Reactive gliosis surrounding amyloid β (Aβ) plaques is an early feature of Alzheimer’s disease pathogenesis and has been postulated to represent activation of the innate immune system in an apparently ineffective attempt to clear or neutralize Aβ aggregates. To evaluate the role of IFN-γ–mediated neuroinflammation on the evolution of Aβ pathology in transgenic (Tg) mice, we have expressed murine IFN-γ (mIFN-γ) in the brains of Aβ precursor protein (APP) Tg mice using recombinant adeno-associated virus serotype 1. Expression of mIFN-γ in brains of APP TgCRND8 mice results in robust noncell autonomous activation of microglia and astrocytes, and a concomitant significant suppression of Aβ deposition. In these mice, mIFN-γ expression upregulated multiple glial activation markers, early components of the complement cascade as well as led to infiltration of Ly-6c positive peripheral monocytes but no significant effects on APP levels, APP processing or steady-state Aβ levels were noticed in vivo. Taken together, these results suggest that mIFN-γ expression in the brain suppresses Aβ accumulation through synergistic effects of activated glia and components of the innate immune system that enhance Aβ aggregate phagocytosis.

Alzheimer’s disease (AD), the most common form of cognitive dementia, is a progressive neurodegenerative disorder. The neuropathological hallmarks of AD, extracellular fibrillar aggregates of amyloid β (Aβ) in senile plaques, intracellular τ neurofibrillary tangles, and neurodegeneration, are associated with induction of chronic neuroinflammation (1). Senile plaque-associated neuroinflammation occurs early in the disease process in humans and is recapitulated in Aβ precursor protein (APP) transgenic (Tg) mice brains (2, 3). Several lines of evidence suggest that Aβ aggregates directly induce neuroinflammation resulting in neurotoxicity. Aggregated Aβ activates microglia in culture by binding to the receptor for advanced glycation endproducts (4) as well as to different scavenger receptors (5, 6). Such interactions have been reported to be exacerbated by interactions with microglial costimulatory factors like CD14 and CD40L (7, 8), supporting a close pathologic link between Aβ plaque pathology and the chronic activation of the innate immune system. Such inflammation has been proposed to result in increased oxidative stress, mitochondrial dysfunction, upregulation of amyloidogenic APP processing, and increased Aβ deposition (913). Conversely, some recent evidence demonstrates that activation of the innate immune response could play a protective role, at least with respect to plaque deposition. Hippocampal expression of IL-1β, a proinflammatory cytokine, in APPswe/PS1dE9 mice results in increased microglial activation and subsequent amelioration of plaque pathology (14). Stimulation of the TLRs have been shown to significantly decrease Aβ burden (15), whereas knocking out TLR2 or TLR4 in APP mice was shown to accelerate Aβ deposition (16, 17).

Neuroinflammation is a well-defined feature of AD pathology, but its role in regulating Aβ deposition remains controversial. Experimental data suggests that glial activation may enhance or suppress Aβ pathology, and that Aβ accumulation may be critically dependent on the factors driving the immune response, as well as the strength and context of the immune response (1, 18). As part of a broader series of studies examining the effects of numerous cytokines and chemokines on Aβ accumulation (19), we have evaluated the effects of murine IFN-γ (mIFN-γ) on Aβ pathology in APP mice. IFN-γ, a pleiotropic cytokine, is a critical component of the innate immune response against viral and intracellular bacterial infections and in tumor control (20). IFN-γ is the hallmark cytokine secreted by Th1 cells, dendritic cells, and NK cells (21). It is a potent activator of both microglia and astrocytes in the CNS via upregulation of MHC class II (MHCII) Ag and is associated with establishment of the APC phenotype (21). Although IFN-γ levels are not reported to be increased in AD, many IFN-γ responsive genes are upregulated in the AD brain (22, 23). IFN-γ levels have been shown to be increased in APP Tg mice (2426). Current studies do not demonstrate a clear role for IFN-γ with respect to Aβ deposition phenotypes. Deletion of the IFN-γ receptor in APP Tg mice has been reported to decrease Aβ plaque burden via inhibiting IFN-γ–mediated pathogenic APP processing (13), consistent with in vitro studies showing that IFN-γ enhances amyloidogenic APP processing via the β- and γ-secretases (27). Expression of human IFN-γ also leads to increased intracellular Aβ immunoreactivity in mutant APP/τ/PS1 triple Tg mice with no changes in APP levels (28). On the other hand, low doses of IFN-γ were reported to clear Aβ plaques in vivo by T cell-dependent mechanisms (29) and improve learning in APP Tg mice (30).

To further explore the role of IFN-γ in regulating Aβ accumulation, we have used recombinant adeno-associated virus serotype 1 (rAAV1) to express mIFN-γ in the brains of APP TgCRND8 mice. The rAAV1–mIFN-γ overexpression led to widespread noncell autonomous activation of glia, upregulation of MHCII and CD11c and complement system components as well as infiltration of Ly-6c positive monocytes. The mIFN-γ expression was accompanied by a significant decrease in Aβ plaque burden with no alterations in steady state Aβ levels, APP processing, or APP levels. Taken together, these results provide clear evidence that mIFN-γ attenuates Aβ accumulation in vivo, an effect that is likely mediated by synergistic actions of activated glia and components of the innate immune system that enhance Aβ aggregate phagocytosis.

All animal husbandry procedures performed were approved by the Mayo Clinic Institutional Animal Care and Use Committee in accordance with National Institutes of Health guidelines. To generate CRND8 mice, male TgCRND8 mice containing a double mutation in the human APP gene (KM670/671NL and V717F) (31) were mated with female B6C3F1/Tac mice (Harlan Breeders, Indianapolis, IN). Hemizygous male Tg2576 mice (32) expressing mutant human APP (KM670/671NL) gene were mated with female B6SJLF1 mice (The Jackson Laboratory, Bar Harbor, ME). All animals were housed three to five to a cage and maintained on ad libitum food and water with a 12 h light/dark cycle.

The mIFN-γ was cloned in pAAV vector from Image clone 8733812 (Open Biosystems, Huntsville, AL). The mTNF-α was cloned in pAAV vector from Image clone 40126376 (Open Biosystems). The pAAV-enhanced GFP (EGFP) is a kind gift from M. During (Ohio State University). The rAAV1 viruses expressing mIFN-γ, EGFP, or mTNF-α, under the control of the CMV enhancer/chicken β actin promoter were generated by calcium-phosphate transfection of pAM/CBA-pI-WPRE-BGH, rAAV1 cis-plasmid pH21 (rAAV1 helper plasmid), and pF6 into a HEK293 cell line. Forty-eight hours after transfection, cells were lysed in the presence of 0.5% sodium deoxycholate and 50 U/ml benzonase (Sigma-Aldrich, St. Louis, MO) by repeated rounds of freeze/thaws at –80°C and 37°C. The virus was isolated using a discontinuous iodixanol gradient and then affinity purified on a HiTrap HQ column (GE Healthcare, Piscataway, NJ). Samples were eluted from the column and buffer exchanged to PBS using an Amicon Ultra 100 Centrifugation device (Millipore, Billerica, MA). The genomic titer of each virus was determined by Q-PCR using the ABI 7900 (Applied Biosystems, Foster City, CA).

The injection procedures were performed as described previously (19, 33). Both APP Tg and non-Tg TgCRND8 littermates were injected with rAAV1–mIFN-γ or rAAV1–EGFP on neonatal day P2 (36–48 h after birth). Briefly, P2 pups were cryoanesthetized and 2 μl rAAV1 construct (1012 particles/ml) were bilaterally injected into the cerebral ventricle of newborn mice using a 10 μl Hamilton syringe with a 30-inch needle (Hamilton, NV). The pups were placed on a heating pad for recovery and returned to their mother. Mice were euthanized at the end of 5 mo for analysis (n = 10/group). For Tg2576 mice, P0 pups (<24 h after birth) were injected in the cerebral ventricles with rAAV1–mIFN-γ and rAAV1–EGFP (1012 particles/ml) and mice were euthanized after 3 mo for analysis (n = 6/group).

