Deletion of the type-1 interferon receptor in APP_SWE/PS1_ΔE9 mice preserves cognitive function and alters glial phenotype

APP_SWE/PS1_ΔE9 transgenic mice [30] on a C57BL/6 background were sourced from JAX. (B6.Cg-Tg(APPswe,PSEN1dE9)85Dbo/Mmjax, JAX ID: 005864, https://​www.​jax.​org/​strain/​005864). IFNAR1^−/− mice on a C57Bl/6 background were initially generated by [28]. APP_SWE/PS1_ΔE9 transgenic mice lacking IFNAR1 were generated by interbreeding. APP_SWE/PS1_ΔE9 and IFNAR1^−/− mice to produce F1 progeny. APP_SWE/PS1_{ΔE9 x} IFNAR1^+/− mice from F1 progeny were then interbred to yield APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice (F2 progeny). In all animal experiments, mice were used at 9 months of age with aged-matched littermate non-transgenic wildtype and IFNAR1^−/− control mice. All mice were determined as specific pathogen-free, housed in sterile micro-isolator cages and fed ad-libitum on standard chow with open access to water. All animal procedures were performed in accordance with the University of Melbourne animal care committee’s regulations.

All animals used in this study were analysed for correct genotypes before use. This genotyping was either performed manually (Additional file 1: Figure S1), as described below, or in partnership with Transnetyx™ (Cordova, TN, USA).

Tails from mice were obtained pre-weaning and genomic DNA was extracted. Tissue was digested using Proteinase K (9.3 mg/ml, New England Biolabs) in Tris buffer (containing 1 % w/v SDS). Upon removal of protein with Potassium acetate (1.5 M) and precipitation using propan-2-ol, the extracted DNA was washed in 70 % Ethanol and reconstituted in Tris-EDTA (TE) buffer. PCR was then conducted using the GoTaq® DNA polymerase system (M3005, Promega) under the following conditions:

PCR products were then loaded into a 2 % w/v agarose Et-Br-labelled (40 μg/ml) gel and electrophoresis was performed to separate bands. A pre-stained BenchTop 100 bp DNA ladder (G8291, Promega) was used to determine sample band sizes upon gel imaging using the ChemiDoc™ MP image system (Biorad). Specific oligonucleotide primers used for amplification of APP_SWE, PS1_ΔE9, IFNAR1 and internal control DNA sequences are detailed below:

The number of mice used in this study were as follows: Wildtype: 15; IFNAR1^−/−: 18; APP_SWE/PS1_ΔE9; APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 9. Both male and female mice were used in the study in 50:50 proportion. No significant sex difference was detected in behavior and/or biochemical readouts and thus sexes were pooled. All mice were subjected to Morris water testing then 9 mice from each genotype were randomly selected for biochemical processing. Half hemispheres were taken for immunohistochemistry, whilst the other half was snap frozen and ground on liquid nitrogen in order to isolate both protein and RNA from the same mice.

Mixed cortical and hippocampal neurons were isolated from embryonic P0-1 embryos as previously described [35]. Briefly, cortices were isolated and meninges surgically removed. The cleaned cortical tissue was then digested in hanks buffered sulphate solution (HBSS, 14025–092, Gibco) using trypsin/DNAse (1 mg/ml, T9201, D5025, Sigma) until a single cell suspension was achieved. Cells were then plated at a density of 1 brain/10 ml in culture medium (DMEM, 31985–062, Gibco, 20 % FBS, 0.5 % penicillin-streptomycin) in T75cm² flasks. Media was then replaced every two days until the glial cultures formed a comprehensive monolayer. Cells were seeded at 5 x 10⁵ cells/ml for experimental use between 14 and 28 days in vitro.

Mixed cortical and hippocampal neurons were isolated as described previously [63]. Briefly, cortices were isolated from embryonic day 14–16 pups and meninges were removed. Cleaned cortices were then digested in Krebs solution containing trypsin (250 μg/ml) and DNAse (33 μg/ml) and mechanically agitated to ensure a single cell suspension. Cells were then plated into pre-coated Poly-L-lysine (0.5 mg/ml, P6282, sigma) plastic ware at a density of 1 x 10⁶ cells/ml in neurobasal media (17504–044, Gibco) containing B-27 growth factor supplement (17504–044, Gibco), L-glutamine (500 μM, G7513, Sigma) and 2 % FBS. The following day, FBS was removed from the media and cultures were supplemented with fresh culture media every two days until experimental use. Neuronal purity was assessed at >90 % using NeuN (neuronal nuclei) immunohistochemistry (data not shown) and all cultures were used day 9–10 in vitro.

Mice were deeply anaesthetized using intra-peritoneal injection of combinatorial ketamine (90 mg/kg) and xylazine (4.5 mg/kg, K113, Sigma). Mice were cardiac perfused with ice-cold heparinized PBS (1U/ml, H3393, Sigma). Brains were then excised and separated for use in immunohistochemistry or for RNA/protein biochemical analysis. Isolation of the cortex for RNA/protein biochemistry was performed using a modified dissection technique [24]. Hemispheres were placed on an ice cold glass dissection plate and orientated in a sagittal plane. The cerebellum was removed, and the striatum, thalamus, midbrain and brain stem remnants were identified. These structures were then removed using sterilized blunt spatulas, exposing the hippocampal complex and interior wall of the cortex. The hippocampus was then peeled away from the cortex, and cortical tissue was snap frozen in liquid nitrogen and stored at −80 °C until required.

