Extracellular matrix alterations in the ketamine model of schizophrenia

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EXTRACELLULAR MATRIX ALTERATIONS IN THE KETAMINE MODEL OF SCHIZOPHRENIA

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GABRIELA MATUSZKO, a SEBASTIANO CURRELI, a,b RAHUL KAUSHIK, a AXEL BECKER c AND ALEXANDER DITYATEV a,d,e*

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a Molecular Neuroplasticity, German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany

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b Neuroscience and Brain Technologies Department, Istituto Italiano di Tecnologia, Genova 16163, Italy

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c Institute of Pharmacology and Toxicology, Faculty of Medicine, Otto-von-Guericke-University Magdeburg, 39120 Magdeburg, Germany

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Center for Behavioral Brain Sciences (CBBS), 39120 Magdeburg, Germany

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e Medical Faculty, Otto-von-Guericke University, 39120 Magdeburg, Germany

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mPFC specific, and was not detected in the hippocampus, suggesting regional specificity of ECM alterations. These data open an avenue for further investigations of functional importance of ECM abnormalities in schizophrenia as well as for search of treatments for their compensation. Ó 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Key words: prefrontal cortex, hippocampus, perineuronal net, CS56, WFA, schizophrenia, parvalbumin. 19

Abstract—The neural extracellular matrix (ECM) plays an important role in regulation of perisomatic GABAergic inhibition and synaptic plasticity in the hippocampus and cortex. Decreased labeling of perineuronal nets, a form of ECM predominantly associated with parvalbuminexpressing interneurons in the brain, has been observed in post-mortem studies of schizophrenia patients, specifically, in brain areas such as prefrontal cortex, entorhinal cortex, and amygdala. Moreover, glial ECM in the form of dandelion clock-like structures was reported to be altered in schizophrenia patients. Here, we verified whether similar abnormalities in neural ECM can be reproduced in a rat model of schizophrenia, in which animals received subchronic administration of ketamine to reproduce the aspects of disease related to disrupted signaling through N-methylD-aspartate receptors. Our study focused on two schizophrenia-related brain areas, namely the medial prefrontal cortex (mPFC) and hippocampus. Semi-quantitative immunohistochemistry was performed to evaluate investigate ECM expression using Wisteria floribunda agglutinin (WFA) and CS56 antibody, both labeling distinct chondroitin sulfate epitopes enriched in perineuronal nets and glial ECM, respectively. Our analysis revealed that ketaminetreated rats exhibit reduced number of WFA-labeled perineuronal nets, and a decreased intensity of parvalbumin fluorescence in mPFC interneurons somata. Moreover, we found an increased intensity of CS56 immunoreactive form of ECM. Importantly, the loss of perineuronal nets was

*Correspondence to: Alexander Dityatev, German Center for Neurodegenerative Diseases (DZNE), Leipziger Str. 44, Haus 64, 39120 Magdeburg, Germany. Fax: +49-391-6724530. E-mail address: [email protected] (A. Dityatev). Abbreviations: ECM, extracellular matrix; mPFC, medial prefrontal cortex; NGS, normal goat serum; PBS, phosphate buffer solution; PNN, perineuronal net; PV, parvalbumin; ROIs, regions of interest; WFA, Wisteria floribunda agglutinin. http://dx.doi.org/10.1016/j.neuroscience.2017.03.010 0306-4522/Ó 2017 IBRO. Published by Elsevier Ltd. All rights reserved. 1

