/strong\u003e\u003cstrong\u003edependent.\u0026nbsp;\u003c/strong\u003eOur previous [22] and current data show that both global and microglia-selective STING knockouts reduce inflammation and support cognitive recovery after TBI. Another aspect of the cGAS-STING pathway is the interferon-\u0026alpha;/\u0026beta; receptor 1 (IFNAR1), which is the primary receptor for type I interferons, alpha and beta\u0026nbsp;[34-36]. These pathways were apparent in the NanoString analyses at 7 dpi in the cortex (Fig.4). Thus, we next examined components of cognition and inflammation in male global IFNAR1\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emice. These mice were subjected to control or TBI (mFPI) and cortical and hippocampal-mediated cognition was assessed 7 dpi using NOR/NOL\u0026nbsp;(Fig.5A-F). There were no differences in total time exploring the objects between groups (Fig.5B). Fig.5C\u0026amp;D show there were TBI-induced deficits in NOR 6 dpi with reduced time exploring the novel object and impairments in the discrimination index (TBI, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,20\u003c/sub\u003e = 20.83, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), but these effects were independent of IFNAR1. These effects were mirrored in the NOL task 7 dpi (Fig.5E-G). Time spent with the object in the novel location and discrimination index were reduced by TBI (F\u003csub\u003e1,20\u0026nbsp;\u003c/sub\u003e= 70.15, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, Fig.5E-G), but again these effects were independent of IFNAR1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;After completion of the NOR/NOL cognitive assessment in these mice, cortices were extracted 7 dpi for RNA analyses. TBI increased interferon receptor-related \u003cem\u003eIrf7\u0026nbsp;\u003c/em\u003eexpression, and this increase was dependent on IFNAR1(Interaction, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e,\u003csub\u003e20\u003c/sub\u003e, = \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0017, Fig.5H). Post-hoc analysis confirmed that \u003cem\u003eIrf7\u0026nbsp;\u003c/em\u003eexpression was highest in the TBI-WT group compared to all other groups including the TBI-IFNAR1\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003egroup (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, Fig.5H). These \u003cem\u003eIrf7\u003c/em\u003e data are consistent with the global knockout of IFNAR1. Moreover, several genes associated with inflammation (\u003cem\u003eTnf, Gfap, H2-eb1\u003c/em\u003e) were increased in the cortex 7 dpi (TBI, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,18\u003c/sub\u003e = 7.92, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, for each, Fig.6I-K). The increases in these mRNA levels in the cortex 7 dpi, however, were independent of IFNAR1. Collectively, TBI-associated cognitive deficits and inflammatory mRNA expression in the cortex 7 dpi were independent of IFNAR1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNeuronal injury and cognitive deficits 7 dpi were mSTING\u003c/strong\u003e\u003cstrong\u003edependent.\u0026nbsp;\u003c/strong\u003eOur data show that mSTING (and not\u0026nbsp;IFNAR1) was important for inflammation after diffuse TBI. Moreover\u003cstrong\u003e,\u003c/strong\u003e our previous single cell and single nuclei RNA-seq studies show reduced homeostasis of cortical neurons 7 dpi was dependent on microglia [11, 22]. Based on these data, neuronal health/injury was assessed 7 dpi. First, NeuN\u003csup\u003e+\u0026nbsp;\u003c/sup\u003esignaling [37] and lipid debris (i.e., lipofuscin) in the cortex were assessed 7 dpi [26, 38]\u003cstrong\u003e.\u003c/strong\u003e For NeuN\u003csup\u003e+\u003c/sup\u003e labeling in the cortex 7 dpi, percent area of NeuN\u003csup\u003e+\u003c/sup\u003e was influenced by TBI and mSTING\u003csup\u003e-/-\u003c/sup\u003e (Interaction, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,24\u0026nbsp;\u003c/sub\u003e= 9.68, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.005, Fig.6A\u0026amp;B). Post hoc analyses indicates that TBI-STING\u003csup\u003e+/+\u003c/sup\u003e mice had the lowest NeuN\u003csup\u003e+\u003c/sup\u003e expression compared to all groups including the TBI-mSTING\u003csup\u003e-/-\u003c/sup\u003e mice (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, Fig.6B). Lipofuscin accumulation in the brain with age, disease, or brain injury may also represent reduced homeostasis of neurons and glia [38-40]. There was auto-fluorescent lipid debris visible in the cortex 7 dpi, especially within NeuN+ cells (Fig.6C). Quantification indicates that there tended to be increased auto-fluorescent lipid debris in cortical neurons (NeuN\u003csup\u003e+\u003c/sup\u003e) 7 dpi (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,19\u0026nbsp;\u003c/sub\u003e= 3.19, \u003cem\u003ep\u003c/em\u003e=0.08, Fig.6D) that tended to be reduced by genotype (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,19\u0026nbsp;\u003c/sub\u003e= 3.93, \u003cem\u003ep\u003c/em\u003e=0.06, Fig.6D). Thus, there was reduced NeuN\u003csup\u003e+\u003c/sup\u003e signaling and increased lipofuscin in cortical neurons 7 dpi that was attenuated by mSTING\u003csup\u003e-/-\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eNext, neurofilament light chain (NF-L), a relevant biomarker of neural injury after TBI [40], was determined in the plasma of mice [29]. TBI increased NF-L protein (pg/ml) levels (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,23\u003c/sub\u003e = 28.37, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, Fig.6E), and this increase was influenced by mSTING\u003csup\u003e-/-\u003c/sup\u003e (Interaction, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,23\u0026nbsp;\u003c/sub\u003e= 9.99, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.005). Post-hoc analyses confirmed TBI-STING\u003csup\u003e+/+\u003c/sup\u003e mice had the highest average NF-L expression (~3,000 pg/ml) in the plasma compared to all groups including the TBI-mSTING\u003csup\u003e-/-\u003c/sup\u003e mice (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.005). We interpret these results to indicate that TBI increased neuronal damage and dysfunction in the cortex 7 dpi that was dependent on STING in microglia.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn a similar study, control and\u0026nbsp;mSTING\u003csup\u003e-/-\u003c/sup\u003e mice\u0026nbsp;were subjected to control or TBI (mFPI), and cortical and hippocampal mediated cognition was assessed 7 dpi using NOR/NOL (Fig.6F-K). There were no differences in total time exploring the objects between groups (Fig.6F). Fig.6G-H shows TBI-induced reductions in exploration of the novel object 6 dpi (TBI, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,39\u0026nbsp;\u003c/sub\u003e= 24.53, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001). Time spent interacting with the novel object was influenced by TBI and\u0026nbsp;mSTING\u003csup\u003e-/-\u003c/sup\u003e (Interaction, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,39\u0026nbsp;\u003c/sub\u003e=12.01, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.005, Fig.6G-H). Post-hoc analyses confirmed that TBI-STING\u003csup\u003e+/+\u003c/sup\u003e mice spent the least amount of time with the novel object compared to all other groups, including the mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emice (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, Fig.6G\u0026amp;H).\u0026nbsp;These effects and interactions were mirrored in the NOL task at 7 dpi (Fig.6I-K). Time spent interacting with the novel object was influenced by TBI and genotype (Interaction, \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,43\u0026nbsp;\u003c/sub\u003e=10.81, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.005, Fig.6J\u0026amp;K). Post-hoc analyses confirmed that TBI-STING\u003csup\u003e+/+\u003c/sup\u003e mice spent the least amount of time with the novel object compared to all other groups, including the TBI-mSTING\u003csup\u003e-/-\u003c/sup\u003e mice (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, Fig.6J\u0026amp;K). Overall, microglial STING signaling was critical for neuronal dysfunction and cognitive impairment following TBI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle nucleus RNA-sequencing of cortical neurons 7 days after TBI..