Animals
Wild-type (WT) and human APOE Ɛ4 knock-in (TGRA8960), male and female Sprague Dawley rats, (four groups, n = 6/group), were obtained from Horizon Discovery (Saint Louis MO). All rats were studied between four and five months of age. Rats were housed in Plexiglas cages (two per cage) and maintained in ambient temperature (22–24 °C) on a 12:12 light:dark cycle (lights on at 07:00 a.m.). Food and water were provided ad libitum. Rats were imaged during the light phase of the circadian cycle. All rats were acquired and cared for in accordance with the guidelines published in the NIH Guide for the Care and Use of Laboratory Animals. All methods and procedures described below were pre-approved by the Northeastern University Institutional Animal Care and Use Committee.
Transgenics
All animal work was performed in accordance with the approved animal protocols and Institutional Animal Care and Use Committee. Rats were housed in standard cages and maintained on a 12hr light/dark cycle with ad libitum access to food and water. Routine health monitoring of the colony was performed at IDEXX (Columbia, MO) and revealed no evidence of infection with serious known pathogens.
Small guide RNA (sgRNA) template preparation
Two overlapping DNA oligonucleotides, one containing T7 promoter sequence and 20 nucleotides of Cas9 target sequence (specific oligo), and the other containing sgRNA backbone (common reverse oligo), were combined in a PCR reaction, together with a T7 forward and a backbone reverse primer. PCR was performed using AccuPrime HiFi Taq polymerase (Invitrogen, Waltham, MA USA) under the following conditions: 95oC, 2 min, then 35 cycles of 95oC, 30 sec; 60oC, 30 sec; 68oC, 30 sec. PCR product was purified by QiaQuick PCR purification kit (Qiagen, Venio, Netherlands), and the DNA was used as a template for in vitro sgRNA synthesis with HiScribe™ T7 Quick High Yield RNA Synthesis Kit (New England Biolabs, Whitby, ON, Canada). The RNA was purified by ethanol precipitation with 3M sodium acetate and quantified by Qubit BR RNA assay. Recombinant Cas9 protein was acquired from New England Biolabs.
Cas9 cleavage activity assay
Rat C6 glioma cells were maintained in F-12K media (ATCC) containing 15% horse serum, 2.5% FBS, and 1% penicillin/streptomycin at 37oC with 5% CO2. All cell transfections were performed with a Nucleofector (Lonza, Basel, Switzerland) according to the manufacturer’s 96-well shuttle protocol. Transfected cells were harvested 24 hours post-transfection into QuickExtract DNA extraction solution (Epicentre, Madison WI, USA), and incubated at 65oC for 15 min and 98oC for 3 min. Regions of interest were amplified by PCR using the extracted genomic DNA as a template and AccuStart II PCR SuperMix (Quanta Biosciences, Gaithersburg, MD, USA). The following PCR program was used: 95oC, 2 min, 35 cycles of 95oC, 15 sec, 60oC, 15 sec, and 72oC, 20 sec. Ten microliters of the above PCR reactions were incubated under the following program: 95oC, 10 min, 95oC to 85oC, at -2oC/s, 85oC to 25oC at -0.1oC/s. One microliter each of nuclease S (Cel-I) and enhancer (Transgenomics, New Haven CT, USA) were added to digest the above reaction at 42oC for 20 min. The mixture was resolved on a 10% polyacrylamide TBE gel.
Microinjection
Four- to five-week-old Sprague-Dawley female donors were injected with PMS followed by hCG injection after 48 hr of the PMS injection and then immediately mated with stud males after the hCG injection. Fertilized eggs were harvested a day later for microinjection. Microinjection reagents contained Cas9 protein/sgRNA (RNP) complex that was formed at 37oC for five minutes, and then placed on ice until use. Just before a microinjection session, the RNP complex, donor plasmid, and injection buffer were carefully mixed together and injected into fertilized single-cell embryos. Injected zygotes were transferred into pseudo-pregnant females for live births.