INTRODUCTION

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Neural extracellular matrix (ECM) is a well-organized complex molecular structure surrounding neurons and glia cells. Perineuronal net (PNN) is a mesh-like form of ECM, ensheathing somata and proximal dendrites of specific subclasses of neurons. Hyaluronic acid constitutes the backbone of PNN, which binds to chondroitin sulfate proteoglycans (Dityatev et al., 2010a). This complex is stabilized by glycoprotein tenascin-R and link proteins (Yamaguchi, 2000). Tenascin-R carries the human natural killer 1 (HNK-1) carbohydrate, which plays a pivotal role in regulation of perisynaptic inhibition (Saghatelyan et al., 2000). A lack of tenascin-R or HNK-1 leads to reduction in perisomatic inhibition and impaired long-term potentiation (Saghatelyan et al., 2000, 2001, 2003). LTP in tenascinR knockout mice might be rescued by agonists of GABAA receptors, an antagonist of postsynaptic GABAB receptors and HNK-1 carbohydrate mimetics (Bukalo et al., 2007). In addition to regulation of perisomatic GABAergic inhibition and LTP, PNNs appeared to control excitability of fast-spiking interneurons (Dityatev et al., 2007). These findings on the role of ECM in regulation of GABAergic innervation and activity are particularly relevant in the context of schizophrenia, because impaired GABAergic inhibition is one of the putative causes of this disease (Beasley et al., 2002; Reynolds et al., 2004; Sakai et al., 2008). Reduced levels of 67kDa glutamate decarboxylase (GAD67) mRNA in parvalbumin (PV)-expressing interneurons are frequently reported in the PFC of schizophrenic patients (Benes et al., 1996; Volk et al., 2001; Volk and Lewis, 2002). Importantly, human post-mortem brain studies revealed the reduction of PNN density in multiple brain areas, including prefrontal and entorhinal cortices, and amygdala (Pantazopoulos et al., 2010). Also, dandelion clock-like structures, presumably a glial form of ECM, were mark-

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edly reduced in the amygdala of schizophrenia patients (Pantazopoulos et al., 2015). Genetic studies also revealed several interesting connections between ECM encoding genes and schizophrenia. Common variation of neurocan, one of the chondroitin sulfate proteoglycans, has been reported to be associated with this mental disorder (Mu¨hleisen et al., 2012) and confirmed by a more recent study (Ripke et al., 2013). Another genetic study on schizophrenia patients has reported single nucleotide polymorphism (SNP) of b-1,3-glucuronyltransferease 2 (B3GAT2), an enzyme involved in HNK-1 biosynthesis, as a schizophrenia risk allele, associated with decreased cortex volume in patients (Kahler et al., 2011). Also matrix metalloprotease MMP-16, link protein HAPLN4 and neuroglycan C were identified as genes associated with schizophrenia (Ripke et al., 2013; Consortium SWGotPG, 2014). Furthermore, 50% reduction of mRNA and protein levels of the ECM glycoprotein Reelin was found in several brain areas, including PFC and hippocampus, in schizophrenia patients (Costa, 1998; Fatemi et al., 1999; Guidotti et al., 2000). However, one should be cautious with interpretation of the mentioned post-mortem brain studies, as ECM alterations in patient brains may at least partially reflect increased sensitivity to proteolysis during postmortem period or be related to drug treatment of patients. Thus, it is important to verify human findings using animal models of schizophrenia. Moreover, models would allow one to search for pharmacological treatments to restore ECM and to dissect the impact of ECM on positive, negative and cognitive symptoms in schizophrenia. Our study aimed to investigate ECM alterations, in particular in the number and prominence of PNNs and CS56+ glial ECM, using a pharmacological rat model based on sub-chronic administration of NMDA receptor antagonist ketamine (Becker et al., 2003). Ketamine-treated rats have impaired latent inhibition and reduced percentage of non-aggressive interactions in sociability test (Becker et al., 2003), and are considered as a model of schizophrenia predominantly reflecting negative symptoms of the disease (Chindo et al., 2012). Our immunohistochemical analysis revealed a reduced number of PNNs and increased intensity of CS56+ ECM in the prefrontal cortex of ketamine-treated rats.

EXPERIMENTAL PROCEDURES

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Animals

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Sprague–Dawley (MolTac:SD, Taconic Denmark, SPD) male rats were used in all experiments. The animals were kept in controlled laboratory conditions: at 20 ± 2 °C, air humidity 55–60% and 12-h day/night cycle (lights on at 6 a.m.). The rats were housed in group of five animals in Macrolon IV cages, with free access to food pellet (Altronim 1326) and tap water.

