Abstract Autism spectrum disorders affect millions of individuals worldwide, but their heterogeneity complicates therapeutic intervention that is essentially symptomatic. A versatile yet relevant model to rationally screen among hundreds of therapeutic options would help improving clinical practice. Here we investigated whether neurons differentiated from pluripotent stem cells can provide such a tool using SHANK3 haploinsufficiency as a proof of principle. A library of compounds was screened for potential to increase SHANK3 mRNA content in neurons differentiated from control human embryonic stem cells. Using induced pluripotent stem cell technology, active compounds were then evaluated for efficacy in correcting dysfunctional networks of neurons differentiated from individuals with deleterious point mutations of SHANK3. Among 202 compounds tested, lithium and valproic acid showed the best efficacy at corrected SHANK3 haploinsufficiency associated phenotypes in cellulo. Lithium pharmacotherapy was subsequently provided to one patient and, after one year, an encouraging decrease in autism severity was observed. This demonstrated that pluripotent stem cell-derived neurons provide a novel cellular paradigm exploitable in the search for specific disease-modifying treatments. Abbreviations: ADHD, Attention Deficit Hyperactive Disorder; ADOS, Autism Diagnosis Observational Scale; ASD, autism spectrum disorders; DMSO, dimethylsulfoxyde; FDA, Food and Drug Administration; GAS, Global Assessment Scale; HTS, high throughput screening; hESC, human embryonic stem cells; iPSC, induced pluripotent stem cells; NSC, neural stem cells; PPIA, Peptidylprolyl Isomerase A; PPVT, Peabody Picture Vocabulary Test; PSC, pluripotent stem cells; RPM, Raven's progressive matrices; SHANK3, SH3 and multiple ankyrin repeat domains 3; SRS, Social Responsiveness Scale; VPA, valproic acid Keywords: Autism, SHANK3, High throughput screening, Valproate, Lithium, Drug repurposing Highlights * • Human neurons were used to screen for compounds correcting symptoms associated with SHANK3 haploinsufficiency syndrome. * • Screening criteria were the ability to increase SHANK3 expression and to increase glutamatergic transmission. * • Selected hit compounds were then validated using neurons differentiated from individuals with SHANK3 disrupting mutations. * • Lithium was selected and delivered to one of SHANK3 patient showing encouraging positive clinical outcomes after one year. The clinical heterogeneity between individuals affected by autism makes it difficult to anticipate the effectiveness of a treatment. Furthermore, clinical practice lacks biological tools to help make such decisions. Here we use neurons, produced from pluripotent stem cells derived from patients affected by SHANK3 haploinsufficiency syndrome, to test the efficiency of therapeutic compounds. We screened the biological activity of more than 200 compounds on SHANK3 expression. Lithium was ultimately selected and delivered to one patient with a SHANK3-disruptive mutation. This resulted in a positive outcome, as determined by improved autistic core symptoms, thus supporting the usefulness of this type of predictive approach. 1. Introduction Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders that affect 1% of the population in developed countries and are characterized by persistent impairment in reciprocal social communication and restricted repetitive patterns of behavior ([53]Newschaffer et al., 2007). Challenges in developing efficient pharmacotherapies for ASD reside in the limited understanding of ASD etiology, the difficulties to experimentally model the disease, the heterogeneity of symptoms and the large variety of potential triggers. Nonetheless, in around a third of patients a genetic cause has been identified ([54]Kumar and Christian, 2009) and there appears to be a convergence on mechanisms controlling synaptic homeostasis and neuronal connectivity ([55]Kumar and Christian, 2009, [56]Toro et al., 2010, [57]Bourgeron, 2015). Synapses and altered neuronal networks could be a relevant target to develop new therapeutic strategies for ASD ([58]Spooren et al., 