International Graduate School in Molecular Medicine Ulm International PhD Programme in Molecular Medicine
Synaptic pathways related to Shank3 and its interaction partner ProSAPiP1
Dissertation submitted in partial fulfilment of the requirements for the degree of „Doctor rerum naturalium” (Dr. rer. nat.) of the International Graduate School in Molecular Medicine Ulm
Dominik Reim Born in Nürtingen, Germany Institute for Anatomy and Cell Biology, Head: Prof. Dr. Tobias M. Böckers
2016 1. Current dean / chairman of the Graduate School: Prof. Dr. Michael Kühl
2. Thesis Advisory Committee: - First supervisor: Prof. Dr. Tobias M. Böckers - Second supervisor: Prof. Dr. Thomas Wirth - Third supervisor: Dr. Chiara Verpelli
3. External reviewer: Prof. Dr. Matthias Kneussel
4. Day doctorate awarded: March 20, 2017
Results gained in my thesis have previously been published in the following publications:
Reim, D., Distler, U., Halbedl, S., Verpelli, C., Sala, C., Bockmann, J., Tenzer, S., Boeckers, T.M., and Schmeisser, M.J. (2017). Proteomic analysis of postsynaptic density fractions from Shank3 mutant mice reveals brain region specific changes relevant to autism spectrum disorder. Front Mol Neurosci, doi: 10.3389/fnmol.2017.00026
Reim, D., Weis, T.M., Halbedl, S., Delling, J.P., Grabrucker, A.M., Boeckers, T.M., and Schmeisser, M.J. (2016). The Shank3 Interaction Partner ProSAPiP1 Regulates Postsynaptic SPAR Levels and the Maturation of Dendritic Spines in Hippocampal Neurons. Front Synaptic Neurosci 8, 13, doi: 10.3389/fnsyn.2016.00013
Vicidomini, C., Ponzoni, L., Lim, D., Schmeisser, M.J., Reim, D., Morello, N., Orellana, D., Tozzi, A., Durante, V., Scalmani, P., Mantegazza, M., Genazzani, A.A., Giustetto, M., Sala, M., Calabresi, P., Boeckers, T.M., Sala, C., and Verpelli, C. (2016). Pharmacological enhancement of mGlu5 receptors rescues behavioral deficits in SHANK3 knock-out mice. Mol Psychiatry. doi: 10.1038/mp.2016.30
Distler, U., Schmeisser, M.J., Pelosi, A., Reim, D., Kuharev, J., Weiczner, R., Baumgart, J., Boeckers, T.M., Nitsch, R., Vogt, J., and Tenzer, S. (2014). In-depth protein profiling of the postsynaptic density from mouse hippocampus using data- independent acquisition proteomics. Proteomics 14, 2607-2613 doi: 10.1002/pmic.201300520
Table of contents
Table of contents
TABLE OF CONTENTS 4
1 ABBREVIATIONS 7
2 INTRODUCTION 9
2.1 Autism spectrum disorder (ASD) 9
2.2 The postsynaptic density (PSD) 11 2.2.1 Structural organization of the PSD 12 2.2.2 The ProSAP/Shank protein family 13
2.3 Association of SHANK genes and ASD 14 2.3.1 SHANK genes in human ASD 15 2.3.2 Shank mutant animal models 16
2.4 The Fezzins – Shank interaction partners at the PSD 19 2.4.1 The Fezzin protein family 19 2.4.2 ProSAPiP1 recruits SPAR proteins to synaptic sites 20 2.4.3 A potential role of PROSAPIP1 in ASD 21
2.5 Aim of this study 22
3 MATERIAL AND METHODS 23
3.1 Material 23 3.1.1 Mice 23 3.1.2 Labware 23 3.1.3 Consumable supplies 24 3.1.4 Universal chemical reagents 25 3.1.5 Cell culture media and material 26 3.1.6 Viral particles 26 3.1.7 Kits 27 3.1.8 Buffers 27 3.1.9 Western blot gels 30 3.1.10 Primary antibodies 30 3.1.11 Secondary antibodies 31 3.1.12 DNA and shRNA constructs 31
3.2 Methods – Cell Culture 32 3.2.1 Plasmid preparation 32 3.2.2 HEK293T cells 32
Page | 4 Table of contents
3.2.3 Transfection of HEK293T cells 32 3.2.4 Transfection of HEK293T cells – Production of viral particles 33 3.2.5 Primary hippocampal neurons 33 3.2.6 Viral infections 33 3.2.7 Primary hippocampal neuron lysates 34 3.2.8 Immunofluorescent staining of primary hippocampal neurons 34 3.2.9 Image analysis 35
3.3 Methods – Protein biochemistry 36 3.3.1 Subcellular fractionation – cell culture lysates 36 3.3.2 Subcellular fractionation – brain tissue 36 3.3.3 Subcellular fractionation – brain tissue, fast protocol 37 3.3.4 Bradford assay 37 3.3.5 Western blot analysis 38 3.3.6 Mass-Spectrometry 38 3.3.7 Mass-Spectrometry data analysis 39
4 RESULTS 40
4.1 Proteomic analysis of postsynaptic density fractions from Shank3 mutant mice reveals brain region specific changes relevant to autism spectrum disorder 40 4.1.1 Confirmation of successful PSD fractionation 40 4.1.2 Confirmation of the Shank3 KO genotype in homogenates and PSD fractions 42 4.1.3 Large-scale proteomic analysis comparing WT and Shank3 KO in mouse striatum and hippocampus using LC-MS 43 4.1.4 Significant enrichment of gene ontology (GO) terms and KEGG pathways among the significantly altered proteins in the striatal and hippocampal WT and Shank3 KO PSD 51 4.1.5 Protein-protein interaction networks of significantly altered proteins in the striatal and hippocampal PSD fraction 59 4.1.6 Significant alterations converge between the striatal and the hippocampal Shank3Δ11-/- mutant PSDs and a previously published Shank3 in-vivo interactome 60
4.2 The Shank3 interaction partner ProSAPiP1 regulates postsynaptic SPAR levels and the maturation of dendritic spines in hippocampal neurons 62 4.2.1 Verification of successful ProSAPiP1 knock down 62 4.2.2 Verification of successful ProSAPiP1 overexpression 63 4.2.3 ProSAPiP1 is not necessary to determine the number of synapses 64 4.2.4 ProSAPiP1 does not influence synaptic Shank3 levels but selectively regulates postsynaptic protein levels of SPAR 66 4.2.5 ProSAPiP1 does not regulate postsynaptic PSD95 levels 68 4.2.6 Overexpression of GFP-ProSAPiP1 increases the amounts of LAPSER1 at the synapse 69 4.2.7 ProSAPiP1 accounts for proper dendritic spine maturation 70
Page | 5 Table of contents
5 DISCUSSION 73
5.1 PSD fractionation 73
5.2 Large-scale proteomic analysis of striatal and hippocampal PSDs of Shank3Δ11-/- mutant mice 74
5.3 Functional aspects of ProSAPiP1 at the PSD 78
6 SUMMARY 82
7 REFERENCES 84
8 ACKNOWLEDGEMENTS 97
9 STATUTORY DECLARATION 98
10 LIST OF PUBLICATIONS 99
Page | 6 Abbreviations
1 Abbreviations
AMPA α-amino-3-hydroxy-5-methyl-4- isoxazolepropionic acid ANK Ankyrin repeats ASD Autism spectrum disorder cm Centimeter CNS Central nervous system DAVID Database for Annotation, Visualization and Integrated Discovery DIV Days in-vitro °C Degree Celcius E18/E19 Embryonic day 18/19 GO Gene ontology x g G-force g Gram GFP Green fluorescent protein Ho Homogenate HRP Horeseradish peroxidase h Hour ICC Immunocytochemistry ID Intellectual disability kDa Kilodalton KO Knock-out (Shank3Δ11-/- mutation) KEGG Kyoto Encyclopedia of Genes and Genomes LTD Long-term depression LTP Long-term potentiation MAGUK membrane-associated guanylate kinase µg Microgram µl Microliter µm Micrometer ml Milliliter mm Millimeter mM Millimolar
Page | 7 Abbreviations min Minute M Molar nm nanometer NMDA N-Methyl-D-Aspartate P2 Pellet 2 (crude membrane fraction) PMS Phelan-McDermid syndrome PSD Postsynaptic density Pro Proline-rich clusters ProSAP/Shank Proline-rich synapse-associated protein / SH3 and multiple ankyrin repeat domain protein ProSAPiP1 ProSAP-interacting protein 1 PDZ PSD-95/DLG/ZO-1 domain RapGAP Rap GTPase-activating protein RFP Red fluorescent protein rpm Revolutions per minute RNAi Ribonucleic acid interference Scr Scrambled STRING Search Tool for the Retrieval of Interacting Genes/Proteins shRNA Small hairpin ribonucleic acid SPAR Spine-associated RapGAP SH3 Src homology 3 domain SAM Sterile alpha motif S1 Supernatant 1 (purified homogenate) S2 Supernatant 2 (cytosol) S3 Supernatant 3 (synaptic cytosol) Syn Synaptosomes U Unit V Volt WB Western blot WT Wild-type
Page | 8 Introduction
2 Introduction
2.1 Autism spectrum disorder (ASD)
The first documentations of autistic patients showing social deficits and several stereotypies were recorded by Leo Kanner in 1943 and Hans Asperger in 1944 (Asperger, 1944; Kanner, 1943). Today, the term autism spectrum disorder (ASD) comprises a variety of complex and diverse neurodevelopmental conditions clinically defined by the aforementioned two core symptoms according to the Diagnostic and Statistical Manual of Mental Disorders edition 5 (DSM-5): (1) an impairment of social interaction and communication and (2) the occurrence of stereotype repetitive behaviors (American-Psychiatric-Association, 2013; Volkmar and Pauls, 2003). Importantly, ASD affects approximately 1% of the human population (Zoghbi and Bear, 2012). Unlike several other disorders with a clear-cut phenotype, ASD does not manifest in a uniform phenotype, thus eliminating the notion of ‘the one autism’. Additionally, several co-morbidities frequently occur in ASD patients ranging from intellectual disability (ID) (60%, (Amaral et al., 2008)) or epilepsy (5-44%, (Tuchman and Rapin, 2002)), to anxiety and mood disorders (Lecavalier, 2006), sleep disorders (Richdale and Prior, 1995), hyperactivity or sensory disturbances (Nickl-Jockschat and Michel, 2011). The highly diversified and heterogeneous phenotypic spectrum of ASD further results from an increasing number of genes implicated in its pathogenesis and a broad background of risk factors involved (Zoghbi and Bear, 2012). Furthermore, a classification between syndromic and non-syndromic autism can be defined. In the case of non-syndromic autism, the patient’s ‚autism‘ is the primary diagnosis. In contrast, syndromic autism describes the cases in which the patient’s autism is diagnosed secondarily to an already defined, primarily monogenetic developmental disorder such as Fragile X or Rett syndrome. A list of exemplary disorders can be found in Table 1.
Page | 9 Introduction
Table 1 | Single-gene syndromic ASDs. Data obtained from (Costales and Kolevzon, 2015; Kelleher and Bear, 2008). ID: Intellectual Disability; n.d.: not determined.
GENE DISORDER RATE OF AUTISM RATE IN ASD ID Mecp2 Rett Syndrome 100% 2% + Shank3 Phelan-McDermid syndrome 84-94% 0.5-2% + Tsc1/2 Tuberous sclerosis 25-60% 1-4 % + Ube3a Angelman syndrome 40% 1% + Fmr1 Fragile X syndrome 15-30% 2-5 % + Nf1 Neurofibromatosis type 1 4% 0-4 % + Pten PTEN hamartoma syndrome n.d. 1% +
The diagnosis of ASD usually is made within the first three years of life. Within this period, the human brain is adjusting to our environment and undergoes important developmental procedures, including intense synaptogenesis. Usually, the first detection of autistic traits, and thus the basis for the ASD diagnosis, occurs between 6 months and 3 years of age (Bourgeron, 2009; Huttenlocher and Dabholkar, 1997). Moreover, ASD is considered as a neurodevelopment condition and indeed, the core features and most of the co-morbid disorders are highly implicating developmental disturbances in the central nervous system (CNS). Studies on head circumference, representing brain size, and additional MRI studies show a 5-10% enlargement of the total brain in autistic children at early postnatal life (Courchesne et al., 2003; Courchesne et al., 2001; Dementieva et al., 2005). While the enhanced growth of the brain normally decelerates to regular growth in the second year of life, the absolute brain size persistently stays enlarged in ASD during childhood (Amaral et al., 2008; Dawson et al., 2007). Further studies compared the sizes of subregions of the brain in autistic patients. Interestingly, alterations in shape and volume have been observed for cortical regions, the hippocampus and the caudate nucleus, as part of the striatum (Amaral et al., 2008; Casanova et al., 2002; Casanova et al., 2006; Dager et al., 2007; Hollander et al., 2005; Schumann et al., 2004). Among various functions, cortical regions and the hippocampus have been associated with speech, learning and memory functions. Thus, morphological changes might result in the formation of several core and co-morbid features, including impaired social interaction and mental retardation. Furthermore, structural changes in the striatum have been correlated with repetitive behaviour in autistic patients (Hollander et al., 2005). These studies indicate that developmental disturbances of brain anatomy might contribute to the formation of an ASD phenotype. In ASD research, much attention has
Page | 10 Introduction been drawn to synapses (Belmonte and Bourgeron, 2006; Bourgeron, 2009; Zoghbi, 2003). Indeed, an association with increased risk for ASD was shown for various mutations in genes involved in the regulation of synaptogenesis and neuronal circuit formation as well as in regulating the levels of synaptic proteins or genes coding for synaptic proteins themselves (Bourgeron, 2009; Spooren et al., 2012; Toro et al., 2010). As a result, these genes may be associated with synaptic structure and function. The most frequent single-gene mutations in ASD with ID affect genes, which are critical regulators of synaptic function (Zoghbi and Bear, 2012). Several of the resulting disorders are listed in Table 1.
2.2 The postsynaptic density (PSD)
The mammalian central nervous system (CNS) is formed by billions of neurons, precisely executing its crucial functions. Considering this enormous amount of neurons, their precise organization and interaction has to be fulfilled. The latter is generally achieved by signal transmission from one cell to another. For this purpose, neurons mostly form chemical synapses with each other by which the presynaptic axon is connected to the postsynaptic dendrite across the synaptic cleft. The signal transmission occurs by presynaptic release of a neurotransmitter and its postsynaptic reception. The neurotransmitter differs among special types of neurons and generally interacts with defined receptors on the postsynaptic membrane leading to signal transmission into the receiving neuron and thus either activation (excitation) or inhibition of this cell. A prominent anatomical feature of excitatory glutamatergic synapses is the presence of a subcellular compartment beneath the postsynaptic membrane, the so-called postsynaptic density (PSD). The PSD is an electrondense and highly organized network of several hundred to thousand proteins with a width of ~300-400 nm and a thickness of ~30-50 nm in average, which visibly thickens the postsynaptic membrane and the area underneath as observed by electron microscopy. The PSD is located at the top of dendritic spines, actin-rich protrusions of glutamatergic synapses, and one of its most important features includes proper postsynaptic signaling and synaptic plasticity. The shape of spine heads is tightly associated with the size of the PSD and thus the extent of synaptic strength. Therefore, the PSD serves
Page | 11 Introduction as a highly organized structure to enable proper reception, modulation and transduction of the incoming signal (Boeckers, 2006; Sheng and Hoogenraad, 2007).
2.2.1 Structural organization of the PSD
The precise organization of the PSD is underlined by its classification in three different layers (Boeckers, 2006; Sheng and Hoogenraad, 2007; Valtschanoff and Weinberg, 2001; Verpelli et al., 2012): The first layer is the closest to the presynaptic site, comprising ion channels and membrane receptors such as the ionotropic glutamate receptors of the N-Methyl-D- Aspartate (NMDA) type in the center of the PSD and the α-amino-3-hydroxy-5-methyl- 4-isoxazolepropionic acid (AMPA) type. Additionally, the group 1 metabotropic glutamate receptors mGluR1/5 in the periphery of the PSD and cell adhesion molecules such as the neuroligins, which stabilize the physical connection of synaptic contacts, are included in the first layer (Baude et al., 1993; Kharazia and Weinberg, 1997; Nusser et al., 1994; Racca et al., 2000). The second layer is built up by the proteins of the membrane-associated guanylate kinase (MAGUK) family, including for instance PSD-93, PSD-95, SAP-97 or SAP-102, and signalling molecules like receptor tyrosine kinases in close proximity to the layer one molecules. The proteins in layer two basically transmit the received signal to further downstream components or interconnect proteins of the first two layers with each other as well as with proteins of the third PSD layer. The third PSD layer mostly includes synaptic scaffold proteins as the Shank protein family and finally also the actin cytoskeleton. Together, these proteins serve as a core molecular hub for all other PSD components interconnecting membrane-attached components with their downstream components, further PSD scaffolds and finally the actin cytoskeleton to collectively stabilize and shape the postsynaptic site. This complex, but tightly organized structure is important for optimizing the response to neurotransmitter reception by strengthening the respective transmission efficacy via long-term potentiation (LTP) or weakening the latter via long-term depression (LTD). Any disruption of the underlying molecular anatomy that cannot be compensated has detrimental consequences for the functionality of the corresponding brain region or
Page | 12 Introduction even of the entire brain, since the correct transmission of the synaptic signal can no longer be guaranteed.
2.2.2 The ProSAP/Shank protein family
One of the most important molecular PSD components is the ProSAP/Shank family. These Proline-rich synapse-associated proteins (ProSAP) or SH3 and multiple ankyrin repeat domain proteins (Shank) comprise three family members: Shank1, ProSAP1/Shank2 and ProSAP2/Shank3 (further referred to using ‘Shank’ protein names). All three Shanks are present in the PSD of excitatory synapses (Boeckers et al., 1999a; Naisbitt et al., 1999; Valtschanoff and Weinberg, 2001). Importantly, each Shank is expressed in different isoforms. With six intragenetic promotors, the Shank3 gene for example, causes a huge complexity and thus also a large variety of isoforms. The number of identified Shank3 isoforms is still increasing, with currently 10 identified isoforms (Boeckers et al., 1999a; Jiang and Ehlers, 2013; Lim et al., 1999). Among the different brain regions, the Shanks exhibit different expression levels. Shank1 is predominantly expressed in the cortex, but high levels are also reported in the hippocampus and cerebellum (Boeckers et al., 2004; Lim et al., 1999; Peca et al., 2011). Shank2 expression was detected with the highest levels in cortex, hippocampus and cerebellum and at lower levels also in striatum and thalamus (Boeckers et al., 1999a; Boeckers et al., 2004; Peca et al., 2011; Schmeisser et al., 2012; Zitzer et al., 1999a; Zitzer et al., 1999b). The expression of Shank3 in the CNS, however, is highest in the striatum and thalamic nuclei, while there are also moderate levels reported for cortex and hippocampus (Boeckers et al., 2004; Boeckers et al., 1999b; Peca et al., 2011; Vicidomini et al., 2016; Wang et al., 2014). Moreover, each of the three Shank genes exhibits a brain region and isoform specific expression pattern. In addition, the Shanks additionally show distinct expression profiles in peripheral organs. While Shank1 is predominantly expressed in brain, Shank2 protein was detected in several different tissues such as pancreas, pituitary gland, lung, liver, kidney and testis. Shank3 protein was further found in every tissue examined so far (Boeckers et al., 1999b; Lim et al., 1999; Redecker et al., 2006; Redecker et al., 2001; Tobaben et al., 2000).
Page | 13 Introduction
Within the brain, Shank2 and Shank3 most probably play a crucial role in the formation of new synapses, as both proteins are recruited early during synaptogenesis. With their great capacity of protein-protein interactions, Shank2 and Shank3 might serve as an important molecular framework for the assembly of the PSD during synaptogenesis (Bresler et al., 2004; Grabrucker et al., 2011a). Shank1, however, was found to appear at synapses only at later stages during synaptic maturation (Sala et al., 2001). Furthermore, Shank proteins do not only seem to be important for the generation but also the maintenance of spines and synapses (Roussignol et al., 2005). Shank proteins are considered as the ‚master scaffold‘ proteins in the PSD. Indeed, the Shank proteins interact with a huge amount of different proteins, including themselves and with a still growing number of newly identified interaction partners (Boeckers et al., 1999b; Gundelfinger et al., 2006; Kim et al., 1997; Naisbitt et al., 1999; Takeuchi et al., 1997; Tu et al., 1999; Yao et al., 1999). The great capacity of protein- protein interactions is achieved by the presence of multiple protein-protein interaction domains. These domains comprise N-terminal ankyrin repeats (ANK), a highly conserved Src homology 3 domain (SH3), the PSD-95/DLG/ZO-1 domain (PDZ), Proline-rich clusters (Pro) and a C-terminal sterile alpha motif (SAM) (Figure 1). With these domains, the Shank proteins bind to and interconnect a huge variety of further proteins. Due to several intragenic promoters and alternative splicing events, the different existing Shank gene products possess a different set of protein-protein interaction domains. Due to this high complexity of different isoforms differentially present in distinct brain regions, it certainly is intelligible that disruptions of these tightly regulated processes will result in detrimental consequences for synaptic structure and function, for the functionality of the brain in general and thus for the affected individual.