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Ketamine treatment

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Ketamine treatment was done according to the protocol of Becker et al. (2009). Eight-week-old animals were subjected to sub-chronic administration of ketamine (keta-

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mine hydrochloride, Astrapin, Pfaffen-Schwabenhein, Germany). Ketamine (30 mg/kg b.w.) or 0.9% NaCl vehicle were injected in two sessions of 5 days, with daily injections separated by 2-day break between sessions. Injections were made intraperitonally (IP) at a volume of 1 ml/100 g of animal weight.

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Social interaction test

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Social interaction test was performed as described previously (Becker et al., 2003, 2009). Briefly, two days after the final injection, control rats and ketamine-treated rats were housed singly in Macrolon II cages with food and water ad libitum for 12 days. Two weeks after the last ketamine injection animals were familiarized to the openfield arena (100  100  40 cm) in two trials of 7 min each two days prior to social interaction test. The day prior to testing, rats were allocated to test partners on the basis of pretreatment and body weight. The difference between the two partners was within 20 g. During the test, animal pairs were placed in arena for 7 min. Total time of social interaction was measured and scored as nonaggressive and aggressive interactions between two animals. Data are represented as the time span of nonaggressive behavior as a percentage of total social interaction time.

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Immunohistochemistry

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Two days after social interaction test, animals were deeply anesthetized (400 mg/kg b.w. chloral hydrate injection) and perfused transcardially with 4% PFA. Brains were incubated in 4% PFA containing phosphate buffer solution (PBS), cryoprotected in 30% sucrose PB solution for 48 h, frozen in 100% 2-methylbutan at 80 °C and sliced in 50-mm-thick coronal sections. Floating sections were kept in solution (1 part ethylenglycol, 1 part of glycerin, 2 parts of PBS pH = 7.2). For each staining condition, three sections per brain area of each animal were selected. All sections were washed in 120 mM phosphate buffer pH = 7.2 (PB). For double PV and WFA staining, medial prefrontal cortex (mPFC) and dorsal hippocampal sections were permeabilized with PB containing 0.5% Triton X-100 (Sigma T9284) for 10 min at RT, followed by application of blocking solution (PB supplemented with 0.1% Triton X-100 and 5% normal goat serum (NGS) (Gibco 16210064) for 1 h at RT. Afterward, sections were incubated for 48 h in the presence of primary reagents: biotinylated Wisteria floribunda agglutinin (WFA) and rabbit anti-parvalbumin antibody (staining conditions are described in Table 1). Sections were washed three times in PB followed by incubation with secondary reagents, streptavidin Alexa 488 conjugate and goat anti-rabbit Alexa 546-conjugated secondary antibodies, overnight at 4 °C. Sections were washed in PB and stained with Hoechst 3342 (1 mg/ml in DMSO, 1:500, Sigma B2261) and mounted on SuperFrost glasses with Fluoromount (Sigma F4680). For triple PV, WFA and HNK-1 staining, mPFC sections were permeabilized with PB buffer containing

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G. Matuszko et al. / Neuroscience xxx (2017) xxx–xxx Table 1. Primary and secondary reagents used for histochemistry

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Reagents

Supplier and catalog number

Dilution and incubation time

Primary reagents Rabbit anti-Parvalbumin, whole serum

SWANT PV 25

1:300, 36 h+ 1:200, 36 h+ 1:200, 60 h+ 1:200, 60 h+ 1:500, 36 h+

Mouse anti-L2/HNK-1 carbohydrate epitope antibody [ZN-12], 1 mg/ml Rabbit Anti-S100ß, whole serum

Abcam ab174437

Mouse IgM Anti-CS-56, ascites fluid

Sigma–Aldrich C8035

Biotinylated lectin from Wisteria floribunda (WFA), 1 mg/ml

Sigma–Aldrich L1516

Secondary reagents Goat Anti-IgG rabbit Alexa 647, 2 mg/ml

Thermo Fisher Scientific (A21245)

Goat Anti-IgG mouse Alexa 546, 2 mg/ml

Thermo Fisher Scientific (A11030)