2012, [59]Delorme et al., 2013). Improved understanding of the molecular substrates of autism is raising the hope of innovative “disease-modifying” treatments for altering the course of the disorder. However, while resulting in similar pattern core of symptoms, the synaptic/connectivity alterations in individuals with ASD show a considerable degree of heterogeneity, which may mask the potential beneficial effects of a tested treatment if it is not addressed properly to a subgroup of individuals stratified on the basis of the affected genes or pathways rather than on the clinical phenotype per se ([60]Delorme et al., 2013). This pleads for the design of new experimental and pre-clinical models to identify more personalized pharmacotherapies, approaches that require an access to relevant cellular models and tools that would allow analyzing at high throughput the effects of potential therapeutic compounds on human neurons. In this light, we have previously shown that glutamatergic cortical neurons can be specifically differentiated from pluripotent stem cells (PSC) of either embryonic origin (human embryonic stem cells, hESC) or reprogrammed from somatic cells of patients with ASD caused by SHANK3 haplo-insufficiency (human induced pluripotent stem cells, hiPSC), and that they can serve as a cellular paradigm for high throughput screening (HTS) campaigns ([61]Boissart et al., 2013). Permitting the systematic comparison of hundreds of small molecules in parallel, this can therefore accelerate identification of therapeutic compounds targeting pathophysiological mechanisms underlying distinct forms of ASD. The goal of the present study was to verify such a strategy by focusing on SHANK3 a key autism risk gene that codes for a synaptic scaffolding synaptic protein. The synaptic protein SHANK3 has been linked to autism in different genetic screens where deleterious mutations affecting the SHANK3 gene were present in 0.69 to 2.12% of individuals ([62]Durand et al., 2007, [63]Leblond et al., 2014). SHANK3 is an abundant component of the post-synaptic density (PSD) where it acts as a scaffolding protein recruiting key post-synaptic elements, such as glutamate receptors, and linking them to the actin cytoskeleton ([64]Boeckers et al., 2002). This scaffolding role contributes to the formation, stabilization and strengthening of the glutamatergic synapses and increases the efficiency of the glutamatergic transmission ([65]Grabrucker et al., 2011). SHANK3 Knock-Out mice recapitulate some key autistic behaviors and show reduced number and activity of glutamatergic synapses as well as loss in experience-linked plasticity ([66]Peca et al., 2011). At the cellular level, neurons differentiated from iPSC derived from individuals with SHANK3 haploinsufficiency, exhibit impaired electrophysiological responses to glutamatergic synapse stimulations that can be corrected by re-introducing SHANK3 cDNA expression ([67]Shcheglovitov et al., 2013). Decreased glutamatergic neurotransmission thus appears as a central feature of SHANK3 haploinsufficiency and it can be reversed by restoring correct dosage of SHANK3 even during adulthood ([68]Toro et al., 2010). In individuals with ASD, de novo loss-of-function mutations of SHANK3 reported in the literature affect only one allele of the gene, offering the opportunity to enhance transcription of the second allele, or improve mRNA stability and translation. We have therefore developed a high throughput molecular screening assay in order to pinpoint compounds increasing SHANK3 mRNA levels in human neurons derived from pluripotent stem cells. 