For immunohistochemical analysis, hemispheres were post-fixed in 4 % w/v paraformaldehyde in PBS for 72 h (4 °C) before being transferred into 30 % w/v sucrose in PBS for 48 h (4 °C) and embedded in Optimal Cutting Temperature (OCT, 4583, Sakura) medium for subsequent cryosectioning. Sagittal sections (30 μm) were then cut throughout the hippocampal region using a cryostat (Reichert-Jung) and mounted onto electrostatic Menzel-Gläser Superfrost® plus glass microscopy slides (J1800AMNZ, Thermo-Scientific). Tissue was then permeabilized in PBS-T (0.05 % v/v Tween-20, 5 min, room temperature) and blocked in CAS-Block™ (1 h, room temperature, 008120, Invitrogen). After rinsing with PBS, tissue was then incubated overnight with primary antibody diluted in 10 % v/v CAS-Block™ in PBS (4 °C, humidified chamber). After washing in PBS, slides were then incubated with fluorescent secondary antibodies diluted in 10 % v/v CAS-Block™ in PBS (2 h, room temperature). Post-PBS rinse coverslips were mounted in Vectashield® DAPI-containing mounting media (H-1200, Vector laboratories). Images were then obtained using a Zeiss Axio Observer.Z1 (Carl Zeiss imaging) inverted fluorescence microscope. Details of antibodies used for immunohistochemistry are provided below:

To quantify plaque number and burden, WO-2 immunofluorescent labelled sections were converted to 8-Bit images and an image fluorescence threshold was set using Image J quantification software (NIH). Plaque staining was then analysed by particle quantification giving plaque number. The WO-2 positive pixel coverage value was then expressed relative to total cortical area to calculate cortical plaque burden. For IBA-1 and GFAP immunofluorescence quantification, integrated densities were calculated from entire cortical regions using Image J quantification software (National Institutes of Health, NIH). These values were then normalized to staining background and expressed as relative fluorescence intensity as described previously [32]. All quantified data is from average values generated from ≥3 sections/mouse (each 270 μm apart or every 6th section).

Amyloid peptide stocks were prepared according to methods described previously [2]. Aβ1-42 stocks (A-42-T-1, GenecBio) were initially monomerized in 1, 1, 1, 3, 3, 3-Hexafluoro-2-propanol (0.5 mg/ml, HFIP, 52512, Fluka), lyophilized and stored at −80 °C until required. The peptide was then dissolved in ice cold 5 mM NaOH in Dulbecco’s PBS by rigorous vortexing and protein concentration was determined by absorbance spectrophotometry at 214 nm. Peptide concentrations were calculated using Eq. 1.

Where Abs₂₁₄ = Absorbance value of sample at 214 nm, DF = Sample dilution factor, ε = molar extinction coefficient of Aβ42 (75,887 L/mol/cm).

Primary cultured glial cells were treated with 10 μM Aβ1-42 or NaOH vehicle for up to 96 h in serum-reduced glial treatment medium (DMEM with 2 % FBS and 0.5 % penicillin-streptomycin). The final concentration of NaOH across all treatment groups was <5nM and remained non-toxic.

Following treatment, primary glial cell cultures were washed in ice cold PBS and collected via cell scraping. Cell pellets were briefly sonicated in Tris lysis buffer (50 mM Tris, 150 mM NaCl, 1 % v/v Triton x-100 (T8787, Sigma), 1 % w/v SDS, PhosphoSTOP® phosphatase and cOmplete® protease inhibitors (04906837001, 11697498001, Roche), pH 7.4). Brain tissue was homogenized in Tris lysis buffer (≤100 mg/ml concentration, without 1%w/v SDS). Upon rotation for 90 min at 4 °C, homogenates were centrifuged (12,000xg, 4 °C, 5 min) before supernatants were removed and stored at −80 °C until required. Protein concentrations were determined as per the method of Bradford ([5], 500–0006, Bio-Rad).

Fifty micrograms of protein was denatured in reducing buffer (20 mM Tris, 20%v/v glycerol, 4%w/v SDS, 10 % β-mecaptoethanol (M6250, Sigma), and bromophenol blue). Samples were loaded onto 10 % SDS-PAGE gels (60 mM Tris, 0.1 % w/v SDS, 0.1 % w/v APS, 0.01 % v/v TEMED, 10 % Acrylamide/Bis (161–0156, Bio-Rad)) or 4-20 % Mini-PROTEAN® TGX Stain-Free™ gels (456–8093, Bio-Rad) and electrophoresis was performed at 120 V in Novex® Tris-Glycine SDS running buffer (LC2675-5, Invitrogen). Proteins were then transferred to polyvinylidene fluoride (PVDF) membranes by semi-dry transfer (60 mA/gel, 1.25 h) or using the TransBlot® Turbo™ transfer system (2.5MA, 7 min, 170–4155, Bio-Rad) as per manufacturer’s instructions. Membranes were blocked in 5%w/v skim milk powder in Tris buffered saline-Tween 20 (0.05 % v/v Tween-20, TBS-T) for 1 h before overnight incubation with primary antibodies at 4 °C (dilutions in 2 % w/v skim milk powder in TBS-T). Membranes were then washed in TBS-T before being incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies (dilutions in 2 % w/v skim milk powder in TBS-T) for 90 min at room temperature. HRP signals were detected using an enhanced chemiluminescence (ECL™) prime Western blotting detection kit (RPN2232, Amersham) and visualized using the ChemiDoc™ MP system (Bio-Rad). For densitometry analysis, all raw pixel intensities of HRP signals from Western blots were calculated using Image J quantification software (NIH). Details of antibodies used for Western blotting are provided below:

For quantification of soluble and insoluble Aβ levels, tissues were homogenized in PBS (containing Triton x-100, 1 % v/v, PBS-T) containing PhosphoSTOP® phosphatase and cOmplete® protease inhibitors (04906837001, 11697498001, Roche), pH 7.4) via sonication. After centrifugation (100,000xg, 60 min, 4 °C) the supernatant was collected to detect PBS-T-soluble Aβ1:40 levels. The remaining tissue pellets were further homogenized in 70 % v/v formic acid in PBS, centrifuged (100,000xg, 60 min, 4 °C) and the resulting supernatant was neutralized with 1 M Tris base (20x volume) and collected to detect PBS-T-insoluble Aβ1:40 levels by sandwich ELISA.

Assays were run in 96-well plate format with all standards and samples run in duplicate reactions. ELISA plates were coated in WO-2 capture antibody (diluted in 0.05 M carbonate-bicarbonate, pH 9.6) overnight and blocked in 1 % BSA (diluted in TBS-T) prior to sample incubation (100 μg protein/well, 4 °C, overnight incubation with shaking). Plates were then washed in TBS-T and incubated with an anti-Aβ1:40 casein-1E8 biotinylated monoclonal sandwich detection antibody. After washing in TBS-T plates were incubated with high sensitivity Streptavidin-HRP and signals were developed using TMB substrate and detection at 450 nm. Sample absorbance were normalized to the Aβ1:40 standard curve and concentrations are expressed relative to sample total protein concentrations as determined by Bradford assay.