Goat Anti-IgG rabbit Alexa 546, 2 mg/ml

Thermo Fisher Scientific (A11035)

Goat Anti-IgM mouse Cy5, 1 mg/ml

LifeSpan Biosciences (LS-C349700)

Streptavidin Alexa 488, 2 mg/ml

Thermo Fisher Scientific (S11223)

0.3% Triton X-100 for 10 min and blocked in PB containing 0.1% Triton X-100 and 10% NGS for in 1 h at RT. Afterward, sections were incubated with primary reagents (Table 1). After three washes in PB, secondary reagents, namely streptavidin Alexa 488, goat anti-rabbit Alexa 647 and goat anti-mouse Alexa 546-conjugated antibodies, were applied overnight at +4 °C. For triple WFA, S100b and CS56 staining, mPFC sections were treated with blocking solution (PB containing 0.3% Triton-X 100, 5% NGS and 25 mM glycine) for 1 h at RT. After incubation with primary reagents (Table 1), sections were washed three times with PB and streptavidin Alexa 488, goat anti-rabbit Alexa 546 and goat anti-IgM mouse Cy5-conjugated antibodies were applied for 3 h at RT. PV, WFA and HNK-1 as well as WFA, S100b and CS56 stained sections were washed in PB and stained with DAPI (Invitrogen 01306, 1 mg/ml, 1:1000) and mounted on SuperFrost Plus (Thermo Scientific J800AMNZ) glasses with Fluoromount (Sigma F4680).

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Acquisition and image processing

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Images were acquired using Zeiss LSM 700 confocal microscope and EC Plan-Neofluar 20/0.50 M27 objective, while the experimenter was blinded to the treatment group. For each animal, three 50-mm-thick brain sections sampled with 200-mm distance were selected for counting. For each section, two z-stack images (16 bit, 10 optical sections, 1.55 mm interval between sections, frame 2048  2048, pixel size 0.156 mm) were acquired. Images were processed using ImageJ software. For each z-stack, eight consequent optical sections were chosen to make a z maximum projection. In hippocampal CA1 area, due to a high density of

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Abcam ab868

4 °C 4 °C 4 °C 4 °C 4 °C

1:1000, 12 h+ 4 °C 1:1000, 12 h+ 4 °C 1:1000, 3 h RT 1:1000, 3 h RT 1:1000, 12 h RT

presynaptic PV+ terminals, PV+, WFA+, and double immunoreactive PV+WFA+ cells were counted manually. Dendrites from PV+ cells were tracked manually and the intensity of fluorescence along traced line was measured using ImageJ. Values were averaged with 10-mm step and normalized per mean intensity of somatic signal in the vehicle group. In the mPFC, fluorescence detection threshold was adjusted manually to clearly detect PV+ cells and then cells were counted automatically using a custom made ImageJ macro analyzing particles greater than 130 mm2 (available on request). In order to measure the intensity of fluorescence, zstack images were acquired: six images with PV, WFA and HNK-1 labeling (16 bit, five optical sections, 1.55mm interval between sections, 2048  2048 pixels, pixel size of 0.156 mm) and six images with WFA, S100b and CS-56 labeling (16 bit, 18 optical sections, 0.353-mm interval between sections, 512  512 pixels, pixel size 0.625 mm). For mean fluorescence intensity measurements, WFA, HNK-1 and PV average projections of Z stacks were obtained using ImageJ software. Thresholds were adjusted manually. Cell bodies were recognized automatically as particles greater than 65 mm2 in the PV channel. Three different sets of regions of interest (ROIs) were defined: ‘‘fullROI” to measure mean intensity of signals from the whole PV cell body, a ‘‘donut-ROI” to measure WFA or HNK-1 signals from 1- mm-thick cells rim around a cell body, as shown in the figure 4, and 20.6  20.6 mm ‘‘square-ROI” (3 ROIs per image sampled as far as possible from cell somata) for measurements of neuropil signal between cell bodies. For WFA, S100b and CS56 average projections of Z stacks (16 bit, 18 optical sections, 0.35-mm intervals between sections, 512  512 pixels, pixel size of

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0.625 mm) were obtained using ImageJ software. Intensity of CS56 fluorescence was measured for the whole image. Due to variability of CS56 expression outside clusters they were counted manually (Fig. 5, marked by *).

