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Research Articles, Neurobiology of Disease

Abnormal Microglia and Enhanced Inflammation-Related Gene Transcription in Mice with Conditional Deletion of Ctcf in Camk2a-Cre-Expressing Neurons

Bryan E. McGill, Ruteja A. Barve, Susan E. Maloney, Amy Strickland, Nicholas Rensing, Peter L. Wang, Michael Wong, Richard Head, David F. Wozniak and Jeffrey Milbrandt
Journal of Neuroscience 3 January 2018, 38 (1) 200-219; https://doi.org/10.1523/JNEUROSCI.0936-17.2017
Bryan E. McGill
1Division of Pediatric and Developmental Neurology, Department of Neurology,
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Ruteja A. Barve
2Genome Technology Access Center, Department of Genetics,
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Susan E. Maloney
3Department of Psychiatry, and
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Amy Strickland
4Department of Genetics, Washington University, St. Louis, Missouri 63110
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Nicholas Rensing
1Division of Pediatric and Developmental Neurology, Department of Neurology,
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Peter L. Wang
4Department of Genetics, Washington University, St. Louis, Missouri 63110
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Michael Wong
1Division of Pediatric and Developmental Neurology, Department of Neurology,
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Richard Head
2Genome Technology Access Center, Department of Genetics,
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David F. Wozniak
3Department of Psychiatry, and
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Jeffrey Milbrandt
4Department of Genetics, Washington University, St. Louis, Missouri 63110
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Abstract

CCCTC-binding factor (CTCF) is an 11 zinc finger DNA-binding domain protein that regulates gene expression by modifying 3D chromatin structure. Human mutations in CTCF cause intellectual disability and autistic features. Knocking out Ctcf in mouse embryonic neurons is lethal by neonatal age, but the effects of CTCF deficiency in postnatal neurons are less well studied. We knocked out Ctcf postnatally in glutamatergic forebrain neurons under the control of Camk2a-Cre. CtcfloxP/loxP;Camk2a-Cre+ (Ctcf CKO) mice of both sexes were viable and exhibited profound deficits in spatial learning/memory, impaired motor coordination, and decreased sociability by 4 months of age. Ctcf CKO mice also had reduced dendritic spine density in the hippocampus and cerebral cortex. Microarray analysis of mRNA from Ctcf CKO mouse hippocampus identified increased transcription of inflammation-related genes linked to microglia. Separate microarray analysis of mRNA isolated specifically from Ctcf CKO mouse hippocampal neurons by ribosomal affinity purification identified upregulation of chemokine signaling genes, suggesting crosstalk between neurons and microglia in Ctcf CKO hippocampus. Finally, we found that microglia in Ctcf CKO mouse hippocampus had abnormal morphology by Sholl analysis and increased immunostaining for CD68, a marker of microglial activation. Our findings confirm that Ctcf KO in postnatal neurons causes a neurobehavioral phenotype in mice and provide novel evidence that CTCF depletion leads to overexpression of inflammation-related genes and microglial dysfunction.

SIGNIFICANCE STATEMENT CCCTC-binding factor (CTCF) is a DNA-binding protein that organizes nuclear chromatin topology. Mutations in CTCF cause intellectual disability and autistic features in humans. CTCF deficiency in embryonic neurons is lethal in mice, but mice with postnatal CTCF depletion are less well studied. We find that mice lacking Ctcf in Camk2a-expressing neurons (Ctcf CKO mice) have spatial learning/memory deficits, impaired fine motor skills, subtly altered social interactions, and decreased dendritic spine density. We demonstrate that Ctcf CKO mice overexpress inflammation-related genes in the brain and have microglia with abnormal morphology that label positive for CD68, a marker of microglial activation. Our findings suggest that inflammation and dysfunctional neuron–microglia interactions are factors in the pathology of CTCF deficiency.

  • behavior
  • chemokine
  • CTCF
  • dendritic spine
  • inflammation
  • microglia

Introduction

CCCTC-binding factor (CTCF) is a ubiquitously expressed, 11 zinc finger DNA-binding domain protein encoded by CTCF in humans and Ctcf in mice. CTCF binds throughout the genome (Wang et al., 2012) at the borders of megabase-scale, 3D chromatin structures called topological associated domains (TADs) (Dixon et al., 2012). CTCF-organized TADs control gene expression by packaging enhancers and promoters into distinct spatial compartments within cell nuclei (Merkenschlager and Nora, 2016). CTCF regulates expression of CNS genes, including homeobox (Hox) gene clusters, in developing spinal cord motor neurons (Narendra et al., 2015) and at protocadherin (Pcdh) gene clusters in the brain (Golan-Mashiach et al., 2012). Knock-down of CTCF disrupts TAD structure, leading to widespread dysregulation of gene expression (Zuin et al., 2014).

CTCF is linked to neurodevelopmental disorders. Individuals with haploinsufficiency for CTCF have a neuropsychiatric phenotype characterized by delayed acquisition of developmental milestones, intellectual disability, and autistic features (Gregor et al., 2013). CTCF also regulates transcription at FMR1, the locus for Fragile X syndrome, a common cause of intellectual disability and autism spectrum disorder (ASD) (Lanni et al., 2013), and binds at sites linked to a broad group of neurodevelopmental disorders (Strong et al., 2015; Meguro-Horike et al., 2011; Mégarbané et al., 2013). In addition, mutations in genes encoding CTCF-interacting proteins cause Cornelia de Lange syndrome (Peters et al., 2008) and Rett syndrome (Kernohan et al., 2010).

In addition to CTCF, inflammation is widely thought to contribute to neurodevelopmental disorders including ASD (Estes and McAllister, 2015). ASD-associated mutations occur in genes encoding immune system components (Estes and McAllister, 2015) and transcriptional profiling of ASD brain tissue enriches for immunity genes (Voineagu et al., 2011). ASD is linked to immune dysfunction including anti-brain autoantibodies (Cabanlit et al., 2007), altered serum and CSF cytokine profiles, and aberrant cell-mediated immune responses (Estes and McAllister, 2015). ASD-associated microglial abnormalities include: increased numbers (Vargas et al., 2005; Tetreault et al., 2012), abnormal morphologies (Morgan et al., 2010), and hyperactivation (Suzuki et al., 2013) of these cells. CTCF regulates the expression of genes encoding the inflammatory mediator interleukin-21 (Park et al., 2016) and human leukocyte antigens (Raj et al., 2016), indicating a connection between CTCF and inflammation.

Although constitutive Ctcf knock-out (KO) mice are lethal in the preimplantation phase of embryogenesis (Moore et al., 2012), conditional Ctcf KO mice have provided valuable information about the role of CTCF in neural development. Both Foxg1-Cre mediated deletion of Ctcf in the embryonic neuroepithelium and Nestin-Cre mediated deletion of Ctcf in embryonic neuroprogenitor cells cause massive apoptosis that is lethal embryonically (Foxg1-Cre) or at delivery (Nestin-Cre) (Watson et al., 2014). Conditional Ctcf KO in embryonic postmitotic projection neurons under the control of Nex-Cre produces mice that have aberrant dendritic arborization, fewer dendritic spines, and die by 4 weeks of age (Hirayama et al., 2012). Thus, during embryogenesis CTCF is a survival factor for neural progenitor cells and later contributes to dendritic microstructure development in postmitotic neurons. However, both the effect of depleting CTCF postnatally and the role of CTCF in neuronal function in adult animals are less well studied.

We explored the role of CTCF in neurons of adult animals by crossing mice carrying a loxP-flanked allele of Ctcf (Heath et al., 2008) with mice transgenic for Camk2a-Cre, which express Cre recombinase in postmitotic, glutamatergic neurons of CA1 hippcampus and layer V cerebral cortex (Tsien et al., 1996). The resulting CtcfloxP/loxP;Camk2a-Cre mice (hereafter Ctcf CKO) developed neurobehavioral impairments, reduced dendritic spine density, upregulation of inflammation-related gene expression, and abnormal microglia. Our data show that: (1) CTCF deficiency in adult mice causes behavioral deficits, (2) CTCF is required outside of development to maintain a normal neuronal gene expression profile, and (3) neuronal CTCF deficiency leads to an aberrant microglia phenotype.

Materials and Methods

Mouse husbandry.

All animal procedures were performed in compliance with the National Institutes of Health's Guide for the Care and Use of Laboratory Animals and approved by the Animal Studies Committee in the Division of Comparative Medicine at Washington University School of Medicine in St. Louis (Protocol #20140044). Mice were housed in a temperature-controlled barrier facility maintained at 24°C. Facility lighting was kept on a fixed 12 h light and 12 h dark cycle. Mice had access to fresh water and rodent chow #5001 (Purina) ad libitum. Mouse health was monitored daily by a staff of licensed veterinarians. Mouse lines used in this experiment have been described previously and include: CtcfloxP (Heath et al., 2008), Camk2a-Cre (Tsien et al., 1996; The Jackson Laboratory stock #005359, RRID:IMSR_JAX:005359), Gt(ROSA)26Sortm9(CAG-tdTomato)Hze (Madisen et al., 2010; The Jackson Laboratory stock #007909, RRID:IMSR_JAX:007909), Thy1-YFPHJrs/J (Feng et al., 2000; The Jackson Laboratory stock #003782, RRID:IMSR_JAX:003782), Rpl22tm1.1Psam/J (Sanz et al., 2009; The Jackson Laboratory stock #011029, RRID:IMSR_JAX:011029), and Cx3cr1tm1Litt/J (Jung et al., 2000; The Jackson Laboratory stock #005582, RRID:IMSR_JAX:005582). We intercrossed CtcfloxP and Camk2a-Cre mice to generate CtcfloxP/loxP;Camk2a-Cre+ (Ctcf CKO) and CtcfloxP/loxP;Camk2a-Cre− (control) mice. We intercrossed CtcfloxP, Camk2a-Cre, and Thy1-YFPHJrs/J mice to generate CtcfloxP/loxP;Camk2a-Cre+;Thy1-YFPHJrs/J+ (Ctcf CKO;YFP) and CtcfloxP/loxP;Camk2a-Cre−;Thy1-YFPHJrs/J+ (control;YFP) mice. Similarly, we intercrossed CtcfloxP, Camk2a-Cre, and Rpl22tm1.1Psam/J mice to generate CtcfloxP/loxP;Camk2a-Cre+; Rpl22tm1.1Psam/J+ (Ctcf CKO;RiboTag) and CtcfloxP/loxP;Camk2a-Cre−; Rpl22tm1.1Psam/J+ (control;RiboTag) mice. We verified the extent of expression of Cre in our Camk2a-Cre mice by intercrossing them with Gt(ROSA)26Sortm9(CAG-tdTomato)Hze mice to generate Gt(ROSA)26Sortm9(CAG-tdTomato)Hze;Camk2a-Cre+ (tdTomato;Camk2a-Cre) mice. We verified that Cx3cr1 and Camk2a expression patterns were nonoverlapping by intercrossing tdTomato;Camk2a-Cre and Cx3cr1tm1Litt/J mice to generate animals with all three alleles, Gt(ROSA)26Sortm9(CAG-tdTomato)Hze;Camk2a-Cre+;Cx3cr1tm1Litt/J (Cx3cr1-EGFP; tdTomato;Camk2a-Cre mice). Both male and female animals were used for all experiments.

Mouse behavioral analysis.