\u0026nbsp;\u003c/strong\u003eWe have reported that microglia and type I interferon responses were associated with reduced neuronal homeostasis in the cortex 7 dpi [22]. Here, we aimed to determine the degree to which this was dependent on STING signaling from microglia. Thus, single nucleus RNA-sequencing (snRNA-seq) was conducted in cortical samples after control or TBI (7 dpi) in male and female STING\u003csup\u003e+/+\u003c/sup\u003e or mSTING\u003csup\u003e-/-\u003c/sup\u003e mice.\u0026nbsp;Cortices were dissected, nuclei were isolated, fixed, and barcoded at 7 dpi (Fig.7A). Fig.7B shows that 89,320 nuclei were clustered into twenty distinct clusters. Clusters were identified based on gene expression of distinct markers (Fig.7C-E) (\u003cem\u003eSyt1\u003c/em\u003e- neurons, \u003cem\u003eSlc1a3\u003c/em\u003e-astrocytes, \u003cem\u003eMag\u003c/em\u003e \u0026ndash; oligodendrocytes, \u003cem\u003eFlt1\u003c/em\u003e \u0026ndash; endothelia, and \u003cem\u003eCsf1r\u003c/em\u003e \u0026ndash;microglia). In line with previous work using snRNA-seq, 90% of cells detected in Fig.7D were neurons\u0026nbsp;[22, 41, 42].\u0026nbsp;To delineate the neuronal profile with TBI and mSTING\u003csup\u003e-/-\u003c/sup\u003e 7 dpi, cortical neurons were subset and re-clustered (Fig.7F) using existing gene markers (\u003cem\u003eSlc17a7\u003c/em\u003e, \u003cem\u003eCux1/2\u003c/em\u003e, \u003cem\u003eRorb\u003c/em\u003e, \u003cem\u003eGad1/2\u003c/em\u003e, \u003cem\u003eFoxp2\u003c/em\u003e, \u003cem\u003eAdarb2\u003c/em\u003e) to classify the neuronal populations (Fig.7G\u0026amp;I). The distribution of cells based on the four experimental groups is shown (Fig.7H). Overall, there were approximately 80,000 nuclei collected from \u003cem\u003eSyt1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e cortical neurons 7 dpi, and these nuclei were represented in all the experimental groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAblation of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003emicroglial STING attenuated the response to TBI in cortical neurons.\u003c/strong\u003e Continuing with the snRNA-seq analyses of \u003cem\u003eSyt1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e cortical neurons 7 dpi, the pie chart (Fig.8A) shows the distribution of specific neuronal profiles resolved. Consistent with our previous snRNA-seq experiments assessing cortical neurons [22], 36% of the \u003cem\u003eSyt1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e nuclei corresponded to upper layer neurons (\u003cem\u003eCux1/2\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e), 30% of the \u003cem\u003eSyt1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e nuclei corresponded to layer 4 neurons (\u003cem\u003eRorb\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e), 21% of the \u003cem\u003eSyt1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e nuclei corresponded to deep layer neurons (\u003cem\u003eFoxp2\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e), and 13% \u003cem\u003eSyt1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e nuclei corresponded to inhibitory neurons (\u003cem\u003eGad1/2\u003csup\u003e+\u003c/sup\u003e).\u003c/em\u003e These neuronal sub-clusters were used for analyses. Fig.8B highlights that TBI resulted in both increased and decreased mRNA expression in cortical neurons 7 dpi, with more overall suppression of gene expression. For upper layer neurons, there were 1,146 DEGs (\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05), with 697 increased and 449 decreased DEGs after TBI. Moreover, the influence of TBI on these upper layer neurons was 50% dependent on mSTING (600 DEGs, Fig.8C). For layer 4 neurons, there were 749 DEGs (\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05) with 227 increased and 522 decreased DEGs after TBI. The influence of TBI on layer 4 neurons was 45% dependent on mSTING (357 DEGs, Fig.8C). For deep layer neurons, there were 1104 DEGs (\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05) after TBI with 445 increased and 659 decreased DEGs. The influence of TBI on deep layer neurons was 47% dependent on mSTING (591 DEGs). Last, there were 241 DEGs (\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05) in the inhibitory neurons with 49 increased and 192 decreased. In inhibitory neurons, the influence of TBI was 64% dependent on mSTING for 154 DEGs (\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05, Fig.8C). Thus, there was a robust effect of TBI on cortical neurons 7 dpi and about 50% of the DEGs were prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eNotably, both male and female mice were included in these snRNA-seq studies. Although these studies were not appropriately powered to make comparisons based on sex, we examined male and female mice within the TBI-STING\u003csup\u003e+/+\u003c/sup\u003e group. The top DEGs are shown in the dot plot for male TBI versus female TBI functional wild type mice (Fig.8C). \u003cem\u003eXist\u003c/em\u003e was increased in female wild type TBI mice compared to males and this is an X linked gene [43]. \u003cem\u003eUty\u003c/em\u003e, \u003cem\u003eEif2s3y\u003c/em\u003e, \u003cem\u003eKdm5d\u003c/em\u003e, and \u003cem\u003eDxd3y\u003c/em\u003e were increased in male TBI mice compared to female TBI mice. These genes are all y-linked [33, 44, 45].\u0026nbsp;Thus, male and female snRNA-seq data were analyzed together.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo visualize the significant DEGs in Fig8B\u0026amp;C, volcano plots are shown (Fig8E-J). For upper layer neurons (UL), the volcano plot shows the\u0026nbsp;comparison between Con-STING\u003csup\u003e+/+\u003c/sup\u003e and TBI-STING\u003csup\u003e+/+\u003c/sup\u003e mice with 697 DEGs increased and 449 DEGs decreased (\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05, Fig.8E). For instance, there was a TBI associated reduction in two synaptic plasticity related genes, \u003cem\u003e\u003cbr\u003e\u0026nbsp;Arc\u003c/em\u003e and \u003cem\u003eHomer1\u003c/em\u003e. Fig.8F shows the\u0026nbsp;comparison between Con-mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003eand TBI-mSTING\u003csup\u003e-/-\u003c/sup\u003e mice.In this comparison, 1728 DEGs were increased by TBI and 1312 DEGs were decreased. Fig.8G shows comparison between TBI-mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003eand TBI-STING\u003csup\u003e+/+\u003c/sup\u003e mice. Here, there were 44 DEGs increased and 148 DEGs decreased. These data highlight a reduced influence of TBI on upper layer cortical neurons in the mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emice compared to controls (STING\u003csup\u003e+/+\u003c/sup\u003e mice). For instance, the reduction of \u003cem\u003eHomer1\u003c/em\u003e and \u003cem\u003eArc\u0026nbsp;\u003c/em\u003eafter TBI were prevented in the TBI-mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003egroup.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor deep layer neurons (DL), the volcano plot shows\u0026nbsp;comparison between Con-STING\u003csup\u003e+/+\u003c/sup\u003e and TBI-STING\u003csup\u003e+/+\u003c/sup\u003e mice with 445 DEGs increased and 659 DEGs decreased (\u003cem\u003ep\u003c/em\u003e-adj\u0026lt;0.05, Fig.8H). For instance, there was a TBI associated reduction in three synaptic plasticity related genes, \u003cem\u003eArc, Bdnf,\u003c/em\u003e and \u003cem\u003eHomer1\u003c/em\u003e. Reductions also evident in \u003cem\u003eApoE\u003c/em\u003e (lipid transport), \u003cem\u003eCalm1\u003c/em\u003e (calcium signaling), and \u003cem\u003eAtg4a\u003c/em\u003e (autophagy). Fig.8I shows the\u0026nbsp;comparison between Con-mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003eand TBI-mSTING\u003csup\u003e-/-\u003c/sup\u003e mice.There were 924 DEGs increased and 1662 DEGs decreased. These data highlight that there was a reduced influence of TBI on deep layer cortical neurons in the mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003emice compared to controls (STING\u003csup\u003e+/+\u003c/sup\u003e mice). For instance, the reduction of \u003cem\u003eAtg4a\u0026nbsp;\u003c/em\u003eand \u003cem\u003eHomer1\u003c/em\u003e after TBI were prevented in the TBI-mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003egroup (Fig.8J). Overall, TBI influenced the RNA profile of cortical neurons with a suppressive effect that was influenced by mSTING.