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STATISTICS

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Two-tailed t-test, one- and two-way repeated measures ANOVA were used as indicated in Results and Figure Legends. If Shapiro–Wilk normality test failed, the Mann–Whitney test was used instead of t-test. Differences between groups were considered as significant, if the level of significance p was less than 0.05.

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RESULTS

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Here we aimed to examine ECM alterations in the ketamine model of schizophrenia. In line with the previous studies (Becker et al., 2003, 2009), ketamine treatment led to a reduction in non-aggressive social interaction (Vehicle: 84 ± 4%, n = 7, ketamine: 57 ± 9%, n = 5; one-way ANOVA, p = 0.03). First, we analyzed PNNs in the CA1 region of the hippocampus, because most of the available functional

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data showing impaired synaptic and cognitive functions upon ECM attenuation were obtained for this brain region (Senkov et al., 2014). To evaluate PNN alterations in the CA1 area, PV and WFA double staining was performed and numbers of immunopositive PV+, WFA+, PV WFA+ and double immunopositive PV+WFA+ cells were quantified. Our analysis of cells densities in the CA1 area indicates no statistically significant differences in densities of PV+, WFA+, double PV+WFA+, or PV WFA+ cells between ketamine- and vehicle-treated groups (Fig. 1A, B). Percentages of PV+WFA+ cells among all PV+ and all WFA+ were also unaltered after ketamine treatment (Fig. 1C). Altogether the analysis failed to reveal any ketamine induced alteration in the number of PNNs and PV+ interneurons in the CA1 region. Our previous study demonstrated that analysis of ECM associated with dendrites of PV+ cells can be quite insightful, as this form of ECM strongly depends on expression of tenascin-R (Morawski et al., 2014). In order to examine dendritic PNN expression in the hippocampal CA1 area, we manually traced dendrites of PV+ interneurons and analyzed profiles of WFA intensity signals. However, no statistical significant effect of keta-

Fig. 1. Densities of PV and WFA labeled cells in the hippocampal CA1 area of ketamine-treated rats. (A): Representative images of PV (in red) and WFA (in green)-positive cells in the hippocampal CA1 area. Upper panels show brain sections from vehicle-injected controls, while the lower panels depict sections from ketamine-treated animals. Nuclei were visualized by Hoechst stain (in blue). Scale bar=50 mm. (B): PV+, WFA+, PV+WFA+ and PV WFA+ cell density per mm2 in the hippocampal CA1 area. (C): Number of PV+WFA+ double-positive cells as a percentage of all PV+ or WFA+ cells in the hippocampal CA1.(B, C): Mean + SEM values are shown. Vehicle: n = 5; ketamine: n = 7, two-tailed t-test did not reveal and significant effects. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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GABAergic inhibition (Saghatelyan et al., 2000, 2001), we decided to evaluate the levels of HNK-1 immunofluorescence associated with the neuropil and somata of WFA+ cells. We also investigated whether the loss of PNNs in the mPFC is associated with reduction of PV expression by performing fluorescence analysis of PV, WFA and HNK-1 signals in triply stained mPFC sections. Our results revealed a significant reduction of somatic PV fluorescence intensity in ketamine-treated animals (vehicle: 1 ± 0.02; ketamine: 0.59 ± 0.11; p = 0.048, Mann–Whitney test), while the intensities of WFA and HNK-1 signals measured in perisomatic donut-ROIs were not different between groups (Fig. 4A, B). Then we measured intensity of HNK1 carbohydrate signal in the neuropil, where it may associate with tenascin-R at perisynaptic ECM (Dityatev et al., 2010b) or with GluA2 subunit of glutamate receptors and promote GluA2 cell surface expression (Morita et al., 2009). Expression of HNK-1 in the neuropil was not different between ketamine- and vehicle-treated rats (Fig. 4C). These results indicate that the loss in the number of WFA+ PNNs is associated with reduction of PV expression rather than changes in expression of

