Protein targets of E3 ubiquitin ligase (UBE3A)

Abstract

The present invention relates to the UBE3A protein target and its use as a biomarker of target engagement for compounds that modulate ube3a expression.

Description

[Technical field]

[0001] The present invention provides novel biomarkers whose protein expression levels are modulated when protein levels of ubiquitin-protein ligase E3A (UBE3A) are increased or decreased, and their use in drug development. [Background technology]

[0002] 2. Background of the Invention Angelman syndrome is characterized by severe intellectual and developmental disabilities, sleep disorders, epileptic seizures, jerky movements, EEG abnormalities, frequent laughter or smiling, and severe speech impairment. Angelman syndrome is a neurogenetic disorder caused by the deletion or inactivation of the UBE3A gene and thus the protein on maternally inherited chromosome 15q11.2. Meanwhile, Dup15q syndrome is a clinically identifiable syndrome resulting from a duplication of chromosome 15q11-13.1. In Dup15q syndrome, there is overexpression of UBE3A. In Angelman syndrome (AS), neuronal loss of the E3 ubiquitin ligase UBE3A leads to excessive severe neurological impairment.

[0003] Neuronal loss of UBE3A leads to AS, but knowledge of the downstream molecular and cellular dysfunction is lacking. Identification of relevant UBE3A substrates will provide a better understanding of the role of Ube3a function in health and disease and aid in the discovery of both drugs and biomarkers to monitor UBE3A function. Summary of the Invention

[0004] The present invention relates to novel biomarkers whose protein expression is modulated when the protein levels of Ubiquitin-Protein Ligase E3A (UBE3A) are increased or decreased, some of which form protein complexes with UBE3A. These include the proteins TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3. The invention further relates to pharmaceutical biomarkers and methods for the detection of UBE3A activity based on these proteins for pharmaceutical treatments for diseases that target UBE3A, including Angelman syndrome, 15qdup syndrome, and other autism spectrum disorders. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0005] Detailed Description of the Invention In a first aspect, the present invention provides a method for measuring the regulation of expression of a UBE3A protein in a tissue sample, comprising the steps of: a) providing a tissue sample from an animal or cell culture treated with a UBE3A modulator; b) measuring the protein expression level in the sample of step a) of at least one protein selected from the group consisting of TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3; c) comparing the protein expression level of the at least one protein determined in step b) with the protein expression level of the at least one protein in a control sample; wherein the modulated protein expression level of the at least one protein measured in step b) compared to the protein expression level of the at least one protein in a control sample is indicative of modulation of expression of the UBE3A protein.

[0006] In a second aspect, the present invention provides a method for measuring induction of expression of UBE3A protein in a tissue sample, comprising: a) providing a tissue sample from an animal or cell culture treated with a UBE3A inducer; b) measuring the protein expression level in the sample of step a) of at least one protein selected from the group consisting of TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3; c) comparing the protein expression level of the at least one protein determined in step b) with the protein expression level of the at least one protein in a control; wherein a decreased protein expression level of the at least one protein measured in step b) compared to the protein expression level of the at least one protein in a control is indicative of an induced expression of the UBE3A protein.

[0007] In a further aspect, the present invention provides a method for determining the engagement of a UBE3A modulator with a UBE3A target, comprising: a) providing a tissue sample from an animal or cell culture treated with a UBE3A modulator; b) measuring the protein expression level in the sample of step a) of at least one protein selected from the group consisting of TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3; c) comparing the protein expression level of the at least one protein determined in step b) with the protein expression level of the at least one protein in a control; wherein a modulated protein expression level of the at least one protein measured in step b) compared to the protein expression level of the at least one protein in a control is indicative of engagement of the UBE3A modulator with a UBE3A target.

[0008] In a further aspect, the present invention provides a screening method for identifying a modulator of UBE3A protein expression, comprising the steps of: a) providing a tissue sample from an animal or cell culture that has been treated with a test compound; b) measuring the protein expression level in the sample of step a) of at least one protein selected from the group consisting of TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3; c) comparing the protein expression level of the at least one protein determined in step b) with the protein expression level of the at least one protein in a control; wherein a modulated protein expression level of the at least one protein measured in step b) compared to the protein expression level of the at least one protein in a control is indicative of a UBE3A protein expression modulator.

[0009] In certain embodiments, the tissue sample is a blood sample, a plasma sample, or a CSF sample.

[0010] In certain embodiments, protein expression levels are measured using Western blotting, mass spectrometry (MS), liquid chromatography mass spectrometry (LC-MS), or immunoassays.

[0011] In certain embodiments, the UBE3A modulator is an antisense oligonucleotide, particularly an LNA antisense oligonucleotide.

[0012] In certain embodiments, the UBE3A modulator is a UBE3A protein expression level inducer for the treatment of autism spectrum disorder, Angelman syndrome, or 15qdup syndrome.

[0013] In a particular embodiment, the proteins in step b) are selected from the group consisting of TKT, DZANK1, UBLCP1 and PSME3, the expression levels of which are inversely correlated with the expression level of UBE3A.

[0014] In a particular embodiment, the proteins in step b) are selected from the group consisting of ACYP1, YARS, WARS and SOD2, the expression levels of these proteins directly correlate with said expression levels of the UBE3A protein expression level.

[0015] In a further aspect, the present invention relates to the use of a protein selected from the group consisting of TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3 as a biomarker for regulating UBE3A protein expression levels.

[0016] In a particular embodiment of the use of the present invention, the modulation of UBE3A is by an inducer of UBE3A protein expression level.

[0017] In a particular embodiment of the use of the present invention, the biomarker proteins are selected from the group consisting of TKT, DZANK1, UBLCP1 and PSME3, the protein expression levels of these biomarker proteins being inversely correlated with the UBE3A protein expression level.

[0018] In a particular embodiment of the use of the present invention, the biomarker proteins are selected from the group consisting of ACYP1, YARS, WARS and SOD2, the protein expression levels of these biomarker proteins directly correlate with the UBE3A protein expression level.

[0019] In a particular embodiment of the use of the present invention, the present invention provides a method for determining the engagement of a UBE3A protein expression level regulator with a UBE3A target.

[0020] In a particular embodiment of the use of the present invention, the UBE3A protein expression level regulator is an antisense oligonucleotide, in particular an LNA antisense oligonucleotide.

[0021] In a particular embodiment of the use of the present invention, the UBE3A protein expression level regulator is a UBE3A protein expression level inducer for the treatment of autism spectrum disorder, Angelman syndrome, or 15qdup syndrome.

[0022] definition The term "protein", as used herein, unless otherwise indicated, refers to any naturally occurring protein from any vertebrate source, including mammals such as primates (e.g., humans) and rodents (e.g., mice and rats). The term encompasses the "full-length", unprocessed protein, and any form of the protein that results from processing in a cell, as well as peptides derived from the naturally occurring protein. The term also encompasses naturally occurring variants, such as splice variants or allelic variants. The amino acid sequences shown in Table 2 are exemplary amino acid sequences of the biomarker proteins of the invention.

[0023] In the present invention, a UBE3A protein expression level regulator refers to a molecule that can reduce or enhance the protein expression level of UBE3A. A regulator that can reduce the protein expression level of UBE3A is referred to as a UBE3A inhibitor, and a regulator that can enhance the protein expression level of UBE3A is referred to as a UBE3A enhancer. The UBE3A regulator can be an mRNA interfering RNA molecule. In another embodiment, the UBE3A regulator is a double-stranded RNA (dsRNA), such as a short interfering RNA (siRNA) or a short hairpin RNA (shRNA). The double-stranded RNA can be any type of RNA, including, but not limited to, mRNA, snRNA, microRNA, and tRNA. RNA interference (RNAi) is particularly useful for specifically inhibiting the production of a particular RNA and / or protein. The design and creation of dsRNA molecules suitable for the present invention is within the skill of the art, with particular reference to WO99 / 32619, WO99 / 53050, WO99 / 49029, and WO01 / 34815. Preferably, the siRNA molecule comprises a nucleotide sequence having about 19-23 consecutive nucleotides identical to the target mRNA. The term "shRNA" refers to an siRNA molecule that is paired with a complementary sequence on the same RNA molecule by less than about 50 nucleotides, and the sequence and the complementary sequence are separated by an unpaired region of at least about 4-15 nucleotides (forming a single-stranded loop on the stem structure generated by the two base-complementary regions). There are well-established siRNA design criteria (see, for example, Elbashire et al., 2001).

[0024] The UBE3A regulator can be an antisense oligonucleotide that can regulate the expression of a target gene by hybridizing to a target nucleic acid, particularly a continuous sequence on the target nucleic acid. The antisense oligonucleotide is not double-stranded in nature, and therefore is not an siRNA or shRNA. Preferably, the antisense oligonucleotide is single-stranded. It is understood that a single-stranded oligonucleotide can form a hairpin or intermolecular duplex structure (a duplex between two molecules of the same oligonucleotide), as long as the degree of intra or inter self-complementarity over the entire length of the oligonucleotide is less than 50%. The UBE3A regulator can be a gene therapy that establishes the expression of functional UBE3A protein in a patient in need thereof.

[0025] The term "control sample" refers to a sample that is not treated with a UBE3A modulator. For example, a control sample is a sample of a cell culture that is not treated with a UBE3A modulator, or the cell culture is treated with a compound that is not a UBE3A modulator (negative control).

[0026] The expression levels of the UBE3A marker proteins TKT, DZANK1, UBLCP1 and PSME3 are inversely correlated with the expression levels of UBE3A protein, i.e., low levels of UBE3A protein are correlated with high expression levels of these marker proteins and increased levels of UBE3A protein are correlated with decreased expression levels of these marker proteins.