2.3 Association of SHANK genes and ASD
The genetic background of ASD patients is highly diversified. In the last decade, several genetic mutations or genomic imbalances have been associated to ASD. The respective causative genes, however, usually determine ASD formation in only a minor percentage of all ASD patients. Astonishingly, among these genes, distinct biological pathways can be classified. The most studied biological pathway includes a big consortium of synaptic genes, and interestingly, several of these genes are important
Page | 14 Introduction for the correct balance between excitation and inhibition (E/I balance). Among the group of synaptic genes, the SHANK genes are of particular interest (Durand et al., 2007; Guilmatre et al., 2014; Sudhof, 2008; Toro et al., 2010).
2.3.1 SHANK genes in human ASD
Genetic disruptions in all three SHANK genes have been found in ASD patients. A recent meta-analysis revealed that approximately 1% of patients with the clinical diagnosis of ASD carry a SHANK mutation, with SHANK1 mutations present in 0.04%, SHANK2 mutations present in 0.17% and SHANK3 mutations present in 0.69% of ASD patients. Furthermore, SHANK3 mutations were found in 2.12% of ASD patients that additionally suffer from moderate to severe ID (IQ <70) (Leblond et al., 2014). These data are strongly underlining the significant association of SHANK genes with ASD, with the strongest impact of mutations in the SHANK3 gene. The mildest phenotype has been observed in patients with SHANK1 mutations. Only males carrying a SHANK1 mutation showed high-functioning autism, while females were anxious and shy. Furthermore, ID is rather unlikely for these individuals, since they usually show an IQ of at least 80 or higher (Guilmatre et al., 2014; Sato et al., 2012). Two years earlier, in 2010, the first ASD patients with a SHANK2 mutation were described. These patients and the ones described in further studies showed moderate ID, usually with an IQ between 50 and 70, accompanied with speech and developmental delay in several of the individuals (Berkel et al., 2010; Chilian et al., 2013; Leblond et al., 2012; Pinto et al., 2010; Schluth-Bolard et al., 2013; Wischmeijer et al., 2011). The first association between SHANK3 and ASD was raised in 2007, when three patients with ASD, serious ID and delayed or absent speech were described. These patients were carrying different mutations in the SHANK3 gene, including deletions and frameshift mutations. Interestingly, another patient, carrying a SHANK3 duplication, was diagnosed with Asperger syndrome and the idea of a gene dosage effect of SHANK3 was proposed (Durand et al., 2007). Subsequently, further ASD patients, showing similar symptoms and carrying mutations in the SHANK3 gene, were described (Boccuto et al., 2013; Gauthier et al., 2009; Moessner et al., 2007; Waga et al., 2011).
Page | 15 Introduction
Importantly, deletions of 22q13.3 are causing ‘22q13.3 deletion’ or ‘Phelan-McDermid syndrome’ (PMS), which is regarded as syndromic ASD variant. PMS primarily suffer from global developmental delay, intellectual disability, absent or delayed speech, neonatal hypotonia and facial dysmorphisms, but often also show autistic features. Furthermore, several of the patients also present with various types of epileptic seizures (Nesslinger et al., 1994; Phelan, 2008; Phelan et al., 2001; Watt et al., 1985). Among others, the genes encompassed in the deletion include SHANK3. Although the deletions are varying in size, all PMS patients carry a deletion in 22q13.3, which results in a haploinsufficiency of SHANK3, ACR, RABL2B and MGC70863 (Bonaglia et al., 2006; Durand et al., 2007; Wilson et al., 2003). The deleterious impact of SHANK3 haploinsufficiency in PMS was further emphasized by the description of a patient’s balanced translocation, which interrupts SHANK3 in exon 21. This patient presented typical symptoms for PMS (Bonaglia et al., 2001). Additionally, a translocation affecting the last two exons (21 and 22) of SHANK3 and parts of ACR also resulted in PMS symptoms (Misceo et al., 2011), thus strengthening the impact of SHANK3 in Phelan- McDermid syndrome.
2.3.2 Shank mutant animal models
To explore the precise neurobiological impact of SHANK mutations in ASD, Shank mutant animal models have been generated and intensively studied up to this date. The respective Shank genes have been knocked out and the resulting consequences were analysed on different levels. Interestingly, in Shank mutant mice several autistic traits could be observed: Shank1 knockout mice showed decreases in vocal communication and locomotion, increases in anxiety and a reduced long-term memory, but an enhancement in the working memory (Hung et al., 2008; Silverman et al., 2011; Wohr et al., 2011). Shank2 knockout mice are hyperactive, also show increased anxiety, female specific repetitive grooming as well as abnormal vocal and social behaviour (Schmeisser et al., 2012; Won et al., 2012). Due to the high complexity of the Shank3 gene and different resulting gene products, various different Shank3 knockout models were generated. These models include Shank3∆4-7 (Peca et al., 2011), Shank3∆4-9B (Bozdagi et al., 2010; Yang et al., 2012) and Shank3∆4-9J mice (Wang et al., 2011) all targeting the ankyrin repeats of Shank3,
Page | 16 Introduction
Shank3∆9 mice (Lee et al., 2015), Shank3∆11 mice (Schmeisser et al., 2012; Vicidomini et al., 2016) targeting the SH3 domain, Shank3∆13-16 mice (Peca et al., 2011), targeting the PDZ domain, Shank3∆21 mice (Kouser et al., 2013) and Shank3∆4-22 mice lacking all isoforms of Shank3 (Wang et al., 2016). While these mouse models all represent several of the aspects of ASD (for review see (Jiang and Ehlers, 2013)), the model used in this study is the homozygous Shank3∆11 knockout mouse (Shank3∆11-/-). The deletion of exon 11 of the Shank3 gene in these mice leads to a loss of three Shank3 isoforms Shank3a, Shank3b and Shank3c. Due to the presence of intragenetic promoters, not all Shank3 isoforms are removed and thus are still present in Shank3∆11-/- mice (Schmeisser et al., 2012; Vicidomini et al., 2016). A scheme of the genetic modification and the removed Shank3 isoforms is shown in Figure 1. Shank3∆11-/- mice show both increased repetitive and stereotyped behaviour and impaired social interaction. These behavioural phenotypes represent the core features of ASD. Furthermore, increased aggressiveness and hyposensitivity to pain were observed (Vicidomini et al., 2016). On the molecular level, increased synaptosomal protein levels of hippocampal GluN2B and striatal Shank2 (Schmeisser et al., 2012) and reduced protein levels of cortical and striatal Homer1b/c and cortical mGluR5 in PSD fractions were detected in these mutants. Especially the latter molecular changes seem to be associated with the behavioural phenotype, since a rescue of behavioural deficits was achieved by pharmacological increase of mGluR5 activity (Vicidomini et al., 2016).
Page | 17 Introduction
Figure 1 | Shank3 gene products in wild type and Shank3Δ11-/- mice Schematic illustration of the Shank3 gene (exons represented as blue boxes, intragenetic promoters indicated as arrows) of wild type (upper panel) and Shank3Δ11-/- mice (lower panel, deletion of exon 11 indicated in red) and its currently known gene products with protein-protein interaction domains of Shank3 (ANK: N-terminal ankyrin repeats; SH3: Src homology 3 domain; PDZ: PSD-95/DLG/ZO-1 domain; Pro: Proline-rich clusters; SAM: sterile alpha motif). Faint Shank3 gene products in the lower panel are no longer present in Shank3Δ11-/- mice. Modified from (Jiang and Ehlers, 2013; Elsevier grants permission “to reproduce the aforementioned material subject to the terms and conditions indicated” (Figure 3, Jiang and Ehlers, 2013, reuse in a thesis/dissertation, both print and electronic); Wang et al., 2014; This figure is subjected to the Creative Common License CC BY 2.0, http://creativecommons.org/licenses/by/2.0). Figure partially adapted from (Reim et al., 2017), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. Page | 18 Introduction
2.4 The Fezzins – Shank interaction partners at the PSD
Due to the strong association of SHANK and ASD, it is of high interest to investigate not only the role of the Shank proteins themselves, but also the role of their interaction partners at the PSD. One of the most important protein-protein interaction domains of the Shanks is the PDZ domain. This type of domain is also found in a large number of other synaptic proteins and promotes the formation of big molecular scaffolds in the PSD (Craven and Bredt, 1998; Garner et al., 2000; Harris and Lim, 2001; Kornau et al., 1995; Kornau et al., 1997; Sheng and Sala, 2001). Within the numerous binding partners of the Shank3 PDZ domain, we have identified and studied several of these proteins, including proteins of the Fezzin family (Schmeisser et al., 2009; Schmeisser et al., 2013; Wendholt et al., 2006).
2.4.1 The Fezzin protein family
The Fezzin protein family is a small family of proteins, including ProSAP-interacting protein 1 (ProSAPiP1), PSD-Zip70, LAPSER1 and the Nedd4 binding protein 3 (N4BP3) (Konno et al., 2002; Schmeisser et al., 2009; Schmeisser et al., 2013; Wendholt et al., 2006). All members of the Fezzin family share a molecular weight of approximately 70 kDa and structurally a conserved Fez1 (F37/esophageal cancer- related gene coding leucine zipper motif 1) domain (Ishii et al., 2001). Furthermore, the family members ProSAPiP1, PSD-Zip70 and LAPSER1 additionally share a coiled-coil region enabling homo- and hetero-multimerization and a C-terminal type I PDZ domain-binding motif (Wendholt et al., 2006). Moreover, ProSAPiP1, PSD-Zip70 and LAPSER1 have been detected in the PSD of excitatory synapses. With their type I PDZ domain-binding motif, these Fezzins might further promote postsynaptic cross-talk and the formation of postsynaptic scaffolds by interconnecting the Fezzins with each other and with further interaction partners (Maruoka et al., 2005; Schmeisser et al., 2009; Wendholt et al., 2006). As already indicated above, an interaction of Fezzins with the Shank3 PDZ domain has been described. In particular, co-localization studies with Shank3 and either ProSAPiP1 or LAPSER1 suggested an interaction of these proteins, which was further confirmed in vitro and in vivo. An interaction of Shank3 and PSD-
Page | 19 Introduction
Zip70, however, was not observed thus far, even though PSD-Zip70 is also localized at the PSD (Konno et al., 2002; Schmeisser et al., 2009; Wendholt et al., 2006). Interestingly, the Fez1 domain of all four Fezzin family members was shown to interact with the synaptic Rap GTPase-activating protein (RapGAP) called spine-associated RapGAP (SPAR) (Schmeisser et al., 2009). SPAR is a protein enriched at synaptic sites, where it is suggested to modify Rap activity (Pak et al., 2001; Roy et al., 2002). Structurally, SPAR shares two actin-binding domains (Pak et al., 2001). With these domains, SPAR most probably couples synaptic Rap signalling to the actin cytoskeleton. Due to modulation of Rap-mediated actin reorganization, SPAR might thus influence the structural plasticity of dendritic spines, including formation and elimination as well as maturation and defining the shape of dendritic spines (Hoe et al., 2009; Pak and Sheng, 2003; Pak et al., 2001). With their Fez1 domain, Fezzins are considered to anchor SPAR in spines and at the PSD. (Schmeisser et al., 2009; Wendholt et al., 2006). The precise functions of the Fezzin family members, however, are not yet completely unveiled and only a moderate number of studies investigating Fezzin family members has yet been performed.
2.4.2 ProSAPiP1 recruits SPAR proteins to synaptic sites
ProSAPiP1 was firstly described in 2006 being expressed in the brain with increasing protein levels during development (Wendholt et al., 2006). ProSAPiP1 is mainly found in cerebral cortex, caudate putamen, cerebellum and the hippocampus, on a subcellular level being localized at the PSD. Moreover, ProSAPiP1 was found to bind the synaptic RapGAPs SPAR, SPAR2 and SPAR3 (Dolnik et al., 2016; Spilker et al., 2008; Wendholt et al., 2006). Since ProSAPiP1 further interacts with Shank3, it may therefore link the SPARs to the Shank scaffold and indeed in hippocampal cultures, it was shown that ProSAPiP1 was able to recruit SPAR to the synaptic sites (Spilker et al., 2008; Wendholt et al., 2006). As the SPAR protein is known to regulate dendritic spine morphology (Pak et al., 2001), and ProSAPiP1 recruits SPAR to the synaptic site, a functional association of ProSAPiP1 and spine morphology may be feasible. The precise neuronal function of ProSAPiP1, however, has not yet been specified.
Page | 20 Introduction
2.4.3 A potential role of PROSAPIP1 in ASD
Although the detailed and precise functions of the Fezzins have not yet been perfectly understood, several aspects of their role in the CNS have been elucidated. In general, these proteins are regarded as linker molecules between the postsynaptic protein scaffold and the SPAR family (Schmeisser et al., 2009). As SPAR proteins are critically involved in regulating dendritic spine morphology (Pak et al., 2001; Spilker and Kreutz, 2010), mutations affecting the structure or function of the Fezzins might have severe consequences especially during spine development. Interestingly, a genomic deletion of chromosome 20 including the PROSAPIP1 gene has been identified in a patient with the clinical diagnosis of Asperger syndrome (Sebat et al., 2007). However, the detailed impact of the loss of PROSAPIP1 in this patient on disease pathology has not been examined yet. Therefore, more intense investigation on the precise neuronal function of the Fezzin protein family members and the consequences of disruptions in their genes might be necessary to better understand their possible roles in disease formation and pathology.
Page | 21 Introduction
2.5 Aim of this study
Since Shank3 is a ‘master scaffold’ protein arranging the postsynaptic density of excitatory glutamatergic synapses, mutations in the SHANK3 gene might possibly affect the general organisation and composition of the PSD and thus cause or contribute to patients’ pathology. Many studies have been performed to analyse the behavioural and molecular consequences of diverse Shank3 mutations, however, the precise molecular effects remain elusive. Furthermore, these studies mainly focused on selected proteins at synapses examined in only one brain region.
In this study, we aimed to establish a new protocol for biochemically isolating the PSD fraction of the striatum and the hippocampus of Shank3∆11-/- mice and their wild type littermates to perform large-scale proteomic analysis. Using this unbiased and comprehensive approach, we wanted to identify changes in the molecular composition of the Shank3∆11-/- mutant mouse PSD. Since proteomic analysis is an unbiased approach, we were not only focussing on the common and usual PSD components but we also considered unexpected factors that have not yet been associated with Shank3. Additionally, analysing both, the striatal and hippocampal PSD, we aimed to compare the results of the two brain regions to find region specific but also converging effects of the Shank3∆11-/- mutation.
In a second approach, we did not want to exclusively focus on Shank3 but also on the role of its interaction partners. The Fezzin protein family has recently been identified as Shank3 interaction partners and consists of four proteins, including ProSAPiP1. Interaction studies revealed that ProSAPiP1 interacts with Shank3 and the synaptic RapGAP SPAR, therefore, it was suggested that ProSAPiP1 might anchor SPAR at the PSD. The detailed function of ProSAPiP1 and the confirmation of synaptic SPAR recruitment, however, have not been studied yet. By performing ProSAPiP1 overexpression and knock down experiments in primary rat hippocampal neurons, we modified neuronal ProSAPiP1 protein levels to investigate the resulting molecular effects. Therefore, we aimed to unveil the neuronal function of ProSAPiP1 confirm or reject the idea of ProSAPiP1 recruiting SPAR to the PSD.
Page | 22 Material and Methods
3 Material and Methods
3.1 Material
3.1.1 Mice
Shank3Δ11-/- mice were generated as previously described (Schmeisser et al., 2012). Breeding was performed as het-het breeding on a C57BL/6 background, animal housing followed standard laboratory conditions (average temperature of 22°C with food and water available ad libitum, dark/light cycle as 12/12 rhythm). Shank3Δ11-/- mice and wild type littermates were from both sexes. Animal experiments were approved by the review board of the Land Baden-Wuerttemberg, Permit Number 0.103 and performed in compliance with the guidelines for the welfare of experimental animals issued by the Federal Government of Germany and the Max Planck Society.