The 4-mo-old TgCRND8 mice were injected bilaterally into the hippocampus with rAAV1–mIFN-γ or EGFP (1013 particles/ml). Mice were anesthetized with 1.5% isoflurane in 1% oxygen and secured into a Kopf apparatus (Model 900 Small Animal Stereotaxic Instrument, David Kopf Instruments, Tujunga, CA). All surgical procedures were performed under aseptic conditions. The scalp was scrubbed with betadine and midline incision made. A burr hole (0.5 mm) was drilled in the skull at –2.2 mm caudal and 1.6 mm lateral from the bregma. A 30-inch needle mounted to a 10 μl syringe (Hamilton) preloaded with virus was lowered 1.1 mm from the brain surface. A UMP2 Microsyringe Injector and Micro4 Controller (World Precision Instruments, Sarasota, FL) was used to inject 2 μl virus (1013 particles/ml) at a constant rate over 10 min. After allowing an additional 10 min, the needle was raised slowly. The burr hole was sealed and the scalp incision was closed with surgical staples. Mice were monitored postsurgically and administered analgesics overnight and staples were removed 7–10 d after surgery. Mice were euthanized after 6 wk for analysis (n = 5 for rAAV1–mIFN-γ; n = 6 for rAAV1–EGFP)

Total RNA from mice brain was isolated using the RNaqueous kit (Ambion, Austin,TX) according to the manufacturer's instructions and RNA sample was reverse transcribed using Superscript III (Invitrogen, Carlsbad, CA). Dilutions of each cDNA prep were used to assess actin RNA levels, and samples were then adjusted to give equivalent levels of actin per well. The quantitative real-time PCR (QRT-PCR) was performed using SYBR Green (Applied Biosystems) to detect the amplification products as suggested by the manufacturers. The following cycles were performed in an ABI (Applied Biosystems) 7900HT Fast Real-Time PCR system: initial denaturation cycle of 95°C for 10 min, followed by 40 amplification cycles of 95°C for 15 s and 60°C for 1 min and ending with one cycle at 25°C for 15 s. Analysis was performed on the data output using ABI automation software tools and Microsoft Excel XP. Relative quantification of mRNA expression was calculated by the ∆CT methods described by the manufacturer (ABI Prism 7700 Sequence Detection System, User Bulletin 2). Primer sequences for the murine genes were designed from the Roche Universal Probe Library sequence (Roche, Indianapolis, IN).

Snap-frozen forebrain samples (left hemibrains) were homogenized sequentially in RIPA buffer and 2% SDS buffer with 1× protease inhibitor mixture (Roche). The homogenate was centrifuged at 100,000 × g for 1 h at 4°C at each step. Protein concentration in supernatants was determined using the Bicinchoninic Acid Protein Assay kit (Pierce, Rockford, IL). Protein samples (20–40 μg) were separated on Bis-Tris 12% XT gels (Bio-Rad, Hercules, CA) with XT-MES buffer and transferred to 0.45 μm nitrocellulose membranes. Blots probed with the Ab CT20 (T. E. Golde; anti-APP C-terminal 20 aa; 1:1000); 82E1 (IBL; anti-Aβ 1–16; 1:1000); glial fibrillary acidic protein (GFAP) (Cell Signaling Technology, Danvers, MA; 1:1000); cd11b (Novus Biological, Littleton, CO; 1:500); C3 (Santa Cruz Biotechnology, Santa Cruz, CA, 1:100) and β-site APP-cleaving enzyme 1 (BACE1) (R. Vassar; clone 3D5; 1:500). Blots were reprobed with anti β-actin (Sigma-Aldrich; 1:1000) as a loading control. Relative band intensity was quantified using ImageJ software (National Institutes of Health, Bethesda, MD).

The mIFN-γ levels were evaluated using sandwich capture ELISA assays using RIPA soluble mouse forebrain lysates as per manufacturer’s instructions (BD OptiEIA, BD Biosciences, San Jose, CA). The results were compiled using SoftMax Pro software (Molecular Devices, Sunnyvale, CA).

For brain Aβ ELISAs from P2 injected Tg mice, hemiforebrains (left hemibrain) were sequentially homogenized in RIPA buffer, 2% SDS and 70% formic acid (FA) as described previously (19). For adult mice injected in the hippocampus, the brains were coronally dissected 1 mm anterior and posterior to the point of injection and used for subsequent analysis. Aβ levels were determined by human Aβ end-specific sandwich ELISAs as previously described (33): for Aβ42, capture with mAb 2.1.3 (human Aβx-42 specific) and detection with HRP-conjugated mAb Ab9 (human Aβ1–16 specific); for Aβ40, capture with mAb Ab9 and detection with HRP-conjugated mAb 13.1.1 (human Aβx-40 specific). Detection of endogenous mouse Aβ40 was performed using Diethyl Amine extracted brains of 5-mo-old nonTg mice injected at P2. For detection of endogenous mouse Aβ, Ab 32.4.1 (rodent Aβ1–16 specific) was used for capture, followed by HRP-conjugated mAb 13.1.1 Ab for detection. The results were analyzed using SoftMax Pro software (Molecular Device).

At various timepoints during the study, mice were sacrificed, and the right hemibrain was fixed in 4% paraformaldehyde overnight. For P2-injected mice, sagittal sections initiating from the midline were used for analysis. For adult mice injected in the hippocampus, the brain was coronally dissected at the point of injection and used for subsequent analysis. Paraffin embedded sections (6 μm thick) were immunostained using the following primary Abs and the Dako Envision Plus visualization system (Dako, Carpinteria, CA): pan Aβ Ab 33.1.1 (1:1500, human Aβ1–16 specific); Aβ42 Ab 2.1.3 (1:1000; human Aβ42 specific); Aβ40 Ab 13.1.1 (1:1000; human Aβ40 specific); anti-GFAP (Sigma-Aldrich; 1:1000); anti-ionized calcium-binding adaptor molecule 1 (Iba-1) (Wako, Richmond, VA; 1:1000); anti-EGFP (Invitrogen; 1:1000), anti-CD45 (Chemicon International, Temecula, CA; 1:50), Ly-6C (Abcam, Cambridge, MA; 1:50), MHCII (AbD Serotec, Raleigh, NC; 1:50) and anti-C3 (Abcam; 1:100). Nissl stain, Luxol Fast Blue, and von Kossa stain histological stains were performed on paraffin-embedded sections according to established procedures. Immunohistochemically stained sections were captured using the Scanscope XT image scanner (Aperio Technologies, Vista, CA) and analyzed using the ImageScope program. The final images and layouts were created using Photoshop CS2 (Adobe, San Jose, CA).

Immunostained total Aβ, Aβ42, and Aβ40 plaque burdens in the forebrain (cortex and/or hippocampus) was calculated using the Positive Pixel Count program available with the Imagescope software (Aperio Technologies). At least three sections per brain (n = 10/group for the neonatal P2→5 mo group; n = 5/group for the adult 4→5.5 mo group; n = 5/group for the 4-mo-old unmanipulated group), 30 μm apart, were averaged to calculate the plaque burden for each sample. All of the above analyses were performed in a blinded manner.

This was based on the “unbiased brick counting rule” adapted from Howard et al. (34). Briefly, paraffin-embedded brain sections were stained with Nissl stain and scanned with ScanScope XT (Aperio Technologies) at a magnification of 400× (n = 5/group). The number of cells in a fixed area of interest (a 9000 × 9000 pixel area of the hippocampus) of each sample was counted using Metamorph (Meta Imaging version 7.5.5; Molecular Devices). Ten random blocks of equal size were created, each measuring 300 × 300 Metamorph units and placed randomly within the area of interest. Stained cells touching the left and bottom edges of the blocks were not counted, and cells touching the top and right edges that were equal to or greater than 50% inside the block were counted, as well as all other cells fully placed within the block. The dimensions of the area of interest as well as the individual blocks were maintained constant throughout the analyses. At least three individual sections per sample, 30 μm apart, were averaged to calculate the final cell count. All of the above analyses were performed in a blinded manner.

Using the ImageScope software measurement tool (Metamorph), 30 cells were randomly measured within the same area of interest mentioned previously. The cell diameter was defined as the longest axis through the visible cell membrane. Only the cells placed within the same plane of focus was used for measurements in each case. The average of the 30 measurements was calculated per slide and then these were further averaged among the three triplicates for each sample.