[0027] The expression levels of the UBE3A marker proteins ACYP1, YARS, WARS and SOD2 are directly correlated with the expression levels of UBE3A protein, i.e., low levels of UBE3A protein expression correlate with low expression levels of these marker proteins and increased levels of UBE3A protein correlate with increased expression levels of these marker proteins. [Brief description of the drawings]

[0028] [Figure 1]AS mice display proteomic alterations at birth, which are exacerbated during adolescence and adulthood. Figure 1A: Schematic of the experimental design. Control and AS mice were sacrificed at P1, P21 and P56. Pooled cortical tissue from control and AS animals was used to generate sample-specific spectral libraries for data-independent acquisition (DIA) mass spectrometry. Individual samples were run in DIA mode and data were analyzed using sample-specific libraries. Protein expression data were subjected to statistical and pathway enrichment analysis. Figure 1B: UBE3A raw protein intensity plots of control and AS mouse cortex at P1, P21 and P56 plotted as percentage of P1 control protein levels (mean ± SEM n = 5-6). Figure 1C: Partial least squares discriminant analysis (PLS-DA) performed on the whole proteome of control and AS mouse cortex resolved according to age (T1; P1, P21 and P56) and genotype (T3; control and AS). Figure 1D: Pathway enrichment plot showing normalized enrichment scores using 1D annotation features using GO: cellular component gene sets in AS vs. control mice. Figure 1E: Average Z-score heatmap per time point of significantly changed (p-value < 0.05) proteins in AS vs. control mice. Clusters are defined using Euclidean distance based on the UPGMA method. [Diagram 2]Pathway changes in amino-acyl-tRNA synthetases, proteasomes and synapses are developmentally regulated. Figure 2A: Average Z-scored heatmap per time point for amino-acyl-tRNA synthetase multienzyme complexes and amino-acyl-tRNA synthetases. Clusters are defined using Euclidean distance based on the UPGMA method. Figure 2B: Time course expression of selected proteins from the amino-acyl-tRNA synthetase pathway showing upregulated (Aimp1, Mars) and downregulated (Yars, Wars) sets in AS vs. control. Values ​​represent Z-scored values. Error bars: sem Figure 2C: Average Z-scored heatmap per time point for proteasome complexes based on their subunit classification. Clusters are defined using Euclidean distance based on the UPGMA method. FIG. 2D: Time course expression of selected protein pathways showing upregulated set of proteins from 20S core proteasome subunits (Psma5, Psmb1, Psmb2), 19S proteasome regulatory subunits (Psmc3, Psmc4 and Psmd11) and proteasome interacting proteins (Ublcp1, Uchl5 and Usp14) in AS vs. control. Values ​​represent Z-scored values. Error bars: sem. FIG. 2E: Average Z-scored heatmap per time point for proteins belonging to the term synapse that were significantly changed (p-value < 0.05) at time point P56. Clusters are defined using Euclidean distance based on the UPGMA method. Clustering shows a division between proteins upregulated in AS (red cluster) and proteins downregulated in AS (blue cluster). FIG. 2F: Sunburst visualization of proteins upregulated in AS (F) or downregulated in AS (G). These genes have been annotated against the SynGO CC (SynGO). The colors of the sunburst plots represent the enrichment Q-score of the UP (red) or DOWN (blue) set against the entire measurable proteome (7126 proteins) as background. Proteins belonging to the edge furthest from the central synaptic term are labeled. [Diagram 3]Adult AS rats recapitulate the proteomic changes observed in AS mice across different brain regions. Figure 3A: Schematic of the experimental design. Control and AS rats were sacrificed at P84. Pooled tissues of cerebellum (CB), cortex (CX) and hippocampus (HC) of control and AS animals were used to generate sample-specific spectral libraries in DDA (data-dependent acquisition) mode. Individual samples were further analyzed using data-independent acquisition (DIA) mass spectrometry. Figure 3B: UBE3A raw protein intensity plots (mean ± SEM) of cerebellum (CB), cortex (CX) and hippocampus (HC) of control and AS rats plotted as percentage of CB control protein levels. Figure 3C: Partial least squares discriminant analysis (PLS-DA) performed on the whole proteome of control and AS rats separated according to brain region (T1 and T2; cerebellum, cortex, hippocampus) and genotype (T3; control and AS) and projected in 3D space. Figure 3D: Venn diagram of statistically significant (adjusted p-value < 0.05) proteins changed in each brain region in AS rats. Figure 3E: Heat map of proteins passing statistical significance in the cerebellum. Proteins fall into two categories: up- or down-regulated in AS compared to cerebellar controls. Figure 3F, Figure 3G, and Figure 3H: Volcano plot of p-value vs. Log2 fold change per brain region. Proteins that are statistically significant in each pairwise comparison are highlighted (blue: CB, green: HC, yellow: cortex). Proteins significant in all three brain regions are indicated with black stars. A subset of proteins of interest from Figure 1E are labeled. Figure 3I, Figure 3J, and Figure 3K: Log2 fold change correlation plots between mouse and rat cortex for proteins in the aminoacyl-tRNA synthase pathway (G), proteasome subunits (H), and synaptic proteins (I), filtered from Figure 2F. Correlation coefficients are calculated using Pearson's method. [Figure 4]Restoration of UBE3a in both young and adolescent AS mice rescues protein and pathway alterations. Figure 4A: Schematic of experimental design. Control mice (WT; CreERT2+), AS mice (Ube3aStop / +; CreERT2-), and Ube3a-restored mice (Ube3aStop / +; CreERT2+) were injected with tamoxifen at P21 or P56 and sacrificed at P84. Cortical tissues from both control and AS mice were pooled to create sample-specific spectral libraries in DDA (data-dependent acquisition) mode. Individual samples were further analyzed in data-independent acquisition (DIA) mode. Figure 4B: UBE3A raw protein intensity plots (mean ± SEM) in the cortex of P21 and P56-injected groups of control, AS, and UBE3A-restored mice plotted as a percentage of P21 control protein levels. Figure 4C: Partial least squares discriminant analysis (PLS-DA) performed on the whole proteome of control and AS mouse cortex separated according to time point of UBE3A restoration (T1; P21 and P56) and genotype (T2; control, AS, and restored). Figure 4D: Pathway enrichment plot showing normalized enrichment scores using 1D annotation features using GO: cellular component gene sets in AS mice vs. control mice (blue), Ube3a restored AS mice vs. control at P21 (red) and UBE3A restored AS mice vs. control at P56 (blue). Selected pathways are visualized as observed in Figure 1D. Figure 4E: Heatmap of significantly changed hits between any of the four conditions using ANOVA (adjusted p-value < 0.05). Colors represent the average Z-scored protein intensity for each protein. Figure 4F: Orthogonal validation of UBE3A targeting in independent sample sets of control mice (N=3), AS mice (N=4), and UBE3A restored mice at P21 (N=4) by capillary Western blotting. Statistical analysis was performed using one-way ANOVA followed by Tukey's post-hoc test. (*p<0.05, **p<0.01, ****p<0.0001). [Diagram 5]Transketolase is a direct nuclear target of UBE3A deregulated in rodent and human AS disease models. Figure 5A: Capillary Western blot analysis of Ube3a targets in control, control+UBE3A KD ASO and AS lines of hiPSC-derived neurons. N=3 for all samples. Statistical tests were performed using one-way ANOVA followed by Tukey's post-hoc test. (*p<0.05, **p<0.01, ***p<0.001 ****p<0.0001). Figure 5B: Immunocytochemical images of transketolase (TKT) and the neuronal marker MAP2 in control, control+UBE3A KD ASO and AS lines of hiPSC-derived neurons. Nuclei were counterstained with DAPI. Scale bar: 25 μm. Figure 5C: Quantification of nuclear TKT signal in neurons (MAP2 positive) and non-neuronal cells (MAP2 negative). Individual data points from eight images obtained from different wells in two independent experiments (neuronal differentiation and ASO treatment) were plotted. Statistical analysis was performed using the Kruskal-Wallis test followed by Dunn's post-hoc test. Figure 5D: Immunohistochemical images of transketolase (TKT) and the neuronal marker NEUN in the primary sensory cortex of adult control and AS rats. Nuclei were counterstained with DAPI. Scale bar: 25 μm. Figure 5E: Quantification of nuclear TKT signal in neurons (NEUN positive) and non-neuronal cells (NEUN negative). Individual data points from three images per animal were plotted (control: N = 3, AS: N = 2 animals). Statistical analysis was performed using the Kruskal-Wallis test followed by Dunn's post-hoc test. Figure 5F: Bacterial ubiquitination assay for TKT and RING1B. Figure 5G: Immunohistochemical images of transketolase (TKT) and the neuronal marker NEUN in the primary sensory cortex of adult control and AS rats. Nuclei were counterstained with DAPI. Scale bar: 25 μm. Figure 5F: Immunohistochemical images of transketolase (TKT) and the neuronal marker NEUN in the primary sensory cortex of adult control and AS rats. Nuclei were counterstained with DAPI. Scale bar: 25 μm. Figure 5E: Quantification of nuclear TKT signal in neurons (NEUN positive) and non-neuronal cells (NEUN negative). Capillary Western blot analysis of TKT in mice (KO) (*p<0.05, ****p<0.0001). EXAMPLES

[0029] AS mice exhibit proteomic alterations at birth that are exacerbated throughout postnatal development Data-independent acquisition (DIA) mass spectrometry-based proteomics has emerged as the method of choice for label-free quantitative proteomics due to its reproducibility, coverage depth, and greater dynamic range compared to classical data-dependent acquisition (DDA) [17, 18]. We chose DIA to quantify proteomic changes over the course of mouse cortical development at postnatal days P1, P21, and P56 from control and AS mice. Pooled samples of control and AS cortex from all time points were generated, fractionated, and measured in DDA mode, yielding a sample-specific spectral library containing 8,270 proteins (77,439 unique peptides). Individual samples were then measured in DIA mode, and the DIA data was analyzed using the sample-specific library to quantify 7,187 proteins across all samples. Protein level data were then subjected to differential protein expression profiling analysis at each time point, and pathway enrichment analysis was performed (Figure 1A). The median biological coefficient of variation (%Cov) of observed proteins in each condition was 11–15%, consistent with literature reports for DIA

[17] .

[0030] UBE3A protein was significantly decreased in AS compared to control mice at all time points (<20% of control levels, adjusted p-value <0.05). UBE3A expression levels decreased from P1 to P56 in both controls and AS, consistent with the observation that complete silencing of the parental UBE3A allele in neurons occurs during postnatal development [19, 20] (Figure 1B). Partial least squares discriminant analysis (PLS-DA) of all proteins separated samples by both age (T1) and genotype (T3), with P21 and P56 being significantly different from P1. Separation along T3 revealed that AS mice gradually diverged from control mice with regard to their proteomic profile, with the greatest difference in the adult brain (P56) (Figure 1C).

[0031] Pathway enrichment analysis of all proteins using GO: cellular component (GO: CC) revealed upregulation of aminoacyl-tRNA synthetases and proteasome complexes at all postnatal stages, whereas pre- and post-synaptic pathways were significantly altered at P56, consistent with synaptic maturation (Figure 1D). Next, we aimed to identify differentially regulated proteins at each developmental stage and observe these differences over time. Twenty-eight proteins (Figure 1E) were significantly (q-value < 0.05) regulated between control and AS mice at any time point. Hierarchical clustering of these proteins revealed genotype- and developmental stage-dependent effects of co- and counter-regulation of proteins with respect to UBE3A expression. Although some proteins, such as the metabolic enzyme TKT (transketolase), were altered only at P21 and P56, several other proteins, such as MIOS (a component of the GATOR2 complex), the microtubule protein KIF3C, and the ovarian tumor domain (OTU)-containing deubiquitinating cysteine ​​protease OTUB2, showed dysregulation at all time points ( Fig. 1E ; fig. S2).

