- Research article
- Open Access
αT-catenin in restricted brain cell types and its potential connection to autism
© The Author(s). 2016
- Received: 7 April 2016
- Accepted: 8 June 2016
- Published: 21 June 2016
Recent genetic association studies have linked the cadherin-based adherens junction protein alpha-T-catenin (αT-cat, CTNNA3) with the development of autism. Where αT-cat is expressed in the brain, and how its loss could contribute to this disorder, are entirely unknown.
We used the αT-cat knockout mouse to examine the localization of αT-cat in the brain, and we used histology and immunofluorescence analysis to examine the neurobiological consequences of its loss.
We found that αT-cat comprises the ependymal cell junctions of the ventricles of the brain, and its loss led to compensatory upregulation of αE-cat expression. Notably, αT-cat was not detected within the choroid plexus, which relies on cell junction components common to typical epithelial cells. While αT-cat was not detected in neurons of the cerebral cortex, it was abundantly detected within neuronal structures of the molecular layer of the cerebellum. Although αT-cat loss led to no overt differences in cerebral or cerebellar structure, RNA-sequencing analysis from wild type versus knockout cerebella identified a number of disease-relevant signaling pathways associated with αT-cat loss, such as GABA-A receptor activation.
These findings raise the possibility that the genetic associations between αT-cat and autism may be due to ependymal and cerebellar defects, and highlight the potential importance of a seemingly redundant adherens junction component to a neurological disorder.
- Adherens junction
- Alzheimer’s disease
- Choroid plexus
The pathogenesis of autism spectrum disorder (ASD) is complex, likely reflecting interplay between an underlying genetic predisposition and environmental influence. Through recent advances in clinical genetic analysis of those with ASD, many novel genes have been identified as potentially important mediators of the disorder. One such gene, αT-catenin (αT-cat, CTNNA3), has been implicated to be associated with ASD by a large number of independent genetic analyses [1–9]. Specifically, several genome-wide association studies have linked single nucleotide polymorphisms of αT-cat/CTNNA3 to ASD [1–3]. Moreover, studies of copy number variants demonstrated that those with ASD were more likely to have lost the αT-cat/CTNNA3 gene [4–7]. Additionally, αT-cat has been linked to other neurologic disorders with autistic-like behaviors , and a recent familial study found that compound heterozygote truncating mutations in αT-cat protein were associated with ASD . Despite these connections to ASD, the localization and roles of αT-cat in the brain remain unknown.
α-catenins are essential F-actin-binding proteins of the cadherin/catenin adhesion complex, the major cell-cell adhesion system in tissues throughout the body . αE-catenin (αE-cat, CTNNA1) is the most well studied member of this family, as it is nearly universally expressed . Mouse knockout studies establish its requirement for organ structure and function across various tissue types [12–15]. αT-cat is the most tissue-restricted and developmentally dispensable member of the family, as αT-cat knockout mice are viable and fertile , with expression apparently restricted primarily to the heart and testis . Interestingly, there is some evidence that αT-cat may impact other neurologic diseases, including Alzheimer’s disease (AD) [17–19] and schizophrenia related to maternal cytomegalovirus (CMV)-infection [20, 21]. But despite all these genetic associations, the majority of research on αT-cat is limited to its function in cardiomyocytes [16, 22–24] where it is abundantly expressed. While immunoblot detection of αT-cat has been observed in the brain , the primary cell type and plausible contribution to these neurological diseases have remained unexplored.
All experiments using animals were approved by the Northwestern University IACUC, and the care of experimental animals was in accordance with institutional guidelines. αT-cat KO C57BL/6 mice (obtained via Dr. Glenn Radice, Thomas Jefferson University, Philadelphia, PA)  were bred with C57BL/6 WT to create heterozygote, C57BL/6 breeders. WT and αT-cat KO mice used for experimentation were littermates or descendants from littermates. They were genotyped using αT-cat-KO specific primers, which generate separate bands in KO and WT mice via PCR: F: 5′- TCTATTTTTGAGGCTGTCG-3′; R: 5′-CAAACTTATGCGTGGTG-3′. αT-cat KO was confirmed by PCR, distinguishing from heterozygotes, showing absence of a band generated by WT-specific primers: F: 5′-CCACCCCTGATATGACCTGTAG-3′; R: 5′-TCCCCAGGAATCAAGTCGTT-3′.
