Persistently primed microglia restrict the reactivation of latent cytomegalovirus at the expense of neuronal synaptic connectivity

Persistently primed microglia restrict the reactivation of latent cytomegalovirus at the expense of neuronal synaptic connectivity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Persistently primed microglia restrict the reactivation of latent cytomegalovirus at the expense of neuronal synaptic connectivity Ilija Brizić, Andrea Mihalić, Daria Kveštak, Berislav Lisnić, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5144336/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Microglia are myeloid cells that reside within the central nervous system (CNS), where they maintain homeostasis under normal, non-pathological conditions. In addition, microglia also perform numerous immune functions upon different pathogenic stimuli, including CNS infections with various neurotropic viruses. Herpesviruses establish a lifelong latent infection from which they reactivate intermittently upon waning of immune control. The role of microglia in preventing reactivation of latent herpesviruses remains unclear. In this work, we used congenital cytomegalovirus (CMV) infection as a model to investigate the impact of a persistent virus infection of the brain on microglia. We show that mouse CMV (MCMV) latency in the CNS is associated with permanent microglial priming. The changes induced by persistent infection include continuous, interferon-gamma-dependent microglia activation and extensive transcriptional reprogramming at the single-cell level, leading to the expansion of a microglia subset associated with latent infection. Notably, the maintenance of microglia in a primed state provides enhanced control of latent infection and superior recall response but is associated with excessive loss of synaptic dendritic spines mediated by primed microglia. Altogether, our results indicate that latent CMV infection in the brain causes perturbation of microglial homeostasis, which leads to chronic neuroinflammation that successfully restricts virus reactivation but simultaneously compromises neuronal synaptic connectivity in the brain. Biological sciences/Neuroscience/Neuroimmunology Biological sciences/Neuroscience/Glial biology/Microglia Biological sciences/Immunology/Infection Biological sciences/Immunology/Inflammation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Microglia are resident myeloid cells of the central nervous system (CNS) that originate from the embryonic yolk sac (Saijo and Glass, 2011 ). They comprise 5–10% of all CNS cells and perform a broad range of homeostatic and immune functions (Ransohoff and Perry, 2009 ; Waltl and Kalinke, 2022 ). Microglia are first responders to CNS infections, injury, and neurodegeneration, and while their activation is required to restrict different pathological conditions, they also often contribute to the progression of pathological processes (Ransohoff and Perry, 2009 ). In response to various pathogenic stimuli, microglia shift their activation state toward a proinflammatory phenotype, which includes upregulation of major histocompatibility complex class I (MHC-I) and II (MHC-II), and costimulatory molecules CD80 and CD86 (Prinz et al., 2019 ; Waltl and Kalinke, 2022 ). In addition, microglia produce various proinflammatory and anti-inflammatory cytokines, chemokines and neurotoxic mediators (Lively and Schlichter, 2018 ). The critical role of microglia in containing infection was demonstrated for several DNA and RNA viruses infecting CNS (Chhatbar et al., 2018 ; Katzilieris-Petras et al., 2022 ; Moseman et al., 2020 ; Seitz et al., 2018 ; Tsai et al., 2016 ; Waltl et al., 2018 ). However, despite their indispensability, the exact mechanisms used by microglia to restrain viral CNS infections are still poorly understood. Microglia can migrate to the site of infection, proliferate, and present antigens to T cells to provide control of the virus (Chhatbar et al., 2018 ; Moseman et al., 2020 ). Microglia are the major source of type I interferons (IFN-I), and they prime antiviral defense of astrocytes and neurons during herpes simplex type 1 (HSV-1) infection (Reinert et al., 2016 ). Furthermore, microglia are required for monocyte recruitment during pseudorabies virus (PRV) infection (Fekete et al., 2018 ). Thus, microglia are pivotal in orchestrating the local immune response to acute virus infections in the CNS. Following primary infection, certain viruses, such as herpesviruses, can enter a latent state from which they can reactivate intermittently when immunity wanes due to stress, immunosuppressive therapy, or underlying diseases (Goodrum, 2016 ). The prototypical β-herpesvirus, cytomegalovirus (CMV), infects the brain if the infection occurs in early life and establishes latency in the CNS (Krstanović et al., 2021 ; Mihalić et al., 2024 ; Ribalta et al., 2002 ). Congenital human CMV (cCMV) infection is the most common viral congenital infection, with approximately 0.5% of human infants born with HCMV infection, and frequently resulting in long-term neurological sequelae (Boppana et al., 2013 ). Since there are no effective therapies that mitigate the persistent neurodevelopmental complications associated with cCMV, there is an unmet need to identify targets for therapeutic intervention and/or prophylaxis. Using a well-established cCMV mouse model, we have previously demonstrated that CD8 and CD4 T cells prevent CMV reactivation by controlling the latent virus in the brain (Brizić et al., 2018b , 2019 ), while the contribution of microglia remained unexplored. In this study, we investigated microglia's role in controlling the latent mouse CMV (MCMV) infection in the brain. We show that during MCMV latency, microglia are continuously primed, as demonstrated by their persistent activation, extensive transcriptional reprogramming at the single-cell level, and upregulation of MHC-II. Lifelong microglial MHC-II upregulation was mediated by interferon-gamma (IFN-γ) locally produced by the tissue-resident memory (T RM ) T cells. Importantly, primed microglia enhanced MCMV control, demonstrating the critical role in the surveillance of latent and reactivating virus. However, concomitantly with improved control of the latent virus, primed microglia caused a reduction in neuronal dendritic spine density in the hippocampus, which suggests that the priming of microglia that leads to enhanced control of the latent virus infection comes at the cost of reduced synaptic connectivity of neurons. Thus, our study describes a novel pathological mechanism associated with the latent infection and mediated by microglia. Results MHC-II expression is a hallmark of microglial activation during acute CMV infection in brain Perinatal MCMV infection results in brain infection and subsequent inflammatory response, characterized by infiltration of leukocytes and activation of resident microglia at the site of infection (Bantug et al., 2008 ; Kosmac et al., 2013 ; Kveštak et al., 2021 ). We have previously shown that activated microglia upregulate MHC-I, MHC-II, and the costimulatory molecules CD80 and CD86 (Kveštak et al., 2021 ). To extend these findings, we infected newborn C57BL/6 (Fig. 1 A, 1 C, Suppl. Figure 1A ) and BALB/c (Fig. 1 B, 1 D, Suppl. Figure 1B ) wild-type (WT) mice intraperitoneally (i.p.) with MCMV and harvested brains when MCMV replication peaks in the brain (13 days post-infection, 13 dpi) (Brizić et al., 2018b ; Kveštak et al., 2021 ). The prototypic microglia marker ionized calcium-binding adaptor protein 1 (IBA-1), and MHC-II expression colocalized upon MCMV infection in both strains of mice, indicating that microglia express MHC-II in the brain (Fig. 1 A, B). Expression of MHC-II on microglia in C57BL/6 (Fig. 1 C) and BALB/c (Fig. 1 D) mice was confirmed by flow cytometry. Similarly, MHC-I expression on microglia was also increased in both mouse strains following infection ( Suppl. Figure 1A, B ). To compare our findings in the mouse model to congenital HCMV infection, we analyzed the expression of human MHC-II (HLA-DR) on IBA-1 + cells in cadaveric brain tissues of two cases of cCMV infection. Analogously to congenitally MCMV-infected mice, human microglia expressed MHC-II in HCMV-infected brains (Fig. 1 E). We have previously shown that IFN-γ is required for early microglial activation during the acute phase of perinatal MCMV infection (Kveštak et al., 2021 ). To determine the requirements for HLA-DR upregulation upon HCMV infection of the fetal brain, we have used the recently developed human fetal organotypic brain slice culture (hfOBSC) platform (Rashidi et al., 2024 ). Whereas HCMV infection alone did not result in HLA-DR expression in hfOBSCs (Fig. 1 F), IFN-γ treatment of infected hfOBSCs induced HLA-DR expression on microglia (Fig. 1 F), similar to microglia in MCMV-infected newborn mice (Kveštak et al., 2021 ). Thus, in both humans and mice, cytomegalovirus infection in the brain results in microglia activation in an IFN-γ-dependent manner. MCMV infection of the CNS causes persistent activation of microglia Productive MCMV infection in the brain is resolved by weeks 3 to 4 post-infection, but MCMV DNA remains detectable in these brains for > 3 months, suggesting the establishment of MCMV latency (Brizić et al., 2018a , 2018b ; Koontz et al., 2008 ). We detected MCMV genomes in the brains of MCMV-infected C57BL/6 and BALB/c mice at 3 months post-infection (mpi), a time corresponding to the latency (Fig. 2 A). Moreover, we could not detect viral transcription from any known locus of MCMV in brain homogenates during the latent phase of infection ( Suppl. Figure 2 ), suggesting that the virus established true latency. Next, we performed immune response profiling by analyzing the protein expression of 48 cytokine, chemokine, and growth factor targets in mouse brains. Almost all proteins analyzed were equally or similarly expressed in control and latently MCMV-infected brains ( Suppl. Figure 3 ). However, we detected increased levels of chemokines MCP-1, RANTES, MCP-3, IP-10, and B-cell-activating factor (BAFF) in the brains of latently MCMV-infected mice (Fig. 2 B). Since these cytokines are associated with inflammatory response, we next characterized microglia following the resolution of productive infection in BALB/c mice. The number of microglia was increased in MCMV-infected mice at all time points analyzed (Fig. 2 C). Furthermore, microglia in infected mice expressed relatively higher levels of MHC-I and -II at all time points analyzed, even at 6 mpi (Fig. 2 D, E). MHC-II expression remained restricted to IBA-1 + microglia in the latent phase of MCMV infection, as shown by confocal microscopy (Fig. 2 F). To determine if there are differences in microglia activation between different brain regions, we isolated microglia from the hippocampus, cortex, and cerebellum at 4 mpi and analyzed the expression of MHC-I and -II (Fig. 2 G, H). Compared to cortex and cerebellum, hippocampal microglia expressed the highest MHC-I and -II levels. Notably, the hippocampus also had the relatively highest viral load (Brizić et al., 2024 ), suggesting that MCMV latency shapes the microglial activation status. Next, we analyzed the density and morphology of microglia in the hippocampal CA1 region, which is important for learning and memory-dependent processes and is known to be more susceptible to inflammation during early development (Gomez et al., 2019 ; Korte and Schmitz, 2016 ). Microglia in latently MCMV-infected mice showed increased density (Fig. 2 I), and activated morphology with an increased volume of the whole cell and soma (Fig. 2 J, K). Furthermore, microglial activation has been shown to represent a continuum between ramified activated and amoeboid forms (Ladeby et al., 2005 ). To further assess the microglial morphological changes, the total length and branch points of microglial filaments were examined in both groups. Remarkably, the microglial cells in the latently infected mice exhibited a higher total filament length and a higher number of branching points, indicating a hyper-ramified profile of activated microglial cells (Fig. 2 J, K). Next, we analyzed MHC-I and -II expression on macrophages in the brain, spleen, and liver to determine if MCMV latency shapes the activation state of other tissue-resident macrophages. Notably, splenic red pulp macrophages (F4/80 + CD11b − ) (Fig. 2 L), liver Kupffer cells (F4/80 + CD11b + ) (Fig. 2 M), but also CNS-associated macrophages (CD45.2 hi CD11b + ) (Fig. 2 N), did not have significantly increased MHC-I and -II expression in latently MCMV-infected mice. Altogether, these data demonstrate that microglia are selectively and persistently activated in latently MCMV-infected brains. Latent MCMV infection causes persistent transcriptional alteration of microglia Increased expression of MHC-I and -II on microglia in latently infected brains was still observed at 16 mpi (Fig. 3 A). Since microglia were persistently activated following perinatal MCMV infection, we sorted microglia from MCMV- and mock-infected mice 16 mpi and performed RNA-seq analysis (Fig. 3 B). To elucidate transcriptional differences of microglia between acute and latent infection, we also reanalyzed our previous RNA-seq data of microglia obtained 8 dpi (Kveštak et al., 2021 ). Individual samples from the same experimental groups clustered closely together in the PCA plot, indicating low inter-sample variability (Fig. 3 C). In accordance with previous analysis, acute MCMV infection in the brain strongly reshaped the microglial transcriptome (Fig. 3 C). Microglia from latently MCMV-infected brains were also transcriptionally different when compared to microglia from uninfected mice, even though this difference was smaller than that observed between microglia from acutely infected mice and uninfected mice (Fig. 3 C). The gene ontology over-representation analysis (GO-ORA) showed that microglia from latently infected mice display the transcriptional signature of elevated antiviral response (Fig. 3 D). Gene ontology biological process categories associated with antigen processing and presentation, negative regulation of viral process and interferon − mediated signaling pathway were enriched in microglia of latently infected mice (Fig. 3 D). By comparing the list of differentially expressed (DE) genes in acute and latent infection, we identified 1613 DE genes unique to microglia from the acutely infected brain, 137 DE genes unique to microglia from latently infected brain, and 248 genes that were DE in both microglia from both acute and latently infected brains (Fig. 3 E). Importantly, most of these 248 shared DE genes were associated with antiviral response, including antigen processing and presentation, interferon type I (IFN-I) and type II (IFN-II) pathways, and inflammatory response (Fig. 3 F). Taken together, these data demonstrate the maintenance of a persistent antiviral state of microglia in brains of latently MCMV-infected mice. Differential regulation of microglial and astrocyte transcriptomes at the single cell level in latently MCMV-infected CNS Next, we used the single-cell RNA sequencing (scRNA-seq) approach to decipher the impact of latent MCMV infection on the microglial transcriptome at the individual cell level. For these experiments, newborn C57BL/6 mice were i.p. infected with MCMV and microglia were sorted for scRNA-seq ( Suppl. Figure 4A ). Following data pre-processing and dataset integration, a total of four distinct microglia clusters were detected using the selected clustering resolution (Fig. 4 A), all of which exhibited strong expression of canonical microglia marker genes, such as C1qa , Fcrls , Hexb , P2ry12 , and others ( Suppl. Figure 4C ) (Hammond et al., 2019 ). Interestingly, latent MCMV infection caused a noticeable redistribution of a subset of microglia cells from clusters 0 and 1 into cluster 2 (Figs. 4 A and 4 B), which suggests that latent MCMV infection transcriptionally reprograms a subset of microglia. In addition to the prominent increase in the proportion of cells in microglial cluster 2 in response to latent MCMV infection, various proportions of cells in that cluster were also characterized by a relatively high expression of genes encoding MHC molecules (e.g. B2m , H2-Aa, Cd74 ) and their transcriptional activators (e.g. Ciita , Nlrc5 ), genes involved in type I interferon (IFN-I) and type II interferon (IFN-II) signaling (i.e. Stat1 , Irf1, Irf7, Irf9, Ifit2, Ifit3, Iigp1 ), and genes encoding pro-inflammatory chemokines ( Cxcl9, Cxcl10, Ccl5 ) (Fig. 4 C), in accordance with bulk RNA-seq analysis (Fig. 3 .). Notably, a distinct microglia subset did not display any apparent changes in the expression of these infection or inflammation-associated genes, suggesting that latent MCMV infection shapes microglia towards an activated and proinflammatory phenotype; however, not in all microglial cells in brains of latently MCMV-infected mice. Astrocytes are another type of brain-resident glial cells that can undergo activation and modulate immune responses in different brain diseases (Colombo and Farina, 2016 ; Giovannoni and Quintana, 2020 ). To investigate whether the latent MCMV infection affects astrocytes to the same or similar extent as it affects microglia, we performed scRNA-seq analysis of astrocytes, which were sorted as CD45.2 − CD11b − O1 − ACSA-2 + cells by flow cytometry ( Suppl. Figure 4B ). Four astrocyte clusters were identified in brains of mock- and MCMV-infected mice (Fig. 4 D), and analyzed cells expressed canonical astrocyte markers Slc1a2 , Slc1a3 , Atp1b2 , Sox9 , Glul and Apoe ( Suppl. Figure 4D ) (Batiuk et al., 2020 ). In contrast to microglia, no pronounced changes in the number of cells within individual astrocyte clusters were detected (Fig. 4 D, E). Furthermore, we did not detect a substantial increase in the expression of proinflammatory genes within any astrocyte subpopulation (Fig. 4 F). These results demonstrate that while microglia are transcriptionally reprogrammed at the single-cell level to exert proinflammatory state, astrocytes exhibit homeostatic features in latently MCMV-infected brain. Antiviral interventions limit microglial activation Having shown that MCMV can trigger the establishment of a proinflammatory microglia population in the brain, we next investigated if available interventions can mitigate these changes. Antivirals, such as ganciclovir (GCV), are commonly used to control HCMV infection in humans (D and Rc, 1990 ). In mice, passive immunization protects against MCMV infection in the brain by decreasing both the viral burden and virus-induced pathology (Cekinović et al., 2008 ). To test if antiviral treatment can reduce microglial activation upon MCMV infection, we i.p. infected newborn BALB/c mice and subsequently treated them with either GCV or MCMV immune sera. Mice were treated with immune sera on 1 and 7 dpi, and GCV was administered daily until 14 dpi (Fig. 5 A). Both approaches reduced the upregulation of microglial MHC-I and -II expression (Fig. 5 B), and reduced viral load in the brain (Fig. 5 C). Moreover, the antiviral treatment attenuated microglial MHC-I and -II expression long-term (Fig. 5 D, E), as well as reduced latent viral load in the brain for as long as 90 dpi ( Fig. 5 F ) . Next, we analyzed how anti-viral treatment impacts neuroinflammation if we postpone it for 5 days, the time when MCMV has already reached the brain (Fig. 5 G). Anti-viral treatment initiated at 5 dpi only reduced MHC-II upregulation, but had no effect on MHC-I expression nor the viral load in treated mice (Fig. 5 H-I). Finally, we assessed if antiviral therapy could mitigate neuroinflammation during MCMV latency. To that aim, BALB/c mice infected with MCMV as newborns were treated with GCV starting 2 mpi (Fig. 5 J). One month of antiviral treatment did not affect microglial MHC-I and -II expression (Fig. 5 K) nor latent viral loads in the brain (Fig. 5 L). These data indicate that timely inhibition of virus replication reduces microglial activation, while antiviral treatment during the latent phase of MCMV infection does not affect microglial activation. Continuous IFN-γ signaling maintains microglial MHC-II expression We have previously shown that IFN-γ is critical for early microglial MHC-II upregulation following MCMV infection in the brain (Kveštak et al., 2021 ), and in HCMV-infected human brain organotypic cultures (Fig. 1 F). To assess if IFN-γ is required for long-term microglial MHC-II expression during MCMV latency, we i.p. infected newborn IFN-γ receptor-deficient ( Ifngr1 −/− ) mice, and control WT mice, and subsequently analyzed microglial MHC-II expression. Increased microglial MHC-II expression was not observed in Ifngr1 −/− infected mice 3 mpi (Fig. 6 A). In contrast, IFN-γ signaling was only partially required for increased MHC-I expression in Ifngr1 −/− mice, as the increase in MHC-I expression on microglia was lower than in WT mice (Fig. 6 A). We next investigated whether continuous IFN-γ receptor signaling is required to maintain MHC-II expression on microglia. We first generated an inducible conditional knockout mouse strain ( Sall1 CreERT2 Ifngr1 fl/fl ), in which the IFN-γ receptor (IFNGR) expression in microglia can be eliminated upon tamoxifen treatment. We infected newborn Sall1 CreERT2 Ifngr1 fl/fl mice and administered tamoxifen 3 mpi (Fig. 6 B). Tamoxifen treatment efficiently decreased IFNGR expression (Fig. 6 C), accompanied by loss of MHC-II (Fig. 6 D) and decrease in MHC-I (Fig. 6 E) expression on microglia in Sall1 CreERT2 Ifngr1 fl/fl mice, which was not observed in control and non-treated Sall1 CreERT2 Ifngr1 fl/fl and Ifngr1 fl/fl mice ( Suppl. Figure 5A, B ). These results demonstrate that IFN-γ is required continuously to maintain an activated microglial state during latent MCMV infection. Tissue-resident CD8 T cells are the major source of IFN-γ in latently MCMV-infected