[0032] Interestingly, the abundance of proteins belonging to the aminoacyl-tRNA synthetase pathway (QARS, DUS3L, YARS) was both increased and decreased in AS at different time points, whereas the proteasome subunits UBLCP1, UCHL5, PSME3 were increased at all time points, necessitating further investigation of these pathways.

[0033] Developmentally regulated pathway changes in amino-acyl-tRNA synthetases, proteasomes, and synapses in AS mice Next, we investigated the trajectories of individual proteins within the altered pathway. Aminoacyl-tRNA synthetases (ARS) are evolutionarily conserved enzymes involved in the ligation of amino acids to their cognate tRNAs, and exist either free or as part of the ARS multienzyme complex (MSC)

[21] . We examined the expression of all ARS and MSC proteins across brain maturation (Figure 2A), which revealed that class I ARS proteins, specifically MARS, QARS, RARS, AIMP1 and AIMP2, which belong to MSC, are increased in AS. Conversely, ARS proteins involved in aromatic amino acid loading, namely tryptophanyl-tRNA synthetase WARS and tyrosyl-tRNA synthetase YARS, were decreased in AS (Figure 2A). Interestingly, there was a strong decrease in these proteins during postnatal brain development, regardless of genotype, with a dramatic deviation in disease changes at P21 and P56 in AS (Figure 2B).

[0034] Proteins corresponding to all components of the proteasome were persistently altered from birth to adulthood. Disease-specific molecular trajectories were revealed following individual proteins of the proteasome machinery, including subunits of the 11S and 19S regulatory particles, the 20S core subunit, and proteasome-interacting proteins

[22] (Fig. 2C). We observed a consistent increase in the abundance of several proteasome-interacting proteins (UCHL5, UBLCP1, USP14) as well as proteins belonging to the 11S and 19S regulatory subunits (PSMD11, PSMC3, PSMD1, PSME3), while changes in the 20S core proteasome subunit followed a similar trend but were relatively minor (Fig. 2C, D). Thus, UBE3A leads to an overall increase in proteasome subunits and accessory proteins throughout development, with the most prominent changes seen in the 11S and 19S regulatory subunits and a subset of proteasome-associated proteins.

[0035] Next, we examined synaptic proteins that were selectively altered in AS mice at P56 (AS vs. controls, q-value < 0.05) but not at P1 or P21, and found 63 proteins that met these criteria (Figure 2E). Heatmap visualization and hierarchical clustering of these proteins revealed a bidirectional AS genotype effect, with sets of proteins being upregulated (red cluster, 40 proteins) and downregulated (blue cluster, 23 proteins) in AS vs. controls. To determine whether these two sets of proteins were enriched in specific synaptic subcompartments, we performed pathway enrichment analysis using SynapseGO, a high-quality, manually annotated synaptic GO database

[23] . SynGO CC enrichment analysis for the upregulated set of 40 proteins showed that they were distributed at both pre- and postsynaptic sites. Proteins belonging to synaptic vesicles and presynaptic active zones (STX1A, SYP, VAMP2), as well as proteins that are essential components of the postsynaptic density (GRIA3, ATP2B2, LRRC2), were significantly enriched (FDR-adjusted p-value < 0.05) (Figure 2F, top; Data Table S3). SynGO analysis revealed that proteins decreased in AS also belong to both presynaptic and postsynaptic compartments. Specifically, synaptic vesicle proteins (STXBP5, SLC6A2, ATP6V0C) and postsynaptic density proteins (GRK2, KPNA1, PAK1, PTPRF) were decreased at P56 in AS.

[0036] Thus, protein changes in AS mice are dynamic; ARS and proteasome subunits are altered from birth, whereas many changes in synaptic proteins develop over the final stages of brain maturation.

[0037] Adult AS rats recapitulate the proteomic alterations observed in AS mice across different brain regions. We next investigated whether the observed changes were conserved across species and brain regions in AS rat models by taking advantage of the newly available AS rat model

[24] . We performed DIA-based LC-MS analysis of three rat brain regions (CB: cerebellum, HC: hippocampus, CX: cortex) in adult (P84) control and AS rats (Figure 3A). Hybrid spectral libraries were generated from DDA runs on fractionated pooled samples of all three brain regions from all samples combined with DirectDIA measurements to generate a library of 8,928 proteins (116,603 unique peptides), allowing the quantification of 7,525 proteins across all samples. The coefficient of variation was approximately 10% per sample type. UBE3A expression was robustly reduced in all three brain regions in AS rats (Figure 3B). Similar to mice [25, 26]. Although UBE3A levels in the cerebellum of control rats were lower compared to the hippocampus and cortex, residual UBE3A levels in AS rat cerebellum were higher (27% of control levels in cerebellum vs. less than 10% of control levels in hippocampus and cortex; Fig. 3B). Subsequent PLS-DA analysis revealed a robust separation between genotypes (T3) and brain regions (T2, T1) (Fig. 3C). The proteomic profile of the cerebellum was distinct from the cortex and hippocampus, which shared more similarities with each other, likely reflecting different developmental origins and cytoarchitectures.

[0038] Examination of significantly changed proteins in the brains of AS rats revealed that 34 proteins were altered across all three brain regions, with a large overlap in changes in the hippocampus and cortex (Fig. 3D). Significant hits in the cerebellum were visualized by hierarchical clustering, revealing a set of upregulated (blue cluster) and downregulated (green cluster) proteins (Fig. 3E). Some of the proteins that were altered in the cerebellum showed directional trends in the cortex and hippocampus but did not meet the statistical cutoff. Interestingly, several proteins (including GSTO1, DAB2IP, ASNS, AGAP1) were specifically altered in the cerebellum in AS suggesting cerebellar neuron-specific regulation of these substrates. Proteins belonging to proteasome subunits (including UBLCP1, UCHL5, PSME3) as well as the ARS proteins YARS and WARS were altered in all three brain regions (Fig. 3F,G,H, black stars).

[0039] Next, we examined the correlation between altered proteins corresponding to the three major pathways in AS P56 mouse and rat cortex (Figure 3I-K), as well as across rat brain regions. We subdivided each pathway into a set of proteins that were upregulated (red) or downregulated (blue) in AS mouse cortex at P56 compared to controls. A correlation plot of fold changes for the ARS pathway revealed a significant correlation between rats and mice (R=0.66, p=4.29E-004), with YARS, WARS, and GARS downregulated and MARS, VARS, AIMP1, and AIMP2 upregulated in AS in both mice and rats (Figure 3I).

[0040] Proteasome complex proteins showed strong correlations between rat and mouse cortex (Figure 3J) (R = 0.49, P = 2.12E-004) and across brain regions. Ubiquitin-like domain-containing CTD phosphatase 1; UBLCP1, ubiquitin carboxyl-terminal hydrolase isoenzyme L5; UCHL5 and proteasome activator complex subunit 3; PSME3 were consistently upregulated in adult rats across all three brain regions (Figure 3J). Proteasome assembly chaperone 3; PSME3 and 26S proteasome non-ATPase regulatory subunit 10; PSMD10 were consistently downregulated in AS compared to controls in AS mice as well as AS rat brain regions. As with the aminoacyl-tRNA synthetase pathway, the cortex and hippocampus showed more similarity to each other, with the cerebellum deviating slightly.

[0041] Analysis of synaptic protein changes showed both similarities and differences between species and across rat brain regions (Figure 3K). AS rat cortex was similar to both mouse cortex (R = 0.53, P = 4.86E-006) and rat hippocampus (R = 0.56, P = 1.59E-006), but AS cerebellum diverged (R = 0.21, P = 8.60E-002). Interestingly, synaptic proteins GAD2, ACHE, PLCXD3, and GRK2 were downregulated in AS across all brain regions and species, whereas PSD, DLG4, PLCB1, and VPS11 were upregulated in AS. Others, such as MAP1A, PCLO, PTPRF, and STX1A, showed brain region or species-specific differences.

[0042] Restoration of UBE3A expression in young and adult AS mice rescues the altered proteomic state to different extents We next investigated whether these changes in potential UBE3A targets and pathways could be rescued by UBE3A restoration during clinically relevant treatment time points, i.e., in young and adult mice. To address whether the altered molecular proteome could be rescued by restoring UBE3A expression, we utilized an AS mouse model with a tamoxifen-inducible UBE3A allele [4]. Control (WT; CreERT2+), AS (Ube3aStop / p+). UBE3A-restored mice (Ube3aStop / p+; CreERT2+) were injected with tamoxifen at either P21 or P56, corresponding to juvenile and adult developmental stages, and sacrificed at P84 to compare rescue at the two time points (Figure 4A). Cortical tissue was used to quantify 5325 proteins across all samples in DIA mode, analyzed with pooled libraries created from both control and AS groups.

[0043] Restoration of UBE3A at P21 and P56 was able to rescue <20% to 81% and 71% of cortical UBE3A protein levels in control animals, respectively, as measured by LC / MS (Figure 4B). PLS-DA separated samples by both time point of restoration (T1) and genotype (T2), with controls significantly different from AS mice (Figure 4C). Global proteomic profile analysis revealed that the P21 restored group reverted to controls, while P56 restoration partially rescued the AS proteome. These results suggest that AS-associated alterations in protein homeostasis can be almost completely rescued by UBE3A restoration in the young brain and only to a lesser extent in the adult.

[0044] We next performed expression and pathway analysis of differentially altered proteins to map the trajectories of UBE3A downstream targets between different groups. Pathway enrichment analysis on all proteins using GO: cellular component (GO: CC) analysis comparing AS with control, or AS with recovery at P21 or P56, revealed rescue of aminoacyl-tRNA synthetase at P21 but not at P56, and rescue of both proteasome complex and synaptic protein gene sets at both time points (Figure 4D).

[0045] A heatmap of the top 27 individual proteins significantly changed between any of the four sample sets reveals that the majority of proteins can be restored to some degree with both early and late rescue (adjusted p-value < 0.05; Figure 4E). Hierarchical clustering was performed according to the degree of co-regulation (magenta) or counter-regulation (green) with respect to UBE3A expression. The majority of proteins, including the top hits belonging to ARS (such as YARS and WARS) and proteasome subunits or proteasome accessory proteins (e.g., UBLCP1, UCHL5, PSME3), show enhanced rescue with P21 vs. P56; whereas expression of several synaptic proteins, including FDPS, C2CD4C, FXYD6, TSNAX, and STX7, normalized with P56, indicating that their response to UBE3A can vary.