Histology and immunofluorescence
Mice were anesthetized and subjected to intracardiac perfusion with saline, followed by perfusion of 4 % paraformaldehyde fixative. Whole brains were removed and post-fixed in 4 % formaldehyde and embedded in paraffin blocks. For immunofluorescence, tissue sections were deparaffinized and antigens were retrieved by boiling in citrate buffer for 30 min. Fluorescent images were captured using a Zeiss Axioplan epifluorescence microscope. Primary antibodies used were: BD Biosciences mouse anti-α-E-catenin (#610193), rabbit anti-α-T-catenin (polyclonal #952) , rat anti-α-T-catenin (monoclonal, 1159_12A4S4), Millipore mouse anti-α-T-catenin (MAB2087), BD Transduction Laboratories mouse anti-E-cadherin (610182), BD Transduction Laboratories mouse anti-N-cadherin (#610920), Santa Cruz Biotechnology rabbit anti-β-catenin (H-102, SC-7199), Millipore rabbit anti-Connexin-43 (AB1728), Santa Cruz Biotechnology rabbit anti-p120-catenin (S-19, SC-1101), Santa Cruz Biotechnology goat anti-δ-catenin (C-20, SC-16512), Invitrogen mouse anti-ZO-1 (33-9100), Synaptic Systems rabbit anti GABRA2 (224-103), Santa Cruz Biotechnology goat anti-doublecortin (C-18, SC-8066), Dako rabbit anti-GFAP (Z0334), Leica Biosystems rabbit anti-Ki-67 (NCL-Ki67p), Sigma mouse anti-Tuj1 (T8660), Swant rabbit anti-Calbindin D28K (CB-38). Secondary antibodies used were: Alexa Fluor 488/568 goat anti-mouse/rabbit (Life Technologies) and Alexa Fluor 568 donkey anti-goat (Life Technologies). Tissue processing was supported by the Northwestern University Mouse Histology and Phenotyping Laboratory (MHPL) and a Cancer Center Support Grant (NCI CA060553). H&E histology was performed by the MHPL.
Whole brains, from mice 7-8 weeks old, were lysed in T-PER Tissue Protein Extraction Reagent (ThermoFisher) with Protease and Phosphatase Inhibitor Mini Tablets (Pierce). Tissue was homogenized with tissue grinder pestle. Cerebral cortex and cerebellum tissue was carefully dissected to ensure no contamination from ventricular structures. Samples were run by SDS-PAGE, then transferred to nitrocellulose membrane. For western blot, primary antibodies used were: BD Biosciences mouse anti-α-E-catenin (#610193), rabbit anti-α-T-catenin (polyclonal, #952), BD Biosciences mouse anti-N-cadherin (#610920), Santa Cruz Biotechnology rabbit anti-β-catenin (H-102, SC-7199), Santa Cruz Biotechnology mouse anti-δ-catenin (40.1, SC-81793), Santa Cruz Biotechnology goat anti-doublecortin (C-18, SC-8066), Cell Signaling rabbit anti-α-N-catenin (2163S), Alomone rabbit anti-GABRA2 (AGA002), and Sigma mouse anti-beta-tubulin (T4026). The secondary antibodies were: LI-COR IRDye680 Donkey anti-rabbit (926-68073) and IRDye800 Donkey anti-mouse (926-32212). Imaging performed using the Odyssey Infrared Imaging System (LI-COR).
No consent was necessary for the human data, as de-identified human brain tissue was obtained during autopsy, with an exemption granted from the Northwestern IRB. For both the ependymal and cerebellar tissue, there was no evidence of pathologic damage to the region. Tissues were processed using the Robert H. Lurie Comprehensive Cancer Center of Northwestern University Pathology Core Facility.
