Nuclear-Import Receptors Reverse Aberrant Phase Transitions of RNA-Binding Proteins with Prion-like Domains.

RNA-binding proteins (RBPs) with prion-like domains (PrLDs) phase transition to functional liquids, which can mature into aberrant hydrogels composed of pathological fibrils that underpin fatal neurodegenerative disorders. Several nuclear RBPs with PrLDs, including TDP-43, FUS, hnRNPA1, and hnRNPA2, mislocalize to cytoplasmic inclusions in neurodegenerative disorders, and mutations in their PrLDs can accelerate fibrillization and cause disease. Here, we establish that nuclear-import receptors (NIRs) specifically chaperone and potently disaggregate wild-type and disease-linked RBPs bearing a NLS. Karyopherin-ß2 (also called Transportin-1) engages PY-NLSs to inhibit and reverse FUS, TAF15, EWSR1, hnRNPA1, and hnRNPA2 fibrillization, whereas Importin-α plus Karyopherin-ß1 prevent and reverse TDP-43 fibrillization. Remarkably, Karyopherin-ß2 dissolves phase-separated liquids and aberrant fibrillar hydrogels formed by FUS and hnRNPA1. In vivo, Karyopherin-ß2 prevents RBPs with PY-NLSs accumulating in stress granules, restores nuclear RBP localization and function, and rescues degeneration caused by disease-linked FUS and hnRNPA2. Thus, NIRs therapeutically restore RBP homeostasis and mitigate neurodegeneration.

GM130 Regulates Golgi-Derived Spindle Assembly by Activating TPX2 and Capturing Microtubules.

Spindle assembly requires the coordinated action of multiple cellular structures to nucleate and organize microtubules in a precise spatiotemporal manner. Among them, the contributions of centrosomes, chromosomes, and microtubules have been well studied, yet the involvement of membrane-bound organelles remains largely elusive. Here, we provide mechanistic evidence for a membrane-based, Golgi-derived microtubule assembly pathway in mitosis. Upon mitotic entry, the Golgi matrix protein GM130 interacts with importin α via a classical nuclear localization signal that recruits importin α to the Golgi membranes. Sequestration of importin α by GM130 liberates the spindle assembly factor TPX2, which activates Aurora-A kinase and stimulates local microtubule nucleation. Upon filament assembly, nascent microtubules are further captured by GM130, thus linking Golgi membranes to the spindle. Our results reveal an active role for the Golgi in regulating spindle formation to ensure faithful organelle inheritance.

PQBP1 promotes translational elongation and regulates hippocampal mGluR-LTD by suppressing eEF2 phosphorylation.

Eukaryotic elongation factor 2 (eEF2) mediates translocation of peptidyl-tRNA from the ribosomal A site to the P site to promote translational elongation. Its phosphorylation on Thr56 by its single known kinase eEF2K inactivates it and inhibits translational elongation. Extensive studies have revealed that different signal cascades modulate eEF2K activity, but whether additional factors regulate phosphorylation of eEF2 remains unclear. Here, we find that the X chromosome-linked intellectual disability protein polyglutamine-binding protein 1 (PQBP1) specifically binds to non-phosphorylated eEF2 and suppresses eEF2K-mediated phosphorylation at Thr56. Loss of PQBP1 significantly reduces general protein synthesis by suppressing translational elongation. Moreover, we show that PQBP1 regulates hippocampal metabotropic glutamate receptor-dependent long-term depression (mGluR-LTD) and mGluR-LTD-associated behaviors by suppressing eEF2K-mediated phosphorylation. Our results identify PQBP1 as a novel regulator in translational elongation and mGluR-LTD, and this newly revealed regulator in the eEF2K/eEF2 pathway is also an excellent therapeutic target for various disease conditions, such as neural diseases, virus infection, and cancer.

Deciphering the genetic architecture of human brain structure and function: a brief survey on recent advances of neuroimaging genomics.