brains Since our results indicated that continuous IFN-γ receptor signaling in microglia was required to maintain microglia in an activated state, we next determined the cellular source of IFN-γ. IFN-γ could be produced by lymphocytes in the brain parenchyma or the periphery, reaching the brain by blood (Ivashkiv, 2018 ). To differentiate between both options, we first assessed if systemic IFN-γ causes microglial activation. To test this possibility, we neutralized IFN-γ for two weeks in latently MCMV-infected mice by i.p. administration of a neutralizing IFN-γ antibody ( Fig. 6 F ) . As control of peripheral IFN-γ neutralization, we infected adult C57BL/6 mice with MCMV and neutralized IFN-γ during acute infection (Suppl. Figure 5C) . In contrast to control mice, MHC-II was not upregulated on peritoneal macrophages in mice treated with IFN-γ neutralizing antibody ( Suppl. Figure 5C ), indicating successful neutralization of IFN-γ. However, MHC-II expression levels on microglia were unaffected by IFN-γ neutralization (Fig. 6 F), indicating that local but not systemic IFN-γ production is required for the maintenance of microglial MHC-II expression. Even though we did not detect IFN-γ protein in brain homogenates of latently MCMV-infected mice ( Suppl. Figure 5D ), we detected increased numbers of IFN-γ transcripts (Fig. 6 G). We have previously demonstrated that NK cells are the main producers of IFN-γ during acute MCMV infection in the brain, mediating microglial MHC-II expression (Kveštak et al., 2021 ). To determine which cell type is a major source of IFN-γ during latency, we stimulated mononuclear cells isolated from latently MCMV-infected brains. CD8 T cells were the main producers of IFN-γ, while other cell types accounted for minimal IFN-γ production in latently infected brains (Fig. 6 H, I). In accordance with the data obtained by neutralizing peripheral IFN-γ, most IFN-γ + CD8 T cells were T RM cells, expressing CD69, or co-expressing both canonical T RM cell markers CD69 and CD103 (Fig. 6 J) (Mueller and Mackay, 2016 ). Since we observed the highest microglial activation in the hippocampus, we assessed the numbers of CD8 T cells in different brain regions. The highest numbers of total CD8 T cells were detected in the hippocampus ( Suppl. Figure 5E ). Similarly, virus-specific CD8 T cells, as assessed by analyzing M38-tetramer positive cells, were the most numerous in hippocampus and displayed T RM phenotype (Fig. 6 K, Suppl. Figure 5F ). Overall, these data suggest that virus-specific CD8 T RM cells are major producers of IFN-γ during MCMV latency in the brain. Persistently activated microglia enhance control of latent virus Having established that long-term microglia activation is a hallmark of latent CMV infection, we hypothesized that such microglia have enhanced functionality, corresponding to the emerging concepts of innate immune cells adaptation to different pathological conditions (Divangahi et al., 2021 ). To determine the role of activated microglia during MCMV latency in the brain, we used PLX5622, a colony-stimulating factor 1 receptor (CSF1R) inhibitor, to deplete microglia (Xu et al., 2020 ). C57BL/6 mice were infected as newborns, and after the establishment of latency, mice were fed with a PLX5622-formulated diet (further referred to as PLX-diet) or a control diet (Fig. 7 A). Microglial numbers were strongly reduced in mice fed with the PLX-diet for 2 weeks (Fig. 7 B). Notably, PLX-mediated depletion of microglia resulted in MCMV reactivation in the brain (Fig. 7 C), demonstrating the importance of microglia in preventing MCMV reactivation. To further evaluate the role of persistently activated microglia in virus control, we have performed an intracranial challenge with MCMV in latently infected and control mock-infected mice (Fig. 7 D). In control mice, microglia depletion did not significantly affect virus titers upon intracranial challenge (Fig. 7 E). In sharp contrast, microglial depletion had a major role in controlling productive MCMV infection upon intracranial challenge of latently infected mice (Fig. 7 E), resulting in ~ 100-fold increase in virus titer when compared to the non-depleted group of mice. Altogether, these data indicate that activated microglia have an important role in controlling both productive as well as preventing reactivation of latent MCMV in the brain. Microglia compromise synaptic connectivity of neurons in the hippocampus during latent infection As the resident macrophages in the brain, microglia can remove pathogens, cell debris, but also synaptic connections between neurons under pathological conditions (Boche et al., 2013 ; Demuth et al., 2023 ). The next step was, therefore, to analyze whether microglia engulf and digest synaptic terminals, followed by degradation in lysosomes (Demuth et al., 2023 ). Since the total volume of lysosomes in microglia is proportional to their phagocytic activity (Demuth et al., 2023 ), we first investigated the volumetric changes of microglial lysosomes in infected mice compared to control mice. We detected increased lysosome volume labeled with lysosome-associated membrane protein-1 (LAMP-1) in microglia in the CA1 subregion of the hippocampus (Fig. 7 F, G). Next, we analyzed Homer-1, a synaptic scaffolding protein in postsynaptic terminals that regulates glutamatergic synapses and spine morphogenesis (Tao-Cheng et al., 2014 ), in microglia in all experimental groups. We detected an increased number of Homer-1 puncta in lysosomes in microglia from latently infected mice, demonstrating that activated microglia excessively phagocytose excitatory postsynaptic terminals of hippocampal neurons during MCMV latency (Fig. 7 G). To investigate whether the increased phagocytosis of postsynaptic terminals of excitatory neurons is reflected in the reduced synaptic connections, we evaluated the dendritic spine density as a morphological indicator of the hippocampal neurons. Spines are dendritic protrusions that carry the majority of excitatory synapses in the hippocampus, and changes in spine density can provide information about changes in the connectivity of hippocampal neurons (Demuth et al., 2023 ; Gabele et al., 2024 ; Hosseini et al., 2018 ). Spines were counted on the apical dendrites of CA1 pyramidal neurons. Notably, the density of spines was reduced in the apical dendrites of CA1 neurons of latently infected mice (Fig. 7 H). Intriguingly, the depletion of microglia during latency restored the numbers of dendritic spines to the levels observed in control uninfected mice (Fig. 7 H), demonstrating that activated microglia associated with latent CMV infection are the cause of dendritic spine loss on the neurons. These data indicate that persistent microglial activation compromises synaptic connectivity in the hippocampus. Discussion Viral infections in the CNS initiate inflammatory processes that restrict viral replication (Waltl and Kalinke, 2022 ). Microglia have a key role in antiviral immunity by orchestrating intracerebral innate and adaptive immune responses to different viruses, such as arboviruses and neurotropic influenza A viruses (IAVs) (Garber et al., 2019 ; Hosseini et al., 2018 ). However, the role of microglia in the surveillance and control of persistent virus infections has not been well studied. Here, we show that latent virus infection shapes microglia, a process critical to preventing virus reactivation. However, enhanced viral control comes at a cost, as persistent microglial activation reduces synaptic connectivity. Cytomegalovirus is a highly prevalent β-herpesvirus infecting most of the world’s population (Fowler et al., 2022 ; Mussi-Pinhata et al., 2009 ). Congenital HCMV infection is the most common congenital infection (Manicklal et al., 2013 ; Mussi-Pinhata et al., 2009 ), which can cause acute and chronic neurodevelopmental disorders, intellectual disabilities, and sensorineural hearing loss (Adle-Biassette and Teissier, 2020 ). Following the resolution of productive infection, CMV remains latent for the lifetime in the host (Goodrum, 2016 ). However, the latent phase of HCMV infection in the human brain and its consequences remain unexplored. Microglia are infected with HCMV during congenital infection and with MCMV upon infection of neonatal mice (Kveštak et al., 2021 ; Teissier et al., 2014 ). Here, by using postmortem brain tissues of human fetuses infected with HCMV, we show that microglia are activated and express MHC-II during congenital HCMV infection. Furthermore, by using hfOBSCs we demonstrated that IFN-γ is required for microglial activation in human brain slices upon experimental HCMV infection, as is the case with MCMV infection of mouse brain (Kveštak et al., 2021 ). Thus, we have established that the mouse model of congenital CMV infection shares crucial elements with cCMV and is thus an excellent small animal model for investigating this important human congenital infection. Upon establishment of latency in the CNS, brain immune homeostasis is permanently reshaped, as CMV-specific T RM cells, usually not present in the brains, are retained in the tissue (Brizić et al., 2018c; Mihalić et al., 2024 ). Here, we show that microglia, brain-resident cells, remain activated after the resolution of productive MCMV infection in the brain throughout the life of the congenitally infected host. Interestingly, we showed that this long-term activation is a feature characteristic of microglia and not macrophages in other tissues during the latent phase of MCMV infection. The explanation for these differences remains unclear. However, brain parenchyma is an immune-privileged site, less exposed to environmental factors and consequent low-level inflammation (Louveau et al., 2015 ). Indeed, while other macrophages typically constitutively express specific levels of MHC molecules (Reith et al., 2005 ), microglia do not. Thus, MCMV colonization of the brain could increase the basal activation level of microglia, which is set by exposure to environmental factors in other tissue macrophages. Recent studies have demonstrated that innate immune cells can adapt to different pathological conditions, which can be associated with enhanced responsiveness to secondary stimuli (Divangahi et al., 2021 ; Netea et al., 2020 ). Enhanced responsiveness can be secured by primed and trained innate immune cells. The trained immunity is considered to be due to epigenetic changes, with transcriptional and activation status restored to homeostatic levels (Divangahi et al., 2021 ), while priming is considered to result in transcriptional reprogramming and enhanced activation status (Divangahi et al., 2021 ). Here, we have demonstrated that microglia primed by latent infection enhance control of latent and reactivating MCMV. We did not observe a significant contribution of microglia in control mice that were challenged i.c. with MCMV but were not infected as newborns. This is in sharp contrast to infection with several other viruses where microglia contribute to virus control (Waltl and Kalinke, 2022 ). One possible explanation is the timing of analysis, as we have analyzed virus control 3 dpi. Most of the previous studies analyzed virus titers at later time points of infection, allowing for the generation of T cell responses, which microglia supported and were shown to be crucial in restricting viral infections (Waltl and Kalinke, 2022 ). In the case of HSV-1, microglia enhanced virus control as early as 2 dpi by producing IFN-I in a STING-dependent manner (Reinert et al., 2016 ). MCMV has been shown to evade STING activation (Stempel et al., 2019 ), thus potentially explaining microglia's lack of significant contribution to virus control in previously uninfected mice. The immune responses mediated by microglia can also be pathological (Miron and Priller, 2020 ; Waltl and Kalinke, 2022 ). Here, we have demonstrated that enhanced responsiveness to MCMV comes at the cost of reduced synaptic connectivity. Depletion of microglia abolishes the impact on reduced synaptic connectivity, implying that the consequences of latent infection are reversible. Microglial hyper-ramification is observed during MCMV latency and has previously been related to acute and chronic stress response and might be implicated in synaptic modifications (Vidal-Itriago et al., 2022 ). Excessive synaptic pruning has been shown in a model of lymphocytic choriomeningitis virus (LCMV) infection, where IFN-γ produced by CD8 + T cells acts on neurons, resulting in phagocyte recruitment that mediates synapse loss (Di Liberto et al., 2018 ). Furthermore, complement mediates synapse loss upon West Nile virus infection (Vasek et al., 2016 ), with IFN-γ acting on microglia being critical in this process (Garber et al., 2019 ). We have recently shown that MCMV establishes latent infection in neurons, and not microglia and astrocytes (Brizić et al., 2024 ). Thus, it could be speculated that during latent MCMV infection, IFN-γ probably acts on microglia or neurons, mediating synapse loss. Microglia can mediate pathological synapse loss in different pathological conditions, as shown in a model of Parkinson's disease (Zhang et al., 2021 ), multiple sclerosis (Beckmann et al., 2018 ; Wies Mancini et al., 2022 ), traumatic brain injury model, (Henry et al., 2020 ; Witcher et al., 2021 ), cerebral ischemic stroke (Du et al., 2020 ), and age-associated neuroinflammation (Stojiljkovic et al., 2022 ). Whether the presence of CMV in such conditions could enhance the disease progression remains to be determined. Using RNAseq analysis, we have identified a set of proinflammatory genes induced in microglia adapted to latent infection, most notably associated with type I and II interferon responses. Recent studies investigating the transcriptional profile of microglia in neuroinflammation, neurodegenerative conditions and aging detected similar activated microglia signatures (Ajami et al., 2018 ; Escoubas et al., 2023 ; Frigerio et al., 2019 ). Moreover, IFN-γ-responsive microglia were induced during aging and localized near CD8 T cells in white matter, resulting in oligodendrocyte loss (Kaya et al., 2022 ). Using single-cell RNA-seq analysis of microglia, we have demonstrated a subset of microglia associated with MCMV latency. The principal characteristic of this population was increased expression of MHC molecules and numerous antiviral factors, such as interferon-stimulated genes. Many genes that were upregulated during the latent phase of infection were similarly regulated during the acute phase, suggesting the central role of microglia in virus control. High levels of several proinflammatory chemokines and cytokines (MCP-1, RANTES and IP-10) were detected in latently infected brains. Transcripts for these and other chemokines were increased in microglia but not in the astrocytes during latency, suggesting that microglia are the major source of these chemokines in the brain. Many of these chemokines are important for the recruitment of T and NK cells to the brain upon viral infections (Hosking and Lane, 2010 ; Kveštak et al., 2021 ; Thapa et al., 2008 ; Trifilo et al., 2004 ). Thus, microglia-derived chemokines and cytokines probably orchestrate T RM cells in the brain during latency. Astrocytes are also infected and activated during acute CMV infection (Brizić et al., 2022 ). However, unlike microglia, which were persistently activated, we did not detect reactive astrocytes by single-cell sequencing, as observed in other CNS diseases (Liddelow et al., 2017 ), suggesting that there is a fine regulation of inflammatory response during latent CMV infection in the brain. Indeed, we did not detect increased transcripts coding for IL-1α, TNF-α, and C1q in microglia, all of the three being required for the induction of reactive astrocytes (Liddelow et al., 2017 ). While a comprehensive description of the mechanism that maintains microglia in an activated state remains elusive, we have demonstrated that persistent upregulation of microglial MHC-II depends on continuous IFN-γ receptor signaling in microglia. Virus-specific CD4 and CD8 T cells can produce IFN-γ in the brain in a mouse model of congenital CMV infection (Brizić et al., 2019 ). We show that IFN-γ is mainly produced by virus-specific CD8 T RM cells. A recent study suggested that IFN-γ epigenetically reprograms microglia following early immune activation (Schwabenland et al., 2023 ). Cooperation between both mechanisms may be needed to secure persistent activation. Besides IFN-γ, IFN-I is probably required for microglial activation, as suggested by our RNAsq analysis. Among congenitally HCMV-infected infants with clinically apparent symptoms, the majority will have neurological sequelae. However, even infants with asymptomatic cCMV infection can present long-term CNS manifestations later in life (Brizić et al., 2018a ; Cheeran et al., 2009 ). Antivirals, such as acyclovir (ACV) and GCV, are used in clinics to control HCMV and other herpesviral infections (D and Rc, 1990 ). In a mouse model of congenital CMV infection, MCMV-specific antibodies limit inflammation and viral replication in the brains of newborn mice (Cekinović et al., 2008 ). Furthermore, treatment of newborn mice with IFN-γ or TNF-α neutralizing antibodies (Kveštak et al., 2021 ; Seleme et al., 2017 ) or glucocorticoids (Kosmac et al., 2013 ) reduced inflammation and brain pathology without affecting viral replication. Similarly, we showed here that the anti-viral treatment with GCV effectively reduced neuroinflammation and virus load in the brain if treatment was done during the acute phase of infection. In addition, the beneficial effect of early anti-viral treatment on microglial activation and viral load was maintained even during latency. However, if antiviral treatment started during latency, microglial activation and viral loads were not changed. This finding underscores the importance of early-life testing for cCMV and timely treatment with readily available drugs. To this day, there is no approved HCMV vaccine, the use of antiviral therapies is limited by toxicity, and interventional therapies cannot entirely prevent adverse outcomes of HCMV-associated diseases like cCMV. The development of more efficient therapies requires better insight into the virus and host factors and cell types involved in the protection versus pathogenesis of viral diseases. Here, we showed that latent CMV infection in the brain primes microglia, which in turn enhances surveillance of the chronic infection. Still, at the same time, activated microglia mediate pathological damage in the CNS. Interestingly, the reduced synaptic connectivity caused by persistent microglial activation is reversible by microglia depletion, opening new therapeutic options. On average, 0.5% of human infants are estimated to be born with HCMV (Kenneson and Cannon, 2007 ; Mussi-Pinhata et al., 2009 ). However, the extent of the population carrying latent HCMV in the CNS is not known, but it seems that HCMV DNA is present at a much higher frequency in human brains, as would be expected based on the prevalence of congenital HCMV infection (Ribalta et al., 2002 ). Furthermore, a recent study reported activated microglia in postmortem samples of human brains with CMV-positivity (Zheng et al., 2023 ). However, the consequences of latent CMV infection in the brain and whether CMV and microglia could be important targets in improving brain health remain to be determined. Materials and methods Mice Mice were strictly age-matched within experiments and handled in accordance with institutional and national guidelines. All mice were housed and bred under specific pathogen–free conditions at the animal facility of the Faculty of Medicine, University of Rijeka where they were maintained at 22°C in a 12-h light–dark cycle, and relative humidity (40–50%). C57BL/6J (strain #:000664), BALB/c (00651), 129/SvJ (000691), Ifngr1 −/− (003288), Ifng −/− (002287) and Ifngr1 fl/fl (IFN-γR1 floxed; 025394) mice were obtained from The Jackson Laboratory. Sall1Cre ERT2 mice were provided by Riuchi Nishinakamura (Inoue et al., 2010 ; Kanda et al., 2014 ), at Kumamoto University. All animal experiments were approved by The Animal Welfare Committee at the University of Rijeka, Faculty of Medicine and The National Ethics Committee for the Protection of Animals Used for Scientific Purposes (Ministry of Agriculture (UP/I-322-01/17 − 01/101, UP/I-322-01/19 − 01/25, UP/I-322-01/21 − 01/51, UP/I-322-01/23 − 01/33)). Viruses Tissue culture-derived MCMV reconstituted from BAC pSM3fr-MCK-2fl (WT) was used in all experiments (Jordan et al., 2011 ). Virus stocks were kept at − 80°C. Viral titers were determined by plaque assay on murine embryonic fibroblasts (MEFs) and expressed as plaque-forming units (PFUs) (Brizić et al., 2022 ). Newborn BALB/c mice were infected intraperitoneally (i.p.) with 400 PFU of MCMV (6–18 hours post birth), while other mouse strains were i.p. infected with 200 PFU of MCMV (24–48 hours post birth). Adult, 5-month-old mice were infected i.p. with 2 × 10 5 PFU of MCMV. For HCMV infection experiments RV-TB40-BAC KL7 -SE-EGFP (KL7-EGFP) virus was used, a kind gift from Christian Sinzger (Sampaio et al., 2017 ). Antibodies and flow cytometry Single-cell leukocyte suspensions were prepared using previously published methods (Bantug et al., 2008 ). In brief, the suspension of 30% Percoll (#GE17-0891-09, Cytivia) and brain homogenate was overlaid on 70% Percoll in PBS and then centrifuged at 1,800 rpm for 25 min. Cells in the interphase were collected. Adult Brain Dissociation Kit (#130-107-677, Miltenyi Biotec) was used to isolate astrocytes from the brain. After tissue dissociation and red blood cell removal, myelin was removed using magnetic beads (#130-096-433, Myelin Removal Beads, Miltenyi Biotec). Before staining lymphocytes, Fc receptors were blocked using anti-mouse CD16/CD32 monoclonal antibody (clone 93) #14-0161-82 (dilution 1:50), Thermo Fisher). The following