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAblation of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003emicroglial STING attenuated TBI-induced imbalance in neuronal homeostasis of cortical neurons.\u003c/strong\u003e Continuing with the snRNA-seq analyses of \u003cem\u003eSyt1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e cortical neurons 7 dpi, DEGs (\u003cem\u003ep-\u003c/em\u003eadj\u0026lt;0.05) were analyzed in IPA for canonical pathways, master regulators and upstream regulators. Significant canonical pathways (\u003cem\u003ez\u0026nbsp;\u003c/em\u003escore, -3.8 to 3.9) influenced by TBI are shown in upper layer (UL), layer 4 (L4), deep layer (DL) and inhibitory (IN) cortical neurons (Fig.9A). These pathways were conserved across the four neuronal subtypes. For example, TBI increased canonical pathways associated with neuronal restructuring (e.g., Cilium Assembly, VDR/RXR Activation, RHOGDI Signaling, Transcriptional Regulation by MECP2, and Netrin Signaling) and inhibition of growth (PTEN signaling). TBI also suppressed canonical pathways associated with neuronal homeostasis and metabolism (CREB Signaling, Synaptogenesis, S100 Family Signaling). These data are consistent with our previous work on the effects of TBI on neurons [22]. Next the significant canonical pathways induced by TBI and prevented by mSTING are shown in upper layer (UL), layer 4 (L4), deep layer (DL) and inhibitory (IN) cortical neurons (Fig.9B). Canonical pathways that were decreased following TBI and influenced by mSTING were associated with neuronal health (Oxytocin Signaling, Endothelin-1 Signaling, CREB Signaling, and Orexin Signaling). Canonical pathways that were increased by TBI associated with neuronal restructuring (Cilium Assembly) and inhibition of growth (PTEN) were also prevented by mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003e(Fig.9B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNext, significant master regulators that were influenced by TBI are shown in upper layer (UL), layer 4 (L4), deep layer (DL) and inhibitory (IN) cortical neurons (Fig.9C). TBI increased DLGAP3, MYCBP2, RELN, CDK5 in upper layer and layer 4 neurons, and decreased CAMK, CREM, IL-4R, and GRM5. Master regulators reduced by TBI associated with neuronal homeostasis (e.g., CAM4K, CREM, IL4R, GRM5, ADORA2A) were prevented by mSTING, especially in deep layer neurons (Fig.9D). As such, deep layer neurons had the\u0026nbsp;most master regulators prevented by mSTING\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003e(7). Upper layer neurons had the most upstream regulators induced by TBI and prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e (7). These upstream regulators are associated with neuronal homeostasis (e.g., MECP2, MKNK1, CREB1, IL4R, CREM, ADORA2A, BDNF). These regulators were reduced by TBI, and this reduction was prevented by mSTING\u003csup\u003e-/-\u003c/sup\u003e (Fig.9F). Upstream regulators increased by TBI include HNRNPU, PTF1A, FMR1, and MAPT and decreased upstream regulators include BDNF, IL4R, CREM, and CREB1 (Fig.9E). These changes were prevented by mSTING, especially in upper layer cortical neurons (Fig.9F). Taken together, TBI reduced cortical neuronal homeostasis, and this was dependent on STING in microglia 7 dpi.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe previously reported that a global knockout of the stimulator of interferons genes (STING) reduced chronic inflammation and cognitive impairment associated with diffuse TBI [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e]. Thus, the aim of this study was to determine the degree to which a microglia-specific knockout of STING influenced neuroinflammation, neuronal dysfunction, and cognitive deficits induced by diffuse TBI. Here, TBI induced microglial morphological restructuring and cortical inflammation 7 dpi were mSTING dependent. In addition, neuronal injury and cognitive impairment 7 dpi were also dependent on mSTING. With snRNA-seq of cortical neurons after TBI, there were reductions in CREB signaling, synaptogenesis, and oxytocin signaling and increases in cilium assembly and PTEN signaling. These reductions in neuronal homeostasis were mSTING dependent. Collectively, ablation of STING in microglia attenuated TBI-induced IFN-dependent responses, cortical inflammation, cortical pathology, neuronal dysfunction, and cognitive impairment.\u003c/p\u003e\n\u003cp\u003eOne key finding of this study was that increased STING expression 7 days after TBI in the cortex was localized to IBA1\u003csup\u003e+\u003c/sup\u003e microglia, and this increase in STING was ablated by microglial STING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e. The increase in STING expression in the cortex after TBI is consistent with previous findings showing enhanced IFN-I responses after either diffuse [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e] or penetrating TBI [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e]. Moreover, studies of penetrating TBI induced by controlled cortical impact (CCI) indicate that STING is localized to IBA1\u003csup\u003e+\u003c/sup\u003e microglia [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e]. The extension here is that STING was localized to cortical microglia after diffuse TBI and this increase was ablated by a transgenic model of mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e. While STING induction was detected in other cell types including neurons and astrocytes after TBI [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e], STING after diffuse TBI was localized in cortical microglia and undetectable in astrocytes and neurons. Assessment of mRNA from percoll enriched microglia paralleled these data with a TBI-dependent increase in STING mRNA 7 dpi and ablation by microglial STING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e. These findings are also consistent with our previous reports using snRNA-seq that microglia, not neurons, expressed genes associated with the production of IFN-I after TBI [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e]. These RNA and protein findings validate the targeted knock out of STING in microglia. Overall, TBI increased STING expression within IBA1\u003csup\u003e+\u003c/sup\u003e microglia 7 dpi was ablated in mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice.\u003c/p\u003e\n\u003cp\u003eAnother relevant point is that TBI-induced microglial restructuring (IBA1\u003csup\u003e+\u003c/sup\u003e percent area increase) 7 dpi was dependent on mSTING. Rod-shaped microglia and GFAP\u003csup\u003e+\u003c/sup\u003e astrocytes were also increased 7 dpi, but were independent of mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e. These data are similar to our previous reports where TBI-induced microglial restructuring was reduced by global STING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e, but astrogliosis was unaffected [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e]. In addition, another report showed that astrocytes were unresponsive to STING activation after TBI [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]. Rod-shaped microglia are detected in humans and rodents in the context of advanced age, neurodegeneration, and TBI [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e], but their function is unclear. In a previous report, rod-shaped microglia were reduced in the cortex 7 dpi of global STING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e]. Here, rod-shaped microglia were unaffected by mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e. One explanation for this difference is that rod-shaped microglia in the cortex 7 dpi are mSTING independent and may serve a neuroprotective role. For instance, these structurally unique and elongated microglia aligned with apical dendrites of damaged neurons in the cortex 7 dpi [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]. These cells were present 7 dpi in the cortex of mice with microglia depletion (PLX5622), which was associated with reduced neuroinflammation and cognitive improvement [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. Furthermore, elimination of rod-shaped microglia using a TREM2 knock out