Microglia were obtained from cerebral cortices of neonate mice (1–2 d old). Isolated cortices were minced and triturated in HBSS containing 50 μg/ml DNase I (Sigma-Aldrich). Cells were then resuspended in DMEM High Glucose media in the presence of 25 ng/ml GM-CSF (Sigma-Aldrich) to yield a primary mixed neuronal culture. Microglia were shaken off the primary mixed culture after 7 d and plated in a chamber slide system for analysis (Lab-Tek-II slide system, Fisher Scientific, Pittsburgh, PA) at a concentration of 2–4 × 105 cells/ml. Immunocytochemistry with anti–Iba-1 (1:250, Wako) was done to assess the purity of isolated microglia. All studies were conducted on cultures in which >95% of cells were positive for Iba-1. CD68 (FA-11, Abcam, 1:200) immunofluorescence was performed on 2% paraformaldehyde (containing 50 mM sucrose) fixed glia. Hilyte 568 labeled Aβ42 peptide (Anaspec, Fremont, CA) was allowed to aggregate by incubating in PBS buffer at 37°C for 6 h. The aggregated fibrillar Aβ (fAβ) 42 was then sonicated (3 × 10 s burst) to generate smaller fibrillar structures (microaggregates) for use in microglial phagocytosis assay. The glial culture in chamber slides was incubated with 200 ng/ml recombinant carrier-free mIFN-γ (R&D Systems, Minneapolis, MN) for 4 h and then after changing the culture medium, 1.5 μg sonicated preaggregated Aβ42-HilyteFluor 568 was added for 10 min at 37°C. Cells were washed in warm medium and then with sterile PBS, fixed in 2% paraformaldehyde containing 50 mM sucrose and mounted in fluorescent mounting medium containing DAPI (Vector Laboratories, Burlingame, CA) and visualized under fluorescence. All of the images were captured at the same time using the same exposure time. Unmanipulated fluorescent images were analyzed using Metamorph program. The areas of interest defined by a fixed area was used to measure average fluorescence intensity in the “red” channel using an embedded program.

Two-way ANOVA with post hoc Holm-Sidak multiple-comparison test or two-tailed Student t test was used for statistical comparison (SigmaStat 3.0 version). Variability of the estimates was reported as SE. A p value of <0.05 was considered significant and denoted by asterisks in the figures. All graphical analyses were performed using Prism 4 (GraphPad Software, GraphPad, San Diego, CA).

Two paradigms were used to evaluate the effects of rAAV1-mediated expression of mIFN-γ on Aβ pathology in APP TgCRND8 mice. The first paradigm investigated the effects of mIFN-γ expression initiated prior to the onset of plaque deposition. TgCRND8 mice pups (36–48 h old; neonatal day P2) were bilaterally injected with rAAV1–mIFN-γ or rAAV1–EGFP (control mice) into the cerebral ventricles and analyzed after 5 mo (P2→5 mo). P2 somatic brain Tg technique delivery results in expression largely localized in the choroid plexus and ependymal cells lining the ventricles, along with a few neurons in the hippocampus, cortex, and cerebellum, as measured by immunohistochemical analysis with anti EGFP Ab (Supplemental Fig. 1AH). In contrast, injection in P0 mice (0–12 h old) results in widespread transduction and expression of the transgene in mouse brain (19). In pilot studies, rAAV1–mIFN-γ injection on day P0 resulted in lethality, runted litters and general malaise indicating that neonatal P0 delivery of rAAV1–mIFN-γ is neurotoxic. In contrast, pilot studies of P2 rAAV1–mIFN-γ injections showed that it was well-tolerated; therefore, we generated larger cohorts of P2 injected mice for further investigation.

The second paradigm evaluated the effects of rAAV1–mIFN-γ or rAAV1–EGFP delivery to the hippocampus of adult 4-mo-old TgCRND8 mice. rAAV1–mIFN-γ or rAAV1–EGFP was stereotaxically injected into the hippocampus of 4-mo-old TgCRND8 mice and mice were sacrificed 6 wk later (4→5.5 mo). Immunohistochemical analysis with anti-EGFP Ab shows that the viral transgene is predominantly expressed in the hippocampal CA neurons, parts of the dentate gyrus, neuronal projections in the cortex, and some overlying cortical neurons after intrahippocampal delivery of rAAV1–EGFP (Supplemental Fig. 1IL). We have previously shown that rAAV1–EGFP expression has no effect on amyloid pathology or gliosis when compared with noninjected or PBS-injected mice (19, 33). Therefore, rAAV1–EGFP-expressing mice were used as the control cohorts in all the paradigms tested in this study.

Detailed immunohistochemical analysis of the P2→5 mo rAAV1–mIFN-γ expressing TgCRND8 mice showed extensive microgliosis and astrogliosis, compared with EGFP-expressing control mice. There was a massive increase in both GFAP reactive astrocytes and Iba-1 reactive microglia in these mice (Fig. 1A–L). Widespread Iba-1 positive reactive microglia were seen around the hippocampal CA1-CA3 region, periventricular areas, frontal cortex, basal ganglia, and cerebellum compared with control mice (Fig. 1A–F). Although Iba-1 immunostaining results in detection of all microglia in the brain, the Iba-1 reactive microglia in mIFN-γ–expressing mice displayed increased hypertrophic processes, indicating a heightened state of activation (Fig. 1F). Quantitation of Iba-1 immunostaining shows a striking increase in microglial immunoreactivity in mIFN-γ expressing mice brains compared with controls (Fig. 1M). Similarly, significant numbers of GFAP immunoreactive activated astrocytes displaying hypertrophic processes were seen in the cortex, hippocampus, midbrain, and cerebellum of P2→5-mo-old TgCRND8 mice injected with mIFN-γ compared with controls (Fig. 1G–L). Quantitation of GFAP immunoreactivity also indicates a substantial increase in astrocytic activation in mIFN-γ expressing mice compared with controls (Fig. 1M). Immunoblot analysis of the microglial activation marker CD11b/complement receptor 3 (CR3) and the astrocytic marker GFAP showed significant increases in both markers in P2→5-mo-old rAAV1–mIFN-γ injected TgCRND8 mice compared with age-matched controls (Fig. 1O, 1P). Using lysates obtained from the forebrain of P2→5 mo mice, we also demonstrate significant increases in mIFN-γ protein levels in rAAV1–mIFN-γ injected animals compared with rAAV1–EGFP injected control animals (Fig. 1N), indicating that rAAV1–mIFN-γ transduction led to expression and secretion of mIFN-γ in the brain.

FIGURE 1.

rAAV1–mIFN-γ expression in TgCRND8 mice after neonatal intracerebroventricular injection results in extensive induction of microgliosis and astrogliosis. AF, rAAV1–mIFN-γ or rAAV1–EGFP (control mice) was injected into the cerebral ventricles of TgCRND8 mice on neonatal day P2 and sacrificed after 5 mo (P2→5 mo). Representative images of Iba-1 immunoreactivity in paraffin-embedded whole brain sections (A, B) and higher magnifications of the hippocampus (lowerpanels, CF) are shown. Abundant activated microglia displaying hypertrophic processes are present in mIFN-γ–expressing mice (B, D, F) compared with EGFP-expressing control mice (A, C, E). Scale bar, 600 μm (A, B), 150 μm (C, D), and 25 μm (E, F) (n = 10/group). GL, Representative images of GFAP immunoreactivity in paraffin-embedded sections of P2→5-mo-old TgCRND8 mice expressing mIFN-γ or EGFP is depicted. Whole brain sections (G, H) along with higher magnification pictures (lowerpanels, IL) showing detailed morphology of the activated astrocytes in and around the corresponding hippocampus are shown. Abundant astrocytes are evident in mIFN-γ-expressing mice (H, J, L) compared with EGFP-expressing control mice (G, I, K). Scale bar, 600 μm (G, H), 150 μm (I, J), and 25 μm (K, L) (n = 10/group). M, Quantitation of Iba-1 and GFAP immunoreactivity burden (% area) in paraffin-embedded sections of P2→5 mo old TgCRND8 mice expressing mIFN-γ or EGFP as control (n = 5/group; *p < 0.05). N, Levels of mIFN-γ protein were increased in mIFN-γ–expressing P2→5-mo-old TgCRND8 mice brains compared with age-matched controls. mIFN-γ protein levels were analyzed using RIPA buffer solubilized brain lysates by sandwich ELISA (n = 5/group; *p < 0.05). O and P, Representative immunoblot showing increased levels of CD11b and GFAP levels in P2→5-mo-old mIFN-γ–expressing TgCRND8 mice compared with controls (O). β-actin has been used as a loading control. Intensity analysis of CD11b and GFAP immunoreactive bands normalized to β actin is depicted (P) (n = 3/group; *p < 0.05).