anti-mouse antibodies purchased from Thermo Fisher were used: anti-mouse CD45.2 (clone 104) FITC # 11-0454-82 and Alexa Fluor 700 # 56-0454-82 (dilution 1:100), anti-mouse CD11b (clone M1/70) PE-Cyanine7 # 25-0112-82 (dilution 1:400), anti-mouse MHC class II (I-A/I-E) (clone M5/114.15.2) APC # 17-5321-82 and PE-eFluor610 # 61-5321-82 (dilution 1:200), anti-mouse MHC cIass I (H-2Db) (clone 28-14-8) FITC # 11-5999-82 (dilution 1:100), anti-mouse MHC cIass I (H-2Kb) (clone AF6-88-5.5.3) APC # 17-5958-82 (dilution 1:100), anti-mouse CD8a (clone 53 − 6.7) PE-eFluor610 # 61-0081-82 (dilution 1:400), anti-mouse CD4 (clone RM4-5) PE-Cyanine7 # 25-0042-82 (dilution 1:100), anti-mouse CD69 (clone H1.2F3) FITC # 11-0691-82 (dilution 1:100), anti-mouse CD103 (clone 2E7) APC # 17-1031-82 (dilution 1:200), anti-mouse F4/80 (clone BM8) PE # 12-4801-82 (dilution 1:100), anti-mouse IFN-γ (clone XMG1.2) PE # 12-7311-82 (dilution 1:100), anti-mouse CD3e (clone 145-2C11) PE-eFluor610 # 61-0031-82 (dilution 1:100), anti-mouse CD19 (clone eBio1D3) PE-eFluor610 # 61-0193-82 (dilution 1:600), anti-mouse NK1.1 (clone PK136) PE-eFluor610 # 61-5941-82 (dilution 1:100), anti-mouse NKp46 (clone 29A1.4) PE-eFluor610 # 61-3351-82 (dilution 1:100), anti-mouse O1 (clone O1) eFluor660 # 50-6506-82 (dilution 1:80), anti-mouse MHC Class I H2 Dd (clone 34-5-8S) PE # A15445 (dilution 1:100). Anti-mouse H-2Dd (REA1173) PE # 130-121-058 (dilution 1:100), anti-mouse H-2 (REA857) PE # 130-112-480 (dilution 1:100) and anti-mouse ACSA-2 (IH3-18A3) PE # 130-123-284 (dilution 1:100), were purchased from Miltenyi Biotec. Anti-mouse CD8a BV786 #563332 (dilution 1:200) was purchased from BD Biosciences. M38 tetramer (SSPPMFRV, H2-K(b)) BV421 # 65758 (dilution 1:400) was synthesized by the National Institutes of Health tetramer core facility. To analyze cytokine production, leukocytes were stimulated for 5 hours at 37°C in the presence of Brefeldin A (10 mg/ml; 1000x, eBioscience), PMA/Ionomycin in RPMI 1640 (PAN-Biotech) supplemented with 10% FCS (PAN-Biotech). For intracellular staining, permeabilization and fixation of cells were done using the Fixation/Permeabilization kit (Thermo Fisher). All data was acquired using FACSAriaIIu, and were analyzed using FlowJo v10 (Tree Star) software. In vivo treatment Neutralization of IFN-γ was performed by intraperitoneal (i.p.) injection of 250 µg of anti-IFN-γ antibody ((XMG1.2) # ICH1141-25MG, ichorbio) in 500 µl of PBS, twice a week. Ganciclovir ( Cymevene ) was obtained as a lyophilized powder, reconstituted in deionized water, and administered i.p. daily at 60 mg/kg of body weight. Mice were treated with MCMV-immune sera on 1 and 7 dpi. PBS was injected i.p. daily to the control group of mice. To induce site-specific recombination in Sall1Cre ERT2 mice, Tamoxifen (#T5648, Sigma-Aldrich) was diluted in corn oil (#C8267, Sigma-Aldrich) to make solution of 10 mg/ml, and was protected from light. Tamoxifen solution was freshly prepared on the day of injections and placed on a shaker to dissolve for one hour at 50°C. For adult mice, 2 mg per day of tamoxifen was given by oral gavage injections in 500 µl corn oil (Jahn et al., 2018 ). Tamoxifen was administered for three consecutive days for adult mice. PLX5622 (#A18888, Adooq Bioscience) was formulated in standard AIN-76A rodent diet (ssniff Spezialdiäten GmbH) at a concentration of 1200 mg/kg (Vichaya et al., 2020 ). AIN76-A rodent diet (ssniff Spezialdiäten GmbH) was used as a control. Virus reactivation assay Virus reactivation assay was adapted from standard plaque assay procedures (Polić et al., 1998 ). Brain tissue was homogenized and centrifuged for 1 min. The supernatant was collected and added to 5 ml of 3% DMEM medium. Samples were vortexed, and 200 µl was distributed per well on a 24-well plate, previously seeded with MEF. Plates were incubated for 30 min, followed by centrifugation (2100 rpm, 30 min), and additional 30 min incubation. 400 µl of 3% DMEM medium was added to each well, and plates were left to incubate for 5 days, then supernatants were transferred to new MEF-seeded 48-well plates and analyzed for plaque formation after 5 days. Confocal microscopy To analyze MHC-II expression in latently infected brains, mice underwent transcardiac perfusion with saline (brief wash), followed by 4% paraformaldehyde (PFA), and brains were then submerged in 4% PFA for 24 hours at 4°C. After fixation, brains were stored in PBS at 4°C. Using a Vibratome (VT1200, Leica Microsystems), brains were cut coronally in 50 µm thick serial sections collected in cold PBS. Free-floating sections were blocked and permeabilized by incubating for 45 min in 0.01 M PBS pH 7.4, containing 10% normal goat serum (#X0907, Dako) and 0.2% Triton X-100 at RT (# T8532, Sigma). For analysis of MHC-II expression in acute infected brains and single cell imaging of microglia, following fixation, brains were submerged in 30% sucrose-PBS for 48 h at 4°C and stored in optima cutting temperature compound (OCT) at -70°C (Hosseini et al., 2018 ; Hosseini et al., 2021b). For MHC-II expression, the tissue was frozen on dry ice in OCT (Sakura, #4583) embedding media and stored at -80°C until cutting. Both types of sections were incubated in primary antibodies anti-Iba1 (#019-19741, dilution 1:500, FUJIFILM Wako) and MHC Class II (I-A/I-E) (#14-5321-82, dilution 1:250, Invitrogen) overnight. Subsequently the sections were incubated in the corresponding secondary antibodies; Alexa Fluor 488 conjugated anti-rat (#4416, dilution 1:250, Cell Signaling) and Alexa Fluor 555 conjugated anti-rabbit (#4413, dilution 1:250, Cell Signaling). For single cell imaing of microglia frozen brain hemispheres were cut into 20 µm thick slices using a Leica 2800E Frigocut cryostat microtome. Sections were incubated for 1 hour in the blocking solution containing 0.3% Triton X-100, 5% goat serum, 5% donkey serum and 5% bovine serum albumin (BSA) at room temperature (RT) on the shaker, following with overnight incubation at 4°C with the primary antibodies diluted in blocking solution. Polyclonal rabbit anti-IBA1 (1:1.000, Synaptic Systems—RRID: AB_10641962), rat anti-mouse CD107a (LAMP-1; 1:500, BD Pharmingen™-RRID: AB_2134499) and polyclonal anti-homer-1 chicken (1:500, Synaptic Systems—RRID: AB_2631222), were used. The next day sections were incubated with the secondary antibodies including Cy™3 AffiniPure goat anti-rabbit IgG (H + L) (1:500, Jackson Immuno Research - RRID: AB_2338006), Cy™5 AffiniPure goat anti-rat IgG (H + L) (1:500, Jackson Immuno Research - RRID: AB_2338264) and Alexa Fluor® 488 AffiniPure Donkey Anti-Chicken IgY (IgG) (H + L) (1:500, Jackson Immuno Research - RRID: AB_2340375), in 0.05% Triton X-100 and PBS 1X for 2 h at RT on the shaker in the dark. Afterwards, the sections were incubated with 4′,6-diamidino-2-phenylindole (DAPI) (1:1,000, Sigma-Aldrich) for 5 min. Finally, the sections were mounted on glass slides in fluorogel mounting medium (Electron Microscopy Sciences, Hatfield, PA). To detect MHC-II on microglia in humans, fetal brain tissue was fixed in zinc formalin for 1 week and embedded in paraffin. Antigen retrieval was performed in sodium citrate buffer (pH 6.0). MHC-II was detected with anti-HLA-DR antibody (#ab20181, dilution 1:250, Abcam). All sections were counterstained with DAPI (dilution 1:1000, #422801, Biolegend) and mounted in ProLong mountant (#P36934, Invitrogen). Images were acquired with a laser scanning confocal microscope Leica DMi8 (Leica Microsystems). Human fetal organotypic brain slice cultures Human fetal organotypic brain slice cultures (hfOBSCs) were prepared as previously described in Rashidi et al (Rashidi et al., 2024 ). The hfOBSC were infected with 10 6 PFU of cell-free HCMV RV-TB40-BAC KL7 -SE-EGFP. After 1 h of incubation at 37°C, the inoculum was removed, and the brain slices were washed with PBS and subsequently maintained in the culture medium for 48 h post-infection at 37°C in a CO 2 incubator. Additionally, one group of brain slices was treated with 1,000 U/ml of recombinant human IFN-γ (#300-02, Peprotech) for 48 h. The hfOBSCs were fixed in PBS containing 4% paraformaldehyde and embedded in paraffin for histological analyses. For immunofluorescent staining, brain slices were treated with TrueBlack (#23007, Biotium) after citrate buffer antigen retrieval to decrease autofluorescence. The following primary antibodies were used: FITC goat anti-GFP (#ab6662, dilution 1:250, Abcam), rabbit anti-Iba1 (#019-19741, dilution 1:500, FUJIFILM Wako) and mouse anti-HLA-DP/DQ/DP (#M0775, dilution 1:250, clone CR3/43, DAKO). Unconjugated primary antibody was labeled with the appropriate secondary antibodies: donkey anti-rabbit IgG conjugated to AF555 (#A-31572, dilution 1:250, Invitrogen) and goat anti-mouse IgG conjugated to AF647 (#A-21235, dilution 1:250, Invitrogen). Nuclei were stained with Hoechst 33342 Solution (#62249, Thermo Scientific). Images were taken using a Leica Stellaris 5 Low Incidence Angle confocal microscope. Intracranial injection of virus C57BL/6 mice were intracranially injected with 2x10 5 PFU of MCMV, 2 weeks after PLX5622-diet or control diet. Intracranial injection of virus (2 µL) was performed using Angle two small animal stereotaxic instrument (Leica Biosystems) as previously described (Brizić et al., 2018b ). Cytokine Luminex® Performance Assay Mice were perfused with 20 ml of cold PBS and brains were collected into cryotubes (Greiner Bio-One GmbH, Kremsmünster), weighed and snap-frozen in liquid nitrogen, and stored at − 80°C for further processing. Frozen brains were homogenized using Procartaplex™ buffer (Thermo Scientific). The concentration of tissue proteins was analyzed using ProcartaPlex™ Mouse Immune Monitoring Panel 48-Plex, according to the manufacturer’s instructions (EPX480-20834-901, Thermo Scientific). The concentration of cytokines was measured using the Bio-Plex200™ instrument (Bio-Rad). Concentrations were determined using standard curves and software provided by the manufacturer (Luminex Manager Software). qPCR DNA was extracted from animal brains using NucleoSpin TriPrep kit (Macherey-Nagel, #740966.250). qPCR was performed using a 7500 Fast Real Time PCR (Applied Biosystems), and primers and probe for detecting M86 region (M86 forward GGTCGTGGGCAGCTGGTT, M86 reverse CCTACAGCACGGCGGAGAA, probe: TCGGCCGTGTCCACCAGTTTGATCT (FAM, 250 nM)). Gapdh (FAM, Mm05724508_g1) housekeeping gene was used. Cycling conditions were as follows: Holding stage: 2 min 50°C; 3 min 95°C, followed by 50 cycles for 3 s at 95°C, and annealing for 40 s at 56.2°C. All samples were in technical duplicates. Golgi-Cox staining To examine hippocampal neuron morphology, Golgi-Cox staining was performed using the FD Rapid GolgiStain™ Kit (FD Rapid GolgiStain™ Kit, #PK401) according to the manufacturer’s protocol. 2.5 mpi, C57BL/6 mice were put on PLX5622-formulated or control diet. After two weeks, mice were sacrificed and right hemispheres of the different experimental groups were incubated in the Golgi-Cox solution mixture. Before sectioning, the cerebral hemispheres were embedded in 2% agar. Coronal sections of the hemispheres with a thickness of 200 µm were cut with a Leica Vibratome (VT 1000S) and mounted on gelatin-coated slides. In the following steps, the sections were further processed for signal development according to the kit manufacturer’s protocol. Finally, the sections were mounted with Permount (Thermo Fisher Scientific). Single cell imaging and analysis of microglia Single microglial cells were imaged from the triplicate stained sections (IBA-1/LAMP-1/Homer-1). Using a confocal laser scanning microscope (cLSM, Olympus), Z-stacks of microglial cells were imaged at 0.35-µm increments with a ×40 UPLFLN oil objective (N.A. 1.30) and ×6 zoom. The final pixel size was 0.103 µm × 0.103 µm. For each animal, Z-stacks of three randomly selected single microglial cells in the CA1 hippocampal subregions of three sections were acquired. Prior to analysis in IMARIS (Bitplane), images were deconvoluted by blind 3D deconvolution in AutoQuantX (Adobe Systems GmbH). In IMARIS, the surface of the microglial cells was modeled using IBA-1 staining (surface detail: 0.2 µm). Then, within the constructed microglia surface, the positive LAMP-1 signals were masked to model the surface of the LAMP-1 vesicles (surface detail: 0.2 µm). The Homer-1 spots in the LAMP-1 vesicles within the microglial cells were labeled with the spot function (spot diameter: 0.5 µm). In addition, the microglia structure was made accessible by first masking the IBA-1 signal into the constructed IBA-1 cell surface. The “Add New Cell” tool was used to model the cell soma (filter width: 1 µm, sphere diameter: 0.8 µm) and “Filament Analysis” was used to access the complexity of the microglial branches (largest diameter: 5 µm, thinnest diameter: 0.3 µm, sphere region diameter: 15 µm). Various parameters such as the IBA-1 volume in µm3, the LAMP-1 volume in IBA-1 in µm3, the number of Homer-1 points in LAMP-1, the number of branching points and the size of microglial somas in µm3 were recorded and transferred to Excel (Microsoft). Image analysis of the Golgi-Cox staining After a drying period of at least 2 weeks, the Golgi stained sections were imaged using a ZEISS microscope equipped with an Apotome module and a ×63 objective (N.A. 1.4, oil). Z-stacks in 0.3 µm steps were acquired from the secondary apical dendrites of the CA1 pyramidal neuron and from the dendrites of the granule cells in the superior leaflet of the dentate gyrus. At least 8 dendrites with a length of more than 60–70 µm, at least 40–50 µm from the cell soma, were imaged per region and animal. The spine density per µm of the imaged dendrites was analyzed manually using Fiji software (BioVoxxel). All slides were coded and the analysis was performed blind. 10x Genomics Single-cell RNA-Seq library preparation To analyze the transcriptional differences of microglia and astrocytes from latently infected mice to uninfected mice, the single-cell RNA sequencing was performed. Microglia population is isolated using standard protocol for isolation of mononuclear cells from whole brains using density gradient separation (Bantug et al., 2008 ), while astrocytes were isolated using previously described protocols (Holt et al., 2019 ). Cells from five brains were pooled into one sample per group (infected and uninfected group), for both cell populations. Microglia (CD45.2 int CD11b + ) and astrocytes (CD45.2 − CD11b − O1 − ACSA-2 + ) were sorted into RPMI medium containing 10% FBS using a 100-µm nozzle on FACSAria III (BD Bioscience). Following adjustment of cell density of 1000 cells/µl, sorted cells were partitioned into Gel Bead-In-EMulsions (GEMs) using a Chromium Controller (10x Genomics). Afterwards, reverse transcription, cDNA amplification and library construction were performed using a Chromium Single Cell 3′ GEM, Library & Gel Bead Kit v3 (10x Genomics) according to manufacturer’s instructions. Libraries were sequenced on a NovaSeq 6000 sequencer (Illumina) using NovaSeq 6000 S1 Reagent Kit (100 cycles, 28_8_0_89 bp) with a depth of 50,000 readings per cell. Single-cell RNA-Seq data analysis Demultiplexed, sample-associated FASTQ files were processed using the 10x Genomics Cell Ranger v8.0 count pipeline (Dobin et al., 2013 ; Dobin and Gingeras, 2015 ; Zheng et al., 2017 ) in order to create separate raw and filtered feature-barcode count matrices for each sample. Initial cell calling and the elimination of background technical noise from the obtained raw count matrices were performed using the deep generative model implemented in the CellBender v0.3.0 software package (Fleming et al., 2023 ). Filtered count matrices produced by Cellbender were then used as the initial count data input for the construction of AnnData objects (Bernstein et al., 2020 ) using Scanpy v1.10.2 (Wolf et al., 2018 ). In the initial pre-filtering step, cells expressing less than 250 genes and genes expressed in less than five cells were removed from the AnnData objects before downstream processing. Next, doublet cells in the pre-filtered datasets were identified using the Solo neural network model (Bernstein et al., 2020 ) as implemented in the scvi-tools library (Gayoso et al., 2022 ; Virshup et al., 2023 ), and the cells with a doublet probability score higher than 0.6 were labeled as doublets. Following the identification and removal of doublets, five median absolute deviations (5xMAD) values for complexity, number of detected genes, and percentage of ribosomal counts were calculated for each cell within the microglia and astrocyte dataset. In each dataset, cells with more than 5% of mitochondrial counts, or those exceeding the upper 5×MAD boundary value for ribosomal counts percentage, and cells with complexity values below the lower 5×MAD boundary were considered outliers. In addition to these general criteria, cells containing less than the lower 5×MAD boundary of detected genes or cells having more than 0.02% of S100a8 transcripts were labeled as outliers in the microglia datasets, whereas cells containing less than 250 detected genes were treated as outliers within the astrocyte datasets. After the doublets and outlier cells had been identified and removed, annotation of the remaining cell types within microglia and astrocyte datasets was performed using CellTypist v1.6.3 (Domínguez Conde et al., 2022 ), and only cells having greater than a 50% probability of being the expected cell type (microglia or astrocyte) were labeled as non-intruders in their corresponding datasets. For each dataset, the above quality control procedures resulted in the identification of barcodes labeled as either doublets, outliers, or intruders, and any such cell was removed from the dataset as part of the cell-level filtering procedure. Following cell-level filtering, mitochondrial, ribosomal, and genes expressed in less than 15 cells were then also removed from the count matrices as part of the gene-level filtering procedure, except for six genes of interest ( H2-Aa , Cd74 , C3 , Cxcl9 , Ccl5 , and Ccl2 ) in the astrocyte dataset. Cell and gene-level filtered microglia and astrocyte-associated Seurat objects, containing cells from Mock-infected and MCMV-infected mice, (Hao et al., 2024 ) were then integrated separately using the scVI integration procedure (Lopez et al., 2018 ). Following integration, construction of the shared nearest-neighbor graphs, cluster identification and UMAP dimensionality reduction were performed using Seurat v5.0.1 (Hao et al., 2024 ). Custom-made R functions, based on the output of Seurat's DimPlot and FeaturePlot functions and functionalities available in the tidyverse package (Wickham et al., 2019 ), were used to visualize cluster affiliation and gene expression levels for individual cells in UMAP scatterplots. Sample preparation, quality control of isolated RNA, and bulk RNASeq Mononuclear cells were isolated from whole brains of naive or MCMV-infected mice at 16 mpi as described previously (Bantug et al., 2008 ). Following isolation, mononuclear cells were labeled with anti-CD45 and anti-CD11b antibodies, and microglia, defined as CD45 int CD11b + cells, were separated from the mixture using FACS cell sorting on Aria IIu, using a 100-µm nozzle. Sort purity was determined by sorting an aliquot of cells into 10% RPMI and then immediately reanalyzing the sorted aliquot by flow cytometry. Prior to library generation, RNA was subjected to DNase I digestion (Thermo Fisher Scientific) followed by RNeasyMinElute column clean up (Qiagen). RNA-seq libraries were generated using the SMARTSeq v4 Ultra Low Input RNA Kit (Clontech Laboratories) as per the manufacturer’s recommendations. From cDNA, final libraries were generated using the Nextera XT DNA Library Preparation Kit (Illumina). Concentrations of the final libraries were measured with a Qubit 2.0 Fluorometer (Thermo Fisher Scientific), and fragment length distribution was analyzed with the DNA High Sensitivity Chip on an Agilent 2100 Bioanalyzer (Agilent Technologies). All samples were normalized to 2 nM and pooled at equimolar concentrations and the library pool was sequenced on the NextSeq500 (Illumina). Prior to downstream processing, adapter sequences were hard-clipped from raw sequencing reads as part of the bcl2fastq pipeline (version 2.20.0.422). Overall quality of the trimmed sequences was assessed by FastQC v0.12.1 (Andrews, 2010). Where applicable, quality data from individual analyses were aggregated using MultiQC v1.24 (Ewels et al., 2016). Analysis of the bulk RNA-Seq data, pertaining to DE analysis, was performed as described previously (Rožmanić et al., 2023 ), with minor modifications related to the availability of newer versions of mouse genome and transcriptome sequences, as well as updated versions of operating systems, computing environments, libraries and packages used in the analysis. Detailed description of the steps in RNASeq data analysis is available in Supplementary methods. Statistical analyses Statistical analysis for bulk RNASeq, along with other pertinent information, is described in supplementary information. Data are presented as mean ± SEM or median values. Statistical significance was determined by either two-tailed unpaired Student’s t test, Mann–Whitney U test or two-way ANOVA test, using GraphPad Prism 8. A value of P > 0.05 was considered as not statistically significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P ≤ 0.0001. Declarations Acknowledgments This work has been fully supported by “Research Cooperability“ program of the Croatian Science Foundation funded by the European Union from the European Social Fund under the “Operational Programme Efficient Human Resources 2014 2020“ (PZS-2019-02-7879, I. B. ), the grant “Strengthening the capacity of CerVirVac for research in virus immunology and vaccinology” (KK.01.1.1.01.0006) granted to the Scientific Centre of Excellence for Virus Immunology and Vaccines and co-financed by the European Regional Development Fund (S.J.), the Croatian Science Foundation under the project numbers IP-2022-10-3371 and DOK-2020-01-5362 to I. B., the National Institutes of Health (grant “Inflammation and Hearing Loss Following Congenital CMV Infection” [1 R01 DC015980-01A1] to S. J. and W. J.B., and University of Rijeka (uniri-iskusni-biomed-23-231 to I. B and uniri-biomed-18-234 to B. Lisnić). This study was in part supported by the grant PIE-0008 of the Helmholtz Impulse and Networking fund to LC-S, IB and SJ and by the German Scientific Foundation (DFG) via the DFG research group 2830 funding to LC-S and SJ. We thank Dijana Rumora, Ante Miše, Mihaela Gašparević, Cristina Paulović, and Antonija Šarlija for their excellent technical and administrative support. References Adle-Biassette, H., Teissier, N., 2020. Cytomegalovirus Infections of the CNS, in: Infections of the Central Nervous System. John Wiley & Sons, Ltd, pp. 65–76. Ajami, B., Samusik, N., Wieghofer, P., Ho, P.P., Crotti, A., Bjornson, Z., Prinz, M., Fantl, W.J., Nolan, G.P., Steinman, L., 2018. 