in an ALS model increased neuronal hyperactivity, worsened motor deficits, and further reduced survival rates in mice [\u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e]. Collectively, there were structurally divergent profiles of cortical glia 7 dpi and the reactive microglia profile was attenuated by mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAnother point for discussion is the increased IFN-I and pro-inflammatory signaling in the cortex 7 dpi was dependent on microglial STING. For example, there were 232 genes detected in the NanoString panel (770 genes) associated with type I interferon signaling, inflammation, and antigen presentation 7 dpi. A majority of these TBI-associated genes were reduced (86%) by mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e. Notably, there were minimal sex differences detected in the cortical mRNA analyses with only two sex-linked genes (\u003cem\u003eKdm5d\u003c/em\u003e and \u003cem\u003eUty\u003c/em\u003e) [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e] different between male and female TBI mice. Overall, TBI increased genes associated with IFN-I and inflammation in male and female mice, and these were reduced by mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e. Consistent with these DEGs, IPA canonical pathways and master regulator analyses showed myriad IFN-I and inflammatory pathways increased after TBI including activation of IRF, NF\u0026kappa;B, and cGAS-STING. These increases in genes and pathways associated with IFN-I, inflammation, and microglial priming are consistent with previous reports 7 dpi [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e]. Key pathways induced by TBI 7 dpi and prevented by mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e included cGAS-STING, NF-\u0026kappa;B, and neuroinflammation signaling. Notably, some DEGs (35) and IPA pathways that were induced by TBI were unaffected by mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e. These DEGS were genes associated with the complement cascade (\u003cem\u003eC3, C4a\u003c/em\u003e), astrocyte associated genes (\u003cem\u003eAldh1l1, Gja1)\u003c/em\u003e and endothelia associated genes (\u003cem\u003eBlnk, Enpp6)\u003c/em\u003e. There were 12 total genes uniquely increased by TBI in mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice. A majority of these increased DEGs were neuronal (\u003cem\u003eTubb3, Gria, Slc17a7, Rala, etc.)\u003c/em\u003e, and may represent improved neuroprotection following TBI in mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice. Thus, the inflammatory and IFN-I responses in the cortex 7 dpi were robustly influenced by STING in microglia.\u003c/p\u003e\n\u003cp\u003eOne notable finding of this study was that global IFNAR1 knockout did not reduce cortical inflammation or cognitive impairment 7 dpi. We and others have shown increased genes and pathways following diffuse and penetrating TBI related to the IFNAR1 pathway [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]. Presumably cGAS-STING activation in microglia after TBI increases \u003cem\u003eIrf3\u003c/em\u003e and corresponding IFN-I that would use the IFNAR1 [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e]. Indeed, several studies show improvements in inflammation, cognition, and neurologic dysfunction following selective modulation of the IFNAR1 pathway with diffuse [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e] and penetrating TBI [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. Here, global IFNAR1 knockout did not reduce cortical inflammation or cognitive impairment 7 dpi. Global IFNAR1 knockout, however, reduced the induction of \u003cem\u003eIrf7\u003c/em\u003e 7 dpi. One explanation is that the STING pathway also promotes NF-\u0026kappa;B-mediated genes (e.g., \u003cem\u003eIL-6\u003c/em\u003e, \u003cem\u003eTNF\u003c/em\u003e and \u003cem\u003eIL-1\u003c/em\u003e) [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e] and these pro-inflammatory cytokines are more responsible for the downstream effects on neurons and cognitive processes. For instance, the IL-1 receptor-1 (IL1-R1) is highly expressed on DG neurons of the hippocampus [\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e] and IL-1/IL-R1 responses are evident chronically after closed head TBI [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e]. Another explanation is that there are reported confounds of IFNAR1\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e. For instance, one report showed that global and microglia specific knockouts of IFNAR1 led to dysfunctional microglia with a \u0026ldquo;bubble\u0026rdquo; phagosome formation and increased accumulation of DNA-damaged neurons [\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e]. Another study showed that astrocytic IFNAR1 deletion in mice caused cognitive dysfunction and reduced synaptic plasticity [\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e]. Because of the potential confounds of these global IFNAR1\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice, we conducted only limited studies with them and instead focused on mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice. Taken together, the interpretation is that ablating STING in microglia was more beneficial than targeting IFNAR1 because STING is upstream and thus affects both IFN-I and NF-\u0026kappa;B mediated responses after diffuse TBI.\u003c/p\u003e\n\u003cp\u003eAnother relevant finding was the neuropathological influences of TBI (7 dpi) were dependent on STING in microglia. For example, there was reduced percent area labeling of NeuN\u003csup\u003e+\u003c/sup\u003e in the cortex 7 dpi, which was attenuated in TBI-mSTING mice. The interpretation is that reduced NeuN\u003csup\u003e+\u003c/sup\u003e labeling corresponds with more dysfunction or atypical neurons in the cortex after diffuse TBI. A similar TBI-induced reduction of NeuN in the cortex 7 dpi was detected in a weight drop model of TBI in mice (up to 6 months later) and associated with increase blood brain barrier permeability after TBI [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]. In the same study, the reduced NeuN\u003csup\u003e+\u003c/sup\u003e neurons were associated with reduced synaptic plasticity [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]. Parallel to this, lipofuscin (i.e., autofluorescent lipid debris) detected here in cortical neurons may also represent reduced homeostasis [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e]. Indeed, several studies show increased lipofuscin in the brain with age or after TBI [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]. Moreover, increased lipofuscin after TBI in aged mice was associated with neuronal loss, glial activation, and oxidative stress [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]. Taken together, targeted mSTING deletion prevented inflammatory cytokine, chemokine, and IFN-I production that deleteriously affected neuronal homeostasis in the cortex.\u003c/p\u003e\n\u003cp\u003eConsistent with the above data, we show novel data that the TBI-associated increase in plasma NF-L (7 dpi) was attenuated in the TBI-mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice. NF-L is a clinically validated biomarker for neuronal and axonal injury after moderate to severe TBI in humans [\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]. Moreover, use of plasma NF-L as a biomarker reflecting the extent of underlying neuropathology in humans has been validating using MRI and cerebral microdialysis [\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]. Thus, we interpret the data to show ablating STING in microglia was neuroprotective with less axonal and neuronal damage after diffuse TBI. Non-selectively inhibition of microglia after CNS injury may have off target effects that worsen recovery. For instance, minocycline reduced microglia activation in humans (by MRI) after TBI, but increased the neuronal damage marker, NF-L, in the plasma [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e]. Furthermore, depletion of microglia prior to spinal cord injury worsened pathology by interfering with astrocytic dynamics [\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e]. Thus, inhibition of specific microglia pathways, like STING, are critical for addressing