We performed behavioral analysis of two cohorts of Ctcf CKO and control mice. Testing was conducted on the first (adult) cohort of 9 Ctcf CKO and 10 control mice, including 11 females and 9 males, at 3–4 months of age. Mice were evaluated on a 1 h locomotor activity test, a battery of sensorimotor measures, the Morris water maze (MWM), and the social approach test, in that order. Testing of the second (adolescent) cohort of 10 Ctcf CKO (5 males, 5 females) and 10 control mice (6 males, 4 females) occurred at 6–8 weeks of age. These mice were evaluated on a 1 h locomotor activity test, a battery of sensorimotor measures, and the MWM, in that order.

The 1 h locomotor activity test was conducted during a 1 h session inside transparent 47.6 × 25.4 × 20.6 cm high polystyrene enclosures as described previously (Wozniak et al., 2004). Computerized photobeam instrumentation was used to measure ambulatory activity and exploration including total ambulations (whole-body movements), number of vertical rearings, and time spent, distance traveled, and entries made into a central 33 × 11 cm zone.

The sensorimotor battery was performed as described previously (Wozniak et al., 2004) and consisted of the ledge and platform tests (to evaluate balance and fine motor coordination); the pole, 60° inclined screen test, and 90° inclined screen test (to assess agility); the inverted screen test (to assess strength); and the walking initiation test (to assess movement initiation).

The MWM was performed as described previously (Wozniak et al., 2007) in a 118-cm-diameter pool of opaque water monitored by a computerized video tracking and recording system (ANY-maze; Stoelting, RRID:SCR_014289) that computed escape path length and latency to reach the target platform and calculated swimming speed, platform crossings, and time spent in each quadrant of the pool. Testing included cued (visible platform marked by a red tennis ball on a pole), place (submerged platform obscured from view), and probe (platform absent) trials. Both cued and place trials occurred in 2 blocks of 2 trials daily (4 trials per day), with a 2 h break between blocks. Each trial lasted a maximum of 60 s and was followed by a 60 s intertrial interval, during which the mouse was allowed to remain on the platform for the first 30 s. Cued trials occurred over 2 consecutive days. Salient spatial cues were not present in the room during the cued trials and the platform location varied from trial to trial to train the mice to navigate to the platform but minimize spatial learning during this phase of testing. Place trials were initiated 3 d later and occurred over 5 consecutive days. Spatial cues were prominently displayed during these trials to encourage spatial (hippocampal-dependent) learning. The probe trial was conducted 1 h after the last place trial on the fifth day. For the probe trial, spatial cues were again prominently displayed, but the escape platform was completely removed from the pool. The mouse was placed in the pool starting from the quadrant diagonal to the last location of the escape platform and allowed to search the pool for 60 s while time spent in each quadrant and the number of crossings over the previous location of the platform was recorded.

The general procedures for conducting the social approach test were similar to our previously published methods (Dougherty et al., 2013), which were adapted from earlier works (Moy et al., 2004; Silverman et al., 2011). The test involved quantifying sociability, or the tendency to initiate social investigation of an unfamiliar conspecific (stimulus mouse) contained in a small withholding cage, compared with the investigation of an empty withholding cage. The apparatus was a rectangular 3-chambered Plexiglas box (each chamber measuring 19.5 cm × 39 cm × 22 cm) containing Plexiglas dividing walls with rectangular openings (5 × 8 cm) covered by sliding Plexiglas doors. A small stainless-steel withholding cage (10 cm h × 10 cm diameter; Galaxy Pencil/Utility Cup; Spectrum Diversified Designs) was used to sequester a stimulus mouse. The withholding cage consisted of vertical bars, which allowed for restricted social interactions between the mice but prevented fighting and sexual contact, and one cage was located in each outer chamber. A digital video camera connected to a PC loaded with a tracking software program (ANY-maze; Stoelting) recorded the movement of the mouse within the apparatus and quantified time spent in each chamber and in investigation zones surrounding the withholding cages, the latter being scored when the head of the mouse intersected the zones. The investigation zones were 12 cm in diameter, encompassing 2 cm around the withholding cages. The test sequence consisted of three consecutive 10 min trials. For the first trial, each mouse was placed in the middle chamber with the doors to the outer chambers shut to become acclimated to the apparatus. During the second trial, the mouse was allowed to investigate and habituate to all three chambers freely, including the empty withholding cages (Page et al., 2009; Naert et al., 2011; Pobbe et al., 2012). The third (test) trial assessed sociability exhibited toward an unfamiliar stimulus mouse versus the familiar, empty withholding cage by placing an unfamiliar, age- and gender-matched stimulus mouse in one withholding cage while the other was left empty. The test mouse was allowed to explore the apparatus freely and investigate the novel mouse in the withholding cage. The locations of the stimuli mice in the outer chambers were counterbalanced within and across groups.

Mouse electroencephalography.

Adult (3–4 months old) control and Ctcf CKO mice (n = 6/genotype) underwent continuous video-EEG monitoring using standard methods for implanting epidural electrodes and performing continuous video-EEG recordings, as described previously (Erbayat-Altay et al., 2007). Briefly, mice were anesthetized with isoflurane and placed in a stereotaxic frame. Five epidural screw electrodes were surgically implanted on the skull and secured using dental cement. Video and EEG data were acquired simultaneously with a stellate video-EEG acquisition system. Continuous 24/7 video-EEG data were obtained for 6 weeks from each mouse and were analyzed for seizures or interictal epileptiform abnormalities. Electrographic seizures were defined as a characteristic pattern of discrete periods of rhythmic spike discharges that evolved in frequency and amplitude lasting at least 10 s.

Western blot.

We harvested hippocampus and cerebral cortex from adult (3–6 months old) Ctcf CKO and control mice (n = 18 animals per genotype for hippocampus; n = 26 animals per genotype for cerebral cortex). Tissues were snap frozen in liquid nitrogen and homogenized in lysis buffer containing 50 mm Tris pH 7.4, 150 mm NaCl, 1% Triton X-100, 0.5% sodium deoxycholate, 0.1% SDS, 1 mm PMSF, 1 mm sodium orthovanadate, and complete protease inhibitor mixture (Sigma-Aldrich). The lysates were cleared by centrifugation at 13,800 × g for 10 min at 4°C and total protein was quantified using the MicroBCA assay kit (Pierce). Proteins were separated by SDS-PAGE and transferred to nitrocellulose membrane (GE Life Sciences). Membranes were blocked for 1 h at room temperature in 5% nonfat dry milk in Tris-buffered saline with 0.05% Tween (TBST) and incubated overnight at 4°C with either 1:1000 anti-CTCF antibody (Cell Signaling Technology catalog#2899, RRID:AB_2086794) in TBST plus 5% bovine serum albumin or 1:1000 anti-GAPDH antibody (Cell Signaling Technology catalog#5174, RRID:AB_10622025) in TBST plus 5% nonfat dry milk. The next day, membranes were washed with TBST and incubated with 1:5000 goat anti-rabbit conjugated to horseradish peroxidase (GE Life Sciences) in TBST for 2 h at room temperature before a final wash. Membranes were developed with Western Bright Quantum HRP substrate (Advansta). Blots were imaged on a G:Box gel documentation system (Syngene) running GeneSys acquisition software (RRID:SCR_015770). Tag image file format-style images were exported to the Fiji build of ImageJ (RRID:SCR_002285) and analyzed using the Gel Analyzer function.

Total mRNA isolation.

Brain regions were harvested from both male and female adult (3–6 months old) Ctcf CKO and control mice after behavioral testing. Tissues were snap frozen in liquid nitrogen and homogenized in TRIzol (Life Technologies) using a bullet blender (Next Advance). The TRIzol procedure was performed according to the manufacturer's instructions. RNA was purified on NucleoSpin RNA columns with on-column DNase digestion (Machery-Nagel) according to the manufacturer's intructions. RNA concentration was determined using a NanoDrop (Thermo Scientific) and RNA integrity was verified using an Agilent Technologies bioanalyzer and either RNA 6000 nano or pico chips, depending on the concentration of the sample. Only high-quality RNA samples, defined as having both a 260/280 nm aborbance ratio of 1.8 to 2.1 on the NanoDrop and RNA integrity number > 8.0 on the Bioanalyzer, were used in downstream microarray and qRT-PCR applications.

Histology, immunofluorescent antigen detection, and microscopy.

Three- to 6-month-old mice were anesthetized with isoflurane and transcardially perfused with either 4% paraformaldehyde in PBS or, for Timm staining, with 0.9% sodium chloride, 0.37% sodium sulfide sulfide solution, and 4% formaldehyde. Brains were dissected and fixed overnight in 4% paraformaldehyde in PBS, cryopreserved in 30% sucrose in PBS, and embedded in Tissue-Tek optimal cutting temperature compound (Sakura Finetek). Then, 40-μm-thick sections were cut on a cryostat and mounted on Fisherbrand Superfrost/Plus microscope slides, which were air-dried and stored at −20C. Nissl staining was performed with cresyl violet (Sigma-Aldrich) as described previously (Paul et al., 2008). Timm staining was performed as described previously (Guo et al., 2013). Light microscope imaging was performed with a NanoZoomer 2.0-HT digital slide scanner (Hamamatsu). For immunofluorescent antigen detection, frozen sections were washed, antigen retrieved for 30 min at 80°C in 10 mm tribasic sodium citrate dihydrate, 0.05% Triton X-100, pH 6, and blocked in TBST with 10% normal horse serum and 0.3% Triton X-100 for 1 h at room temperature. Sections were incubated with primary antibodies diluted in blocking buffer overnight at 4°C. After 3 5 min washes with PBS, sections were incubated with secondary antibodies diluted in blocking buffer for 1 h at room temperature. Immunostained sections were mounted with Vectashield hard-set mounting medium with DAPI (Vector Laboratories, RRID:AB_2336788). Primary antibodies included the following: 1:100 anti-NeuN (EMD Millipore catalog#ABN78A4, RRID:AB_10920751), 1:500 anti-glial fibrillary acidic protein (GFAP) (Millipore catalog #AB5804, RRID:AB_10062746), 1:500 anti-Iba1 (Wako catalog #019-19741, RRID:AB_839504), 1:200 anti-Ki67 (Vector Laboratories catalog#VP-K451, RRID:AB_2314701), 1:150 anti-Caspase-3 D175A (Cell Signaling Technology catalog#9661, RRID:AB_2341188), 1:400 anti-S100-β (S100B; Dako catalog#Z0311, RRID:AB_10013383), 1:200 anti-CD68 (Bio-Rad catalog#MCA1957GA, RRID:AB_324217). Secondary antibodies included 1:500 anti-rabbit Alexa Fluor 488 (Thermo Fisher catalog #A11034, RRID:AB_2576217) and 1:500 anti-rabbit Cy3 (Jackson Immunoresearch catalog#111-165-144, RRID:AB_2338006). Confocal images were captured with a Leica DMI4000 confocal microscope equipped with diode 405 nm and solid-state 488 and 561 nm lasers and 20×, 63×, and 100× oil-immersion objectives. For each stain and antibody described above, at least eight sections from each of three to six brains per genotype were examined. Representative sections are displayed. The LASX software analysis suite (Leica) was used to generate maximum intensity projections of each image. For each antibody, a uniform threshold was applied to all images from both genotypes. Thresholded images were binarized and imported into the Fiji build of ImageJ (RRID:SCR_002285), which was used to calculate the area of the binary image equivalent to the area of the image occupied by a given antibody. This value was divided by the total image area to determine a percentage area. For CD68, we divided by the Iba-1-positive image area to determine the percentage microglial area occupied by CD68. For quantification of dendritic spines, we collected full-thickness confocal z-stacks of apical dendrites using 100× magnification, 512 × 512 resolution, 3 frame average, and 140nm z-step size (n = 10–20 image stacks per animal, 3 animals per genotype). We selected individual dendrites (n = 50 dendrites/animal for hippocampus, n = 28–32 dendrites/animal for cortex) of at least 10 μm length, generated mean intensity projection images using the LASX software analysis suite (Leica), and counted the number of spines manually, which we report as spines per micrometer of dendrite length. Individuals blinded to genotype performed all counting. We evaluated the patterns of enhanced green fluorescent protein (EGFP) and red fluorescent tdTomato protein in the hippocampus and cerebral cortex of Cx3cr1-EGFP; tdTomato;Camk2a-Cre mice using 10 images of each tissue, which were collected from a total of three animals.