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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-5144336","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":360801090,"identity":"74bae405-f2b9-4860-99a5-0e3e2005ab9d","order_by":0,"name":"Ilija Brizić","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIie3RvWrDMBSG4U8I1EXEa4MdcgvHeAr9u5WUQqaGGrpkdDDYS0NXDb0OZU3QkItoKOniqUOgSwuBVjIltIPAYwe9gzGWH+RjAaHQP0ycsIKAFQRYgT3slbvnBIlTD+G/CFNdCNoXLGnvpSPHJQ/pcV7kH9je9SIzf7+4PR8sa4g4z18SxIud78PSBzSjCusynupJ9mQsUXQvkWzIO4uEIcHmFZ9qc624JZLGdpaJd/z04AhnFR/pr24ka3cRljC96kgSakhIVvYX+iZTnJVnjggPGdZ1k77NtjR83LzuP/XlQEVm/SwP46vIQ9xGhL9/5udohA/YA9z510KhUChk+wZlbEqSeD9qZQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Rijeka, Faculty of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Ilija","middleName":"","lastName":"Brizić","suffix":""},{"id":360801091,"identity":"42fc5447-35fc-4479-bf97-0406f76e6aee","order_by":1,"name":"Andrea Mihalić","email":"","orcid":"","institution":"Center for Proteomics, Faculty of Medicine, University of Rijeka, 51000 Rijeka, Croatia","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"","lastName":"Mihalić","suffix":""},{"id":360801092,"identity":"a12d8e53-b01e-4d69-aa49-e0bdb910bb4d","order_by":2,"name":"Daria Kveštak","email":"","orcid":"","institution":"Center for Proteomics, Faculty of Medicine, University of Rijeka, 51000 Rijeka, Croatia","correspondingAuthor":false,"prefix":"","firstName":"Daria","middleName":"","lastName":"Kveštak","suffix":""},{"id":360801093,"identity":"5331286e-4b5c-404d-ac44-7020c7510df9","order_by":3,"name":"Berislav Lisnić","email":"","orcid":"","institution":"Center for Proteomics, Faculty of Medicine, University of Rijeka, 51000 Rijeka, Croatia","correspondingAuthor":false,"prefix":"","firstName":"Berislav","middleName":"","lastName":"Lisnić","suffix":""},{"id":360801094,"identity":"85ec1eb6-bdfd-4afb-9cea-cb347b8eab65","order_by":4,"name":"Fran Krstanović","email":"","orcid":"https://orcid.org/0000-0003-2779-0359","institution":"Center for Proteomics, Faculty of Medicine, University of Rijeka","correspondingAuthor":false,"prefix":"","firstName":"Fran","middleName":"","lastName":"Krstanović","suffix":""},{"id":360801095,"identity":"3589fcd1-c952-401e-83ea-eb7278299c13","order_by":5,"name":"Shirin Hosseini","email":"","orcid":"","institution":"Department of Cellular Neurobiology, Zoological Institute, Technische Universität Braunschweig, Braunschweig, Germany; 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Helmholtz Centre for Infection Research, Research Group Neuroinflammatio","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Korte","suffix":""},{"id":360801106,"identity":"146d4857-d2e3-41cf-85d1-4b7fa05fdd7f","order_by":16,"name":"Luka Čičin-Šain","email":"","orcid":"","institution":"Department of Viral Immunology, Helmholtz Centre for Infection Research, 38124 Braunschweig, Germany; Centre for individualized Infection Medicine, a joint venture of the Helmholtz Centre for Infeci","correspondingAuthor":false,"prefix":"","firstName":"Luka","middleName":"","lastName":"Čičin-Šain","suffix":""},{"id":360801107,"identity":"b6c64568-f623-4821-ba2c-06d44f523962","order_by":17,"name":"Stipan Jonjić","email":"","orcid":"","institution":"Center for Proteomics, Faculty of Medicine, University of Rijeka, 51000 Rijeka, Croatia; Department of Biomedical Sciences, Croatian Academy of Sciences and Arts, 51000 Rijeka, Croatia","correspondingAuthor":false,"prefix":"","firstName":"Stipan","middleName":"","lastName":"Jonjić","suffix":""}],"badges":[],"createdAt":"2024-09-24 10:45:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5144336/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5144336/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65856165,"identity":"db4e58bc-3a76-42db-9a2d-89269577a880","added_by":"auto","created_at":"2024-10-03 15:18:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3138012,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAcute CMV infection causes MHC-II upregulation on microglia in the brain tissue.\u003c/strong\u003e Newborn C57BL/6 \u003cstrong\u003e(A, C)\u003c/strong\u003e and BALB/c \u003cstrong\u003e(B, D)\u003c/strong\u003e mice were infected with MCMV intraperitoneally (i.p.). \u003cstrong\u003e(A, B)\u003c/strong\u003e Expression of MHC-II on microglia (IBA-1\u003csup\u003e+\u003c/sup\u003e) was determined by confocal microscopy 13 days post-infection (dpi). \u003cstrong\u003e(C, D) \u003c/strong\u003eThe expression of MHC-II on microglia was analyzed using flow cytometry 13 dpi. \u003cstrong\u003e(E)\u003c/strong\u003e Expression of HLA-DR on microglia in brain tissues congenitally infected with HCMV was determined by immunohistochemistry.\u003cstrong\u003e (F)\u003c/strong\u003e Human fetal organotypic brain slice cultures were either mock infected, infected with HCMV, or infected with HCMV and stimulated with recombinant IFN-γ. HLA-DR expression on microglia (IBA-1\u003csup\u003e+\u003c/sup\u003e) 48 h after infection was examined by confocal microscopy. Representative images (\u003cstrong\u003eA, B, E, F\u003c/strong\u003e) and histograms (\u003cstrong\u003eC, D\u003c/strong\u003e) are shown. Scale bars for A, B, and F are 25 μm; the scale bar for E is 75 μm. DAPI (nucleus), IBA-1 (microglia), HLA-DR (MHC-II).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5144336/v1/4401a997bb047d1ecf04fa1b.png"},{"id":65856171,"identity":"09858761-7a03-45b1-ae29-21661687bddd","added_by":"auto","created_at":"2024-10-03 15:18:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3196272,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMicroglia is persistently activated in latently infected brain.\u003c/strong\u003e Newborn C57BL/6 \u003cstrong\u003e(A, G-J)\u003c/strong\u003e or BALB/c \u003cstrong\u003e(A, C-F, K-M)\u003c/strong\u003e mice were infected with MCMV intraperitoneally (i.p.).\u003cstrong\u003e (A)\u003c/strong\u003e MCMV M86 gene was detected in the brains of of C57BL/6 and BALB/c mice 3 months post-infection (mpi) by qPCR. The line represents the median value of Cq values obtained for each individual sample; n=2 Mock; for MCMV group n=10 C57BL/6, n=9 BALB/c. \u003cstrong\u003e(B)\u003c/strong\u003e Concentration of cytokines MCP-1, RANTES, MCP-3, IP-10, and BAFF in brain lysates of BALB/c mice, 6 mpi. Median values are shown. n=10 mice per group. Mann–Whitney (U) test was used. \u003cstrong\u003e(C)\u003c/strong\u003e The number of microglia at different times post-infection in whole brains. For 1 mpi n=3 Mock, n=5 MCMV; for 3 mpi n=4 Mock, n=4 MCMV, for 6 mpi n=4 Mock, n=5 MCMV. Normalized expression levels of \u003cstrong\u003e(D) \u003c/strong\u003eMHC-II and \u003cstrong\u003e(E)\u003c/strong\u003e MHC-I on microglia at indicated times post-infection. Mean values ± SEM are shown. n= 3 Mock, n=5 MCMV, N=2. Unpaired two-tailed Student’s test was used. \u003cstrong\u003e(F)\u003c/strong\u003e The expression of MHC-II\u0026nbsp;on\u0026nbsp;microglia (IBA-1\u003csup\u003e+\u003c/sup\u003e)\u0026nbsp;was determined by\u0026nbsp;confocal\u0026nbsp;microscopy at 3 mpi. Scale bars, 50 μm. The expression of \u003cstrong\u003e(G)\u003c/strong\u003e MHC-I (Db) and \u003cstrong\u003e(H)\u003c/strong\u003e MHC-II on microglia in different brain regions was determined at 4 mpi by flow cytometry. Crb – cerebellum, Ctx – cortex, Hipp – hippocampus. Mean values ± SEM are shown. n = 6 Mock, n=10 MCMV, N=2. Pooled data from two experiments are shown. Two-way ANOVA multiple comparisons analysis was used. \u003cstrong\u003e(I)\u003c/strong\u003e Quantification and representative images of microglial density in CA1 hippocampal region. Mean values ± SEM are shown. Unpaired two-tailed Student’s test was used. (\u003cstrong\u003eJ\u003c/strong\u003e) Representative 3D reconstruction of microglial soma (red), filaments (blue), and branch points (small red dots in filaments) in CA1 hippocampal region of Mock- and MCMV-infected C57BL/6 mice, 5 mpi. \u003cstrong\u003e(K) \u003c/strong\u003eQuantification of microglial volume, soma volume, filament length, and number of branching points is shown. Expression of MHC-II and MHC-I on \u003cstrong\u003e(L)\u003c/strong\u003e splenic red pulp macrophages (F4/80\u003csup\u003e+\u003c/sup\u003eCD11b\u003csup\u003e-\u003c/sup\u003e), \u003cstrong\u003e(M)\u003c/strong\u003e liver Kuppfer cells (F4/80\u003csup\u003e+\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e), and \u003cstrong\u003e(N)\u003c/strong\u003e CNS-associated macrophages (CD45.2\u003csup\u003ehi\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e) in BALB/c mice, 6 mpi. Mean values ± SEM are shown (n=4 mice per group, N=2). Unpaired two-tailed Student’s test was used. Statistically significant differences are indicated (p values).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5144336/v1/79338fcff1d3a1c65ef7d9db.png"},{"id":65857446,"identity":"906d4ef6-fca0-416e-9a05-c340cbd351dd","added_by":"auto","created_at":"2024-10-03 15:26:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":523618,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLatent infection of the brain alters transcriptional landscape of microglia. (A-B) \u003c/strong\u003eNewborn BALB/c mice were intraperitoneally (i.p.) infected with MCMV. \u003cstrong\u003e(A) \u003c/strong\u003eExpression of MHC-I and MHC-II on microglia 16 months post infection (mpi) was determined by flow cytometry. Mean values ± SEM are shown (n = 4-5, N=1). Unpaired two-tailed Student’s test was used. Statistically significant differences are indicated (p values).\u003cstrong\u003e (B) \u003c/strong\u003eExperimental sheme. Brains were collected 16 mpi, and microglia was sorted as CD45.2\u003csup\u003eint\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e population by flow cytometry. \u003cstrong\u003e(C) \u003c/strong\u003ePrincipal component analysis (PCA) plot,showing distinct separation of all experimental groups and low intra-group variability, was drawn for acute and latency samples (MCMV vs Mock) using the normalized, rlog-transformed count dataas inputs for the PCAtools Rpackage. Variability over the first (PC1) and second (PC2) principal components is shown on the x and y-axis, respectively. \u003cstrong\u003e(D) \u003c/strong\u003eSelected enriched gene ontology biological process (GO:BP) terms in a set of differentially expressed genes from the latent MCMV vs Mock contrast. \u003cstrong\u003e(E)\u003c/strong\u003e Venn diagram showing the number of genes whose expression was significantly altered in response to either acute (1861) or latent (385) MCMV infection. Expression of as much as 248 shared genes remained persistently altered in response to latent infection of the brain. \u003cstrong\u003e(F)\u003c/strong\u003e Barplot of Log\u003csub\u003e2\u003c/sub\u003eFC values and expression heatmap\u0026nbsp;\u0026nbsp; of selected, persistently altered shared genesassociated with antigen presentation, interferon type I/II signaling, and inflammation. Colors in the heatmap correspond to normalized, rlog-transformed, gene-wise scaled, and centered gene expression read counts, whereas the average changes in expression of selected genes between MCMV and Mock infected mice are represented with log\u003csub\u003e2\u003c/sub\u003eFC values obtained using DESeq2. Each row in the heatmap corresponds to an individual biological replicate (Rep).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5144336/v1/060d40b5b9a18f73e942ad20.png"},{"id":65858065,"identity":"c6491e33-8c9e-4536-b20a-73ed9844beee","added_by":"auto","created_at":"2024-10-03 15:34:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1669210,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMCMV infection results in the formation of a proinflammatory microglial cluster associated with latency. \u003c/strong\u003eNewborn C57BL/6 mice were infected with 200 PFU MCMV intraperitoneally (i.p.), and brains were collected 2.5 months post-infection (mpi). Cells from five mice brains per group (Mock and MCMV) were pooled into a single sample for scRNASeq analysis. Microglia cells were sorted as CD45.2\u003csup\u003eint\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e population \u003cstrong\u003e(A-C) (Suppl. Fig. 4A), \u003c/strong\u003eand astrocytes were sorted as CD45.2\u003csup\u003e-\u003c/sup\u003eCD11b\u003csup\u003e-\u003c/sup\u003eO1\u003csup\u003e-\u003c/sup\u003eACSA-2\u003csup\u003e+ \u003c/sup\u003e\u003cstrong\u003e(D-F) (Suppl. Fig. 4B)\u003c/strong\u003e. After cell sorting, cDNA library was generated based on Drop-seq method, using cell- and transcript-specific barcodes (UMI - unique molecular identifiers on beads), that capture mRNA from lysed cell. Barcoded-labeled libraries were pooled, and RNA sequenced on Illumina NovaSeq 6000 using NovaSeq 6000 S1 Reagent Kit. \u003cstrong\u003e(A)\u003c/strong\u003e UMAP plots showing identified microglia clusters in Mock and MCMV samples during latency in the brain. \u003cstrong\u003e(B)\u003c/strong\u003e Condition-specific percentages of the microglia cells present within individual clusters. \u003cstrong\u003e(C)\u003c/strong\u003e UMAP plots showing the expression of the selected proinflammatory genes within individual microglia cell clusters. \u003cstrong\u003e(D)\u003c/strong\u003e UMAP plots showing identified astrocyte clusters in Mock and MCMV samples during latency in the brain. \u003cstrong\u003e(E)\u003c/strong\u003e Condition-specific percentages of the astrocytes present within individual clusters. \u003cstrong\u003e(F)\u003c/strong\u003e UMAP plots showing the expression of the selected proinflammatory genes within individual astrocyte clusters. Each point in the UMAP plots represents an individual cell, and the affiliation of each cell to a particular cluster in the microglia or astrocyte dataset is designated with the corresponding cluster color in Fig 4A and 4D. Gene expression levels in the UMAP plots are displayed using the designated color palette, whereby each color corresponds to the log-normalized value of gene expression in each individual cell.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5144336/v1/8925c2d2cd69205cab2c206e.png"},{"id":65856168,"identity":"bc72fa1d-01c8-4bda-94a4-7f71d43e43e1","added_by":"auto","created_at":"2024-10-03 15:18:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":831714,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMCMV load in the brain correlates with the extent of microglial activation. \u003c/strong\u003eNewborn BALB/c mice were intraperitoneally (i.p.) Mock- or MCMV-infected.\u003cstrong\u003e (A)\u003c/strong\u003eExperimental schemes for B-C. Groups of MCMV-infected mice were treated with immune sera at 1 and 7 days post-infection (dpi), were daily injected with 60 mg/kg ganciclovir (GCV) starting on 1 dpi, or were treated with PBS. \u003cstrong\u003e(B)\u003c/strong\u003e Microglial MHC-I and MHC-II expression on 14 dpi\u003cstrong\u003e \u003c/strong\u003eis shown. Mean values ± SEM are shown. An unpaired two-tailed Student test was used. For B-C: n=5 Mock, n=7 MCMV, n=4 Immune sera, n=7 GCV; N=2. \u003cstrong\u003e(C)\u003c/strong\u003e Virus titer in the brain 14 dpi, after daily GCV treatment of perinatally infected BALB/c mice. Median values are shown. Mann–Whitney (U) test was used. \u003cstrong\u003e(D)\u003c/strong\u003e Experimental schemes for E-F. \u003cstrong\u003e(E)\u003c/strong\u003e Expression of MHC-I and MHC-II on microglia 90 dpi is shown. \u003cstrong\u003e(F)\u003c/strong\u003e The Number of virus genomes per 200 ng of DNA was determined in brains at 90 dpi. Mean values ± SEM are shown. Unpaired two-tailed Student’s test was used. For E-F: n=6 Mock, n=4 MCMV, n=3 Immune sera, n=6 GCV; N=2. \u003cstrong\u003e(G)\u003c/strong\u003e Experimental scheme for H-I. Newborn BALB/c mice were intraperitoneally (i.p.) infected with MCMV on PND0 or Mock-infected. Groups of MCMV-infected mice were daily injected with 60 mg/kg GCV, starting with 5 dpi.\u003cstrong\u003e(H)\u003c/strong\u003e Expression of MHC-I and MHC-II on microglia 14 dpi is shown. \u003cstrong\u003e(I)\u003c/strong\u003e Number of virus genomes per 200 ng of DNA was determined in brains on 14 dpi. Mean values ± SEM are shown. Unpaired two-tailed Student’s test was used. For H-I: n=4 Mock, n=6 MCMV, n=10 GCV; N=2. \u003cstrong\u003e(J)\u003c/strong\u003e Experimental scheme for K-L. MCMV-infected mice were treated daily for 1 month with 60 mg/kg of GCV, starting at 2 months post-infection (mpi). \u003cstrong\u003e(K)\u003c/strong\u003e Expression of MHC-I and MHC-II on microglia 3 mpi is shown. \u003cstrong\u003e(L)\u003c/strong\u003e Number of virus genomes per 200 ng of DNA was determined in brains after GCV latency treatment. Mean values ± SEM are shown. Unpaired two-tailed Student’s test was used. For K-L: n=4 Mock, n=8 MCMV, n=10 GCV. Pooled data of N=2. Statistically significant differences are indicated (p values).\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-5144336/v1/232cf1bf8f69711e67660ba9.png"},{"id":65856170,"identity":"4a97b0df-2d7a-4073-96bb-bc198cfa7a89","added_by":"auto","created_at":"2024-10-03 15:18:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":719719,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eT-cell-derived IFN-γ is required for the maintenance of microglial MHC-II expression during CMV latency. \u003c/strong\u003eNewborn mice were intraperitoneally (i.p.) infected with 200 PFU MCMV on PND1.\u003cstrong\u003e (A) \u003c/strong\u003eExpression of MHC-II and MHC-I on microglia of 129/SvJ and \u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003e−/− \u003c/sup\u003emice at 2.5 mpi. For 129/SvJ mice, n=4 Mock, n=6 MCMV; for\u003cem\u003e Ifngr1\u003c/em\u003e\u003csup\u003e-/-\u003c/sup\u003e, n=4 Mock, n=4 MCMV; N=2. \u003cstrong\u003e(B)\u003c/strong\u003e Experimental scheme for C-E. Following infection of \u003cem\u003eSall1\u003c/em\u003eCre\u003csup\u003eERT2\u003c/sup\u003e\u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003efl/fl \u003c/sup\u003eand \u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003efl/fl \u003c/sup\u003emice with MCMV, tamoxifen (TAM) was administered to mice 2.5 mpi. Expression of \u003cstrong\u003e(C)\u003c/strong\u003e IFNGR1, \u003cstrong\u003e(D)\u003c/strong\u003e MHC-II, and \u003cstrong\u003e(E)\u003c/strong\u003e MHC-I on microglia 1.5 months after TAM treatment. n=9 mice per group for\u003cem\u003e Ifngr1\u003c/em\u003e\u003csup\u003efl/fl\u003c/sup\u003e, n=10 Mock and n=12 MCMV for \u003cem\u003eSall1\u003c/em\u003eCre\u003csup\u003eERT2\u003c/sup\u003e\u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003efl/fl\u003c/sup\u003e; N=2. \u003cstrong\u003e(F) \u003c/strong\u003e5 mpi, IFN-γ was neutralized using anti–IFN-γ antibodies for a period of 2 weeks and levels of MHC-I and MHC-II expression on microglia were measured. n=5 Mock, n=5 MCMV, n=6 MCMV+α-IFN-γ; N=2. \u003cstrong\u003e(G)\u003c/strong\u003e The expression of \u003cem\u003eIfng\u003c/em\u003e in the brain of C57BL/6 mice was determined at 2.5 mpi. n = 6 Mock, n=8 MCMV. RQ, relative quantification. \u003cstrong\u003e(H) \u003c/strong\u003eMononuclear cells were isolated from brains at 1.5 mpi and stimulated with PMA/Ionomcycin. Representative flow cytometry contour plots of IFN-γ production by CD45\u003csup\u003ehi\u003c/sup\u003e, CD8\u003csup\u003e+,\u003c/sup\u003e and CD4\u003csup\u003e+\u003c/sup\u003e T cells are shown. n=8, N=3. \u003cstrong\u003e(I)\u003c/strong\u003e Quantification of the percentage of IFN-γ\u003csup\u003e+\u003c/sup\u003e CD8\u003csup\u003e+\u003c/sup\u003e and CD4\u003csup\u003e+\u003c/sup\u003e T cells and \u003cstrong\u003e(J)\u003c/strong\u003e percentage of IFN-γ\u003csup\u003e+\u003c/sup\u003e CD8 TRM cells. n=8, with 2 brains pooled per sample; N=2. In all experiments, mean values ± SEM are shown. Unpaired two-tailed Student’s test was used. \u003cstrong\u003e(K)\u003c/strong\u003e Mean values ± SEM of the numbers of M38-tetramer positive CD8 T cells per gram of tissue at 4 mpi for each indicated brain region are shown. n=2 Mock, n=4 MCMV. Ctx-cortex, Crb-cerebellum, Hipp-hippocampus. Statistically significant differences are indicated (p values).\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-5144336/v1/7516887ceb918c7790632cd6.png"},{"id":65857448,"identity":"14c617e2-53c7-4272-b100-dc58380ea1cc","added_by":"auto","created_at":"2024-10-03 15:26:14","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1798208,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePersistently activated microglia provide enhanced control of latent virus in the brain but also mediate dendritic spine loss in the hippocampus. (A) \u003c/strong\u003eExperimental scheme for B-C.