Brain imaging genomics is an emerging interdisciplinary field, where integrated analysis of multimodal medical image-derived phenotypes (IDPs) and multi-omics data, bridging the gap between macroscopic brain phenotypes and their cellular and molecular characteristics. This approach aims to better interpret the genetic architecture and molecular mechanisms associated with brain structure, function and clinical outcomes. More recently, the availability of large-scale imaging and multi-omics datasets from the human brain has afforded the opportunity to the discovering of common genetic variants contributing to the structural and functional IDPs of the human brain. By integrative analyses with functional multi-omics data from the human brain, a set of critical genes, functional genomic regions and neuronal cell types have been identified as significantly associated with brain IDPs. Here, we review the recent advances in the methods and applications of multi-omics integration in brain imaging analysis. We highlight the importance of functional genomic datasets in understanding the biological functions of the identified genes and cell types that are associated with brain IDPs. Moreover, we summarize well-known neuroimaging genetics datasets and discuss challenges and future directions in this field.

MorbidGCN: prediction of multimorbidity with a graph convolutional network based on integration of population phenotypes and disease network.

Exploring multimorbidity relationships among diseases is of great importance for understanding their shared mechanisms, precise diagnosis and treatment. However, the landscape of multimorbidities is still far from complete due to the complex nature of multimorbidity. Although various types of biological data, such as biomolecules and clinical symptoms, have been used to identify multimorbidities, the population phenotype information (e.g. physical activity and diet) remains less explored for multimorbidity. Here, we present a graph convolutional network (GCN) model, named MorbidGCN, for multimorbidity prediction by integrating population phenotypes and disease network. Specifically, MorbidGCN treats the multimorbidity prediction as a missing link prediction problem in the disease network, where a novel feature selection method is embedded to select important phenotypes. Benchmarking results on two large-scale multimorbidity data sets, i.e. the UK Biobank (UKB) and Human Disease Network (HuDiNe) data sets, demonstrate that MorbidGCN outperforms other competitive methods. With MorbidGCN, 9742 and 14 010 novel multimorbidities are identified in the UKB and HuDiNe data sets, respectively. Moreover, we notice that the selected phenotypes that are generally differentially distributed between multimorbidity patients and single-disease patients can help interpret multimorbidities and show potential for prognosis of multimorbidities.

Matrix factorization for biomedical link prediction and scRNA-seq data imputation: an empirical survey.

Advances in high-throughput experimental technologies promote the accumulation of vast number of biomedical data. Biomedical link prediction and single-cell RNA-sequencing (scRNA-seq) data imputation are two essential tasks in biomedical data analyses, which can facilitate various downstream studies and gain insights into the mechanisms of complex diseases. Both tasks can be transformed into matrix completion problems. For a variety of matrix completion tasks, matrix factorization has shown promising performance. However, the sparseness and high dimensionality of biomedical networks and scRNA-seq data have raised new challenges. To resolve these issues, various matrix factorization methods have emerged recently. In this paper, we present a comprehensive review on such matrix factorization methods and their usage in biomedical link prediction and scRNA-seq data imputation. Moreover, we select representative matrix factorization methods and conduct a systematic empirical comparison on 15 real data sets to evaluate their performance under different scenarios. By summarizing the experimental results, we provide general guidelines for selecting matrix factorization methods for different biomedical matrix completion tasks and point out some future directions to further improve the performance for biomedical link prediction and scRNA-seq data imputation.

The role of PQBP1 in neural development and function.

Mutations in the polyglutamine tract-binding protein 1 (PQBP1) gene are associated with Renpenning syndrome, which is characterized by microcephaly, intellectual deficiency, short stature, small testes, and distinct facial dysmorphism. Studies using different models have revealed that PQBP1 plays essential roles in neural development and function. In this mini-review, we summarize recent findings relating to the roles of PQBP1 in these processes, including in the regulation of neural progenitor proliferation, neural projection, synaptic growth, neuronal survival, and cognitive function via mRNA transcription and splicing-dependent or -independent processes. The novel findings provide insights into the mechanisms underlying the pathogenesis of Renpenning syndrome and may advance drug discovery and treatment for this condition.

Gαq splice variants mediate phototransduction, rhodopsin synthesis, and retinal integrity in Drosophila.