[0046] Transketolase is a nuclear target of UBE3A in rodents and humans To orthogonally validate the subset of top identified UBE3A targets, biochemical analysis of an independent cohort of cortical samples from control, AS, and P21 restored mice was performed using capillary Western blotting (Figure 4F). Significant changes in protein levels were detected in control compared to AS mice, and in P21 restored compared to AS mice for several of the tested hits, including TKT, UCHL5, ACYP1, YARS, DZANK, and SOD2. These results confirm the robustness of the identified targets across independent experiments and protein quantification methods. Furthermore, transcript levels of the top identified hits in cortical tissues from control and AS mice were not significantly different, indicating that changes in expression levels were at the translational or post-translational level.

[0047] Next, we investigated whether the top UBE3A-dependent hits in rodents were altered in neurons derived from induced pluripotent stem cells (iPSCs) generated from AS patient and control blood

[27] (Pandya et al., 2021). After 6 weeks of differentiation, the expression of this selected set of proteins was analyzed by capillary Western blotting. All proteins tested showed significant upregulation in AS neurons compared to controls, including all proteins related to the proteasome (UCHL5, PSMD2, USP14, UBLCP1, PSME3) and ARS pathways (YARS, WARS). Furthermore, treatment of control neurons with UBE3A-targeting ASO to reduce UBE3A expression (UBE3A KD) mimicked the changes seen in AS patient neurons, albeit with smaller fold changes in most cases (Figure 5A). Consistently, TKT revealed the greatest fold changes across AS patient neurons, as well as AS mouse and rat brains (Figure 5A). Therefore, we sought to address the mechanism of UBE3A-dependent regulation of TKT.

[0048] Unlike other enzymes in the pentose phosphate pathway, TKT has substantial nuclear localization in certain cancer cells and normal tissues and has previously been reported to contain a nuclear localization signal [28, 29]. Similarly, TKT appeared mostly in the nucleus in human and rat neurons (Fig. 5B, D). In human neurons, co-labeling with DAPI and MAP2 revealed that TKT expression was higher in neuronal nuclei compared to non-neuronal cells (MAP2+ vs. MAP2- cells) and increased in an AS neuron- and UBE3A-dependent manner (Fig. 5B, C). TKT nuclear intensity in both neuronal iPSC-derived AS and UBE3A KD cultures revealed a significant upregulation of TKT expression (MAP2-positive nuclei compared to control, +59%; Fig. 5B, C). In rat cortex, expression was low in both neuronal (NeuN-positive) and non-neuronal cells. Consistent with patient neurons, nuclear TKT signal was significantly upregulated in AS conditions (+95%; Figure 5D,E). In rat brains, there was a slight increase in non-neuronal cells, which may be due to a decrease in UBE3A gene dosage (Figure 5E).

[0049] To assess whether TKT is a direct target of UBE3A, we used a previously described cellular ubiquitination assay performed in E. coli [14, 30]. To this end, E. coli cells were transformed with plasmids encoding rabbit ubiquitin-like modifier activating enzyme 1 (UBA1), the E2 ubiquitin conjugating enzyme UBCH5, the E3 ligase UBE3A (or a catalytically inactive variant), ubiquitin, and either TKT or RING1B. RING1B is a well-established target of UBE3A and serves as a positive control in this assay [14, 31]. The presence of active UBE3A and all components of the ubiquitination cascade results in the formation of slower migrating bands for both RING1B and TKT (Figure 5F). These slower migrating bands are not seen in the absence of ubiquitin or in the presence of catalytically inactive UBE3AC817S. These results strongly suggest that UBE3A can directly ubiquitinate TKT.

[0050] UBE3A has been shown to be expressed in several isoforms that differ from each other in cellular localization. In humans, there are three functional isoforms that vary at the N-terminus [32, 33], whereas in mice, there are only two: a shorter, predominantly nuclear isoform (mUBE3A-Iso3), and a longer cytosolic isoform (mUBE3a-Iso2). Furthermore, loss of the nuclear UBE3A isoform has been shown to be sufficient to induce AS phenotypes in mice

[13] . Given the UBE3A-dependent upregulation of TKT in neuronal nuclei, we investigated whether the regulation was UBE3A isoform specific. Lysates from cortical tissues of mUBE3A-Iso3 and mUBE3a-Iso2 knockout mice and their respective controls were analyzed by capillary Western blotting. As mUBE3A-Iso3 represents the majority of UBE3A protein, knockout of this isoform reduced total UBE3A levels by more than 60% (Figure 5G). Compared to wild-type controls, the levels of both TKT and UCHL5 (a known UBE3A target localized in the nucleus) were upregulated in tissues from mUBE3A-Iso3 knockout mice (+12.8% and +28.4%, respectively), but knockout of the cytoplasmic isoform mUBE3a-Iso2 did not significantly affect expression levels ( Figure 5G ), suggesting that TKT protein levels are regulated by the nuclear isoform mUBE3A-Iso3.

[0051] Consideration In this study, we comprehensively map UBE3A-driven temporal and spatial changes in the rodent proteome. Combined with previous proteomic analysis of AS patient-derived neurons, we highlight disease alterations across species. We demonstrate that the AS proteome deteriorates over the course of postnatal development and can be reversed by UBE3A restoration at postnatal stages in juveniles and young adults, although rescue is more effective at earlier time points. Furthermore, we identify three major cellular pathways affected by UBE3A loss in mice that were also observed in rat and human models of AS: the proteasome, the ARS, and several synaptic pathways. These results imply that the regulation of fundamental global cellular processes is controlled by UBE3A and that alterations of UBE3A display distinct developmental trajectories.

[0052] The most prominent change observed in the AS proteome across all species and all developmental stages was the upregulation of proteasome subunits and proteasome accessory proteins. It has previously been reported that UBE3A can directly interact with the 26S proteasome and regulate the turnover of proteasome subunits [13, 16, 34, 35]. Our data indicate that changes in protein abundance affected the 19S and 11S regulatory subunits and proteasome accessory proteins to a greater extent than the 20S core. In non-neuronal contexts, several top hits, including the polyubiquitination receptor PSMD4, the deubiquitinase UCHL5, and the regulatory subunit PSMC3, may be directly ubiquitinated by UBE3A, which may then negatively affect proteasome function, including the binding and processing of its substrates

[36] . It is therefore conceivable that loss of UBE3A may affect proteasome function in a similar manner in vivo, resulting in a cumulative effect on the AS proteome. Furthermore, alterations in accessory protein abundance and function may directly contribute to disease phenotypes by impeding the recognition of specific disease-associated substrates in neurons. Future studies should address the extent to which Ube3a proteasome dysfunction and the contribution of nuclear and cytoplasmic Ube3a are altered to broad proteomic disease alterations.

[0053] Similar to the proteasome pathway, we observed changes in ARS across all developmental time points. ARSs are a family of nuclear-encoded enzymes that ensure correct translation by conjugating amino acids to their cognate tRNA molecules to provide a critical initial step in protein translation

[21] . Similar to the proteasome, ARSs play a central role in protein homeostasis, in this case translation, but in contrast to the subunits of the proteasome, their association with UBE3A-dependent mechanisms is less clear. A comprehensive network analysis using the human protein-protein interaction database identified several ARSs, including AIMP1, AIMP2, MARS, and QARS, as part of the UBE3A interactome, although none of them have been reported to act as direct substrates

[37] . This is consistent with our findings that individual proteins in the ARS pathway are not universally upregulated. Protein abundance QARS and AIMP1 proteins were elevated, whereas YARS and WARS were decreased in AS mice, suggesting a more complex UBE3A-dependent regulatory mechanism with both direct and indirect effects. During eukaryotic evolution, multicellular organisms have acquired additional ARS protein domains that perform functions beyond translation

[38] . Whole-exome and whole-genome sequencing in patients with unknown etiology has linked loss-of-function mutations in ARS genes, such as the class I ARS proteins YARS and WARS, to nervous system dysfunction, developmental delay, and epilepsy [39, 40]. Mutations in the catalytic domain may reduce the rate of aminoacylation or the accuracy of tRNA recognition by ARS, disrupting protein synthesis, thereby contributing to many of the associated disorders. In addition, tyrosine and tryptophan are important components of serotonin and dopamine, which are essential for normal synaptic function, and the contribution of neurotransmitter imbalance to AS behavioral phenotypes has been reported in AS patients and mouse models of AS

[41] . The presence of disease-causing ARS mutations that do not interfere with catalytic function indicates that non-canonical ARS functions may also contribute to pathological phenotypes.Changes in the abundance of individual ARS proteins in AS may affect MSC composition and translation-independent roles, such as mitochondrial homeostasis, nuclear rRNA synthesis, and cytokine stimulation.

[42] Future studies will be required to determine whether the translation machinery or other ARS-related functions are disrupted in AS and how this contributes to the disease phenotype.

[0054] In contrast to the proteasome and tRNA synthase pathways, synaptic hits were mostly altered at later developmental stages, consistent with full maturation of the nervous system. Many UBE3A downstream targets involved in neuronal function have been previously characterized, but for the majority of these targets, it remains to be determined whether they are direct substrates. A wide range of synaptic proteins were increased or decreased in abundance in our dataset, confirming synaptic dysregulation at the molecular level. Our analysis revealed that the hits were localized to both pre- and postsynaptic compartments, including synaptic vesicles, presynaptic active zones, and integral components of the postsynaptic density, indicating global synaptic perturbations rather than changes in a single synaptic compartment. How changes in the abundance of each individual component affect neuronal function and the extent of crosstalk, either directly through UBE3a or through pathways such as the proteasome or ARS that emerge as a consequence at earlier developmental stages, remains to be determined.

[0055] Recently, a novel rat model of AS was generated that harbors a deletion of the maternal UBE3A gene and recapitulates many of the behavioral phenotypes previously observed in AS mice

[24] . Our study represents the first proteomic study of AS rat brain tissue, and we confirmed the top hits identified in AS mice, including members of the ARS families YARS and WARS, proteasome subunits and accessory proteins such as UBLCP1 and UCHL5, and the metabolic enzyme TKT, which showed consistent upregulation across all of our AS datasets. Alterations in proteasome, ARS, and synaptic pathways in rat AS cortex strongly correlated with P56 AS mice, indicating conserved alterations in UBE3A-dependent pathways and pointing to widespread underlying disease mechanisms in AS.