\u003cstrong\u003e \u003c/strong\u003eNewborn C57BL/6 mice were Mock- or MCMV-infected. Groups of Mock and latently infected mice were fed with a PLX5622-formulated diet starting 2.5 months post-infection (mpi). \u003cstrong\u003e(B)\u003c/strong\u003e Absolute numbers of microglia following 2 weeks (2w) of PLX5622-formulated diet are shown. n=5 mice per group; N=2. \u003cstrong\u003e(C) \u003c/strong\u003eBrain regions were separated, homogenized, and layered on MEF cells in multi-wall plates. The frequency of MCMV-positive wells following 4 weeks (4w) of PLX5622-formulated diet was determined. Results for individual mice are shown (squares). Median values are shown. Mann–Whitney (U) test was used. n=6 mice per group. \u003cstrong\u003e(D)\u003c/strong\u003e Experimental scheme. Mice fed with a control or PLX5622-formulated diet for 2 weeks were intracranially (i.c.) injected with 2x10\u003csup\u003e5\u003c/sup\u003e PFU of MCMV. \u003cstrong\u003e(E)\u003c/strong\u003e Virus titers in the brain post intracranial challenge (p.i.c.) are shown. Median values are shown. Mann–Whitney (U) test was used. n=3 Mock, n=6 MCMV for group of mice on control diet; n=4 Mock, n=6 MCMV for group of mice on PLX5622-formulated diet; N=3.\u003cstrong\u003e (F-G)\u003c/strong\u003e Newborn C57BL/6 mice were infected with MCMV or Mock-infected. Brains were harvested, and the CA1 hippocampal subregion was analyzed at 3 mpi. 3D representative image of microglia morphology from Mock and MCMV-infected mice. \u003cstrong\u003e(F)\u003c/strong\u003e Representative reconstruction of a microglial cell, a lysosomal compartment, and Homer-1 positive postsynaptic terminals in CA1 hippocampal subregion of Mock- (left) and MCMV-infected (right) mice. The entire microglial cell is shown on the left image (scale bars, 10 μm), while an enlarged section is shown on the right side. IBA-1 surface was remodeled in IMARIS, as well as LAMP-1 volume inside the IBA-1 and Homer-1 puncta, which were localized inside the LAMP-1 volume inside the IBA-1 surface (scale bars, 2 μm). \u003cstrong\u003e(G)\u003c/strong\u003e Quantification of microglial phagocytic morphology in the CA1 subregion. Mean values ± SEM are shown. Unpaired two-tailed Student’s test was used. n=5 Mock, n=5 MCMV. \u003cstrong\u003e(H)\u003c/strong\u003e Newborn C57BL/6 mice were infected with MCMV on PND1 or Mock-infected. 2.5 mpi, a group of Mock and latently infected mice were put on a PLX5622-formulated diet for 2 weeks. Brains were harvested, and dendritic spine morphology and numbers of spines per dendrite in the CA1 hippocampal subregion were analyzed. Mean values ± SEM are shown. Two-way ANOVA multiple comparisons analysis was used. Representative images show dendritic spines of hippocampal CA1 neurons in all tested groups. Scale bars, 2 μm. n=5 Mock, n=5 MCMV for a group of mice on control diet; n=6 Mock, n=6 MCMV for a group of mice on PLX5622-formulated diet. Statistically significant differences are indicated (p values).\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-5144336/v1/19c42d93994432eacc8b9cfd.png"},{"id":65859139,"identity":"918be9e5-28b5-433b-ab01-fae6338c83cd","added_by":"auto","created_at":"2024-10-03 15:42:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13921588,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5144336/v1/d23c5abb-4ae9-4414-a1cd-c68ba269e076.pdf"},{"id":65856173,"identity":"9550d208-c429-4339-b866-2d1b15bca4f8","added_by":"auto","created_at":"2024-10-03 15:18:14","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3568819,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"MihaliXXetalSupplementalFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-5144336/v1/d2a393c8b95d72edc14e24c2.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Persistently primed microglia restrict the reactivation of latent cytomegalovirus at the expense of neuronal synaptic connectivity","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMicroglia are resident myeloid cells of the central nervous system (CNS) that originate from the embryonic yolk sac (Saijo and Glass, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). They comprise 5\u0026ndash;10% of all CNS cells and perform a broad range of homeostatic and immune functions (Ransohoff and Perry, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Waltl and Kalinke, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Microglia are first responders to CNS infections, injury, and neurodegeneration, and while their activation is required to restrict different pathological conditions, they also often contribute to the progression of pathological processes (Ransohoff and Perry, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In response to various pathogenic stimuli, microglia shift their activation state toward a proinflammatory phenotype, which includes upregulation of major histocompatibility complex class I (MHC-I) and II (MHC-II), and costimulatory molecules CD80 and CD86 (Prinz et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Waltl and Kalinke, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In addition, microglia produce various proinflammatory and anti-inflammatory cytokines, chemokines and neurotoxic mediators (Lively and Schlichter, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe critical role of microglia in containing infection was demonstrated for several DNA and RNA viruses infecting CNS (Chhatbar et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Katzilieris-Petras et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Moseman et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Seitz et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Tsai et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Waltl et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, despite their indispensability, the exact mechanisms used by microglia to restrain viral CNS infections are still poorly understood. Microglia can migrate to the site of infection, proliferate, and present antigens to T cells to provide control of the virus (Chhatbar et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Moseman et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Microglia are the major source of type I interferons (IFN-I), and they prime antiviral defense of astrocytes and neurons during herpes simplex type 1 (HSV-1) infection (Reinert et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Furthermore, microglia are required for monocyte recruitment during pseudorabies virus (PRV) infection (Fekete et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Thus, microglia are pivotal in orchestrating the local immune response to acute virus infections in the CNS.\u003c/p\u003e \u003cp\u003eFollowing primary infection, certain viruses, such as herpesviruses, can enter a latent state from which they can reactivate intermittently when immunity wanes due to stress, immunosuppressive therapy, or underlying diseases (Goodrum, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The prototypical β-herpesvirus, cytomegalovirus (CMV), infects the brain if the infection occurs in early life and establishes latency in the CNS (Krstanović et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mihalić et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ribalta et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Congenital human CMV (cCMV) infection is the most common viral congenital infection, with approximately 0.5% of human infants born with HCMV infection, and frequently resulting in long-term neurological sequelae (Boppana et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Since there are no effective therapies that mitigate the persistent neurodevelopmental complications associated with cCMV, there is an unmet need to identify targets for therapeutic intervention and/or prophylaxis. Using a well-established cCMV mouse model, we have previously demonstrated that CD8 and CD4 T cells prevent CMV reactivation by controlling the latent virus in the brain (Brizić et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), while the contribution of microglia remained unexplored.\u003c/p\u003e \u003cp\u003eIn this study, we investigated microglia's role in controlling the latent mouse CMV (MCMV) infection in the brain. We show that during MCMV latency, microglia are continuously primed, as demonstrated by their persistent activation, extensive transcriptional reprogramming at the single-cell level, and upregulation of MHC-II. Lifelong microglial MHC-II upregulation was mediated by interferon-gamma (IFN-γ) locally produced by the tissue-resident memory (T\u003csub\u003eRM\u003c/sub\u003e) T cells. Importantly, primed microglia enhanced MCMV control, demonstrating the critical role in the surveillance of latent and reactivating virus. However, concomitantly with improved control of the latent virus, primed microglia caused a reduction in neuronal dendritic spine density in the hippocampus, which suggests that the priming of microglia that leads to enhanced control of the latent virus infection comes at the cost of reduced synaptic connectivity of neurons. Thus, our study describes a novel pathological mechanism associated with the latent infection and mediated by microglia.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMHC-II expression is a hallmark of microglial activation during acute CMV infection in brain\u003c/h2\u003e \u003cp\u003ePerinatal MCMV infection results in brain infection and subsequent inflammatory response, characterized by infiltration of leukocytes and activation of resident microglia at the site of infection (Bantug et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Kosmac et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We have previously shown that activated microglia upregulate MHC-I, MHC-II, and the costimulatory molecules CD80 and CD86 (Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). To extend these findings, we infected newborn C57BL/6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, \u003cb\u003eSuppl. Figure\u0026nbsp;1A\u003c/b\u003e) and BALB/c (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD, \u003cb\u003eSuppl. Figure\u0026nbsp;1B\u003c/b\u003e) wild-type (WT) mice intraperitoneally (i.p.) with MCMV and harvested brains when MCMV replication peaks in the brain (13 days post-infection, 13 dpi) (Brizić et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e; Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The prototypic microglia marker ionized calcium-binding adaptor protein 1 (IBA-1), and MHC-II expression colocalized upon MCMV infection in both strains of mice, indicating that microglia express MHC-II in the brain (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, B). Expression of MHC-II on microglia in C57BL/6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC) and BALB/c (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) mice was confirmed by flow cytometry. Similarly, MHC-I expression on microglia was also increased in both mouse strains following infection (\u003cb\u003eSuppl. Figure\u0026nbsp;1A, B\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo compare our findings in the mouse model to congenital HCMV infection, we analyzed the expression of human MHC-II (HLA-DR) on IBA-1\u003csup\u003e+\u003c/sup\u003e cells in cadaveric brain tissues of two cases of cCMV infection. Analogously to congenitally MCMV-infected mice, human microglia expressed MHC-II in HCMV-infected brains (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). We have previously shown that IFN-γ is required for early microglial activation during the acute phase of perinatal MCMV infection (Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). To determine the requirements for HLA-DR upregulation upon HCMV infection of the fetal brain, we have used the recently developed human fetal organotypic brain slice culture (hfOBSC) platform (Rashidi et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Whereas HCMV infection alone did not result in HLA-DR expression in hfOBSCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF), IFN-γ treatment of infected hfOBSCs induced HLA-DR expression on microglia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF), similar to microglia in MCMV-infected newborn mice (Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Thus, in both humans and mice, cytomegalovirus infection in the brain results in microglia activation in an IFN-γ-dependent manner.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMCMV infection of the CNS causes persistent activation of microglia\u003c/h3\u003e\n\u003cp\u003eProductive MCMV infection in the brain is resolved by weeks 3 to 4 post-infection, but MCMV DNA remains detectable in these brains for \u0026gt;\u0026thinsp;3 months, suggesting the establishment of MCMV latency (Brizić et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e; Koontz et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). We detected MCMV genomes in the brains of MCMV-infected C57BL/6 and BALB/c mice at 3 months post-infection (mpi), a time corresponding to the latency (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Moreover, we could not detect viral transcription from any known locus of MCMV in brain homogenates during the latent phase of infection (\u003cb\u003eSuppl. Figure\u0026nbsp;2\u003c/b\u003e), suggesting that the virus established true latency.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNext, we performed immune response profiling by analyzing the protein expression of 48 cytokine, chemokine, and growth factor targets in mouse brains. Almost all proteins analyzed were equally or similarly expressed in control and latently MCMV-infected brains (\u003cb\u003eSuppl. Figure\u0026nbsp;3\u003c/b\u003e). However, we detected increased levels of chemokines MCP-1, RANTES, MCP-3, IP-10, and B-cell-activating factor (BAFF) in the brains of latently MCMV-infected mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Since these cytokines are associated with inflammatory response, we next characterized microglia following the resolution of productive infection in BALB/c mice. The number of microglia was increased in MCMV-infected mice at all time points analyzed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Furthermore, microglia in infected mice expressed relatively higher levels of MHC-I and -II at all time points analyzed, even at 6 mpi (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD, E). MHC-II expression remained restricted to IBA-1\u003csup\u003e+\u003c/sup\u003e microglia in the latent phase of MCMV infection, as shown by confocal microscopy (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). To determine if there are differences in microglia activation between different brain regions, we isolated microglia from the hippocampus, cortex, and cerebellum at 4 mpi and analyzed the expression of MHC-I and -II (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG, H). Compared to cortex and cerebellum, hippocampal microglia expressed the highest MHC-I and -II levels. Notably, the hippocampus also had the relatively highest viral load (Brizić et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), suggesting that MCMV latency shapes the microglial activation status.\u003c/p\u003e \u003cp\u003eNext, we analyzed the density and morphology of microglia in the hippocampal CA1 region, which is important for learning and memory-dependent processes and is known to be more susceptible to inflammation during early development (Gomez et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Korte and Schmitz, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Microglia in latently MCMV-infected mice showed increased density (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI), and activated morphology with an increased volume of the whole cell and soma (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ, K). Furthermore, microglial activation has been shown to represent a continuum between ramified activated and amoeboid forms (Ladeby et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). To further assess the microglial morphological changes, the total length and branch points of microglial filaments were examined in both groups. Remarkably, the microglial cells in the latently infected mice exhibited a higher total filament length and a higher number of branching points, indicating a hyper-ramified profile of activated microglial cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ, K). Next, we analyzed MHC-I and -II expression on macrophages in the brain, spleen, and liver to determine if MCMV latency shapes the activation state of other tissue-resident macrophages. Notably, splenic red pulp macrophages (F4/80\u003csup\u003e+\u003c/sup\u003eCD11b\u003csup\u003e\u0026minus;\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eL), liver Kupffer cells (F4/80\u003csup\u003e+\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eM), but also CNS-associated macrophages (CD45.2\u003csup\u003ehi\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eN), did not have significantly increased MHC-I and -II expression in latently MCMV-infected mice. Altogether, these data demonstrate that microglia are selectively and persistently activated in latently MCMV-infected brains.\u003c/p\u003e\n\u003ch3\u003eLatent MCMV infection causes persistent transcriptional alteration of microglia\u003c/h3\u003e\n\u003cp\u003eIncreased expression of MHC-I and -II on microglia in latently infected brains was still observed at 16 mpi (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Since microglia were persistently activated following perinatal MCMV infection, we sorted microglia from MCMV- and mock-infected mice 16 mpi and performed RNA-seq analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). To elucidate transcriptional differences of microglia between acute and latent infection, we also reanalyzed our previous RNA-seq data of microglia obtained 8 dpi (Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Individual samples from the same experimental groups clustered closely together in the PCA plot, indicating low inter-sample variability (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). In accordance with previous analysis, acute MCMV infection in the brain strongly reshaped the microglial transcriptome (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Microglia from latently MCMV-infected brains were also transcriptionally different when compared to microglia from uninfected mice, even though this difference was smaller than that observed between microglia from acutely infected mice and uninfected mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The gene ontology over-representation analysis (GO-ORA) showed that microglia from latently infected mice display the transcriptional signature of elevated antiviral response (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Gene ontology biological process categories associated with antigen processing and presentation, negative regulation of viral process and interferon\u0026thinsp;\u0026minus;\u0026thinsp;mediated signaling pathway were enriched in microglia of latently infected mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). By comparing the list of differentially expressed (DE) genes in acute and latent infection, we identified 1613 DE genes unique to microglia from the acutely infected brain, 137 DE genes unique to microglia from latently infected brain, and 248 genes that were DE in both microglia from both acute and latently infected brains (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). Importantly, most of these 248 shared DE genes were associated with antiviral response, including antigen processing and presentation, interferon type I (IFN-I) and type II (IFN-II) pathways, and inflammatory response (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). Taken together, these data demonstrate the maintenance of a persistent antiviral state of microglia in brains of latently MCMV-infected mice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDifferential regulation of microglial and astrocyte transcriptomes at the single cell level in latently MCMV-infected CNS\u003c/b\u003e \u003c/p\u003e \u003cp\u003eNext, we used the single-cell RNA sequencing (scRNA-seq) approach to decipher the impact of latent MCMV infection on the microglial transcriptome at the individual cell level. For these experiments, newborn C57BL/6 mice were i.p. infected with MCMV and microglia were sorted for scRNA-seq (\u003cb\u003eSuppl. Figure\u0026nbsp;4A\u003c/b\u003e). Following data pre-processing and dataset integration, a total of four distinct microglia clusters were detected using the selected clustering resolution (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), all of which exhibited strong expression of canonical microglia marker genes, such as \u003cem\u003eC1qa\u003c/em\u003e, \u003cem\u003eFcrls\u003c/em\u003e, \u003cem\u003eHexb\u003c/em\u003e, \u003cem\u003eP2ry12\u003c/em\u003e, and others (\u003cb\u003eSuppl. Figure\u0026nbsp;4C\u003c/b\u003e) (Hammond et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Interestingly, latent MCMV infection caused a noticeable redistribution of a subset of microglia cells from clusters 0 and 1 into cluster 2 (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), which suggests that latent MCMV infection transcriptionally reprograms a subset of microglia. In addition to the prominent increase in the proportion of cells in microglial cluster 2 in response to latent MCMV infection, various proportions of cells in that cluster were also characterized by a relatively high expression of genes encoding MHC molecules (e.g. \u003cem\u003eB2m\u003c/em\u003e, \u003cem\u003eH2-Aa, Cd74\u003c/em\u003e) and their transcriptional activators (e.g. \u003cem\u003eCiita\u003c/em\u003e, \u003cem\u003eNlrc5\u003c/em\u003e), genes involved in type I interferon (IFN-I) and type II interferon (IFN-II) signaling (i.e. \u003cem\u003eStat1\u003c/em\u003e, \u003cem\u003eIrf1, Irf7, Irf9, Ifit2, Ifit3, Iigp1\u003c/em\u003e), and genes encoding pro-inflammatory chemokines (\u003cem\u003eCxcl9, Cxcl10, Ccl5\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), in accordance with bulk RNA-seq analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.). Notably, a distinct microglia subset did not display any apparent changes in the expression of these infection or inflammation-associated genes, suggesting that latent MCMV infection shapes microglia towards an activated and proinflammatory phenotype; however, not in all microglial cells in brains of latently MCMV-infected mice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAstrocytes are another type of brain-resident glial cells that can undergo activation and modulate immune responses in different brain diseases (Colombo and Farina, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Giovannoni and Quintana, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). To investigate whether the latent MCMV infection affects astrocytes to the same or similar extent as it affects microglia, we performed scRNA-seq analysis of astrocytes, which were sorted as CD45.2\u003csup\u003e\u0026minus;\u003c/sup\u003eCD11b\u003csup\u003e\u0026minus;\u003c/sup\u003eO1\u003csup\u003e\u0026minus;\u003c/sup\u003eACSA-2\u003csup\u003e+\u003c/sup\u003e cells by flow cytometry (\u003cb\u003eSuppl. Figure\u0026nbsp;4B\u003c/b\u003e). Four astrocyte clusters were identified in brains of mock- and MCMV-infected mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), and analyzed cells expressed canonical astrocyte markers \u003cem\u003eSlc1a2\u003c/em\u003e, \u003cem\u003eSlc1a3\u003c/em\u003e, \u003cem\u003eAtp1b2\u003c/em\u003e, \u003cem\u003eSox9\u003c/em\u003e, \u003cem\u003eGlul\u003c/em\u003e and \u003cem\u003eApoe\u003c/em\u003e (\u003cb\u003eSuppl. Figure\u0026nbsp;4D\u003c/b\u003e) (Batiuk et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In contrast to microglia, no pronounced changes in the number of cells within individual astrocyte clusters were detected (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD, E). Furthermore, we did not detect a substantial increase in the expression of proinflammatory genes within any astrocyte subpopulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). These results demonstrate that while microglia are transcriptionally reprogrammed at the single-cell level to exert proinflammatory state, astrocytes exhibit homeostatic features in latently MCMV-infected brain.