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HNK-1. As the previous work revealed changes in CS56+ ECM in schizophrenia patients (Pantazopoulos et al., 2015), we also analyzed CS56 labeling, presumably of glial origin, in combination with WFA labeling and astrocytic S100b immunostaining (Fig. 5A). Interestingly, intensity of CS56 immunolabeling in the mPFC appeared to be elevated within CS56+ clusters and between them (Fig. 5B). We did not observe obvious changes in WFA or S-100b signals associated with CS56+ clusters in ketamine-treated groups (Fig. 5A, ‘‘Merge” panel). Quantitative analysis confirmed that the CS56 signal per image area was 1.4 ± 0.05-fold increased in ketamine-treated rats (p = 0.0005, two-tailed t-test; Fig. 5B). The number of CS56+ clusters was not changed (Fig. 5B). Thus, there is an elevation of CS56+ ECM after ketamine treatment.

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DISCUSSION

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In the present study, we evaluated ECM alterations in rats sub-chronically administrated with ketamine as a validated model of schizophrenia and found a reduction in the number of WFA+ PNNs in the mPFC. This is qualitatively in line with human postmortem brain studies, which have reported a loss of PNNs around

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Fig. 2. Expression of dendritic ECM in the hippocampal CA1 area of ketamine-treated rats. (A): Representative images of ECM visualized by WFA (in green) along dendrites of PV+ cells in the hippocampal CA1 area. Arrows indicate the region where a dendrite was tracked. Scale bar=10 mm. (B): Relative intensity of fluorescence was quantified as a function of distance from cell body (distance = 0). Mean ± SEM values are shown relative to the mean value in vehicle controls. Vehicle: n = 5; ketamine: n = 7. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312

mine treatment on dendritic WFA labeling was detected by a two-way ANOVA (Fig. 2). As a previous human post mortem brain study reported a loss of PNN around interneurons in mPFC (Mauney et al., 2013), a region highly important for etiology of disease, we performed next PNN analysis in mPFC sections. Here we detected a significant reduction of WFA+ cells density in ketamine-treated animals (vehicle: 108.4 ± 10 cells/mm2; ketamine: 80.7 ± 6 cells/mm2; p = 0.04, two-tailed t-test) and strong tendency in reduction of double-positive PV+WFA+ cells (vehicle: 93 ± 9 cells/mm2; ketamine: 69 ± 6 cells/mm2; p = 0.06, two-tailed t-test). Also, the percentage of PV+WFA+ among all PV+ cells showed a similar tendency to be reduced after ketamine treatment (p = 0.06, two-tailed t-test Fig. 3C). In contrast, PV+ and PV WFA+ cells populations were unaffected by ketamine treatment (Fig. 3A, B). Percentages of PV+WFA+ among all PV+ cells and among all WFA+ cells were also not significantly different between ketamine- and vehicle-treated rats. Noteworthy, the reduced number of WFA+ cells after ketamine treatment was confirmed by staining of another set of mPFC slices from the same animals (two-tailed ttest, p = 0.04), highlighting reproducibility of this major finding. Since previous animals studies revealed that the HNK-1 carbohydrate plays a crucial role in regulating

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Fig. 3. Densities of PV and WFA-positive cells in the mPFC of ketamine-treated rats. (A): Representative images of PV (in red) and WFA (in green)positive cells in the mPFC. Upper panels correspond to vehicle-injected controls, lower panels show ketamine-treated animal brains. Nuclei were visualized by Hoechst stain (in blue). Scale bar=50 mm. (B): PV+, WFA+, PV+WFA+ and PV WFA+ cells density per mm2 in the mPFC. (C): PV+WFA+ double-positive cells as a percentage of all PV+ and WFA+ cells in mPFC (C). Mean + SEM values are presented. *p = 0.04, twotailed t-test. Vehicle: n = 5, ketamine: n = 7. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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interneurons in various brain areas, including PFC (Mauney et al., 2013), entorhinal cortex, and amygdala (Pantazopoulos et al., 2010). Quantitatively, our cell density analysis in mPFC revealed 20% reduction in density of WFA+ cells, while the human postmortem study detected more prominent 70% reduction of WFA+ cells in PFC of schizophrenia patients (Mauney et al., 2013). This is not surprising considering relatively short duration of ketamine treatment and post-treatment interval as compared to the time-course of disease. It would be interesting to test in follow-up studies if the treatment with typical and atypical neuroleptics would lead to abrogation or exaggeration of PNN alterations found in the mPFC of ketamine-treated rats. A previous study performed in our settings demonstrated that injection of ketamine induced impairment in PFC-dependent behaviors, such as latent inhibition and social interactions (Becker et al., 2003). Here, ketamine treatment was also found to reliably