[0056] Individual brain region analysis in rats identified commonalities and regional differences between the cortex, hippocampus, and cerebellum (locations that show dysfunction in AS patients and have been the main focus of research for many years)

[43] . It is particularly interesting to examine the molecular mechanisms underlying potential region-specific dysfunctions such as cognitive and learning impairments, ataxia, and motor coordination problems. Interestingly, conserved proteins and pathways between AS mice and rats were also identified as altered across different brain regions. Interestingly, the cerebellar AS proteome diverges from the cortex and hippocampus, which may influence the motor dysfunction and ataxia seen in rodent models and AS patients. Cerebellar neuronal cytoarchitecture is very unique, and the majority of neurons, cerebellar cells, hardly express UBE3A, therefore, possible UBE3A protein changes may originate from Purkinje cells or Golgi cells

[26] . Some of the AS cerebellum-specific proteins are either exclusively expressed or show significant enrichment in the cerebellum compared to other brain regions. DPYSL5 is an enzyme expressed in the developing brain and regulates neurite outgrowth through its interaction with actin

[44] . In the adult cerebellum, it regulates dendritic development and synaptic plasticity of mouse Purkinje cells

[45] . Anti-CRMP5 antibodies are frequently detected in the serum of patients with subacute cerebellar ataxia

[46] , and proteomic profiling revealed significantly increased expression in patients with cortical dysplasia and epilepsy

[47] . BRAF kinase gain-of-function mutations are associated with CFC, a condition that presents with a variety of neurological phenotypes similar to AS, including developmental delay, intellectual disability, and seizures. In iPSC-derived neurons, BRAF gain-of-function led to immature neuronal differentiation and depletion of the progenitor pool, and neurons generated in these cultures showed higher intrinsic excitability

[48] . Finally, loss of function of the asparagine synthetase ASNS is associated with microcephaly, most likely caused by reduced proliferation of progenitors

[49] . ASNS metabolically connects the four amino acids L-aspartate, L-asparagine, L-glutamate, and L-glutamine, and therefore dysregulation of the balance of these amino acids in the brain may contribute to microcephaly and brain dysfunction.

[0057] Although larger deletions of the UBE3A locus are observed in AS patients, loss of UBE3A expression alone has been shown to be sufficient to induce AS. Thus, restoration of UBE3A expression is a promising therapeutic strategy currently undergoing clinical trials. Conditional AS mouse models with an inducible maternal UBE3A allele demonstrated age-dependent rescue of certain behavioral phenotypes after UBE3A restoration [4,50]. Furthermore, however, a single intracerebroventricular injection of UBE3A ATS ASO in adult AS mice failed to rescue most behavioral phenotypes [7]. ASO injections into newborn mice rescued many behavioral phenotypes (Milazzo in press). Although rodent behavior suggests that UBE3A restoration is more effective at earlier time points, this may not necessarily be the case for molecular / proteomic changes. Ube3a neuronal loss at early stages of development may cause developmental changes that are difficult to disentangle from direct or indirect protein regulation in mature neurons. We therefore investigated to what extent the mouse AS proteome could be reverted by restoring UBE3A at adolescence (P21) and adulthood (P56). Surprisingly, restoration of UBE3A expression at either stage restored proteome homeostasis to a significant extent, but P21 rescue was more efficient. For the most part, alterations in proteasome and synaptic pathways were reverted at both time points, which is consistent with the observation that most electrophysiological parameters could also be restored upon restoration of adult UBE3A

[51] . These results highlight that the disease trajectory of proteins and associated pathways is UBE3A-dependent and can be restored postnatally. Interestingly, some proteins were only regulated in adult rescue, suggesting a role in fully mature neurons. P56-specific synaptic hits included TSNAX, a signaling protein important for synaptic plasticity

[52] , and STX7, a component of synaptic vesicles (SVs) that may play a role in maintaining the presynaptic recycling pool of SVs

[53] .These results demonstrate that restoration of UBE3A expression in early adulthood could significantly revert the AS proteome and potentially rescue proteasome and synaptic function, further facilitating progress in disease-modifying treatments in AS.

[0058] A previous study uncovered a set of human-specific UBE3A targets, including the GAG ​​domain-containing protein PEG10, after proteomic analysis of patient-derived iPSC neuronal cultures and UBE3A restoration using ASOs

[27] . Furthermore, several top hits identified in patient neurons, including PPID, DST, and UCHL5, were also altered in AS models. Several additional proteasome and ARS proteins were found in AS neurons and phenocopied by knockdown of UBE3A. Notably, TKT, the protein that showed the greatest change across rodent models and was validated as a direct UBE3A target, was also the most altered in human AS neurons. TKT is the rate-limiting enzyme of the pentose phosphate pathway (PPP), a metabolic pathway that generates NADPH and building blocks for nucleotide synthesis. Furthermore, TKT is part of the nonoxidative branch of the PPP connecting it with glycolysis and, due to its reversible nature, can control flux through the PPP. TKT function depends on the coenzyme thiamine, and thiamine deficiency as well as rare mutations in the TKT gene underlie a range of neurological dysfunctions, although the exact mechanisms by which TKT loss of function leads to these phenotypes are not fully understood [54, 55]. Interestingly, TKT localization in both human neurons and rat brain tissue was found to be predominantly nuclear, even though the PPP occurs in the cytosol

[56] . Using mouse models with deletion of either the nuclear or cytoplasmic isoforms of UBE3A (see), we demonstrated that TKT is directly regulated by nuclear UBE3A. The tight regulation of TKT by nuclear UBE3A and its upregulation in AS conditions raise the questions of 1) whether regulation by UBE3A is directly related to its metabolic function and the PPP, or 2) whether there are unknown non-canonical functions of TKT in the nucleus, and 3) whether excess of TKT contributes to the disease phenotype. Non-canonical regulatory functions have been described for many metabolic enzymes, including glycolytic enzymes that can act as protein kinases and transcriptional regulators

[57] , and there are reports that nuclear TKT interacts with EGFR functionally independent of TKT enzymatic activity

[28] .Future studies are needed to elucidate whether TKT has a role in AS pathophysiology.

[0059] Together with previous proteomic analysis of neurons from AS patients

[27] , our study provides a proteomic resource to support biomarker and translational research. Future efforts are needed to determine the altered human proteome from AS brain postmortem samples and analyze patient CSF samples to determine whether TKT and other proteins are secreted from diseased neurons and validate them as downstream UBE3A biomarkers.

[0060] In summary, we provide proteomic datasets from 143 runs across three different AS rodent models: 1) mouse cortex across different developmental stages, 2) rat cortex and other disease-relevant brain regions, and 3) mice after UBE3A rescue; providing a comprehensive proteomic atlas of UBE3A-dependent protein and pathway alterations.

[0061] Materials and Methods animal Mice were housed in individually ventilated cages (IVC; 1145 T cages from Techniplast) in a barrier facility. All animals were kept at 22±2°C with a 12-h light-dark cycle and provided with mouse chow (801727CRM(P) from Special Dietary Service) and water ad libitum. All animal experiments were performed in accordance with the European Commission Council Directive 2010 / 63 / EU (CCD approval AVD101002016791).

[0062] Data Independent Acquisition (DIA) Mass Analysis Total protein profiling of rat and mouse tissues was performed at Biognosys AG (Schlieren, Switzerland) using Biognosys' Hyper Reaction Monitoring (HRM™) label-free discovery proteomics workflow. All solvents were HPLC grade from Sigma-Aldrich and all chemicals not otherwise specified were obtained from Sigma-Aldrich.

[0063] Sample preparation Tissue samples were denatured using Biognosys denaturation buffer and reduced and alkylated using Biognosys reduction and alkylation solution for 60 min at 37°C. Digestion to peptides was then performed overnight at 37°C using trypsin (1 50 w / w ratio Promega). Samples were prepared using the PreOmics sample preparation kit and frozen as dried peptides. Peptides were resuspended in LC solvent A (1% acetonitrile, 0.1% formic acid (FA)) supplemented with Biognosys iRT kit calibration peptides. Peptide concentrations were determined using a UV / VIS spectrometer (SPECTROstar Nano, BMG Labtech).

[0064] HPRP fractionation Cortical samples (P1, P21, P56): Peptides were pooled according to genotype (2 pools: WT and AS). Ammonium hydroxide was added to both pools to a pH value >10. Fractionation was performed on an Acquity UPLC CSH C18 1.7 μm, 2.1x150 mm column (Waters) using a Dionex UltiMate 3000RS pump (Thermo Scientific). The gradient was 1% to 40% solvent B in 20 min, with solvents A: 20 mM ammonium formate in water, B: acetonitrile. Fractions were collected every 30 s and pooled sequentially into 6 fraction pools for mouse cortex samples and 8 fraction pools for rat brain samples. For mouse cortex samples, the eluate was dried and separated in 15 μl of solvent A and Biognosys's HRM kit calibration peptide was added, while rat samples were separated in 12 μL of solvent A and Biognosys's iRT kit calibration peptide was added.

[0065] Mouse cortex samples (Ube3a recovery): Two pools of peptides were generated (WT; CreERT+ and Ube3aStop / p+; CreERT-, 6 samples each). The two pools were diluted 4-fold with 0.2 M ammonium formate (pH 10) and applied to a C18 MicroSpin column (The Nest Group). Peptides were then eluted with a buffer containing 0.05 M ammonium formate and increasing acetonitrile concentrations (5%, 10%, 15%, 20%, 25%, and 50%) at pH 10. The eluate was dried and separated in 15 μl of solvent A, and Biognosys HRM kit calibration peptides were added. The 5% and 50% fractions were pooled. All peptide concentrations were determined using a UV / VIS spectrometer.

[0066] Shotgun LC MS / MS for Spectral Library Generation For LC MS / MS measurements of mouse brain tissue, 2 μg of peptide per fraction (or 4 μg for fraction 5+50% cortical sample with Ube3a recovery) was injected onto an in-house packed C18 column (Dr. Maisch ReproSil Pur 1.9 μm particle size, 120 Å pore size 75 μm internal diameter, 50 cm length, New Objective) on a Thermo Scientific™ Easy nLC 1200 nano liquid chromatography system connected to a Thermo Scientific Q Exactive™ HF mass spectrometer equipped with a standard nanoelectrospray source. LC solvents were A: 1% acetonitrile in water with 0.1% FA; B: 15% water in acetonitrile with 0.1% FA. The LC gradient was 1-55% solvent B for 60 min, followed by 55-90% B for 10 s, 90% B for 10 min, 90%-1% B for 0.1 min, and 1% B for 5 min. A modified TOP15 method was used

[58] .