Heterotrimeric G proteins mediate a variety of signaling processes by coupling G protein-coupled receptors to intracellular effector molecules. In Drosophila, the Gαq gene encodes several Gαq splice variants, with the Gαq1 isoform protein playing a major role in fly phototransduction. However, Gαq1 null mutant flies still exhibit a residual light response, indicating that other Gαq splice variants or additional Gq α subunits are involved in phototransduction. Here, we isolated a mutant fly with no detectable light responses, decreased rhodopsin (Rh) levels, and rapid retinal degeneration. Using electrophysiological and genetic studies, biochemical assays, immunoblotting, real-time RT-PCR, and EM analysis, we found that mutations in the Gαq gene disrupt light responses and demonstrate that the Gαq3 isoform protein is responsible for the residual light response in Gαq1 null mutants. Moreover, we report that Gαq3 mediates rhodopsin synthesis. Depletion of all Gαq splice variants led to rapid light-dependent retinal degeneration, due to the formation stable Rh1-arrestin 2 (Arr2) complexes. Our findings clarify essential roles of several different Gαq splice variants in phototransduction and retinal integrity in Drosophila and reveal that Gαq3 functions in rhodopsin synthesis.

The Renpenning syndrome-associated protein PQBP1 facilitates the nuclear import of splicing factor TXNL4A through the karyopherin ß2 receptor.

Renpenning syndrome belongs to a group of X-linked intellectual disability disorders. The Renpenning syndrome-associated protein PQBP1 (polyglutamine-binding protein 1) is intrinsically disordered, associates with several splicing factors, and is involved in pre-mRNA splicing. PQBP1 uses its C-terminal YxxPxxVL motif for binding to the splicing factor TXNL4A (thioredoxin like 4A), but the biological function of this interaction has yet to be elucidated. In this study, using recombinant protein expression, in vitro binding assays, and immunofluorescence microscopy in HeLa cells, we found that a recently reported X-linked intellectual disability-associated missense mutation, resulting in the PQBP1-P244L variant, disrupts the interaction with TXNL4A. We further show that this interaction is critical for the subcellular location of TXNL4A. In combination with other PQBP1 variants lacking a functional nuclear localization signal required for recognition by the nuclear import receptor karyopherin ß2, we demonstrate that PQBP1 facilitates the nuclear import of TXNL4A via a piggyback mechanism. These findings expand our understanding of the molecular basis of the PQBP1-TXNL4A interaction and of the etiology and pathogenesis of Renpenning syndrome and related disorders.

A graph regularized generalized matrix factorization model for predicting links in biomedical bipartite networks.

MOTIVATION: Predicting potential links in biomedical bipartite networks can provide useful insights into the diagnosis and treatment of complex diseases and the discovery of novel drug targets. Computational methods have been proposed recently to predict potential links for various biomedical bipartite networks. However, existing methods are usually rely on the coverage of known links, which may encounter difficulties when dealing with new nodes without any known link information. RESULTS: In this study, we propose a new link prediction method, named graph regularized generalized matrix factorization (GRGMF), to identify potential links in biomedical bipartite networks. First, we formulate a generalized matrix factorization model to exploit the latent patterns behind observed links. In particular, it can take into account the neighborhood information of each node when learning the latent representation for each node, and the neighborhood information of each node can be learned adaptively. Second, we introduce two graph regularization terms to draw support from affinity information of each node derived from external databases to enhance the learning of latent representations. We conduct extensive experiments on six real datasets. Experiment results show that GRGMF can achieve competitive performance on all these datasets, which demonstrate the effectiveness of GRGMF in prediction potential links in biomedical bipartite networks. AVAILABILITY AND IMPLEMENTATION: The package is available at https://github.com/happyalfred2016/GRGMF. CONTACT: leouyang@szu.edu.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Behavioral analyses in mouse models of autism spectrum disorders.

Autism spectrum disorder is a group of genetically-related developmental disorders of the nervous system. Patients mainly present with core symptoms such as social behavior defects, repetitive stereotyped behaviors, and learning and memory disorders. The mouse models are critical for the studies of the pathogenic mechanisms and potential therapeutic strategies of autism spectrum disorder. The assessments of mouse behaviors provide understandings of the effects of different genetic manipulations as well as pathogenic mechanisms of these diseases. This article describes various mouse behavioral assays corresponding to the core symptoms of ASD patients and provides a detailed description of protocols, cautions, and data analysis for those assays, thereby helping researchers to establish their own experimental designs. In addition, behavioral phenotypes of currently known ASD mouse models are summarized to provide a reference for researchers in the field.