impair non-aggressive social interactions, thus confirming that the employed protocol induces an equivalent of negative symptoms, which are characteristic for schizophrenia. The ketamine model used here obviously may not reproduce all aspects of schizophrenia. Here we focused on deficiency in NMDA receptors as one of major hallmarks of disease. In vitro studies did not detect the effect of NMDA receptor antagonist AP5 on formation of WFA+ PNNs in hippocampal cultures in vitro (Dityatev et al., 2007), but neither acute not chronic effects of NMDA receptor blockade on maintenance of cortical PNNs have been studied. However, because expression of PNN components and enzymes cleaving them is activity-dependent (Dityatev et al., 2010a,b), one can expect complex effects of ketamine on PNNs, which may depend on the duration of ketamine treatment and induced cumulative changes in the pattern of neural activity in the mPFC. Interestingly, low concentrations of ketamine may preferentially affect NMDA receptors on interneurons and lead to disinhibition

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Fig. 4. Expression of PV, WFA and HNK-1 in the mPFC of ketamine-treated rats. (A): Representative images of PV (in gray), PNNs visualized by WFA (in green) and HNK-1 (in red) expression patterns in the mPFC. Nuclei were visualized by Hoechst stain (in blue). Picture inserts indicate different types of regions of interests (ROI): full ROI for PV, donut-ROI for WFA and HNK-1 signals around cell bodies, and rectangular ROI (continuous line) for perisynaptic HNK-1. Magnified ROIs shown in inserts correspond to rectangular areas outlined by dashed lines. Scale bar=50 mm. (B): Relative intensity of fluorescence signal per cell body, normalized per mean value in the control group. Mean + SEM values are shown. *p = 0.048, Mann–Whitney test. Vehicle: 5 mice, ketamine: 7 mice. (C): Relative intensity of HNK-1 carbohydrate fluorescence in the neuropil region normalized per mean value in the control group. Mean + SEM values are shown. Vehicle: 5 mice, ketamine: 7 mice, two-tailed t-test did not detect any difference. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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that may mediate anti-depressant effects of ketamine. Strikingly, enzymatic digestion of PNNs with chondroitinase ABC abolished sustained anti-depressant action of ketamine, thus showing an interaction between the drug and PNN organization (Donegan and Lodge, 2016). Our analysis did not detect changes in the number of WFA+ cells in the CA1 area of the hippocampus. Also there are no human studies showing alteration in number of PNNs in hippocampus. This is congruent with the hypothesis that schizophrenia-related ECM alterations are brain region specific. Our data also show reduction of PV signal intensity in the mPFC. This is in line with a recent human postmortem study that also reported the decreased intensity of PV, rather than a loss of PV+ cells, in dorsolateral PFC of schizophrenia patients (Enwright et al., 2016). Interestingly, pharmacogenetic inhibition of PV neurons is sufficient to induce large fractions of low-differentiated (low PV and GAD67 expression) basket cells with low excitatory-to-inhibitory synaptic-density ratios (Donato et al., 2013). Further analysis of excitatory/inhibitory