3.1.2 Labware
Machine Company Avanti™ J-25 Beckman, Krefeld Axio Imager. Z1 Zeiss, Oberkochen Axiovert 40 CFL cell culture Zeiss, Oberkochen microscope Biofuge Fresco Kendro Laboratory, Hanau Blot transfer apparatus Biorad, Munich Cell culture sterile bench Nunc, Wiesbaden Centrifuge 5430 R Eppendorf, Hamburg Centrifuge 5804 R Eppendorf, Hamburg Certomat® H B. Braun Biotech international, Melsungen Certomat® R B. Braun Biotech international, Melsungen Cytoperm 2 Incubator Heraeus, Hanau Electroporator 2510 Eppendorf, Hamburg ELISA reader Thermo Scientific, USA Freezer (-20°C) Liebherr, Biberach Freezer (-80°C) Thermo Scientific, USA Gel chamber Biorad, Munich Gel tray Biorad, Munich Glass plates Biorad, Munich
Page | 23 Material and Methods
HERA cell Incubator Heraeus, Hanau Heraeus Pico 17 Thermo Scientific, USA Homogenization Vial S 2 ml and Sartorius, Göttingen Teflon Douncer Horizontal shaker Sigma-Aldrich, USA MicroChemi 4.2 station BNC Bio-Imaging Systems, Israel MiniProtean® Tetra System Bio-Rad, Munich NanoDrop 2000 Thermo Scientific, USA spectrophotometer Optima™ Max-E Ultracentrifuge Beckman, Krefeld Orbital shaker Heidolf, Schwabach Pipetboy Hirschmann, Eberstadt Pipettes Eppendorf, Hamburg Potter S B. Braun Biotech international, Melsungen Q-Pod MilliQ Millipore, USA Refrigerator (4°C) Liebherr, Biberach Rotor MLS-50 Beckman, Krefeld Rotor JA 25.50 Beckman, Krefeld SDS-Page apparatus Biorad, Munich Sterile bench Heraeus, Hanau Sterile bench Eppendorf, Hamburg Trans-Blot® Turbo Transfer Bio-Rad, Munich System Vertical shaker Eppendorf, Hamburg Vortex shaker Heidolf, Schwabach Vortexer Heraeus, Hanau Waterbath Grant, Munich Whatman filter papers Schleicher & Schuell, Dassel
3.1.3 Consumable supplies
Consumable supply Company 6-well plates Falcon, #353046 24-well plates Falcon, #353047 96-well plates Cellstar®, Greiner, #655180 Cell culture filter 0.45 µm Sarstedt, #83.1826 Cell scrapers Sarstedt, #83.1830 Glass coverslips Karl Hecht GmbH, Sondheim, #1001/13 Nitrocellulose blotting membrane GE Healthcare, Life Sciences, UK, #10600004 0.2 µm
Page | 24 Material and Methods
Page Ruler™ Prestained Protein Thermo Scientific, #26616 Ladder Petri dishes 60 mm Cellstar®, Greiner, #628160 Pipette tips 10 µl, 200 µl, 1000 µl Eppendorf, Hamburg Reaction tubes 0.5 ml, 1.5 ml, 2 ml Eppendorf, Hamburg Reaction tubes 15 ml Sarstedt, #62.554.001 Reaction tubes 50 ml Sarstedt, #62.547.254 Spectra™ Multicolor Broad Range Thermo Scientific, #26623 Protein Ladder Trans-Blot® Turbo™ Midi-size Bio-Rad, #BR20150917 Nitrocellulose Trans-Blot® Turbo™ Midi-size Bio-Rad, #BR20150705 Transfer Stacks Ultra-Clear™ Centrifuge Tubes Beckman, #344057
3.1.4 Universal chemical reagents
Substance Company Acrylamide SERVA Electrophoresis, #A3678-1006 Ampicillin sodium salt Roth, #K029.2 APS Sigma-Aldrich, # A3678 Bromphenol blue Sigma-Aldrich, # B0126-25G Bovine serum albumin Applichem, #A1391 DAPI Thermo Scientific™, USA DPBS, with Ca2+/Mg2+ PAA, # H15-001 DPBS, without Ca2+/Mg2+ GIBCO, # 14190 DTT Sigma, #D9779-5G EDTA Applichem, #131669.1209 EGTA Sigma, #E4378-10G Ethanol absolute Sigma-Aldrich, # 32205-2.5L Glycerol Sigma-Aldrich, # 15523-1L-R β-glycerolphosphate Applichem, #A2253,0100 Glycine Sigma-Aldrich, # 33226 HCl Sigma-Aldrich, #30721.1L HEPES Roth, #9105.4 Horse serum, heat inactivated Sigma, #H1138 Kanamycinsulfate Roth, #T832.2 Lennox L Agar Invitrogen, #22700-041 Lennox L BROTH Base Invitrogen, #12780-029 Methanol Sigma-Aldrich, # 32313-5L
MgCl2 Roth, #KK36.1 NaCl Sigma-Aldrich, # 31434-1KG-R
Page | 25 Material and Methods
NaDOC Merck, #6504 NaF Merck, #6449 NP40 Sigma, #13021 Paraformaldeyde Merck, # 1.04005.1000 Phosphatase Inhibitor Cocktail Roche, #04906837001 Tablets Phosphoric acid VWR, #20624.295 Protease Inhibitor Cocktail Tablets Roche, #04693132001 Polyethylenimine Sigma, #P-3143 SDS ultrapure Roth, # 2326.2 Serva Blue G Serva, #35050 Sodium orthovanadate Sigma, #S-6508 Sucrose Roth, #4621.1 TEMED Bio-Rad, #161-0801 Tris Sigma, # 93362 Triton-X-100 Roche, #10789704001 Tryptone Fluka, #T9410-250G Tween-20 Roth, # 2326.2 VectaMount™ AQ Vector Laboratories, # H-5501 Yeast extract Merk, #1.11926.100
3.1.5 Cell culture media and material
Substance Company B27 supplement Gibco, #17540-044 DNAse Invitrogen, #18047-019 DMEM Gibco, #41965-039 FBS Gibco, #10500 Glutamine Gibco, #25030-024 HBSS Gibco, #H15-010 Neurobasal medium (NB) Gibco, #21103-049 Penicillin-Streptomycin Gibco, #15140-122 Poly-L-Lysine Sigma-Aldrich, #P-0671 Trypsin Gibco, #15090-046
3.1.6 Viral particles
Viral particles Company LifeAct® lentiviral particles Ibidi, #60142
Page | 26 Material and Methods
3.1.7 Kits
Kit Company JetStar® 2.0 Plasmid Genomed, #210025 Pierce® ECL detection solution Thermo Scientific, #32106
3.1.8 Buffers
Blocking and permeabilization buffer 2 % Bovine serum albumin 1 % Horse serum 0.1 % Triton-X-100
10x Blotting buffer 25 mM Tris 192 mM Glycine 20 % Methanol
Bradford solution 0.01 % Serva Blue 8.5 % Phosphoric acid 4.75 % Ethanol in H2O
BSA blocking solution 5 % Bovine serum albumin 0.1 % Tween 20 in TBS
Buffer A 0.32 M Sucrose 5 mM HEPES, pH 7.4 Protease inhibitor cocktail (Roche) in H2O
Buffer B 0.32 M Sucrose 5 mM Tris, pH 8.1 Protease inhibitor cocktail (Roche) in H2O
Buffer C 0.32 M Sucrose
Page | 27 Material and Methods
12 mM Tris, pH 8.1 1 % Triton-X-100 Protease inhibitor cocktail (Roche) in H2O
Buffer 1 10 mM HEPES, pH 7.4 2 mM EDTA 5 mM Sodium orthovanadate 30 mM Sodium fluoride 20 mM β-glycerolphosphate Protease inhibitor cocktail (Roche) in H2O
Buffer 2 50 mM HEPES, pH 7.4 2 mM EDTA 2 mM EGTA 5 mM Sodium orthovanadate 30 mM Sodium fluoride 20 mM β-glycerolphosphate 1 % Triton-X-100 Protease inhibitor cocktail (Roche) in H2O
Buffer 3 50 mM Tris, pH 9 5 mM Sodium orthovanadate 30 mM Sodium fluoride 20 mM β-glycerolphosphate 1 % NaDOC Protease inhibitor cocktail (Roche) in H2O
Fixation solution 4 % Paraformaldehyde 4 % Sucrose 100 mM NaH2PO4•H2O 100 mM HNa2O4P•2H2O in H2O
LB plate + antibiotic 0.64 g LB Agar 1 mg Ampicillin / Kanamycin In 20 ml H2O
Page | 28 Material and Methods
LB medium + antibiotic 20 g LB BROTH Base 100 µg Ampicillin / Kanamycin In 1 L H2O
RIPA 1 M Tris, pH 8 5 M NaCl 10 % SDS 10 % NaDOC 100 mM Sodium orthovanadate 10 % NP40 Protease inhibitor cocktail (Roche)
10x Running buffer 250 mM Tris 1.92 M Glycine 1 % SDS
4x SDS loading buffer 200 mM Tris HCl, pH 6.8 200 mM DTT 4 % SDS 4 mM EDTA 40 % Glycerol 0.02 % Bromphenol blue (10 mg/ml)
SOB medium 20 M Peptone 5 M Yeast 0.5 M NaCl 2 M MgCl2
10x TBS 0.2 M Tris, pH 7.5 1 M NaCl
TBST 0.2 % 0.2 % Tween 20 in 1x TBS
Turbo blotting buffer 200 ml TransBlot®Turbo™ 5x Transfer Buffer 600 ml H2O 200 ml Ethanol
Page | 29 Material and Methods
3.1.9 Western blot gels
8 % 10 % 12 % Separation gel 2.3 ml 1.9 ml 1.6 ml Aqua bidest 1.3 ml 1.7 ml 2 ml 30 % acrylamide mix 1.3 ml 1.3 ml 1.3 ml 1.5 M Tris (pH 6.8) 0.05 ml 0.05 ml 0.05 ml 10 % SDS 0.05 ml 0.05 ml 0.05 ml 10 % APS 0.005 ml 0.005 ml 0.005 ml TEMED
5 % Stacking gel 0.68 ml Aqua bidest 0.17 ml 30 % acrylamide mix 0.13 ml 1.0 M Tris (pH 8.8) 0.01 ml 10 % SDS 0.01 ml 10 % APS 0.001 ml TEMED
3.1.10 Primary antibodies
Antibody Species Dilution Application Company β3-Tubulin Rabbit 1:250.000 WB Covance, #PRB-435P β-Actin Mouse 1:250.000 WB Sigma, #A5316 Bassoon Mouse 1:500 ICC Enzo Life Sciences, #SAP7F407 Homer1 Rabbit 1:20.000 WB Synaptic Systems, #160022 LAPSER Rabbit 1:500 ICC Self-made, Pineda, Berlin ProSAPiP1 Rabbit 1:1000 WB Self-made, Pineda, Berlin PSD95 Mouse 1:2000 WB Synaptic Systems, #124011 PSD95 Mouse 1:500 ICC Synaptic Systems, #124011 Shank3 Fr.1+2 Rabbit 1:2000 WB Self-made, Pineda, Berlin Shank3 Fr.1+2 Rabbit 1:500 ICC Self-made, Pineda, Berlin SPAR Rabbit 1:1000 WB Self-made, Pineda, Berlin SPAR Rabbit 1:500 ICC Self-made, Pineda, Berlin Synaptophysin Rabbit 1:20.000 WB Abcam, #ab14692 VGAT Rabbit 1:500 ICC Synaptic Systems, #131002 VGluT1 Rabbit 1:500 ICC Synaptic Systems, #135302
Page | 30 Material and Methods
3.1.11 Secondary antibodies
Antibody Species Dilution Application Company Anti-rabbit (HRP) Swine 1:1000 WB Dako, #P0399 Anti-mouse (HRP) Goat 1:3000 WB Dako, #P0260 Anti-goat (HRP) Rabbit 1:1000 WB Dako, #P0141 Anti-rabbit (568) Goat 1:750 ICC Invitrogen, #A-11011 Anti-mouse (568) Goat 1:750 ICC Invitrogen, #A-11004
3.1.12 DNA and shRNA constructs
DNA construct Backbone Reference / Company FUGW FUGW Neo GFP Addgene plasmid 14883 ProSAPiP1 FUGW Neo GFP (Reim et al., 2016) SPAR pEGFP (Richter et al., 2007) SPAR2 pEGFP (Spilker et al., 2008) SPAR3 pEGFP (Dolnik et al., 2016) Spax2 pSpax2 Addgene plasmid 12260 VsVg VsVg Addgene plasmid 14888
shRNA target sequence Backbone Reference construct ProSAPiP1- GCCTTCAAGCCTG FUGW (Reim et al., 2016) RNAi TTGTAC Neo GFP Scrambled GGTACGTGGCAA FUGW (Grabrucker et al., 2014) CTTCTTACAGGC Neo GFP
Page | 31 Material and Methods
3.2 Methods – Cell Culture
3.2.1 Plasmid preparation
To amplify DNA constructs, 1 µl of the DNA was added to 50 ml electrocompetent XL- 1 cells. Electroporation was subsequently performed in 800 µl SOB-Medium (20 M Peptone, 5 M Yeast, 0.5 M NaCl, 2 M MgCl2) and 1800 V and bacteria were put for 1h on the horizontal shaker at 37°C. After centrifugation at 4000 x g, the pellet was plated on LB-plates (0.64 g LB Agar in 20 ml H2O) containing the respective antibiotic (50 µg/mL) at 37°C overnight. The next day, colonies were picked and cultured in 4 ml LB- medium containing the respective antibiotic for 8 h on the horizontal shaker at 37°C. The grown culture was transferred to 100 ml LB-medium containing the respective antibiotic and was cultured on the horizontal shaker at 37°C overnight. The next day, plasmid preparation was performed according to manufacturers’ protocol (Genomed). The obtained DNA was collected in 50 µL preheated RNAse-free H2O (MilliQ) and the concentration was measured with a NanoDrop 2000 spectrophotometer.
3.2.2 HEK293T cells
HEK293T cells (DSMZ) were cultured in DMEM++ (DMEM, 10% FBS, penicillin/streptomycin at 100 U/ml, all Gibco) at 37 °C in 5% CO2 and were splitted every 3rd day by incubation with Trypsin (Gibco) for 2 min at 37°C and distribution to new flasks. Cells were kept in culture until they were required for DNA transfection.
3.2.3 Transfection of HEK293T cells
For DNA transfection into HEK293T cells, the cells were splitted 1:15 and plated on a petri dish (Cellstar, ø 10 cm). The next day, a mixture of 240 µl DMEM, 25 µl polyethylenimine and 4 µg of DNA was prepared. After 10 min of incubation, 800 µl DMEM (10% FBS) was added and the complete volume was carefully distributed on the petri dish. Cells were kept at 37°C in 5% CO2 for 24-48 h until a sufficient signal of the GFP-reporter was seen. HEK293T cells were washed in PBS (Gibco) and lysed in 2xSDS loading buffer (100 mM Tris HCl (pH 6.8), 100 mM DTT, 2% SDS, 2 mM EDTA, 20% Glycerol, 0.01% Bromphenol blue (5 mg/ml)) by scratching off the dish and boiling for 10 min to use for western blot analysis as described below.
Page | 32 Material and Methods
3.2.4 Transfection of HEK293T cells – Production of viral particles
For production of lentiviral particles for infecting hippocampal neurons, HEK293T cells were splitted 1:15 and plated on a petri dish (ø 10 cm). The next day, cells were transfected with 20 µg DNA (GFP-tagged constructs: Scrambled control (Scr), ProSAPiP1-RNAi (RNAi), FUGW empty vector (Vector) or FUGW containing full length ProSAPiP1 (GFP-ProSAPiP1)), 15 µg Spax2, 10 µg VsVg added to 70 µl polyethylenimine in 1 ml DMEM. After incubation of 10 min at room temperature, the medium on the cells was changed to DMEM and the transfection mixture was carefully added. The cells were incubated for 16-20 h at 37°C in 5% CO2 until the medium was changed to Neurobasal medium (NB) for suiting best to the neuronal cell medium on the target cells for viral infection. 48-56 h after starting the transfection, the medium was collected, filtered (0.45 mm) and stored in 0.5-1 ml aliquots at -80°C until use.
3.2.5 Primary hippocampal neurons
For immunofluorescence stainings, glass coverslips were put into each well of a 24- well plate (Falcon) and coated with Poly-L-Lysine (Sigma Aldrich, diluted in HBSS) for 30 min at 37°C. For protein biochemistry, petridishes were coated with Poly-L-Lysine likewise. Primary hippocampal neurons were prepared from rat embryos (Sprague Dawley, Janvier Labs, France) at E18/E19. The pregnant rat was anesthetized with slowly increasing concentrations of CO2 and decapitated. The fetuses were taken and their heads were separated. After opening the skull, the brains were collected and the hippocampi were carefully dissected at the microscope. All hippocampi were put in ice cold HBSS (Gibco). Subsequently, the dissected hippocampi were washed with HBSS three times on room temperature and incubated with 200 µl Trypsin (Gibco) for 20 min on 37°C to dissociate the cells. To stop the Trypsin reaction and to wash the dissociated cells, the medium was changed to DMEM+++ (DMEM, 10% FBS, 0.5 mM L-glutamine, penicillin/streptomycin at 100 U/ml, all Gibco). After two washing steps, 0.05% DNAse (Invitrogen) diluted in HBSS was added. Single cells were filtered (0.45 µm), counted and plated in DMEM+++ on petri dishes (Cellstar, ø 4 cm) or 24-well plates (Falcon, 30.000 cells per well). The cells were kept 2-3 h at 37°C to attach before the medium was changed to NB+++ (Neurobasal, 2% B27 supplement, 0.5 mM L- glutamine, penicillin/streptomycin at 100 U/ml, all Gibco). Cells were kept in culture until they were required, each week 100 µl of fresh NB+++ was added.
3.2.6 Viral infections
Primary hippocampal neurons were infected with lentiviruses, production see in Transfection of HEK293T cells - Production of viral particles, expressing the following GFP-tagged constructs: Scrambled control (Scr), ProSAPiP1-RNAi (RNAi), FUGW
Page | 33 Material and Methods empty vector (Vector) or FUGW containing full length ProSAPiP1 (GFP-ProSAPiP1). Infection was performed on DIV1 and neurons were cultured until required for either protein biochemistry or immunofluorescent staining on DIV14 or DIV28, respectively. The cultured hippocampal neurons, which were used for spine analysis, were additionally infected on DIV24 with RFP-tagged LifeAct® lentiviral particles (Ibidi), visualizing F-actin and thus visualizing dendritic spines, and kept in culture until fixation on DIV28 as described in immunofluorescent staining of primary hippocampal neurons.
3.2.7 Primary hippocampal neuron lysates
Primary hippocampal neurons were plated on petri dishes (Cellstar, ø 4 cm) in a density of 750.000-1.000.000 cells per dish. When the cultures reached the required age, they were washed twice with PBS (Gibco) and scraped off in 300 µl RIPA buffer (1 M Tris pH 8, 5 M NaCl, 10% SDS, 10% NaDOC, 100 mM Sodium orthovanadate, 10% NP40, protease inhibitor cocktail (Roche)). Cell lysates were placed for 1 h on the orbital shaker at 4°C. The lysate was stored at -80°C until used for western blot analysis as described below.
3.2.8 Immunofluorescent staining of primary hippocampal neurons
Cells on glass coverslips were washed twice in PBS (with Ca2+ and Mg2+, Gibco) and fixed in fixation solution (4 % paraformaldehyde, 4 % sucrose, 100 mM NaH2PO4•H2O, 100 mM HNa2O4P•2H2O) for 20 min at 37°C. After three washing steps with PBS (without Ca2+ and Mg2+, Gibco), cells were blocked and permeabilized in blocking and permeabilization buffer (2 % bovine serum albumin (BSA), 1 % horse serum and 0.1% Triton-X-100) for 1 h at room temperature and subsequently incubated with primary antibodies diluted in blocking and permeabilization buffer. For incubation, coverslips were put on a horizontal shaker at 4°C over night. For visualization, secondary antibodies coupled to Alexa Fluor® 568 (Life Technologies) were diluted in PBS (Gibco) and added on the coverslips for 1 h at room temperature after three washing steps with PBS (Gibco). After further three washing steps with PBS (Gibco) and one washing step with H2O (MilliQ) to remove salts, the coverslips were mounted over night in VectaMount (Vector labs) containing 4’,6-diamidino-2-phenylindole (DAPI, 1:50.000), protected from light. Images were acquired using an Axioskop 2 microscope and the Axiovision software (both from Zeiss). For analysing fluorescence intensities, all images were acquired with the same exposure time as their respective control. For analysing spine parameters, using RFP-tagged LifeAct (Ibidi), the ApoTome (Zeiss) was additionaly used for image acquisition.
Page | 34 Material and Methods
3.2.9 Image analysis
For quantification of signal number and intensity, the ImageJ software was used (http://imagej.nih.gov/ij/). Puncta were counted along three primary and three secondary dendrites for each cell, five cells per condition and three independent biological replicates, and the puncta density was calculated as puncta per dendrite length. Puncta intensity was measured likewise. Five puncta along the dendrites with no signal of the protein of interest were used to calculate the threshold for background values. To ensure that we measured synaptic puncta, we only included signals of the protein of interest which overlapped with the signals of a synaptic marker (Bassoon or VGluT- 1) and only if both signals, protein of interest and synaptic marker, exceeded the threshold for background values. Puncta intensity was calculated as relative puncta intensity normalized to the respective control. For the analysis of dendritic spines we initially deconvolved the images of the 568 channel, including only RFP signals (F-actin visualized by LifeAct), using the AutoQuant X software (MediaCybernetics). The deconvolved pictures were imported into the Imaris software (Bitplane) and the Filament Tracer software (Imaris, Bitplane) was used to design a reconstructed model of dendrites and spines, applying default settings. Spines were further reconstructed with the software and their density was calculated in Microsoft Excel as the number of reconstructed spines per dendrite length. Spine classification was subsequently determined with the Spine Classifier software (Imaris, Bitplane) with the following settings: Spines were classified into four categories by the following settings: “Mushroom” (spine length < 2 µm; spine mean width > 0,5 µm; spine neck length > 0,2 µm), “Thin” (spine length < 2 µm; spine mean width < 0,5 µm), “Stubby” (spine length < 2 µm; spine mean width > 0,5 µm; spine neck length < 0,2 µm) and “Filopodia” (spine length > 2 µm; spine mean width < 0,5 µm). The classification was further analysed with Microsoft Excel to calculate the percentage of the categories on the total amount of spines.
Page | 35 Material and Methods
3.3 Methods – Protein biochemistry
3.3.1 Subcellular fractionation – cell culture lysates
For subcellular fractionation of primary hippocampal neurons, cells were scratched off in phosphate-buffered saline (PBS) containing protease inhibitor cocktail (Roche), homogenized with a douncer (12 strokes at 900 rpm) and centrifuged at 12.000 x g for 15 min. The pellet containing the crude membrane fraction was resuspended in PBS containing protease inhibitor mix.
3.3.2 Subcellular fractionation – brain tissue
The analysed brain regions, hippocampus and striatum, were dissected from mice on C57BL/6 background with an age of 8-12 weeks. Mice were anesthetized with CO2 and decapitated. The brains were extracted, separated into the two hemispheres and immediately frozen with liquid nitrogen to be stored at -80°C until dissection. The hemispheres were slowly thawed and hippocampus and striatum, as the brain regions of interest, were carefully dissected and stored at -80°C. For each sample of PSD fractionation, the hippocampi or striata of five different mice were combined to have a sufficient amount of tissue. To avoid protein degradation, all steps were performed on ice or at 4°C and with buffers containing various protease inhibitors and a protease inhibitor cocktail (Roche). Homogenization of the tissue was performed with a Teflon douncer (used in Potter S, B. Braun Biotech International) and in buffer A (10ml/g of initial tissue, 0.32 M sucrose, 5 mM HEPES pH 7.4, protease inhibitor cocktail (Roche)) The tissue was homogenized with 12 strokes at 900 rpm. The obtained homogenate was centrifuged at 1.000 x g for 10 min to remove nuclei, extracellular matrix and cell debris (all included in pellet P1) from further procedure. To enhance the yield of the resulting subcellular fractions, pellet P1 was homogenized and centrifuged a second time with the same conditions to receive pellet P1’ and supernatant S1’. Supernatants (S1 and S1’) were combined and centrifuged at 12.000 x g for 20 min to separate microsomes and cytosol (both in S2) from the crude membrane fraction (pellet P2). To enhance the purity of the crude membrane fraction, pellet P2 was resuspended and centrifuged a second time with the same conditions. Pellet P2 was resuspended in buffer B (1.5 ml/g of initial tissue, 0.32 M sucrose, 5 mM Tris pH 8.1, protease inhibitor cocktail (Roche)) and loaded on a three-layered discontinuous sucrose density gradient (0.85 M / 1.0 M / 1.2 M), which was freshly generated on ice. After centrifugation at 85.000 x g for 120 min, three layers appeared in the sucrose density gradient. The myelin layer on top and the light membrane layer (intracellular membranes and microsomes, 0.85/1.0 sucrose interphase) were collected, frozen in liquid nitrogen and stored at -80°C. The purified synaptosomal
Page | 36 Material and Methods fraction was collected at the 1.0M/1.2M sucrose interphase, diluted 1:1 with buffer C (0.32 M sucrose, 12 mM Tris pH 8.1, 1% Triton-X-100, protease inhibitor cocktail (Roche)) and stirred for 15min at 4°C. Meanwhile, the mitochondria in the pellet below the sucrose gradient were collected, frozen in liquid nitrogen and stored in -80°C. The lysed synaptosomes were further centrifuged at 32.800 x g for 60 min to obtain the supernatant (S3) including the soluble synaptosomes and a pellet (P3) containing the PSD fraction, which was finally dissolved in H2O, frozen in liquid nitrogen and stored at -80°C until further use.
