Impaired OTUD7A-dependent Ankyrin regulation mediates neuronal dysfunction in mouse and human models of the 15q13.3 microdeletion syndrome.

Copy number variations (CNVs) are associated with psychiatric and neurodevelopmental disorders (NDDs), and most, including the recurrent 15q13.3 microdeletion disorder, have unknown disease mechanisms. We used a heterozygous 15q13.3 microdeletion mouse model and patient iPSC-derived neurons to reveal developmental defects in neuronal maturation and network activity. To identify the underlying molecular dysfunction, we developed a neuron-specific proximity-labeling proteomics (BioID2) pipeline, combined with patient mutations, to target the 15q13.3 CNV genetic driver OTUD7A. OTUD7A is an emerging independent NDD risk gene with no known function in the brain, but has putative deubiquitinase function. The OTUD7A protein-protein interaction network included synaptic, axonal, and cytoskeletal proteins and was enriched for ASD and epilepsy risk genes (Ank3, Ank2, SPTAN1, SPTBN1). The interactions between OTUD7A and Ankyrin-G (Ank3) and Ankyrin-B (Ank2) were disrupted by an epilepsy-associated OTUD7A L233F variant. Further investigation of Ankyrin-G in mouse and human 15q13.3 microdeletion and OTUD7AL233F/L233F models revealed protein instability, increased polyubiquitination, and decreased levels in the axon initial segment, while structured illumination microscopy identified reduced Ankyrin-G nanodomains in dendritic spines. Functional analysis of human 15q13.3 microdeletion and OTUD7AL233F/L233F models revealed shared and distinct impairments to axonal growth and intrinsic excitability. Importantly, restoring OTUD7A or Ankyrin-G expression in 15q13.3 microdeletion neurons led to a reversal of abnormalities. These data reveal a critical OTUD7A-Ankyrin pathway in neuronal development, which is impaired in the 15q13.3 microdeletion syndrome, leading to neuronal dysfunction. Furthermore, our study highlights the utility of targeting CNV genes using cell type-specific proteomics to identify shared and unexplored disease mechanisms across NDDs.

Identification of HnRNPC as a novel Tau exon 10 splicing factor using RNA antisense purification mass spectrometry.

Alternative splicing in Tau exon 10 generates 3 R- and 4 R-Tau proteoforms, which have equal abundance in healthy adult human brain. Aberrant alternative splicing in Tau exon 10 leads to distortion of the balanced 3 R- and 4 R-Tau expression levels, which is a causal factor to trigger toxic Tau aggregation, neuron dysfunction and patient death in a group of neurodegenerative diseases known as tauopathies. Hence, identification of regulators upstream of the Tau exon 10 splicing events are crucial to understanding pathogenic mechanisms driving tauopathies. In this study, we used RNA Antisense Purification with Mass Spectrometry (RAP-MS) analysis to identify RNA-binding proteins (RBPs) that interact with the Tau pre-mRNA near exon 10. Among the newly identified RBP candidates, we show that knockdown of hnRNPC induces Tau exon 10 skipping whereas overexpression of hnRNPC promotes Tau exon 10 inclusion. In addition, we show that hnRNPC interacts with the poly-uridine (U-tract) sequences in introns 9 and 10 of Tau pre-mRNA. Mutation of these U-tract motifs abolished binding of hnRNPC with Tau pre-mRNA fragment and blocked its impact on Tau exon 10 inclusion. These findings indicate that hnRNPC binds and utilizes these U-tract motifs located in introns 9 and 10 of Tau pre-mRNA to promote Tau exon 10 inclusion. Intriguingly, high hnRNPC expression level is associated with progressive supranuclear palsy (PSP), a sporadic tauopathy with pathological accumulation of Tau species that contain exon 10, which suggests a putative therapeutic role of hnRNPC for PSP treatment. [Figure: see text].

Proteomic Analysis Reveals Autism-Associated Gene DIXDC1 Regulates Proteins Associated with Mitochondrial Organization and Function.