chronic neuroinflammation elicited by traumatic CNS injury while minimizing off target effects of treatment. Parallel with the evidence of increased neuronal injury 7 dpi, TBI reduced cortical/hippocampal dependent memory with reduced novel object/exploration 7 dpi. Here, novel data shows that these reductions in cognition after TBI were mSTING dependent. These data are consistent with previous studies of global STING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e] and microglial elimination [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e] showing that limiting inflammatory pathways in microglia improved behavioral and cognitive recovery after diffuse TBI. Taken together, TBI induced neuronal and cognitive dysfunction 7 dpi associated with increased NF-L, reduced NeuN\u003csup\u003e+\u003c/sup\u003e expression, and cognitive deficits were prevented by mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eConsistent with our previous data [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e] snRNA-seq analysis in the cortex 7 dpi shows suppression of neuronal pathways associated with metabolism and homeostasis (CREB Signaling in Neurons, Synaptogenesis, S100 Signaling, GPCR Mediated Nutrient Sensing, and Cholecystokinin Signaling). This pattern was conserved across all neuronal subtypes sampled, especially the excitatory neurons (DL, L4, and UL) indicating a shared pattern of cortical neuron suppression. Here, novel data shows that t extension was that STING ablation in microglia prevented these imbalances. For instance, approximately 50% of all DEGs influenced by TBI were prevented in microglial mSTING\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice. The mSTING dependent reversals of the TBI effects in upper layer (UL), layer 4 (L4), and deep layer (DL) neurons included canonical pathways (Cilium Assembly, RHODI, and Netrin Signaling) and master regulators (HNRNPU, PTF1A, FMR1, MAPT) associated with neuronal restructuring. These RNA data are consistent with the physiological neuronal restructuring and dendritic atrophy detected after TBI [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. These physiological changes reported after TBI in mice were associated with cognitive dysfunction and depressive-like behavior [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. In addition, the mSTING dependent reversals of the TBI effects in UL, L4, and DL neurons included canonical pathways (Oxytocin Signaling, GPCR Mediated Nutrient Sensing, CREB Signaling, S100 Family Signaling) and master regulators (MECP2, CREB1, IL4R, and BDNF) associated with neuronal homeostasis and metabolism. These pathways and master regulators increased following TBI are related to neuronal and synaptic remodeling, and likely represent the same cassette of genes previously reported to be associated with the Phosphatase and Tensin Homolog (PTEN) signaling [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e]. PTEN is a master regulator of neuronal and dendritic morphological restructuring [\u003cspan class=\"CitationRef\"\u003e59\u003c/span\u003e], and the increase in PTEN following traumatic CNS injuries is a potential target of intervention [\u003cspan class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e]. In summary, the reduced homeostasis of neurons in the cortex 7 dpi was associated with increased STING responses in microglia.\u003c/p\u003e\n\u003cp\u003eA final point for discussion is that this study was not powered for sex comparisons. Nonetheless, male and female mice were used and there were similar patterns of responses following TBI. For instance, NanoString and single nucleus RNA-seq analyses revealed the same sex-linked genes (\u003cem\u003eUty\u003c/em\u003e, \u003cem\u003eKdm5d\u003c/em\u003e) were the top DEGs between male and female mice 7 dpi. Again, sex differences in TBI is an important issue and several reports indicate sexually dimorphic responses following TBI [\u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e]. Nonetheless, STING and IFN-I responses to diffuse TBI were conserved in male and females 7 dpi. In conclusion, while sex differences are important aspects to interrogate with TBI, STING, and IFN-I responses after diffuse TBI were conserved in males and females.\u003c/p\u003e\n\u003cp\u003eIn summary, we show that diffuse TBI induced a STING response in microglia associated with IFN-I that impairs cortical neuronal homeostasis and cognition. The TBI-induced neuronal restructuring, neuronal damage, and snRNA-profiles were dependent on microglial STING. Targeted pharmacotherapies to reduce this microglial STING response may be beneficial in reducing neuroinflammation and corresponding neurocognitive complications following TBI.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Declaration:\u003c/strong\u003e This research was supported by a National Institute of Neurological Disorders and Stroke (NINDS)\u0026nbsp;R01 grant (NS118037 to JPG). JMP and ACD were supported by OSU Distinguished University Fellowships. LMW was supported by an NINDS T32 grant (NS105864). In\u0026nbsp;addition, this work was supported by an NINDS P30 Core Grant (NS045758)\u0026nbsp;to the Center for Brain and Spinal Cord Repair.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e. BioRender was used to construct Figure 8C. The authors thank Dr. Kim Green (University of California-Irvine) and his laboratory for their help with the protocol and initial pilot study for the analyses of neurofilament light chain (NF-L) in the plasma. The authors also thank Ryan Bullard, Braedan Oliver, Zoë Tapp-Poole, and Lauren Otto (The Ohio State University) for with their technical assistance on aspects on the project.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Disclosures:\u003c/strong\u003e The authors have no financial conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e All authors contributed to the study’s conception and design. Material preparation and data collection were performed by JMP, SGG, LMW, ACD, and CEB. Experimental design and data analyses were performed by JMP and JPG. The manuscript was written by JMP and JPG and all authors were involved in editing. Funding acquisition, administration, and supervision were performed by JPG. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Declaration:\u0026nbsp;\u003c/strong\u003eWe affirm that this paper contains original data that have not been submitted elsewhere for publication and that all authors have read and approved the manuscript. All authors also report no financial conflicts of interest. All procedures were performed in accordance with the National Institute of Health Guidelines for the Care and Use of Laboratory Animals, the Public Health Service’s Policy on Human Care and Use of Laboratory Animals, and the Guide for the Care and Use of Laboratory Animals and were approved by The Ohio State University Institutional Laboratory Animal Care and Use Committee.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eM. Faul, V. Coronado, Epidemiology of traumatic brain injury, Handb Clin Neurol 127 (2015) 3-13.\u003c/li\u003e\n \u003cli\u003eO.N. Kokiko-Cochran, J.P. Godbout, The Inflammatory Continuum of Traumatic Brain Injury and Alzheimer\u0026apos;s Disease, Front Immunol 9 (2018) 672.\u003c/li\u003e\n \u003cli\u003eL.M. Wangler, J.P. Godbout, Microglia moonlighting after traumatic brain injury: aging and interferons influence chronic microglia reactivity, Trends Neurosci 46(11) (2023) 926-940.\u003c/li\u003e\n \u003cli\u003eR.J. Henry, D.J. Loane, Targeting chronic and evolving neuroinflammation following traumatic brain injury to improve long-term outcomes: insights from microglial-depletion models, Neural Regen Res 16(5) (2021) 976-977.\u003c/li\u003e\n \u003cli\u003eD.J. Loane, A. Kumar, B.A. Stoica, R. Cabatbat, A.I. Faden, Progressive neurodegeneration after experimental brain trauma: association with chronic microglial activation, J Neuropathol Exp Neurol 73(1) (2014) 14-29.\u003c/li\u003e\n \u003cli\u003eA.F. Ramlackhansingh, D.J. Brooks, R.J. Greenwood, S.K. Bose, F.E. Turkheimer, K.M. Kinnunen, S. Gentleman, R.A. Heckemann, K. Gunanayagam, G. Gelosa, D.J. Sharp, Inflammation after trauma: microglial activation and traumatic brain injury, Ann Neurol 70(3) (2011) 374-83.