[0067] In addition, a mouse somatosensory cortex 1 barrel field and a mouse cerebellum library from the MCP publication by Bruderer et al.

[59] were used in the analysis.

[0068] For DDA LC MS / MS measurements of rat brain samples, 1 μg of peptides per fraction was injected onto an in-house packed reversed-phase column (75 μm inner diameter, 60 cm length and 10 μm tip PicoFrit emitter from New Objective packed with 1.7 μm charged surface hybrid C18 particles from Waters) on a Thermo Scientific EASY-nLC™ 1200 nano liquid chromatography system connected to a Thermo Scientific Orbitrap Fusion Tribrid mass spectrometer equipped with a Nanospray Flex™ ion source. LC solvents were A: 1% acetonitrile in water with 0.1% FA; B: 20% water in acetonitrile with 0.1% FA. The nonlinear LC gradient was 1–59% solvent B in 95 min, followed by 59–90% B in 10 s, 90% B for 8 min, 90%–1% B for 10 s, and 1% B for 5 min at a flow rate of 250 nl / min at 60° C. A modified maximum velocity method (3 s cycle time) according to Hebert et al.

[60] was used.

[0069] Database searching of shotgun LC MS / MS data For developmental time course cortical samples (P1, P21, P56), mass spectrometry data were analyzed using Biognosys' search engine SpectroMine™, and for cortical samples with Ube3a recovery, Biognosys' search engine Pulsar (version 1.0.19846) was used. The false discovery rate at peptide and protein level was set to 1%. The mouse UniProt fasta database (Mus musculus, 2019-07-01) was used as the search engine, allowing for two missed cleavages and variable modifications (N-terminal acetylation, methionine oxidation).

[0070] For rat brain tissue samples, mass spectrometry data were analyzed using the Biognosys search engine SpectroMine™ (version 1.0.190808) with a false discovery rate of 1% at peptide and protein level. The rat UniProt / Trembl.Fasta database (Rattus norvegicus, 2019-07-01) was used as the search engine, allowing for two missed cleavages and variable modifications (N-terminal acetylation, methionine oxidation).

[0071] HRM ID + mass spectrometry acquisition For LC MS / MS HRM measurements, 2 μg of peptides per sample were injected onto an in-house packed C18 column (Dr. Maisch ReproSil Pur, 1.9 μm particle size, 120 Å pore size; 75 μm inner diameter, 50 cm length, New Objective) on a Thermo Scientific Easy nLC 1200 nano liquid chromatography system connected to a Thermo Scientific Q Exactive HF mass spectrometer equipped with a standard nanoelectrospray source. LC solvents were A: 1% acetonitrile in water with 0.1% FA; B: 15% water in acetonitrile with 0.1% FA. The nonlinear LC gradient was 1–55% solvent B in 120 min, followed by 55–90% B for 10 s, and 90% B for 10 min. The DIA method with one full range survey scan and 22 DIA windows was used, with a gradient length of 135 min.

[0072] HRM data analysis HRM mass spectrometry data were analyzed using Spectronaut Pulsar software (Biognosys, versions 12 and 13.8.190930). False discovery rates at peptide and protein levels were set to 1% and data were filtered using line-based extraction. The assay library (protein inventory) generated in this project was used for the analysis in combination with the one from MCP (Bruderer et al., 2017). HRM measurements analyzed with Spectronaut were normalized using local regression normalization

[61] .

[0073] HRM data analysis Mouse developmental time course Statistical and bioinformatics analyses were performed with the R statistical environment

[62] and Perseus software

[63] .

[0074] Protein intensities below 20 on the original scale were considered below the noise threshold and marked as missing. Data were log2 transformed and filtered to include 50% significant values ​​across all samples. Only three proteins were excluded due to complete DIA data, retaining a total of 7,184 protein groups for further analysis.

[0075] Partial least squares discriminant analysis (PLS-DA) was performed using the Discriminer R Package [ 64 ] with default settings and based on the fully measured set of 7,029 proteins.

[0076] To identify differentially expressed proteins, we used the samr R package

[65] , which allows permutation-based false discovery rate control and reports the associated q-values ​​

[66] . A two-class independent test with 100 permutations was used to compare the AS and WT genotypes separately at each time point. Proteins were classified as statistically significantly differentially expressed if they met a q-value threshold of 5%.

[0077] Pathway analysis was performed with Perseus software using the 1D annotation function. Gene Ontology (GO) annotations for each protein were downloaded from UniProt

[67] . Because multiple enrichment tests were performed, the Benjamini-Hochberg method was used to correct for multiple hypothesis testing. For completeness, we plot pathway enrichment scores for all three comparisons and explicitly mark those significantly modulated.

[0078] Rat brain regions A similar analysis strategy as above was applied to the rat dataset. Briefly, protein expression values ​​below 20 were converted to NA. Data were log2 transformed and filtered to retain protein groups with measured values ​​in at least 50% of all samples, resulting in 7,524 protein groups. PLS-DA analysis was performed using proteins with measurements across all samples (7,346) using the DiscriMiner R package

[64] . Differentially expressed proteins were identified between KO and WT rat samples across each brain region separately. The same function was used for the two-class independent test, and a q value of 0.05 was considered to mark a protein as statistically significantly differentially expressed.

[0079] Restoration of mouse Ube3a Protein expression values ​​below 20 were considered below the detection limit and converted to NA, and data were log2 transformed. A set of 5,325 proteins contained measurements in at least 50% of all samples and were used for subsequent statistical analysis. PLS-DA analysis was performed on proteins measured across all samples (5,314) using the DiscriMiner R package

[64] .

[0080] The samr function with response type set to “multiclass” from the package was used to identify groups of proteins that were differentially expressed across the four conditions: WT, KO, rescue with p21, and rescue with p56. To determine which pairwise comparisons were significant, Tukey’s Honestly Significant Difference test from the R statistical package

[62] was used with the alpha level set to 5%.

[0081] To identify up- or downregulated pathways, the 1D annotation test of the Perseus software was used. For each pairwise comparison KO vs. WT, Rescue p21 vs. KO, and Rescue p56 vs. KO, proteins were first mapped to GO annotations and keywords downloaded from the Uniprot database. Subsequently, enrichment scores were calculated and multiple hypothesis testing correction using the Benjamini-Hochberg procedure was applied to identify statistically significant differences. For completeness, pathway enrichment scores for all three comparisons were always plotted and those significantly regulated were explicitly marked.

[0082] Capillary Western Blot Protein expression of putative Ube3a targets in mouse brain and hiPSC lysates was analyzed by automated capillary Western blotting (Sally Sue, Protein Simple). All experimental steps were performed according to the manufacturer's instructions. Briefly, after protein extraction and quantification, a final sample concentration of 0.25 mg / ml was loaded into a capillary cartridge (12-230 kDa Peggy Sue or Sally Sue Separation Module, #SM-S001). Chemiluminescent protein detection was performed using anti-rabbit and anti-mouse detection modules (#DM-001 and #DM-002). Analysis of relative protein expression was performed using Compass for SW software (version 4.1.0, Protein Simple) and statistical analysis was performed using ANOVA followed by Tukey's post-hoc test using GraphPad Prism software (version 8).

[0083] hIPSC culture Cell culture of NPCs and neurons was performed as described by Costa et al. and Pandya et al. [27, 68]. IPSC staining and imaging

[0084] Control and AS-deficient neurons were cultured in BGAA medium. Medium was changed 1 day before treatment. hiPSC-derived neurons were treated with 1 μM ASO in PBS for 6 weeks during neuronal differentiation. After treatment, cells were immediately fixed and stained for TKT (Sigma-Aldrich, HPA029480; 1:200), UBE3a (Sigma-Aldrich, SAB1404508; 1:200), Map2 (Abcam, ab5392; 1:500) and DAPI as previously described

[27] .

[0085] Imaging and imaging data analysis Images were acquired with a Leica TCS SP5 confocal microscope. Z-stack projections were performed using the "sum slices" command in FIJI (ImageJ). Automated quantification of nuclear UBE3A and TKT expression was performed by using DAPI staining as a mask and measuring the integrated density of fluorescence in each cell. Manual thresholding of HuC / D staining in each independent experiment was performed to distinguish between neuronal and non-neuronal cells. Replicates from two independent differentiations were combined for data analysis. Statistical analysis was performed with GraphPad Prism software (version 8) using the Kruskal-Wallis test followed by Dunn's post-hoc test. ASO treatment [Table 1]

[0086] immunohistochemistry Brain tissue was fixed with 4% PFA and prepared for cryosectioning. Immunohistochemical staining for Tkt (Sigma-Aldrich, HPA029480; 1:200), Ube3a (Sigma-Aldrich, SAB1404508; 1:400) and NeuN (Sigma-Aldrich, MAB377; 1 / 500) in rat brain tissue was performed as previously described

[13] . Briefly, sections were blocked with PBS containing 0.5% Triton X-100 and 5% normal horse serum for 1 h at room temperature. Primary antibody labeling was performed overnight at room temperature in PBS containing 0.5% Triton X-100 and 1% normal horse serum. After primary antibody labeling, sections were washed with PBS and incubated with the corresponding Alexa-conjugated secondary antibodies and DAPI in PBS buffer containing 0.5% Triton X-100, 1% normal horse serum for 2 h at room temperature.

[0087] Imaging and data analysis Images were acquired with a Leica TCS SP8 confocal microscope. Z-stack projections were performed using the "sum slices" command in FIJI (ImageJ). Automated quantification of nuclear UBE3A and TKT expression was performed by using DAPI staining as a mask and measuring the integrated density of fluorescence in each cell. Manual thresholding of NeuN staining was performed and kept consistent across animals to distinguish neuronal from non-neuronal cells. Statistical analysis was performed with GraphPad Prism software (version 8) using the Kruskal-Wallis test followed by Dunn's post-hoc test.