inputs to PV+ cells as a function of ECM expression in schizophrenia models may give insights into the mechanisms underlying the observed changes in WFA and PV expression and their functional impact. Although the general organization of neural ECM associated with somata versus dendrites of fast-spiking GABAergic interneurons, or with glutamatergic principal cells is similar, there are differences in the level of expression of major components (hyaluronic acid, diverse chondroitin sulfate proteoglycans, tenascin-R and link proteins). Hence dysregulation in the levels of a particular ECM molecule or ECM digesting protease may differentially affect ECM associated with different cell types and subcellular domains. Here, we failed to detect changes in dendritic WFA labeling or in tenascinR-associated HNK-1 expression in the neuropil. As tenascin-R is one of major carriers of HNK-1 (Saghatelyan et al., 2001), the latter finding suggests a specificity of changes in PNNs rather than in perisynaptic ECM localized in the neuropil. Still, these data should be interpreted cautiously as the HNK-1 carbohydrate is also

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Fig. 5. Dandelion clock-like CS56+ ECM structures in the mPFC of ketamine-treated rats. (A): Representative images of PNNs visualized by WFA (in green), astrocytes visualized by anti-S100b (in red) and glial ECM visualized by anti-CS56 antibodies. *Point to the centers of CS56+ clusters. Nuclei were visualized by Hoechst stain (in blue). Scale bar=50 mm. (B, C): Intensity of CS56+ immunofluorescence per area and number of CS56 + clusters. Mean + SEM values are shown. ***p = 0.0005, two-tailed t-test. Vehicle: 5 mice, ketamine: 5 mice. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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carried by a number of cell adhesion molecules (Kleene and Schachner, 2004), which may mask possible alteration in expression of HNK-1 in perisynaptic ECM. Additional perisynaptic ECM markers and super-resolution imaging of perisynaptic ECM should be used in the future to re-investigate this issue. However, our study makes a progress in highlighting differential regulation of ECM forms in a schizophrenia model by showing that the decrease in density of WFA+ cells in mPFC is accompanied by upregulation of CS56+ ECM, which was suggested to be of glial origin and has an influence on regulation of synaptic plasticity (Hayashi et al., 2007). Our study shows a statistically significant increase in the total intensity of CS56 immunofluorescence, but not in the number of CS56+ clusters in the mPFC. Previous human postmortem studies did not investigate glial ECM in the PFC of schizophrenia patients, although a decreased number of CS56-positive clusters was found in the amygdala (Pantazopoulos et al., 2015). Currently available data are not sufficient to discuss possible reasons for the difference between these studies and we can just speculate that elevated CS56 immunoreactivity might reflect changes in the state of glial cells. In fact, human post mortem studies revealed

a subgroup of schizophrenia patients (38%) with increased expression of inflammatory marker mRNAs such as interleukin-6, SERPINA3, interleukin-1b and interleukin-8 and increased microglia density in dorsolateral PFC (Fillman et al., 2013). Individuals with schizophrenia and neuroinflammation have been shown to have increased expression of glial fibrillary acidic protein mRNA and hypertrophic astrocyte morphology (Catts et al., 2014). In conclusion, we show mPFC-specific changes in PNNs in the ketamine induced experimental model of schizophrenia. As animals were not treated with antipsychotics, and perfused and fixed in well-controlled conditions, and thus free of limitations typical for human post mortem studies, our study provides a strong support to previous human findings. Moreover, the results open new opportunities to further investigate molecular mechanisms of PNNs and glial ECM dysregulation and possible functional consequences of these ECM modifications for excitability of fast-spiking interneurons, perisomatic GABAergic transmission, synaptic plasticity and astroglial functions (Saghatelyan et al., 2003; Bukalo et al., 2007; Dityatev et al., 2007). Also rescue experiments with overexpression of PNN

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components or knockdown of glial ECM molecules could be instrumental to discover modulation of which ECM forms might be beneficial for treatment of schizophrenia.

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Acknowledgments—We thank Artem Turetskyy for automatization of image analysis methods, Jenny Schneeberg for technical support, and Thomas Frodl and Johann Steiner for critical comments to the manuscript. This work has been supported by the funding from the European Union’s 7 Framework Programme under the Marie Curie grant agreement No 606950, EXTRABRAIN.

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(Received 18 November 2016, Accepted 7 March 2017) (Available online xxxx)

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