After staining for α-E-catenin as above, the total fluorescent intensity density of exposure-matched images was measured. This was done by outlining the entirely of the ependymal cell layer along the visible cellular borders of the anterior lateral ventricles using ImageJ, and measuring the density of the signal averaged across this area. Although the majority of the α-E-catenin signal was present near the apical junctions of the cells, the entire ependymal layer was quantified to reduce any potential bias in quantification. Two measurements were performed per mouse, one for each ventricle in the section of each coronally sectioned brain tissue. Therefore, for each group, 6 measurements were performed, with 3 mice per group. For the quantification of Ki-67 positive cells, the total numbers of Ki-67 cells were counted from each ventricular area from coronal H&E-stained sections of the anterior lateral ventricles. Both ventricles present were quantified, and the mean of both Ki-67 positive counts was utilized per mouse for quantification.
Ventricle size quantification
After dissection of the brain, cerebellar tissue (n = 3) was used for RNA extraction using TRIzol/chloroform during homogenation of the fatty brain tissue. Subsequently, the Aurum Total RNA mini Kit (Bio-rad) was used according to the manufacturer’s protocol. RNA dissolved in elution buffer was frozen to -80 °C and shipped to the VIB Nucleomics Core (VIB, Belgium) for RNA sequencing by Next Generation Sequencing technology, i.e. massive parallel sequencing using Illumina Truseq procedures on an Illumina Hi-Seq apparatus.
Read preprocessing and mapping of RNA-sequencing data
The raw data of FASTQ format were processed to remove as much technical artifacts as possible. Low quality ends (phred score <20) were trimmed using the FASTX tool kit (http://hannonlab.cshl.edu/fastx_toolkit). Adapter trimming was performed with cutadapt 1.2.1 . Reads shorter than 15 bp after adapter trimming were removed. Quality filtering was done using FastX 0.0.13 and ShortRead 1.16.3 . PolyA-reads (more than 90 % of the bases equal A), ambiguous reads (containing N), low quality reads (more than 50 % of the bases < Q25) and artifact reads (all but 3 bases in the read equal one base type) were removed. The remaining clean reads were aligned against the reference genome of Mus musculus (mus_musculus_GRCm38.73), using the TopHat v2.0.8b software . As parameter options we used: --library-type fr-unstranded –min-intron-length 50 --max-intron-length 500000 –no-coverage-search --no-mixed --read-realign-edit-dist 3. Quality filtering (removal of reads that are non-primary mappings or have a mapping quality < 20), sorting and indexing of the resulting bam-files were done with samtools 0.1.19 .
Identification of differentially expressed genes
Gene expressions of the transcripts were calculated by counting the number of reads in the alignments that overlap with the gene features, using htseq-count 0.5.4p3 . As parameters we took: -m union --stranded = reverse -a 0 -t exon -i gene id. Subsequently, the edgeR 3.12.0 tool  was utilized to detect the differentially expressed genes between the αT-cat WT and KO samples. The modeling of the variance for each gene was done using both the common dispersion model (the same dispersion value is used for each gene) and the moderated tagwise dispersion model (a distinct, individual dispersion is estimated and used for each gene). EdgeR used with the moderated tagwise dispersion model tends to rank more highly as DE genes that are more consistent in their counts within groups. Finally, genes with a p-value ≤ 0.01, corresponding to a false discovery rate (FDR) value ≤ 0.3, were considered as differentially expressed (DE).
The biological interpretation of the DE genes observed in the WT versus αT-cat KO samples was performed using QIAGEN’s IngenuityR Pathway Analysis (IPAR, QIAGEN Redwood City, www.qiagen.com/ingenuity), in order to identify and characterize biological functions, canonical pathways and gene networks associated with these genes. IPA analyses rely on the Ingenuity Pathways Knowledge Base (IPKB), a manually curated database containing data extracted from the full text of journals as well as gene annotation databases and interaction data from third party databases, such as DIP, IntAct, MINT, MIPS, BIND and BIOGRID. An IPA (Core) analysis consists of mapping each gene identifier to its corresponding gene object (focus gene) in the IPKB, the generation of networks using the uploaded focus genes as seeds, identification of the biological processes, diseases, or toxicological functions affected in the experiment (functional analysis) and identification of the canonical pathways the experimental dataset may be involved in (canonical pathways). IPA uses Fisher’s exact test to calculate a p-value determining the probability that each biological process, disease or toxicological function assigned to the data set is due to chance alone.