\u003c/li\u003e\n \u003cli\u003eJ.M. Coughlin, Y. Wang, I. Minn, N. Bienko, E.B. Ambinder, X. Xu, M.E. Peters, J.W. Dougherty, M. Vranesic, S.M. Koo, H.H. Ahn, M. Lee, C. Cottrell, H.I. Sair, A. Sawa, C.A. Munro, C.J. Nowinski, R.F. Dannals, C.G. Lyketsos, M. Kassiou, G. Smith, B. Caffo, S. Mori, T.R. Guilarte, M.G. Pomper, Imaging of Glial Cell Activation and White Matter Integrity in Brains of Active and Recently Retired National Football League Players, JAMA Neurol 74(1) (2017) 67-74.\u003c/li\u003e\n \u003cli\u003eJ.M. Coughlin, Y. Wang, C.A. Munro, S. Ma, C. Yue, S. Chen, R. Airan, P.K. Kim, A.V. Adams, C. Garcia, C. Higgs, H.I. Sair, A. Sawa, G. Smith, C.G. Lyketsos, B. Caffo, M. Kassiou, T.R. Guilarte, M.G. Pomper, Neuroinflammation and brain atrophy in former NFL players: An in vivo multimodal imaging pilot study, Neurobiol Dis 74 (2015) 58-65.\u003c/li\u003e\n \u003cli\u003eV.E. Johnson, J.E. Stewart, F.D. Begbie, J.Q. Trojanowski, D.H. Smith, W. Stewart, Inflammation and white matter degeneration persist for years after a single traumatic brain injury, Brain 136(Pt 1) (2013) 28-42.\u003c/li\u003e\n \u003cli\u003eC.E. Bray, K.G. Witcher, D. Adekunle-Adegbite, M. Ouvina, M. Witzel, E. Hans, Z.M. Tapp, J. Packer, E. Goodman, F. Zhao, T. Chunchai, S. O\u0026apos;Neil, S.C. Chattipakorn, J. Sheridan, O.N. Kokiko-Cochran, C. Askwith, J.P. Godbout, Chronic Cortical Inflammation, Cognitive Impairment, and Immune Reactivity Associated with Diffuse Brain Injury Are Ameliorated by Forced Turnover of Microglia, J Neurosci 42(20) (2022) 4215-4228.\u003c/li\u003e\n \u003cli\u003eK.G. Witcher, C.E. Bray, T. Chunchai, F. Zhao, S.M. O\u0026apos;Neil, A.J. Gordillo, W.A. Campbell, D.B. McKim, X. Liu, J.E. Dziabis, N. Quan, D.S. Eiferman, A.J. Fischer, O.N. Kokiko-Cochran, C. Askwith, J.P. Godbout, Traumatic Brain Injury Causes Chronic Cortical Inflammation and Neuronal Dysfunction Mediated by Microglia, J Neurosci 41(7) (2021) 1597-1616.\u003c/li\u003e\n \u003cli\u003eK.G. Witcher, C.E. Bray, J.E. Dziabis, D.B. McKim, B.N. Benner, R.K. Rowe, O.N. Kokiko-Cochran, P.G. Popovich, J. Lifshitz, D.S. Eiferman, J.P. Godbout, Traumatic brain injury-induced neuronal damage in the somatosensory cortex causes formation of rod-shaped microglia that promote astrogliosis and persistent neuroinflammation, Glia 66(12) (2018) 2719-2736.\u003c/li\u003e\n \u003cli\u003eR.J. Henry, R.M. Ritzel, J.P. Barrett, S.J. Doran, Y. Jiao, J.B. Leach, G.L. Szeto, J. Wu, B.A. Stoica, A.I. Faden, D.J. Loane, Microglial Depletion with CSF1R Inhibitor During Chronic Phase of Experimental Traumatic Brain Injury Reduces Neurodegeneration and Neurological Deficits, J Neurosci 40(14) (2020) 2960-2974.\u003c/li\u003e\n \u003cli\u003eH. Gangal, J. Iannucci, Y. Huang, R. Chen, W. Purvines, W.T. Davis, A. Rivera, G. Johnson, X. Xie, S. Mukherjee, V. Vierkant, K. Mims, K. O\u0026apos;Neill, X. Wang, L.A. Shapiro, J. Wang, Traumatic Brain Injury Exacerbates Alcohol Consumption and Neuroinflammation with Decline in Cognition and Cholinergic Activity, bioRxiv (2024).\u003c/li\u003e\n \u003cli\u003eB.P. Todd, M.S. Chimenti, Z. Luo, P.J. Ferguson, A.G. Bassuk, E.A. Newell, Traumatic brain injury results in unique microglial and astrocyte transcriptomes enriched for type I interferon response, J Neuroinflammation 18(1) (2021) 151.\u003c/li\u003e\n \u003cli\u003eL.M. Wangler, C.E. Bray, J.M. Packer, Z.M. Tapp, A.C. Davis, S.M. O\u0026apos;Neil, K. Baetz, M. Ouvina, M. Witzel, J.P. Godbout, Amplified Gliosis and Interferon-Associated Inflammation in the Aging Brain following Diffuse Traumatic Brain Injury, J Neurosci 42(48) (2022) 9082-9096.\u003c/li\u003e\n \u003cli\u003eJ.P. Barrett, S.M. Knoblach, S. Bhattacharya, H. Gordish-Dressman, B.A. Stoica, D.J. Loane, Traumatic Brain Injury Induces cGAS Activation and Type I Interferon Signaling in Aged Mice, Front Immunol 12 (2021) 710608.\u003c/li\u003e\n \u003cli\u003eH. Ishikawa, Z. Ma, G.N. Barber, STING regulates intracellular DNA-mediated, type I interferon-dependent innate immunity, Nature 461(7265) (2009) 788-92.\u003c/li\u003e\n \u003cli\u003eA. Decout, J.D. Katz, S. Venkatraman, A. Ablasser, The cGAS-STING pathway as a therapeutic target in inflammatory diseases, Nat Rev Immunol 21(9) (2021) 548-569.\u003c/li\u003e\n \u003cli\u003eT. Abe, G.N. Barber, Cytosolic-DNA-mediated, STING-dependent proinflammatory gene induction necessitates canonical NF-kappaB activation through TBK1, J Virol 88(10) (2014) 5328-41.\u003c/li\u003e\n \u003cli\u003eS. Yum, M. Li, Y. Fang, Z.J. Chen, TBK1 recruitment to STING activates both IRF3 and NF-kappaB that mediate immune defense against tumors and viral infections, Proc Natl Acad Sci U S A 118(14) (2021).\u003c/li\u003e\n \u003cli\u003eJ.M. Packer, C.E. Bray, N.B. Beckman, L.M. Wangler, A.C. Davis, E.J. Goodman, N.E. Klingele, J.P. Godbout, Impaired cortical neuronal homeostasis and cognition after diffuse traumatic brain injury are dependent on microglia and type I interferon responses, Glia 72(2) (2024) 300-321.\u003c/li\u003e\n \u003cli\u003eL.E. Fritsch, J. Ju, E.K. Gudenschwager Basso, E. Soliman, S. Paul, J. Chen, A.M. Kaloss, E.A. Kowalski, T.C. Tuhy, R.D. Somaiya, X. Wang, I.C. Allen, M.H. Theus, A.M. Pickrell, Type I Interferon Response Is Mediated by NLRX1-cGAS-STING Signaling in Brain Injury, Front Mol Neurosci 15 (2022) 852243.\u003c/li\u003e\n \u003cli\u003eL.E. Fritsch, C. Kelly, J. Leonard, C. de Jager, X. Wei, S. Brindley, E.A. Harris, A.M. Kaloss, N. DeFoor, S. Paul, H. O\u0026apos;Malley, J. Ju, M.L. Olsen, M.H. Theus, A.M. Pickrell, STING-Dependent Signaling in Microglia or Peripheral Immune Cells Orchestrates the Early Inflammatory Response and Influences Brain Injury Outcome, J Neurosci 44(12) (2024).\u003c/li\u003e\n \u003cli\u003eA.M. Fenn, J.C. Gensel, Y. Huang, P.G. Popovich, J. Lifshitz, J.P. Godbout, Immune activation promotes depression 1 month after diffuse brain injury: a role for primed microglia, Biol Psychiatry 76(7) (2014) 575-84.\u003c/li\u003e\n \u003cli\u003eS.M. O\u0026apos;Neil, K.G. Witcher, D.B. McKim, J.P. Godbout, Forced turnover of aged microglia induces an intermediate phenotype but does not rebalance CNS environmental cues driving priming to immune challenge, Acta Neuropathol Commun 6(1) (2018) 129.\u003c/li\u003e\n \u003cli\u003eZ.M. Tapp, S. Cornelius, A. Oberster, J.E. Kumar, R. Atluri, K.G. Witcher, B. Oliver, C. Bray, J. Velasquez, F. Zhao, J. Peng, J. Sheridan, C. Askwith, J.P. Godbout, O.N. Kokiko-Cochran, Sleep fragmentation engages stress-responsive circuitry, enhances inflammation and compromises hippocampal function following traumatic brain injury, Exp Neurol 353 (2022) 114058.\u003c/li\u003e\n \u003cli\u003eE.S. Wohleb, A.M. Fenn, A.M. Pacenta, N.D. Powell, J.F. Sheridan, J.P. Godbout, Peripheral innate immune challenge exaggerated microglia activation, increased the number of inflammatory CNS macrophages, and prolonged social withdrawal in socially defeated mice, Psychoneuroendocrinology 37(9) (2012) 1491-505.\u003c/li\u003e\n \u003cli\u003eK.M. Tran, S. Kawauchi, E.A. Kramar, N. Rezaie, H.Y. Liang, J.S. Sakr, A. Gomez-Arboledas, M.A. Arreola, C.D. Cunha, J. Phan, S. Wang, S. Collins, A. Walker, K.X. Shi, J. Neumann, G. Filimban, Z. Shi, G. Milinkeviciute, D.I. Javonillo, K. Tran, M. Gantuz, S. Forner, V. Swarup, A.J. Tenner, F.M. LaFerla, M.A. Wood, A. Mortazavi, G.R. MacGregor, K.N. Green, A Trem2(R47H) mouse model without cryptic splicing drives age- and disease-dependent tissue damage and synaptic loss in response to plaques, Mol Neurodegener 18(1) (2023) 12.\u003c/li\u003e\n \u003cli\u003eR.C. Paolicelli, A. Sierra, B. Stevens, M.E. Tremblay, A. Aguzzi, B. Ajami, I. Amit, E. Audinat, I. Bechmann, M. Bennett, F. Bennett, A. Bessis, K. Biber, S. Bilbo, M. Blurton-Jones, E. Boddeke, D. Brites, B. Brone, G.C. Brown, O. Butovsky, M.J. Carson, B. Castellano, M. Colonna, S.A. Cowley, C. Cunningham, D. Davalos, P.L. De Jager, B. de Strooper, A. Denes, B.J.L. Eggen, U. Eyo, E. Galea, S. Garel, F. Ginhoux, C.K. Glass, O. Gokce, D. Gomez-Nicola, B. Gonzalez, S. Gordon, M.B. Graeber, A.D. Greenhalgh, P. Gressens, M. Greter, D.H. Gutmann, C. Haass, M.T. Heneka, F.L. Heppner, S. Hong, D.A. Hume, S. Jung, H. Kettenmann, J. Kipnis, R. Koyama, G. Lemke, M. Lynch, A. Majewska, M. Malcangio, T. Malm, R. Mancuso, T. Masuda, M. Matteoli, B.W. McColl, V.E. Miron, A.V. Molofsky, M. Monje, E. Mracsko, A. Nadjar, J.J. Neher, U. Neniskyte, H. Neumann, M. Noda, B. Peng, F. Peri, V.H. Perry, P.G. Popovich, C. Pridans, J. Priller, M. Prinz, D. Ragozzino, R.M. Ransohoff, M.W. Salter, A. Schaefer, D.P. Schafer, M. Schwartz, M. Simons, C.J. Smith, W.J. Streit, T.L. Tay, L.H. Tsai, A. Verkhratsky, R. von Bernhardi, H. Wake, V. Wittamer, S.A. Wolf, L.J. Wu, T. Wyss-Coray, Microglia states and nomenclature: A field at its crossroads, Neuron 110(21) (2022) 3458-3483.