2. Methods 2.1. Human Pluripotent Stem Cells (hPSC) Origin One hESC and 4 iPSC lines were used in this study. The male hESC line SA001 was obtained from Cellartis (Goteborg, Sweden). The work involving hESC line was supervised by the French Bioethics Agency (Agreement number NOR AFSB 12002 43S). The control iPSC line 1869 was published previously ([69]Boissart et al., 2013) and reprogrammed from fibroblasts obtained from the Coriell's biorepository (Coriell Institute for Medical Research, NJ, USA). The control line PB12 was reprogrammed from PBMC obtained from an anonymous blood donor at the French Blood Donor Organization. SHANK3-iPSC lines were derived from fibroblasts of 2 children with ASD carrying independent de novo SHANK-3 mutations. The 2 patients were diagnosed with autism and severe intellectual deficiency at the Robert Debré and Pitié-Salpétrière Hospitals according to DSM-IVTR criteria. Patient 1 (AUN-003, [70]Leblond et al., 2014) carries a de novo truncating mutation P.Glu809X in exon 21 and corresponds to iPSC line SHANK3-STOP. Patient 2 carries a frame shift mutation (c.3853_3857dup, p. Gly1287Alafs X15) and corresponds to the iPSC line SHANK3 frame-shift. Both were included initially in a national observational study (IDRCB 2008-A00019-46). After patient's legal representatives approval, 8-mm skin punch biopsies were obtained (study approval by Committee for the Protection of Persons, CPP no. C07-33). Fibroblasts were derived from the donated tissue and reprogrammed using the four human genes OCT4, SOX2, c-Myc, and KLF4 cloned in Sendai viruses (Life Technologies, Carlsbad, CA, USA) and iPSC lines characterized according to [71]Nakagawa et al. (2008). The same procedure was used to reprogrammed and characterized control iPSC lines. 2.2. Derivation of Cortical Neural Stem Cells (NSC) from PSC Commitment of PSC to the neural lineage and derivation of stable cortical NSC was described previously ([72]Boissart et al., 2012, [73]Boissart et al., 2013). Briefly, neural commitment was induced using the BMP inhibitor Noggin (500 ng/ml, Peprotech, London, UK) and the Nodal inhibitor SB431542 (20 μM, Tocris Biosciences, Ellisville, Missouri, USA). At day 10, neural rosettes containing neuro-epithelial cells were collected and plated en bloc in poly-l-ornithin/laminin treated culture dishes in N2B27 medium containing Epidermal Growth Factor (EGF, 10 ng/ml, Peprotech, Neuilly, France), FGF-2 (10 ng/ml, Peprotech) and Brain-derived Growth Factor (BDNF, 20 ng/ml, Peprotech). At confluence, the passages were performed using trypsin at a density of 50,000 cells/cm^2. Mass amplification was performed until passage 8 and cells were frozen. To start the terminal differentiation as post-mitotic neurons, cortical NSC were dissociated and plated in N2B27 without growth factors. 2.3. Compound Library Two hundred and two small molecules were investigated, belonging to two commercially available libraries (Screen-Well® Kinase Inhibitor library, Enzo-life Sciences, 76 compounds and Screen-Well® Epigenetics library, Enzo-life Sciences, 43 compounds), I-stem laboratory reference compounds ([74]Boissart et al., 2013, 50 compounds) and FDA approved drugs or related active principle (33 compounds). The complete list of compounds is provided in [75]Table S1. 2.4. Automated and High Throughput Quantification of SHANK3 mRNA in Human Neurons To start cortical neuron differentiation, NSC were dissociated and plated in N2B27 at a density of 6000 cells/wells in poly-l-ornithin/laminin pre-treated 384 well plates using the Bravo™ automated liquid handling platform equipped with a 384 pipette head (Agilent Technologies Inc., Santa-Clara, CA, USA). Half of the medium was changed twice a week. In those conditions, neuronal differentiation is achieved after 11 to 14 days. Kinetic of SHANK3 mRNA expression was established to determine the best time point to perform the screening ([76]Fig. S1) and day 14 was chosen since it offered the best dynamic range to quantify increase in SHANK3 mRNA expression. At day 14, compounds to be tested were added using the same platform in four replicates. The development and validation of the automated high throughput PCR assay by itself was performed following published standards for qPCR based HTS ([77]Bittker, 2012). mRNAs were extracted and directly converted in cDNA in the assay plate using the Fastlane technology (FastLane Cell Multiplex Kit, Qiagen, Courtaboeuf, France) with minor modifications. A duplex qPCR strategy was used, consisting in amplifying and quantifying both SHANK3 and the house keeping gene PeptidylProlyl Isomerase A (PPIA) in the same well (QuantiFast Probe Assay DP Kit). The robustness of this method was evaluated by