Genotyping
Genotyping of live-born pups was performed by genomic PCR. Several reactions were routinely run to identify the founders that carried the desired mutation, such as 5’ and 3’ junctions, internal cassette, and plasmid backbone PCR to test for random integration of the DNA donor. Only founders positive by all PCR reactions and negative for plasmid backbone were verified by DNA sequencing.
Neuroimaging
Imaging sessions were conducted using a Bruker Biospec 7.0T/20-cm USR horizontal magnet (Bruker, Billerica, MA, USA) and a 20-G/cm magnetic field gradient insert (ID = 12 cm) capable of a 120-µs rise time. Radio frequency signals were sent and received with a quadrature volume coil built into the animal restrainer (Animal Imaging Research, Holden, Massachusetts). The design of the restraining system included a padded head support obviating the need for ear bars helping to reduce animal discomfort while minimizing motion artifact. All rats were imaged under 1% isoflurane with a respiratory rate of 40–50/min. At the beginning of each imaging session, a high-resolution anatomical data set was collected for volumetric analysis using the RARE pulse sequence with following parameters: TR/TE = 3310/36 ms; matrix size 256 × 256 × 40, field of view = 30 × 30 mm, spatial resolution, 0.117 × 0.117 × 0.7 mm.
Voxel-based morphometry analysis
A 3D MRI Rat Brain Atlas © (Ekam Solutions LLC, Boston, MA) was used to calculate brain volumes, and registered the standard structural rat template image onto high resolution T2-weighted images for each subject using a non-linear registration method implemented by Unix based software package Deformable Registration via Attribute Matching and Mutual-Saliency Weighting (DRAMMS; https://www.cbica.upenn.edu/sbia/software/dramms/index.html). The atlas (image size 256 × 256 × 63) (H x W x D) was then warped from the standard space into the subject image space (image size 256 × 256 × 40) using the deformation obtained from the above step using nearest-neighbor interpolation method. In the volumetric analysis, each brain region was therefore segmented, and the volume values were extracted for all 173 ROIs, calculated by multiplying unit volume of voxel in mm3 by the number of voxels using an in-house MATLAB script. To account for different brain sizes, all ROI volumes were normalized by dividing each subject’s ROI volume by their total brain volume
Diffusion weighted imaging – quantitative anisotropy
DWI was acquired with a spin-echo echo-planar-imaging (EPI) pulse sequence having the following parameters: TR/TE = 500/20 msec, eight EPI segments, and 10 non-collinear gradient directions with a single b-value shell at 1000s/mm2 and one image with a B-value of 0 s/mm2 (referred to as B0). Geometrical parameters were: 48 coronal slices, each 0.313 mm thick (brain volume) and with in-plane resolution of 0.313 × 0.313 mm2 (matrix size 96 × 96; FOV 30 mm2). The imaging protocol was repeated two times for signal averaging. Each DWI acquisition took 35 min and the entire MRI protocol lasted ca. 70 min. Image analysis included DWI analysis of the DW-3D-EPI images to produce the maps of fractional anisotropy (FA) and apparent diffusion coefficient (ADC). DWI analysis was completed with MATLAB and MedINRIA (1.9.0; http://www-sop.inria.fr/asclepios/software/MedINRIA/index.php) software. Because sporadic excessive breathing during DWI acquisition can lead to significant image motion artifacts that are apparent only in the slices sampled when motion occurred, each image (for each slice and each gradient direction) was screened, prior to DWI analysis. If found, acquisition points with motion artifacts were eliminated from analyses.
For statistical comparisons between rats, each brain volume was registered to the 3D rat atlas allowing voxel-based statistics. All image transformations and statistical analyses were carried out using the in-house MIVA software (http://ccni.wpi.edu/). For each rat, the B0 image was co-registered with the B0 template (using a 6-parameter rigid-body transformation). The co-registration parameters were then applied on the DWI indexed maps for the different indices of anisotropy. Normalization was performed on the maps since they provided the most detailed visualization of brain structures and allow for more accurate normalization. The normalization parameters were then applied to all DWI indexed maps that were then smoothed with a 0.3-mm Gaussian kernel. To ensure that FA and ADC values were not affected significantly by the pre-processing steps, the ‘nearest neighbor’ option was used following registration and normalization.