Metallophosphoesterase regulates light-induced rhodopsin endocytosis by promoting an association between arrestin and the adaptor protein AP2.

Light-induced endocytosis of rhodopsin in the retina is critical for preventing photoreceptor hyperactivity and for the survival of photoreceptor cells. In Drosophila, this process is mediated by arrestin1 (Arr1). Because Arr1 lacks a clathrin-binding domain required for receptor internalization and the C-terminal sequence that interacts with the ß-subunit of the clathrin adaptor protein AP2, the mechanism of how Arr1 mediates endocytosis of the major rhodopsin Rh1 is unclear. Here, using several approaches, including Arr binding and pulldown assays, immunofluorescence techniques, and EM imaging, we found that Drosophila metallophosphoesterase (dMPPE) is involved in light-induced rhodopsin endocytosis. We observed that the photoreceptor cells of a dmppe mutant exhibit impaired light-induced rhodopsin endocytosis and that this impairment is independent of dMPPE phosphoesterase activity. Furthermore, dMPPE directly interacted with Arr1 and promoted the association of Arr1 with AP2. Of note, genetic dmppe deletion largely prevented retinal degeneration in norpA (encoding phospholipase C) mutants, which were reported previously to contribute to retinal degeneration, by suppressing Rh1 endocytosis. Our findings demonstrate that Arr1 interacts with AP2 and that dMPPE functions as a critical regulator in Rh1 endocytosis and retinal degeneration.

Mutations of PQBP1 in Renpenning syndrome promote ubiquitin-mediated degradation of FMRP and cause synaptic dysfunction.

Renpenning syndrome is a group of X-linked intellectual disability syndromes caused by mutations in human polyglutamine-binding protein 1 (PQBP1) gene. Little is known about the molecular pathogenesis of the various mutations that cause the notable variability in patients. In this study, we examine the cellular and synaptic functions of the most common mutations found in the patients: c.461_462delAG, c.459_462delAGAG and c.463_464dupAG in an AG hexamer in PQBP1 exon 4. We discovered that PQBP1 c.459_462delAGAG and c.463_464dupAG mutations encode a new C-terminal epitope that preferentially binds non-phosphorylated fragile X mental retardation protein (FMRP) and promotes its ubiquitin-mediated degradation. Impairment of FMRP function up-regulates its targets such as MAP1B, and disrupts FMRP-dependent synaptic scaling in primary cultured neurons. In Drosophila neuromuscular junction model, PQBP1 c.463_464dupAG transgenic flies showed remarkable defects of synaptic over-growth, which can be rescued by exogenously expressing dFMRP. Our data strongly support a gain-of-function pathogenic mechanism of PQBP1 c.459_462delAGAG and c.463_464dupAG mutations, and suggest that therapeutic strategies to restore FMRP function may be beneficial for those patients.

X chromosome-linked intellectual disability protein PQBP1 associates with and regulates the translation of specific mRNAs.

X chromosome-linked intellectual disability is a common developmental disorder, and mutations of the polyglutamine-binding protein 1 (PQBP1) gene have been linked to this disease. In addition to existing in the nucleus as a splicing factor, PQBP1 is also found in cytoplasmic RNA granules, where it associates with RNA-binding proteins. However, the roles of cytoplasmic PQBP1 are largely unknown. Here, we show that the Drosophila homolog of PQBP1 (dPQBP1) is present in the cytoplasm of photoreceptor cells, and its loss results in defective rhabdomere morphogenesis, which is due to impaired Chaoptin translation. We also show that dPQBP1 regulates mRNA translation by interacting with dFMR1, which binds to specific mRNAs and facilitates their assembly into translating ribosomes, a function that is conserved for human PQBP1 and FMRP. Our findings reveal the conserved function of PQBP1 in mRNA translation and provide molecular insights into the pathogenic mechanisms underlying Renpenning syndrome.