performing it in 66 technical replicates. Ct values were consistent between technical replicates with minimal inter-well variations ([78]Fig. S1). In order to evaluate the sensitivity of the duplex TaqMan PCR to SHANK3 mRNA level modifications, SHANK3 specific shRNAs were used to artificially decrease the level of transcripts in PSC-derived neurons. Sister neuronal cultures were nucleofected (Amaxa, Lonza, Amboise, France) with non-targeting shRNAs as controls. The performance of the simplex method was compared with the automated duplex Taqman qPCR strategy and both strategies found equally efficient, indicating than automation and multiplexing had not compromised the sensitivity and specificity of the assay ([79]Fig. S1). Finally, the dynamics of SHANK3 mRNA synthesis was analyzed in order to estimate a relevant duration of treatment with the tested compounds. Neurons were treated with 5,6-dichloro-1-beta-d-ribofuranosylbenzimidazole (DRB) during 48 h to block mRNA production ([80]Fig. S1 [81]Sehgal et al., 1976). Treatment with 100 μM of DRB decreased SHANK3 mRNA content by 63%. After 24 h of release from DRB, SHANK3 mRNA contents were partially reconstituted and reached 80% of the non-treated cells. Neurons were, therefore, treated over 24 h for drug screening. The final screening workflow is summarized in [82]Fig. 1a. Fold change variations induced by compound treatments were calculated using the 2ΔCt method with DMSO-treated cells as controls and PPIA as the reference gene. Fig. S1. [83]Fig. S1 [84]Open in a new tab SHANK-3 screening assay development a) Quantification of SHANK-3 mRNA in hESC-derived differentiating neurons using manual mRNA extraction and SYBR green detection techniques. b) Expression of SHANK-3 protein in neurons at day 14. Scale bar = 200 μm c) Mean Ct values and standard deviations of SHANK-3 and PPIA detection using Duplex Taqman method evaluated in 66 technical replicates of DMSO treated neurons. ΔCt corresponds to Ct PPIA-Ct SHANK-3. d) Comparison of the sensitivity of the manual RNA extraction following by simplex SYBR green detection method with the automated RNA extraction combined with TaqMan duplex detection method using neurons transfected with control or SHANK-3 specific shRNAs. Results represent mean ± SD of 4 independent biological replicates. * p < 0.001 t-test. e) Determination of SHANK-3 mRNA turn over using the mRNA synthesis inhibitor 5,6-dichloro-1-beta-D-ribofuranosylbenzimidazole (DRB). Results represent mean ± SD of 3 independent biological replicates. * p < 0.001 t-test. Fig. 1. [85]Fig. 1 [86]Open in a new tab SHANK3 screening results. a) Screening work flow. b) Screening success rate. Among 202 molecules, 29 primary hits (increase of at least 30% of expression of the DMSO-treated wells which correspond to a statistical deviation of more than 2 σ) were identified. Independent re-testing confirmed 22 compounds. Dose response experiments revealed a concentration-dependent mode of action for 15 compounds. Among this list of 15 compounds, 6 were chosen for further investigation. c) Table summarizing the name of the 15 compounds demonstrating a dose-dependent effect on up-regulating SHANK3 mRNA, their known biological target or medical application and their performance in the primary screening. Results are presented as the mean fold-change values compared to DMSO treated cells and standard deviations (SD) of the 4 biological replicates. The 6 compounds chosen for further investigation are in red. 2.5. Automated Image-based High Content Screening For high-content screening assays, cells were fixed in 4% paraformaldehyde for 15 min at 4 °C. Primary antibodies ([87]Table S2) diluted in blocking buffer were applied overnight at 4 °C. Hoechst 33,258 (2 μg/ml, Sigma) and secondary antibodies conjugated to Alexa fluorophores (Molecular Probes, Eugene, Oregon, United States) were diluted at 1:1000 in blocking buffer and applied for 2 h at room temperature. To quantify synapses, image acquisition and analyses were performed using the ImageXpress® Micro XLS system (Molecular Devices, Sunnyvale, CA, USA). A presynaptic marker and a postsynaptic marker were used and