[0088] Biomarker Proteins of the Invention (human proteins listed). [Table 2]

[0089] References 1.Buiting K,Williams C,Horsthemke B.Angelman syndrome-insights into a rare neurogenetic disorder.Nat Rev Neurol.2016;12:584-593. 2.Mabb AM,Judson MC,Zylka MJ,Philpot BD.Angelman syndrome:Insights into genomic imprinting and neurodevelopmental phenotypes.Trends Neurosci.2011;34:293-303. 3.Rotaru DC,Mientjes EJ,Elgersma Y.Angelman Syndrome:From Mouse Models to Therapy.Neuroscience.2020. 4.Silva-santos S,Woerden GM Van,Bruinsma CF,Mientjes E.Ube3a reinstatement identifies distinct treatment windows in Angelman syndrome model mice.J Clin Invest.2015;125:2069-2076. 5.Gu B,Carstens KE,Judson MC,Dalton KA,Rougie M,Clark EP,et al.Ube3a reinstatement mitigates epileptogenesis in Angelman syndrome model mice.J Clin Invest.2019.2019.https: / / doi.org / 10.1172 / JCI120816. 6.Huang HS,Allen JA,Mabb AM,King IF,Miriyala J,Taylor-Blake B,et al.Topoisomerase inhibitors unsilence the dormant allele of Ube3a in neurons.Nature.2012.2012.https: / / doi.org / 10.1038 / nature10726. 7.Meng L,Ward AJ,Chun S,Bennett CF,Beaudet AL,Rigo F.Towards a therapy for Angelman syndrome by targeting a long non-coding RNA.Nature.2014;518:409-412. 8.Meng L,Person RE,Huang W,Zhu PJ,Costa-Mattioli M,Beaudet AL.Truncation of Ube3a-ATS Unsilences Paternal Ube3a and Ameliorates Behavioral Defects in the Angelman Syndrome Mouse Model.PLoS Genet.2013;9. 9.Elgersma Y,Sonzogni M.UBE3A reinstatement as a disease-modifying therapy for Angelman syndrome.Dev Med Child Neurol.2021. 10.Egawa K,Kitagawa K,Inoue K,Takayama M,Takayama C,Saitoh S,et al.Decreased tonic inhibition in cerebellar granule cells causes motor dysfunction in a mouse model of angelman syndrome.Sci Transl Med.2012.2012.https: / / doi.org / 10.1126 / scitranslmed.3004655. [ PubMed ] 11.Sun J,Zhu G,Liu Y,Standley S,Ji A,Tunuguntla R,et al.UBE3A Regulates Synaptic Plasticity and Learning and Memory by Controlling SK2 Channel Endocytosis.Cell Rep.2015;12:449-4 [ PubMed ] [ Cross Ref ] 12.Sun J,Liu Y,Jia Y,Hao X,Lin WJ,Tran J,et al.UBE3A-mediated p18 / LAMTOR1 ubiquitination and degradation regulate mTORC1 activity and synaptic plasticity. 13.Avagliano Trezza R,Sonzogni M,Bossuyt SNV,Zampeta FI,Punt AM,van den Berg M,et al.Loss of nuclear UBE3A causes electrophysiological and behavioral deficits in mice and is associated with Angelman syndrome.Nat Neurosci.2019.2019.https: / / doi.org / 10.1038 / s41593-019-0425-0. 14.Avagliano Trezza R,Punt AM,Mientjes E,van den Berg M,Zampeta FI,de Graaf IJ,et al.Mono-ubiquitination of Rabphilin 3A by UBE3A serves a non-degradative function.Sci Rep. 2021. 2021. https: / / doi.org / 10.1038 / s41598-021-82319-9. 15.Bossuyt SNV,Punt AM,de Graaf IJ,van den Burg J,Williams MG,Heussler H,et al.Loss of nuclear UBE3A activity is the predominant cause of Angelman syndrome in individuals carrying UBE3A missense mutations.Hum Mol Genet.2021.2021.https: / / doi.org / 10.1093 / hmg / ddab050. 16.Tomaie V,Banks L.Angelman syndrome-associated ubiquitin ligase UBE3A / E6AP mutants interfere with the proteolytic activity of the proteasome.Cell Death Dis.2015.2015.https: / / doi.org / 10.1038 / cddis.2014.572. 17.Koopmans F,Pandya NJ,Franke SK,Phillippens IHCMH,Paliukhovich I,Li KW,et al.Comparative Hippocampal Synaptic Proteomes of Rodents and Primates:Differences in Neuroplasticity-Related Proteins.Front Mol Neurosci.2018.2018.https: / / doi.org / 10.3389 / fnmol.2018.00364. 18.Ludwig C,Gillet L,Rosenberger G,Amon S,Collins BC,Aebersold R.Data-independent acquisition-based SWATH-MS for quantitative proteomics:a tutorial.Mol Syst Biol.2018.2018.https: / / doi.org / 10.15252 / msb.20178126. 19.Judson MC,Sosa-Pagan JO,Del Cid WA,Han JE,Philpot BD.Allelic specificity of Ube3a expression in the mouse brain during postnatal Development.J Comp Neurol.2014.2014.https: / / doi.org / 10.1002 / cne.23507. 20.Sonzogni M,Hakonen J,Bernabe Kleijn M,Silva-Santos S,Judson MC,Philpot BD,et al.Delayed loss of UBE3A reduces the expression of Angelman syndrome-associated phenotypes.Mol Autism.2019.2019.https: / / doi.org / 10.1186 / s13229-019-0277-1. 21.Kwon NH,Fox PL,Kim S.Aminoacyl-tRNA synthetases as therapeutic targets.Nat Rev Drug Discov.2019. 22.Tanaka K.The proteasome:Overview of structure and functions.Proc Japan Acad Ser B Phys Biol Sci.2009. 23.Koopmans F,van Nierop P,Andres-Alonso M,Byrnes A,Cijsouw T,Coba MP,et al.SynGO:An Evidence-Based,Expert-Curated Knowledge Base for the Synapse.Neuron.2019.2019.https: / / doi.org / 10.1016 / j.neuron.2019.05.002. 24.Berg EL,Pride MC,Petkova SP,Lee RD,Copping NA,Shen Y,et al.Translational outcomes in a full gene deletion of ubiquitin protein ligase E3A rat model of Angelman syndrome.Transl Psychiatry.2020.2020.https: / / doi.org / 10.1038 / s41398-020-0720-2. 25.Wang T,van Woerden GM,Elgersma Y,Borst JGG.Enhanced transmission at the calyx of held synapse in a mouse model for angelman syndrome.Front Cell Neurosci.2018.2018.https: / / doi.org / 10.3389 / fncel.2017.00418. 26.Bruinsma CF,Schonewille M,Gao Z,Aronica EMA,Judson MC,Philpot BD,et al.Dissociation of locomotor and cerebellar deficits in a murine Angelman syndrome model.J Clin Invest.2015.2015.https: / / doi.org / 10.1172 / JCI83541. 27.Pandya NJ.Secreted retrovirus-like GAG domain-containing protein PEG10 is regulated by UBE3A and is involved in Angelman syndrome pathophysiology.Cell Reports Med.2021.2021.https: / / doi.org / https: / / doi.org / 10.1016 / j.xcrm.2021.100360. 28.Qin Z,Xiang C,Zhong F,Liu Y,Dong Q,Li K,et al.Transketolase(TKT)activity and nuclear localization promote hepatocellular carcinoma in a metabolic and a non-metabolic manner.J Exp Clin Cancer Res.2019.2019.https: / / doi.org / 10.1186 / s13046-019-1131-1. 29.Li M,Zhang X,Lu Y,Meng S,Quan H,Hou P,et al.The nuclear translocation of transketolase inhibits the farnesoid receptor expression by promoting the binding of HDAC3 to FXR promoter in hepatocellular carcinoma cell lines.Cell Death Dis.2020.2020.https: / / doi.org / 10.1038 / s41419-020-2225-6. 30.Geerts-Haages A,Bossuyt SNV,den Besten I,Bruggenwirth H,van der Burgt I,Yntema HG,et al.A novel UBE3A sequence variant identified in eight related individuals with neurodevelopmental delay,results in a phenotype which does not match the clinical criteria of Angelman syndrome.Mol Genet Genomic Med.2020.2020.https: / / doi.org / 10.1002 / mgg3.1481. [ PMC free article ] [ PubMed ] 31. Zaaroor-Regev D, De Bie P, Scheffner M, Noy T, Shemer R, Heled M, et al A. 2010. 2010. https: / / doi.org / 10.1073 / pnas. 32.Zampeta FI,Sonzogni M,Niggl E,Lendemeijer B,Smeenk H,De Vrij FMS,et al.Conserved UBE3A subcellular distribution between human and mice is facilitated by non-homologous isoforms.Hum Mol Genet.2020.2020.https: / / doi.org / 10.1093 / hmg / da194. [ PubMed ] 33.Sirois CL,Bloom JE,Fink JJ,Gorka D,Keller S,Germain ND,et al.Abundance and localization of human UBE3A protein isoforms.Hum Mol Genet. [ PMC free article ] [ PubMed ] 34.Yi JJ,Paranjape SR,Walker MP,Choudhury R,Wolter JM,Fragola G,et al.The autism-linked UBE3A T485A mutant E3 ubiquitin ligase activates the Wnt / β-catenin pathway by inhibiting the proteasome.J Biol Chem.2017.2017.https: / / doi.org / 10.1074 / jbc.M117.788448. 35.Martinez-Noel G,Galligan JT,Sowa ME,Arndt V,Overton TM,Harper JW,et al.Identification and Proteomic Analysis of Distinct UBE3A / E6AP Protein Complexes.Mol Cell Biol.2012.2012.https: / / doi.org / 10.1128 / mcb.00201-12. 36.Jacobson AD,MacFadden A,Wu Z,Peng J,Liu CW.Autoregulation of the 26S proteasome by in situ ubiquitination.Mol Biol Cell.2014.2014.https: / / doi.org / 10.1091 / mbc.E13-10-0585. 37.Martinez-Noel G,Luck K,Kuehnle S,Desbuleux A,Szajner P,Galligan JT,et al.Network Analysis of UBE3A / E6AP-Associated Proteins Provides Connections to Several Distinct Cellular Processes.J Mol Biol.2018.2018.https: / / doi.org / 10.1016 / j.jmb.2018.01.021. 38.Guo M,Yang XL,Schimmel P.New functions of aminoacyl-tRNA synthetases beyond translation.Nat Rev Mol Cell Biol.2010. 39.Boczonadi V,Jennings MJ,Horvath R.The role of tRNA synthetases in neurological and neuromuscular disorders.FEBS Lett.2018. 40.Ognjenovie J,Simonovie M.Human aminoacyl-tRNA synthetases in diseases of the nervous system.RNA Biol.2018. 41.Farook MF,DeCuypere M,Hyland K,Takumi T,LeDoux MS,Reiter LT.Altered serotonin,dopamine and norepinepherine levels in 15q duplication and Angelman syndrome mouse models.PLoS One.2012.2012.https: / / doi.org / 10.1371 / journal.pone.0043030. 42.Smirnova E V.,Lakunina VA,Tarassov I,Krasheninnikov IA,Kamenski PA.Noncanonical functions of aminoacyl-tRNA synthetases.Biochem.2012. 43.Maranga C,Fernandes TG,Bekman E,da Rocha ST.Angelman syndrome:a journey through the brain.FEBS J.2020. 44.Gong X,Tan M,Gao Y,Chen K,Guo G.CRMP-5 interacts with actin to regulate neurite outgrowth.Mol Med Rep.2016.2016.https: / / doi.org / 10.3892 / mmr.2015.4662. 45.Yamashita N,Mosinger B,Roy A,Miyazaki M,Ugajin K,Nakamura F,et al.CRMP5(Collapsin Response Mediator Protein 5)regulates dendritic development and synaptic plasticity in the cerebellar purkinje cells.J Neurosci.2011.2011.https: / / doi.org / 10.1523 / JNEUROSCI.5337-10.2011. 46.Yu Z,Kryzer TJ,Griesmann GE,Kim KK,Benarroch EE,Lennon VA.CRMP-5 neuronal autoantibody:Marker of lung cancer and thymoma-related autoimmunity.Ann Neurol.2001.2001.https: / / doi.org / 10.1002 / 1531-8249(20010201)49:2<146::AID-ANA34>3.0.CO;2-E. 47.Qin L,Liu X,Liu S,Liu Y,Yang Y,Yang H,et al.Differentially expressed proteins underlying childhood cortical dysplasia with epilepsy identified by iTRAQ proteomic profiling.PLoS One.2017.2017.https: / / doi.org / 10.1371 / journal.pone.0172214. 48.Yeh E,Dao DQ,Wu ZY,Kandalam SM,Camacho FM,Tom C,et al.Patient-derived iPSCs show premature neural differentiation and neuron type-specific phenotypes relevant to neurodevelopment.Mol Psychiatry.2018.2018.https: / / doi.org / 10.1038 / mp.2017.238. 49.Schleinitz D,Seidel A,Stassart R,Klammt J,Hirrlinger PG,Winkler U,et al.Novel mutations in the asparagine synthetase gene(ASNS)associated with microcephaly.Front Genet.2018.2018.https: / / doi.org / 10.3389 / fgene.2018.00245. 50.Sonzogni M,Zhai P,Mientjes EJ,Van Woerden GM,Elgersma Y.Assessing the requirements of prenatal UBE3A expression for rescue of behavioral phenotypes in a mouse model for Angelman syndrome.Mol Autism.2020.2020.https: / / doi.org / 10.1186 / s13229-020-00376-9. 51.Rotaru DC,van Woerden GM,Wallaard I,Elgersma Y.Adult Ube3a gene reinstatement restores the electrophysiological deficits of prefrontal cortex layer 5 neurons in a mouse model of angelman syndrome.J Neurosci.2018.2018.https: / / doi.org / 10.1523 / JNEUROSCI.0083-18.2018. 52.Park AJ,Havekes R,Fu X,Hansen R,Tudor JC,Peixoto L,et al.Learning induces the translin / trax RNase complex to express activin receptors for persistent memory.Elife.2017.2017.https: / / doi.org / 10.7554 / eLife.27872. 53.Suedhof TC.Synaptic Vesicles:An Organelle Comes of Age.Cell.2006. 54.Alexander-Kaufman K,Harper C.Transketolase:observations in alcohol-related brain damage research.Int J Biochem Cell Biol.2009;41:717-720. 55.Boyle L,Wamelink MMC,Salomons GS,Roos B,Pop A,Dauber A,et al.Mutations in TKT Are the Cause of a Syndrome Including Short Stature,Developmental Delay,and Congenital Heart Defects.Am J Hum Genet.2016.2016.https: / / doi.org / 10.1016 / j.ajhg.2016.03.030. 56.Kruger NJ,Von Schaewen A.The oxidative pentose phosphate pathway:Structure and organisation.Curr Opin Plant Biol.2003. 57.Snaebjornsson MT,Schulze A.Non-canonical functions of enzymes facilitate cross-talk between cell metabolic and regulatory pathways.Exp Mol Med.2018. 58.Scheltema RA,Hauschild J-P,Lange O,Hornburg D,Denisov E,Damoc E,et al.The Q Exactive HF,a Benchtop Mass Spectrometer with a Pre-filter,High-performance Quadrupole and an Ultra-high-field Orbitrap Analyzer.Mol Cell Proteomics.2014;13:3698-3708. 59.Bruderer R,Bernhardt OM,Gandhi T,Xuan Y,Sondermann J,Schmidt M.Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results.Mol Cell Proteomics.2017;41. 60.Hebert AS,Richards AL,Bailey DJ,Ulbrich A,Coughlin EE,Westphall MS,et al.The one hour yeast proteome.Mol Cell Proteomics.2014.2014.https: / / doi.org / 10.1074 / mcp.M113.034769. 61.Callister SJ,Barry RC,Adkins JN,Johnson ET,Qian WJ,Webb-Robertson BJM,et al.Normalization approaches for removing systematic biases associated with mass spectrometry and label-free proteomics.J Proteome Res.2006.2006.https: / / doi.org / 10.1021 / pr050300l. 62.R Core Team.R Core Team(2014).R:A language and environment for statistical computing.R Found Stat Comput Vienna,Austria URL Http / / WwwR-ProjectOrg / .2014.2014. 63.Tyanova S,Temu T,Sinitcyn P,Carlson A,Hein MY,Geiger T,et al.The Perseus computational platform for comprehensive analysis of(prote)omics data.Nat Methods.2016. 64.Gaston A,Sanchez MG.DiscriMiner:Tools of the Trade for Discriminant Analysis.R Packag Version 01-29.2013.2013. 65.Redei GP.SAM(significance analysis of microarrays).Encycl.Genet.Genomics,Proteomics Informatics,2008. 66.Storey JD.A direct approach to false discovery rates.J R Stat Soc Ser B Stat Methodol.2002.2002.https: / / doi.org / 10.1111 / 1467-9868.00346. 67.Bateman A.UniProt:A worldwide hub of protein knowledge.Nucleic Acids Res.2019.2019.https: / / doi.org / 10.1093 / nar / gky1049. 68.Costa V,Aigner S,Vukcevic M,Sauter E,Behr K,Ebeling M,et al.MTORC1 Inhibition Corrects Neurodevelopmental and Synaptic Alterations in a Human Stem Cell Model of Tuberous Sclerosis.Cell Rep.2016;15:86-95.