Statistical differences in measures of voxel-based morphology and DWI between genotypes and sex were determined using a nonparametric Newman-Keuls multiple comparisons test (alpha set at 5%) followed by post hoc analyses using a Wilcoxon rank-sum test for individual differences. The formula below was used to account for false discovery from multiple comparisons.
P(i) is the p value based on the t test analysis. Each of 173 ROIs (i) within the brain containing (V) ROIs was ranked in order of its probability value (see Table 1). The false-positive filter value q was set to 0.2 and the predetermined c(V) was set to unity [12]. The corrected probability is noted on each table.
Resting state functional connectivity
Scans were collected using a spin-echo triple-shot EPI sequence (imaging parameters: matrix size = 96 × 96 × 20 (H x W x D), TR/TE = 1000/15 msec, voxel size = 0.312 × 0.312 × 1.2 mm, slice thickness = 1.2 mm, with 200 repetitions, time of acquisition 10 min. There are numerous studies detailing the benefits of multi-shot EPI in BOLD imaging [13–17]. We avoided using single shot EPI because of its sever geometrical distortion at high field strengths (≥ 7T) and loss of effective spatial resolution as the readout period increases [14, 18, 19]. There is also the possibility of signal loss in single shot EPI due to accumulated magnetic susceptibility or field inhomogeneity [13].
Preprocessing was accomplished through the use of the software packages: AFNI (NIHM, Rockville, MD), FSL (FMRIB, Oxford, UK), DRAMMS (SBIA, Philadelphia, PA) and MATLAB (Mathworks, Natick, MA). Brain tissue masks for resting-state functional images were manually drawn using 3DSlicer (https://www.slicer.org/) and applied for skull-stripping. Motion outliers were detected in the dataset (i.e. data corrupted by extensive motion) and the corresponding time points were recorded so that they could be regressed out in a later step. Functional data were assessed for motion spikes, and large spikes were identified and removed in time-course signals, followed by slice timing correction from interleaved slice acquisition order. Head motion correction (six motion parameters) was carried out using the first volume as a reference image. Normalization was completed by registering functional data to the MRI rat brain atlas described above, using affine registration through DRAMMS. After quality assurance, band-pass filtering (0.01 Hz ~ 0.1 Hz) was preformed to reduce low-frequency drift effects and high-frequency physiological noise for each subject. The resulting images were further detrended and spatially smoothed (full width at half maximum [FWHM] = 0.8 mm). Finally, regressors comprised of motion outliers, the six motion parameters, the mean white matter (WM), and cerebrospinal fluid time series were fed into general linear models (GLM) for nuisance regression to remove unwanted effects.
The region-to-region functional connectivity method was performed to measure the correlations in spontaneous BOLD fluctuations. A network is comprised of nodes and edges; nodes being the ROIs and edges being the connections between regions. The 3D MRI Rat Brain Atlas containing 173 annotated brain regions was used for segmentation. Data are reported in 166 brain areas, as seven regions in the brain atlas were excluded from analysis due to the large size of three brains. These brains fell slightly outside our imaging field of view and thus we did not get any signal from the extreme caudal tip of the cerebellum and underlying brainstem. Whole brains that contain all regions of interest are needed for analyses so rather than excluding the animals, we removed the brain sites across all animals. Voxel time series data were averaged in each node based on the residual images using the nuisance regression procedure. Pearson’s correlation coefficients across all pairs of nodes (13695 pairs) were computed for each subject among all three groups to assess the interregional temporal correlations. The correlation coefficients (ranging from − 1 to 1) were z-transformed using the Fisher’s Z transform for normality. 166 × 166 symmetric connectivity matrices were constructed with each entry representing the strength of edge. Group-level analysis was performed to look at the functional connectivity in controls, and Ɛ4 rats. The resulting Z-score matrices from one-group t-tests were clustered using the K-nearest neighbors clustering method to identify how nodes cluster together and form resting state networks. An arbitrary Z-score threshold of |Z|=2.3 was applied to remove spurious or weak node connections.