3.3.3 Subcellular fractionation – brain tissue, fast protocol
To perform subcellular fractionation with less material and in shorter time, the fast protocol of PSD fractionation was applied. PSDs of single brain regions of one animal can be obtained with this protocol, although purification is less thorough. The brain regions were dissected as described in the section above and tissue was homogenized with the Teflon douncer (used in Potter S, B. Braun Biotech International) in buffer 1 (10 mM HEPES pH 7.4, 2 mM EDTA, 5 mM Sodium orthovanadate, 30 mM Sodium fluoride, 20 mM β-glycerolphosphate, protease inhibitor cocktail (Roche)) with 12 strokes at 900 rpm. The homogenates were centrifuged at 500 x g for 5 min at 4°C to remove nuclei, extracellular matrix and cell debris (all included in pellet P1) from further procedure. Supernatant S1 was collected and centrifuged at 10.000 x g for 15 min at 4°C to separate the crude membrane fraction (P2) and the cytosol (S2). Pellet P2 was resuspended in 300-500 µl buffer 2 (50 mM HEPES pH 7.4, 2 mM EDTA, 2 mM EGTA, 5 mM Sodium orthovanadate, 30 mM Sodium fluoride, 20 mM β- glycerolphosphate, 1% Triton-X-100, protease inhibitor cocktail (Roche)) and centrifuged at 20.000 x g for 80 min at 4°C to obtain pellet P3 (Triton-X-100 insoluble PSD fraction) and supernatant S3 (Triton-X-100 soluble synaptic cytosol). Pellet P3 was resuspended in 50 µl buffer 3 (50 mM Tris pH 9, 5 mM Sodium orthovanadate, 30 mM Sodium fluoride, 20 mM β-glycerolphosphate, 1 % NaDOC, protease inhibitor cocktail (Roche)) and frozen in liquid nitrogen to be stored at -80°C.
3.3.4 Bradford assay
To determine the general protein concentration of samples, this assay was used. 20 µl of 150 mM NaCl were pipetted into a well of a 96-well plate (Cellstar®) and 2 µl of the respective sample were added. Finally, 200 µl of the Bradford solution (0.01 % Serva blue, 8.5 % phosphoric acid, 4.75 % ethanol in H2O) were added. All samples were prepared in duplicates. The signal intensity was measured with an ELISA reader (Labelsystems Multiscan, Thermo labsystems) and the protein concentration was calculated in Microsoft Excel by matching the signal intensity to a standard curve.
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3.3.5 Western blot analysis
To analyse protein levels in western blot analysis, the general protein concentration was determined by Bradford assay, as described above. Equal amounts of 8-10 µg total protein were filled up with water (MilliQ) to a total volume of 7.5 µl. 2.5 µl of 4x SDS loading buffer (200 mM Tris HCl pH 6.8, 200 mM DTT, 4 % SDS, 4 mM EDTA, 40 % Glycerol, 0.02 % Bromphenol blue (10 mg/ml)) were added and the samples were boiled at 95 °C for 10 min. Stacking gels and separating gels were freshly prepared and stored for maximum 1 week. The samples and protein ladder were loaded on the gels and an electric field of 120 V was applied. When the samples passed the stacking gel, the electric field was increased to 200-220 V until the required separation of proteins was obtained. After electrophoresis, the gel was transferred on a nitrocellulose membrane and wrapped by two whatman papers. For transferring the proteins from the gel onto the membrane, the unit was either enveloped by sponges, put into blot cassette and blotting chamber (filled up with blotting buffer) and the transfer was performed applying an electric field of 90 V for 90 min at 4°C, or the unit was put into Turbo blotting cassettes, moistened with Turbo blotting buffer and the transfer was performed applying the MIXED MW programme (25 V for 7 min). After the transfer, the membranes were blocked in BSA blocking solution (5 % Bovine serum albumin, 0.1 % Tween-20 in TBS) for 30-60 min on a horizontal shaker at room temperature and subsequently incubated with primary antibodies on a horizontal shaker at 4°C over night. After three washing steps with TBST 0.2 %, the membranes were further incubated with HRP-conjugated secondary antibodies on a horizontal shaker for 1 h at room temperature, followed by further three washing steps with TBST 0.2 %. The signals were finally visualized with ECL Western blotting substrate (Pierce) and the MicroChemi 4.2 machine. For signal quantification, the Gelanalyzer software (http://www.gelanalyzer.com) was used and the calculated values were normalized against the respective loading controls. After use, the membranes were washed three times in H2O, dried over night and stored in a folder for further use.
3.3.6 Mass-Spectrometry
PSD samples were sent on dry ice to the Johannes Gutenberg University Mainz, Mainz, Germany. Large-scale proteomic analysis was kindly performed by Ute Distler and Stefan Tenzer (Institute for Immunology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany) using the LC-MS (Liquid- Chromatography-Mass-Spectrometry) approach as previously described (Distler et al., 2014).
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3.3.7 Mass-Spectrometry data analysis
The data obtained from Mass-Spectrometry were processed, searching against the UniprotKB/Swissprot mouse database, and post-processed using the software package ISO-Quant (Distler et al., 2014). Both processing steps were kindly performed by Ute Distler and Stefan Tenzer (Institute for Immunology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany). Significant differences between the genotypes were determined, applying an unpaired two-tailed t-test, which was further and harshly corrected by the amount of identified proteins in the respective datasets. Pre-analysed datasets were sorted and all entries, which significantly differed between the genotypes, were further analysed with the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7 (https://david.ncifcrf.gov) (Huang da et al., 2009a; b). For evaluating the biological function and enrichment of biological terms/functions annotated with the entries, a functional annotation chart was constructed with the DAVID online tool using the gene ontology terms (GO-terms) ”cellular compartment”, “biological process” and “molecular function” as well as the KEGG-Pathway as annotation categories. For searching against known and predicted protein-protein interactions, the data was analysed with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database v10.0 (http://string-db.org) (Szklarczyk et al., 2015). Obtained protein-protein interactions were further visualized with the Gephi software v0.9.1 (https://gephi.org) (Bastian M., 2009).
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4 Results
4.1 Proteomic analysis of postsynaptic density fractions from Shank3 mutant mice reveals brain region specific changes relevant to autism spectrum disorder
4.1.1 Confirmation of successful PSD fractionation
Since Shank3 is a protein, which is highly enriched and of high functional relevance for the postsynaptic density (PSD) (Boeckers et al., 1999a), we performed subcellular fractionation of striatal and hippocampal tissue from wild type (WT) and Shank3∆11-/- mice (KO), to obtain the respective PSD samples. To reduce the required amount of tissue and time for performing the subcellular fractionation until the PSD fraction, we used a new protocol, extensively described in the Material and Methods section and discussed below. Each sample used for the PSD fractionation consists of striatal or hippocampal tissue of five mice being combined. The dissected tissue was combined and homogenized (Figure 2A). The lysates were centrifuged twice to remove nuclei, extracellular matrix and cell debris and to subsequently obtain the crude membrane fraction, removing the cytoplasm (Figure 2B). The crude membrane fraction was further loaded on a three-layered discontinuous sucrose gradient (Figure 2C) to separate myelin, light membranes and mitochondria from synaptosomes (Figure 2D) by applying ultracentrifugation. After treatment with Triton-X-100, the synaptosomes were additionally centrifuged to finally obtain a pellet containing the PSD fraction (Figure 2E) of the respective brain region. The generated PSD samples were subsequently analysed to evaluate the success of the new protocol. Western Blot analyses were performed to examine the distribution of the postsynaptic marker protein PSD95 within the obtained subcellular fractions. As we do not expect standard controls as β-Actin or β3-Tubulin to distribute equally among the different subcellular fractions, these proteins can not serve as general loading controls and we only applied Bradford assay to load 10µg of protein in each lane. However, as additional control, we also examined the distribution of presynaptic Synaptophysin on the exact same Western Blot membranes, which is expected to differ from the postsynaptic markers and should thus further exclude false loading of the
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Western Blot lanes. The measured signal intensities of PSD95 and Synaptophysin were normalized on their respective intensity in the homogenate.
Figure 2 | Scheme of the PSD fractionation protocol PSD fractionation was performed according to the illustrated protocol, showing exemplary pictures of the steps of homogenisation (A), obtaining the crude membrane fraction (B) the three-layered discontinuous sucrose gradient (C), the separation of myelin, light membranes, synaptosomes and mitochondria after ultracentrifugation (D) and the final pellet containing the PSD fraction (E). Below each of the picture a schematic illustration represents the respective content of the currently obtained subcellular fraction (A,B,D,E) or the desired area obtained in the next step as the purpose of preparing the three-layered discontinuous sucrose gradient (C).
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Both synaptic proteins are increased in the crude membrane fraction and the synaptosomal fraction. Postsynaptic PSD95 is highly increased in the PSD fraction, whereas presynaptic Synaptophysin is reduced in the same samples. Exemplary Western blot signals are shown in Figure 3. According to an enrichment of a postsynaptic protein and a depletion of a presynaptic protein, we conclude that the protocol modification will successfully provide PSD fractions, however, with a reduced amount of tissue and time required.
Figure 3 | Successful PSD fractionation Distribution of PSD95 (A) and Synaptophysin (B) in different cellular compartments (Homogenate (Ho), purified homogenate (S1), Crude membrane fraction (P2), Cytosol (S2), Synaptosomes (Syn), PSD and Synaptic cytosol (S3)) shows a successful PSD fractionation in both, wild type (WT, white) and Shank3Δ11-/- mutant (KO, red) samples. Single values (dots) and mean intensity (dashed line) are displayed. Exemplary Western blots for the respective proteins are shown below the diagrams. Data includes combined results of striatal and hippocampal tissue. No difference between the brain regions was observed (not shown).
4.1.2 Confirmation of the Shank3 KO genotype in homogenates and PSD fractions
In Shank3Δ11-/- mutant mice, exon 11 of the murine Shank3 gene is targeted. This deletion leads to a frameshift, which causes a translational stop and the loss of Shank3a, Shank3b and Shank3c. We therefore analysed the Shank3 isoform pattern in mouse brain tissue by performing Western Blot analysis. We compared the Shank3 signals between WT and Shank3Δ11-/- mutant mice, examining the signals in striatal
Page | 42 Results and hippocampal lysates of homogenates and PSD fractions. Exemplary blots are shown in Figure 4. A clearly different pattern of Shank3 isoforms in the homogenate can be seen in the KO lane in both of the brain regions analysed (Figure 4A). Equal amounts of total protein loaded on each lane are represented by the β-actin signals (Figure 4). Since the PSD fractions were obtained with the newly established protocol, we analysed the pattern of Shank3 isoforms in three independent WT and KO mutant samples, each of them containing the respective combined tissue of five mice. As in the homogenates, we clearly observed a different pattern of Shank3 isoforms in all of the KO lanes on the Western Blot. Equal amounts of total protein loaded on each lane are represented by the β-actin signals (Figure 4B)
Figure 4 | Verification of Shank3Δ11-/- mutant genotype in homogenates and PSD fractions Western blot analysis of striatal and hippocampal homogenates (A) and PSD fractions (B) confirms Shank3Δ11-/- mutant genotype, α- and β-isoforms of Shank3 are present in wild type (WT) but not in Shank3Δ11-/- mutant (KO) samples of the striatum and hippocampus. Equal amounts of total protein per lane are represented by the β-actin loading control. Representative Western Blots are shown.
4.1.3 Large-scale proteomic analysis comparing WT and Shank3 KO in mouse striatum and hippocampus using LC-MS
To evaluate differences between striatal or hippocampal WT and KO mouse PSDs in a large-scale and unbiased approach, we analysed the PSD fractions by mass- spectrometry-based proteomic analysis. For large-scale proteomic analysis, we generated PSD fractions from striatal and hippocampal tissue of both genotypes as described above (Figure 2 and Figure 3). The successful PSD fractionation of these samples was verified, showing an enrichment of postsynaptic Shank3 and PSD95 and reduced levels of presynaptic Synaptophysin in the PSD fractions of both, striatal and hippocampal samples of WT and KO mice. Furthermore, the KO genotype was clearly
Page | 43 Results visible comparing the Shank3 signal of the subcellular fractions of WT and KO samples in both, striatum and hippocampus. Hence, we proved a successful Shank3 KO and a proper PSD fractionation for all samples used in the large-scale proteomic analysis. Exemplary Western blots are shown in Figure 5A. Proteomic analysis was kindly performed by Ute Distler and Stefan Tenzer (Institute for Immunology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany) using the LC-MS (Liquid-Chromatography-Mass- Spectrometry) approach as previously described (Distler et al., 2014). The proteomic analysis identified 2463 proteins in the WT striatal and 2377 proteins in the WT hippocampal PSD, while 2461 and 2345 proteins were detected in the Shank3 KO striatal PSD or hippocampal PSD, respectively (Figure 5D). We further correlated the number of proteins with the corresponding concentration in the PSD fraction (ppm of total protein) to investigate the dynamic range of the detected PSD proteins and found comparable results for WT and Shank3 KO PSD fractions for both, striatum and hippocampus (Figure 5B). The measured protein levels of each of the identified proteins were compared between WT and Shank3 KO striatal and hippocampal PSD fractions. Statistical testing for significance was performed using unpaired two-tailed t-test with further correction and a sample size of n=5 biological replicates. Each sample consists of the respective tissue combined from five mice. Samples were measured in three technical replicates. After strict statistical testing, only a small number of proteins remained significantly different between WT and Shank3 KO in the striatal PSD fraction (61 proteins (2.47%), Figure 5D, Table 2) and in the hippocampal PSD fraction (55 proteins (2.34%), Figure 5D, Table 3) with more proteins being significantly reduced (Figure 5D). We further correlated the log2 ratio of KO/WT with the respective negative log10 p-value to visualize the extent of change and the corresponding significance for all identified proteins. Stronger alterations between WT and Shank3 KO are more distant from the vertical dashed baseline, which represents no change at all. Stronger significances of the alterations between WT and Shank3 KO are located higher in the diagram with the horizontal dashed baseline, which is labelled with ‘sign.’ and serving as the threshold for statistical significance (Figure 5C).
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Figure 5 | Large-scale proteomic analysis of wild type (WT) and Shank3Δ11-/- mutant (KO) striatal and hippocampal postsynaptic density (PSD) fraction Large-scale proteomic analysis: (A) Verification of proper PSD fractionation in samples used for proteomic analysis. Western Blot analysis of all obtained subcellular fractions: Homogenate (Ho), Purified homogenate 2 (S1), Crude membrane fraction (P2), Cytosol (S2), Synaptosomes (Syn), PSD and Synaptic cytosol (S3) in WT and KO samples. Enrichment of Shank3 and PSD95 and reduction of Synaptophysin (Syp) in the PSD fraction is shown in both brain regions. (B) Dynamic range of all detected PSD proteins: Correlation of the number of identified proteins with a distinct protein concentration (ppm of total protein) comparing WT (black) and KO (red) PSD of striatal (STR) and hippocampal (HIP) tissue. Numbers in diagram legends represent the total amount of proteins identified. (C) Visualization of all changes between wild type and Shank3Δ11-/- mutant (log2(KO/WT), x-axis) and the respective statistical significance (-log10(p-value), y-axis) of all identified proteins. Significantly changed proteins (above horizontal dashed line, “sign.”) are coloured (downregulated: blue and left of vertical dashed line; upregulated: orange and right of vertical dashed line). Changes that did not reach statistical significance, remained black. Statistical analysis was performed using unpaired two-tailed t- test with a correction by the number of total proteins identified and a sample size of n=5 independent biological replicates. (D) Information on total proteins identified and significant changes, omitting the remaining Shank3 protein (downregulated: blue; upregulated: orange) between WT and KO. Figure partially adapted from (Reim et al., 2017), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/.
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Table 2 | Significantly decreased (upper part) and increased (lower part) proteins in the striatal Shank3Δ11-/- mutant proteome. Table adapted from (Reim et al., 2017).