RiboTag isolation of Camk2a-Cre expressing cell-specific mRNA: The RiboTag isolation method was performed as described previously (Sanz et al., 2009). Briefly, hippocampus was dissected rapidly from naive adult mice (2 males and 2 females, each at least 3 months old) and homogenized in polysome buffer consisting of 50 mm Tris, pH 7.5, 100 mm KCl, 12 mm MgCl2, 1% Nonidet P-40, 1 mm DTT, 200 U/ml Rnasin Plus (Promega), 200 U/ml Superasin (Life Technologies), 100 μg/ml cyclohexamide, 1 mg/ml heparin, and 1× complete protease inhibitor tablet mixture (Sigma-Aldrich). Samples were centrifuged at 10,000 × g for 10 min at 4°C. The supernatants were collected and immunoprecipitated with anti-HA antibody (HA.11, BioLegend catalog #901502, RRID:AB_2565007) overnight at 4°C and, the next day, antibody-antigen-RNA complexes were recovered with Dynabeads protein G. The beads were washed 3 times for 5 min each in high-salt buffer consisting of 50 mm Tris, pH 7.5, 300 mm KCl, 12 mm MgCl2, 1% Nonidet P-40, 1 mm DTT, and 100 μg/ml cyclohexamide. Then, the antigen–antibody–RNA complexes were eluted with RA1 buffer (Machery-Nagel) containing 1:100 β-mercaptoethanol. RNA was recovered from the eluate using NucleoSpin RNA columns (Machery-Nagel) with on-column DNase digestion. RNA concentration was determined using a NanoDrop (Thermo Scientific) and RNA integrity was verified using an Agilent Technologies nioanalyzer and either RNA 6000 nano or pico chips, depending on the concentration of the sample. The remainder of each sample was frozen at −80°C until further use.

qRT-PCR.

We used the qScript cDNA synthesis kit (Quanta Bio) to generate cDNA from 10 ng samples of RiboTag-isolated RNA or 500 μg of TRIzol-isolated RNA. qRT-PCR was performed using PerfeCTa SYBR Green FastMix (Quanta Bio) on an ABI Prism 7900HT Sequence Dectection System (Applied Biosystems). All qRT-PCRs were run using a standard program: 2 min at 50°C, 10 min at 95°C, followed by 40 cycles of 15 s at 95°C, 30 s at 60°C, and 30 s at 72°C. The following primer pairs were used: Gapdh 5′-AATGTGTCCGTCGTGGATCT-3′ forward and 5′-GTTGAAGTCGCAGGAGACAA-3′ reverse; C1ql1 5′-CCAACCTAGGCAACAACTAC-3′ forward and 5′-GTAGTTCTGGTCTGCATCCT-3′ reverse; Ccl17 5′-GATGCCATCGTGTTTCTGAC-3′ forward and 5′-CCAATCTGATGGCCTTCTTC-3′ reverse; Tnfrsf12a 5′-GAGAAAAGTTTACTACCCCCATAGAG-3′ forward and 5′-GGCTGACTCCAGAATGAATGAA-3′ reverse; Grk4 5′-GGTGCATTGAATTCTTGGATG-3′ forward and 5′-GGGACTTCTGACTTCTCTTTG-3′ reverse; Nefh 5′-TGCCGCTTACAGAAAGCTC-3′ forward and 5′-GCGTGGATATGGAGGGAATTT-3′ reverse; Tlr2 5′-ACCTCAGACAAAGCGTCAAA-3′ forward and 5′-TTGCTGAAGAGGACTGTTATGG-3′ reverse; Ptgs2 5′-CCAGAGCAGAGAGATGAAATAC-3′ forward and 5′-TCCTTCTCTCCTGTAAGTTCT-3′ reverse; Ccl2 5′-CTCTCTTCCTCCACCACCAT-3′ forward and 5′-CGTTAACTGCATCTGGCTGAG-3′ reverse; Ccl3 5′-TTCTCTGTACCATGACACTCTGC-3′ forward and 5′-CGTGGAATCTTCCGGCTGTAG-3′ reverse; Ccl9 5′-ATCACACATGCAACAGAGACA-3′ forward and 5′-TGGAACCCCCTCTTGCTGAT-3′ reverse; Cd83 5′-GTTGCTCTTCTCTCTGGTTG-3′ forward and 5′-CTTGTTCCGTACCAGGTTTAG-3′ reverse; Cd14 5′-CCACCGCTGTAAAGGAAAGA-3′ and 5′-CCAGAAGCAACAGCAACAAG-3′ reverse; and Cd52 5′-GGTTGTGATTCAGATACAAACAG-3′ forward and 5′-GAGGTAGAAGAGGCACATTAAG-3′ reverse. We used the standard curve method to quantify gene expression levels, which were normalized to Gapdh expression. For analysis of Ctcf expression, n = 6 samples per genotype per tissue were used. For analysis of Tlr2, Ptgs2, Ccl2, Ccl3, Ccl9, Cd83, Cd14, and Cd52, n = 8 samples per genotype were used. For analysis of C1ql1, Ccl17, Tnfrsf12a, Grk4, and Nefh, n = 12 samples per genotype were used.

Microarray analysis.

For microarray on RNA derived from whole hippocampus tissue, RNA was amplified and reverse transcribed to cDNA using the MessageAmpII kit (Life Technologies) according to the manufacturer's instructions. The amplified cDNA was then fluorescently labeled using the Kreatech ULS kit (Kreatech Diagnostics) according to the manufacturer's instructions. Labeled cDNAs were purified on QIAquick PCR purification columns (Qiagen) and quantified using a NanoDrop spectrophotometer. Then, the labeled cDNAs were hybridized to Agilent Technologies mouse GE 4x44k v2 microarrays according to the manufacturer's instructions. Slides were scanned on an Agilent Technologies SureScan microarray scanner to detect fluorescence. Gridding and analysis of images was performed using Agilent Technologies Feature Extraction software version 11.5 (RRID:SCR_014963) and the resulting feature (probe)-extracted .txt data for each sample was used for downstream bioinformatic analysis as described below. For analysis of whole hippocampus gene expression by microarray, we used three independent biological replicates per genotype (Ctcf CKO and control). Each biological replicate consisted of a pool of paired hippocampi from 3 individual mice 3–6 months of age. One Ctcf CKO biological replicate was hybridized twice to microarrays to generate a single technical replicate. Data from both technical replicates were combined and averaged for downstream analysis. In a separate microarray experiment, RiboTag-derived RNA from hippocampus (n = 4 individual Ctcf CKO;RiboTag and Control;RiboTag animals) was processed as described above, except for the following: (1) RNA was amplified and reverse transcribed to cDNA using the WTA2 Complete Whole Transcriptome Amplification Kit (Sigma-Aldrich); and(2) labeled cDNAs were hybridized to Agilent Technologies SurePrint G3 Mouse GE 8x60k microarrays. Microarray data from all experiments described here was submitted to the ArrayExpress Repository (RRID:SCR_002964; accession number pending; Parkinson et al., 2007).

Bioinformatic analysis of microarray data.

Microarray raw data were normalized using IRON: iterative rank order normalization method (Welsh et al., 2013) and analyzed in the R programming environment using the software packages Bioconductor (Huber et al., 2015; RRID:SCR_006442) and limma (Ritchie et al., 2015; RRID:SCR_010943). Results are expressed in terms of fold changes relative to controls and unadjusted p-values. We used a less stringent cutoff of p < 0.05 because we planned to do extensive wet-lab validation of the genes of interest, keeping in mind that FDR or multiple testing corrections can be too restrictive. Genes with a >±1.5 fold change and p < 0.05 were further analyzed for biological pathway enrichment using EnrichR (Chen et al., 2013; RRID:SCR_001575). We report pathways and biological processes with adjusted p < 0.05. To generate a profile for the non-neural component, we compared the profiles of the whole hippocampus and RiboTag-derived samples and “subtracted” the RiboTag-derived genelist from that of the whole hippocampus.

Flow cytometry.

We used flow cytometry to determine the composition of inflammatory cells in the hippocampus and cortex of Ctcf CKO mice. First, we isolated microglia from these brain regions, which were dissected, dispersed in homogenization medium (RPMI 1640 medium; Thermo Fisher catalog #11875085) plus 2% heat inactivated fetal bovine serum and passed through a disposable 70 μm filter to remove debris. Cells were pelleted by centrifugation at 400 × g for 6 min at 4C and resuspended in 40% Percoll in homogenization media. This was carefully layered upon 80% Percoll in homogenization media and centrifuged at 1000 × g for 20 min at 18C. The immiscible layer (containing the inflammatory infiltrate) was collected, washed in homogenization medium, and centrifuged at 400 × g for 6 min at 4C to pellet the cells. The cells were resuspended in flow cytometry buffer (Hanks' balanced salt solution without calcium, magnesium, or phenol red; Thermo Fisher catalog #14175079, +2% heat inactivated fetal bovine serum) and blocked with 1:100 purified anti-mouse CD16/32 antibody (BioLegend catalog #101302, RRID:AB_312801). The cells were then incubated with 1:100 FITC anti-mouse CD45 antibody (BioLegend catalog #103108, RRID:AB_312973) and 1:100 PE/Cy7 anti-mouse/human CD11b antibody (BioLegend catalog #101216, RRID:AB_312799) for 20 min at 4°C protected from light. Samples were stained with SYTOX blue (Thermo Fisher catalog #S348857) at a final concentration of 1 μm per the manufacturer's instructions. Cells were analyzed on a FACScan 2 flow cytometer (BD Biosciences) using a gating strategy similar to one described previously to isolate microglia, myeloid, and lymphoid cells (Galatro et al., 2017). All gating strategies incorporated size and doublet discrimination based on forward and side scatter parameters. Data analysis was performed using FlowJo (RRID:SCR_008520) version 10.4 for Macintosh.

Sholl analysis of microglial morphology.