RNA was extracted from cell pellets or brain tissue by methods previously described [12] using TRIzol® reagent (15596018, Life-Technologies). Contaminating genomic DNA was then removed prior to reverse transcription using the TURBO DNA-free™ kit (AM1907, Ambion) according to manufacturer’s guidelines. Yield quantities and purity of the RNA product was then assessed using the nanodrop 1000 spectrophotometer (Thermo Scientific). One microgram of RNA was then reverse transcribed to produce cDNA using a high capacity cDNA reverse transcription kit (4368814, Applied Biosciences) as per manufacturer’s instructions and cDNA was then diluted 1:3 in diethylpyrocarbonate (DEPC)-treated dH₂O for use in QPCR.

All QPCR was performed in standard 384-well plates (4309849, Applied Biosystems) using the 7900ht fast real-time PCR system (Applied Biosystems) and reactions for a given sample were performed in triplicate. All Taqman gene expression assays were purchased commercially (431182, Applied Biosystems) and reactions were performed under the following thermal conditions:

For SYBR® green-based detection, gene-specific primers were synthesized commercially (Geneworks) and reactions were performed under the following thermal conditions:

Fold change readouts presented throughout the study were calculated using the ΔΔct calculation method [36]. For each experiment a fluorescence detection threshold was automatically set at 1.0 RFU and the cycle number at which each reaction reached this threshold was calculated (cycle threshold (Ct)). Triplicate Ct value for genes of interest were then normalized back to the Ct values of the GAPDH housekeeping gene to account for differences in original cDNA concentration between samples (ΔCt). The calculated ΔCt of treatment or genotype groups were then normalized back to the ΔCt of appropriate genotype-specific control samples. In addition, ΔΔCt values were converted to fold change data using Eq. 2.

Primers used for QPCR analysis are listed below:

Cell viability was measured by the ability to metabolize 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS, CellTiter 96® AQ_ueous non-radioactive cell proliferation assay, G5421, Promega) in the presence of the electron coupler phenazine methosulfate (PMS) to a media soluble formazan product, as described previously [9]. Combined MTS (400 μg/ml) and PMS (44 μg/ml) solution was incubated on primary cultured neurons for 4 h (37 °C). Culture medium absorbance at 492 nm was then determined using a Multiskan Ascent spectrophotometer (Thermo Scientific). All sample absorbance readings were then blank normalized using a negative control reaction containing only culture medium and the MTS/PMS reagent. Absorbance readings of all treatment groups were then normalized back to genotype-specific vehicle controls and expressed as a percentage of vehicle control cell viability. Experiments were performed in technical triplicate and staurosporine (1 μM, S6942, Sigma) was used to induce cellular apoptosis in primary neuronal cultures for positive control means.

Morris water maze (MWM) testing was conducted in a black circular pool 1.6 m in diameter and 0.8 m deep. A white Perspex 10 cm² circular platform was then secured to the enclosure 25 cm from the pool wall. The pool was then filled with water at 21–23 °C until the white platform was submerged 1 cm below the surface. Non-toxic, water soluble white ceiling paint (Taubmans) was then used to opacify the water. The room was brightly illuminated using wall-mounted halogen lamps. Several distinct and distal extra-maze cues were placed around the pool as points of reference. These cues remained in place throughout the duration of testing and the platform was only removed to conduct the probe trial.

Mice were subjected to a 4 trial/day protocol for 7 days with 60 s maximum trial duration. Mice were removed from their test cage and placed into the water maze, at a randomized cardinal point, facing towards the pool wall. The 60 s trial commenced after the mouse had entered the MWM for 2 s. If the test mouse found, mounted and stayed on the hidden platform for 2 s the trial was deemed complete and latency to reach the platform was calculated. The mouse remained on the hidden platform for 20 s before being removed from the water maze and placed back in their testing cage. If the mouse failed to find or remain on the platform for at least two seconds before the 60 s time allowance, the researcher entered the testing area and guided the mouse to the hidden platform. Once an individual mouse completed the trial and was towel dried, the next mouse within the testing group was immediately placed into the MWM for testing. Each mouse underwent 4 trials per day, according to the aforementioned trial parameters and had an inter-trial resting time of 10 min. All MWM testing was recorded to DVD and automatically tracked using Ethovision® XT (Noldus). For all individual trials, latency to platform, success rate, path length and swim speed was calculated. A 60 s value for latency was awarded for all trials where the test mouse failed to find the platform within the allocated time.

To assess spatial reference memory, a probe trial was conducted on day 7 of MWM acquisition. Mice were placed into the maze at the north cardinal point and allowed to explore for the standard 60 s trial length with the escape platform removed. The maze was virtually divided up into quadrants and time spent in the quadrant which previously held the platform was calculated. All primary readouts reported from MWM testing conducted in this study are well-established in the AD field [7].

GraphPad Prism software (version 6.0, http://​www.​graphpad.​com/​scientific-software/​prism/​) was used for all t-tests, ANOVAs and post-hoc statistical evaluation. Where comparisons of multiple groups was required a one or two-way analysis of variance (ANOVA) was performed, with mouse genotype as the fixed variable. A Bonferroni post-hoc or Tukey’s HSD multiple comparisons test was then performed. Otherwise an unpaired two-tailed Student’s t-test was used. For all statistical tests a two-tailed α value of 0.05 was utilized. Box plots were used to display data in which the midline represents the median value and the upper and lower margins equate to the 25 % and 75 % quartiles. The whiskers display data within the 1.5xinterquartile range and values beyond this were determined as outliers (represented as circles). All other numerical data is presented as mean ± SEM. Power values for each test where calculated post-hoc using G*Power (version 3.1, http://​gpower.​hhu.​de/​), based upon the effect size, group number and sample size. Exact p-values were calculated for all Student’s t-tests and multiplicity adjusted p-values were determined for all Bonferroni’s and Tukey’s post-hoc tests. A p-value <0.05 was considered statistically significant. All use of statistics is detailed in Additional file 2: Table S1.