DESCRIPTION ACCESSION ENTRY P-VALUE LOG2 (퐊퐎) 퐊퐎 [%] 퐖퐓 퐖퐓 Dedicator of cytokinesis protein 3 OS=Mus musculus GN=Dock3 Q8CIQ7 DOCK3_MOUSE 1.0E-04 -1.44 36.88 PE=1 SV=1 SH3 and multiple ankyrin repeat domains protein 3 OS=Mus Q4ACU6 SHAN3_MOUSE 3.3E-20 -1.29 40.94 musculus GN=Shank3 PE=1 SV=2 Cytosolic carboxypeptidase 1 OS=Mus musculus GN=Agtpbp1 Q641K1 CBPC1_MOUSE 1.4E-02 -1.10 46.51 PE=1 SV=2 Casein kinase I isoform epsilon OS=Mus musculus GN=Csnk1e Q9JMK2 KC1E_MOUSE 5.3E-04 -0.98 50.57 PE=1 SV=2 Semaphorin-7A OS=Mus musculus Q9QUR8 SEM7A_MOUSE 3.1E-06 -0.93 52.54 GN=Sema7a PE=1 SV=1 Mucin-2 (Fragments) OS=Mus Q80Z19 MUC2_MOUSE 3.9E-07 -0.85 55.53 musculus GN=Muc2 PE=1 SV=2 Transgelin-3 OS=Mus musculus Q9R1Q8 TAGL3_MOUSE 1.5E-03 -0.83 56.12 GN=Tagln3 PE=1 SV=1 Tyrosine-protein phosphatase non- receptor type 23 OS=Mus musculus Q6PB44 PTN23_MOUSE 1.5E-02 -0.83 56.34 GN=Ptpn23 PE=1 SV=2 Ubiquitin carboxyl-terminal hydrolase CYLD OS=Mus musculus Q80TQ2 CYLD_MOUSE 1.5E-17 -0.74 59.89 GN=Cyld PE=1 SV=2 Phosphoglycerate kinase 2 OS=Mus P09041 PGK2_MOUSE 2.4E-02 -0.72 60.87 musculus GN=Pgk2 PE=1 SV=4 Homer protein homolog 1 OS=Mus Q9Z2Y3 HOME1_MOUSE 3.2E-09 -0.69 61.78 musculus GN=Homer1 PE=1 SV=2 Spermatogenesis-associated protein 2-like protein OS=Mus Q8BNN1 SPA2L_MOUSE 4.6E-11 -0.69 61.99 musculus GN=Spata2l PE=2 SV=1 Wiskott-Aldrich syndrome protein family member 3 OS=Mus musculus Q8VHI6 WASF3_MOUSE 4.3E-02 -0.67 62.78 GN=Wasf3 PE=2 SV=1 Inward rectifier potassium channel 2 OS=Mus musculus GN=Kcnj2 PE=1 P35561 IRK2_MOUSE 2.3E-03 -0.65 63.85 SV=1 Dual specificity protein phosphatase 3 OS=Mus musculus GN=Dusp3 Q9D7X3 DUS3_MOUSE 4.5E-02 -0.63 64.62 PE=1 SV=1 Citron Rho-interacting kinase OS=Mus musculus GN=Cit PE=1 P49025 CTRO_MOUSE 9.3E-09 -0.59 66.61 SV=3 Guanine nucleotide-binding protein G(i) subunit alpha-1 OS=Mus B2RSH2 GNAI1_MOUSE 5.5E-03 -0.58 66.92 musculus GN=Gnai1 PE=2 SV=1 Dedicator of cytokinesis protein 4 OS=Mus musculus GN=Dock4 P59764 DOCK4_MOUSE 7.8E-04 -0.57 67.24 PE=1 SV=1 Cadherin-6 OS=Mus musculus P97326 CADH6_MOUSE 1.9E-02 -0.53 69.04 GN=Cdh6 PE=1 SV=2 Inositol-trisphosphate 3-kinase A OS=Mus musculus GN=Itpka PE=2 Q8R071 IP3KA_MOUSE 5.5E-03 -0.52 69.73 SV=1 Nck-associated protein 1 OS=Mus P28660 NCKP1_MOUSE 3.8E-03 -0.51 70.05 musculus GN=Nckap1 PE=1 SV=2 Casein kinase II subunit alpha OS=Mus musculus GN=Csnk2a1 Q60737 CSK21_MOUSE 1.8E-02 -0.51 70.28 PE=1 SV=2 Disabled homolog 2-interacting protein OS=Mus musculus Q3UHC7 DAB2P_MOUSE 1.6E-10 -0.51 70.32 GN=Dab2ip PE=1 SV=1
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Cyclin-dependent kinase-like 5 OS=Mus musculus GN=Cdkl5 PE=2 Q3UTQ8 CDKL5_MOUSE 2.6E-03 -0.49 71.44 SV=1 Disks large-associated protein 3 OS=Mus musculus GN=Dlgap3 Q6PFD5 DLGP3_MOUSE 2.7E-08 -0.48 71.59 PE=1 SV=1 Glutamate receptor ionotropic, kainate 5 OS=Mus musculus Q61626 GRIK5_MOUSE 8.2E-03 -0.44 73.49 GN=Grik5 PE=2 SV=2 BTB/POZ domain-containing protein 17 OS=Mus musculus GN=Btbd17 Q9DB72 BTBDH_MOUSE 3.6E-03 -0.42 74.82 PE=2 SV=1 Brain-specific angiogenesis inhibitor 1-associated protein 2 OS=Mus Q8BKX1 BAIP2_MOUSE 1.8E-05 -0.42 74.95 musculus GN=Baiap2 PE=1 SV=2 Brain-enriched guanylate kinase- associated protein OS=Mus Q68EF6 BEGIN_MOUSE 7.2E-05 -0.39 76.28 musculus GN=Begain PE=1 SV=2 Rabphilin-3A OS=Mus musculus P47708 RP3A_MOUSE 1.3E-02 -0.35 78.34 GN=Rph3a PE=1 SV=2 Protein shisa-9 OS=Mus musculus Q9CZN4 SHSA9_MOUSE 8.0E-03 -0.34 78.85 GN=Shisa9 PE=1 SV=2 Disks large-associated protein 2 OS=Mus musculus GN=Dlgap2 Q8BJ42 DLGP2_MOUSE 6.8E-07 -0.34 78.91 PE=1 SV=2 Protein shisa-7 OS=Mus musculus Q8C3Q5 SHSA7_MOUSE 1.3E-03 -0.34 79.25 GN=Shisa7 PE=1 SV=3 Adherens junction-associated protein 1 OS=Mus musculus A2ALI5 AJAP1_MOUSE 1.3E-02 -0.33 79.37 GN=Ajap1 PE=2 SV=1 PH and SEC7 domain-containing protein 1 OS=Mus musculus Q5DTT2 PSD1_MOUSE 1.5E-02 -0.33 79.59 GN=Psd PE=1 SV=2 Proline-rich transmembrane protein 1 OS=Mus musculus GN=Prrt1 O35449 PRRT1_MOUSE 6.6E-05 -0.33 79.60 PE=1 SV=1 Glutamate receptor ionotropic, NMDA 2B OS=Mus musculus Q01097 NMDE2_MOUSE 7.0E-07 -0.32 79.89 GN=Grin2b PE=1 SV=3 Voltage-dependent calcium channel gamma-8 subunit OS=Mus Q8VHW2 CCG8_MOUSE 2.3E-02 -0.31 80.82 musculus GN=Cacng8 PE=1 SV=1 Guanine nucleotide-binding protein G(s) subunit alpha isoforms XLas Q6R0H7 GNAS1_MOUSE 4.9E-02 -0.30 81.41 OS=Mus musculus GN=Gnas PE=2 SV=1 Glutamate receptor 1 OS=Mus P23818 GRIA1_MOUSE 1.6E-02 -0.29 81.82 musculus GN=Gria1 PE=1 SV=1 Leucine-rich repeat transmembrane neuronal protein 4 OS=Mus Q80XG9 LRRT4_MOUSE 3.4E-03 -0.29 81.86 musculus GN=Lrrtm4 PE=1 SV=2 Cysteine-rich protein 2 OS=Mus Q9DCT8 CRIP2_MOUSE 1.8E-02 -0.29 81.87 musculus GN=Crip2 PE=1 SV=1 Glutamate receptor ionotropic, NMDA 1 OS=Mus musculus P35438 NMDZ1_MOUSE 2.2E-02 -0.26 83.45 GN=Grin1 PE=1 SV=1 Actin-related protein 2 OS=Mus P61161 ARP2_MOUSE 4.6E-02 -0.25 84.04 musculus GN=Actr2 PE=1 SV=1 BTB/POZ domain-containing protein KCTD16 OS=Mus musculus Q5DTY9 KCD16_MOUSE 2.1E-02 -0.25 84.37 GN=Kctd16 PE=1 SV=2 Triple functional domain protein OS= Mus musculus GN=Trio PE=1 Q0KL02 TRIO_MOUSE 2.6E-02 -0.24 84.50 SV=3 Glutamate receptor 2 OS=Mus P23819 GRIA2_MOUSE 1.5E-03 -0.24 84.52 musculus GN=Gria2 PE=1 SV=3
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Calcium-activated potassium channel subunit alpha-1 OS=Mus Q08460 KCMA1_MOUSE 1.2E-02 -0.24 84.96 musculus GN=Kcnma1 PE=1 SV=2 Leucine-rich repeat-containing protein 7 OS=Mus musculus Q80TE7 LRRC7_MOUSE 4.3E-02 -0.13 91.36 GN=Lrrc7 PE=1 SV=2
DESCRIPTION ACCESSION ENTRY P-VALUE LOG2 (퐊퐎) 퐊퐎 [%] 퐖퐓 퐖퐓 60S ribosomal protein L36a OS=Mus musculus GN=Rpl36a P83882 RL36A_MOUSE 1.8E-02 0.24 118.01 PE=3 SV=2 60S ribosomal protein L19 OS=Mus P84099 RL19_MOUSE 1.1E-03 0.24 118.11 musculus GN=Rpl19 PE=1 SV=1 60S ribosomal protein L36 OS=Mus P47964 RL36_MOUSE 1.9E-03 0.26 119.34 musculus GN=Rpl36 PE=2 SV=2 Contactin-2 OS=Mus musculus Q61330 CNTN2_MOUSE 4.5E-02 0.27 120.40 GN=Cntn2 PE=1 SV=2 60S ribosomal protein L5 OS=Mus P47962 RL5_MOUSE 2.6E-02 0.31 123.56 musculus GN=Rpl5 PE=1 SV=3 60S ribosomal protein L7a OS=Mus P12970 RL7A_MOUSE 4.6E-04 0.32 124.46 musculus GN=Rpl7a PE=2 SV=2 Kinectin OS=Mus musculus Q61595 KTN1_MOUSE 3.7E-02 0.35 127.69 GN=Ktn1 PE=2 SV=1 40S ribosomal protein S4, X isoform OS=Mus musculus GN=Rps4x P62702 RS4X_MOUSE 3.3E-02 0.36 127.99 PE=2 SV=2 Integral membrane protein 2B OS=Mus musculus GN=Itm2b PE=2 O89051 ITM2B_MOUSE 2.5E-02 0.39 130.80 SV=1 Plasminogen activator inhibitor 1 RNA-binding protein OS=Mus Q9CY58 PAIRB_MOUSE 7.6E-04 0.39 130.88 musculus GN=Serbp1 PE=1 SV=2 Cadherin-4 OS=Mus musculus P39038 CADH4_MOUSE 2.0E-02 0.39 131.14 GN=Cdh4 PE=2 SV=1 Annexin A2 OS=Mus musculus P07356 ANXA2_MOUSE 3.7E-02 0.47 138.57 GN=Anxa2 PE=1 SV=2 Myelin expression factor 2 OS=Mus Q8C854 MYEF2_MOUSE 4.9E-02 0.62 153.82 musculus GN=Myef2 PE=1 SV=1 E3 ubiquitin-protein ligase TTC3 OS=Mus musculus GN=Ttc3 PE=2 O88196 TTC3_MOUSE 4.8E-03 0.65 157.39 SV=2
Table 3 | Significantly decreased (upper part) and increased (lower part) proteins in the hippocampal Shank3Δ11-/- mutant proteome. Table adapted from (Reim et al., 2017).
DESCRIPTION ACCESSION ENTRY P-VALUE LOG2 (퐊퐎) 퐊퐎 [%] 퐖퐓 퐖퐓 FERM, RhoGEF and pleckstrin domain-containing protein 2 Q91VS8 FARP2_MOUSE 9.7E-08 -3.23 10.63 OS=Mus musculus GN=Farp2 PE=1 SV=2 SH3 and multiple ankyrin repeat domains protein 3 OS=Mus Q4ACU6 SHAN3_MOUSE 6.7E-15 -2.05 24.10 musculus GN=Shank3 PE=1 SV=2 Keratin, type II cytoskeletal 6B OS=Mus musculus GN=Krt6b PE=2 Q9Z331 K2C6B_MOUSE 4.3E-02 -1.61 32.84 SV=3 Dedicator of cytokinesis protein 3 OS=Mus musculus GN=Dock3 Q8CIQ7 DOCK3_MOUSE 1.5E-15 -1.21 43.13 PE=1 SV=1 Calmodulin OS=Mus musculus P62204 CALM_MOUSE 1.8E-02 -0.78 58.29 GN=Calm1 PE=1 SV=2 Homer protein homolog 3 OS=Mus Q99JP6 HOME3_MOUSE 6.5E-09 -0.66 63.10 musculus GN=Homer3 PE=1 SV=2
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cTAGE family member 5 OS=Mus Q8R311 CTGE5_MOUSE 9.8E-03 -0.59 66.50 musculus GN=Ctage5 PE=1 SV=1 40S ribosomal protein SA OS=Mus P14206 RSSA_MOUSE 4.4E-03 -0.57 67.45 musculus GN=Rpsa PE=1 SV=4 GRIP1-associated protein 1 OS=Mus musculus GN=Gripap1 Q8VD04 GRAP1_MOUSE 6.2E-04 -0.53 69.32 PE=1 SV=1 DnaJ homolog subfamily A member 4 OS=Mus musculus GN=Dnaja4 Q9JMC3 DNJA4_MOUSE 1.7E-05 -0.51 70.03 PE=2 SV=1 Peroxiredoxin-2 OS=Mus musculus Q61171 PRDX2_MOUSE 6.2E-03 -0.50 70.64 GN=Prdx2 PE=1 SV=3 cAMP-dependent protein kinase type II-alpha regulatory subunit P12367 KAP2_MOUSE 2.5E-02 -0.47 72.08 OS=Mus musculus GN=Prkar2a PE=1 SV=2 Tubulin beta-2B chain OS=Mus Q9CWF2 TBB2B_MOUSE 7.1E-03 -0.43 74.04 musculus GN=Tubb2b PE=1 SV=1 Ubiquitin carboxyl-terminal hydrolase CYLD OS=Mus musculus Q80TQ2 CYLD_MOUSE 5.8E-07 -0.42 74.53 GN=Cyld PE=1 SV=2 Spermatogenesis-associated protein 2-like protein OS=Mus Q8BNN1 SPA2L_MOUSE 1.5E-07 -0.42 74.68 musculus GN=Spata2l PE=2 SV=1 Microtubule-associated protein RP/EB family member 2 OS=Mus Q8R001 MARE2_MOUSE 4.9E-02 -0.42 74.69 musculus GN=Mapre2 PE=1 SV=1 Adenylate kinase isoenzyme 5 OS=Mus musculus GN=Ak5 PE=2 Q920P5 KAD5_MOUSE 3.2E-04 -0.42 74.81 SV=2 Actin, alpha skeletal muscle OS=Mus musculus GN=Acta1 PE=1 P68134 ACTS_MOUSE 3.7E-04 -0.41 75.28 SV=1 Homer protein homolog 1 OS=Mus Q9Z2Y3 HOME1_MOUSE 1.2E-04 -0.40 75.72 musculus GN=Homer1 PE=1 SV=2 Copine-7 OS=Mus musculus Q0VE82 CPNE7_MOUSE 7.6E-04 -0.40 75.81 GN=Cpne7 PE=2 SV=1 Gelsolin OS=Mus musculus P13020 GELS_MOUSE 5.0E-02 -0.40 75.84 GN=Gsn PE=1 SV=3 Protein kinase C and casein kinase substrate in neurons protein 1 Q61644 PACN1_MOUSE 1.2E-02 -0.40 75.89 OS=Mus musculus GN=Pacsin1 PE=1 SV=1 Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-2 P62880 GBB2_MOUSE 3.4E-03 -0.40 76.04 OS=Mus musculus GN=Gnb2 PE=1 SV=3 14-3-3 protein epsilon OS=Mus P62259 1433E_MOUSE 6.8E-03 -0.39 76.56 musculus GN=Ywhae PE=1 SV=1 Dihydropyrimidinase-related protein 3 OS=Mus musculus GN=Dpysl3 Q62188 DPYL3_MOUSE 3.4E-02 -0.38 77.00 PE=1 SV=1 Profilin-2 OS=Mus musculus Q9JJV2 PROF2_MOUSE 9.8E-03 -0.37 77.25 GN=Pfn2 PE=1 SV=3 Inositol-trisphosphate 3-kinase A OS=Mus musculus GN=Itpka PE=2 Q8R071 IP3KA_MOUSE 2.6E-02 -0.37 77.43 SV=1 14-3-3 protein gamma OS=Mus P61982 1433G_MOUSE 2.1E-04 -0.36 78.17 musculus GN=Ywhag PE=1 SV=2 14-3-3 protein eta OS=Mus P68510 1433F_MOUSE 2.5E-02 -0.32 80.05 musculus GN=Ywhah PE=1 SV=2 T-complex protein 1 subunit zeta OS=Mus musculus GN=Cct6a PE=1 P80317 TCPZ_MOUSE 2.7E-02 -0.31 80.71 SV=3 Copine-6 OS=Mus musculus Q9Z140 CPNE6_MOUSE 3.5E-03 -0.31 80.86 GN=Cpne6 PE=2 SV=1
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Coronin-1C OS=Mus musculus Q9WUM4 COR1C_MOUSE 3.9E-03 -0.30 81.33 GN=Coro1c PE=1 SV=2 V-type proton ATPase subunit E 1 OS=Mus musculus GN=Atp6v1e1 P50518 VATE1_MOUSE 9.4E-04 -0.29 81.51 PE=1 SV=2 MAGUK p55 subfamily member 2 OS=Mus musculus GN=Mpp2 PE=1 Q9WV34 MPP2_MOUSE 1.7E-03 -0.29 81.86 SV=1 Growth arrest-specific protein 7 OS=Mus musculus GN=Gas7 PE=1 Q60780 GAS7_MOUSE 4.5E-02 -0.29 82.07 SV=1 Abl interactor 1 OS=Mus musculus Q8CBW3 ABI1_MOUSE 5.1E-03 -0.27 82.79 GN=Abi1 PE=1 SV=3 Tubulin beta-2A chain OS=Mus Q7TMM9 TBB2A_MOUSE 4.1E-02 -0.27 83.07 musculus GN=Tubb2a PE=1 SV=1 Synapsin-3 OS=Mus musculus Q8JZP2 SYN3_MOUSE 8.6E-03 -0.26 83.44 GN=Syn3 PE=1 SV=2 F-actin-capping protein subunit beta OS=Mus musculus GN=Capzb P47757 CAPZB_MOUSE 1.5E-05 -0.23 85.22 PE=1 SV=3
DESCRIPTION ACCESSION ENTRY P-VALUE LOG2 (퐊퐎) 퐊퐎 [%] 퐖퐓 퐖퐓 60S ribosomal protein L27a OS=Mus musculus GN=Rpl27a P14115 RL27A_MOUSE 3.0E-03 0.24 118.03 PE=2 SV=5 Calmin OS=Mus musculus Q8C5W0 CLMN_MOUSE 1.6E-02 0.25 119.16 GN=Clmn PE=1 SV=2 Voltage-dependent N-type calcium channel subunit alpha-1B OS=Mus O55017 CAC1B_MOUSE 4.0E-02 0.27 120.55 musculus GN=Cacna1b PE=1 SV=1 Cytochrome b-c1 complex subunit 2, mitochondrial OS=Mus musculus Q9DB77 QCR2_MOUSE 1.4E-02 0.28 121.27 GN=Uqcrc2 PE=1 SV=1 Apoptosis-inducing factor 1, mitochondrial OS=Mus musculus Q9Z0X1 AIFM1_MOUSE 4.0E-02 0.30 123.22 GN=Aifm1 PE=1 SV=1 ATP synthase F(0) complex subunit B1, mitochondrial OS=Mus Q9CQQ7 AT5F1_MOUSE 7.8E-05 0.31 124.10 musculus GN=Atp5f1 PE=1 SV=1 Neuroligin-2 OS=Mus musculus Q69ZK9 NLGN2_MOUSE 1.3E-02 0.36 128.00 GN=Nlgn2 PE=1 SV=2 TNF receptor-associated factor 3 OS=Mus musculus GN=Traf3 PE=1 Q60803 TRAF3_MOUSE 1.3E-02 0.38 129.93 SV=2 Tyrosine-protein kinase Fer OS= P70451 FER_MOUSE 2.1E-02 0.38 130.55 Mus musculus GN=Fer PE=1 SV=2 Thyrotropin-releasing hormone- degrading ectoenzyme OS=Mus Q8K093 TRHDE_MOUSE 6.2E-04 0.40 131.96 musculus GN=Trhde PE=2 SV=1 Phenylalanine--tRNA ligase alpha subunit OS=Mus musculus Q8C0C7 SYFA_MOUSE 1.5E-02 0.41 133.14 GN=Farsa PE=2 SV=1 AFG3-like protein 2 OS=Mus Q8JZQ2 AFG32_MOUSE 6.4E-07 0.44 136.02 musculus GN=Afg3l2 PE=1 SV=1 Succinate-semialdehyde dehy- drogenase, mitochondrial OS=Mus Q8BWF0 SSDH_MOUSE 2.0E-02 0.52 143.51 musculus GN=Aldh5a1 PE=1 SV=1 Dynactin subunit 1 OS=Mus O08788 DCTN1_MOUSE 2.7E-07 0.56 147.87 musculus GN=Dctn1 PE=1 SV=3 Peripherin OS=Mus musculus P15331 PERI_MOUSE 7.4E-03 0.85 179.90 GN=Prph PE=1 SV=2 MHC class II transactivator OS=Mus P79621 C2TA_MOUSE 1.3E-06 0.89 185.88 musculus GN=Ciita PE=2 SV=2 Pre-mRNA-processing factor 40 homolog B OS=Mus musculus Q80W14 PR40B_MOUSE 4.2E-04 1.05 207.19 GN=Prpf40b PE=2 SV=2
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4.1.4 Significant enrichment of gene ontology (GO) terms and KEGG pathways among the significantly altered proteins in the striatal and hippocampal WT and Shank3 KO PSD
After identifying several significantly altered proteins in the striatal and hippocampal Shank3 KO PSD, we further analysed these subsets of proteins. For evaluating the biological function and an enrichment of biological terms and functions, which are annotated with these proteins, we constructed a functional annotation chart with the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7 (https://david.ncifcrf.gov) (Huang da et al., 2009a; b), providing statistically enriched annotations. We therefore analysed the gene ontology (GO, http://geneontology.org/) terms within the categories ‘cellular compartment’, ‘biological process’ and ‘molecular function’ as well as pathways identified by the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database (http://www.genome.jp/kegg/pathway.html). Among the 61 significantly altered proteins in the striatal Shank3 KO PSD, we found a significant enrichment of 36 GO terms for the category ‘cellular compartment’, 31 GO terms for the category ‘biological process’, and 27 GO terms for the category ‘molecular function’, while 6 pathways were identified by the KEGG Pathway Database (Table 4). Among the 55 significantly altered proteins in the hippocampal Shank3Δ11-/- mutant PSD, we observed a significant enrichment of 17 GO terms for the category ‘cellular compartment’, 28 GO terms for the category ‘biological process’, and 12 GO terms for the category ‘molecular function’. Additionally, two pathways were identified by the KEGG Pathway Database (Table 5). Interestingly, the GO term analysis revealed different results between striatum and hippocampus. Within the striatal subset, the top five of all enriched annotations for the categories ‘cellular compartment’ (Figure 6A),‘biological process’ and ‘molecular function’ (Figure 6B) mainly suggest disturbances in glutamate receptor activity and cell-cell signalling at the striatal PSDs, which is further supported by the significantly enriched KEGG pathways, including the pathways ‘Long-term potentiation’, ‘Neuroactive ligand-receptor interaction’, ‘Long-term depression’ and ‘Adherens junction’ (Table 4). These data suggest that the changes observed by large-scale proteomic analysis in the striatum of Shank3 KO mice imply a disturbance of signal transmission and postsynaptic function of striatal synapses.
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Within the hippocampal subset of significantly altered proteins, the top five of all enriched annotations for the categories ‘cellular compartment’ (Figure 6C), ‘biological process’ and ‘molecular function’ (Figure 6D) mainly include annotations associated with correct functionality of the cytoskeleton such as (actin) cytoskeleton binding and organization or protein polymerization. Therefore, these data imply a critical affection of the proper organisation of the cytoskeleton. However, the analysis of KEGG pathways did not include an enriched pathway associated with the cytoskeletal organization or function (Table 5).
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Figure 6 | Gene ontology analysis of significantly altered proteins in the Shank3Δ11-/- mutant PSD from striatum and hippocampus. Functional annotation of proteins with significantly altered expression levels in the striatal (A, B) and hippocampal (C, D) Shank3Δ11-/- mutant PSDs was performed using DAVID (v6.7, https://david.ncifcrf.gov). Bar diagrams visualize the top five significantly enriched GO terms for ‘cellular compartment’ for molecular alterations in the striatal (A) or hippocampal (C) PSD. The top five significantly enriched GO terms for ‘biological process’ and ‘molecular function’ for molecular alterations in the striatal (B) or hippocampal (D) PSD are listed in table-like diagrams. Figure partially adapted from (Reim et al., 2017), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/.
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Table 4 | GO term enrichment in significantly altered proteins of the striatal Shank3Δ11-/- mutant PSD. Statistical enrichment was assessed with the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7 (https://david.ncifcrf.gov). Table adapted from (Reim et al., 2017).