multiplexed with the neuronal markers HuC/D and beta III Tubulin (anti-Tuj-1 antibodies) to identify neurons and create a “neurite” mask. An algorithm was then generated using MetaXpress™ software application modules in order to identify pre- and post-synaptic spots specifically located on neurites, then to count the number of spot co-localization (considered as synapses). Results were expressed as the density of spots for 100 μm of neurite. A minimum of 10 sites per well (approximately 2000 neurons) was analyzed. For neuritic network parameter analysis, image acquisition was performed using Cellomics Arrayscan system (Thermofischer Scientific, Waltham, MA, USA). Beta-III tubulin staining was used to track neurite using “Neuronal profiling” bioapplication as described in ([88]Boissart et al., 2013). 2.6. Spontaneous Calcium Oscillation Recording After 35 to 42 days of differentiation, neurons were treated during 120 h with compounds of interest in 384 well-plates. Cells were incubated for 10 min at 37 °C with the Fluo-4 probe diluted at 1 mM in a loading buffer (HBSS 1X, Hepes Buffer 20 mM, pH 7.4). After 3 washes with Mg^2 +-free Buffer (HBSS w/o CaCl2, w/o MgCl2, Hepes Buffer 20 mM, CaCl2 2 mM, pH = 7.4), neurons were recorded in the Mg^2 +-free Buffer. The fluorescence reading was performed with the ImageXpress® Micro XLS System at 37 °C. Neurons were recorded every second during 3 min with an exposure time of 350 ms. Total fluorescence curves were extrapolated using MetaXpress software. 2.7. Transcriptome Analysis For transcriptome analysis of gene expression perturbations induced by lithium and VPA, human neurons differentiated from the SA001 line were treated during 24 h with compounds and RNA extracted using RNAeasy extraction kit following manufacturer's instructions (Qiagen). Fifty ng of total RNA was reverse transcribed using the Ion AmpliSeq Transcriptome Human Gene Expression kit (Revision A.0) following the protocol of the manufacturer (Thermo Fisher Scientific). The cDNA libraries were amplified and barcoded using Ion AmpliSeq Transcriptome Human Gene Expression core panel and Ion Xpress Barcode Adapter (Thermo Fisher Scientific). The amplicons were quantified using Agilent High Sensitivity DNA kit before the samples were pooled in sets of eight. Emulsion PCR and Enrichment and loading was performed on the Ion Chef Instrument using the Ion PI IC 200 Kit (Thermo Fisher Scientific). Samples were loaded on an Ion PI v3 Chip and sequenced on the Ion Proton System using Ion PI IC Hi-Q 200 Kit chemistry (200 bp read length Thermo Fisher Scientific). The output files (FASTQ files) were imported into the RNA-seq pipeline of Partek Flow software (v 4.0, Partek Inc., St Louis, MO, USA) using hg19 as a reference genome. To determine genes that are differentially expressed between groups mapped reads were quantified using Partek E/M algorithm (the resulting counts represent the gene expression levels for over 20,800 different genes present in the AmpliSeq Human Gene Expression panel) and differentially expressed gene were identified using Partek Gene Specific Analysis (GSA) algorithm. Biological interpretations of the list of differentially expressed genes were performed using Partek Flow v4.0 and the pathway analysis plateform EnrichR ([89]Chen et al., 2013). 2.8. Statistical Analyses Data were subjected to ANOVA following by a t-test to evaluate statistical differences between cells treated with tested compounds and DMSO-treated controls. The number of biological replicates, corresponding to independent differentiations or neuronal cultures, is indicated in figure legends. 