FIGURE 1.

rAAV1–mIFN-γ expression in TgCRND8 mice after neonatal intracerebroventricular injection results in extensive induction of microgliosis and astrogliosis. AF, rAAV1–mIFN-γ or rAAV1–EGFP (control mice) was injected into the cerebral ventricles of TgCRND8 mice on neonatal day P2 and sacrificed after 5 mo (P2→5 mo). Representative images of Iba-1 immunoreactivity in paraffin-embedded whole brain sections (A, B) and higher magnifications of the hippocampus (lowerpanels, CF) are shown. Abundant activated microglia displaying hypertrophic processes are present in mIFN-γ–expressing mice (B, D, F) compared with EGFP-expressing control mice (A, C, E). Scale bar, 600 μm (A, B), 150 μm (C, D), and 25 μm (E, F) (n = 10/group). GL, Representative images of GFAP immunoreactivity in paraffin-embedded sections of P2→5-mo-old TgCRND8 mice expressing mIFN-γ or EGFP is depicted. Whole brain sections (G, H) along with higher magnification pictures (lowerpanels, IL) showing detailed morphology of the activated astrocytes in and around the corresponding hippocampus are shown. Abundant astrocytes are evident in mIFN-γ-expressing mice (H, J, L) compared with EGFP-expressing control mice (G, I, K). Scale bar, 600 μm (G, H), 150 μm (I, J), and 25 μm (K, L) (n = 10/group). M, Quantitation of Iba-1 and GFAP immunoreactivity burden (% area) in paraffin-embedded sections of P2→5 mo old TgCRND8 mice expressing mIFN-γ or EGFP as control (n = 5/group; *p < 0.05). N, Levels of mIFN-γ protein were increased in mIFN-γ–expressing P2→5-mo-old TgCRND8 mice brains compared with age-matched controls. mIFN-γ protein levels were analyzed using RIPA buffer solubilized brain lysates by sandwich ELISA (n = 5/group; *p < 0.05). O and P, Representative immunoblot showing increased levels of CD11b and GFAP levels in P2→5-mo-old mIFN-γ–expressing TgCRND8 mice compared with controls (O). β-actin has been used as a loading control. Intensity analysis of CD11b and GFAP immunoreactive bands normalized to β actin is depicted (P) (n = 3/group; *p < 0.05).

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Focal expression of rAAV1–mIFN-γ in the hippocampus (adult 4→5.5 mo paradigm) also resulted in robust reactive microgliosis (Supplemental Fig. 2AF) and astrogliosis (Supplemental Fig. 2GL) compared with rAAV1–EGFP-expressing control mice, especially in and around the hippocampus. Quantification of Iba-1 and GFAP immunoreactivity showed a massive increase in both markers in mIFN-γ–expressing mice compared with controls (Supplemental Fig. 2M). In addition, immunoblot analysis also showed significant increases in CD11b/CR3 and GFAP levels in mIFN-γ–expressing mice compared with age-matched controls (Supplemental Fig. 2O, 2P). ELISA analysis of mIFN-γ levels from RIPA soluble brain lysates (dissected 1 mm anterior and 1 mm posterior to the injection site) confirmed a significant increase in mIFN-γ protein levels in rAAV1–mIFN-γ injected animals compared with age-matched controls (Supplemental Fig. 2N).

Next, we characterized the pathological attributes of mIFN-γ expression in P2→5 mo APP TgCRND8 mice. In addition to reactive gliosis, mice expressing mIFN-γ developed mineralized deposits in the thalamus and basal ganglia (Supplementa Fig. 3A, 3B). However, in 4→5.5 mo TgCRND8 mice, no calcification was evident, suggesting that this is an age- and dose-dependent effect of mIFN-γ in brain (Supplemental Fig. 3C, 3D). The focal mineralization stained positive with von Kossa indicating presence of calcium (Supplemental Fig. 3E). In all cases examined, the hippocampus and frontal cortex were spared of dystrophic calcification (Supplemental Fig. 3E, inset 1). CD3 immunopositive T cells were not seen in the hippocampus and frontal cortex of mIFN-γ–expressing mice (Supplemental Fig. 3FK). As a positive control for CD3 immunohistochemical reactivity, we included a brain section from genotype and age-matched CRND8 mice injected with rAAV1–TNF-α, which shows copious amounts of CD3 immunoreactivity in the brain parenchyma (Supplemental Fig. 3H, 3K). To determine whether mIFN-γ overexpression affected neuronal viability, we performed image analysis of Nissl stained hippocampal neurons in mIFN-γ–expressing TgCRND8 mice. Quantification of the pyramidal layer showed a 14% decrease in cell number in mIFN-γ injected mice compared with control mice; although no statistically significant change in cell diameter was evident (Supplemental Fig. 3LN).

We analyzed the effects of mIFN-γ expression on Aβ deposition in the various expression paradigms. P2→5 mo TgCRND8 mice expressing rAAV1–mIFN-γ had significantly lower Aβ levels compared with rAAV1–EGFP-expressing control mice as demonstrated by both immunohistological and biochemical analyses (Fig. 2). There was a significant decrease in Aβ plaque burdens in the mIFN-γ injected animals as shown by Aβ immunostaining (Fig. 2A–H). Quantification of Aβ plaque immunoreactivity in the forebrain and hippocampus of the P2→5 mo mIFN-γ injected TgCRND8 mice showed a 73% and 70% reduction in plaque burden, respectively (Fig. 2I, 2J). Biochemical analysis of Aβ levels in the SDS and FA solubilized mice brain lysates showed a similar magnitude of decrease in Aβ deposition after mIFN-γ–expression. In P2→5 mo mIFN-γ injected TgCRND8 mice, Aβ42 levels was decreased by 65% in the SDS and 79% in the FA fractions compared with control mice (Fig. 2K, 2L). Similarly, Aβ40 levels was decreased by 83% in the SDS and 85% in the FA fractions compared with control mice (Fig. 2K, 2L).

FIGURE 2.

Significant attenuation of amyloid deposition in mIFN-γ–expressing (P2→5 mo) TgCRND8 mice. AH, rAAV1–mIFN-γ or rAAV1–EGFP was injected into the cerebral ventricles of TgCRND8 mice on neonatal day P2 and sacrificed after 5 mo (P2→5 mo). The mIFN-γ–expressing TgCRND8 mice (A, CE) were analyzed along with age-matched EGFP-expressing mice (B, F–H, control). Representative sections of the whole brain (A, B) as well as hippocampus (CH) from three mice from each group is shown following pan Aβ immunostaining. Scale bar, 600 μm (A, B), 150 μm (C–H) (n = 10–12/group). I and J, Image analysis of amyloid plaque immunoreactivity shows a significant decrease in Aβ plaque burdens in the forebrain (I) and hippocampus (J) of mIFN-γ–expressing mice compared with EGFP-expressing control mice (n = 10–12/group; *p < 0.05). K and L, Biochemical analyses of Aβ42 and Aβ40 levels in P2→5-mo-old mIFN-γ–expressing TgCRND8 mice compared with EGFP-expressing age-matched controls. Both SDS-soluble and SDS-insoluble (FA fraction) Aβ42 and Aβ40 levels in the forebrain of mIFN-γ injected mice were significantly reduced compared with control mice (n = 10/group; *p < 0.05; **p < 0.05).

FIGURE 2.

Significant attenuation of amyloid deposition in mIFN-γ–expressing (P2→5 mo) TgCRND8 mice. AH, rAAV1–mIFN-γ or rAAV1–EGFP was injected into the cerebral ventricles of TgCRND8 mice on neonatal day P2 and sacrificed after 5 mo (P2→5 mo). The mIFN-γ–expressing TgCRND8 mice (A, CE) were analyzed along with age-matched EGFP-expressing mice (B, F–H, control). Representative sections of the whole brain (A, B) as well as hippocampus (CH) from three mice from each group is shown following pan Aβ immunostaining. Scale bar, 600 μm (A, B), 150 μm (C–H) (n = 10–12/group). I and J, Image analysis of amyloid plaque immunoreactivity shows a significant decrease in Aβ plaque burdens in the forebrain (I) and hippocampus (J) of mIFN-γ–expressing mice compared with EGFP-expressing control mice (n = 10–12/group; *p < 0.05). K and L, Biochemical analyses of Aβ42 and Aβ40 levels in P2→5-mo-old mIFN-γ–expressing TgCRND8 mice compared with EGFP-expressing age-matched controls. Both SDS-soluble and SDS-insoluble (FA fraction) Aβ42 and Aβ40 levels in the forebrain of mIFN-γ injected mice were significantly reduced compared with control mice (n = 10/group; *p < 0.05; **p < 0.05).