Category Term Count % p-value cellular compartment postsynaptic density 8 13,3 5,8E-10 cellular compartment postsynaptic membrane 10 16,7 6,5E-10 cellular compartment synapse part 11 18,3 3,8E-9 cellular compartment ionotropic glutamate receptor complex 5 8,3 1,6E-7 cellular compartment synapse 11 18,3 1,8E-7 cellular compartment cell junction 12 20,0 7,6E-7 intracellular non-membrane-bounded cellular compartment 21 35,0 4,7E-6 organelle cellular compartment non-membrane-bounded organelle 21 35,0 4,7E-6 cellular compartment cell projection 12 20,0 5,4E-6 cellular compartment plasma membrane part 18 30,0 3,6E-5 cellular compartment cell fraction 11 18,3 4,8E-5 cellular compartment ribosome 7 11,7 6,8E-5 cellular compartment membrane fraction 10 16,7 8,3E-5 cellular compartment insoluble fraction 10 16,7 1,1E-4 cellular compartment presynaptic membrane 4 6,7 1,4E-4 cellular compartment receptor complex 5 8,3 2,4E-4 cellular compartment cytoskeleton 13 21,7 5,6E-4 cellular compartment plasma membrane 22 36,7 6,7E-4 cellular compartment neuron projection 6 10,0 2,0E-3 cellular compartment synaptic vesicle 4 6,7 2,0E-3 cellular compartment integral to plasma membrane 8 13,3 3,0E-3 cellular compartment intrinsic to plasma membrane 8 13,3 3,8E-3 cellular compartment clathrin-coated vesicle 4 6,7 6,5E-3 cellular compartment ribonucleoprotein complex 7 11,7 6,6E-3 cellular compartment cytoskeletal part 9 15,0 6,7E-3 cellular compartment extrinsic to membrane 7 11,7 7,3E-3 cellular compartment cell leading edge 4 6,7 8,0E-3 cellular compartment coated vesicle 4 6,7 1,1E-2 cellular compartment ruffle 3 5,0 1,3E-2 alpha-amino-3-hydroxy-5-methyl-4- cellular compartment isoxazolepropionic acid selective 2 3,3 1,5E-2 glutamate receptor complex cellular compartment cytoplasmic membrane-bounded vesicle 6 10,0 1,7E-2 cellular compartment membrane-bounded vesicle 6 10,0 1,8E-2 N-methyl-D-aspartate selective glutamate cellular compartment 2 3,3 2,2E-2 receptor complex cellular compartment perinuclear region of cytoplasm 4 6,7 3,2E-2 cellular compartment cytoplasmic vesicle 6 10,0 3,8E-2 cellular compartment vesicle 6 10,0 4,1E-2
Category Term Count % p-value biological process cell-cell signaling 9 15,0 7,0E-6 biological process synaptic transmission 7 11,7 3,6E-5
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biological process transmission of nerve impulse 7 11,7 1,4E-4 biological process neuromuscular process 4 6,7 1,2E-3 regulation of excitatory postsynaptic biological process 3 5,0 2,2E-3 membrane potential biological process ion transport 9 15,0 3,2E-3 regulation of postsynaptic membrane biological process 3 5,0 3,5E-3 potential biological process receptor metabolic process 3 5,0 3,8E-3 biological process memory 3 5,0 4,7E-3 biological process translation 6 10,0 5,2E-3 biological process regulation of synaptic transmission 4 6,7 5,3E-3 biological process regulation of system process 5 8,3 5,4E-3 regulation of transmission of nerve biological process 4 6,7 6,3E-3 impulse biological process membrane depolarization 3 5,0 7,1E-3 biological process regulation of neurological system process 4 6,7 7,4E-3 biological process regulation of membrane potential 4 6,7 8,5E-3 regulation of neuron projection biological process 3 5,0 1,2E-2 development regulation of cell morphogenesis involved biological process 3 5,0 1,3E-2 in differentiation biological process regulation of cell projection organization 3 5,0 1,7E-2 biological process receptor internalization 2 3,3 1,8E-2 biological process metal ion transport 6 10,0 1,9E-2 biological process regulation of dendrite morphogenesis 2 3,3 2,4E-2 biological process regulation of dendrite development 2 3,3 2,8E-2 biological process long-term memory 2 3,3 2,8E-2 biological process phosphorus metabolic process 8 13,3 3,1E-2 biological process phosphate metabolic process 8 13,3 3,1E-2 biological process suckling behavior 2 3,3 3,1E-2 biological process cation transport 6 10,0 3,4E-2 biological process learning or memory 3 5,0 3,9E-2 biological process glutamate signaling pathway 2 3,3 4,5E-2 biological process regulation of cell morphogenesis 3 5,0 4,6E-2
Category Term Count % p-value molecular function ionotropic glutamate receptor activity 5 8,3 3,1E-7 extracellular-glutamate-gated ion channel molecular function 5 8,3 3,1E-7 activity molecular function gated channel activity 9 15,0 3,3E-6 molecular function glutamate receptor activity 5 8,3 7,1E-6 molecular function ion channel activity 9 15,0 1,6E-5 molecular function substrate specific channel activity 9 15,0 2,0E-5 molecular function channel activity 9 15,0 2,2E-5 passive transmembrane transporter molecular function 9 15,0 2,2E-5 activity molecular function ligand-gated channel activity 6 10,0 2,5E-5 molecular function ligand-gated ion channel activity 6 10,0 2,5E-5 extracellular ligand-gated ion channel molecular function 5 8,3 6,5E-5 activity
Page | 55 Results molecular function SH3 domain binding 5 8,3 1,3E-4 molecular function structural constituent of ribosome 6 10,0 1,3E-4 molecular function protein domain specific binding 6 10,0 4,1E-4 molecular function GTPase regulator activity 7 11,7 1,1E-3 nucleoside-triphosphatase regulator molecular function 7 11,7 1,2E-3 activity molecular function cation channel activity 6 10,0 1,3E-3 metal ion transmembrane transporter molecular function 6 10,0 2,6E-3 activity molecular function cytoskeletal protein binding 6 10,0 1,1E-2 molecular function guanyl-nucleotide exchange factor activity 4 6,7 1,3E-2 molecular function structural molecule activity 6 10,0 1,6E-2 molecular function voltage-gated channel activity 4 6,7 2,1E-2 molecular function voltage-gated ion channel activity 4 6,7 2,1E-2 molecular function calcium channel activity 3 5,0 2,1E-2 molecular function small GTPase regulator activity 4 6,7 3,7E-2 molecular function voltage-gated potassium channel activity 3 5,0 4,2E-2 molecular function nucleotide binding 13 21,7 4,7E-2
Category Term Count % p-value KEGG pathway Ribosome 6 10,0 4,1E-5 KEGG pathway Amyotrophic lateral sclerosis (ALS) 4 6,7 2,1E-3 KEGG pathway Long-term potentiation 4 6,7 3,7E-3 KEGG pathway Neuroactive ligand-receptor interaction 5 8,3 2,8E-2 KEGG pathway Long-term depression 3 5,0 4,2E-2 KEGG pathway Adherens junction 3 5,0 4,6E-2
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Table 5 | GO term enrichment in significantly altered proteins of the hippocampal Shank3Δ11-/- mutant proteome. Statistical enrichment was assessed with the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7 (https://david.ncifcrf.gov). Table adapted from (Reim et al., 2017).
Category Term Count % p-value cellular compartment cytoskeleton 18 32,1 9,3E-8 cellular compartment non-membrane-bounded organelle 21 37,5 2,0E-6 intracellular non-membrane-bounded cellular compartment 21 37,5 2,0E-6 organelle cellular compartment cytoskeletal part 13 23,2 9,7E-6 cellular compartment cell leading edge 5 8,9 6,3E-4 cellular compartment cell projection 8 14,3 3,6E-3 cellular compartment synapse 6 10,7 5,0E-3 cellular compartment neuron projection 5 8,9 1,1E-2 cellular compartment postsynaptic density 3 5,4 1,4E-2 cellular compartment lamellipodium 3 5,4 2,1E-2 cellular compartment cell junction 6 10,7 2,4E-2 cellular compartment sarcomere 3 5,4 3,2E-2 cellular compartment actin cytoskeleton 4 7,1 3,5E-2 cellular compartment contractile fiber part 3 5,4 3,7E-2 cellular compartment synapse part 4 7,1 3,8E-2 cellular compartment myofibril 3 5,4 4,1E-2 cellular compartment contractile fiber 3 5,4 4,4E-2
Category Term Count % p-value biological process cytoskeleton organization 9 16,1 1,0E-5 biological process actin cytoskeleton organization 6 10,7 2,1E-4 biological process actin filament-based process 6 10,7 2,8E-4 biological process protein polymerization 4 7,1 3,1E-4 negative regulation of cellular component biological process 4 7,1 3,6E-3 organization biological process skeletal muscle fiber development 3 5,4 5,0E-3 biological process cellular protein complex assembly 4 7,1 5,4E-3 biological process muscle fiber development 3 5,4 7,0E-3 biological process striated muscle cell development 3 5,4 1,4E-2 biological process actin filament organization 3 5,4 1,5E-2 metabotropic glutamate receptor signaling biological process 2 3,6 1,6E-2 pathway biological process muscle cell development 3 5,4 1,7E-2 biological process regulation of neurotransmitter levels 3 5,4 1,8E-2 biological process skeletal muscle tissue development 3 5,4 2,4E-2 biological process skeletal muscle organ development 3 5,4 2,5E-2 biological process actin filament polymerization 2 3,6 2,6E-2 cellular macromolecular complex biological process 4 7,1 3,5E-2 assembly biological process striated muscle cell differentiation 3 5,4 3,5E-2 biological process ATP metabolic process 3 5,4 3,6E-2 biological process transmission of nerve impulse 4 7,1 3,9E-2 biological process protein complex biogenesis 4 7,1 3,9E-2
Page | 57 Results biological process protein complex assembly 4 7,1 3,9E-2 biological process actin polymerization or depolymerization 2 3,6 4,2E-2 biological process glutamate signaling pathway 2 3,6 4,2E-2 purine ribonucleoside triphosphate biological process 3 5,4 4,4E-2 metabolic process ribonucleoside triphosphate metabolic biological process 3 5,4 4,5E-2 process cellular macromolecular complex subunit biological process 4 7,1 4,7E-2 organization purine nucleoside triphosphate metabolic biological process 3 5,4 4,8E-2 process
Category Term Count % p-value molecular function cytoskeletal protein binding 11 19,6 9,3E-7 molecular function actin binding 8 14,3 4,7E-5 molecular function purine nucleotide binding 15 26,8 2,6E-3 molecular function structural molecule activity 7 12,5 3,9E-3 molecular function protein domain specific binding 5 8,9 4,0E-3 molecular function purine ribonucleotide binding 14 25,0 5,3E-3 molecular function ribonucleotide binding 14 25,0 5,3E-3 molecular function nucleotide binding 15 26,8 1,1E-2 molecular function adenyl nucleotide binding 12 21,4 1,2E-2 molecular function purine nucleoside binding 12 21,4 1,2E-2 molecular function nucleoside binding 12 21,4 1,3E-2 molecular function adenyl ribonucleotide binding 11 19,6 2,2E-2
Category Term Count % p-value KEGG_PATHWAY Oocyte meiosis 4 7,1 2,0E-2 KEGG_PATHWAY Neurotrophin signaling pathway 4 7,1 2,7E-2
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4.1.5 Protein-protein interaction networks of significantly altered proteins in the striatal and hippocampal PSD fraction
We further analysed the 61 significantly altered striatal (Table 2) and the 55 significantly altered hippocampal (Table 3) proteins of the Shank3Δ11-/- mutant PSD, investigating possible protein-protein interaction networks. We inserted the entries into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database v10.0 (http://string-db.org) (Szklarczyk et al., 2015), which contains information on known and predicted protein-protein interactions. The database research revealed protein-protein interactions of 42 proteins in the striatal subgroup and 36 proteins interacting with each other in the hippocampal subgroup. In both brain regions, the protein-protein interactions revealed large clusters of proteins that are all linked to each other. These clusters are illustrated in Figure 8D, proteins that did not interact with any other protein of the respective subgroup were not included in this illustration.
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Figure 7 | Protein-protein interaction networks of significantly altered proteins Protein-protein interaction networks have been determined for striatal (A) and hippocampal (B) mutant PSD fractions using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database v10.0 (http://string-db.org) and are displayed as grey lines. Only significantly altered proteins with at least one interaction partner are included. Significantly downregulated entries are displayed with blue colour, significantly upregulated entries with orange colour.
4.1.6 Significant alterations converge between the striatal and the hippocampal Shank3Δ11-/- mutant PSDs and a previously published Shank3 in-vivo interactome
We further compared the significantly different proteins of the striatal (Table 2) and hippocampal (Table 3) Shank3Δ11-/- mutant PSDs with each other and a previously published Shank3 in-vivo interactome (Han et al., 2013). Interestingly, several of the significantly altered proteins of the striatum and hippocampus are included in the Shank3 in-vivo interactome (Figure 8A), indicating that these proteins interact in-vivo with Shank3. Among these proteins there are 6 proteins converging between the striatal alterations and the interactome. The matches between the significant hippocampal alterations and the in-vivo interactome include 9 proteins, whereas comparing the two subsets of significantly altered proteins of the striatal and
Page | 60 Results hippocampal Shank3Δ11-/- mutant PSDs resulted in a group of 5 proteins, overlapping between the two regions (Figure 8A). Interestingly, Homer1 can be found in each of the three subgroups: We found a significant reduction of Homer1 in both, striatum and hippocampus and it was identified as a Shank3 interaction partner by the Shank3 in- vivo interactome, thus confirming an important interplay between Homer1 and Shank3. Since the reduced protein levels of Homer1 in the striatal and hippocampal PSD was revealed by Mass-Spectrometry, we performed Western Blot analyses to confirm these data. We analysed the protein levels of Homer1 in wild type and Shank3Δ11-/- mutant PSD fractions of the striatum or hippocampus, respectively. In the striatal PSD fractions we could confirm a significant reduction, confirming the results provided by the Shank3Δ11-/- mutant proteome. However, we only observed a slight reduction of Homer1 protein levels but no significant change in the hippocampal PSD (Figure 8B). Statistical analysis was performed using unpaired two-tailed t-test with a sample size of 3 independent PSD fractions of both, wild type and Shank3Δ11-/- mutants. Equal amounts of total protein in each lane is represented by the β3-Tubulin control.
Figure 8 | Converging alterations in the striatal and hippocampal Shank3Δ11-/- mutant PSD (A) Significant alterations of the striatal and hippocampal Shank3Δ11-/- mutant PSDs overlap between the brain regions and several of these changes can be found in a recently published Shank3 in-vivo interactome (Han et al., 2013). Numbers represent the amount of remaining entries in the respective subgroup. Homer1 was reduced in both brain regions (blue colour) and additionally found as a Shank3 interaction partner (Han et al., 2013). (B) Western Blot analysis of striatal and hippocampal wild type (WT) and Shank3Δ11-/- mutant (KO) PSD fractions confirming the reduction of Homer1 protein levels observed in the striatal Shank3Δ11-/- mutant proteome. Protein levels were normalized on β3-Tubulin, exemplary Western Blots are shown. Statistical analysis was performed using unpaired two-tailed t-test with a sample size of 3 independent PSD fractions of both, wild type and Shank3Δ11-/- mutants. *: p<0.05, **: p<0.01. Data is presented as mean ± SEM. Figure partially adapted from (Reim et al., 2017), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/.
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4.2 The Shank3 interaction partner ProSAPiP1 regulates postsynaptic SPAR levels and the maturation of dendritic spines in hippocampal neurons
4.2.1 Verification of successful ProSAPiP1 knock down
Since the Asperger syndrome patient reported in (Sebat et al., 2007), shows a genetic deletion, which includes the PROSAPIP1 gene, we generated a shRNA approach to knock down ProSAPiP1 protein levels. The shRNA or scrambled control shRNA, fused into the FUGW Neo GFP vector backbone, was transfected into HEK293T cells together with Spax2 and VsVg plasmids to produce lentiviral particles. These particles were further used to infect primary rat hippocampal neurons on DIV1 for reducing their endogenous ProSAPiP1 protein levels. As the subsequent analyses were performed at DIV28, we examined the endogenous ProSAPiP1 protein levels of infected primary rat hippocampal neurons and control on DIV28 by extracting protein lysates and performing Western Blot analyses. ProSAPiP1 protein levels were significantly reduced in the RNAi based knock down approach (RNAi) compared to uninfected cells or scrambled control (Scr). No significant difference was observed between uninfected cells and cells infected with the scrambled control. As a reference for endogenous ProSAPiP1, rat hippocampal postsynaptic density (PSD, obtained with the “fast protocol”, see Material and Methods section) was included. Protein levels were normalized on β3-Tubulin and β-Actin and the uninfected control (Figure 9). Statistical analysis was performed using One-way ANOVA with a sample size of n=3 independent biological replicates for each condition; *: p<0.05.
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Figure 9 | shRNA based knock down of ProSAPiP1 Western Blot analysis of primary hippocampal neuron lysate reveals a significant reduction of endogenous ProSAPiP1 protein levels in the shRNA based knock down of ProSAPiP1 (RNAi) compared to both uninfected (Uninf.) and scrambled control (Scr). Equal amounts of total protein levels are provided by the β3-Tubulin and β-Actin controls. Rat hippocampal postsynaptic density (PSD) was included as a reference for endogenous ProSAPiP1. Statistical analysis was performed using One-way ANOVA with a sample size of n=3 independent biological replicates for each condition. *: p<0.05. Data is presented as mean ± SEM. Adapted from (Reim et al., 2016), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/.
4.2.2 Verification of successful ProSAPiP1 overexpression
To assess the functional importance of ProSAPiP1 in primary hippocampal neurons, we further generated lentiviral particles including GFP-tagged full-length ProSAPiP1, fused into the FUGW Neo GFP vector backbone as well as lentiviral particles including the empty FUGW Neo GFP vector backbone as control. Primary rat hippocampal neurons were infected with either GFP-ProSAPiP1 lentiviral particles or the empty vector control on DIV1 and kept in culture until DIV28. Protein lysates were extracted and Western Blot analyses were performed to validate the successful overexpression of GFP-ProSAPiP1. We observed a signal for endogenous ProSAPiP1 in both conditions, GFP-ProSAPiP1 overexpression and control, whereas a signal for GFP- ProSAPiP1 was only present after its overexpression at the expected molecular weight of 125 kDa and not in the respective control. Furthermore, the protein levels of endogenous ProSAPiP1 were compared between both conditions. Overexpression of GFP-ProSAPiP1 was also significantly increasing the amount of endogenous ProSAPiP1 protein. As a reference for endogenous ProSAPiP1, rat hippocampal postsynaptic density (PSD, obtained with the “fast protocol”, see Material and Methods section) was included. Protein levels were normalized on β3-Tubulin and β-Actin and the uninfected control (Figure 10). Statistical analysis was performed using unpaired
Page | 63 Results two-tailed t-test with a sample size of n=3 independent biological replicates for each condition; *: p<0.05.
Figure 10 | Overexpression of GFP-ProSAPiP1 and its effect on endogenous ProSAPiP1 (A) Western Blot analysis of primary hippocampal neuron lysate reveals a successful overexpression of GFP-ProSAPiP1 compared to the uninfected (Uninf.) control. (B) Determining the protein levels of endogenous ProSAPiP1 shows a significant increase when GFP-ProSAPiP1 is overexpressed. Equal amounts of total protein levels are assured by the β3-Tubulin and β-Actin controls. Rat hippocampal postsynaptic density (PSD) was included as a reference for endogenous ProSAPiP1. Statistical analysis was performed using unpaired two-tailed t-test with a sample size of n=3 independent biological replicates for each condition. *: p<0.05. Data is presented as mean ± SEM. Adapted from (Reim et al., 2016), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/.
4.2.3 ProSAPiP1 is not necessary to determine the number of synapses
To determine, whether reduced ProSAPiP1 protein levels will have an effect on the general number of synapses, primary rat hippocampal neurons were infected with ProSAPiP1 RNAi lentiviral particles, scrambled control, GFP-ProSAPiP1 or FUGW empty vector on DIV1 and kept in culture until DIV28, when ProSAPiP1 shows a distinct synaptic localization (Reim et al., 2016). Subsequently, immunocytochemistry was performed, staining against Bassoon to represent presynaptic specializations. Infected cells co-expressed GFP and could thus be distinguished from uninfected cells by their fluorescent signal. Bassoon positive signals were analysed for their density and intensity, however, no significant difference could be observed between ProSAPiP1 RNAi and scrambled control nor between GFP-ProSAPiP1 or the empty vector (Figure 11A). Statistical analysis was performed using unpaired two-tailed t-test with a sample size of 3 dendrites per cell, 5 cells per condition and n=3 independent
Page | 64 Results biological replicates for each condition. Therefore, we conclude that ProSAPiP1 is not involved in regulating the general number of synapses. We next analysed whether a shift in the excitatory/inhibitory balance could be observed when ProSAPiP1 protein levels are reduced. Infected rat hippocampal neurons were infected and kept in culture until DIV28. Immunocytochemistry was performed to stain against presynaptic VGluT1 or VGAT, representing excitatory or inhibitory synapses, respectively. However, no significant alteration of the VGluT1 or VGAT density was observed between ProSAPiP1 RNAi based knock down and scrambled control (Figure 11B). Statistical analysis was performed using unpaired two-tailed t-test with a sample size of 3 dendrites per cell, 5 cells per condition and n=3 independent biological replicates for each condition. These data suggest, that the excitatory/inhibitory balance is not disrupted in primary rat hippocampal neurons when ProSAPiP1 protein levels are reduced.
