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

doi:10.21203/rs.3.rs-5144336/v1

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

https://doi.org/10.21203/rs.3.rs-5144336/v1

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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

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.

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. 1A, 1C, Suppl. Figure 1A) and BALB/c (Fig. 1B, 1D, 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. 1A, B). Expression of MHC-II on microglia in C57BL/6 (Fig. 1C) and BALB/c (Fig. 1D) 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. 1E). 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. 1F), IFN-γ treatment of infected hfOBSCs induced HLA-DR expression on microglia (Fig. 1F), 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. 2A). 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. 2B). 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. 2C). Furthermore, microglia in infected mice expressed relatively higher levels of MHC-I and -II at all time points analyzed, even at 6 mpi (Fig. 2D, E). MHC-II expression remained restricted to IBA-1⁺ microglia in the latent phase of MCMV infection, as shown by confocal microscopy (Fig. 2F). 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. 2G, 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. 2I), and activated morphology with an increased volume of the whole cell and soma (Fig. 2J, 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. 2J, 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. 2L), liver Kupffer cells (F4/80⁺CD11b⁺) (Fig. 2M), but also CNS-associated macrophages (CD45.2^hiCD11b⁺) (Fig. 2N), 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. 3A). 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. 3B). 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. 3C). In accordance with previous analysis, acute MCMV infection in the brain strongly reshaped the microglial transcriptome (Fig. 3C). 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. 3C). The gene ontology over-representation analysis (GO-ORA) showed that microglia from latently infected mice display the transcriptional signature of elevated antiviral response (Fig. 3D). 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. 3D). 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. 3E). 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. 3F). 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. 4A), 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. 4A and 4B), 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. 4C), 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. 4D), 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. 4D, E). Furthermore, we did not detect a substantial increase in the expression of proinflammatory genes within any astrocyte subpopulation (Fig. 4F). 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. 5A). Both approaches reduced the upregulation of microglial MHC-I and -II expression (Fig. 5B), and reduced viral load in the brain (Fig. 5C). Moreover, the antiviral treatment attenuated microglial MHC-I and -II expression long-term (Fig. 5D, E), as well as reduced latent viral load in the brain for as long as 90 dpi (Fig. 5F). 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. 5G). 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. 5H-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. 5J). One month of antiviral treatment did not affect microglial MHC-I and -II expression (Fig. 5K) nor latent viral loads in the brain (Fig. 5L). 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. 1F). 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. 6A). 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. 6A).

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^CreERT2Ifngr1^fl/fl), in which the IFN-γ receptor (IFNGR) expression in microglia can be eliminated upon tamoxifen treatment. We infected newborn Sall1^CreERT2Ifngr1^fl/fl mice and administered tamoxifen 3 mpi (Fig. 6B). Tamoxifen treatment efficiently decreased IFNGR expression (Fig. 6C), accompanied by loss of MHC-II (Fig. 6D) and decrease in MHC-I (Fig. 6E) expression on microglia in Sall1^CreERT2Ifngr1^fl/fl mice, which was not observed in control and non-treated Sall1^CreERT2Ifngr1^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. 6F). 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. 6F), 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. 6G).

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. 6H, 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. 6J) (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. 6K, 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. 7A). Microglial numbers were strongly reduced in mice fed with the PLX-diet for 2 weeks (Fig. 7B). Notably, PLX-mediated depletion of microglia resulted in MCMV reactivation in the brain (Fig. 7C), 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. 7D). In control mice, microglia depletion did not significantly affect virus titers upon intracranial challenge (Fig. 7E). In sharp contrast, microglial depletion had a major role in controlling productive MCMV infection upon intracranial challenge of latently infected mice (Fig. 7E), 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. 7F, 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. 7G).

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. 7H). Intriguingly, the depletion of microglia during latency restored the numbers of dendritic spines to the levels observed in control uninfected mice (Fig. 7H), 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.

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.

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 × 10⁵ 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 10⁶ 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 CO₂ 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 2x10⁵ 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^intCD11b⁺) 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^intCD11b⁺ 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.

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.

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

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Abstract

Figures

Introduction

Results

MHC-II expression is a hallmark of microglial activation during acute CMV infection in brain

MCMV infection of the CNS causes persistent activation of microglia

Latent MCMV infection causes persistent transcriptional alteration of microglia

Antiviral interventions limit microglial activation

Continuous IFN-γ signaling maintains microglial MHC-II expression

Tissue-resident CD8 T cells are the major source of IFN-γ in latently MCMV-infected brains

Persistently activated microglia enhance control of latent virus

Microglia compromise synaptic connectivity of neurons in the hippocampus during latent infection

Discussion

Materials and methods

Mice

Viruses

Antibodies and flow cytometry

In vivo treatment

Virus reactivation assay

Confocal microscopy

Human fetal organotypic brain slice cultures

Intracranial injection of virus

Cytokine Luminex® Performance Assay

qPCR

Golgi-Cox staining

Single cell imaging and analysis of microglia

Image analysis of the Golgi-Cox staining

10x Genomics Single-cell RNA-Seq library preparation

Single-cell RNA-Seq data analysis

Sample preparation, quality control of isolated RNA, and bulk RNASeq

Statistical analyses

Declarations

Acknowledgments

References

Additional Declarations

Supplementary Files

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