DIX-domain containing 1 (Dixdc1) is an important regulator of neuronal development including cortical neurogenesis, neuronal migration and synaptic connectivity, and sequence variants in the gene have been linked to autism spectrum disorders (ASDs). Previous studies indicate that Dixdc1 controls neurogenesis through Wnt signaling, whereas its regulation of dendrite and synapse development requires Wnt and cytoskeletal signaling. However, the prediction of these signaling pathways is primarily based on the structure of Dixdc1. Given the role of Dixdc1 in neural development and brain disorders, we hypothesized that Dixdc1 may regulate additional signaling pathways in the brain. We performed transcriptomic and proteomic analyses of Dixdc1 KO mouse cortices to reveal such alterations. We found that transcriptomic approaches do not yield any novel findings about the downstream impacts of Dixdc1. In comparison, our proteomic approach reveals that several important mitochondrial proteins are significantly dysregulated in the absence of Dixdc1, suggesting a novel function of Dixdc1.

NHS-Ester Tandem Labeling in One Pot Enables 48-Plex Quantitative Proteomics.

Stable-isotope labeling strategies are extensively used for multiplex quantitative proteomics. Hybrid-isotope labeling strategies that combine the use of isotopic mass difference labeling and isobaric tags can greatly increase sample multiplexity. In this work, we present a novel hybrid-isotope labeling approach that we termed NHS-ester tandem labeling in one pot (NETLOP). We first optimized 16-plex isobaric TMTpro labeling of lysine residues followed by 2-plex or 3-plex isotopic mTRAQ labeling of peptide N-termini, both of which with commercially available NHS-ester reactive reagents. We then demonstrated the utility of the NETLOP approach by labeling HeLa cell samples and performing proof-of-principle quantitative 32-plex and 48-plex proteomic analyses, each in a single LC-MS/MS experiment. Compared to current hybrid-isotope labeling methods, our NETLOP approach requires no sample cleanup between different labeling steps to minimize sample loss, induces no retention time shifts that compromise quantification accuracy, can be adapted to other NHS-ester isotopic labeling reagents to further increase multiplexity, and is compatible with samples from any origin in a wide array of biological and clinical proteomics applications.

NanoTPOT: Enhanced Sample Preparation for Quantitative Nanoproteomic Analysis.

With the ever-growing need for protein-level understanding in pathological research, proteomics researchers thrive to examine detailed proteome dynamics using crucial, yet often limited, primary and clinical samples. Aside from mass spectrometer instrumentation advancement, a single-tube-based high-throughput sample processing workflow is imperative to ensure sensitive, quantitative, and reproducible protein analysis for these increasingly sophisticated studies. Leveraging the benefits of an acid-cleavable detergent, RapiGest SF Surfactant (Waters Corporation), we developed and optimized a nanoproteomic workflow that we termed Nanogram TMT Processing in One Tube (NanoTPOT). Through the assessment of proteolytic digestion, tandem mass tag (TMT) labeling, online and offline fractionation strategies, our optimized workflow effectively eliminated the need for sample desalting and enabled compatible sample processing for mass spectrometry analysis. We further applied the NanoTPOT workflow to examine cellular response to stress caused by dithiothreitol in HeLa cells, where we identified and quantified 6935 and 5474 proteins in TMT 10-plex experiments with one microgram of lysate protein and 2000 sorted HeLa cells (roughly half microgram lysate protein) in each channel, respectively. Our workflow has been proven to be an effective alternative for current nanoproteomic sample processing to minimize sample loss in biological and clinical applications.

Step-Wise Assessment and Optimization of Sample Handling Recovery Yield for Nanoproteomic Analysis of 1000 Mammalian Cells.