Figure 11 | Immunocytochemistry reveals no different number of synapses at altered ProSAPiP1 protein levels and no disrupted excitatory/inhibitory balance in ProSAPiP1 knock down (A) Primary hippocampal cultures were infected with FUGW empty vector (Vector), GFP-ProSAPiP1, scrambled control (Scr) or ProSAPiP1 shRNA (RNAi) lentiviral particles on DIV1 and stained on DIV28 for Bassoon (red). No significant differences were observed in the density of Bassoon positive puncta per 10 μm dendrite length between GFP-ProSAPiP1 and Vector or RNAi and Scr control. (B) Primary hippocampal cultures were infected with scrambled control (Scr) or ProSAPiP1 shRNA (RNAi) lentiviral particles on DIV1 and stained on DIV28 for VGluT1 (red) or VGAT (red) as indicated. No significant differences were observed in the density of VGluT1 or VGAT positive puncta per 10 μm dendrite length between Scr and RNAi. (A, B) Scale bars: 10 μm. Statistical analysis was performed using unpaired two-sided t-test. n = 15 neurons from three independent cultures. Data is presented as mean ± SEM. Adapted from (Reim et al., 2016), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/.
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4.2.4 ProSAPiP1 does not influence synaptic Shank3 levels but selectively regulates postsynaptic protein levels of SPAR
Since ProSAPiP1 is an interaction partner of the postsynaptic scaffold protein Shank3 (Wendholt et al., 2006), we were interested whether changing the levels of ProSAPiP1 will have an influence on synaptic protein levels of Shank3. Immunocytochemistry was performed on primary rat hippocampal neurons, which were infected on DIV1 with ProSAPiP1 RNAi lentiviral particles, scrambled control, GFP-ProSAPiP1 or FUGW empty vector and kept in culture until DIV28. Cells were stained for Shank3 and the density and intensity of synaptic puncta was measured in all conditions. However, both intensity and density of synaptic Shank3 puncta did not reveal significant differences neither when ProSAPiP1 was overexpressed (GFP-ProSAPiP1, Figure 12A) nor knocked-down (RNAi, Figure 12B) and compared to the respective controls (Scr for RNAi and Empty vector for GFP-ProSAPiP1). Statistical analysis was performed using unpaired two-tailed t-test with a sample size of 3 dendrites per cell, 5 cells per condition and n=3 independent biological replicates for each condition. Therefore, we conclude that ProSAPiP1 does not regulate the synaptic protein levels of Shank3 in primary rat hippocampal neurons. In the same experimental approach, we analysed whether changes in ProSAPiP1 levels will have an effect on synaptic levels of SPAR. To assure that we only analyse SPAR puncta, we tested our self-made SPAR antibody on specificity and cross- reactivity. Overexpression of GFP-SPAR and either SPAR RNAi or control vector in HEK293T cells confirmed the specificity of our antibody, since a reduced signal for GFP-SPAR was observed by Western Blot analysis when SPAR-RNAi (kindly provided by Daniel Pak, Department of Pharmacology & Physiology, Georgetown University, Washington, USA) was co-expressed. Cross-reactivity of the antibody was excluded by overexpression of GFP-SPAR, GFP-SPAR2 or GFP-SPAR3 in HEK293T cells, which only displayed a signal in Western Blot analysis in the case of GFP-SPAR overexpression (Figure 13). Using this antibody, we measured density and intensity of SPAR puncta in all conditions of altering ProSAPiP1 levels in primary rat hippocampal cultures. Overexpression of GFP-ProSAPiP1 resulted in a significantly increased intensity of SPAR puncta, compared to the empty vector control. Likewise, RNAi based knock down of ProSAPiP1 levels led to a reduction in both density and intensity of SPAR
Page | 66 Results puncta compared to the scrambled control, suggesting a cumulative effect of ProSAPiP1 on synaptic SPAR levels (Figure 12). Statistical analysis was performed using unpaired two-tailed t-test with a sample size of 3 dendrites per cell, 5 cells per condition and n=3 independent biological replicates for each condition; *: p<0.05, **: p<0.01. These data suggest that ProSAPiP1 selectively regulates the postsynaptic levels of SPAR.
Figure 12 | ProSAPiP1 selectively regulates postsynaptic protein levels of SPAR (A) Primary hippocampal cultures were infected with FUGW empty vector (Vector) or GFP-ProSAPiP1 lentiviral particles on DIV1 and stained on DIV28 for Shank3 (red) or SPAR (red) as indicated. No significant differences were observed for the density of Shank3 or SPAR positive puncta per 10 μm dendrite length nor the intensity of Shank3 positive puncta comparing GFP-ProSAPiP1 with the Vector control. The intensity of SPAR positive puncta was significantly increased in GFP-ProSAPiP1 overexpression compared to the Vector control. (B) Primary hippocampal cultures were infected with scrambled control (Scr) or ProSAPiP1 shRNA (RNAi) lentiviral particles on DIV1 and stained on DIV28 for Shank3 (red) or SPAR (red) as indicated. No significant differences were observed for the density or intensity of Shank3 positive puncta per 10 μm dendrite length. SPAR positive puncta were significantly reduced in their density per 10 µm dendrite length and their intensity comparing RNAi with Scr control. (A, B) Scale bars: 10 μm. Statistical analysis was performed using unpaired two-sided t-test. n = 15 neurons from three independent cultures. *: p<0.05, **: p<0.01. Data is presented as mean ± SEM. Adapted from (Reim et al., 2016), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/.
Page | 67 Results
Figure 13 | Characterization of the self-made SPAR antibody (A) Specificity: Western Blot analysis using cell lysates with overexpression of GFP-SPAR and SPAR RNAi or empty vector control in HEK293T cells. Both, our self-made SPAR antibody (left panel) and the commercial GFP antibody (right panel) show the reduction of GFP-SPAR protein levels. Equal amounts of total protein are assured by the β-Actin control. (B) Cross-reactivity: Western Blot analysis using cell lysates with overexpression of GFP-SPAR, GFP-SPAR2 or GFP-SPAR3 in HEK293T cells. Our self-made SPAR antibody only provides a signal of GFP-SPAR and at the expected molecular weight. Expression of each of the GFP-linked constructs, however, is shown by GFP signals in each lane. Adapted from (Reim et al., 2016), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/.
4.2.5 ProSAPiP1 does not regulate postsynaptic PSD95 levels
As ProSAPiP1 interacts with Shank3 and this interaction might be necessary for the assembly of further postsynaptic scaffold proteins to the PSD, we analysed if overexpression or knock down of ProSAPiP1 will have an impact on the density or intensity of PSD95, an important PSD scaffold molecule and interaction partner of SPAR, in primary rat hippocampal neurons. Cultures were infected on DIV1 with lentiviral particles to overexpress (GFP-ProSAPiP1) or knock down (RNAi) ProSAPiP1 or with the respective control constructs (empty vector and Scr) and kept in culture until DIV28. Using immunocytochemistry, we stained and analysed the PSD95 positive puncta. However, neither density nor intensity of PSD95 signals were significantly different from the respective controls after overexpression or knock down of ProSAPiP1 (Figure 14). Statistical analysis was performed using unpaired two-tailed t- test with a sample size of 3 dendrites per cell, 5 cells per condition and n=3 independent biological replicates for each condition. Thus, ProSAPiP1 does not seem to be involved in regulating postsynaptic PSD95 levels.
Page | 68 Results
4.2.6 Overexpression of GFP-ProSAPiP1 increases the amounts of LAPSER1 at the synapse
Since ProSAPiP1 seems to regulate the postsynaptic levels of SPAR, we investigated possible effects of altered ProSAPiP1 levels on LAPSER1, another member of the Fezzin family and a protein, which is supposed to connect SPAR with the PSD scaffold. Primary rat hippocampal neuron cultures were infected with lentiviral particles on DIV1 to overexpress (GFP-ProSAPiP1) or knock down (RNAi) ProSAPiP1 levels and with the respective control constructs (empty vector and Scr). Neurons were kept in culture until DIV28 and immunocytochemistry was performed, staining against LAPSER1 to measure density and intensity of LAPSER1 puncta. Neither of the conditions revealed significant differences in LAPSER1 density or intensity. Only overexpression of GFP- ProSAPiP1 resulted in a significantly increased intensity of LAPSER1 puncta compared to the empty vector control, accounting for more LAPSER1 protein at the postsynapse (Figure 14). Statistical analysis was performed using unpaired two-tailed t-test with a sample size of 3 dendrites per cell, 5 cells per condition and n=3 independent biological replicates for each condition. These data indicate that increased levels of ProSAPiP1 lead to higher levels of synaptic LAPSER1.
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Figure 14 | Analysis of PSD95 and LAPSER1 after ProSAPiP1 overexpression and knockdown in mature primary hippocampal neurons. (A) Primary hippocampal cultures were infected with FUGW empty vector (Vector) or GFP-ProSAPiP1 lentiviral particles on DIV1 and stained on DIV28 for PSD95 (red) or LAPSER1 (red) as indicated. No significant differences were observed for the density of PSD95 or LAPSER1 positive puncta per 10 μm dendrite length nor the intensity of PSD95 positive puncta comparing GFP-ProSAPiP1 with the Vector control. The intensity of LAPSER1 positive puncta was significantly increased in GFP-ProSAPiP1 overexpression compared to the Vector control. (B) Primary hippocampal cultures were infected with scrambled control (Scr) or ProSAPiP1 shRNA (RNAi) lentiviral particles on DIV1 and stained on DIV28 for PSD95 (red) or LAPSER1 (red) as indicated. No significant differences were observed for the density or intensity of PSD95 or LAPSER1 positive puncta per 10 μm dendrite length comparing RNAi with Scr control. (A, B) Scale bars: 10 μm. Statistical analysis was performed using unpaired two-sided t-test. n = 15 neurons from three independent cultures. *: p<0.05. Data is presented as mean ± SEM. Adapted from (Reim et al., 2016), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/.
4.2.7 ProSAPiP1 accounts for proper dendritic spine maturation
As we have shown, that ProSAPiP1 is regulating postsynaptic SPAR levels and SPAR has previously been associated with dendritic spine morphology, we examined whether alterations in ProSAPiP1 protein levels will have an impact on dendritic spine parameters. Primary rat hippocampal neurons were infected with lentiviral particles on DIV1 to overexpress (GFP-ProSAPiP1) or knock down (RNAi) ProSAPiP1 and with the respective control constructs (empty vector and Scr). To visualize F-actin, and thus
Page | 70 Results dendritic spines, we additionally infected the neuronal cultures on DIV24 with RFP- tagged LifeAct® lentiviral particles (Ibidi). Cells were kept in culture until DIV28 and the RFP-signals (F-actin, visualizing dendritic spines) of GFP positive cells (containing GFP-ProSAPiP1, FUGW empty vector, ProSAPiP1 RNAi or scrambled constructs) were analysed. The relative amounts of spines, characterized by the Imaris Spine Classifier software package as ‘Mushroom’, ‘Thin’, ‘Stubby’ or ‘Filopodia’, were determined and the average number of spines in general per 10 µm dendrite length was measured within the four conditions of altering ProSAPiP1 protein levels. When ProSAPiP1 was overexpressed (GFP-ProSAPiP1, Figure 15A), dendrites possessed significantly less spines in general and a significantly lower amount of ‘Filopodia’ assigned spines, indicating increased dendritic spine maturation. However, when ProSAPiP1 was knocked-down (RNAi, Figure 15B), the general spine number was increased, although not significantly, whereas the relative amount of ‘Mushroom’ assigned spines was significantly reduced, suggesting decreased dendritic spine maturation. Statistical analysis was performed using unpaired two-tailed t-test with a sample size of 3 dendrites per cell, 5 cells per condition and n=3 independent biological replicates for each condition. Finally, these data suggest that ProSAPiP1 is involved in regulating the general number of dendritic spines and supports their maturation.
Page | 71 Results
Figure 15 | ProSAPiP1 regulates proper dendritic spine maturation in primary hippocampal neurons (A,B) Primary hippocampal cultures were infected with FUGW empty vector (Vector), GFP-ProSAPiP1, scrambled control (Scr) or ProSAPiP1 shRNA (RNAi) lentiviral particles on DIV1. For spine analysis, neurons were additionally infected with RFP-tagged LifeAct (ibidi) visualizing F-actin on DIV24 and kept in culture until DIV28. (A) Comparing GFP-ProSAPiP1 overexpression to the Vector control, spine density and the percentage of filopodia were significantly decreased in neurons overexpressing GFP- ProSAPiP1 as indicated. (B) Spine density remained unchanged between Scr and RNAi while the percentage of mushroom-like spines was significantly decreased after knockdown of ProSAPiP1 as indicated. (A, B) IF, immunofluorescence; RM, reconstructed model. Scale bar: 10 μm. Statistical analysis was performed using unpaired two-sided t-test. n = 15 neurons from three independent cultures. *: p<0.05, ***: p<0.001. Data is presented as mean ± SEM. Adapted from (Reim et al., 2016), this figure is subjected to the Creative Common License CC BY 4.0, https://creativecommons.org/licenses/by/4.0/.
Page | 72 Discussion
5 Discussion
5.1 PSD fractionation
The isolation of ‘synaptosomes’, synaptic structures including parts of the postsynaptic membrane and free from most other structures, has been performed since the 1960s (De Robertis et al., 1962; Gray and Whittaker, 1962). Subsequently it was discovered that the non-ionic detergent Triton-X-100 selectively removes the pre- and postsynaptic membranes from synaptic complexes (Rodriguez de Lores et al., 1967), and thus releases the postsynaptic density. This observation serves as a basis for today’s protocols for performing subcellular PSD fractionation. Since then, modifications of the distinct protocols have been performed to achieve higher purity of the obtained PSD fractions and to reduce the time and tissue required (Carlin et al., 1980; Cohen et al., 1977; Kahne et al., 2012). In this study, we established a protocol of gaining high quality PSD fractions, isolated from defined murine brain regions, with a low amount of tissue required in shorter time than the current protocols (Distler et al., 2014). Our protocol includes tissue homogenization and centrifugation steps to obtain the crude membrane fraction, comparable to established protocols. Subsequently we perform ultracentrifugation with the crude membrane fraction loaded on a three-layered discontinuous sucrose gradient to collect the synaptosomes. Treatment with Triton-X- 100 and further centrifugation finally provides the PSD fractions (Figure 2). Our protocol requires the dissected brain tissue of only five mice combined, which is clearly less material than used in other protocols. While the standard fractionation protocols, obtaining similar purity of the PSD fraction, usually include a highly time-consuming working procedure (Carlin et al., 1980; Cohen et al., 1977; Kahne et al., 2012), in our protocol the PSD fraction can be obtained already after approximately 7 hours. To confirm the successful subcellular fractionation, we performed Western Blot analyses, comparing postsynaptic PSD-95 and presynaptic Synaptophysin protein levels among all collected subcellular fractions and the homogenate. We observed increased levels of both, PSD-95 and Synaptophysin, as synaptic proteins, in the synaptosomal fraction. Using this fraction for further centrifugation to distinguish between PSD fraction and synaptic cytosol (S3), we found clearly enriched levels of postsynaptic PSD-95 in the PSD fraction and only low levels in S3. Moreover,
Page | 73 Discussion presynaptic Synaptophysin was clearly reduced in the PSD fraction while being enriched in S3 (Figure 3). These results confirm a successful enrichment of synaptic proteins into the synaptosomal fraction. This fraction is further separated into PSD and synaptic cytosol and we could show an enrichment of a post- and a presynaptic marker in the respective fraction. These analyses confirm a successful subcellular PSD fractionation performing our newly established protocol. Finally, with low requirements of tissue and time, this protocol surely serves as a promising alternative replacing the current tissue- and time-consuming subcellular fractionation protocols.
5.2 Large-scale proteomic analysis of striatal and hippocampal PSDs of Shank3Δ11-/- mutant mice
Many studies on Shank3 mutations have already been performed, however, the molecular consequences in precise detail are not fully understood. Moreover, present studies mostly focus on a single brain region and only a biased selection of PSD proteins has been analysed (Bozdagi et al., 2010; Kouser et al., 2013; Lee et al., 2015; Peca et al., 2011; Schmeisser et al., 2012; Vicidomini et al., 2016; Wang et al., 2016; Wang et al., 2011; Yang et al., 2012). We therefore use this new protocol, to generate striatal and hippocampal PSD fractions of wild type and Shank3Δ11-/- mutant mice (Schmeisser et al., 2012) to compare the molecular setup of PSDs between mice with normal protein levels of Shank3 and those lacking major isoforms of Shank3. We addressed the question of molecular consequences on the PSD composition when Shank3 as one of the ‘master scaffolds’ (Boeckers, 2006) in the PSD is partially absent. Thus, we further performed ion-mobility enhanced data-independent label-free LC-MS/MS and obtained an unbiased and comprehensive dataset of molecular changes in vivo in striatal and hippocampal PSD fractions lacking the major Shank3 isoforms. We identified 2461 proteins in the striatal and 2345 proteins in the hippocampal PSD of Shank3Δ11-/- mutant mice. The levels of 61 of these proteins have been significantly altered in the striatal KO PSD and 55 in the hippocampal KO PSD (Figure 5D, Table 2, Table 3). Among the group of significantly altered proteins, we further investigated their biological function or role and a significant enrichment of annotated biological terms and functions with the Database for Annotation, Visualization and Integrated
Page | 74 Discussion
Discovery (DAVID) v6.7 (https://david.ncifcrf.gov) (Huang da et al., 2009a; b). This gene-ontology analysis revealed a significant enrichment of several annotations in the categories ‘cellular component’, ‘biological process’, ‘molecular function’ and ‘KEGG pathways’ for both brain regions. Interestingly, the significant changes in the striatal PSD mainly included annotations representing glutamatergic synaptic transmission (Table 4). Furthermore, in the hippocampal PSD the significant changes essentially involved annotation representing cytoskeleton-associated functions and processes (Table 5). The significant enrichment of the respective annotations was specific for each of the brain regions, as no terms indicating defects in glutamatergic synaptic transmission have been enriched in the hippocampal PSD and no terms indicating defects in cytoskeleton-associated functions and processes have been enriched in the striatal PSD of Shank3Δ11-/- mutant mice. These findings are perfectly matching a previous study on the same Shank3 mutant mouse model: Electrophysiology on medium spiny neurons derived from the striatum revealed defects in glutamate synaptic transmission in Shank3Δ11-/- mutant mice, with a focus on metabotropic glutamate receptor 5. In hippocampal neurons, however, such defects were not observed, thus underlining the brain region specific alterations in Shank3Δ11-/- mutant mice (Vicidomini et al., 2016). Furthermore, impaired striatal glutamate synaptic transmission was also observed in other Shank3 mutant mice (Jaramillo et al., 2016a; Jaramillo et al., 2016b; Peca et al., 2011; Peixoto et al., 2016; Wang et al., 2016; Zhou et al., 2016) and seems to be a common striatal defect observed in the different Shank3 mutant mice. The significant changes in the hippocampal PSDs of Shank3Δ11-/- mutant mice were mainly involved in cytoskeletal organization. This association is further supported by previous studies on Shank3 in vivo interaction partners. Combining the results obtained with yeast two-hybrid screening experiments and with in vivo immunoprecipitation, these studies present a Shank3 interactome (Han et al., 2013; Sakai et al., 2011). Gene ontology and pathway analysis revealed an impact of ‘regulation of the acting cytoskeleton’ in the list of these Shank3 interaction partners. Interestingly, the Shank3 interactors comprise plenty of actin-related proteins, including subunits of the Arp2/3 complex, which initiates Actin polymerization, as well as WASF1 and cortactin, both activating the Arp2/3 complex (Campellone and Welch, 2010; Han et al., 2013; Naisbitt et al., 1999; Proepper et al., 2007). Moreover, increasing the protein levels of Shank3 in cultured hippocampal neurons resulted in an
Page | 75 Discussion increase of F-actin and levels were restored after expression of Shank3 siRNA (Han et al., 2013). Since several actin-related proteins are among the recently identified Shank3 interaction partners and levels of actin could be altered in cultured hippocampal neurons by modulating Shank3 protein dosage, the regulation of the actin cytoskeleton seems to be tightly connected to Shank3 protein, as shown for hippocampal neurons (Han et al., 2013). Therefore, our study further confirms an impact of Shank3 protein levels on (actin) cytoskeleton organization in hippocampal neurons. Furthermore, the significantly altered proteins of both brain regions are not single independent proteins. Instead, they show many protein-protein interactions with each other and form big clusters with most of the members being reduced when major isoforms of Shank3 are absent (Figure 8). The significant brain region specific changes we identified seem to affect large protein clusters, possibly part of certain signalling pathways. As large clusters of proteins are affected from the Shank3 mutation, these changes might have a more detrimental consequence than single and independent changes in protein levels. Since several components of the protein cluster are affected, functional compensation by similar proteins included in the same complex might thus be less likely. Interestingly, the Shank3Δ11-/- mutation has diverging consequences on the striatal and hippocampal PSD, leading to different biological pathways being affected and disrupted. These discrepancies might arise from the complexity of the Shank3 gene and its expression. Expression of Shank3 was analysed in several brain regions, revealing the highest levels in the striatum and moderate levels in the hippocampus (Boeckers et al., 2004; Boeckers et al., 1999b; Peca et al., 2011; Vicidomini et al., 2016; Wang et al., 2014). However, the Shank3 gene product comprises at least 10 currently identified Shank3 isoforms (Figure 1) (Wang et al., 2016), which are also differentially expressed (Wang et al., 2014). These findings might open several hypotheses: The respective Shank3 gene products are differentially expressed in the striatum and the hippocampus. Each isoform contains a different setup of protein interaction domains and might therefore fulfil a distinct function by anchoring only selected proteins to the PSD scaffold. Due to the different expression of the isoforms, a loss of Shank3a-c as in our Shank3Δ11-/- mutant model could be partially compensated by the other remaining isoforms. Since these show a different pattern in striatum and hippocampus, the resulting effects of a possible
Page | 76 Discussion compensation might vary, thus leading to brain region specific consequences of a Shank3Δ11-/- mutation. On the other side, the Shank3 protein in general might have a brain region specific function and impact in organizing the respective PSD. While in the striatal PSDs Shank3 could generally be important for regulating glutamatergic synaptic signalling, in the hippocampus it is important for organizing the underlying (actin-based) cytoskeleton. Loss of certain isoforms of Shank3 might therefore result in a reduced ability of Shank3 to fulfil its distinct function and brain region specific impairments appear. Interestingly, a defect in striatal glutamatergic synaptic transmission is observed in various Shank3 mutant mouse models, with different genetic mutations causing a model specific loss of distinct or all isoforms (Bozdagi et al., 2010; Kouser et al., 2013; Lee et al., 2015; Peca et al., 2011; Schmeisser et al., 2012; Vicidomini et al., 2016; Wang et al., 2016; Wang et al., 2011; Yang et al., 2012). Eventually, the model specific pattern of remaining and absent Shank3 isoforms, which is though leading to a common phenotype in the striatal PSDs of Shank3 mutant mouse models, would rather support the second hypothesis. Furthermore, another common phenotype of several Shank3 mutant mouse models is alterations in Homer1 protein levels: Shank3 is known to contain a Homer binding site (Grabrucker et al., 2011b) and an interaction of Shank3 and Homer1 has been shown previously (Han et al., 2013; Tu et al., 1999). Together these proteins are forming complexes in the PSD (Hayashi et al., 2009; Tu et al., 1999) to anchor further proteins such as mGluR5 and also GKAP/PSD-95 to the PSD (Hayashi et al., 2009; Tu et al., 1999; Tu et al., 1998). Thus, Shank3 and Homer1 seem to be closely associated with each other in the PSD. Not all studies on the different Shank3 mutant mouse models have analysed altered synaptic proteins in their models. However, the majority of studies including such investigation report reduced protein levels of Homer1 (Peca et al., 2011; Vicidomini et al., 2016; Wang et al., 2016; Wang et al., 2011), indicating that Shank3 is recruiting Homer1 to the PSD (Vicidomini et al., 2016). In this study, we could also show reductions in Homer1 protein levels in the PSDs of both the striatum and the hippocampus by performing ion-mobility enhanced data- independent label-free LC-MS/MS. Interestingly, this was the only converging significant alteration between the striatal and hippocampal PSDs of Shank3Δ11-/- mutant mice. These results could be confirmed by Western Blot, however only for the striatal PSD (Figure 8). Since the recruitment of Homer1 to the PSD by Shank3 was
Page | 77 Discussion shown to be important especially in the striatum of Shank3Δ11-/- mutant mice (Vicidomini et al., 2016), our data match with the previous observations of reduced Homer1 protein levels in the PSD with a special importance in the striatum.