To investigate the effect of removing type-1 IFN signaling in AD we generated APP_SWE/PS1_ΔE9 x IFNAR1^−/−. APP_SWE/PS1_ΔE9 mice aged 9 months display an enhanced type-1 IFN and pro-inflammatory cytokine response [64]. Hence, we focused on characterizing phenotypic alterations in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice at this age. With variable hippocampal Aβ plaque deposition at this age in both APP_SWE/PS1_ΔE9 and APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice (data not shown), the current study focused on cortical regions only, not hippocampus. To assess potential alterations in Aβ plaque burden, immunohistochemistry was performed on APP_SWE/PS1_ΔE9 and APP_SWE/PS1_ΔE9 x IFNAR1^−/− mouse brain sagittal sections, stained with anti-Aβ mAb WO-2 (n = 9 per genotype, Fig. 1a, b). Both APP_SWE/PS1_ΔE9 and APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice display extensive plaque deposition within cortical regions but no difference was detected between genotypes when Aβ plaques were counted (n = 9 per genotype, Fig. 1c) or when cortical plaque burden percentage was quantified (n = 9 per genotype, Fig. 1d). To validate these immunohistochemical findings we prepared PBS-T-soluble and PBS-T-insoluble fractions from cortical tissue to quantify Aβ levels by ELISA. We did not observe any differences in PBS-T-soluble or PBS-T-insoluble Aβ1:40 levels measured from cortical tissue lysates of APP_SWE/PS1_ΔE9 and APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice (n = 4–6 per genotype, Fig. 1e, d). These findings suggest that removal of type-1 IFN signaling in APP_SWE/PS1_ΔE9 mice does not influence amyloid plaque deposition at 9 months of age.

Whilst amyloid plaque levels remained unchanged in the APP_SWE/PS1_ΔE9 IFNAR1^−/− mouse, the oligomerization state of soluble Aβ species may be altered. This can influence peptide toxicity and potentially impact cognitive phenotypes [1, 15, 44]. To investigate the oligomerization state of various Aβ species, we analyzed Tris–HCl soluble cortical fractionations from wildtype, IFNAR1^−/−, APP_SWE/PS1_ΔE9 and APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice by western blotting, probed with anti-Aβ mAb WO-2 (n = 4–6 per genotype, Fig. 1g). Analysis of Aβ oligomers in wildtype and IFNAR1^−/− mice displayed constitutive Aβ production but not overexpression that is characteristic of the APP_SWE/PS1_ΔE9 transgene. Densitometry identified a trend, albeit not statistically significant, to decreased transgenic human APP-CTF expression (n = 4–6 per genotype, p = 0.0618, Fig. 1h) and significant reductions in endogenous murine APP-CTF levels (n = 4–6 per genotype, p < 0.0001, Fig. 1i) in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice compared to APP_SWE/PS1_ΔE9 mice. Densitometry confirmed a significant 4.3 ± 0.2-fold decrease of cortical Aβ monomer levels in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice compared to APP_SWE/PS1_ΔE9 mice (n = 4–6 per genotype, p = 0.0122, Fig. 1j). Although not statistically significant, Aβ trimer (3-mer) levels also trended to a decrease in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice compared to APP_SWE/PS1_ΔE9 mice (n = 4–6 per genotype, p = 0.0569, Fig. 1k). Collectively, this data highlights that removal of IFNAR1 in APP_SWE/PS1_ΔE9 mice does not influence Aβ plaque deposition, but may influence oligomerization through modest, but significant, reductions in Aβ monomer levels.

To assess if removal of type-1 IFN signaling can alleviate the cognitive deficits observed in APP_SWE/PS1_ΔE9 we analyzed spatial learning and memory performance of wildtype, IFNAR1^−/−, APP_SWE/PS1_ΔE9 and APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice using the Morris water maze. Compared to wildtype, APP_SWE/PS1_ΔE9 mice required more time to find the escape platform, whilst APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice were initially impaired but recovered to wildtype levels as pheno-copied by IFNAR1^−/− mice (n = 9–18 per genotype, 0.05 < p < 0.001, Fig. 2a). Compared to wildtype, an initial decline in trial success rate was seen for all genotypes but this was only maintained by the APP_SWE/PS1_ΔE9 mice over the course of acquisition (n = 9–18 per genotype, 0.05 < p < 0.0001, Fig. 2b). Compared to wildtype, all genotypes initially selected longer escape paths but only APP_SWE/PS1_ΔE9 mice maintained this abnormality throughout testing (n = 9–18 per genotype, p < 0.01, Fig. 2c). Representative tracks (Day 7 acquisition) of APP_SWE/PS1_ΔE9 mice display a lack of cue-directed swimming to find the platform, partially rectified in the APP_SWE/PS1_ΔE9 IFNAR1^−/− counterparts. Wildtype and IFNAR1^−/− behaved similarly (Fig. 2d, Additional file 2: Table S1 for detailed analysis).

After the 7 day acquisition period, the escape platform was removed from the maze and persistence of the mouse to escape was measured. Although not statistically significant, APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice spent more time exploring the escape quadrant than APP_SWE/PS1_ΔE9 mice (APP_SWE/PS1_ΔE9: 27.3 ± 3.8 % vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 39.0 ± 7.7 %, n = 9–18 per genotype, p = 0.5111, Fig. 2e). Interestingly, IFNAR1^−/− mice spent a significantly greater amount of time in the escape quadrant than APP_SWE/PS1_ΔE9 mice (IFNAR1^−/−: 45.6 ± 0.5 % vs. APP_SWE/PS1_ΔE9: 27.3 ± 3.8 %, n = 9–18 per genotype, p = 0.0488, Fig. 2e). As swimming ability can represent a potential confounding factor in the Morris water maze, average swim speed was measured. APP_SWE/PS1_Δ9 mice swim at a significantly lower velocity than their wildtype counterparts (Wildtype: 18.5 ± 0.5 cm/s vs. APP_SWE/PS1_Δ9: 15.9 ± 0.4 cm/s, n = 9–18 per genotype, p = 0.0025, Fig. 2f); however this difference at a physiological level is minor and observed swimming technique remained consistent amongst genotypes. Collectively, this data implicates that removal of type-1 IFN signaling in APP_SWE/PS1_ΔE9 mice rescues spatial learning and memory deficits assessed using the Morris water maze.