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In the 4→5.5 mo treatment paradigm, after immunohistochemical staining for Aβ, a 50% decrease in Aβ plaque burden was seen within the dissected coronal section in the mIFN-γ–expressing mice compared with EGFP injected mice (Fig. 3A–F, 3J). There was a 34% and 58% decrease in SDS extractable Aβ42 and Aβ40 levels, respectively, in mIFN-γ–expressing mice compared with controls (Fig. 3K). The FA fractions showed a 76% reduction in Aβ42 and a 47% reduction in Aβ40 levels in rAAV1–mIFN-γ–expressing mice compared with controls (Fig. 3L).

FIGURE 3.

Amyloid deposition is suppressed after acute focal expression of mIFN-γ in the hippocampus of TgCRND8 mice. AI, The 4-mo-old TgCRND8 mice were stereotaxically injected in the hippocampus with either rAAV1–mIFN-γ or rAAV1–EGFP and sacrificed after 6 wk. Representative brain sections stained with pan Aβ Ab depict attenuation of Aβ deposition in mIFN-γ–expressing mice (D–F) compared with EGFP injected controls (A–C) in the immediate vicinity of the injection site. Unmanipulated 4-mo-old TgCRND8 brains, dissected at the same level, are depicted (G–I). Scale bar, 150 μm (n = 5/group). J, Aβ plaque burden analysis shows a significant decrease in amyloid deposition in 5.5-mo-old mIFN-γ–expressing mice compared with EGFP-expressing age-matched control mice. The Aβ plaque burden in the 5.5-mo-old mIFN-γ–expressing mice remains higher than the plaque burden of unmanipulated 4-mo-old TgCRND8 (n = 5/group; *p < 0.05). K and L, Biochemical analyses of Aβ42 and Aβ40 levels by ELISA show significant reductions in both SDS-soluble (K) and SDS-insoluble FA fractions (L) in mIFN-γ expressing mice compared with controls (n = 5/group; *p < 0.05; **p < 0.05).

FIGURE 3.

Amyloid deposition is suppressed after acute focal expression of mIFN-γ in the hippocampus of TgCRND8 mice. AI, The 4-mo-old TgCRND8 mice were stereotaxically injected in the hippocampus with either rAAV1–mIFN-γ or rAAV1–EGFP and sacrificed after 6 wk. Representative brain sections stained with pan Aβ Ab depict attenuation of Aβ deposition in mIFN-γ–expressing mice (D–F) compared with EGFP injected controls (A–C) in the immediate vicinity of the injection site. Unmanipulated 4-mo-old TgCRND8 brains, dissected at the same level, are depicted (G–I). Scale bar, 150 μm (n = 5/group). J, Aβ plaque burden analysis shows a significant decrease in amyloid deposition in 5.5-mo-old mIFN-γ–expressing mice compared with EGFP-expressing age-matched control mice. The Aβ plaque burden in the 5.5-mo-old mIFN-γ–expressing mice remains higher than the plaque burden of unmanipulated 4-mo-old TgCRND8 (n = 5/group; *p < 0.05). K and L, Biochemical analyses of Aβ42 and Aβ40 levels by ELISA show significant reductions in both SDS-soluble (K) and SDS-insoluble FA fractions (L) in mIFN-γ expressing mice compared with controls (n = 5/group; *p < 0.05; **p < 0.05).

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To help determine whether the reduction in Aβ levels is attributable to actual clearance of predeposited plaques or attenuation of additional deposition, we analyzed Aβ plaque burdens within the dissected coronal section of the 4→5.5 mo experimental cohorts and compared with Aβ plaque burden in control 4 mo old TgCRND8 mice that had not undergone any interventions (Fig. 3, Supplemental Fig. 4). Immunohistochemical analysis revealed that the forebrain Aβ plaque burden in the 5.5-mo-old mIFN-γ–expressing mice was significantly reduced compared with age matched EGFP-expressing controls (Fig. 3A–F), whereas, the total Aβ plaque burden of 4-mo-old control mice was lower than the 5.5-mo-old mIFN-γ–expressing mice (Fig. 3G–J). To further probe whether there was a difference in the “cored” plaques and “diffuse” plaques in the 5.5-mo-old mIFN-γ–expressing mice compared with the age-matched controls and unmanipulated 4-mo-old controls, we quantified the forebrain plaque burden after immunostaining with Aβ40 specific Ab (indicative of “cored” Aβ plaques; Supplemental Fig. 4DF) and Aβ42 specific Ab (indicative of both “diffuse” and “cored” Aβ plaques; Supplemental Fig. 4AC). There was a 45% decrease in Aβ42 plaque burden and a 32% decrease in Aβ40 plaque burden in the 5.5-mo-old mIFN-γ–expressing mice compared with age-matched EGFP-expressing controls (Supplemental Fig. 4G). However, both the Aβ42 and the Aβ40 burden of the unmanipulated 4-mo-old group was lower than the mIFN-γ–expressing mice (Supplemental Fig. 4G).

To investigate whether mIFN-γ induced reduction in Aβ levels in TgCRND8 mice is due to changes in APP processing or Aβ production, we conducted additional studies. We first measured APP levels in the RIPA extracted brains of mIFN-γ overexpressing P2→5 mo and 4→5.5 mo TgCRND8 mice. We did not detect any significant changes in APP levels between control and mIFN-γ overexpressing animals in P2→5 mo cohorts (Fig. 4A, 4B). Nor were there any significant changes apparent in APP processing as measured by quantitation of APP C-terminal fragments (CTFα and CTFβ) in the P2→5 mo mIFN-γ injected group compared with controls (Fig. 4C, 4D). Similarly, in the 4→5.5 mo mIFN-γ injected adult TgCRND8 mice, no changes in APP levels or CTFα levels were seen (Fig. 4E, 4F).

FIGURE 4.

APP processing is not significantly altered in mIFN-γ–expressing P2→5-mo-old TgCRND8 mice. A and B, Representative anti CT20 immunoblot depicting APP levels in mIFN-γ–expressing P2→5-mo-old TgCRND8 and age-matched control mice (A). Intensity analysis of anti-CT20 immunoreactive APP bands normalized to β-actin reveal no significant changes in APP levels in mIFN-γ–expressing TgCRND8 mice compared with age-matched controls (B) (n = 4/group). C and D, Representative immunoblot showing CTFα (anti-CT20) and CTFβ (anti-82E1) levels in P2→5-mo-old TgCRND8 mice expressing mIFN-γ or EGFP (C). Intensity analysis of CTFα and CTFβ bands normalized to β-actin reveal no significant changes in P2→5-mo-old TgCRND8 mice expressing mIFN-γ compared with age-matched controls (D) (n = 3/group). E and F, Representative anti-CT20 immunoblot showing APP or CTFα levels in mIFN-γ expressing 4→5.5-mo-old TgCRND8 mice and age-matched controls (E). Intensity analysis of APP and CTFα levels normalized to β-actin show no significant changes in 4→5.5-mo-old TgCRND8 mice expressing mIFN-γ compared with age-matched controls (F) (n = 5/group).

FIGURE 4.

APP processing is not significantly altered in mIFN-γ–expressing P2→5-mo-old TgCRND8 mice. A and B, Representative anti CT20 immunoblot depicting APP levels in mIFN-γ–expressing P2→5-mo-old TgCRND8 and age-matched control mice (A). Intensity analysis of anti-CT20 immunoreactive APP bands normalized to β-actin reveal no significant changes in APP levels in mIFN-γ–expressing TgCRND8 mice compared with age-matched controls (B) (n = 4/group). C and D, Representative immunoblot showing CTFα (anti-CT20) and CTFβ (anti-82E1) levels in P2→5-mo-old TgCRND8 mice expressing mIFN-γ or EGFP (C). Intensity analysis of CTFα and CTFβ bands normalized to β-actin reveal no significant changes in P2→5-mo-old TgCRND8 mice expressing mIFN-γ compared with age-matched controls (D) (n = 3/group). E and F, Representative anti-CT20 immunoblot showing APP or CTFα levels in mIFN-γ expressing 4→5.5-mo-old TgCRND8 mice and age-matched controls (E). Intensity analysis of APP and CTFα levels normalized to β-actin show no significant changes in 4→5.5-mo-old TgCRND8 mice expressing mIFN-γ compared with age-matched controls (F) (n = 5/group).