We performed Sholl analysis of microglial morphology as described previously (Norris et al., 2014). Briefly, we used confocal microscopy to collect full thickness 63× z-stack images of CA1 hippocampus from 40-μm-thick brain sections that were immunostained for Iba-1 and DAPI (as outlined above; n = 6 mice/genotype, 25 image stacks per animal). Z-stacks were collected at 512 × 512 resolution with 3 frame averages for each color channel and 1 μm z-step size. We used LASX software (Leica) to prepare a maximum intensity projection image of the Iba-1 channel, which we thresholded and exported to the Fiji build of ImageJ (RRID:SCR_002285). For each image, we removed surrounding processes manually in Fiji, thereby isolating a total of 25 microglia per mouse. We used the line segment tool to draw a line from the center of each soma to the tip of its longest process, which provided the maximum process length. We used the Sholl analysis plugin (Ferreira et al., 2014), with the first shell set at 10 μm and subsequent shells set at 5 μm step sizes, to determine intersections at each Sholl radius. This also provided the critical radius (radius value with the highest number of intersections), the process maxiumum (the highest number of intersections regardless of radius value), and the number of primary branches (intersections at the first Sholl radius). We measured the soma size in Fiji and counted branch endpoints using the cell counter plugin. Finally, we counted microglia per 63× image stack manually to determine the mean number of microglia per high-power field.

Experimental design and statistical analysis.

ANOVA models and t tests were used to analyze the behavioral data. Repeated-measures ANOVA (rmANOVA) models containing one between-subjects variable (genotype) and one within-subjects (repeated measures) variable (e.g., blocks of trials, time blocks) were typically used to analyze certain variables within the activity, spatial learning/memory, and social approach datasets. The Greenhouse–Geisser adjustment of α levels was used for all within-subjects effects containing more than two levels to help protect against violations of sphericity/compound symmetry assumptions underlying rmANOVA models. Pairwise comparisons were also conducted following relevant overall ANOVA effects and were considered significant according to Bonferroni-corrected levels. This involved controlling familywise error rates by dividing 0.05 by the exact number of comparisons that were conducted and using that criterion value to determine significance. Planned within-subjects contrasts were also conducted when appropriate. Data from measures within the sensorimotor battery and some variables from the probe trial were analyzed with t tests. We analyzed mouse weight, qRT-PCR, dendritic spine, flow cytometry, and immunostaining data for NeuN, GFAP, and cleaved caspase-3 with two-tailed t tests. Western blot data and immunostaining data for S100B, Ki67, and CD68 did not follow a normal distribution and was analyzed with the Mann–Whitney U test. We analyzed microglia intersections per Sholl radius using an rmANOVA model with Greenhouse–Geisser adjustment, using genotype as the between-subjects variable and radius as the within-subjects (repeated measures) variable. Other Sholl measurements were evaluated with two-tailed t tests. Number, age, and sex of animals used in individual experiments are noted above.

Results

To determine the effect of Ctcf KO in postnatal neurons, we bred Ctcf CKO mice by crossing CtcfloxP mice (Heath et al., 2008) with Camk2a-Cre mice, which express Cre recombinase in excitatory glutamatergic neurons of layer V cerebral cortex and CA1 hippocampus under the control of the promoter for Camk2a, the gene encoding α-calcium-calmodulin-dependent kinase II (Tsien et al., 1996). We verified the appropriate Cre expression pattern by crossing Camk2a-Cre mice with a reporter line carrying a Cre-inducible allele of the cytoplasmic, membrane-targeted, red fluorescent protein tdTomato (Gt(ROSA)26Sortm9(CAG-tdTomato)Hze mice; Madisen et al., 2010). At birth, the brains of the resulting Gt(ROSA)26Sortm9(CAG-tdTomato)Hze;Camk2a-Cre mice (hereafter, tdTomato;Camk2a-Cre mice) had no discernible red fluorescence (Fig. 1A,D). By 3 weeks of age, tdTomato;Camk2a-Cre mice had obvious red fluorescence visible in cortex and hippocampus (Fig. 1B,E) and, by 6 weeks of age, red fluorescence was robust in cortex and hippocampus (Fig. 1C,F), consistent with previous reports of the chronology of Camk2a-Cre activity (Tsien et al., 1996).

Figure 1.
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Figure 1.

Ctcf CKO mice have depletion of Ctcf mRNA and CTCF protein. A–C, Midsagittal brain section of tdTomato;Camk2a-Cre+ mouse at birth (A) and at 3 weeks (B) and 6 weeks (C) of age. D–F, Hippocampus of tdTomato;Camk2a-Cre+ mouse at birth (D) and at 3 weeks (E) and 6 weeks (F) of age. For A–F, Cre-dependent expression of floxed tdTomato reporter mice indicates Cre activity. Note that no tdTomato fluorescence is visible at birth. By 6 weeks of age, bright red tdTomato-fluorescence is visible in areas where Camk2a-Cre is active, primarily in olfactory bulbs (olf), cerebral cortex (cc), hippocampus (hc), and striatum (str), whereas tdTomato fluorescence is minimal in brainstem (br) and cerebellum (cb). In the hippocampus, tdTomato is prominent in CA1 (ca1) and dentate gyrus (dg). Scale bars: A–C, 2.5 mm; D–F, 500 μm. G, H, Ctcf mRNA (normalized to Gapdh) was depleted from the hippocampus (n = 6/genotype, t test: t(10) = 3.516, **p = 0.0056; G) and cerebral cortex (n = 6/genotype, t test: t(10) = 2.714, †p = 0.0218; H) of Ctcf CKO mice compared with controls. For both tissues, the Ctcf CKO result is displayed relative to the control, which is set to 1 for comparison. I, J, Representative Western blots of tissue lysates from control and Ctcf CKO mouse hippocampus (I) and cerebral cortex (J), which were probed for CTCF (top) and control GAPDH (bottom). We found reduced levels of CTCF protein relative to GAPDH in both tissues from Ctcf CKO mice, where Camk2a-Cre is highly active. This is quantified in K for hippocampus (n = 18/genotype, Mann–Whitney U = 50, §p = 0.0002) and in L for cerebral cortex (n = 26/genotype, Mann–Whitney U = 125, ‡p < 0.0001). Values are plotted as means ± SEM.

Next, we used qRT-PCR to characterize Ctcf expression levels in the hippocampus (Fig. 1G) and cerebral cortex (Fig. 1H) of Ctcf CKO mice, where Camk2a-Cre was highly expressed, as well as in controls (n = 6 per genotype per tissue). Ctcf expression was reduced in both tissues in Ctcf CKO mice (Fig. 1G; hippocampus: t test, t(10) = 3.516, **p = 0.0056; Fig. 1H; cerebral cortex: t test, t(10) = 2.714, †p = 0.0218). CTCF protein levels also were visibly diminished in lysates from Ctcf CKO hippocampus (Fig. 1I) and cerebral cortex (Fig. 1J) compared with the internal control protein GAPDH. We confirmed this difference by quantifying CTCF and GAPDH protein levels in hippocampus (Fig. 1K, n = 18/genotype, Mann–Whitney U = 50, §p = 0.0002) and cerebral cortex (Fig. 1L, n = 26/genotype, Mann–Whitney U = 125, ‡p < 0.0001). Therefore, we found reductions of Ctcf mRNA and CTCF protein in Ctcf CKO mouse hippocampus and cerebral cortex, both brain regions with high Camk2a-Cre activity.

Ctcf CKO mice were viable for at least 1 year of life, the longest time period at which we evaluated them. The body mass of adult (3–5 months old) Ctcf CKO mice was similar to controls (data not shown, n = 30/genotype, t test, t(58) = 0.3821, p = 0.7038). Likewise, the brain mass of adult (3–4 months old) Ctcf CKO mice was similar to controls (data not shown, n = 18/genotype, t test, t(34) = 0.2167, p = 0.8298). At 1 year of age, in contrast to controls, Ctcf CKO mice displayed hindlimb clasping, a sign of upper motor neuron dysfunction in the CNS (Guyenet et al., 2010).

To determine whether Ctcf CKO mice had deficits of motor performance, we evaluated them on a 1 h locomotor activity test and a battery of 7 sensorimotor tests (Wozniak et al., 2004). In the 1 h locomotor activity test, the adult (3–4 months old) Ctcf CKO mice showed a trend toward higher levels of ambulatory activity during the entire 1 h test, although rmANOVA showed that the main effect of genotype was not significant (Fig. 2; F(1,17) = 4.16, p = 0.057). However, the analysis revealed a genotype × time interaction (Fig. 2; F(5,85) = 3.86, *p = 0.037), where differences were greatest during block 6 (p = 0.028), although these differences were not significant according to Bonferroni correction (p < 0.05/6 = 0.0083). In addition, the control and Ctcf CKO groups each showed significant decreases in activity from block 1 versus block 6 (Fig. 2; †p < 0.00005 and §p = 0.022, respectively). In addition, we found no differences between the adult Ctcf CKO mice and controls with respect to rearing frequency or center-of-the field variables, including time spent, distance traveled, or number of entries in the center of the test arena (data not shown), suggesting comparable levels of emotionality. Results from testing the adolescent (6–8 weeks old) mice on the 1 h locomotor activity test showed that the Ctcf CKO mice and controls did not differ significantly on any of the dependent variables (Table 1).

Figure 2.
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Figure 2.

Locomotor activity levels in adult Ctcf CKO mice. The general ambulatory (horizontal) activity of adult (3–4 months old) Ctcf CKO (n = 9) and control (n = 10) mice was evaluated over a 1 h period. The Ctcf CKO mice tended to have more total ambulations (whole-body movements) across the test session compared with the control group and a significant genotype × time interaction (*p = 0.037) suggested that these differences varied with time. Both control and Ctcf CKO groups showed significant decreases in activity from block 1 versus block 6 (§p < 0.00005 and †p = 0.022, respectively). Values are plotted as means ± SEM.

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Table 1.

Behavioral results from adolescent Ctcf CKO mice and controls

We further evaluated Ctcf CKO mice for deficits in balance, strength, movement initiation, agility, and fine motor coordination with a battery of seven sensorimotor tests (listed in Table 2). Adult Ctcf CKO and control mice performed similarly on all three screen tasks. These results and the finding that they showed similar latencies to initiate movement suggest that the Ctcf CKO were not impaired in strength, agility, or in executing basic movements. However, the Ctcf CKO did exhibit deficits during tasks requiring balance and fine motor coordination. Specifically, the Ctcf CKO mice spent significantly less time balancing on a narrow, elevated Plexiglas ledge (Table 2; t(17) = 2.90, *p = 0.010) and on an elevated small circular platform (Table 2; t(17) = 3.80, **p = 0.001) compared with controls. In addition, adult Ctcf CKO mice took significantly longer times to climb down an elevated pole (Table 2; t(17) = 2.25, *p = 0.038), which requires fine motor coordination between the forelimbs and hindlimbs. Unlike adult animals, adolescent Ctcf CKO mice performed as well as controls on all sensorimotor measures except the pole test, during which adolescent Ctcf CKO mice were slower to descend (Table 1). Therefore, at 3–4 months of age, the Ctcf CKO mice exhibited a normal activity level and normal strength, but displayed subtle deficits in balance and fine motor coordination.

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Table 2.