\u003c/li\u003e\n \u003cli\u003eJ.M. Ziebell, S.E. Taylor, T. Cao, J.L. Harrison, J. Lifshitz, Rod microglia: elongation, alignment, and coupling to form trains across the somatosensory cortex after experimental diffuse brain injury, J Neuroinflammation 9 (2012) 247.\u003c/li\u003e\n \u003cli\u003eM.I. Love, W. Huber, S. Anders, Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2, Genome Biol 15(12) (2014) 550.\u003c/li\u003e\n \u003cli\u003eM. Kosugi, M. Otani, Y. Kikkawa, Y. Itakura, K. Sakai, T. Ito, M. Toyoda, Y. Sekita, T. Kimura, Mutations of histone demethylase genes encoded by X and Y chromosomes, Kdm5c and Kdm5d, lead to noncompaction cardiomyopathy in mice, Biochem Biophys Res Commun (2020).\u003c/li\u003e\n \u003cli\u003eA.J. Sadler, B.R. Williams, Interferon-inducible antiviral effectors, Nat Rev Immunol 8(7) (2008) 559-68.\u003c/li\u003e\n \u003cli\u003eJ.P. Barrett, R.J. Henry, K.A. Shirey, S.J. Doran, O.D. Makarevich, R.M. Ritzel, V.A. Meadows, S.N. Vogel, A.I. Faden, B.A. Stoica, D.J. Loane, Interferon-beta Plays a Detrimental Role in Experimental Traumatic Brain Injury by Enhancing Neuroinflammation That Drives Chronic Neurodegeneration, J Neurosci 40(11) (2020) 2357-2370.\u003c/li\u003e\n \u003cli\u003eB.P. Todd, Z. Luo, N. Gilkes, M.S. Chimenti, Z. Peterson, M.R. Mix, J.T. Harty, T. Nickl-Jockschat, P.J. Ferguson, A.G. Bassuk, E.A. Newell, Selective neuroimmune modulation by type I interferon drives neuropathology and neurologic dysfunction following traumatic brain injury, Acta Neuropathol Commun 11(1) (2023) 134.\u003c/li\u003e\n \u003cli\u003eC. Munoz-Ballester, D. Mahmutovic, Y. Rafiqzad, A. Korot, S. Robel, Mild Traumatic Brain Injury-Induced Disruption of the Blood-Brain Barrier Triggers an Atypical Neuronal Response, Front Cell Neurosci 16 (2022) 821885.\u003c/li\u003e\n \u003cli\u003eR.M. Ritzel, Y. Li, Y. Jiao, Z. Lei, S.J. Doran, J. He, R.A. Shahror, R.J. Henry, R. Khan, C. Tan, S. Liu, B.A. Stoica, A.I. Faden, G. Szeto, D.J. Loane, J. Wu, Brain injury accelerates the onset of a reversible age-related microglial phenotype associated with inflammatory neurodegeneration, Sci Adv 9(10) (2023) eadd1101.\u003c/li\u003e\n \u003cli\u003eS.M. O\u0026apos;Neil, E.E. Hans, S. Jiang, L.M. Wangler, J.P. Godbout, Astrocyte immunosenescence and deficits in interleukin 10 signaling in the aged brain disrupt the regulation of microglia following innate immune activation, Glia 70(5) (2022) 913-934.\u003c/li\u003e\n \u003cli\u003eN.S.N. Graham, K.A. Zimmerman, F. Moro, A. Heslegrave, S.A. Maillard, A. Bernini, J.P. Miroz, C.K. Donat, M.Y. Lopez, N. Bourke, A.E. Jolly, E.J. Mallas, E. Soreq, M.H. Wilson, G. Fatania, D. Roi, M.C. Patel, E. Garbero, G. Nattino, C. Baciu, E. Fainardi, A. Chieregato, P. Gradisek, S. Magnoni, M. Oddo, H. Zetterberg, G. Bertolini, D.J. Sharp, Axonal marker neurofilament light predicts long-term outcomes and progressive neurodegeneration after traumatic brain injury, Sci Transl Med 13(613) (2021) eabg9922.\u003c/li\u003e\n \u003cli\u003eE.J. Goodman, R.G. Biltz, J.M. Packer, D.J. DiSabato, S.P. Swanson, B. Oliver, N. Quan, J.F. Sheridan, J.P. Godbout, Enhanced fear memory after social defeat in mice is dependent on interleukin-1 receptor signaling in glutamatergic neurons, Mol Psychiatry (2024).\u003c/li\u003e\n \u003cli\u003eE.J. Goodman, D.J. DiSabato, J.F. Sheridan, J.P. Godbout, Novel microglial transcriptional signatures promote social and cognitive deficits following repeated social defeat, Commun Biol 7(1) (2024) 1199.\u003c/li\u003e\n \u003cli\u003eA. Loda, E. Heard, Xist RNA in action: Past, present, and future, PLoS Genet 15(9) (2019) e1008333.\u003c/li\u003e\n \u003cli\u003eJ. Xu, X. Deng, R. Watkins, C.M. Disteche, Sex-specific differences in expression of histone demethylases Utx and Uty in mouse brain and neurons, J Neurosci 28(17) (2008) 4521-7.\u003c/li\u003e\n \u003cli\u003eH. Shen, A. Yanas, M.C. Owens, C. Zhang, C. Fritsch, C.M. Fare, K.E. Copley, J. Shorter, Y.E. Goldman, K.F. Liu, Sexually dimorphic RNA helicases DDX3X and DDX3Y differentially regulate RNA metabolism through phase separation, Mol Cell 82(14) (2022) 2588-2603 e9.\u003c/li\u003e\n \u003cli\u003eA. Abdullah, M. Zhang, T. Frugier, S. Bedoui, J.M. Taylor, P.J. Crack, STING-mediated type-I interferons contribute to the neuroinflammatory process and detrimental effects following traumatic brain injury, J Neuroinflammation 15(1) (2018) 323.\u003c/li\u003e\n \u003cli\u003eT. Sen, P. Saha, R. Gupta, L.M. Foley, T. Jiang, O.S. Abakumova, T.K. Hitchens, N. Sen, Aberrant ER Stress Induced Neuronal-IFNbeta Elicits White Matter Injury Due to Microglial Activation and T-Cell Infiltration after TBI, J Neurosci 40(2) (2020) 424-446.\u003c/li\u003e\n \u003cli\u003eA.D. Bachstetter, E.T. Ighodaro, Y. Hassoun, D. Aldeiri, J.H. Neltner, E. Patel, E.L. Abner, P.T. Nelson, Rod-shaped microglia morphology is associated with aging in 2 human autopsy series, Neurobiol Aging 52 (2017) 98-105.\u003c/li\u003e\n \u003cli\u003eM. Xie, A.S. Miller, P.N. Pallegar, A. Umpierre, Y. Liang, N. Wang, S. Zhang, N.K. Nagaraj, Z.C. Fogarty, N.B. Ghayal, B. Oskarsson, S. Zhao, J. Zheng, F. Qi, A. Nguyen, D.W. Dickson, L.J. Wu, Rod-shaped microglia interact with neuronal dendrites to regulate cortical excitability in TDP-43 related neurodegeneration, bioRxiv (2024).\u003c/li\u003e\n \u003cli\u003eY. Wang, X. Ning, P. Gao, S. Wu, M. Sha, M. Lv, X. Zhou, J. Gao, R. Fang, G. Meng, X. Su, Z. Jiang, Inflammasome Activation Triggers Caspase-1-Mediated Cleavage of cGAS to Regulate Responses to DNA Virus Infection, Immunity 46(3) (2017) 393-404.\u003c/li\u003e\n \u003cli\u003eX. Liu, T. Yamashita, Q. Chen, N. Belevych, D.B. McKim, A.J. Tarr, V. Coppola, N. Nath, D.P. Nemeth, Z.W. Syed, J.F. Sheridan, J.P. Godbout, J. Zuo, N. Quan, Interleukin 1 type 1 receptor restore: a genetic mouse model for studying interleukin 1 receptor-mediated effects in specific cell types, J Neurosci 35(7) (2015) 2860-70.\u003c/li\u003e\n \u003cli\u003eJ.C. Vincent, C.N. Garnett, J.B. Watson, E.K. Higgins, T. Macheda, L. Sanders, K.N. Roberts, R.K. Shahidehpour, E.M. Blalock, N. Quan, A.D. Bachstetter, IL-1R1 signaling in TBI: assessing chronic impacts and neuroinflammatory dynamics in a mouse model of mild closed-head injury, J Neuroinflammation 20(1) (2023) 248.\u003c/li\u003e\n \u003cli\u003eC.C. Escoubas, L.C. Dorman, P.T. Nguyen, C. Lagares-Linares, H. Nakajo, S.R. Anderson, J.J. Barron, S.D. Wade, B. Cuevas, I.D. Vainchtein, N.J. Silva, R. Guajardo, Y. Xiao, P.V. Lidsky, E.Y. Wang, B.M. Rivera, S.E. Taloma, D.K. Kim, E. Kaminskaya, H. Nakao-Inoue, B. Schwer, T.D. Arnold, A.B. Molofsky, C. Condello, R. Andino, T.J. Nowakowski, A.V. Molofsky, Type-I-interferon-responsive microglia shape cortical development and behavior, Cell 187(8) (2024) 1936-1954 e24.\u003c/li\u003e\n \u003cli\u003eS. Hosseini, K. Michaelsen-Preusse, G. Grigoryan, C. Chhatbar, U. Kalinke, M. Korte, Type I Interferon Receptor Signaling in Astrocytes Regulates Hippocampal Synaptic Plasticity and Cognitive Function of the Healthy CNS, Cell Rep 31(7) (2020) 107666.\u003c/li\u003e\n \u003cli\u003eL. Hashemzadeh-Bonehi, R.G. Phillips, N.J. Cairns, S. Mosaheb, J.R. Thorpe, Pin1 protein associates with neuronal lipofuscin: potential consequences in age-related neurodegeneration, Exp Neurol 199(2) (2006) 328-38.\u003c/li\u003e\n \u003cli\u003eS. Richter, E. Czeiter, K. Amrein, A. Mikolic, J. Verheyden, K. Wang, A.I.R. Maas, E. Steyerberg, A. Buki, D.K. Menon, V.F.J. Newcombe, Prognostic Value of Serum Biomarkers in Patients With Moderate-Severe Traumatic Brain Injury, Differentiated by Marshall Computer Tomography Classification, J Neurotrauma 40(21-22) (2023) 2297-2310.\u003c/li\u003e\n \u003cli\u003eG. Scott, H. Zetterberg, A. Jolly, J.H. Cole, S. De Simoni, P.O. Jenkins, C. Feeney, D.R. Owen, A. Lingford-Hughes, O. Howes, M.C. Patel, A.P. Goldstone, R.N. Gunn, K. Blennow, P.M. Matthews, D.J. Sharp, Minocycline reduces chronic microglial activation after brain trauma but increases neurodegeneration, Brain 141(2) (2018) 459-471.