Claims

1. 1. A method for measuring the regulation of expression of a UBE3A protein in a tissue sample, comprising: a) providing a tissue sample from an animal or cell culture that has been treated with a UBE3A modulator; b) measuring the protein expression level in the sample of step a) of at least one protein selected from the group consisting of TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3; c) comparing the protein expression level of the at least one protein measured in step b) with the protein expression level of the at least one protein in a control; wherein the modulated protein expression level of the at least one protein measured in step b) compared to the protein expression level of the at least one protein in the control indicates modulation of expression of UBE3A protein.

2. 10. The method of claim 1 for measuring induction of UBE3A protein expression in a tissue sample, comprising: d) providing a tissue sample from an animal or cell culture treated with a UBE3A inducer; e) measuring the protein expression level in the sample of step a) of at least one protein selected from the group consisting of TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3; f) comparing the protein expression level of the at least one protein measured in step b) with the protein expression level of the at least one protein in a control; wherein a decreased protein expression level of the at least one protein measured in step b) compared to the protein expression level of the at least one protein in the control indicates induced expression of UBE3A protein.

3. 1. A method for determining the engagement of a UBE3A modulator with a UBE3A target, comprising: a) providing a tissue sample from an animal or cell culture that has been treated with a UBE3A modulator; b) measuring the protein expression level in the sample of step a) of at least one protein selected from the group consisting of TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3; c) comparing the protein expression level of the at least one protein measured in step b) with the protein expression level of the at least one protein in a control; wherein the modulated protein expression level of the at least one protein measured in step b) compared to the protein expression level of the at least one protein in the control indicates involvement of the UBE3A modulator in a UBE3A target.

4. 4. The method of claim 1 or 3, wherein the tissue sample is a blood sample, a plasma sample, or a CSF sample.

5. 4. The method of claim 1 or 3, wherein the protein expression level is measured using Western blotting, mass spectrometry (MS), liquid chromatography-mass spectrometry (LC-MS), or immunoassay.

6. The method of claim 1 or 3, wherein the UBE3A modulator is an antisense oligonucleotide, particularly an LNA antisense oligonucleotide.

7. The method of claim 1 or 3, wherein the UBE3A modulator is a UBE3A protein expression level inducer for the treatment of autism spectrum disorder, Angelman syndrome, or 15qdup syndrome.

8. The method of claim 1 or 3, wherein the protein in step b) is selected from the group consisting of TKT, DZANK1, UBLCP1 and PSME3, and the expression levels of these proteins are inversely correlated with the expression level of UBE3A.

9. The method of claim 1 or 3, wherein the proteins in step b) are selected from the group consisting of ACYP1, YARS, WARS and SOD2, and the expression levels of these proteins are directly correlated with the expression level of UBE3A protein expression level.

10. A screening method for identifying a regulator of UBE3A protein expression, comprising: a) providing a tissue sample from an animal or cell culture that has been treated with a test compound; b) measuring the protein expression level in the sample of step a) of at least one protein selected from the group consisting of TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3; c) comparing the protein expression level of the at least one protein measured in step b) with the protein expression level of the at least one protein in a control; wherein a modulated protein expression level of the at least one protein measured in step b) compared to the protein expression level of the at least one protein in the control is indicative of a UBE3A protein expression modulator.

11. 1. Use of a protein selected from the group consisting of TKT, DZANK1, ACYP1, UBLCP1, YARS, WARS, SOD2 and PSME3 as a biomarker for regulating UBE3A protein expression levels.

12. The use according to claim 11, wherein the regulation of UBE3A is by a UBE3A protein expression level inducer.

13. The use of claim 11, wherein the protein expression level of the UBE3A biomarker protein is inversely correlated with the UBE3A protein expression level.

14. The use of claim 11 , wherein the protein expression level of the UBE3A biomarker protein directly correlates with the UBE3A protein expression level.

15. The use according to claim 11 for determining the involvement of a regulator of UBE3A protein expression level in a UBE3A target.

16. The use according to claim 11, wherein the UBE3A protein expression level regulator is an antisense oligonucleotide, in particular an LNA antisense oligonucleotide.

17. The use according to any one of claims 11 to 16, wherein the UBE3A protein expression level regulator is a UBE3A protein expression level inducer for the treatment of autism spectrum disorder, Angelman syndrome, or 15qdup syndrome.

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