Performance on a battery of sensorimotor tests of adult Ctcf CKO mice and controls

We evaluated Ctcf CKO mice for deficits of spatial learning and memory by testing them in the MWM (Morris, 1981) and found that adult (3–4 months old) Ctcf CKO mice had severe performance impairments (Fig. 3, Table 3; the table contains inferential statistics for cued and place trials). A two-way rmANOVA of the path length data from the cued (visible platform location) trials (Fig. 3A) yielded a significant genotype × blocks of trials interaction (Fig. 3A; *p = 0.029), but this effect appeared to be due mainly to significantly longer path lengths for the Ctcf CKO mice for only block 3 (p = 0.009). Moreover, within-subjects contrasts indicated that both groups exhibited significantly decreased path lengths across the cued trials (Fig. 3A; block 1 vs block 4; † and §p < 0.00005 for each group), suggesting that both the Ctcf CKO and control mice showed evidence of learning to swim to the cued platform locations. rmANOVA of the escape latency data (Fig. 3B) revealed a significant genotype effect (Fig. 3B; **p = 0.004), but analysis of the swim velocity data (Fig. 3C) showed that the latency data were artifactually exaggerated by significantly slower swimming velocities on the part of the Ctcf CKO mice across the blocks of trials (Fig. 3C; genotype effect, ***p = 0.0003). Therefore, although the slower swimming velocities of the Ctcf CKO mice confirmed the results from the sensorimotor battery showing possible fine motor coordination deficits, the results suggest that this functional disturbance had minimal effects on the cued learning of the Ctcf CKO group as indexed by the path length variable.

Figure 3.
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Figure 3.

Adult Ctcf CKO mice exhibit severe deficits in spatial learning and memory in the MWM. Adult (3–4 months old) Ctcf CKO (n = 9) and control (n = 10) mice were evaluated in the MWM to assess spatial learning and memory. A, rmANOVA of the path length data from the cued trials revealed a significant genotype × blocks of trials interaction (*p = 0.029), but path lengths were significantly increased in the Ctcf CKO mice for only block 3 (p = 0.009). Moreover, path lengths were significantly reduced across the cued trials (block 1 vs block 4; † and §p < 0.00005 for each group), suggesting that both the Ctcf CKO and control mice showed evidence of cued learning. B, rmANOVA of the escape latency data revealed a significant main effect of genotype (**p = 0.004), but this effect was confounded by differences between the groups in swimming velocities (C) thus making the use of latency as a performance variable inappropriate. C, Analysis of the swim velocity data showing that the Ctcf CKO mice were significantly slower on average across the blocks of trials (genotype effect: ***p = 0.0003), with significant differences being observed for blocks 2 (p = 0.003), 3 (p = 0.003), and 4 (p = 0.0001). D, Analysis of the place (spatial learning) trials revealed severe acquisition deficits in the Ctcf CKO mice compared with the control group in terms of path length, (genotype effect: ***p = 0.0009). Importantly, the control group showed a significant decrease in path length across blocks of trials (block 1 vs block 5: §p = 0.0001), whereas the Ctcf CKO mice did not show improved performance during acquisition training, suggesting that the control mice learned the location of the hidden platform, whereas the Ctcf CKO mice failed to do so. Significant between-groups differences were observed for blocks 4 (p = 0.0004) and 5 (p < 0.00005). E, Similar findings were observed with regard to escape latency (genotype effect: **p = 0.001) although this effect was confounded once more by the Ctcf CKO group again displaying significantly decreased swimming velocities (F, genotype effect: *p = 0.014; block 3: p = 0.007). G, H, Retention performance of the Ctcf CKO mice was also profoundly impaired during the probe trial, where they made significantly fewer platform crossings (***p = 0.0006; G) and spent significantly less time in the target quadrant (**p = 0.003; H) compared with controls. I, Control group exhibited spatial bias for the target quadrant by spending significantly more time in it versus the times spent in each of the other quadrants (**p < 0.004), indicating that they learned and retained the hidden platform location, whereas the Ctcf CKO mice did not. Values are plotted as means ± SEM. For the cued and place trials, p-values for relevant individual pairwise comparisons between genotypes are shown within parentheses for individual blocks.

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Table 3.

Results of repeated-measures ANOVA on Morris water maze data from Ctcf CKO mice and controls

Analysis of the data from the place trials showed robust acquisition deficits (Fig. 3D) in the Ctcf CKO mice compared with the control group in terms of path length, (Fig. 3D; genotype effect: ***p = 0.0009), with the greatest differences occurring during blocks 4 and 5 (p = 0.0004 and p < 0.0005, respectively). Importantly, the control group showed a significant decrease in path length across blocks of trials (Fig. 3D; block 1 vs block 5: §p = 0.0001), whereas the Ctcf CKO mice did not, but rather exhibited similar path lengths throughout acquisition training, suggesting that the control mice learned the location of the hidden platform whereas the Ctcf CKO mice failed to do so. Similar findings were observed with regard to escape latency, although differences were spuriously increased (Fig. 3E) because the Ctcf CKO group again showed significantly decreased swimming velocities compared with the control mice (Fig. 3F).

Consistent with the place learning results, the retention performance of the Ctcf CKO mice was impaired profoundly across all three dependent variables analyzed from the probe trial. Specifically, the Ctcf CKO group made significantly fewer platform crossings (Fig. 3G; t(17) = 4.17: ***p = 0.0006) and spent significantly less time in the target quadrant (Fig. 3H; t(17) = 3.46: **p = 0.003) compared with controls. Moreover, within-subjects contrasts showed that the control group exhibited spatial bias for the target quadrant by spending significantly more time in it versus the times spent in each of the other quadrants (Fig. 3I; **p < 0.004), whereas the Ctcf CKO mice did not. In summary, the 3- to 4-month-old Ctcf CKO mice exhibited severe spatial learning and memory impairments to the degree that there was no evidence that any learning had occurred in these mutant mice. Although the Ctcf CKO had significantly slower swimming velocities that may have affected their MWM performance, the lack of differences in path length during the cued trials suggest that the spatial learning and memory deficits were likely cognitive in nature rather than the result of nonassociative influences.

In contrast to the severe spatial learning and memory deficits exhibited by the 3- to 4-month-old Ctcf CKO mice, the adolescent Ctcf CKO mice did not show convincing evidence of impairments during MWM testing relative to the control group (Table 1). Specifically, no significant effects involving genotype were found for any of the MWM variables with the exception of escape latency during the place condition (*p = 0.032; Table 1). However, no significant differences were observed for the path length data during the place trials and no differences were found for any of the probe trials variables, suggesting that the escape latency findings may have been affected by differences in swimming speeds.

We assessed Ctcf CKO mice for potential deficits in sociability by quantifying investigatory behaviors during the social approach test (Dougherty et al., 2013; Silverman et al., 2011; Moy et al., 2004). During habituation, in which no conspecific (stimulus mouse) was present, both Ctcf CKO and control mice tended to explore the target zone surrounding the withholding cage that would later contain the stimulus mouse compared with the withholding cage that would remain empty, but analysis of the data did not yield any significant effects involving genotype (Fig. 4A). However, when a stimulus mouse was introduced into the target withholding cage for the test trial, only controls preferred to investigate it (Fig. 4B). This was documented by a significant genotype × zone interaction effect (Fig. 4B; F(1,17) = 6.55, *p = 0.020), followed by planned within-subjects comparisons showing that the control mice spent significantly more time in the investigation zones surrounding the stimulus mouse compared with the one surrounding the empty withholding cage (Fig. 4B; ***p = 0.0004), whereas the Ctcf CKO group showed no differences in zone times. Latencies to enter both investigation zones were similar during habituation (Fig. 4C), but, during the test trial (Fig. 4D), Ctcf CKO mice had significantly longer latencies, on average, to enter the two investigation zones (Fig. 4D; genotype effect: F(1,17) = 5.82, *p = 0.027). This effect was mostly due to significantly increased zone latencies in the Ctcf CKO mice compared with the control group for the target zone around the stimulus mouse, (Fig. 4D; F(1,17) = 7.04, §p = 0.017). Therefore, although there were no significant genotype effects concerning the test trial variables, the results of planned comparison suggested that 3- to 4 month-old Ctcf CKO mice exhibit reduced levels of social interaction with a conspecific, possibly indicating abnormally low levels of sociability.

Figure 4.
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Figure 4.

Adult Ctcf CKO mice exhibit decreased levels of sociability in the social approach test. Potential disturbances in sociability were assessed by quantifying investigatory behaviors during the social approach test. A, During the habituation trial, both the Ctcf CKO (n = 9) and control mice (n = 10) tended to explore the target zone surrounding the withholding cage that would later contain the stimulus mouse compared with the withholding cage that would remain empty during the test trial, but statistical analysis of the data yielded no significant effects involving genotype. B, In the test trial, control mice, but not Ctcf CKO mice, spent more time exploring the target investigation zone surrounding the withholding cage containing the stimulus mouse and less time exploring the zone surrounding the empty withholding cage. This was documented by a significant genotype × zone interaction (*p = 0.020) and planned comparisons showing that the control mice spent significantly more time in the investigation zones surrounding the stimulus mouse compared with the one surrounding the empty withholding cage (***p = 0.0004), whereas the Ctcf CKO group showed no differences in zone times. C, During habituation, latencies to enter both investigation zones were similar between genotypes. D, However, during the test trial, Ctcf CKO mice had significantly longer latencies, on average, to enter the two investigation zones surrounding the withholding cages (genotype effect: *p = 0.027). This effect was primarily due to increased zone latencies in the Ctcf CKO mice compared with controls for the target zone around the stimulus mouse withholding cage (§p = 0.017). Data are shown as means ± SEM.

Hippocampal seizures impair spatial learning and sociability in rodents (Gilbert et al., 2000; Krishnan et al., 2017). Therefore, we performed EEG recording of adult Ctcf CKO and control mice (n = 6 per genotype, 6 weeks of continuous monitoring per animal) to screen for seizure activity. No seizures were detected in Ctcf CKO mice (data not shown).

After our behavioral phenotyping of Ctcf CKO mice, we performed detailed histological analyses of their brains. We used adult mice that were 3–4 months old, the same age at which we identified behavioral abnormalities. Nissl staining of neuronal cell bodies was similar between Ctcf CKO mice and controls, indicating that gross neuroanatomical structures were preserved in Ctcf CKO mice (Fig. 5A,B). The pattern of Timm silver sulfide staining (Danscher and Zimmer, 1978) was similar between Ctcf CKO and control mice (Fig. 5C,D), indicating that the overall anatomy of synaptic vesicle-containing nerve fiber tracts was preserved. We performed immunostaining on brain sections from Ctcf CKO and control mice (n = 3 mice/genotype) and evaluated cerebral cortex for the neuron-specific antigen NeuN (Fig. 5E,F; n = 24 images/genotype) and the astrocyte antigens GFAP (Fig. 5G,H; n = 12 images/genotype) and S100B (Fig. 5I,J; n = 8 images/genotype). We quantified the percentage area of each section stained by each antibody and found no significant differences between genotypes (Fig. 5Q–S; NeuN: t test, t(46) = 0.6865, p = 0.4958; GFAP: t test, t(22) = 0.9306; p = 0.3621; and S100B: Mann–Whitney U = 18, p = 0.1605). Similarly, we evaluated CA1 hippocampus from sections immunostained for NeuN (Fig. 5K,L; n = 13 CKO and 12 control images), GFAP (Fig. 5M,N; n = 12 images/genotype), and S100B (Fig. 5O,P; n = 6 CKO and 7 control images). Again, quantification of the area stained by each antibody revealed no differences between genotypes (Fig. 5T–V; NeuN: t test, t(23) = 1.08, p = 0.2912; GFAP: t test, t(22) = 0.5123, p = 0.6136; and S100B: Mann–Whitney U = 15, p = 0.4452). Overall, we found that Ctcf CKO and control mouse brains have similar structural features, including equivalent complements of neurons and astrocytes.