Behavioral assay: novel object preference
A novel object preference test (NOP) was used to assess episodic learning and memory related stimulus recognition [20, 21]. The task was performed over the course of two days. On day one, rats were placed into a cube-shaped open field arena (100 cm x 100 cm x 35 cm black opaque plexiglass) for 15 minutes for habituation to the testing environment. The following day, for the first phase of testing (the familiar phase), rats were placed into the apparatus facing an unoccupied corner and allowed to investigate two identical objects (familiar objects) for 5 minutes, and then returned to their home cages for a 90-minute retention phase. After the retention phase, rats were again placed into the arena for an additional 3 minutes, this time with one of the familiar objects removed and replaced with a novel object. Objects for both phases were placed in opposite corners, and were equidistant from each other and the perimeter of the field. Object presentation was counterbalanced for each rat, and the apparatus and objects were cleaned with 30% ethanol between each session to remove scent cues.
Behavioral assay: Barnes maze
The Barnes maze is used to assess spatial learning and memory for various rodent models [22–24]. The maze consists of a circular platform (diameter: 121 cm, elevated 40 cm), with 18 escape holes along the perimeter at 30 cm intervals. A black, removable enclosed Plexiglas “goal” box (l: 40.0 x w:12.7 x h:7.6 cm) was positioned under a single escape hole on the underside of the maze in the same position relative to the testing room across all trials. Between trials, the maze was rotated 45 degrees and the goal box was shifted accordingly for cardinal consistency.
Each trial began by placing an animal inside the goal box for 1 min and then under an enclosed container at the center of the maze for 30 sec. The container was then lifted to start the trial. For each trial, if the animals failed to reach the goal box within the test period (4 min), they were gently nudged into the goal box and allowed to stay for 1 min, and then placed back in their home cages between trials (3 trials/day for 4 days). All animals were analyzed for goal box latency (i.e., the amount of time before the animals entered the goal box), and path efficiency delta (i.e., the difference in path efficiency between acquisition days 1 and 4).
Behavioral assay: elevated plus maze
The Elevated Plus Maze (EPM) is a sensitive assay typically used to screen anxiolytic drug effects and is a valid apparatus for measuring anxious responding in rodents[25]. The apparatus consists of two open and two closed arms (l:30 x w:5 cm) arranged in a plus (“+”) shape elevated to a height of 38.5 cm with an intersecting in a central platform (l:5 x w:5 cm and black Plexiglas walls (15 cm high) lining the closed arms.
Animals were individually placed at the center of the apparatus facing one of the closed arms. The number of entries into the open arms, as well as the duration of time spent beyond a full body length in each arm were recorded for a period of 5 min for each animal. Increased entries and duration of time spent in the open arms is an established index of anxiolytic behavior, while the combine total number of entries into all arms of the maze provides a measure of locomotor activity.
Behavioral assays: statistics
For the NOP, each IR score group average was individually compared to chance (i.e., x̅ = 50%) using a single-sample t-test, where an IR significantly greater than chance denotes preference for the novel object. For all behavioral assays, unless otherwise stated, groups were compared using 2-Way ANOVAs with planned comparison t-tests between Ɛ4 and their respective WT controls and then their respective sex counterparts (e.g., male Ɛ4 vs female Ɛ4, not male Ɛ4 vs female WT) to conserve power. For NOR, Barnes maze, and EPM all trials were digitally recorded. Data were analyzed using manual methods by experimenters blind to treatment condition and verified with automated scoring using ANY-maze® software when possible (Stoelting, Wood Dale, IL).
Availability Of Data And Material
All data can be accessed through a link to Mandeley. DOI to follow