Structural and energetic basis of ALS-causing mutations in the atypical proline-tyrosine nuclear localization signal of the Fused in Sarcoma protein (FUS).

Mutations in the proline/tyrosine-nuclear localization signal (PY-NLS) of the Fused in Sarcoma protein (FUS) cause amyotrophic lateral sclerosis (ALS). Here we report the crystal structure of the FUS PY-NLS bound to its nuclear import receptor Karyopherinß2 (Kapß2; also known as Transportin). The FUS PY-NLS occupies the structurally invariant C-terminal arch of Kapß2, tracing a path similar to that of other characterized PY-NLSs. Unlike other PY-NLSs, which generally bind Kapß2 in fully extended conformations, the FUS peptide is atypical as its central portion forms a 2.5-turn α-helix. The Kapß2-binding epitopes of the FUS PY-NLS consist of an N-terminal PGKM hydrophobic motif, a central arginine-rich α-helix, and a C-terminal PY motif. ALS mutations are found almost exclusively within these epitopes. Each ALS mutation site makes multiple contacts with Kapß2 and mutations of these residues decrease binding affinities for Kapß2 (K(D) for wild-type FUS PY-NLS is 9.5 nM) up to ninefold. Thermodynamic analyses of ALS mutations in the FUS PY-NLS show that the weakening of FUS-Kapß2 binding affinity, the degree of cytoplasmic mislocalization, and ALS disease severity are correlated.

Drosophila neuroligin 4 regulates sleep through modulating GABA transmission.

Sleep is an essential and evolutionarily conserved behavior that is closely related to synaptic function. However, whether neuroligins (Nlgs), which are cell adhesion molecules involved in synapse formation and synaptic transmission, are involved in sleep is not clear. Here, we show that Drosophila Nlg4 (DNlg4) is highly expressed in large ventral lateral clock neurons (l-LNvs) and that l-LNv-derived DNlg4 is essential for sleep regulation. GABA transmission is impaired in mutant l-LNv, and sleep defects in dnlg4 mutant flies can be rescued by genetic manipulation of GABA transmission. Furthermore, dnlg4 mutant flies exhibit a severe reduction in GABAA receptor RDL clustering, and DNlg4 associates with RDLs in vivo. These results demonstrate that DNlg4 regulates sleep through modulating GABA transmission in l-LNvs, which provides the first known link between a synaptic adhesion molecule and sleep in Drosophila.

A new simplified risk assessment model enhances postoperative prophylaxis of venous thromboembolism in Chinese adult patients with inguinal hernia (CHAT-3): A prospective, multicenter, randomized controlled trial.

BACKGROUND: Venous thromboembolism (VTE) significantly affects the prognosis of surgical patients with inguinal hernia. The complex Caprini score, commonly used for postoperative VTE risk assessment, poses practical challenges for surgeons in clinical settings. METHODS: The CHAT-3 trial, a prospective, multicenter, randomized controlled trial, compared a simple three-factor model to assess VTE risk against routine practices in post-inguinal hernia surgery (IHS) patients. The patients were randomly assigned (1:1) to the intervention or control arm. The intervention group used the three-factor model to identify patients at moderate or high risk of VTE for subsequent prophylaxis according to clinical guidelines. Both groups were followed for four weeks, with randomization implemented using computer-generated sequences. The primary outcome measured was the rate of VTE prophylaxis. Secondary outcomes included time spent on VTE risk assessment (surgeon self-reported), postoperative D-dimer trends, perioperative VTE occurrence, bleeding events, and the net clinical benefit. RESULTS: Of the 1,109 participants, 508 in the experimental group and 601 in the control group completed follow-up. The three-factor model showed higher VTE prophylaxis rates in all patients (pharmacologic prophylaxis: 26.2% vs. 6.00%, P<0.001) and particularly in those at high risk (pharmacologic prophylaxis: 57.3% vs. 9.50%, P<0.001). The experimental group significantly reduced VTE risk assessment time compared to the Caprini score (1.39±0.55 min vs. 5.73±1.35 min, P<0.001). The experimental group had lower D-dimer levels (0.26±0.73 mg/L vs. 0.35±0.55 mg/L, P=0.028). In the experimental group, the patients did not experience an increased risk of VTE (0% vs. 1.66%, P=0.268) and bleeding (1.18% vs. 0.67%, P=0.558) compared to the controls. There was no significant difference in net clinical benefit, which combined VTE and bleeding events, between the experimental and control groups (1.18% vs. 0.83%, P=0.559). CONCLUSION: Applying the simple three-factor model in perioperative VTE management could quickly identify the patient with a high risk of VTE and improve the prophylaxis rate of perioperative VTE. TRIAL REGISTRATION: XXX. TRIAL REGISTRATION: ChiCTR2000033769.