Previously it has been demonstrated that removal of IFNAR1 attenuates the type-1 IFN response to soluble Aβ1-42 in primary cultured neurons and confers neuro-protection [64]. To investigate alterations in the type-1 IFN response in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice, Q-PCR was performed on cortical tissue. Levels of IFNα expression were significantly elevated in APP_SWE/PS1_ΔE9 mice compared to wildtype mice with this elevation attenuated in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice (Wildtype: 1.0 ± 0.08-fold vs. APP_SWE/PS1_ΔE9: 3.4 ± 0.8-fold, p = 0.0009; APP_SWE/PS1_ΔE9: 3.4 ± 0.8-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 1.3 ± 0.1-fold, p = 0.0063, n = 9 per genotype, Fig. 3a). This data confirms that aged APP_SWE/PS1_ΔE9 display enhanced type-1 IFNα expression that is IFNAR1-dependent. We also analyzed IFNβ transcript levels in both wildtype and APP_SWE/PS1_ΔE9 cortical tissue but were unable to detect a difference between genotypes (n = 7 per genotype, Additional file 3: Figure S2).

As IRF7 and IRF3 are critical mediators of IFNα [27] and IFNβ [56] production respectively, mRNA levels were also analyzed to assess the capacity for type-1 IFN production in these mice. Levels of IRF7 expression were significantly elevated in APP_SWE/PS1_ΔE9 mice compared to wildtype mice, implying elevated capacity for IFNα production in these mice (Wildtype: 1.1 ± 0.08-fold vs. APP_SWE/PS1_ΔE9: 2.2 ± 0.3-fold, p < 0.0001, n = 9 per genotype, Fig. 3a). This elevation in IRF7 was attenuated in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice (APP_SWE/PS1_ΔE9: 2.2 ± 0.3-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 0.3 ± 0.03-fold, p < 0.0001, n = 9 per genotype, Fig. 3a). Interestingly, IFNAR1^−/− mice exhibit basal reductions in IRF7 expression levels compared to wildtype mice (Wildtype: 1.1 ± 0.08-fold vs. IFNAR1^−/−: 0.2 ± 0.02-fold, p = 0.0019, n = 9 per genotype, Fig. 3a). Expression levels of IRF3 were significantly elevated in APP_SWE/PS1_ΔE9 mice compared to wildtype mice (Wildtype: 1.1 ± 0.06-fold vs. APP_SWE/PS1_ΔE9: 1.5 ± 0.1-fold, p = 0.0004, n = 9 per genotype, Fig. 3a). However no alteration was detected when IRF3 levels in APP_SWE/PS1_ΔE9 mice were compared to APP_SWE/PS1_ΔE9 x IFNAR1^−/−, implying that signaling through IFNAR1 does not regulate IRF3 expression in these mice (APP_SWE/PS1_ΔE9: 1.5 ± 0.1-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 1.4 ± 0.09-fold, p = 0.4369, n = 9 per genotype, Fig. 3a). We also analyzed transcript levels of IRF8, a type-1 IFN-regulated mediator important in microglial activation and phenotype [40]. Levels of IRF8 expression were significantly elevated in APP_SWE/PS1_ΔE9 mice compared to wildtype mice (Wildtype: 1.1 ± 0.07-fold vs. APP_SWE/PS1_ΔE9: 1.7 ± 0.2-fold, p = 0.0009, n = 9 per genotype, Fig. 3a) and this elevation was maintained in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice (APP_SWE/PS1_ΔE9: 1.7 ± 0.2-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 1.9 ± 0.1-fold, p = 0.3845, n = 9 per genotype, Fig. 3a).

Considering type-1 IFNs signal via the JAK-Stat cascade and induce pro-inflammatory cytokine transcription, phosphorylation of Stat-3 was analyzed as a reporter of net type-1 IFN signaling in the APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice. Western blotting confirmed elevated phosphorylation of Stat-3 in APP_SWE/PS1_ΔE9 mice compared to both wildtype and IFNAR1^−/− mice (n = 4 per genotype, Fig. 3b). Densitometry of these blots identified a trend for decreased Stat-3 activation in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice compared to APP_SWE/PS1_ΔE9 mice (APP_SWE/PS1_ΔE9: 2.4 ± 0.8-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 1.1 ± 0.4-fold, p = 0.1955, n = 4 per genotype Fig. 3c). Collectively, these data highlight that removal of IFNAR1 attenuates the type-1 IFN response in aged APP_SWE/PS1_ΔE9 mice, correlating with cognitive benefits and modest reductions in Aβ monomer load.

Type-1 IFNs are master regulators of the innate immune response, regulating pro-inflammatory cytokine production [33]. To investigate if the removal of type-1 IFN signaling alters pro-inflammatory cytokine secretion in APP_SWE/PS1_ΔE9 mice, Q-PCR analyzing cortical tissue was performed. IL-1β mRNA transcript levels were upregulated in the APP_SWE/PS1_ΔE9 mice compared wildtype mice (Wildtype: 1.1 ± 0.09-fold vs. APP_SWE/PS1_ΔE9: 3.1 ± 0.4-fold, p < 0.0001, n = 9 per genotype, Fig. 3d). Interestingly, APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice displayed elevated IL-1β mRNA levels compared to APP_SWE/PS1_ΔE9 mice alone (APP_SWE/PS1_ΔE9: 3.1 ± 0.4-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 4.5 ± 0.5-fold, p = 0.0071, n = 9 per genotype, Fig. 3d). Whilst IL-6 expression levels were significantly elevated in APP_SWE/PS1_ΔE9 mice when compared to wildtype mice, this response was not significantly altered in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice (Wildtype: 1.1 ± 0.1-fold vs. APP_SWE/PS1_ΔE9: 2.0 ± 0.2-fold, p = 0.0005, n = 9 per genotype, Fig. 3d). TNFα mRNA transcript levels were upregulated in the APP_SWE/PS1_ΔE9 mice compared wildtype mice (Wildtype: 1.0 ± 0.09-fold vs. APP_SWE/PS1_ΔE9: 2.2 ± 0.2-fold, p < 0.0001, n = 9 per genotype, Fig. 3d) Significantly, TNFα expression was reduced in the APP_SWE/PS1_ΔE9 IFNAR1^−/− mice compared to APP_SWE/PS1_ΔE9 counterparts (APP_SWE/PS1_ΔE9: 2.2 ± 0.2-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 1.4 ± 0.1-fold, p = 0.0037, n = 9 per genotype, Fig. 3d). These data suggest that type-1 IFN signaling through IFNAR1 is an important regulator of pro-inflammatory cytokine expression in APP_SWE/PS1_ΔE9 mice.