Protein and peptide adhesion is a major factor contributing to sample loss during proteomic sample preparation workflows. Sample loss often has detrimental effects on the quality of proteomic analysis by compromising protein identification and data reproducibility. When starting with a low sample amount, only the most abundant proteins can be identified, which often offers little insights for biological research. Although the general idea about severe sample loss from low amount of starting material is widely presumed in the proteomics field, quantitative assessment on the impact of sample loss has been poorly investigated. In the present study, we have quantitatively assessed sample loss during each step of a conventional in-solution sample preparation workflow using bicinchoninic acid (BCA) and targeted LC/MS/MS protein and peptide assays. According to our assessment, for starting materials of ∼1000 mammalian cells, surface adhesion, along with desalting and speed-vacuum drying steps, all contribute heavily to sample loss, in particular for low-abundance proteins. With this knowledge, we have adapted slippery liquid infused porous surface (SLIPS) treatment, commercial LoBind tubes, and in-line desalting during sample processing. With these improvements, we were able to use a conventional in-solution sample handling method to identify on average 829 proteins with 1000 U2OS osteosarcoma cells (∼100 ng) with 75-min LC/MS/MS runs, an 11-fold increase in protein identification. Our optimized in-solution workflow is straightforward and also much less equipment- and technique-demanding than other advanced sample preparation protocols in the field.

Neuron-specific protein network mapping of autism risk genes identifies shared biological mechanisms and disease-relevant pathologies.

There are hundreds of risk genes associated with autism spectrum disorder (ASD), but signaling networks at the protein level remain unexplored. We use neuron-specific proximity-labeling proteomics (BioID2) to identify protein-protein interaction (PPI) networks for 41 ASD risk genes. Neuron-specific PPI networks, including synaptic transmission proteins, are disrupted by de novo missense variants. The PPI network map reveals convergent pathways, including mitochondrial/metabolic processes, Wnt signaling, and MAPK signaling. CRISPR knockout displays an association between mitochondrial activity and ASD risk genes. The PPI network shows an enrichment of 112 additional ASD risk genes and differentially expressed genes from postmortem ASD patients. Clustering of risk genes based on PPI networks identifies gene groups corresponding to clinical behavior score severity. Our data report that cell type-specific PPI networks can identify individual and convergent ASD signaling networks, provide a method to assess patient variants, and highlight biological insight into disease mechanisms and sub-cohorts of ASD.

Characterization of an RNA binding protein interactome reveals a context-specific post-transcriptional landscape of MYC-amplified medulloblastoma.

Pediatric medulloblastoma (MB) is the most common solid malignant brain neoplasm, with Group 3 (G3) MB representing the most aggressive subgroup. MYC amplification is an independent poor prognostic factor in G3 MB, however, therapeutic targeting of the MYC pathway remains limited and alternative therapies for G3 MB are urgently needed. Here we show that the RNA-binding protein, Musashi-1 (MSI1) is an essential mediator of G3 MB in both MYC-overexpressing mouse models and patient-derived xenografts. MSI1 inhibition abrogates tumor initiation and significantly prolongs survival in both models. We identify binding targets of MSI1 in normal neural and G3 MB stem cells and then cross referenced these data with unbiased large-scale screens at the transcriptomic, translatomic and proteomic levels to systematically dissect its functional role. Comparative integrative multi-omic analyses of these large datasets reveal cancer-selective MSI1-bound targets sharing multiple MYC associated pathways, providing a valuable resource for context-specific therapeutic targeting of G3 MB.

Metabolic flexibility determines human NK cell functional fate in the tumor microenvironment.

NK cells are central to anti-tumor immunity and recently showed efficacy for treating hematologic malignancies. However, their dysfunction in the hostile tumor microenvironment remains a pivotal barrier for cancer immunotherapies against solid tumors. Using cancer patient samples and proteomics, we found that human NK cell dysfunction in the tumor microenvironment is due to suppression of glucose metabolism via lipid peroxidation-associated oxidative stress. Activation of the Nrf2 antioxidant pathway restored NK cell metabolism and function and resulted in greater anti-tumor activity in vivo. Strikingly, expanded NK cells reprogrammed with complete metabolic substrate flexibility not only sustained metabolic fitness but paradoxically augmented their tumor killing in the tumor microenvironment and in response to nutrient deprivation. Our results uncover that metabolic flexibility enables a cytotoxic immune cell to exploit the metabolic hostility of tumors for their advantage, addressing a critical hurdle for cancer immunotherapy.