\u003c/p\u003e\n\u003ch3\u003eAntiviral interventions limit microglial activation\u003c/h3\u003e\n\u003cp\u003eHaving shown that MCMV can trigger the establishment of a proinflammatory microglia population in the brain, we next investigated if available interventions can mitigate these changes. Antivirals, such as ganciclovir (GCV), are commonly used to control HCMV infection in humans (D and Rc, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). In mice, passive immunization protects against MCMV infection in the brain by decreasing both the viral burden and virus-induced pathology (Cekinović et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). To test if antiviral treatment can reduce microglial activation upon MCMV infection, we i.p. infected newborn BALB/c mice and subsequently treated them with either GCV or MCMV immune sera. Mice were treated with immune sera on 1 and 7 dpi, and GCV was administered daily until 14 dpi (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Both approaches reduced the upregulation of microglial MHC-I and -II expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB), and reduced viral load in the brain (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Moreover, the antiviral treatment attenuated microglial MHC-I and -II expression long-term (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, E), as well as reduced latent viral load in the brain for as long as 90 dpi \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e. Next, we analyzed how anti-viral treatment impacts neuroinflammation if we postpone it for 5 days, the time when MCMV has already reached the brain (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). Anti-viral treatment initiated at 5 dpi only reduced MHC-II upregulation, but had no effect on MHC-I expression nor the viral load in treated mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH-I). Finally, we assessed if antiviral therapy could mitigate neuroinflammation during MCMV latency. To that aim, BALB/c mice infected with MCMV as newborns were treated with GCV starting 2 mpi (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ). One month of antiviral treatment did not affect microglial MHC-I and -II expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK) nor latent viral loads in the brain (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eL). These data indicate that timely inhibition of virus replication reduces microglial activation, while antiviral treatment during the latent phase of MCMV infection does not affect microglial activation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eContinuous IFN-γ signaling maintains microglial MHC-II expression\u003c/h3\u003e\n\u003cp\u003eWe have previously shown that IFN-γ is critical for early microglial MHC-II upregulation following MCMV infection in the brain (Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and in HCMV-infected human brain organotypic cultures (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). To assess if IFN-γ is required for long-term microglial MHC-II expression during MCMV latency, we i.p. infected newborn IFN-γ receptor-deficient (\u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e) mice, and control WT mice, and subsequently analyzed microglial MHC-II expression. Increased microglial MHC-II expression was not observed in \u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e infected mice 3 mpi (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). In contrast, IFN-γ signaling was only partially required for increased MHC-I expression in \u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice, as the increase in MHC-I expression on microglia was lower than in WT mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe next investigated whether continuous IFN-γ receptor signaling is required to maintain MHC-II expression on microglia. We first generated an inducible conditional knockout mouse strain (\u003cem\u003eSall1\u003c/em\u003e\u003csup\u003eCreERT2\u003c/sup\u003e\u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003efl/fl\u003c/sup\u003e), in which the IFN-γ receptor (IFNGR) expression in microglia can be eliminated upon tamoxifen treatment. We infected newborn \u003cem\u003eSall1\u003c/em\u003e\u003csup\u003eCreERT2\u003c/sup\u003e\u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003efl/fl\u003c/sup\u003e mice and administered tamoxifen 3 mpi (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Tamoxifen treatment efficiently decreased IFNGR expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC), accompanied by loss of MHC-II (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD) and decrease in MHC-I (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE) expression on microglia in \u003cem\u003eSall1\u003c/em\u003e\u003csup\u003eCreERT2\u003c/sup\u003e\u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003efl/fl\u003c/sup\u003e mice, which was not observed in control and non-treated \u003cem\u003eSall1\u003c/em\u003e\u003csup\u003eCreERT2\u003c/sup\u003e\u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003efl/fl\u003c/sup\u003e and \u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003efl/fl\u003c/sup\u003e mice (\u003cb\u003eSuppl. Figure\u0026nbsp;5A, B\u003c/b\u003e). These results demonstrate that IFN-γ is required continuously to maintain an activated microglial state during latent MCMV infection.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTissue-resident CD8 T cells are the major source of IFN-γ in latently MCMV-infected brains\u003c/h2\u003e \u003cp\u003eSince our results indicated that continuous IFN-γ receptor signaling in microglia was required to maintain microglia in an activated state, we next determined the cellular source of IFN-γ. IFN-γ could be produced by lymphocytes in the brain parenchyma or the periphery, reaching the brain by blood (Ivashkiv, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). To differentiate between both options, we first assessed if systemic IFN-γ causes microglial activation. To test this possibility, we neutralized IFN-γ for two weeks in latently MCMV-infected mice by i.p. administration of a neutralizing IFN-γ antibody \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e. As control of peripheral IFN-γ neutralization, we infected adult C57BL/6 mice with MCMV and neutralized IFN-γ during acute infection \u003cb\u003e(Suppl. Figure\u0026nbsp;5C)\u003c/b\u003e. In contrast to control mice, MHC-II was not upregulated on peritoneal macrophages in mice treated with IFN-γ neutralizing antibody (\u003cb\u003eSuppl. Figure\u0026nbsp;5C\u003c/b\u003e), indicating successful neutralization of IFN-γ. However, MHC-II expression levels on microglia were unaffected by IFN-γ neutralization (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF), indicating that local but not systemic IFN-γ production is required for the maintenance of microglial MHC-II expression. Even though we did not detect IFN-γ protein in brain homogenates of latently MCMV-infected mice (\u003cb\u003eSuppl. Figure\u0026nbsp;5D\u003c/b\u003e), we detected increased numbers of IFN-γ transcripts (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003eWe have previously demonstrated that NK cells are the main producers of IFN-γ during acute MCMV infection in the brain, mediating microglial MHC-II expression (Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). To determine which cell type is a major source of IFN-γ during latency, we stimulated mononuclear cells isolated from latently MCMV-infected brains. CD8 T cells were the main producers of IFN-γ, while other cell types accounted for minimal IFN-γ production in latently infected brains (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH, I). In accordance with the data obtained by neutralizing peripheral IFN-γ, most IFN-γ\u003csup\u003e+\u003c/sup\u003e CD8 T cells were T\u003csub\u003eRM\u003c/sub\u003e cells, expressing CD69, or co-expressing both canonical T\u003csub\u003eRM\u003c/sub\u003e cell markers CD69 and CD103 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ) (Mueller and Mackay, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Since we observed the highest microglial activation in the hippocampus, we assessed the numbers of CD8 T cells in different brain regions. The highest numbers of total CD8 T cells were detected in the hippocampus (\u003cb\u003eSuppl. Figure\u0026nbsp;5E\u003c/b\u003e). Similarly, virus-specific CD8 T cells, as assessed by analyzing M38-tetramer positive cells, were the most numerous in hippocampus and displayed T\u003csub\u003eRM\u003c/sub\u003e phenotype (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eK, \u003cb\u003eSuppl. Figure\u0026nbsp;5F\u003c/b\u003e). Overall, these data suggest that virus-specific CD8 T\u003csub\u003eRM\u003c/sub\u003e cells are major producers of IFN-γ during MCMV latency in the brain.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePersistently activated microglia enhance control of latent virus\u003c/h3\u003e\n\u003cp\u003eHaving established that long-term microglia activation is a hallmark of latent CMV infection, we hypothesized that such microglia have enhanced functionality, corresponding to the emerging concepts of innate immune cells adaptation to different pathological conditions (Divangahi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). To determine the role of activated microglia during MCMV latency in the brain, we used PLX5622, a colony-stimulating factor 1 receptor (CSF1R) inhibitor, to deplete microglia (Xu et al., \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). C57BL/6 mice were infected as newborns, and after the establishment of latency, mice were fed with a PLX5622-formulated diet (further referred to as PLX-diet) or a control diet (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Microglial numbers were strongly reduced in mice fed with the PLX-diet for 2 weeks (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). Notably, PLX-mediated depletion of microglia resulted in MCMV reactivation in the brain (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC), demonstrating the importance of microglia in preventing MCMV reactivation. To further evaluate the role of persistently activated microglia in virus control, we have performed an intracranial challenge with MCMV in latently infected and control mock-infected mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). In control mice, microglia depletion did not significantly affect virus titers upon intracranial challenge (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). In sharp contrast, microglial depletion had a major role in controlling productive MCMV infection upon intracranial challenge of latently infected mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE), resulting in ~\u0026thinsp;100-fold increase in virus titer when compared to the non-depleted group of mice. Altogether, these data indicate that activated microglia have an important role in controlling both productive as well as preventing reactivation of latent MCMV in the brain.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eMicroglia compromise synaptic connectivity of neurons in the hippocampus during latent infection\u003c/h3\u003e\n\u003cp\u003eAs the resident macrophages in the brain, microglia can remove pathogens, cell debris, but also synaptic connections between neurons under pathological conditions (Boche et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Demuth et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The next step was, therefore, to analyze whether microglia engulf and digest synaptic terminals, followed by degradation in lysosomes (Demuth et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Since the total volume of lysosomes in microglia is proportional to their phagocytic activity (Demuth et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), we first investigated the volumetric changes of microglial lysosomes in infected mice compared to control mice. We detected increased lysosome volume labeled with lysosome-associated membrane protein-1 (LAMP-1) in microglia in the CA1 subregion of the hippocampus (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF, G). Next, we analyzed Homer-1, a synaptic scaffolding protein in postsynaptic terminals that regulates glutamatergic synapses and spine morphogenesis (Tao-Cheng et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), in microglia in all experimental groups. We detected an increased number of Homer-1 puncta in lysosomes in microglia from latently infected mice, demonstrating that activated microglia excessively phagocytose excitatory postsynaptic terminals of hippocampal neurons during MCMV latency (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003eTo investigate whether the increased phagocytosis of postsynaptic terminals of excitatory neurons is reflected in the reduced synaptic connections, we evaluated the dendritic spine density as a morphological indicator of the hippocampal neurons. Spines are dendritic protrusions that carry the majority of excitatory synapses in the hippocampus, and changes in spine density can provide information about changes in the connectivity of hippocampal neurons (Demuth et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gabele et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Hosseini et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Spines were counted on the apical dendrites of CA1 pyramidal neurons. Notably, the density of spines was reduced in the apical dendrites of CA1 neurons of latently infected mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eH). Intriguingly, the depletion of microglia during latency restored the numbers of dendritic spines to the levels observed in control uninfected mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eH), demonstrating that activated microglia associated with latent CMV infection are the cause of dendritic spine loss on the neurons. These data indicate that persistent microglial activation compromises synaptic connectivity in the hippocampus.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eViral infections in the CNS initiate inflammatory processes that restrict viral replication (Waltl and Kalinke, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Microglia have a key role in antiviral immunity by orchestrating intracerebral innate and adaptive immune responses to different viruses, such as arboviruses and neurotropic influenza A viruses (IAVs) (Garber et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hosseini et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, the role of microglia in the surveillance and control of persistent virus infections has not been well studied. Here, we show that latent virus infection shapes microglia, a process critical to preventing virus reactivation. However, enhanced viral control comes at a cost, as persistent microglial activation reduces synaptic connectivity.\u003c/p\u003e \u003cp\u003eCytomegalovirus is a highly prevalent β-herpesvirus infecting most of the world\u0026rsquo;s population (Fowler et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mussi-Pinhata et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Congenital HCMV infection is the most common congenital infection (Manicklal et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Mussi-Pinhata et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), which can cause acute and chronic neurodevelopmental disorders, intellectual disabilities, and sensorineural hearing loss (Adle-Biassette and Teissier, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Following the resolution of productive infection, CMV remains latent for the lifetime in the host (Goodrum, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, the latent phase of HCMV infection in the human brain and its consequences remain unexplored. Microglia are infected with HCMV during congenital infection and with MCMV upon infection of neonatal mice (Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Teissier et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Here, by using postmortem brain tissues of human fetuses infected with HCMV, we show that microglia are activated and express MHC-II during congenital HCMV infection. Furthermore, by using hfOBSCs we demonstrated that IFN-γ is required for microglial activation in human brain slices upon experimental HCMV infection, as is the case with MCMV infection of mouse brain (Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Thus, we have established that the mouse model of congenital CMV infection shares crucial elements with cCMV and is thus an excellent small animal model for investigating this important human congenital infection. Upon establishment of latency in the CNS, brain immune homeostasis is permanently reshaped, as CMV-specific T\u003csub\u003eRM\u003c/sub\u003e cells, usually not present in the brains, are retained in the tissue (Brizić et al., 2018c; Mihalić et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Here, we show that microglia, brain-resident cells, remain activated after the resolution of productive MCMV infection in the brain throughout the life of the congenitally infected host. Interestingly, we showed that this long-term activation is a feature characteristic of microglia and not macrophages in other tissues during the latent phase of MCMV infection. The explanation for these differences remains unclear. However, brain parenchyma is an immune-privileged site, less exposed to environmental factors and consequent low-level inflammation (Louveau et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Indeed, while other macrophages typically constitutively express specific levels of MHC molecules (Reith et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), microglia do not. Thus, MCMV colonization of the brain could increase the basal activation level of microglia, which is set by exposure to environmental factors in other tissue macrophages.\u003c/p\u003e \u003cp\u003eRecent studies have demonstrated that innate immune cells can adapt to different pathological conditions, which can be associated with enhanced responsiveness to secondary stimuli (Divangahi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Netea et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Enhanced responsiveness can be secured by primed and trained innate immune cells. The trained immunity is considered to be due to epigenetic changes, with transcriptional and activation status restored to homeostatic levels (Divangahi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), while priming is considered to result in transcriptional reprogramming and enhanced activation status (Divangahi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Here, we have demonstrated that microglia primed by latent infection enhance control of latent and reactivating MCMV. We did not observe a significant contribution of microglia in control mice that were challenged i.c. with MCMV but were not infected as newborns. This is in sharp contrast to infection with several other viruses where microglia contribute to virus control (Waltl and Kalinke, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). One possible explanation is the timing of analysis, as we have analyzed virus control 3 dpi. Most of the previous studies analyzed virus titers at later time points of infection, allowing for the generation of T cell responses, which microglia supported and were shown to be crucial in restricting viral infections (Waltl and Kalinke, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the case of HSV-1, microglia enhanced virus control as early as 2 dpi by producing IFN-I in a STING-dependent manner (Reinert et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). MCMV has been shown to evade STING activation (Stempel et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), thus potentially explaining microglia's lack of significant contribution to virus control in previously uninfected mice.