Statistical analysis was performed using Student’s t-test, two-tailed and unpaired, with a p-value of less than 0.05 considered significant. Calculations were performed using GraphPad Prism software (Graph Pad Software Inc., La Jolla, CA).
αT-cat is expressed in the cell-cell junctions of ependymal cells, but not the choroid plexus
Ependymal cell junctions are morphologically and compositionally distinct from those of the choroid plexus
αT-cat is detected in the cerebellar, but not the cerebral, cortex
Importantly, αT-cat was specifically detected within the molecular- (cellular processes), but not the granular- (cell bodies), layer of the cerebellum, consistent with previous data  (Fig. 6d). Using human cerebellar tissue, αT-cat, but not αE-cat, was clearly detected along neurite projections within the molecular layer (Fig. 6e). Although differences in junctional protein expression were found by western blot, overt changes to junctional structures within the cerebellum were absent between WT and αT-cat KO mice (Additional file 1: Figure S1). Since the murine cerebellum did not appear to have the discrete, traditional cell-cell junctions usually visualized by these proteins, the cerebellar function of the altered cell-cell junction proteins shown in Fig. 6c could not be described. While there is some data suggesting that αT-cat and αE-cat may be able to stabilize dendritic spines , whether this occurs in the cerebellum is unknown.
Lastly, αT-cat was also found in cell junctions of the pia-arachnoid surrounding the brain (Fig. 6d), which is a simple epithelium that lines the sub-arachnoid space filled with CSF. Since this space is contiguous with the ventricles lined by ependymal cells, these data indicate that αT-cat participates in junctions from simple cuboidal (ependymal) and squamous (pia-arachnoid) epithelia that line this fluid-filled space.
RNA sequencing analysis of cerebella implicates αT-cat in several neurological disease pathways
While there were no overt morphological or cellular changes found in αT-cat KO mice cerebella when compared to WT, we suspect that the upregulation of cell adhesion proteins in the absence of αT-cat (Fig. 6c) compensates for this loss, as both αE-cat and αT-cat may share similar neural functions . To assess more subtle changes due to the loss of αT-cat that may be relevant to neurological diseases, we performed an RNA-sequencing (RNA-seq) analysis between WT and αT-cat KO mouse cerebella. From this, we discovered a number of gene transcripts altered by the loss of αT-cat, from which we associated with several neurologic disease-relevant pathways. The complete RNA-seq dataset shows these results in complete detail (see Additional file 2). Notable among these were two pathways previously implicated in ASD, including amyloid-β precursor protein APP  and estrogen (ESR1)  (Additional file 1: Figure S2). Interestingly, the loss αT-cat was associated with changes to a number of other hormone signaling pathways, including corticotropin (CRH)  and somatostain (SST) , which have also been previously associated with ASD. The cerebellum is not the canonical secretion site for any of these hormones, so αT-cat’s influence on them remains a mystery. One possible hypothesis may be that αT-cat regulates either local production or signaling of these hormones, but further research will need to be conducted to ultimately test this. Finally, notable among the top identified genes influenced by αT-cat was MEIS2 , which has also associated with ASD. Importantly, for all of these genes identified by the RNA-seq analysis, each will need to be validated by future experiments to definitively link their expression to αT-cat.