5.3 Functional aspects of ProSAPiP1 at the PSD
The postsynaptic Shank scaffold is very important for the proper organization of the PSD and thus its functionality. Disruptions in this network caused by SHANK mutations, predominantly SHANK3 (Leblond et al., 2014), are known to result in various neuropsychiatric disorders (Grabrucker et al., 2011b; Guilmatre et al., 2014). Therefore, a detailed understanding of Shank3 and its interaction partners is crucial for developing new strategies in counteracting neuropsychiatric disease. We recently identified the postsynaptic Fezzin family member ProSAPiP1 as a binding partner of Shank3 and SPAR (Wendholt et al., 2006). A contribution of ProSAPiP1 to neuropsychiatric disorders could be possible, since ProSAPiP1 was included in the genomic deletion identified in an Asperger syndrome patient (Sebat et al., 2007). Therefore, we were highly interested in the neuronal function of ProSAPiP1, which has not yet been intensively studied. Since it has been reported that Shank3 is fundamental for the formation of functional synaptic contacts (Arons et al., 2012; Grabrucker et al., 2011b; Roussignol et al., 2005; Verpelli et al., 2011) and some Shank3 interactors such as Abi-1 (Proepper et al., 2007) or Abp1 (Haeckel et al., 2008) are involved in synapse formation, we were interested in whether ProSAPiP1 as Shank3 interaction partner contributes to the formation of synapses. Therefore, we modulated ProSAPiP1 protein levels in primary hippocampal neurons, by RNAi based knock down (Figure 9) and viral overexpression (Figure 10), respectively, and analysed the number of Bassoon positive puncta. However, we did not observe significant differences and suggested that the general synapse numbers are not significantly different when ProSAPiP1 protein levels are altered. Therefore, we concluded that ProSAPiP1 does not participate in regulating synapse formation. Furthermore, we also excluded an impact of ProSAPiP1 protein levels in influencing the excitatory/inhibitory balance, since we also did not observe significantly different numbers of presynaptic markers, including excitatory VGluT1 and inhibitory VGAT positive signals, when ProSAPiP1 protein levels were reduced (Figure 11). Similar observations have been reported for PSD-Zip70, which is another member Page | 78 Discussion of the Fezzin protein family and a homologue of ProSAPiP1: In hippocampal neurons overexpressing the dominant-negative short C-terminal region of PSD-Zip70 or after RNAi based knock down of PSD-Zip70, no significant changes for bassoon positive puncta have been observed (Maruoka et al., 2005). Furthermore, cortical neurons from PSD-Zip70 KO mice also do not show differences in bassoon or VGAT positive puncta. However, an increase of VGluT1 positive puncta has been reported these neurons, when PSD-Zip70 was knocked out (Mayanagi et al., 2015). Since ProSAPiP1 was shown to interact with Shank3 (Wendholt et al., 2006), we investigated whether ProSAPiP1 protein levels influence the levels of Shank3 or PSD95 as a further important PSD scaffold protein. Shank3 and PSD95 are among the most important and most concentrated scaffold proteins in the PSD (Boeckers, 2006; Sheng and Hoogenraad, 2007), however, neither the amount nor intensity of Shank3 and PSD95 positive puncta are significantly changed after modifying ProSAPiP1 protein levels (Figure 12, Figure 14). Therefore, we suggest that the impact of ProSAPiP1 protein levels is rather limited on the excitatory postsynaptic scaffold. Previous studies from our group have shown that ProSAPiP1 links SPAR to the Shank3 platform and thus postulated that ProSAPiP1 recruits SPAR to synapses (Wendholt et al., 2006). We therefore analysed the postsynaptic levels of SPAR when ProSAPiP1 is overexpressed or knocked down. Interestingly, we indeed found that overexpression of ProSAPiP1 led to a significant increase of postsynaptic SPAR intensity, while knock down of ProSAPiP1 caused a significant decrease (Figure 12). Additionally, decreased protein levels of ProSAPiP1 also resulted in a significantly reduced density of SPAR puncta, whereas overexpression did not have an effect on SPAR puncta density. We therefore suggest that due to reduced intensity of SPAR puncta, several synaptic SPAR clusters do no longer exceed the threshold for detection in our analysis. We finally conclude that the protein levels of ProSAPiP1 influence postsynaptic SPAR protein levels. Thus, our data support the hypothesis of ProSAPiP1 recruiting SPAR to synapses (Wendholt et al., 2006). Previously published yeast two- hybrid screens reveal that all Fezzin family members are able to bind the C-terminus of SPAR (Schmeisser et al., 2009), which has been further confirmed for ProSAPiP1, PSD-Zip70 and LAPSER1 (Maruoka et al., 2005; Mayanagi et al., 2015; Schmeisser et al., 2009; Wendholt et al., 2006). A reduction of the synaptic localization of SPAR was also observed after overexpression of the dominant-negative short C-terminal region of PSD-Zip70 or after RNAi based knock down of PSD-Zip70. Expression of
Page | 79 Discussion exogeneous PSD-Zip70 in PSD-Zip70 KO neurons, however, restored the synaptic localization of SPAR (Maruoka et al., 2005; Mayanagi et al., 2015). We therefore suggest, that Fezzin family members might regulate the synaptic localization of SPAR and thus influence its levels in the PSD. In the PSD, SPAR interacts with and interconnects the PSD95-NMDAR complex and F-actin and further reorganizes the actin cytoskeleton to finally shape the dendritic spines. SPAR localization to the dendritic spines results in enlargement of the spine heads, while reduced SPAR levels were shown to cause a narrowed and elongated spine morphology (Pak et al., 2001). Since synaptic SPAR levels have an important impact on dendritic spine morphology and ProSAPiP1 recruits SPAR to synapses, we investigated the influence of ProSAPiP1 protein levels on both, spine density and morphology. Interestingly, we observed that overexpression of ProSAPiP1 caused a reduction in the spine density, in particular strongly decreasing the amount of filopodia. In contrast, knock down of ProSAPiP1 resulted in a significant decrease of mushroom- like spines (Figure 15). Filopodia are considered as the precursors for mature dendritic spines, since they are highly present at early stages in vivo and the first postnatal days in vivo until they are replaced by stubby spines (Boyer et al., 1998; Fiala et al., 1998; Hering and Sheng, 2001). Finally, thin and mushroom-like spines as mature dendritic spines become the predominant type of spine shapes (Fiala et al., 1998; Harris et al., 1992). Here, we show that high levels of ProSAPiP1 promote the reduction of filopodia as dendritic spine precursors and low levels of ProSAPiP1 promote the reduction of mature mushroom-like spines. Since ProSAPiP1 recruits SPAR to synapses and the effects of SPAR on spine morphology (Pak et al., 2001) resemble our observation with high and with low ProSAPiP1 protein levels, we postulate that ProSAPiP1 and SPAR collaborate in regulating spine morphology. Interestingly, similar results have been obtained for PSD-Zip70, since deficiency of PSD-Zip70 not only caused reductions in synaptic SPAR protein levels but also tiny-headed immature dendritic spines. Since synaptic SPAR decrease in PSD-Zip70 KO neurons caused aberrant Rap2 activation in this study, this pathway was proposed as the underlying mechanism for altered spine shape and maturity in PSD-Zip70 KO neurons (Mayanagi et al., 2015). Whether overexpression or knock down of ProSAPiP1 also affects Rap2 activity to regulate spine morphology seems to be likely, but needs to be further addressed in future studies.
Page | 80 Discussion
In this study, we could further uncover functional aspects of ProSAPiP1, one of the Fezzin family members. Since ProSAPiP1 was identified within the genomic deletion of an Asperger syndrome patient (Sebat et al., 2007) we suggest a possible contribution of ProSAPiP1 to the patients pathology. Interestingly, post-mortem neuropathological studies on Fragile X syndrome patients observed structural abnormalities of dendritic spines (Comery et al., 1997; Irwin et al., 2000), and studies found increases of spine density in Fmr1 KO mice (Dolen et al., 2007) as well as decreases in Mecp2 mutant mice (Belichenko et al., 2009). An impact of altered spine density or morphology can be observed in various disorders of ASD, therefore, a contribution of ProSAPiP1 in the Asperger syndrome patient’s pathology might be possible. In addition to ProSAPiP1 in the Asperger syndrome patient (Sebat et al., 2007), also LAPSER1 was mentioned in a human ASD context: A single nucleotide polymorphism (SNP) with suggestive association signals to ASD has been identified in the genomic locus of LAPSER1 in a whole-genome study on large cohorts of patients and healthy controls (Wang et al., 2009). We therefore assessed synaptic LAPSER1 protein levels after overexpression or knock down of ProSAPiP1 and found an increase of LAPSER1 puncta intensity when ProSAPiP1 was overexpressed (Figure 14). As Fezzin family members are able to form homo- and hetero-multimers via their coiled- coil domain, additional ProSAPiP1 protein at the PSD might provide the basis for further LAPSER1 at the synapse. If this might contribute to altered spine density or morphology when ProSAPiP1 is overexpressed or if this might have an impact on further unknown functional aspects of ProSAPiP1, however, remains elusive. Moreover, neither of the two studies indicating a connection of Fezzins and human ASD, however, proves a direct implication of the respective Fezzin gene locus on the formation of the disease or the extent of the disease pathology. With our findings on functional aspects of ProSAPiP1 in neurons, we provide the basis for further detailed and mechanistic studies, but more intense investigation on the Fezzin protein family members and the consequences of disruptions in their genes might be necessary to better understand their possible roles in disease formation and pathology.
Page | 81 Summary
6 Summary
Autism spectrum disorders (ASD) affect approximately 1% of the human population. The underlying mechanisms for disease formation and pathology have been addressed in many studies. Due to the high complexity of ASD, however, these mechanisms are still not completely understood. The three SHANK genes are frequently mutated in ASD patients with the highest contribution of SHANK3. Mutations in SHANK3 are causing several neuropsychiatric diseases including Phelan-McDermid syndrome, ASD and intellectual disability. Many studies investigated molecular alterations in Shank3 mutant mouse models. However, a comprehensive approach analysing an unbiased set of proteins has not yet been performed in Shank3 mutant mouse models. In this study, we established a new protocol to isolate the postsynaptic density (PSD) fraction from mouse brain tissue. Applying this protocol, we generated striatal and hippocampal PSD fractions of wild type and Shank3Δ11-/- mutant mice to compare the molecular setup of their PSD. Therefore, we performed ion-mobility enhanced data-independent label-free LC-MS/MS on the isolated PSD fractions to obtain an unbiased and comprehensive dataset of molecular changes in vivo in striatal and hippocampal PSD fractions lacking the major isoforms of Shank3. In the absence of these Shank3 isoforms, we identified brain region specific molecular alterations in the PSD, indicating disruptions in striatal glutamatergic synaptic transmission, while in the hippocampal PSD of Shank3Δ11-/- mutant mice mainly cytoskeleton-associated functions and processes were affected. Postsynaptic Homer1 was the only protein found significantly altered in both brain regions. We observed reductions in Homer1 in both brain regions, which are in line with previous observations in Shank3Δ11-/- and other Shank3 mutant mouse models. Our study is the first comprehensive analysis of brain region specific PSD proteomes of Shank3 mutant mice. We provide information on Shank3Δ11-/- mutant PSD composition, which will be important for further Shank3 based studies and pharmaceutical treatment experiments. Furthermore, we investigated functional aspects of ProSAP-interacting protein 1 (ProSAPiP1), a member of the Fezzin protein family and interaction partner of Shank3 and Spine-associated RapGAP (SPAR) with yet unknown function. We virally knocked down and overexpressed ProSAPiP1 to analyse functional consequences in primary hippocampal neurons. While general synapse numbers and the protein levels of main PSD scaffold proteins Shank3 and PSD95 were not altered, we observed that
Page | 82 Summary
ProSAPiP1 regulates the postsynaptic protein levels of its interaction partner SPAR. In line with previously described consequences of alterations in postsynaptic SPAR protein levels, we observed an impact of ProSAPiP1 protein levels on dendritic spine maturation. Our results therefore suggest that ProSAPiP1 regulates SPAR levels to modulate dendritic spine maturity.
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Page | 96 Acknowledgements
8 Acknowledgements
My sincerest thanks go to all people who have helped and supported me in any way during my work. It is not possible to accomplish this work all by oneself. Therefore, I would like to further thank people, who have particularly been an important support:
I would like to especially thank Prof. Tobias M. Böckers for the opportunity to perform this thesis in the Institute for Anatomy and Cell Biology as one of the leading institutes in the field of Shank research. Your guidance and your mentorship was indispensable for this work and I truly enjoyed working in the institute as well as on interesting, yet sometimes quite challenging, projects. I am truly thankful for you always having an open door and ear for all ideas, questions, discussions, issues and concerns.
I further want to deeply thank PD Michael J. Schmeisser for the substantial supervision and inspiring discussions during this work. I am truly grateful for the intense time you spent in advancing the projects, providing help with the right ideas and directions to proceed, arranging several possibilities for participation in collaborative projects and discussions and being a great help and permanent support all time.
I would like to thank my Thesis Advisory Committee members Prof. Thomas Wirth and Dr. Chiara Verpelli as well as Prof. Carlo Sala and Prof. Gaia Novarino for their helpful discussions, support and input contributing to this work.
I also want to thank the International Graduate School in Molecular Medicine Ulm for the educational programme and the financial support.
I owe my deepest gratitude to all colleagues and friends in the lab, who have been such a great aid in the lab and who generate such great atmosphere: Sonja Halbedl, Alberto Catanese, Dominik Langgartner, Mascha Koenen, Claudia Soi, Silvia Cursano, Michael Schön, Francesca Rizzo, Constantin Mett, Susanne Gerlach-Arbeiter, Maria Manz, Oksana Kuc, Jan Philipp Delling, Tobias Weis, Christopher Heise, Ursula Pika- Hartlaub Natalie Damm and all other members of the Institute for Anatomy and Cell Biology. Thank you for your enormous support, help and advice, for sharing the times of happiness, challenge, success, defeat, craziness and fun all together as a team.
Finally, I want to greatly thank my friends and family for the limitless support and the wonderful time we are always spending together.
Thank you! Page | 97 Statutory declaration
9 Statutory declaration
I hereby declare that I wrote the present dissertation with the topic:
“Synaptic pathways related to Shank3 and its interaction partner ProSAPiP1”
independently and used no other aids that those cited. In each individual case, I have clearly identified the source of the passages that are taken word for word or paraphrased from other works. I also hereby declare that I have carried out my scientific work according to the principles of good scientific practice in accordance with the current „Satzung der Universität Ulm zur Sicherung guter wissenschaftlicher Praxis“ [Rules of the University of Ulm for Assuring Good Scientific Practice].
Ulm,
------Dominik Reim
Page | 98 List of publications
10 List of publications
Reim, D., and Schmeisser, M.J. Neurotrophic factors in mouse models of autism spectrum disorder: focus on Bdnf and Igf-1. Adv Anat Embryol Cell Biol (submitted).
Reim, D., Distler, U., Halbedl, S., Verpelli, C., Sala, C., Bockmann, J., Tenzer, S., Boeckers, T.M., and Schmeisser, M.J. (2017). Proteomic analysis of postsynaptic density fractions from Shank3 mutant mice reveals brain region specific changes relevant to autism spectrum disorder. Front Mol Neurosci.
Rothe, M., Kanwal, N., Dietmann, P., Seigfried, F., Hempel, A., Schütz, D., Reim, D., Engels, R., Linnemann, A., Schmeisser, M.J., Bockmann, J., Kühl, M., Boeckers, T.M., and Kühl, S. (2016). An Epha4/Sipa1l3/Wnt pathway regulates eye development and lens maturation. Development.
Reim, D., Weis, T.M., Halbedl, S., Delling, J.P., Grabrucker, A.M., Boeckers, T.M., and Schmeisser, M.J. (2016). The Shank3 Interaction Partner ProSAPiP1 Regulates Postsynaptic SPAR Levels and the Maturation of Dendritic Spines in Hippocampal Neurons. Front Synaptic Neurosci 8, 13.
Heise, C., Schroeder, J.C., Schoen, M., Halbedl, S., Reim, D., Woelfle, S., Kreutz, M.R., Schmeisser, M.J., and Boeckers, T.M. (2016). Selective Localization of Shanks to VGLUT1-Positive Excitatory Synapses in the Mouse Hippocampus. Front Cell Neurosci 10, 106.
Vicidomini, C., Ponzoni, L., Lim, D., Schmeisser, M.J., Reim, D., Morello, N., Orellana, D., Tozzi, A., Durante, V., Scalmani, P., Mantegazza, M., Genazzani, A.A., Giustetto, M., Sala, M., Calabresi, P., Boeckers, T.M., Sala, C., and Verpelli, C. (2016). Pharmacological enhancement of mGlu5 receptors rescues behavioral deficits in SHANK3 knock-out mice. Mol Psychiatry.
Schroeder, J.C., Reim, D., Boeckers, T.M., and Schmeisser, M.J. (2015). Genetic Animal Models for Autism Spectrum Disorder. Curr Top Behav Neurosci.
Distler, U., Schmeisser, M.J., Pelosi, A., Reim, D., Kuharev, J., Weiczner, R., Baumgart, J., Boeckers, T.M., Nitsch, R., Vogt, J., and Tenzer, S. (2014). In- depth protein profiling of the postsynaptic density from mouse hippocampus using data-independent acquisition proteomics. Proteomics 14, 2607-2613.
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