Both microgliosis and astrocyte reactivity are important hallmarks of the neuro-inflammation evident in AD and are primary sources of pro-inflammatory cytokine production [25]. To establish if removal of type-1 IFN signaling alters astrocyte reactivity in APP_SWE/PS1_ΔE9 mice, immunohistochemistry was performed. Representative images and fluorescence quantification of sagittaly sectioned cortex revealed a significant 2.2 ± 0.3-fold increase in GFAP reactivity in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice compared to APP_SWE/PS1_ΔE9 counterparts (p = 0.0006, n = 9 per genotype, Fig. 4a, b). High power magnification images demonstrate this elevated astrocyte reactivity surrounds Aβ plaques, generating a localized inflammatory environment (Fig. 4c). Collectively, this data highlights that removal of IFNAR1 triggers increased astrocyte reactivity in cortical areas of Aβ accumulation in APP_SWE/PS1_ΔE9 mice. However, further investigation is required to conclude if this is a compensatory or direct effect of removing type-1 IFN signaling in APP_SWE/PS1_ΔE9 mice.

To assess if ablation of type-1 IFN signaling affects microgliosis in APP_SWE/PS1_ΔE9 mice further immunohistochemistry was performed. Representative images and fluorescence quantification of sagittaly sectioned cortex revealed a significant 1.5 ± 0.09-fold decrease in IBA-1 reactivity in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice compared to APP_SWE/PS1_ΔE9 counterparts (p = 0.0032, n = 9 per genotype, Fig. 4d, e). High power magnification images demonstrate a hypertrophic and reactive microglial phenotype surrounding Aβ plaques in the APP_SWE/PS1_ΔE9 mice. IBA-1 positive cells detected in APP_SWE/PS1_ΔE9 x IFNAR1^−/− display decreased staining intensity and remain embedded within plaque deposition, adopting a different morphology than cells in APP_SWE/PS1_ΔE9 mice (Fig. 4f). These findings suggest that ablation of type-1 IFN signaling in APP_SWE/PS1_ΔE9 mice attenuates cortical microgliosis and alters cellular morphology within the amyloid plaque microenvironment.

It has been suggested that pro-inflammatory microglial phenotypes enhance are largely deleterious in AD whereas anti-inflammatory microglial activity can promote beneficial inflammatory resolution [53]. We have shown that altered gliosis, decreased type-1 IFN responses and altered pro-inflammatory cytokine secretion is evident in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice, thus we were interested in assessing expression of glial inflammatory phenotypic markers. Cortical tissue from wildtype, IFNAR1^−/−, APP_SWE/PS1_ΔE9 and APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice were analyzed by Q-PCR for pro- and anti-inflammatory glial phenotype markers.

Elevation of iNOS pro-inflammatory marker expression was confirmed in APP_SWE/PS1_ΔE9 mice compared to wildtype mice (Wildtype: 1.1 ± 0.1-fold vs. APP_SWE/PS1_ΔE9: 2.6 ± 0.4-fold, p < 0.0001, n = 9 per genotype, Fig. 5a). Significantly, iNOS expression was decreased in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice compared to APP_SWE/PS1_ΔE9 mice alone (APP_SWE/PS1_ΔE9: 2.6 ± 0.4-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 1.4 ± 0.1-fold, p = 0.0053, n = 9 per genotype, Fig. 5a). Transcript levels of the pro-inflammatory marker CD11b were elevated in APP_SWE/PS1_ΔE9 mice compared to wildtype mice (Wildtype: 1.0 ± 0.07-fold vs. APP_SWE/PS1_ΔE9: 2.4 ± 0.4-fold, p = 0.0014, n = 9 per genotype, Fig. 5a). Similar to the iNOS expression, CD11b transcript levels were decreased in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice compared to APP_SWE/PS1_ΔE9 mice alone (APP_SWE/PS1_ΔE9: 2.4 ± 0.4-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 1.4 ± 0.1-fold, p = 0.0371, n = 9 per genotype, Fig. 5a). Expression of the CD32 pro-inflammatory marker was elevated in APP_SWE/PS1_ΔE9 mice compared to wildtype, however this elevation was not suppressed in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice (Wildtype: 1.1 ± 0.1-fold vs. APP_SWE/PS1_ΔE9: 3.7 ± 0.6-fold, p < 0.0001, n = 9 per genotype, Fig. 5a). Indeed, CD32 levels in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice were elevated compared to wildtype mice albeit not to the same levels as APP_SWE/PS1_ΔE9 mice (Wildtype: 1.1 ± 0.1-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 2.5 ± 0.3-fold, p = 0.0366, n = 9 per genotype, Fig. 5a). Expression of the CD33 pro-inflammatory marker was elevated in APP_SWE/PS1_ΔE9 mice compared to wildtype, but this elevation was not suppressed in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice (Wildtype: 1.0 ± 0.05-fold vs. APP_SWE/PS1_ΔE9: 1.9 ± 0.3-fold, p = 0.0015, n = 9 per genotype, Fig. 5a).