Figure 5.
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Figure 5.

Brain neuroanatomy of Ctcf CKO mice is grossly normal. A, B, Nissl (cresyl violet) staining of brain from control animals (A) and Ctcf CKO animals (B) demonstrating typical neuroanatomic structures in mice of both genotypes. C, D, Timm's silver sulfide staining of brain from control animals (C) and Ctcf CKO animals (D) was also similar. E, F, NeuN staining for neurons was similar in the cerebral cortex of control animals (E) and Ctcf CKO animals (F; quantitated in Q). G, H, GFAP staining for astrocytes was similar in the cerebral cortex of control animals (G) and Ctcf CKO animals (H; quantitated in R). I, J, Staining for the astrocyte marker S100B was also similar in the cortex of control animals (I) and Ctcf CKO mice (J; quantitated in S). K, In CA1 hippocampus, NeuN staining was similar between control and (L) Ctcf CKO animals (quantitated in T). M, N, GFAP staining in CA1 hippocampus was similar between control animals (M) and Ctcf CKO mice (N; quantitated in U). O, P, S100B staining in CA1 hippocampus also was similar between control animals (O) and Ctcf CKO animals (P; quantitated in V). Images in E–P are counterstained with the nuclear indicator DAPI. Scale bars: A–D, 1 mm; E–J, 75 μm; K–P, 300 μm. In Q–V, we quantified the percentage area of CA1 hippocampus and cortex stained with each antibody (n = images from at least 3 animals per genotype). All quantitative comparisons were nonsignificant (NS) as follows: NeuN cortex (n = 24 images/genotype, t test: t(46) = 0.6865; p = 0.4958; Q); GFAP cortex (n = 12 images/genotype, t test: t(22) = 0.9306; p = 0.3621; R); S100B cortex (n = 8 images/genotype, Mann–Whitney U = 18, p = 0.1605; S); NeuN CA1 hippocampus (n = 13 CKO and 12 control images, t test: t(23) = 1.08, p = 0.2912; T); GFAP CA1 hippocampus (n = 12 images/genotype, t test: t(22) = 0.5123, p = 0.6136; U); and S100B CA1 hippocampus (n = 6 CKO and 7 control images, Mann–Whitney U = 15, p = 0.4452; V). Therefore, we found the density of neurons and astrocytes in the brains of Ctcf CKO and control mice to be similar. Data are shown as means ± SEM.

We also evaluated cell turnover in Ctcf CKO and control mice (n = 3 mice/genotype) by immunostaining for Ki67, a marker of dividing cells (Fig. 6A,B; n = 63 control sections, n = 53 Ctcf CKO sections), and cleaved caspase-3, a marker of cell death (Fig. 6D,E; n = 12 sections/genotype). There were no significant differences between Ctcf CKO mice and controls with regard to either the number of Ki67+ cells/section (Fig. 6C; Mann–Whitney U = 1465, p = 0.2547) or the number of cleaved caspase-3+ cells/section (Fig. 6F; t test: t(22) = 1.749, p = 0.0942). In summary, cell turnover was similar between Ctcf CKO and control mice.

Figure 6.
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Figure 6.

Ctcf CKO mice have normal levels of cell birth and cell death. A, B, Immunostaining for Ki67, an antigen marker of proliferating cells, in control (A) and Ctcf CKO (B) mouse dentate gyrus. C, Quantification of Ki67+ cells based on manual counting of 40-μm-thick brain sections. Most positive cells were present in the dentate gyrus in both groups (n = 63 control sections, n = 53 Ctcf CKO sections, Mann–Whitney U = 1465, p = 0.2547). D, E, Immunostaining for cleaved caspase-3, an antigen marker of apoptotic cells, in control (D) and Ctcf CKO (E) mouse dentate gyrus. Positive cells were rare. Dentate gyrus is shown for comparison with Ki67 above. F, Quantification of cleaved caspase-3+ cells based on manual counting of 40-μm-thick brain sections (n = 12 sections/genotype, t test: t(22) = 1.749, p = 0.0942). Main panel images were taken at 20× magnification. Scale bars, 500 μm. Arrowheads indicate areas of interest depicted in inset images. Insets were taken at 63× magnification. Scale bars, 25 μm. NS, Not significant. Data are shown as means ± SEM.

Dendritic spines are the anatomic structures where most synapses occur on gluatamatergic neurons (Alvarez and Sabatini, 2007). Decreased dendritic spine number is observed in animal models of neurodevelopmental disorders including ASD and intellectual disability (Martínez-Cerdeño, 2017). Ctcf;Nex-Cre conditional KO mice have decreased spine number (Hirayama et al., 2012) and we suspected that Ctcf CKO mice harbored a similar abnormality given their behavioral phenotype. To evaluate dendritic spines in Ctcf CKO mice, we intercrossed them with mice carrying a Thy1-YFP transgene and visualized microscopically brain sections from Ctcf CKO;Thy1-YFP mice and controls carrying the CtcfloxP and Thy1-YFP alleles in the absence of Cre. Compared with controls, Ctcf CKO mice had a significant reduction in dendritic spine density in both layer V of the cerebral cortex (Fig. 7A–C; t test, t(179) = 5.533, ****p < 0.0001) and CA1 hippocampus (Fig. 7D–F; t test, t(298) = 6.731 ****p < 0.0001), the two regions where Camk2a-Cre is primarily expressed. Therefore, Ctcf CKO mice have decreased numbers of dendritic spines in brain regions deficient for CTCF, similar to Ctcf;Nex-Cre conditional KO mice and reminiscent of neuropathologic changes observed in human disorders linked to cognitive dysfunction.

Figure 7.
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Figure 7.

Ctcf CKO mice have decreased dendritic spine density in CA1 hippocampus and cerebral cortex. Individual proximal dendrites from adult (3 months old) control and Ctcf CKO mice carrying a Thy1-YFP allele were imaged with a confocal microscope. The number of dendritic spines (n = 3 animals/genoype, 50 dendrites/animal for hippocampus, 28–32 dendrites/animal for cortex) in each image was quantified. Representative dendrites from layer V of the cerebral cortex of control (A) and Ctcf CKO (B) mice are displayed. C, Ctcf CKO mice had fewer spines per micron than controls in the cerebral cortex (20% reduction, t test: t(179) = 5.533, ****p < 0.0001). Representative dendrites from the CA1 hippocampus of control (D) and Ctcf CKO (E) mice are displayed. F, Ctcf CKO mice also had fewer spines per micron than controls in the CA1 hippocampus (15% reduction, t test: t(298) = 6.731, ****p < 0.0001). Data are shown as means ± SEM.

We went on to characterize gene expression in Ctcf CKO mouse hippocampus by performing microarray analysis of mRNA isolated from pooled tissue from Ctcf CKO mice and controls (n = 3 samples/genotype). We identified 367 upregulated genes and 148 downregulated genes (p < 0.05, fold change >±1.5) in Ctcf CKO hippocampus, including Ctcf. We used the EnrichR bioinformatics tool (Chen et al., 2013) to explore gene ontology–biological process (GO-BP) terms enriched in our list of upregulated genes (Fig. 8A). Suprisingly, most of the significant terms that we identified (45% or 19/42) were related to inflammation, including the overall second-ranked term, regulation of leukocyte migration (GO:0002685; p = 0.0030).

Figure 8.
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Figure 8.

Ctcf CKO mice have increased expression of inflammation-related genes in the hippocampus. mRNA was isolated from the hippocampus of control and Ctcf CKO mice and hybridized to Agilent Technologies 4x44k v2 mouse microarrays (n = 3 samples/genotype, see methods for details). A, Enrichr analysis of upregulated genes from Ctcf CKO mouse hippocampus identified enrichment for 19 gene ontology (biological process) terms related to inflammation. Each bar is labeled with its computed Benjamini–Hochberg adjusted p-value and the bar length corresponds to the magnitude of the Enrichr combined score. B, qRT-PCR for inflammation-related genes on hippocampal mRNA (n = 8 samples/genotype) confirmed significant upregulation of genes Tlr2 (2.8-fold upregulated, t test: t(14) = 3.762, **p = 0.0021), Ptgs2 (encoding COX2; 1.3-fold upregulated, t test: t(14) = 2.57, *p = 0.0222), Ccl2 (encoding MCP-1; 2.4-fold upregulated, t test: t(14) = 3.033 **p = 0.0089), Ccl3 (3.5-fold upregulated, t test: t(14) = 6.259, ****p < 0.0001), Ccl9 (2.0-fold upregulated, t test: t(14) = 2.634, *p = 0.0196), Cd83 (1.5-fold upregulated, t test: t(14) = 5.378, ****p < 0.0001), Cd14 (2.6-fold upregulated, t test: t(14) = 4.461, ***p = 0.0005), and Cd52 (2-fold upregulated, t test: t(14) = 3.545, **p = 0.0032). Data are shown as means ± SEM.

We used qRT-PCR to independently confirm overexpression of inflammation-related genes identified by our bioinformatics analysis (Fig. 8B), including: Tlr2, encoding toll-like receptor 2, which activates brain microglia (t test, t(14) = 3.762, **p = 0.0021; Hayward and Lee, 2014), and Ptgs2, encoding prostaglandin-endoperoxide synthase 2/COX2, which synthesizes inflammatory prostaglandins (t test, t(14) = 2.57, *p = 0.0222; Minghetti, 2004). We also confirmed overexpression of genes encoding secreted inflammatory proteins called chemokines (Miller et al., 2008), including: Ccl2, encoding C-C motif chemokine ligand 2/MCP-1 (t test, t(14) = 3.033 **p = 0.0089); Ccl3, encoding C-C motif chemokine ligand 3 (t test, t(14) = 6.259, ****p < 0.0001); and Ccl9, encoding C-C motif chemokine ligand 9 (t test, t(14) = 2.634, *p = 0.0196). We further confirmed overexpression of microglia markers, including: Cd83, encoding CD83 antigen (t test, t(14) = 5.378, ****p < 0.0001; Fujimoto and Tedder, 2006); Cd14, encoding CD14 antigen (t test, t(14) = 4.461, ***p = 0.0005; Becher et al., 1996); and Cd52, encoding CD52 antigen (t test, t(14) = 3.545, **p = 0.0032; Chatterjee et al., 2014). The enrichment of inflammation-related genes in Ctcf CKO mouse hippocampus suggested to us that immune dysfunction might contribute to the phenotype of these animals given the role of inflammation in neurodevelopmental disorders such as ASD (Estes and McAllister, 2015).