αT-cat may be linked to neurologic diseases through its ependymal and cerebellar functions
We have shown that αT-cat in the brain is expressed in ependymal cells and the neuronal processes within the molecular layer of the cerebellum. A common feature of these distinct cell types may be their proximity to mechanical stressors, consistent with αT-cat’s function in heart. For example, the ependyma and pia-arachnoid are subject to CSF-flow , and the granular neurons of the cerebellum are considered to withstand substantial mechanical forces during development to generate stereotypic cerebellar folds . These region-specific localizations of αT-cat may also have implications for the many genetic linkages between αT-cat and disease. The role of the cerebellum in the development of autism is well defined , and our data suggest that αT-cat may play an important role in regulating the cell junction components in neurite structures or cell signaling within the cerebellum. Because we did not detect αT-cat in neurons of the cerebral cortex, and αT-cat KO mice demonstrate no overt neurologic dysfunction, we suspect there is no direct neuronal link of αT-cat dysfunction to the established, neuronal etiologies of ASD, or even AD, such as neurofibrillary tangles or amyloid plaques . However, there is evidence that enlarged ventricles are associated with late-onset AD , as well as ASD . Whether this is a secondary effect of neural loss or an independent driver of disease remains unknown, but our evidence that αT-cat comprises the junctions that line ventricles raises the formal possibility that an underlying ependymal barrier defect may contribute to ventricular dysfunction in humans. This may also explain why αT-cat polymorphisms were only associated with sporadic, late-onset AD  rather than familial AD. Furthermore, although ASD and AD represent diseases that differ significantly in pathogenesis, our data add to the growing evidence of shared biochemical pathways, particularly in the cerebellum, that link these diseases . Lastly, our finding of αT-cat in ependymal junctions may explain αT-cat’s connection to maternal CMV infection and schizophrenia [20, 21]. Because neonatal CMV primarily infects the ependymal layer , and ventricle enlargement has long been associated with schizophrenia , αT-cat ependymal junction dysfunction might affect susceptibility to CMV infection and subsequent development of schizophrenia.
In summary, we show that αT-cat is expressed in ependymal epithelial cells and cellular processes within the molecular layer of the cerebellum, and propose how alteration of these structures may rationalize the various genetic associations between αT-cat and ASD, AD and schizophrenia. Our work also highlights the emerging importance and disease-relevance of this understudied α-cat family member, which has been long considered to be a redundant, non-essential component of adherens junctions.
AD, Alzheimer’s disease; ASD, autism spectrum disorder; CMV, cytomegalovirus; CP, choroid plexus; CSF, cerebrospinal fluid; KO, knock-out; WT, wild-type; α-cat, alpha-catenin.
We thank the MHPL and Human Pathology Core Facilities of Northwestern, as well as Dr. Richard Miller for his aid in providing the instruments for the fixation and perfusion of mouse brains. We also thank Jack Kessler and his laboratory, particularly Sarah Brooker, as well as Anjen Chenn (University of Illinois, Chicago), for discussions.
S.S.F. is supported by the National Institutes of Health (T32GM008152, T32CA09560, F30 ES024622) and the American Heart Association pre-doctoral fellowship (15PRE21850010). D.R.W. is supported by the National Institutes of Health (T32GM008152). W.G.T. is supported by the National Institutes of Health (NS089626, OD010945 and CA060553). F.v.R.. J.v.H, P.d.B., and K.T. are supported by the Research Foundation - Flanders (FWO) and the Belgian Science Policy (Interuniversity Attraction Poles – IAP7/07). C.J.G. is supported by the National Institutes of Health (GM076561) and Northwestern University bridge funds.
Availability of data and materials
The dataset supporting the conclusions of this article is available in the NCBI GEO database repository GSE83480; (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE83084).
SSF and CJG conception and design of research; SSF, DRW, WGT, and KT performed experiments; SSF, DRW, KT, and PdB and CJG analyzed data; SSF, DRW, KT, JvH, FvR, PdB and CJG interpreted results of experiments; SSF and KT prepared figures; SSF drafted manuscript; SSF, DRW, KT, FvR, JvH, WGT, and CJG edited and revised manuscript; SSF, DRW, KT, FvR, JvH, WGT, and PdB and CJG approved final version of manuscript.
The authors declare that they have no competing interests.
Ethics approval and consent to participate
Ethical concerns relevant to all experiments using animals were approved by the Northwestern University IACUC (Study number: IS00000667), and the care of experimental animals was in accordance with institutional guidelines. No consent was necessary for the human data, as de-identified human brain tissue was obtained during autopsy, with an exemption granted from the Northwestern IRB.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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