Analysis of the anti-inflammatory marker TGFβ revealed elevated expression levels in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice compared to wildtype mice (Wildtype: 1.0 ± 0.06-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 1.6 ± 0.2-fold, p = 0.0189, n = 9 per genotype, Fig. 5b). This elevation was not present in the APP_SWE/PS1_ΔE9 cohort. Transcript levels of the YM1 anti-inflammatory marker were also elevated in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice when compared to both wildtype and APP_SWE/PS1_ΔE9 mice (Wildtype: 1.2 ± 0.2-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 2.5 ± 0.5-fold, p = 0.0061; APP_SWE/PS1_ΔE9: 1.4 ± 0.2-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 2.5 ± 0.5-fold, p = 0.0490, n = 9 per genotype, Fig. 5b). ARG1 anti-inflammatory marker expression levels were elevated in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice when compared to both wildtype and APP_SWE/PS1_ΔE9 cohorts (Wildtype: 1.2 ± 0.1-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 3.0 ± 0.5-fold, p = 0.0002; APP_SWE/PS1_ΔE9: 1.7 ± 0.2-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 3.0 ± 0.5-fold, p = 0.0141, n = 9 per genotype, Fig. 5b). Expression levels of both CD206 and CCL22 M2 markers remained constant amongst all genotypes (n = 9 per genotype, Fig. 5b). Transcript levels of the TREM2 anti-inflammatory marker were elevated in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice when compared to both wildtype and APP_SWE/PS1_ΔE9 mice (Wildtype: 1.0 ± 0.07-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 2.5 ± 0.2-fold, p < 0.0001; APP_SWE/PS1_ΔE9: 2.0 ± 0.1-fold vs. APP_SWE/PS1_ΔE9 x IFNAR1^−/−: 2.5 ± 0.2-fold, p = 0.0056, n = 9 per genotype, Fig. 5b). Of interest is the finding that elevations in TREM2 expression were not unique to the APP_SWE/PS1_ΔE9 x IFNAR1^−/− genotype but also observed in APP_SWE/PS1_ΔE9 mice when compared to wildtype counterparts (Wildtype: 1.0 ± 0.07-fold vs. APP_SWE/PS1_ΔE9: 2.0 ± 0.1-fold, p < 0.0001, n = 9 per genotype, Fig. 5b). Western blot analysis of the anti-inflammatory marker SOCS-3, a negative regulator of type-1 IFN signaling and cytokine production [61, 69], confirmed an up-regulation in APP_SWE/PS1_ΔE9 x IFNAR1^−/− mice compared to APP_SWE/PS1_ΔE9 counterparts. This up-regulation was also confirmed in IFNAR1^−/− mice alone when compared to wildtype mice (Fig. 5c).

From the summarized data depicting pro-inflammatory (Fig. 5d) and anti-inflammatory glial phenotypic marker expression (Fig. 5e), these findings implicate that removal of type-1 IFN signaling shifts the glial phenotype from a pro-inflammatory phenotype towards an anti-inflammatory and presumably neuro-protective phenotype in APP_SWE/PS1_ΔE9 mice.

Astrocytes and microglia are key contributors to the inflammatory phenotype in AD and are also sources of type-1 IFN production within the CNS [51]. To investigate the role of astroglial and microglial type-1 IFN production in response to Aβ1-42, the predominant Aβ species over-produced in APP_SWE/PS1_ΔE9 mice [30, 31], we adopted an in vitro approach using primary cultured mixed glial cultures. Wildtype and IFNAR1^−/− glia were treated with 10 μM Aβ1-42 for 24–96 h and Q-PCR was used to assess IFNα and IFNβ expression. At 72 and 96 h post-treatment IFNAR1^−/− glia displayed reduced IFNα (72 h: Wildtype: 12.7 ± 1.8-fold vs. IFNAR1^−/−: 1.4 ± 0.1-fold, p < 0.0001; 96 h: Wildtype: 9.1 ± 4.4-fold vs. IFNAR1^−/−: 1.3 ± 0.2-fold, p = 0.0007, n = 4–5 per genotype, Fig. 6a) and IFNβ expression (72 h: Wildtype: 6.4 ± 1.3-fold vs. IFNAR1^−/−: 0.7 ± 0.2-fold, p = 0.0006; 96 h: Wildtype: 6.3 ± 2.1-fold vs. IFNAR1^−/−: 0.9 ± 0.3-fold, p = 0.0012, n = 4–5 per genotype, Fig. 6a) compared to wildtype cultures. In contrast to our in vivo data, Western blotting and subsequent densitometry revealed that Aβ1-42 treatment did not induce a p-Stat-3 response in either wildtype or IFNAR1^−/− glial cultures, displaying a comparable expression level (Additional file 4: Figure S3). Overall these findings identify a glial-derived type-1 IFN response to Aβ1-42. Furthermore this type-1 IFN response is attenuated upon removal of IFNAR1, in line with the notion that IFNAR1 is critical in autocrine up-regulation of type-1 IFNs in response to inflammatory stimuli [13, 29].

To investigate if ablation of type-1 IFN signaling decreases the pro-inflammatory cytokine burden in Aβ1-42-treated glial cultures, further Q-PCR analysis was conducted. At 24 and 48 h post-treatment, the IL-1β response to Aβ1-42 was decreased in IFNAR1^−/− cultures compared to wildtype glia (24 h: Wildtype: 10.9 ± 4.4-fold vs. IFNAR1^−/−: 0.8 ± 0.4-fold, p = 0.0105; 48 h: Wildtype: 10.8 ± 3.8-fold vs. IFNAR1^−/−: 0.4 ± 0.1-fold, p = 0.0074, n = 4–5 per genotype, Fig. 6a). Wildtype glia generated an elevated IL-6 response upon Aβ1-42 insult that was attenuated in IFNAR1^−/− cultures at 96 h (Wildtype: 2.7 ± 0.9-fold vs. IFNAR1^−/−: 0.3 ± 0.04-fold, p = 0.0259, n = 4–5 per genotype, Fig. 6a). Expression of TNFα after 24 and 96 h of Aβ1-42 treatment was also reduced in IFNAR1^−/− glia compared to wildtype counterparts (24 h: Wildtype: 7.2 ± 2.6-fold vs. IFNAR1^−/−: 0.6 ± 0.05-fold, p = 0.0003; 96 h: Wildtype: 4.8 ± 0.4-fold vs. IFNAR1^−/−: 0.2 ± 0.09-fold, p = 0.0034, n = 4–5 per genotype, Fig. 6a). These data suggest that type-1 IFN signaling regulates further pro-inflammatory cytokine production in glial cells exposed to Aβ1-42.