\u003c/p\u003e \u003cp\u003eThe immune responses mediated by microglia can also be pathological (Miron and Priller, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Waltl and Kalinke, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Here, we have demonstrated that enhanced responsiveness to MCMV comes at the cost of reduced synaptic connectivity. Depletion of microglia abolishes the impact on reduced synaptic connectivity, implying that the consequences of latent infection are reversible. Microglial hyper-ramification is observed during MCMV latency and has previously been related to acute and chronic stress response and might be implicated in synaptic modifications (Vidal-Itriago et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Excessive synaptic pruning has been shown in a model of lymphocytic choriomeningitis virus (LCMV) infection, where IFN-γ produced by CD8\u003csup\u003e+\u003c/sup\u003e T cells acts on neurons, resulting in phagocyte recruitment that mediates synapse loss (Di Liberto et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Furthermore, complement mediates synapse loss upon West Nile virus infection (Vasek et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), with IFN-γ acting on microglia being critical in this process (Garber et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). We have recently shown that MCMV establishes latent infection in neurons, and not microglia and astrocytes (Brizić et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Thus, it could be speculated that during latent MCMV infection, IFN-γ probably acts on microglia or neurons, mediating synapse loss. Microglia can mediate pathological synapse loss in different pathological conditions, as shown in a model of Parkinson's disease (Zhang et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), multiple sclerosis (Beckmann et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wies Mancini et al., \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), traumatic brain injury model, (Henry et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Witcher et al., \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), cerebral ischemic stroke (Du et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and age-associated neuroinflammation (Stojiljkovic et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Whether the presence of CMV in such conditions could enhance the disease progression remains to be determined.\u003c/p\u003e \u003cp\u003eUsing RNAseq analysis, we have identified a set of proinflammatory genes induced in microglia adapted to latent infection, most notably associated with type I and II interferon responses. Recent studies investigating the transcriptional profile of microglia in neuroinflammation, neurodegenerative conditions and aging detected similar activated microglia signatures (Ajami et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Escoubas et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Frigerio et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Moreover, IFN-γ-responsive microglia were induced during aging and localized near CD8 T cells in white matter, resulting in oligodendrocyte loss (Kaya et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Using single-cell RNA-seq analysis of microglia, we have demonstrated a subset of microglia associated with MCMV latency. The principal characteristic of this population was increased expression of MHC molecules and numerous antiviral factors, such as interferon-stimulated genes. Many genes that were upregulated during the latent phase of infection were similarly regulated during the acute phase, suggesting the central role of microglia in virus control. High levels of several proinflammatory chemokines and cytokines (MCP-1, RANTES and IP-10) were detected in latently infected brains. Transcripts for these and other chemokines were increased in microglia but not in the astrocytes during latency, suggesting that microglia are the major source of these chemokines in the brain. Many of these chemokines are important for the recruitment of T and NK cells to the brain upon viral infections (Hosking and Lane, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Thapa et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Trifilo et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Thus, microglia-derived chemokines and cytokines probably orchestrate T\u003csub\u003eRM\u003c/sub\u003e cells in the brain during latency. Astrocytes are also infected and activated during acute CMV infection (Brizić et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, unlike microglia, which were persistently activated, we did not detect reactive astrocytes by single-cell sequencing, as observed in other CNS diseases (Liddelow et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), suggesting that there is a fine regulation of inflammatory response during latent CMV infection in the brain. Indeed, we did not detect increased transcripts coding for IL-1α, TNF-α, and C1q in microglia, all of the three being required for the induction of reactive astrocytes (Liddelow et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile a comprehensive description of the mechanism that maintains microglia in an activated state remains elusive, we have demonstrated that persistent upregulation of microglial MHC-II depends on continuous IFN-γ receptor signaling in microglia. Virus-specific CD4 and CD8 T cells can produce IFN-γ in the brain in a mouse model of congenital CMV infection (Brizić et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). We show that IFN-γ is mainly produced by virus-specific CD8 T\u003csub\u003eRM\u003c/sub\u003e cells. A recent study suggested that IFN-γ epigenetically reprograms microglia following early immune activation (Schwabenland et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Cooperation between both mechanisms may be needed to secure persistent activation. Besides IFN-γ, IFN-I is probably required for microglial activation, as suggested by our RNAsq analysis.\u003c/p\u003e \u003cp\u003eAmong congenitally HCMV-infected infants with clinically apparent symptoms, the majority will have neurological sequelae. However, even infants with asymptomatic cCMV infection can present long-term CNS manifestations later in life (Brizić et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e; Cheeran et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Antivirals, such as acyclovir (ACV) and GCV, are used in clinics to control HCMV and other herpesviral infections (D and Rc, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). In a mouse model of congenital CMV infection, MCMV-specific antibodies limit inflammation and viral replication in the brains of newborn mice (Cekinović et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Furthermore, treatment of newborn mice with IFN-γ or TNF-α neutralizing antibodies (Kveštak et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Seleme et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) or glucocorticoids (Kosmac et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) reduced inflammation and brain pathology without affecting viral replication. Similarly, we showed here that the anti-viral treatment with GCV effectively reduced neuroinflammation and virus load in the brain if treatment was done during the acute phase of infection. In addition, the beneficial effect of early anti-viral treatment on microglial activation and viral load was maintained even during latency. However, if antiviral treatment started during latency, microglial activation and viral loads were not changed. This finding underscores the importance of early-life testing for cCMV and timely treatment with readily available drugs.\u003c/p\u003e \u003cp\u003eTo this day, there is no approved HCMV vaccine, the use of antiviral therapies is limited by toxicity, and interventional therapies cannot entirely prevent adverse outcomes of HCMV-associated diseases like cCMV. The development of more efficient therapies requires better insight into the virus and host factors and cell types involved in the protection versus pathogenesis of viral diseases. Here, we showed that latent CMV infection in the brain primes microglia, which in turn enhances surveillance of the chronic infection. Still, at the same time, activated microglia mediate pathological damage in the CNS. Interestingly, the reduced synaptic connectivity caused by persistent microglial activation is reversible by microglia depletion, opening new therapeutic options. On average, 0.5% of human infants are estimated to be born with HCMV (Kenneson and Cannon, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Mussi-Pinhata et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). However, the extent of the population carrying latent HCMV in the CNS is not known, but it seems that HCMV DNA is present at a much higher frequency in human brains, as would be expected based on the prevalence of congenital HCMV infection (Ribalta et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Furthermore, a recent study reported activated microglia in postmortem samples of human brains with CMV-positivity (Zheng et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the consequences of latent CMV infection in the brain and whether CMV and microglia could be important targets in improving brain health remain to be determined.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMice\u003c/h2\u003e \u003cp\u003e Mice were strictly age-matched within experiments and handled in accordance with institutional and national guidelines. All mice were housed and bred under specific pathogen\u0026ndash;free conditions at the animal facility of the Faculty of Medicine, University of Rijeka where they were maintained at 22\u0026deg;C in a 12-h light\u0026ndash;dark cycle, and relative humidity (40\u0026ndash;50%). C57BL/6J (strain #:000664), BALB/c (00651), 129/SvJ (000691), \u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e (003288), \u003cem\u003eIfng\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e (002287) and \u003cem\u003eIfngr1\u003c/em\u003e\u003csup\u003efl/fl\u003c/sup\u003e (IFN-γR1 floxed; 025394) mice were obtained from The Jackson Laboratory. \u003cem\u003eSall1Cre\u003c/em\u003e\u003csup\u003eERT2\u003c/sup\u003e mice were provided by Riuchi Nishinakamura (Inoue et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kanda et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), at Kumamoto University. All animal experiments were approved by The Animal Welfare Committee at the University of Rijeka, Faculty of Medicine and The National Ethics Committee for the Protection of Animals Used for Scientific Purposes (Ministry of Agriculture (UP/I-322-01/17\u0026thinsp;\u0026minus;\u0026thinsp;01/101, UP/I-322-01/19\u0026thinsp;\u0026minus;\u0026thinsp;01/25, UP/I-322-01/21\u0026thinsp;\u0026minus;\u0026thinsp;01/51, UP/I-322-01/23\u0026thinsp;\u0026minus;\u0026thinsp;01/33)).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eViruses\u003c/h2\u003e \u003cp\u003eTissue culture-derived MCMV reconstituted from BAC pSM3fr-MCK-2fl (WT) was used in all experiments (Jordan et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Virus stocks were kept at \u0026minus;\u0026thinsp;80\u0026deg;C. Viral titers were determined by plaque assay on murine embryonic fibroblasts (MEFs) and expressed as plaque-forming units (PFUs) (Brizić et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Newborn BALB/c mice were infected intraperitoneally (i.p.) with 400 PFU of MCMV (6\u0026ndash;18 hours post birth), while other mouse strains were i.p. infected with 200 PFU of MCMV (24\u0026ndash;48 hours post birth). Adult, 5-month-old mice were infected i.p. with 2 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e PFU of MCMV. For HCMV infection experiments RV-TB40-BAC\u003csub\u003eKL7\u003c/sub\u003e-SE-EGFP (KL7-EGFP) virus was used, a kind gift from Christian Sinzger (Sampaio et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAntibodies and flow cytometry\u003c/h2\u003e \u003cp\u003eSingle-cell leukocyte suspensions were prepared using previously published methods (Bantug et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In brief, the suspension of 30% Percoll (#GE17-0891-09, Cytivia) and brain homogenate was overlaid on 70% Percoll in PBS and then centrifuged at 1,800 rpm for 25 min. Cells in the interphase were collected. Adult Brain Dissociation Kit (#130-107-677, Miltenyi Biotec) was used to isolate astrocytes from the brain. After tissue dissociation and red blood cell removal, myelin was removed using magnetic beads (#130-096-433, Myelin Removal Beads, Miltenyi Biotec). Before staining lymphocytes, Fc receptors were blocked using anti-mouse CD16/CD32 monoclonal antibody (clone 93) #14-0161-82 (dilution 1:50), Thermo Fisher). The following anti-mouse antibodies purchased from Thermo Fisher were used: anti-mouse CD45.2 (clone 104) FITC # 11-0454-82 and Alexa Fluor 700 # 56-0454-82 (dilution 1:100), anti-mouse CD11b (clone M1/70) PE-Cyanine7 # 25-0112-82 (dilution 1:400), anti-mouse MHC class II (I-A/I-E) (clone M5/114.15.2) APC # 17-5321-82 and PE-eFluor610 # 61-5321-82 (dilution 1:200), anti-mouse MHC cIass I (H-2Db) (clone 28-14-8) FITC # 11-5999-82 (dilution 1:100), anti-mouse MHC cIass I (H-2Kb) (clone AF6-88-5.5.3) APC # 17-5958-82 (dilution 1:100), anti-mouse CD8a (clone 53\u0026thinsp;\u0026minus;\u0026thinsp;6.7) PE-eFluor610 # 61-0081-82 (dilution 1:400), anti-mouse CD4 (clone RM4-5) PE-Cyanine7 # 25-0042-82 (dilution 1:100), anti-mouse CD69 (clone H1.2F3) FITC # 11-0691-82 (dilution 1:100), anti-mouse CD103 (clone 2E7) APC # 17-1031-82 (dilution 1:200), anti-mouse F4/80 (clone BM8) PE # 12-4801-82 (dilution 1:100), anti-mouse IFN-γ (clone XMG1.2) PE # 12-7311-82 (dilution 1:100), anti-mouse CD3e (clone 145-2C11) PE-eFluor610 # 61-0031-82 (dilution 1:100), anti-mouse CD19 (clone eBio1D3) PE-eFluor610 # 61-0193-82 (dilution 1:600), anti-mouse NK1.1 (clone PK136) PE-eFluor610 # 61-5941-82 (dilution 1:100), anti-mouse NKp46 (clone 29A1.4) PE-eFluor610 # 61-3351-82 (dilution 1:100), anti-mouse O1 (clone O1) eFluor660 # 50-6506-82 (dilution 1:80), anti-mouse MHC Class I H2 Dd (clone 34-5-8S) PE # A15445 (dilution 1:100). Anti-mouse H-2Dd (REA1173) PE # 130-121-058 (dilution 1:100), anti-mouse H-2 (REA857) PE # 130-112-480 (dilution 1:100) and anti-mouse ACSA-2 (IH3-18A3) PE # 130-123-284 (dilution 1:100), were purchased from Miltenyi Biotec. Anti-mouse CD8a BV786 #563332 (dilution 1:200) was purchased from BD Biosciences. M38 tetramer (SSPPMFRV, H2-K(b)) BV421 # 65758 (dilution 1:400) was synthesized by the National Institutes of Health tetramer core facility. To analyze cytokine production, leukocytes were stimulated for 5 hours at 37\u0026deg;C in the presence of Brefeldin A (10 mg/ml; 1000x, eBioscience), PMA/Ionomycin in RPMI 1640 (PAN-Biotech) supplemented with 10% FCS (PAN-Biotech). For intracellular staining, permeabilization and fixation of cells were done using the Fixation/Permeabilization kit (Thermo Fisher). All data was acquired using FACSAriaIIu, and were analyzed using FlowJo v10 (Tree Star) software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eIn vivo treatment\u003c/h2\u003e \u003cp\u003eNeutralization of IFN-γ was performed by intraperitoneal (i.p.) injection of 250 \u0026micro;g of anti-IFN-γ antibody ((XMG1.2) # ICH1141-25MG, ichorbio) in 500 \u0026micro;l of PBS, twice a week. Ganciclovir (\u003cem\u003eCymevene\u003c/em\u003e) was obtained as a lyophilized powder, reconstituted in deionized water, and administered i.p. daily at 60 mg/kg of body weight. Mice were treated with MCMV-immune sera on 1 and 7 dpi. PBS was injected i.p. daily to the control group of mice. To induce site-specific recombination in Sall1Cre\u003csup\u003eERT2\u003c/sup\u003e mice, Tamoxifen (#T5648, Sigma-Aldrich) was diluted in corn oil (#C8267, Sigma-Aldrich) to make solution of 10 mg/ml, and was protected from light. Tamoxifen solution was freshly prepared on the day of injections and placed on a shaker to dissolve for one hour at 50\u0026deg;C. For adult mice, 2 mg per day of tamoxifen was given by oral gavage injections in 500 \u0026micro;l corn oil (Jahn et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Tamoxifen was administered for three consecutive days for adult mice. PLX5622 (#A18888, Adooq Bioscience) was formulated in standard AIN-76A rodent diet (ssniff Spezialdi\u0026auml;ten GmbH) at a concentration of 1200 mg/kg (Vichaya et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). AIN76-A rodent diet (ssniff Spezialdi\u0026auml;ten GmbH) was used as a control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eVirus reactivation assay\u003c/h2\u003e \u003cp\u003eVirus reactivation assay was adapted from standard plaque assay procedures (Polić et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Brain tissue was homogenized and centrifuged for 1 min. The supernatant was collected and added to 5 ml of 3% DMEM medium. Samples were vortexed, and 200 \u0026micro;l was distributed per well on a 24-well plate, previously seeded with MEF. Plates were incubated for 30 min, followed by centrifugation (2100 rpm, 30 min), and additional 30 min incubation. 400 \u0026micro;l of 3% DMEM medium was added to each well, and plates were left to incubate for 5 days, then supernatants were transferred to new MEF-seeded 48-well plates and analyzed for plaque formation after 5 days.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eConfocal microscopy\u003c/h2\u003e \u003cp\u003eTo analyze MHC-II expression in latently infected brains, mice underwent transcardiac perfusion with saline (brief wash), followed by 4% paraformaldehyde (PFA), and brains were then submerged in 4% PFA for 24 hours at 4\u0026deg;C. After fixation, brains were stored in PBS at 4\u0026deg;C. Using a Vibratome (VT1200, Leica Microsystems), brains were cut coronally in 50 \u0026micro;m thick serial sections collected in cold PBS. Free-floating sections were blocked and permeabilized by incubating for 45 min in 0.01 M PBS pH 7.4, containing 10% normal goat serum (#X0907, Dako) and 0.2% Triton X-100 at RT (# T8532, Sigma). For analysis of MHC-II expression in acute infected brains and single cell imaging of microglia, following fixation, brains were submerged in 30% sucrose-PBS for 48 h at 4\u0026deg;C and stored in optima cutting temperature compound (OCT) at -70\u0026deg;C (Hosseini et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hosseini et al., 2021b). For MHC-II expression, the tissue was frozen on dry ice in OCT (Sakura, #4583) embedding media and stored at -80\u0026deg;C until cutting. Both types of sections were incubated in primary antibodies anti-Iba1 (#019-19741, dilution 1:500, FUJIFILM Wako) and MHC Class II (I-A/I-E) (#14-5321-82, dilution 1:250, Invitrogen) overnight. Subsequently the sections were incubated in the corresponding secondary antibodies; Alexa Fluor 488 conjugated anti-rat (#4416, dilution 1:250, Cell Signaling) and Alexa Fluor 555 conjugated anti-rabbit (#4413, dilution 1:250, Cell Signaling). For single cell imaing of microglia frozen brain hemispheres were cut into 20 \u0026micro;m thick slices using a Leica 2800E Frigocut cryostat microtome. Sections were incubated for 1 hour in the blocking solution containing 0.3% Triton X-100, 5% goat serum, 5% donkey serum and 5% bovine serum albumin (BSA) at room temperature (RT) on the shaker, following with overnight incubation at 4\u0026deg;C with the primary antibodies diluted in blocking solution. Polyclonal rabbit anti-IBA1 (1:1.000, Synaptic Systems\u0026mdash;RRID: AB_10641962), rat anti-mouse CD107a (LAMP-1; 1:500, BD Pharmingen\u0026trade;-RRID: AB_2134499) and polyclonal anti-homer-1 chicken (1:500, Synaptic Systems\u0026mdash;RRID: AB_2631222), were used. The next day sections were incubated with the secondary antibodies including Cy\u0026trade;3 AffiniPure goat anti-rabbit IgG (H\u0026thinsp;+\u0026thinsp;L) (1:500, Jackson Immuno Research - RRID: AB_2338006), Cy\u0026trade;5 AffiniPure goat anti-rat IgG (H\u0026thinsp;+\u0026thinsp;L) (1:500, Jackson Immuno Research - RRID: AB_2338264) and Alexa Fluor\u0026reg; 488 AffiniPure Donkey Anti-Chicken IgY (IgG) (H\u0026thinsp;+\u0026thinsp;L) (1:500, Jackson Immuno Research - RRID: AB_2340375), in 0.05% Triton X-100 and PBS 1X for 2 h at RT on the shaker in the dark. Afterwards, the sections were incubated with 4\u0026prime;,6-diamidino-2-phenylindole (DAPI) (1:1,000, Sigma-Aldrich) for 5 min. Finally, the sections were mounted on glass slides in fluorogel mounting medium (Electron Microscopy Sciences, Hatfield, PA). To detect MHC-II on microglia in humans, fetal brain tissue was fixed in zinc formalin for 1 week and embedded in paraffin. Antigen retrieval was performed in sodium citrate buffer (pH 6.0). MHC-II was detected with anti-HLA-DR antibody (#ab20181, dilution 1:250, Abcam). All sections were counterstained with DAPI (dilution 1:1000, #422801, Biolegend) and mounted in ProLong mountant (#P36934, Invitrogen). Images were acquired with a laser scanning confocal microscope Leica DMi8 (Leica Microsystems).