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To further probe whether mIFN-γ influences the endogenous levels of APP or Aβ through cellular interaction with transcriptional or posttranscriptional mechanisms, we also analyzed the effects of rAAV1–mIFN-γ expression in P2→5 mo APP TgCRND8 non-Tg littermates. We did not detect any change in endogenous APP levels (Supplemental Fig. 5A, 5B) or in steady-state levels of endogenous Aβx–40 levels between the mIFN-γ injected mice and control cohorts (Supplemental Fig. 5C). To investigate whether mIFN-γ expression could alter the steady-state Aβ levels in young Tg2576 mice, neonatal Tg2576 pups were injected with rAAV1–mIFN-γ or rAAV1–EGFP. Steady-state APP and Aβ40 levels were analyzed at 3 mo of age, well before the onset of Aβ deposition, to avoid interference from possible contamination of deposited Aβ plaques in the ELISA measurements. Despite significantly increased gliosis in the brains of mIFN-γ–expressing Tg2576 mice (data not shown), there was no statistically significant changes in APP and CTF levels (Supplemental Fig. 5D, 5E) or in steady-state Aβ40 levels in rAAV1–mIFN-γ–expressing mice compared with the EGFP injected mice (Supplemental Fig. 5F). Thus, our current data show that, even in the presence of high levels of mIFN-γ expression in the brain, there is no significant change in either APP processing or steady-state Aβ production levels in APP Tg and non-Tg littermates in vivo.

Next, we investigated whether the attenuation in Aβ levels is due to alterations in Aβ degrading enzymes, like Neprilysin or insulin-degrading enzyme. QRT-PCR analysis showed no change in mRNA transcript levels in either of these enzymes in mIFN-γ–expressing TgCRND8 mice compared with controls (Supplemental Fig. 6A). Because IFN-γ has been reported to induce BACE expression by direct binding of STAT1 to BACE1 promoter in astrocytic cultures (35), we investigated whether increased glial activation in the mIFN-γ–expressing mice leads to alterations in BACE1 levels. We did not detect any significant change in BACE1 levels in mIFN-γ–expressing TgCRND8 mice compared with controls despite increased glial activation in these mice (Supplemental Fig. 6B, 6C).

In the absence of detectable changes in steady state Aβ levels, APP expression and APP processing, we first explored whether the amelioration of Aβ deposition in mIFN-γ–expressing TgCRND8 mice could be due to enhanced phagocytosis of Aβ aggregates by activated microglia. Although it has been shown that IFN-γ–stimulated microglia can readily phagocytose Aβ (29), inhibitory effects of IFN-γ on microglia Aβ uptake has also been described (36). To confirm whether mIFN-γ stimulated microglial phagocytosis is an underlying mechanism of Aβ attenuation in the mIFN-γ–expressing mice, we performed in vitro Aβ phagocytosis assay (Supplemental Fig. 7). Using mouse primary microglial cells, we show that pretreatment with recombinant mIFN-γ upregulates the expression of CD68 (Scavenger Receptor class D), an endosomal/lysosomal marker associated with increased phagocytosis (Supplemental Fig. 7AC). Using fluorescent tagged fAβ42 aggregates (Hilyte 568-fAβ42), we also detected increased fAβ42 uptake by the mouse microglia cells that were primed with recombinant mIFN-γ compared with untreated glia (Supplemental Fig. 7DF).

CD45 is an established marker for peripheral macrophages that have infiltrated the CNS. Therefore, we examined whether increased levels of CD45 as well as MHCII is associated with Congophilic plaques in mIFN-γ expressing mice (Supplemental Fig. 8AD). We found that these Abs worked optimally on paraffin-embedded mouse spleen sections (Supplemental Fig. 8A). However, there was no detectable CD45 (Supplemental Fig. 8BD) or MHCII (data not shown) immunostaining around the Congophilic plaques in either the P2→5 mo or the 4→5.5 mo experimental groups. To further probe the involvement of peripheral immune cells in Aβ removal, we used Ly-6c, a marker for bone marrow-derived inflammatory monocytes (37), in conjunction with Congo Red histological stain. Blood-derived Ly-6ChiCCR2+ monocytes were shown to specifically accumulate in CNS lesions and differentiate into microglia (38). Therefore, to determine whether there is influx of bone marrow-derived monocytes in the brain after mIFN-γ expression, we performed anti–Ly-6c immunostaining on paraffin-embedded brain sections of both P2→5 mo as well as 4→5.5-mo-old mIFN-γ expressing mice. Although scattered Ly-6C+ cells with the morphologic appearance of monocytes were present in the parenchyma of both the P2→5 mo and the 4→5.5-mo-old mIFN-γ–expressing mice brains, none were associated with Congophilic plaques in these mice (Supplemental Fig. 8EH).

We evaluated the expression status of multiple microglial markers in vivo by using QRT-PCR of mRNA transcripts in the forebrains of P2→5 mo mIFN-γ–TgCRND8 mice. There were significant increases in MHC class I, MHCII, and CD11c transcript levels in mIFN-γ expressing mice compared with controls (Fig. 5A). We noticed modest increases in inducible NOS, Scavenger Receptor class A and CD68 (Fig. 5A). Because, it has been shown that the chemokine receptor CCR2 is critical for the emigration of Ly-6ChiCCR2+ monocytes from the bone marrow (39), we investigated CCR2 levels and found it to be increased in the brains of 5-mo-old mIFN-γ–expressing mice (Fig. 5A). However, analysis of two alternative “M2” microglial phenotype markers, Ym-1 and Arg, that have been recently reported as potential markers for enhanced microglia-mediated Aβ phagocytosis (40, 41) showed that these were unchanged in mIFN-γ–expressing mice (Fig. 5A). We then performed QRT-PCR analysis of murine cytokine mRNA transcript levels and observed significant increases in IFN-γ and TNF-α transcript levels (Fig. 5B). No significant changes were seen in the transcript levels of IL-1β, IL-6, IL-4, TGF-β, and IL-10 (Fig. 5B).

FIGURE 5.

The mIFN-γ expression leads to alterations in glial activation markers and proinflammatory cytokines. Expression of glial activation markers (A) and cytokines (B) were determined in P2→5-mo-old mIFN-γ–expressing TgCRND8 mice compared with EGFP-expressing age-matched Tg controls using QRT-PCR. Relative quantitation of mRNA transcript levels was performed using the comparative cycle threshold method. The expression levels of different genes were normalized using β-actin levels from the corresponding samples. Data, expressed as relative units of mRNA expression, represents averaged fold change values obtained from mIFN-γ–expressing mice, relative to averaged values obtained from EGFP-expressing mice. The horizontal line represents the reference point used for relative mRNA analysis. Error bars indicate SEM. (n = 4/group; *p < 0.05).

FIGURE 5.

The mIFN-γ expression leads to alterations in glial activation markers and proinflammatory cytokines. Expression of glial activation markers (A) and cytokines (B) were determined in P2→5-mo-old mIFN-γ–expressing TgCRND8 mice compared with EGFP-expressing age-matched Tg controls using QRT-PCR. Relative quantitation of mRNA transcript levels was performed using the comparative cycle threshold method. The expression levels of different genes were normalized using β-actin levels from the corresponding samples. Data, expressed as relative units of mRNA expression, represents averaged fold change values obtained from mIFN-γ–expressing mice, relative to averaged values obtained from EGFP-expressing mice. The horizontal line represents the reference point used for relative mRNA analysis. Error bars indicate SEM. (n = 4/group; *p < 0.05).