Type-1 IFNs can regulate the activity of NFkB, which is required for robust immune responses [50, 65]. To ascertain if attenuation of the type-1 IFN and pro-inflammatory cytokine response to Aβ1-42 observed in IFNAR1^−/− glial cultures resulted in reduced NFkB (p65) activation, further western blotting was performed (n = 3 per genotype, Fig. 6b). Densitometry quantification identified phosphorylation of NFkB (p65) was decreased in Aβ1-42-treated IFNAR1^−/− glia across the entire treatment course when compared to wildtype cultures (24 h: Wildtype: 2.2 ± 0.2-fold vs. IFNAR1^−/−: 0.9 ± 0.08-fold, p = 0.0001; 48 h: Wildtype: 2.1 ± 0.1-fold vs. IFNAR1^−/−: 1.2 ± 0.08-fold, p = 0.0007; 72 h: Wildtype: 1.8 ± 0.2-fold vs. IFNAR1^−/−: 0.8 ± 0.06-fold, p = 0.0002, n = 3 per genotype, Fig. 6c). Collectively this data suggests that type-1 IFN signaling regulates the pro-inflammatory glial response to Aβ1-42.

Within the current study we have demonstrated that removal of IFNAR1 confers an anti-inflammatory glial response in APP_SWE/PS1_ΔE9 mice. Thus we were interested in confirming this phenotype in Aβ1-42-treated IFNAR1^−/− glial cultures that display attenuated pro-inflammatory responses. To analyze the polarization phenotype in response to Aβ1-42, wildtype and IFNAR1^−/− glial cultures were treated with 10 μM Aβ1-42 for 24–96 h and analyzed by Q-PCR.

Significantly, expression of the iNOS pro-inflammatory marker was elevated in wildtype but not IFNAR1^−/− glial cultures in response to Aβ1-42 (24 h: Wildtype: 5.4 ± 2.8-fold vs. IFNAR1^−/−: 1.1 ± 0.3-fold, p = 0.0195; 48 h: Wildtype: 5.9 ± 2.3-fold vs. IFNAR1^−/−: 0.6 ± 0.06-fold, p = 0.0032, n = 4–5 per genotype, Fig. 7a). Transcript levels of the CD11b pro-inflammatory marker were also elevated in Aβ1-42-treated wildtype cultures but not when IFNAR1 was absent (72 h: Wildtype: 3.6 ± 0.9-fold vs. IFNAR1^−/−: 0.7 ± 0.2-fold, p = 0.0274; 96 h: Wildtype: 4.1 ± 1.2-fold vs. IFNAR1^−/−: 0.8 ± 0.2-fold, p = 0.0083, n = 4–5 per genotype, Fig. 7a). Expression levels of the CD32 pro-inflammatory marker were also reduced in IFNAR1^−/− glial cultures when compared to wildtype counterparts upon Aβ1-42 insult (96 h: Wildtype: 4.6 ± 1.4-fold vs. IFNAR1^−/−: 1.4 ± 0.2-fold, p = 0.0054, n = 4–5 per genotype, Fig. 7a).

Analysis of the ARG1 anti-inflammatory marker revealed elevated expression levels in Aβ1-42-treated IFNAR1^−/− glia but not wildtype cultures (72 h: Wildtype: 0.8 ± 0.5-fold vs. IFNAR1^−/−: 2.9 ± 0.9-fold, p = 0.0252; 96 h: Wildtype: 1.3 ± 0.7-fold vs. IFNAR1^−/−: 3.5 ± 0.5-fold, p = 0.0163, n = 4–5 per genotype, Fig. 7b). CCL22 anti-inflammatory marker expression levels were also elevated in Aβ1-42-treated IFNAR1^−/− glia but not wildtype cultures (24 h: Wildtype: 1.0 ± 0.3-fold vs. IFNAR1^−/−: 2.5 ± 0.5-fold, p = 0.0089, n = 4–5 per genotype, Fig. 7b). Expression levels of the anti-inflammatory markers YM1 and TGF-β remained constant across all time points and between genotypes (n = 4–5 per genotype, Fig. 7b). Expression levels of the CD206 anti-inflammatory marker were elevated in response to Aβ1-42 treatment but no difference between culture genotype was detected (n = 4–5 per genotype, Fig. 7b). Expression levels of the TGFβ anti-inflammatory marker remained constant across all time points and between genotypes (n = 4–5 per genotype, Fig. 7b). Collectively these data suggest that wildtype glia adopt a mixed inflammatory polarization phenotype in response to amyloid insult. Removal of IFNAR1 shifts this mixed population towards a predominantly anti-inflammatory polarization state.

To investigate the contribution of the glial polarized inflammatory response to Aβ1-42 on neuronal viability, primary wildtype and IFNAR1^−/− mixed glial cultures were treated with 10 μM Aβ1-42 for 24–48 h and media was collected. Primary wildtype neuronal cultures were then supplemented with this media for 48 h and an MTS assay was performed to assess cellular viability. Significantly, treatment of neurons with wildtype glial conditioned media induced severe cytotoxicity that was attenuated when the same neurons were supplemented with IFNAR1^−/− glial conditioned media (24 h media: Wildtype: 28.9 ± 1.2 % vs. IFNAR1^−/−: 77.8 ± 5.7 %, p = 0.0003; 48 h media: Wildtype: 18.4 ± 1.9 % vs. IFNAR1^−/−: 85.1 ± 7.1 %, p = 0.0001, n = 3 individual neuronal and glial cultures per genotype, Fig. 8). Both genotypes showed equal susceptibility to staurosporine-induced apoptosis. This data implies that the reduced Aβ1-42-induced pro-inflammatory cytokine burden and anti-inflammatory activity identified in IFNAR1^−/− glia is protective to neurons in vitro.