3. Results 3.1. Screening of Compounds Regulating SHANK3 mRNA Expression in Human Neurons Differentiated from hESC A collection of 202 compounds was chosen for the primary screening of SHANK3 regulators. This collection included a set of FDA-approved therapeutic compounds widely used for a variety of psychiatric and neurological diseases including epilepsy, bipolar disorders, major depressive disorders or schizophrenia. It also included epigenetic regulators, kinase inhibitors and compounds identified previously as modulators of neurogenesis ([90]Boissart et al., 2013) ([91]Table S1). Reprogramming of somatic cells into iPSC being potentially responsible for induction of epigenetic and imprinting alterations that could bias the study of gene regulation ([92]Pick et al., 2009, [93]Urbach et al., 2010, [94]Lister et al., 2011), the primary drug screening was conducted using neurons differentiated from the control hESC line SA001. The 202 compounds were screened in 4 biological replicates at one concentration determined for each compound based on data from the literature or from our own previous findings ([95]Boissart et al., 2013, [96]Georges et al., 2015). This primary drug screening identified 29 primary hits that increased SHANK3 mRNA content by at least 30% as compared to DMSO-treated cells and with a deviation from the DMSO mean of more than 2 σ ([97]Fig. 1b and [98]Table S1). Re-testing of these 29 hits in an independent experiment confirmed 22 compounds ([99]Fig. 1b). Dose-response experiments were then conducted and revealed a concentration-dependent mode of action for 15 of them ([100]Fig. 1b and c). Among this list of 15 compounds, 6 were chosen to be further investigated: 5 FDA-approved compounds (fendiline dihydrochloride, lithium, valproic acid, aripiprazol and fluoxetine) and the 5-lipoxygenase inhibitor BWB-70C since it regulated a pathway that can be targeted by the FDA-approved compound Zileuton. The optimal concentrations for each pharmacological compound were determined from the mRNA dose-response curves, and defined as follows: lithium 0.5 mM, valproic acid (VPA) 2 mM, aripiprazol 7.5 μM, fluoxetine 10 μM, fendiline 5 μM, BWB70C 40 μM ([101]Fig. S2). Fig. S2. [102]Fig. S2 [103]Open in a new tab Concentration – response curves of the 6 chosen compounds. Results are expressed as Fold-change compared to DMSO-treated cells and presented as mean ± SD of 3 independent replicates. 3.2. Modification of SHANK3 Synaptic Content and Neuronal Activity by Hit Compounds The functional potential of the six drugs was first evaluated in neurons derived from the SA001 hESC line. SHANK3 protein levels and its recruitment to the glutamatergic synapses, as well as increased glutamatergic activity of neuronal network were used as indicators of compound efficacy. The time course of synaptogenesis was analyzed by quantifying the number of spots of the pre-synaptic protein Synapsin and of the post-synaptic density component PSD-95 present on neurites, a co-localization suggesting a glutamatergic synapse ([104]Fig. 2a). In untreated hESC-derived neuronal cultures, expression of Synapsin and PSD-95 in the neuritic compartment progressively increased from day 14 to 28 and synapses were clearly present at day 28. The effects of the 6 compounds on SHANK3 synaptic content was therefore analyzed at that later stage. In order to optimally quantify SHANK3 protein production following treatment, cells were exposed to compounds for at least 120 h. Fig. 2. [105]Fig. 2 [106]Open in a new tab Effect of hit compounds on SHANK3 protein expression and synaptic location. a) Time course analysis of synapse formation in hESC-derived developing neurons. Results are expressed as mean ± SD of 3 independent neuronal cultures (biological replicates, left panel). Representative images of the pre-synaptic marker Synapsin (green) and the post-synaptic marker PSD-95 (red) are shown on the right panels. Arrow indicates example of co-localization of PSD-95 and Synapsin signaling structural synapses. b) Quantification of SHANK3 protein expression on dendrites after treatment with hit compounds. Results are expressed as mean ± SD of 6–8 independent neuronal culture/ treatment (biological replicates) and as fold change compared to DMSO-treated cells. * p < 0.01 t-test c) Quantification of SHANK3 protein co-localization with synapsin and PSD-95 after compound treatment. Results are expressed as fold change of DMSO treated cells (mean ± SD, 6–8 biological replicates par treatment). d) Representative image of SHANK3 (green) co-localization with synapsin (red). Scale bar = 50 μm. (For interpretation of the references to color in this figure legend, the reader is referred to