Next, we sought to assess the transcriptional profile of Camk2a-expressing cells to distinguish altered gene expression specific to Ctcf-deficient neurons from secondary changes in non-neuronal cells. To this end, we intercrossed Ctcf CKO and RiboTag mice (Sanz et al., 2009), which express a hemagglutinin-tagged version of ribosomal protein Rpl22 in cells expressing Cre-recombinase. We performed affinity purification of HA-tagged ribosomes and associated mRNA from Camk2a-Cre expressing cells in the hippocampus of Ctcf CKO;RiboTag and Camk2a-Cre;RiboTag control mice (n = 4 individual animals per genotype) and analyzed differential gene expression by microarray. We identified 312 upregulated and 167 downregulated genes (p < 0.05, fold change >±1.5). We analyzed the list of upregulated genes to identify ones capable of triggering increased expression of inflammation-related genes, such as those observed in whole hippocampus. We used qRT-PCR to independently confirm overexpression of four such genes in Ctcf CKO;RiboTag samples (Fig. 9), including: C1ql1, encoding complement C1q-like 1, a neuronally expressed complement protein involved in activity-dependent synapse formation (t test, t(22) = 2.563, *p = 0.0177; Yuzaki, 2017); Ccl17, encoding C-C motif chemokine ligand 17 (also known as thymus- and activation-regulated chemokine, or TARC), a neuronally expressed chemokine (t test, t(22) = 4.759, ****p < 0.0001; Henry et al., 2015); Tnfrsf12a, encoding TNF receptor superfamily member 12A (also known as fibroblast growth factor-inducible 14, FN14, or TNF-related weak inducer of apoptosis receptor, TWEAK-R), a receptor for microglia-produced cytokines (t test, t(22) = 4.025, ***p = 0.0006; Winkles, 2008); and Grk4, encoding G-protein-coupled receptor kinase 4 (t test, t(22) = 2.119, *p = 0.0457), a member of a family of kinases that interact with chemokine receptors (Ali et al., 2000). We also identified upregulation of Nefh, encoding neurofilament heavy polypeptide, a marker of neuronal injury (t test, t(22) = 2.548, *p = 0.0183; Gresle et al., 2008).

Figure 9.
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Figure 9.

Hippocampal Camk2a-Cre-expressing neurons lacking Ctcf overexpress immunomodulatory genes. RiboTag-isolated mRNA from Camk2a-Cre-expressing hippocampal cells in control;RiboTag and Ctcf CKO;RiboTag mice (n = 4 samples/genotype) was hybridized to Agilent Technologies 8x60k mouse microarrays. We confirmed overexpression of select genes by qRT-PCR on RiboTag-isolated mRNA (n = 12 samples/genotype), including C1ql1 (1.9-fold upregulated, t test: t(22) = 2.563, *p = 0.0177), Ccl17 (encoding TARC; 1.9-fold upregulated, t test: t(22) = 4.759, ****p < 0.0001), Tnfrsf12a (encoding FN14/TWEAK-R; 1.8-fold upregulated, t test: t(22) = 4.025, ***p = 0.0006), Grk4 (1.7-fold upreglated, t test: t(22) = 2.119, *p = 0.0457), and Nefh (1.3-fold uprelated, t test: t(22) = 2.548, *p = 0.0183). Data are shown as means ± SEM.

We compared the gene expression profiles obtained from both microarray experiments by “subtracting” the RiboTag-derived Ctcf CKO-profile from the whole hippocampus Ctcf CKO profile. We observed upregulation of microglia markers (e.g., Cd14, Cd52, Cd83, Tlr2; Zhang et al., 2014) in the “non neural” component; that is, increased expression in the Ctcf CKO whole hippocampus, but not in the Ctcf CKO RiboTag set. This suggested the presence of microglia in the hippocampus and led us to investigate the composition of inflammatory cells in the relevant brain regions of Ctcf CKO mice.

First, we performed flow cytometry to isolate live cells from dissociated hippocampal and cerebral cortical tissues of Ctcf CKO and control mice (n = 14/genotype; Fig. 10A–D). We used CD45 and CD11b expression to identify inflammatory cells and sort them into three populations: microglia (CD11b high, CD45 intermediate); myeloid cells, including macrophages and neutrophils (CD11b high, CD45 high); and lymphoid cells, including B and T lymphocytes (CD11b low, CD45 high; Galatro et al., 2017). We found no effect of genotype on the proportion of cells of each lineage isolated from cerebral cortex (Figure 10E–G; microglia t test: t(27) = 1.61, p = 0.1189; myeloid cells t test: t(27) = 1.72, p = 0.0969; lymphoid cells t test: t(27) = 0.9363, p = 0.3574). However, compared with controls, (Fig. 10H) the inflammatory cells isolated from Ctcf CKO hippocampus (Fig. 10I) had an increased proportion of microglia (Fig. 10J; t test, t(27) = 2.214, *p = 0.0355) and a decreased proportion of myeloid cells (Fig. 10J; t test, t(27) = 2.128, †p = 0.0426); the proportion of lymphoid cells in the hippocampus was similar between genotypes (Fig. 10J; t test, t(27) = 1.671, p = 0.1062).

Figure 10.
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Figure 10.

Flow cytometry revealing an increased proportion of CD11b high, CD45 intermediate microglia in the hippocampus of Ctcf CKO mice. Flow cytometry was performed on Ctcf CKO and control mouse hippocampus (n = 14/genotype). A–C, Whole hippocampus and cerebral cortex cell suspensions (A) were gated for cells (B), which in turn were gated for single cells (C). D, SYTOX blue-negative, live cells were selected and sorted according to CD11b and CD45 status as shown in E, F, H, and I. Populations of CD11b-high, CD45-intermediate microglia, CD11b-high, CD45-high myeloid cells, and CD11b-low, CD45-high lymphoid cells were discernible. E, Compared with control cortex samples, (F) Ctcf CKO cortex samples had similar proportions of microglia (quantified in G), t test: t(27) = 1.61, p = 0.1189), myeloid cells (t test: t(27) = 1.72, p = 0.0969), and lymphoid cells (t test: t(27) = 0.9363, p = 0.3574). NS, Not significant. H, Compared with control hippocampus samples, (I) Ctcf CKO hippocampus samples had a higher proportion of microglia (quantified in J, t test: t(27) = 2.214, *p = 0.0355) and a lower proportion of myeloid cells (t test: t(27) = 2.128, †p = 0.0426), whereas the proportion of lymphoid cells was unchanged (t test: t(27) = 1.671 p = 0.1062). Data are shown as means ± SEM.

Next, we performed immunofluorescent staining for Iba1, a marker of microglia (Imai et al., 1996; Fig. 11A–D). We focused on the hippocampus because flow cytometry had indicated an increased proportion of microglia there. We quantified the number of Iba1-positive microglia in CA1 hippocampus and found a significant increase in the number of these cells in Ctcf CKO mice (Table 4; t test, t(298) = 5.478, ****p < 0.0001). Compared with control microglia (Fig. 11E), we observed that microglia from Ctcf CKO mouse hippocampus had a highly bristled appearance (Fig. 11F) and uniquely demonstrated amoeboid morphology (Fig. 11G) and rod-like morphology (Fig. 11H). We evaluated microglia morphology in Ctcf CKO mice by Sholl analysis (Fig. 11I–K, Table 4; n = 6 mice/genotype, 25 microglia per mouse), which confirmed both our observation of rod-like morphology by identifying increased maximum branch length (Table 4; t test, t(298) = 2.376, *p = 0.0181) and our observation of amoeboid morphology by identifying enlarged soma area (Table 4; t test, t(298) = 4.362, ****p < 0.0001). The bristled appearance of Ctcf CKO microglia was reflected by increased branch endpoint number (Table 4; t test, t(298) = 2.781, **p = 0.0058) and an overall increase in the number of process intersections per Sholl radius from Ctcf CKO microglia (Fig. 11K; rmANOVA, genotype effect, F(1,298) = 4.549, *p = 0.0338). Therefore, we found that microglia, the main mediators of innate immunity in the brain, are increased in number and have abnormal morphology in the hippocampus of Ctcf CKO mice.

Figure 11.
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Figure 11.

Hippocampal microglia in Ctcf CKO mice are morphologically abnormal. A–D, Iba1 staining of control (A) and Ctcf CKO (B) cerebral cortex and of control (C) and Ctcf CKO (D) hippocampus demonstrating increased staining for Iba1-positive microglia in Ctcf CKO tissues. E, F, High-power image of anti-Iba1 immunostained CA1 hippocampus from control (E) and Ctcf CKO (F) mice. G, H, Microglia with amoeboid morphology (double arrowhead; G) and rod-shaped microglia (single arrowheads; H) were observed in Ctcf CKO mice, but not in controls. I, Example of thresholded mean intensity projection of Iba1-stained image from CA1 hippocampus of the type used for Sholl analysis. J, Example of single microglial cell with concentric Sholl radii (pink circles) superimposed on the image. K, Sholl analysis (n = 6 mice/genotype, 25 microglia per mouse) identified an overall increase in the number of process intersections per radius in microglia from the CA1 region of Ctcf CKO mice (rmANOVA, genotype effect: F(1,298) = 4.549, *p = 0.0338). Note that only microglia from Ctcf CKO mice had processes that extended ≥ 65 μm from the soma. Scale bars: A, B, 75 μm; C, D, 375 μm; E–J, 25 μm. Graph in K shows means ± SEM.

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Table 4.

Summary of Sholl analysis of hippocampal microglia from Ctcf CKO mice and controls

We sought to determine whether microglia express Camk2a-Cre, which would lead to microglial CTCF deficiency in Ctcf CKO mice. We generated Cx3cr1-EGFP; tdTomato;Camk2a-Cre mice, which produce EGFP in microglia and red fluorescent tdTomato protein in Camk2a-Cre-expressing cells. We used confocal microscopy to collect images from CA1 hippocampus (Fig. 12A–D) and cerebral cortex (Fig. 12E–H) of Cx3cr1-EGFP; tdTomato;Camk2a-Cre mice (n = 10 images obtained from a total of 3 mice). Neither EGFP-positive microglia from hippocampus (Fig. 12D; n = 87 microglia) nor cerebral cortex (Fig. 12H; n = 74 microglia) contained red fluorescent tdTomato protein, leading us to conclude that microglia do not express Camk2a in these brain regions.

Figure 12.
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Figure 12.

Microglia do not express Camk2a-Cre. The hippocampus and cortex of Cx3cr1-EGFP; tdTomato; Camk2a-Cre+ mice were imaged by confocal microscopy (n = 10 images/brain region collected from 3 mice). A, E, DAPI labels cell nuclei. B, F, EGFP expressed under the control of the Cx3cr1 promoter labels microglia. C, G, Red fluorescent tdTomato expressed under the control of Camk2a-Cre labels excitatory glutamatergic neurons. D, H, Merged images for each tissue are shown. Note the lack of overlap between the EGFP and tdTomato channels, indicating that Camk2a is not expressed in microglia. Scale bar, 25 μm.

Inflammation stimulates microglia to shift from a surveillance state to an activated, neurotoxic phenotype characterized by expression of the cell surface marker CD68 (Hanisch and Kettenmann, 2007; Hoogland et al., 2015). We used immunostaining to assess the amount of CD68 present in Iba1-positive microglia from the hippocampus of Ctcf CKO mice compared with controls (Fig. 13; n = 4 animals/genotype, 10–17 images/animal). CD68-positive microglia were rare in controls (Fig. 13A–D), but were identified frequently in images from Ctcf CKO mouse hippocampus (Fig. 13E–H). We determined that the area of Iba1-positive microglia staining positive for CD68 was significantly greater in Ctcf CKO mouse hippocampus compared with controls (Fig. 13I; Mann–Whitney U = 345.5, n = 48 Ctcf CKO images, n = 40 control images, ****p < 0.0001), indicating increased microglial activation in Ctcf CKO hippocampus.

Figure 13.
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Figure 13.