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We also analyzed both mRNA transcript levels and protein levels of components of the complement system as IFN-γ has been previously shown to directly stimulate transcription or stabilize complement C3 and C4 mRNAs (42, 43). QRT-PCR analysis revealed significant upregulation of complement C1q, C3, and C4a mRNA transcript levels in mIFN-γ expressing mice compared with age-matched controls (Fig. 6A). Complement C5a and mouse CR1/2 mRNA transcript levels were not altered (Fig. 6A). Immunoblotting analysis showed that the protein levels of C3 were also significantly increased in mIFN-γ–expressing TgCRND8 mice compared with age-matched controls (Fig. 6B, 6C). Immunofluorescence analysis also showed increased immunoreactivity of neuronally expressed complement protein C3 in mIFN-γ–expressing mice (Fig. 6D–I).

FIGURE 6.

The mIFN-γ expression leads to increased levels of complement protein C3 in 5 mo old TgCRND8 mice. A, Increased mRNA transcript levels of complement protein C1q, C3, and C4a as determined by QRT-PCR in P2→5-mo-old TgCRND8 mice expressing mIFN-γ or EGFP. Relative quantitation of mRNA expression was performed using the comparative cycle threshold method. The expression levels of different genes were normalized using β-actin levels from the corresponding samples. Data, expressed as relative units of mRNA expression, represents averaged fold change values obtained from mIFN-γ–expressing mice, relative to averaged values obtained from EGFP-expressing mice. The horizontal line represents the reference point used for relative mRNA analysis. Error bars indicate SEM. (n = 4/group; *p < 0.05). B and C, Representative immunoblot depicting complement C3 protein levels in P2→5-mo-old TgCRND8 mice expressing mIFN-γ or EGFP (B). Quantitative analysis of anti-C3 positive immunoreactive band normalized to β-actin shows significantly increased levels of C3 in P2→5 mo TgCRND8 mice expressing mIFN-γ compared with age-matched controls (C) (n = 4/group; *p < 0.05). D–I, Representative images depicting anti-C3 immunofluorescence staining (red stain) colocalizing with β-tubulin immunoreactive neurons (green stain) in the hippocampus of mIFN-γ–expressing P2→5-mo-old TgCRND8 mice compared with controls. Blue represents the DAPI stained nuclei (original magnification ×600) (n = 3/group).

FIGURE 6.

The mIFN-γ expression leads to increased levels of complement protein C3 in 5 mo old TgCRND8 mice. A, Increased mRNA transcript levels of complement protein C1q, C3, and C4a as determined by QRT-PCR in P2→5-mo-old TgCRND8 mice expressing mIFN-γ or EGFP. Relative quantitation of mRNA expression was performed using the comparative cycle threshold method. The expression levels of different genes were normalized using β-actin levels from the corresponding samples. Data, expressed as relative units of mRNA expression, represents averaged fold change values obtained from mIFN-γ–expressing mice, relative to averaged values obtained from EGFP-expressing mice. The horizontal line represents the reference point used for relative mRNA analysis. Error bars indicate SEM. (n = 4/group; *p < 0.05). B and C, Representative immunoblot depicting complement C3 protein levels in P2→5-mo-old TgCRND8 mice expressing mIFN-γ or EGFP (B). Quantitative analysis of anti-C3 positive immunoreactive band normalized to β-actin shows significantly increased levels of C3 in P2→5 mo TgCRND8 mice expressing mIFN-γ compared with age-matched controls (C) (n = 4/group; *p < 0.05). D–I, Representative images depicting anti-C3 immunofluorescence staining (red stain) colocalizing with β-tubulin immunoreactive neurons (green stain) in the hippocampus of mIFN-γ–expressing P2→5-mo-old TgCRND8 mice compared with controls. Blue represents the DAPI stained nuclei (original magnification ×600) (n = 3/group).

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Proinflammatory stimuli, including cytokines like IL-1β, IL-6, and IFN-γ, in the brain have been proposed to exacerbate existing AD neuropathology (18, 44). In this study, we used two different in vivo experimental paradigms to investigate the role of mIFN-γ on Aβ accumulation: the P2→5 mo expression paradigm that examines largely non-neuronal expression of mIFN-γ in the brain and the 4→5.5 mo expression paradigm, that tests the neuronal expression of mIFN-γ (in the hippocampus). In both of these experimental procedures, we observed comparable levels of glial activation and Aβ attenuation. The widespread presence of activated glia in both these paradigms indicates that noncell autonomous effects of mIFN-γ are likely responsible for the glial phenotype and Aβ suppression. An initial assessment of cognitive performance did not demonstrate a beneficial effect in mIFN-γ–expressing mice after Aβ reduction (data not shown). However, due to additional pathology induced by mIFN-γ in both the Tg and non-Tg animals (basal ganglia calcification), we believe that these studies are highly confounded by other effects of mIFN-γ, and due to premature mortality induced by the APP transgene and mIFN-γ, were not sufficiently powered to detect subtle effects.

A proposed pathogenic role for IFN-γ and other proinflammatory mediators in AD is largely rooted in previous reports showing that proinflammatory cytokines upregulate APP expression, APP processing, and Aβ production leading to enhanced Aβ accumulation and self-perpetuation of Aβ aggregate-induced neurotoxicity (11, 13, 27, 44). In this study, we demonstrate that CNS expression of mIFN-γ does not significantly alter APP processing as we did not observe any changes in APP levels in Tg mice from both experimental paradigms. In addition, we did not observe any changes in BACE1 or Aβ degrading enzyme (i.e., insulin-degrading enzyme and Neprilysin) levels in mIFN-γ–expressing TgCRND8 mice. Importantly, we did not observe any change in the steady-state Aβ production in young APP Tg mice expressing mIFN-γ. Notably, we also did not observe any changes in endogenous APP or Aβ levels in APP non-Tg mice, demonstrating that mIFN-γ induced neuroinflammation in the brain does not transcriptionally alter the amyloidogenic pathway during the early phases of plaque deposition. Our data refutes the notion that a proinflammatory stimulus alters APP processing and drives further Aβ production, leading to a “cytokine cycle” (44). The reasons for these disparate results may be explained by the fact that these studies were performed in vitro using cultured neurons or astrocytes and thus may be limited by the absence of other contributing factors (i.e., transcriptional or translational) that may be crucially involved in an in vivo setting. In addition to our studies having been done in vivo, we tested mice from two different temporal expression paradigms, notably the P2→5 mo and the 4→5.5-mo-old mIFN-γ mice and their non-Tg cohorts, which adds strength to our hypothesis that mIFN-γ does not lead to a self-reinforcing amyloidogenic feedback loop over time that promotes further Aβ deposition. Rather, our data shows that expression of mIFN-γ results in significant Aβ attenuation in TgCRND8 mice, irrespective of whether mIFN-γ expression is initiated prior to Aβ deposition or in adult mice with pre-existing Aβ deposits. Activated microglia have been previously reported to clear soluble Aβ as well as Aβ aggregates both in vitro and in vivo (4549). Indeed, IFN-γ by itself has been shown to potently activate monocytes and macrophages, resulting in enhanced pinocytosis and receptor-mediated phagocytosis (reviewed in Ref. 20). In the absence of detectable changes in steady state Aβ levels, APP expression and APP processing, and our own evidence that that mIFN-γ stimulated microglia can readily phagocytose Aβ, we believe that mIFN-γ induced phagocytosis of aggregated Aβ by activated microglia may constitute a key pathway for the attenuation of Aβ deposition observed.

The mIFN-γ expression in vivo resulted in significant upregulation of multiple microglial markers, including MHC class I, MHCII, CD11b, and CD11c. This microglial phenotype is reminiscent of a dendritic-like cell presentation previously reported to have a beneficial role in Aβ clearance under different experimental conditions (29, 55). Specifically, IFN-γ expression has been reported to enhance Aβ clearance by activating CD11b/CD68 positive microglia and possible interactions with Aβ reactive CD4+ T cells after Aβ vaccination in APP/IFN-γ bigenic mice (29). Treatment of APP mice with glatiramer acetate was also reported to enhance Aβ clearance in APP Tg mice by inducing Th1 T cell responses and inducing a dendritic cell-like APC phenotype in microglia (55, 56). We, however, did not detect T cells in the forebrains of the mIFN-γ–expressing mice.