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eHuman fetal organotypic brain slice cultures\u003c/h2\u003e \u003cp\u003eHuman fetal organotypic brain slice cultures (hfOBSCs) were prepared as previously described in Rashidi et al (Rashidi et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The hfOBSC were infected with 10\u003csup\u003e6\u003c/sup\u003e PFU of cell-free HCMV RV-TB40-BAC\u003csub\u003eKL7\u003c/sub\u003e-SE-EGFP. After 1 h of incubation at 37\u0026deg;C, the inoculum was removed, and the brain slices were washed with PBS and subsequently maintained in the culture medium for 48 h post-infection at 37\u0026deg;C in a CO\u003csub\u003e2\u003c/sub\u003e incubator. Additionally, one group of brain slices was treated with 1,000 U/ml of recombinant human IFN-γ (#300-02, Peprotech) for 48 h. The hfOBSCs were fixed in PBS containing 4% paraformaldehyde and embedded in paraffin for histological analyses. For immunofluorescent staining, brain slices were treated with TrueBlack (#23007, Biotium) after citrate buffer antigen retrieval to decrease autofluorescence. The following primary antibodies were used: FITC goat anti-GFP (#ab6662, dilution 1:250, Abcam), rabbit anti-Iba1 (#019-19741, dilution 1:500, FUJIFILM Wako) and mouse anti-HLA-DP/DQ/DP (#M0775, dilution 1:250, clone CR3/43, DAKO). Unconjugated primary antibody was labeled with the appropriate secondary antibodies: donkey anti-rabbit IgG conjugated to AF555 (#A-31572, dilution 1:250, Invitrogen) and goat anti-mouse IgG conjugated to AF647 (#A-21235, dilution 1:250, Invitrogen). Nuclei were stained with Hoechst 33342 Solution (#62249, Thermo Scientific). Images were taken using a Leica Stellaris 5 Low Incidence Angle confocal microscope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eIntracranial injection of virus\u003c/h2\u003e \u003cp\u003eC57BL/6 mice were intracranially injected with 2x10\u003csup\u003e5\u003c/sup\u003e PFU of MCMV, 2 weeks after PLX5622-diet or control diet. Intracranial injection of virus (2 \u0026micro;L) was performed using Angle two small animal stereotaxic instrument (Leica Biosystems) as previously described (Brizić et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eCytokine Luminex\u0026reg; Performance Assay\u003c/h2\u003e \u003cp\u003eMice were perfused with 20 ml of cold PBS and brains were collected into cryotubes (Greiner Bio-One GmbH, Kremsm\u0026uuml;nster), weighed and snap-frozen in liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C for further processing. Frozen brains were homogenized using Procartaplex\u0026trade; buffer (Thermo Scientific). The concentration of tissue proteins was analyzed using ProcartaPlex\u0026trade; Mouse Immune Monitoring Panel 48-Plex, according to the manufacturer\u0026rsquo;s instructions (EPX480-20834-901, Thermo Scientific). The concentration of cytokines was measured using the Bio-Plex200\u0026trade; instrument (Bio-Rad). Concentrations were determined using standard curves and software provided by the manufacturer (Luminex Manager Software).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eqPCR\u003c/h2\u003e \u003cp\u003eDNA was extracted from animal brains using NucleoSpin TriPrep kit (Macherey-Nagel, #740966.250). qPCR was performed using a 7500 Fast Real Time PCR (Applied Biosystems), and primers and probe for detecting M86 region (M86 forward GGTCGTGGGCAGCTGGTT, M86 reverse CCTACAGCACGGCGGAGAA, probe: TCGGCCGTGTCCACCAGTTTGATCT (FAM, 250 nM)). \u003cem\u003eGapdh\u003c/em\u003e (FAM, Mm05724508_g1) housekeeping gene was used. Cycling conditions were as follows: Holding stage: 2 min 50\u0026deg;C; 3 min 95\u0026deg;C, followed by 50 cycles for 3 s at 95\u0026deg;C, and annealing for 40 s at 56.2\u0026deg;C. All samples were in technical duplicates.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eGolgi-Cox staining\u003c/h2\u003e \u003cp\u003eTo examine hippocampal neuron morphology, Golgi-Cox staining was performed using the FD Rapid GolgiStain\u0026trade; Kit (FD Rapid GolgiStain\u0026trade; Kit, #PK401) according to the manufacturer\u0026rsquo;s protocol. 2.5 mpi, C57BL/6 mice were put on PLX5622-formulated or control diet. After two weeks, mice were sacrificed and right hemispheres of the different experimental groups were incubated in the Golgi-Cox solution mixture. Before sectioning, the cerebral hemispheres were embedded in 2% agar. Coronal sections of the hemispheres with a thickness of 200 \u0026micro;m were cut with a Leica Vibratome (VT 1000S) and mounted on gelatin-coated slides. In the following steps, the sections were further processed for signal development according to the kit manufacturer\u0026rsquo;s protocol. Finally, the sections were mounted with Permount (Thermo Fisher Scientific).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eSingle cell imaging and analysis of microglia\u003c/h2\u003e \u003cp\u003eSingle microglial cells were imaged from the triplicate stained sections (IBA-1/LAMP-1/Homer-1). Using a confocal laser scanning microscope (cLSM, Olympus), Z-stacks of microglial cells were imaged at 0.35-\u0026micro;m increments with a \u0026times;40 UPLFLN oil objective (N.A. 1.30) and \u0026times;6 zoom. The final pixel size was 0.103 \u0026micro;m \u0026times; 0.103 \u0026micro;m. For each animal, Z-stacks of three randomly selected single microglial cells in the CA1 hippocampal subregions of three sections were acquired. Prior to analysis in IMARIS (Bitplane), images were deconvoluted by blind 3D deconvolution in AutoQuantX (Adobe Systems GmbH).\u003c/p\u003e \u003cp\u003eIn IMARIS, the surface of the microglial cells was modeled using IBA-1 staining (surface detail: 0.2 \u0026micro;m). Then, within the constructed microglia surface, the positive LAMP-1 signals were masked to model the surface of the LAMP-1 vesicles (surface detail: 0.2 \u0026micro;m). The Homer-1 spots in the LAMP-1 vesicles within the microglial cells were labeled with the spot function (spot diameter: 0.5 \u0026micro;m). In addition, the microglia structure was made accessible by first masking the IBA-1 signal into the constructed IBA-1 cell surface. The \u0026ldquo;Add New Cell\u0026rdquo; tool was used to model the cell soma (filter width: 1 \u0026micro;m, sphere diameter: 0.8 \u0026micro;m) and \u0026ldquo;Filament Analysis\u0026rdquo; was used to access the complexity of the microglial branches (largest diameter: 5 \u0026micro;m, thinnest diameter: 0.3 \u0026micro;m, sphere region diameter: 15 \u0026micro;m). Various parameters such as the IBA-1 volume in \u0026micro;m3, the LAMP-1 volume in IBA-1 in \u0026micro;m3, the number of Homer-1 points in LAMP-1, the number of branching points and the size of microglial somas in \u0026micro;m3 were recorded and transferred to Excel (Microsoft).\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eImage analysis of the Golgi-Cox staining\u003c/h2\u003e \u003cp\u003eAfter a drying period of at least 2 weeks, the Golgi stained sections were imaged using a ZEISS microscope equipped with an Apotome module and a \u0026times;63 objective (N.A. 1.4, oil). Z-stacks in 0.3 \u0026micro;m steps were acquired from the secondary apical dendrites of the CA1 pyramidal neuron and from the dendrites of the granule cells in the superior leaflet of the dentate gyrus. At least 8 dendrites with a length of more than 60\u0026ndash;70 \u0026micro;m, at least 40\u0026ndash;50 \u0026micro;m from the cell soma, were imaged per region and animal. The spine density per \u0026micro;m of the imaged dendrites was analyzed manually using Fiji software (BioVoxxel). All slides were coded and the analysis was performed blind.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003e10x Genomics Single-cell RNA-Seq library preparation\u003c/h2\u003e \u003cp\u003eTo analyze the transcriptional differences of microglia and astrocytes from latently infected mice to uninfected mice, the single-cell RNA sequencing was performed. Microglia population is isolated using standard protocol for isolation of mononuclear cells from whole brains using density gradient separation (Bantug et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), while astrocytes were isolated using previously described protocols (Holt et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Cells from five brains were pooled into one sample per group (infected and uninfected group), for both cell populations. Microglia (CD45.2\u003csup\u003eint\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e) and astrocytes (CD45.2\u003csup\u003e\u0026minus;\u003c/sup\u003eCD11b\u003csup\u003e\u0026minus;\u003c/sup\u003eO1\u003csup\u003e\u0026minus;\u003c/sup\u003eACSA-2\u003csup\u003e+\u003c/sup\u003e) were sorted into RPMI medium containing 10% FBS using a 100-\u0026micro;m nozzle on FACSAria III (BD Bioscience). Following adjustment of cell density of 1000 cells/\u0026micro;l, sorted cells were partitioned into Gel Bead-In-EMulsions (GEMs) using a Chromium Controller (10x Genomics). Afterwards, reverse transcription, cDNA amplification and library construction were performed using a Chromium Single Cell 3\u0026prime; GEM, Library \u0026amp; Gel Bead Kit v3 (10x Genomics) according to manufacturer\u0026rsquo;s instructions. Libraries were sequenced on a NovaSeq 6000 sequencer (Illumina) using NovaSeq 6000 S1 Reagent Kit (100 cycles, 28_8_0_89 bp) with a depth of 50,000 readings per cell.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eSingle-cell RNA-Seq data analysis\u003c/h2\u003e \u003cp\u003eDemultiplexed, sample-associated FASTQ files were processed using the 10x Genomics Cell Ranger v8.0 \u003cem\u003ecount\u003c/em\u003e pipeline (Dobin et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Dobin and Gingeras, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Zheng et al., \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) in order to create separate raw and filtered feature-barcode count matrices for each sample. Initial cell calling and the elimination of background technical noise from the obtained raw count matrices were performed using the deep generative model implemented in the CellBender v0.3.0 software package (Fleming et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Filtered count matrices produced by Cellbender were then used as the initial count data input for the construction of AnnData objects (Bernstein et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) using Scanpy v1.10.2 (Wolf et al., \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In the initial pre-filtering step, cells expressing less than 250 genes and genes expressed in less than five cells were removed from the AnnData objects before downstream processing. Next, doublet cells in the pre-filtered datasets were identified using the Solo neural network model (Bernstein et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) as implemented in the scvi-tools library (Gayoso et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Virshup et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and the cells with a doublet probability score higher than 0.6 were labeled as doublets. Following the identification and removal of doublets, five median absolute deviations (5xMAD) values for complexity, number of detected genes, and percentage of ribosomal counts were calculated for each cell within the microglia and astrocyte dataset. In each dataset, cells with more than 5% of mitochondrial counts, or those exceeding the upper 5\u0026times;MAD boundary value for ribosomal counts percentage, and cells with complexity values below the lower 5\u0026times;MAD boundary were considered outliers. In addition to these general criteria, cells containing less than the lower 5\u0026times;MAD boundary of detected genes or cells having more than 0.02% of S100a8 transcripts were labeled as outliers in the microglia datasets, whereas cells containing less than 250 detected genes were treated as outliers within the astrocyte datasets. After the doublets and outlier cells had been identified and removed, annotation of the remaining cell types within microglia and astrocyte datasets was performed using CellTypist v1.6.3 (Dom\u0026iacute;nguez Conde et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and only cells having greater than a 50% probability of being the expected cell type (microglia or astrocyte) were labeled as non-intruders in their corresponding datasets. For each dataset, the above quality control procedures resulted in the identification of barcodes labeled as either doublets, outliers, or intruders, and any such cell was removed from the dataset as part of the cell-level filtering procedure. Following cell-level filtering, mitochondrial, ribosomal, and genes expressed in less than 15 cells were then also removed from the count matrices as part of the gene-level filtering procedure, except for six genes of interest (\u003cem\u003eH2-Aa\u003c/em\u003e, \u003cem\u003eCd74\u003c/em\u003e, \u003cem\u003eC3\u003c/em\u003e, \u003cem\u003eCxcl9\u003c/em\u003e, \u003cem\u003eCcl5\u003c/em\u003e, and \u003cem\u003eCcl2\u003c/em\u003e) in the astrocyte dataset. Cell and gene-level filtered microglia and astrocyte-associated Seurat objects, containing cells from Mock-infected and MCMV-infected mice, (Hao et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) were then integrated separately using the scVI integration procedure (Lopez et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Following integration, construction of the shared nearest-neighbor graphs, cluster identification and UMAP dimensionality reduction were performed using Seurat v5.0.1 (Hao et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Custom-made R functions, based on the output of Seurat's DimPlot and FeaturePlot functions and functionalities available in the tidyverse package (Wickham et al., \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), were used to visualize cluster affiliation and gene expression levels for individual cells in UMAP scatterplots.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eSample preparation, quality control of isolated RNA, and bulk RNASeq\u003c/h2\u003e \u003cp\u003eMononuclear cells were isolated from whole brains of naive or MCMV-infected mice at 16 mpi as described previously (Bantug et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Following isolation, mononuclear cells were labeled with anti-CD45 and anti-CD11b antibodies, and microglia, defined as CD45\u003csup\u003eint\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e cells, were separated from the mixture using FACS cell sorting on Aria IIu, using a 100-\u0026micro;m nozzle. Sort purity was determined by sorting an aliquot of cells into 10% RPMI and then immediately reanalyzing the sorted aliquot by flow cytometry. Prior to library generation, RNA was subjected to DNase I digestion (Thermo Fisher Scientific) followed by RNeasyMinElute column clean up (Qiagen). RNA-seq libraries were generated using the SMARTSeq v4 Ultra Low Input RNA Kit (Clontech Laboratories) as per the manufacturer\u0026rsquo;s recommendations. From cDNA, final libraries were generated using the Nextera XT DNA Library Preparation Kit (Illumina). Concentrations of the final libraries were measured with a Qubit 2.0 Fluorometer (Thermo Fisher Scientific), and fragment length distribution was analyzed with the DNA High Sensitivity Chip on an Agilent 2100 Bioanalyzer (Agilent Technologies). All samples were normalized to 2 nM and pooled at equimolar concentrations and the library pool was sequenced on the NextSeq500 (Illumina). Prior to downstream processing, adapter sequences were hard-clipped from raw sequencing reads as part of the bcl2fastq pipeline (version 2.20.0.422). Overall quality of the trimmed sequences was assessed by FastQC v0.12.1 (Andrews, 2010). Where applicable, quality data from individual analyses were aggregated using MultiQC v1.24 (Ewels et al., 2016). Analysis of the bulk RNA-Seq data, pertaining to DE analysis, was performed as described previously (Rožmanić et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), with minor modifications related to the availability of newer versions of mouse genome and transcriptome sequences, as well as updated versions of operating systems, computing environments, libraries and packages used in the analysis. Detailed description of the steps in RNASeq data analysis is available in Supplementary methods.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eStatistical analysis for bulk RNASeq, along with other pertinent information, is described in supplementary information. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM or median values. Statistical significance was determined by either two-tailed unpaired Student\u0026rsquo;s t test, Mann\u0026ndash;Whitney U test or two-way ANOVA test, using GraphPad Prism 8. A value of P\u0026thinsp;\u0026gt;\u0026thinsp;0.05 was considered as not statistically significant; *, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; ****, P\u0026thinsp;\u0026le;\u0026thinsp;0.0001.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThis work has been fully supported by \u0026ldquo;Research Cooperability\u0026ldquo; program of the Croatian Science Foundation funded by the European Union from the European Social Fund under the \u0026ldquo;Operational Programme Efficient Human Resources 2014 2020\u0026ldquo; (PZS-2019-02-7879, I. B. ), the grant \u0026ldquo;Strengthening the capacity of CerVirVac for research in virus immunology and vaccinology\u0026rdquo; (KK.01.1.1.01.0006) granted to the Scientific Centre of Excellence for Virus Immunology and Vaccines and co-financed by the European Regional Development Fund (S.J.), the Croatian Science Foundation under the project numbers IP-2022-10-3371 and DOK-2020-01-5362 to I. B., the National Institutes of Health (grant \u0026ldquo;Inflammation and Hearing Loss Following Congenital CMV Infection\u0026rdquo; [1 R01 DC015980-01A1] to S. J. and W. J.B., and University of Rijeka (uniri-iskusni-biomed-23-231 to I. B and uniri-biomed-18-234 to B. Lisnić). This study was in part supported by the grant PIE-0008 of the Helmholtz Impulse and Networking fund to LC-S, IB and SJ and by the German Scientific Foundation (DFG) via the DFG research group 2830 funding to LC-S and SJ. We thank Dijana Rumora, Ante Miše, Mihaela Gašparević, Cristina Paulović, and Antonija Šarlija for their excellent technical and administrative support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAdle-Biassette, H., Teissier, N., 2020. Cytomegalovirus Infections of the CNS, in: Infections of the Central Nervous System. John Wiley \u0026amp; Sons, Ltd, pp. 65\u0026ndash;76.\u003c/li\u003e\n \u003cli\u003eAjami, B., Samusik, N., Wieghofer, P., Ho, P.P., Crotti, A., Bjornson, Z., Prinz, M., Fantl, W.J., Nolan, G.P., Steinman, L., 2018. Single cell mass cytometry reveals distinct populations of brain myeloid cells in mouse models of neuroinflammatory and neurodegenerative diseases. Nat. Neurosci. 21, 541\u0026ndash;551.\u003c/li\u003e\n \u003cli\u003eBantug, G.R.B., Cekinovic, D., Bradford, R., Koontz, T., Jonjic, S., Britt, W.J., 2008. CD8+ T-LYMPHOCYTES CONTROL MCMV REPLICATION IN THE CNS OF NEWBORN ANIMALS. J. Immunol. Baltim. 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Psychiatry.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5144336/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5144336/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicroglia are myeloid cells that reside within the central nervous system (CNS), where they maintain homeostasis under normal, non-pathological conditions. In addition, microglia also perform numerous immune functions upon different pathogenic stimuli, including CNS infections with various neurotropic viruses. Herpesviruses establish a lifelong latent infection from which they reactivate intermittently upon waning of immune control. The role of microglia in preventing reactivation of latent herpesviruses remains unclear. In this work, we used congenital cytomegalovirus (CMV) infection as a model to investigate the impact of a persistent virus infection of the brain on microglia. We show that mouse CMV (MCMV) latency in the CNS is associated with permanent microglial priming. The changes induced by persistent infection include continuous, interferon-gamma-dependent microglia activation and extensive transcriptional reprogramming at the single-cell level, leading to the expansion of a microglia subset associated with latent infection. Notably, the maintenance of microglia in a primed state provides enhanced control of latent infection and superior recall response but is associated with excessive loss of synaptic dendritic spines mediated by primed microglia. Altogether, our results indicate that latent CMV infection in the brain causes perturbation of microglial homeostasis, which leads to chronic neuroinflammation that successfully restricts virus reactivation but simultaneously compromises neuronal synaptic connectivity in the brain.\u003c/p\u003e","manuscriptTitle":"Persistently primed microglia restrict the reactivation of latent cytomegalovirus at the expense of neuronal synaptic connectivity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-03 15:18:09","doi":"10.21203/rs.3.rs-5144336/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-neuroscience","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"neuro","sideBox":"Learn more about [Nature Neuroscience](http://www.nature.com/neuro/)","snPcode":"","submissionUrl":"","title":"Nature Neuroscience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6d688358-2b97-4143-b25d-fa4c71258c7d","owner":[],"postedDate":"October 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":38385530,"name":"Biological sciences/Neuroscience/Neuroimmunology"},{"id":38385531,"name":"Biological sciences/Neuroscience/Glial biology/Microglia"},{"id":38385532,"name":"Biological sciences/Immunology/Infection"},{"id":38385533,"name":"Biological sciences/Immunology/Inflammation"}],"tags":[],"updatedAt":"2026-03-20T00:50:37+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-03 15:18:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5144336","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5144336","identity":"rs-5144336","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}