Hippocampal microglia in Ctcf CKO mice are positive for CD68, a marker of microglial activation. Tissue sections from CA1 hippocampus of control (A–D) and Ctcf CKO mice (E–H) were labeled with the nuclear stain DAPI (A, E) and antibodies against microglial marker Iba1 (B, F) and activated microglial marker CD68 (C) and (G). CD68-positive microglia are rare in controls (D), but they are common in Ctcf CKO mice (H, arrowheads). The area of Iba1-positive microglia staining positive for CD68 was significantly greater in Ctcf CKO mouse hippocampus compared with controls (I; n = 48 Ctcf CKO images, n = 40 control images, Mann–Whitney U = 345.5, ****p < 0.0001). Graph shows means ± SEM. Scale bar, 25 μm.

Discussion

Here, we describe the effects of depleting Ctcf postnatally in Camk2a-Cre expressing neurons. In contrast to Ctcf KO in the embryonic CNS, which is rapidly lethal (Watson et al., 2014; Hirayama et al., 2012), we found that mice with postnatal Ctcf KO in excitatory forebrain glutamatergic neurons were viable. Ctcf CKO mice gradually developed a behavioral phenotype characterized by deficits in balance and fine motor coordination, profoundly impaired spatial learning/memory, and reduced sociability. These findings demonstrate that postnatal CTCF depletion causes a neurobehavioral phenotype independent of its effects on neural development and suggest that the phenotype of humans with CTCF haploinsufficency (Gregor et al., 2013) may be due in part to impairment of brain function caused by ongoing CTCF deficiency. CTCF interacts with methyl-CpG-binding protein 2 (MeCP2), which is encoded by MECP2, the gene mutated in the neurodevelopmental disorder Rett syndrome (Kernohan et al., 2010). A previous report described late life reversal of the neurologic phenotype of the Mecp2 KO mouse model of Rett syndrome by reexpressing wild-type Mecp2 (Guy et al., 2007). Whether the neurobehavioral phenotype of Ctcf CKO mice could be similarly improved by reconstituting CTCF sufficiency later in life is an important question to be answered.

We identified upregulation of inflammation-related genes, including known microglia genes, in Ctcf CKO mouse hippocampus by performing microarray-based gene expression analysis on mRNA from whole hippocampal tissue and on mRNA specifically from Camk2a-Cre expressing hippocampal neurons lacking Ctcf, which we collected using the RiboTag ribosome affinity purification technique (Sanz et al., 2009). This unique approach allowed us to parse out the source of gene expression changes that we observed in Ctcf CKO hippocampus. For example, upregulation of Tlr2, Ptgs2, Ccl2, Ccl3, Ccl9, Cd14, Cd52, and Cd83 was observed in mRNA derived from whole Ctcf CKO hippocampus, but not in mRNA isolated from Camk2a-Cre-expressing hippocampal neurons lacking Ctcf. This indicates that these genes are overexpressed in a non-neuronal component of the Ctcf CKO hippocampus. The products of Cd14, Cd52, Cd83, and Tlr2 are expressed on the surface of microglia (Fujimoto and Tedder, 2006; Becher et al., 1996; Chatterjee et al., 2014; Olson and Miller, 2004; Lehnardt, 2010). Active microglia release proinflammatory prostaglandins synthesized by cyclooxygenase-2 (COX2), the product of Ptgs2 (Minghetti, 2004). Microglia also release the products of Ccl2, Ccl3, and Ccl9: the chemokines CCL2/MCP-1 (Kim et al., 2015), CCL3 (Kataoka et al., 2009), and CCL9 (Aravalli et al., 2005), respectively. These observations prompted us to evaluate microglia in Ctcf CKO hippocampus, which were increased in number. We identified microglia with rod-like morphology, a distinct microglia phenotype found in the setting of nerve injury due to trauma and neurodegenerative disease (Tam and Ma, 2014). In addition, we identified microglia with amoeboid morphology, the characteristic shape of active, phagocytic microglia (Davis et al., 1994). Overall, these data point to microglia dysfunction in the setting of neuronal CTCF loss.

We identified upregulation of unique genes in mRNA obtained from Camk2a-Cre expressing neurons lacking Ctcf, but not whole Ctcf CKO hippocampus, including Ccl17. We interpret this as evidence that Ccl17 is overexpressed specifically in Camk2a-Cre-expressing hippocampal neurons lacking Ctcf, and that its twofold upregulation in these neurons is obscured in measurements of whole Ctcf CKO hippocampus gene expression. Ccl17 encodes C-C motif chemokine ligand 17 (TARC), a neuronally expressed secreted chemokine (Cheng et al., 2008) that activates C-C motif chemokine receptor 4 (CCR4) on microglia (Flynn et al., 2003). CCR4 activation promotes an M2 phenotype in macrophages/microglia that suppresses immune overactivation (Gordon, 2003). However, serum levels of CCL17 are elevated in individuals with ASD (Al-Ayadhi and Mostafa, 2013) and Alzheimer's disease (AD) (Neitzert et al., 2015) compared with healthy controls, suggesting that elevated CCL17 signaling may be pathologic. Along these lines, mouse models of AD deficient for Ccl17 are protected from amyloid β deposition, neuronal loss, and cognitive decline (Neitzert et al., 2013). Although the precise role of CCL17 is unclear in Ctcf CKO mice, chemokines are broadly seen as signaling molecules capable of regulating neuron–microglia interactions (Miller et al., 2008). We interpret the upregulation and enrichment of chemokine signaling pathway genes in Camk2a-Cre-expressing hippocampal neurons lacking Ctcf, and the simultaneous upregulation and enrichment of inflammation-related genes in the whole Ctcf CKO hippocampus, as indicative of crosstalk between neurons and microglia.

One explanation for both the upregulation of chemokine signaling pathway genes and the increase in microglia that we observed in Ctcf CKO mouse hippocampus is suggested by our observation of decreased dendritic spine density in this brain region. Microglia are capable of removing spines in adult animals in a process called synaptic stripping (Kettenmann et al., 2013) and chemokines are thought to serve as the major microglial attractants in this process (Trapp et al., 2007). Synaptic stripping occurs in the setting of nerve injury in both the PNS (Moran and Graeber, 2004) and CNS (Trapp et al., 2007). Injury triggers microglia to proliferate and migrate to the injury site, where they remove dendritic spines from injured neurons (Kettenmann et al., 2013), leading to dowregulation of synaptic proteins, including PSD-95 (Moran and Graeber, 2004), We did not observe nerve injury directly in Ctcf CKO mice, but Ctcf CKO;RiboTag neurons upregulated Nefh, which encodes neurofilament heavy polypeptide, a marker of nerve injury (Gresle et al., 2008). We speculate that microglial synaptic stripping is activated in Ctcf CKO mice by upregulation of chemokine signaling in Ctcf KO neurons, by CTCF-deficiency-induced nerve injury, or both.

Dendritic spines provide the structural basis for synaptic plasticity (Holtmaat and Svoboda, 2009), a phenomenon crucial to learning and memory (Gipson and Olive, 2017). In addition to synaptic stripping, microglia modify synaptic plasticity via direct contacts with neurons (Rogers et al., 2011; Schafer et al., 2012) and through the indirect release of growth factors including brain-derived neurotrophic factor (Coull et al., 2005) and cytokines including tumor-necrosis factor α (Pascual et al., 2012). Microglia also modify plasticity-related animal behavior. For example, obsessive-compulsive behavior in Hoxb8-null mice is relieved by bone marrow transplantation, which replaces mutant microglia with wild-type microglia (Chen et al., 2010). Overall, the connection between microglia and brain plasticity (Kettenmann et al., 2013), coupled with our observations of abnormal microglia in Ctcf CKO hippocampus, suggest to us that microglial dysfunction contributes to the abnormalities of dendritic spines and behavior that we identified in these animals.

While this manuscript was in preparation, a description of another line of Ctcf;Camk2a-Cre CKO mice was published (Sams et al., 2016). These mice also displayed deficits in hippocampal-dependent spatial learning, fear conditioning, and social recognition and had decreased dendritic spine density in CA1 hippocampus. Additional testing by the investigators identified abnormal long-term potentiation and abnormal stimulus-evoked transcription of activity-dependent Bdnf exon IV (Sams et al., 2016). The line of Ctcf CKO mice that we describe here confirms that deficiency of Ctcf in Camk2a-Cre expressing neurons leads to severe deficits in spatial learning/memory, impairment in fine motor coordination, subtle alterations in social behavior, and decreased dendritic spine number. In addition, we uniquely identified upregulation of inflammation-related genes in Ctcf CKO mice and demonstrated morphological abnormalities of their microglia. Further studies will determine whether microglia are detrimental in the setting of CTCF deficiency and if approaches that modify the inflammatory state of these animals are capable of mitigating the effects of CTCF loss.

Footnotes

  • This work was supported by the National Institutes of Health (NIH Neurological Sciences Academic Development Grants K12NS001690 and T32NS007205 to B.E.M. and Grants RO1AG013730 and RO1NS087632 to J.M.). We thank the Genome Technology Access Center in the Department of Genetics at Washington University School of Medicine for help with genomic analysis (the Center is partially supported by National Cancer Institute Cancer Center Support Grant NCI P30CA91842 to the Siteman Cancer Center and by the Institute of Clinical and Translational Sciences/Clinical and Translational Science Award Grant UL1TR000448 from the National Center for Research Resources, a component of the NIH, and the NIH Roadmap for Medical Research); the Alvin J. Siteman Cancer Center at Washington University School of Medicine and Barnes-Jewish Hospital in St. Louis, Missouri, for the use of the Siteman Flow Cytometry facility, which provided training and access to the flow cytometer and analysis software (the Siteman Cancer Center is supported in part by NCI Cancer Center Support Grant P30CA091842); the Hope Center Alafi Neuroimaging Laboratory (funded by NIH Shared Instrumentation Grant S10RR027552); and the Intellectual and Developmental Disabilities Research Center at Washington University (funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the NIH Grant U54HD087011). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

  • The authors declare no competing financial interests.

  • Correspondence should be addressed to Dr. Jeffrey Milbrandt, Washington University School of Medicine, Department of Genetics, Campus Box 8232, 4523 Clayton Avenue, St. Louis, MO 63110. jmilbrandt{at}wustl.edu

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3 Jan 2018
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Abnormal Microglia and Enhanced Inflammation-Related Gene Transcription in Mice with Conditional Deletion of Ctcf in Camk2a-Cre-Expressing Neurons
Bryan E. McGill, Ruteja A. Barve, Susan E. Maloney, Amy Strickland, Nicholas Rensing, Peter L. Wang, Michael Wong, Richard Head, David F. Wozniak, Jeffrey Milbrandt
Journal of Neuroscience 3 January 2018, 38 (1) 200-219; DOI: 10.1523/JNEUROSCI.0936-17.2017

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Abnormal Microglia and Enhanced Inflammation-Related Gene Transcription in Mice with Conditional Deletion of Ctcf in Camk2a-Cre-Expressing Neurons
Bryan E. McGill, Ruteja A. Barve, Susan E. Maloney, Amy Strickland, Nicholas Rensing, Peter L. Wang, Michael Wong, Richard Head, David F. Wozniak, Jeffrey Milbrandt
Journal of Neuroscience 3 January 2018, 38 (1) 200-219; DOI: 10.1523/JNEUROSCI.0936-17.2017
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Keywords

  • behavior
  • chemokine
  • CTCF
  • dendritic spine
  • inflammation
  • microglia

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