Another possibility is the involvement of peripheral macrophages and bone marrow-derived monocytes that have been previously implicated as mediators in plaque clearance in APP mouse models (5759). Recent studies have defined the phenotype of bone marrow-derived monocytes recruited to the brain as being Ly-6ChiCCR2+CX3CR1lo monocytes (37, 38). Although we did find Ly-6C positive cells in the parenchyma of mIFN-γ–expressing mouse brains in both experimental groups, none were directly associated with Aβ plaques. QRT-PCR analysis also showed a modest increase in CCR2 in the brain of P2→5-mo-old mIFN-γ–expressing mice. Such data are consistent with an infiltration of bone marrow-derived monocytes in the brain and that these cells may potentially be involved in the attenuation of amyloid deposition. However, because they do not appear to be directly associated with plaques, additional studies will be needed to determine whether peripheral monocyte infiltration in this paradigm contributes to the observed reduction in Aβ accumulation.

A recent study reported that 10 mo of rAAV1-human IFN-γ expression in the hippocampus of triple Tg 3XTg mice resulted in increased microgliosis, unaltered astrocytosis, and decreased τ pathology (28). No alterations in APP were noted, supporting our observations that proinflammatory cytokines are not amyloidogenic. However, the authors reported that intracellular Aβ immunoreactivity in these mice was significantly increased. Given the low levels of human IFN-γ expression in this model and no data with regards to Aβ plaque deposition, it is difficult to draw any parallels between our observations in TgCRND8 mice and the 3×Tg mice, especially because of the paucity of intracellular Aβ immunoreactivity in the TgCRND8 model.

To further define the microglial phenotype observed in this paradigm, we analyzed a subset of macrophage phenotypic markers recently described to be associated with Aβ clearance (40, 41). The mIFN-γ activated microglia in our study resemble the classical M1 phenotype as opposed to the alternative M2 phenotype (40). Although the M2 microglial phenotype has been hypothesized to be associated with enhanced Aβ removal (40), our data suggest that M1 microglia may be equally proficient in restricting Aβ pathology. Indeed, the nature of the inflammatory initiator and the context, timing and strength of the response are likely to be critically important factors that determine the experimental outcome. Therefore, it is challenging to define a restricted subset of microglial markers as predictive of the beneficial microglial function. Nevertheless, in this study, we have provided several lines of evidence to support a direct beneficial role of microglial activation with respect to suppression of Aβ deposition in vivo after expression of mIFN-γ.

Several recent studies have explored the relationship between complement proteins and Aβ (reviewed in Ref. 60). Inhibition of the C3 convertase using a soluble CR sCrry resulted in increased Aβ accumulation, demonstrating a potential beneficial role of complement C3 in Aβ removal (61). Similarly, C3-deficient APP Tg mice show accelerated Aβ deposition (62). Complement C1q in association with Aβ deposits has also been thought to have a protective function by enhancing clearance of cellular debris and protecting neurons against Aβ toxicity (63). In our study, complement system components (e.g., C1q and C3) were significantly upregulated in mIFN-γ–expressing APP mice suggesting the potential beneficial role of complement proteins in Aβ attenuation. Because complement opsonins (C1q, and C3b) interact with surface receptors to promote phagocytosis, it is possible that a synergistic interaction between activated glia and complement proteins may contribute to enhanced Aβ phagocytosis.

Considering the complexities in real-time imaging techniques to monitor Aβ clearance in vivo (47), direct evidence irrevocably showing the mechanism of glial Aβ clearance is challenging. Aβ has been colocalized within microglial endolysosomal compartments (46), providing indirect evidence supporting Aβ uptake by glia, and numerous in vitro studies show that in culture microglia can phagocytose Aβ aggregates (49). In our current study, the Aβ plaque burden of the 4→5.5 mo mIFN-γ–expressing mice was higher than the pretreatment levels, suggesting either that the main effect was attenuation of deposition as opposed to actual clearance or that ongoing and accelerating rate of deposition exceeded the rate of clearance. Future studies in inducible APP mice in which plaque growth can be essentially halted by turning off the APP transgene or using multiphoton microscopy to monitor plaque size alterations in real-time in vivo (47) in response to IFN-γ will be useful in distinguishing between these possibilities.

The relationship between microglial activity and Aβ deposition is clearly a complex one, likely to be dependent on a number of factors. Of interest is a recent report in which microglia were completely ablated for a 4-wk period in APP mice crossed to CD11b-HSVTK mice (50). It was shown that absence of microglia, after ganciclovir treatment for 4 wk, did not significantly affect plaque formation or plaque maintenance or amyloid-associated neuritic dystrophy (50). Although this analysis was done is a relatively short time frame, this study certainly raises the question that microglia may have limited ability to remove Aβ plaques once they are deposited (51). In contrast, our study, and others have demonstrated the feasibility of activating microglia using innate immune mediators, namely, IL-1β (14), IL-6 (19), M-CSF (52), TLR (17), or anti-Aβ Abs (53, 54) to clear or attenuate Aβ deposition in vivo. Thus, although naive or basally activated brain resident microglia may not have the ability to remove plaques or alter the course of amyloid deposition, hyper activation of microglia or recruitment of bone marrow-derived peripheral monocytes into the brain under a variety of conditions may lead to enhanced Aβ phagocytosis and attenuation of Aβ deposition.

Previous studies in genotypically diverse mouse models have shown that IFN-γ or IFN-α expression leads to tissue calcification (64, 65). We also find that mIFN-γ expression in P2→5-mo-old APP TgCRND8 mice leads to calcification in the basal ganglia and thalamus. Although CNS calcification could influence amyloid deposition, we observed robust suppression of Aβ deposition in the 4→5.5 mo expression paradigm with no accompanying calcification. Moreover, in the age range investigated (under 5.5 mo of age), Aβ plaques are primarily deposited in the hippocampus and frontal cortex of TgCRND8 Tg mice, whereas the calcification is restricted to the basal ganglia and thalamus. Thus in the adult hippocampal injection paradigm, we see removal of Aβ without calcification and in the neonatal paradigm, the Aβ removal and occurrence of calcified deposits is spatially distinct. This suggests that basal ganglia calcification and Aβ attenuation are separate and unrelated events.

In summary, we find mIFN-γ expression in brains of TgCRND8 mice resulted in 1) striking glial activation and upregulation of microglial activation markers MHCII, CD11b, and CD11c; 2) upregulation of select complement factors in vivo; 3) modest levels of Ly-6c+ monocyte infiltration into the brain; 4) increased fAβ phagocytosis by mIFN-γ primed mouse microglia in vitro; 5) robust suppression of Aβ deposition in vivo; and 6) no evidence for alterations in APP processing or steady state Aβ levels. Our current results along with other recently published studies suggest that activated innate immune system can significantly restrict Aβ deposition early in the disease process. However, the fact that Aβ aggregates continue to accumulate in the brain with age indicates that the resulting immune response to Aβ aggregates is clearly ineffective. This ineffective clearance may then result in a basal level of chronic immune activation that may contribute to AD type neurodegeneration (18). Although it may be feasible to transiently and selectively activate microglia to modify Aβ deposition in a manner that is both effective and tolerable, any intervention for AD based on activation of the innate immune system clearly must strike a balance between neuroprotective and neurotoxic effects.

We thank Monica Castanedes-Casey, Virginia Phillips, and Linda Rousseau for assistance with tissue processing and immunohistochemical analyses; Ann Serna and Alex Gaukhmann with mouse behavioral analysis; and Faith Conkle, Deborah Maloy, and the Mayo Clinic Veterinary Medicine staff for animal maintenance.

Disclosures The authors have no financial conflicts of interest.

This work was supported by the Mayo Clinic (to T.E.G.), National Institutes of Health, National Institute on Aging Grants RO1AG18454, RO1AG29886, and P01AG25531 (to T.E.G.), American Health Assistance Foundation Grant A2009061 (to P.D.), and a Robert H. and Clarice Smith Foundation post-doctoral fellowship (to P.C.).

The online version of this article contains supplemental material.

Abbreviations used in this paper:

AD

Alzheimer’s disease

amyloid β, APP, Aβ precursor protein

BACE

β-site APP-cleaving enzyme

CTF

C-terminal fragment

CR

complement receptor

EGFP

enhanced GFP

fAβ

fibrillar Aβ

FA

formic acid

GFAP

glial fibrillary acidic protein

Iba-1

ionized calcium-binding adaptor molecule 1

MHCII

MHC class II

mIFN-γ

murine IFN-γ

QRT-PCR

quantitative real-time PCR

rAAV1

recombinant adeno-associated virus serotype 1

Tg

transgenic.

1
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