\u003c/li\u003e\n \u003cli\u003eF.H. Brennan, Y. Li, C. Wang, A. Ma, Q. Guo, Y. Li, N. Pukos, W.A. Campbell, K.G. Witcher, Z. Guan, K.A. Kigerl, J.C.E. Hall, J.P. Godbout, A.J. Fischer, D.M. McTigue, Z. He, Q. Ma, P.G. Popovich, Microglia coordinate cellular interactions during spinal cord repair in mice, Nat Commun 13(1) (2022) 4096.\u003c/li\u003e\n \u003cli\u003eK. Tariq, E. Cullen, S.A. Getz, A.K.S. Conching, A.R. Goyette, M.L. Prina, W. Wang, M. Li, M.C. Weston, B.W. Luikart, Disruption of mTORC1 rescues neuronal overgrowth and synapse function dysregulated by Pten loss, Cell Rep 41(5) (2022) 111574.\u003c/li\u003e\n \u003cli\u003eR. Liu, X.Y. Liao, J.C. Tang, M.X. Pan, S.F. Chen, P.X. Lu, L.J. Lu, Z.F. Zhang, Y.Y. Zou, L.H. Bu, X.P. Qin, Q. Wan, BpV(pic) confers neuroprotection by inhibiting M1 microglial polarization and MCP-1 expression in rat traumatic brain injury, Mol Immunol 112 (2019) 30-39.\u003c/li\u003e\n \u003cli\u003eM. Metcalfe, O. Steward, PTEN deletion in spinal pathways via retrograde transduction with AAV-RG enhances forelimb motor recovery after cervical spinal cord injury; Sex differences and late-onset pathophysiologies, Exp Neurol 370 (2023) 114551.\u003c/li\u003e\n \u003cli\u003eS.J. Doran, R.M. Ritzel, E.P. Glaser, R.J. Henry, A.I. Faden, D.J. Loane, Sex Differences in Acute Neuroinflammation after Experimental Traumatic Brain Injury Are Mediated by Infiltrating Myeloid Cells, J Neurotrauma 36(7) (2019) 1040-1053.\u003c/li\u003e\n \u003cli\u003eS. Villapol, D.J. Loane, M.P. Burns, Sexual dimorphism in the inflammatory response to traumatic brain injury, Glia 65(9) (2017) 1423-1438.\u003c/li\u003e\n \u003cli\u003eN.J. Starkey, B. Duffy, K. Jones, A. Theadom, S. Barker-Collo, V. Feigin, B.R. Group, Sex differences in outcomes from mild traumatic brain injury eight years post-injury, PLoS One 17(5) (2022) e0269101.\u003c/li\u003e\n \u003cli\u003eJ. Iannucci, K. O\u0026apos;Neill, X. Wang, S. Mukherjee, J. Wang, L.A. Shapiro, Sex-Specific and Traumatic Brain Injury Effects on Dopamine Receptor Expression in the Hippocampus, Int J Mol Sci 24(22) (2023).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"journal-of-neuroinflammation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jneu","sideBox":"Learn more about [Journal of Neuroinflammation](http://jneuroinflammation.biomedcentral.com)","snPcode":"12974","submissionUrl":"https://submission.nature.com/new-submission/12974/3","title":"Journal of Neuroinflammation","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Microglia, TBI, Inflammation, Cognitive Dysfunction, Stimulator of Interferon Genes, and Interferon Type I","lastPublishedDoi":"10.21203/rs.3.rs-5960640/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5960640/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNeuropsychiatric complications including depression and cognitive impairment develop, persist, and worsen in the years after traumatic brain injury (TBI), negatively affecting life and lifespan. Inflammatory responses mediated by microglia are associated with the transition from acute to chronic neuroinflammation after TBI. Moreover, type I interferon (IFN-I) signaling is a key mediator of inflammation during this transition. Thus, the purpose of this study was to determine the degree to which a microglia-specific knockout of the stimulator of interferons (STING) influenced TBI-induced neuroinflammation, neuronal dysfunction, and cognitive impairment. Here, microglial inducible STING knockout (CX₃CR1Cre/ERT2 x STING\u003csup\u003efl/fl\u003c/sup\u003e) mice were created and validated (mSTING\u003csup\u003e-/-\u003c/sup\u003e). Diffuse brain injury (midline fluid percussion) in male and female mice increased STING expression in microglia, promoted microglial morphological restructuring, and induced robust cortical inflammation and pathology 7 days post injury (dpi). These TBI-associated responses were attenuated in mSTING\u003csup\u003e-/-\u003c/sup\u003e mice. Increased cortical astrogliosis and rod-shaped microglia induced by TBI were independent of mSTING\u003csup\u003e-/-\u003c/sup\u003e. 7 dpi, TBI induced 237 differentially expressed genes (DEG) in the cortex of functionally wildtype (STING\u003csup\u003e+/+\u003c/sup\u003e)\u003csup\u003e \u003c/sup\u003eassociated with STING, NF- κB, and Interferon Alpha signaling and 85% were attenuated by mSTING\u003csup\u003e-/-\u003c/sup\u003e. Components of neuronal injury including reduced NeuN expression, increased cortical lipofuscin, and increased neurofilament light chain in plasma were increased by TBI and dependent on mSTING. TBI-associated cognitive tasks (novel object recognition/location, NOR/NOL) at 7 dpi were dependent on mSTING. Notably, the TBI-induced cognitive deficits in NOR/NOL and increased cortical inflammation 7 dpi were unaffected in global interferon-α/β receptor 1 knockout (IFNAR1) mice. In the final study, the RNA profile of neurons after TBI in STING\u003csup\u003e+/+\u003c/sup\u003e and mSTING\u003csup\u003e-/-\u003c/sup\u003e mice was assessed 7 dpi by single nucleus RNA-sequencing. There was a TBI-dependent suppression of cortical neuronal homeostasis with reductions in CREB signaling, synaptogenesis, and oxytocin signaling and increases in cilium assembly and PTEN signaling. Overall, mSTING\u003csup\u003e-/-\u003c/sup\u003e prevented 50% of TBI-induced DEGs in cortical neurons. Collectively, ablation of STING in microglia attenuates TBI-induced IFN-dependent responses, cortical inflammation, neuronal dysfunction, neuronal pathology, and cognitive impairment.\u003c/p\u003e","manuscriptTitle":"Diffuse Traumatic Brain Injury Induced Stimulator of Interferons (STING) Signaling in Microglia Drives Cortical Neuroinflammation, Neuronal Dysfunction, and Impaired Cognition","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-17 12:27:29","doi":"10.21203/rs.3.rs-5960640/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-08T19:47:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-08T15:31:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-05T23:33:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-05T03:50:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255371765257520870577202567742461950632","date":"2025-02-17T15:43:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"202969282430262982910127381539562602028","date":"2025-02-16T13:02:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"189633798183475171798243725552513947895","date":"2025-02-16T11:05:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"240225407359579706724003006795361225186","date":"2025-02-14T13:00:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"334335120666541668172226535027319794103","date":"2025-02-14T11:06:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-02-14T10:59:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-14T02:11:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-13T09:06:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Neuroinflammation","date":"2025-02-04T19:40:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroinflammation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jneu","sideBox":"Learn more about [Journal of Neuroinflammation](http://jneuroinflammation.biomedcentral.com)","snPcode":"12974","submissionUrl":"https://submission.nature.com/new-submission/12974/3","title":"Journal of Neuroinflammation","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"957cd613-07ba-4511-90e0-ada66e0e013b","owner":[],"postedDate":"February 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-05T16:06:14+00:00","versionOfRecord":{"articleIdentity":"rs-5960640","link":"https://doi.org/10.1186/s12974-025-03451-1","journal":{"identity":"journal-of-neuroinflammation","isVorOnly":false,"title":"Journal of Neuroinflammation"},"publishedOn":"2025-04-30 15:57:42","publishedOnDateReadable":"April 30th, 2025"},"versionCreatedAt":"2025-02-17 12:27:29","video":"","vorDoi":"10.1186/s12974-025-03451-1","vorDoiUrl":"https://doi.org/10.1186/s12974-025-03451-1","workflowStages":[]},"version":"v1","identity":"rs-5960640","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5960640","identity":"rs-5960640","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}