Improving Alzheimer's Disease Diagnosis With Multi-Modal PET Embedding Features by a 3D Multi-Task MLP-Mixer Neural Network.

Positron emission tomography (PET) with fluorodeoxyglucose (FDG) or florbetapir (AV45) has been proved effective in the diagnosis of Alzheimer's disease. However, the expensive and radioactive nature of PET has limited its application. Here, employing multi-layer perceptron mixer architecture, we present a deep learning model, namely 3-dimensional multi-task multi-layer perceptron mixer, for simultaneously predicting the standardized uptake value ratios (SUVRs) for FDG-PET and AV45-PET from the cheap and widely used structural magnetic resonance imaging data, and the model can be further used for Alzheimer's disease diagnosis based on embedding features derived from SUVR prediction. Experiment results demonstrate the high prediction accuracy of the proposed method for FDG/AV45-PET SUVRs, where we achieved Pearson's correlation coefficients of 0.66 and 0.61 respectively between the estimated and actual SUVR and the estimated SUVRs also show high sensitivity and distinct longitudinal patterns for different disease status. By taking into account PET embedding features, the proposed method outperforms other competing methods on five independent datasets in the diagnosis of Alzheimer's disease and discriminating between stable and progressive mild cognitive impairments, achieving the area under receiver operating characteristic curves of 0.968 and 0.776 respectively on ADNI dataset, and generalizes better to other external datasets. Moreover, the top-weighted patches extracted from the trained model involve important brain regions related to Alzheimer's disease, suggesting good biological interpretability of our proposed method."

High-Throughput Small Molecule Drug Screening For Age-Related Sleep Disorders Using Drosophila melanogaster.

Sleep, an essential component of health and overall well-being, often presents challenges for older individuals who frequently experience sleep disorders characterized by shortened sleep duration and fragmented patterns. These sleep disruptions also correlate with an increased risk of various illnesses in the elderly, including diabetes, cardiovascular diseases, and psychological disorders. Unfortunately, existing drugs for sleep disorders are associated with significant side effects such as cognitive impairment and addiction. Consequently, the development of new, safer, and more effective sleep disorder medications is urgently needed. However, the high cost and lengthy experimental duration of current drug screening methods remain limiting factors. This protocol describes a cost-effective and high-throughput screening method that utilizes Drosophila melanogaster, a species with a highly conserved sleep regulation mechanism compared to mammals, making it an ideal model for studying sleep disorders in the elderly. By administering various small compounds to aged flies, we can assess their effects on sleep disorders. The sleep behaviors of these flies are recorded using an infrared monitoring device and analyzed with the open-source data package Sleep and Circadian Analysis MATLAB Program 2020 (SCAMP2020). This protocol offers a low-cost, reproducible, and efficient screening approach for sleep regulation. Fruit flies, due to their short life cycle, low husbandry cost, and ease of handling, serve as excellent subjects for this method. As an illustration, Reserpine, one of the tested drugs, demonstrated the ability to promote sleep duration in elderly flies, highlighting the effectiveness of this protocol.

PQBP1 regulates striatum development through balancing striatal progenitor proliferation and differentiation.

The balance between cell proliferation and differentiation is essential for maintaining the neural progenitor pool and brain development. Although the mechanisms underlying cell proliferation and differentiation at the transcriptional level have been studied intensively, post-transcriptional regulation of cell proliferation and differentiation remains largely unclear. Here, we show that deletion of the alternative splicing regulator PQBP1 in striatal progenitors results in defective striatal development due to impaired neurogenesis of spiny projection neurons (SPNs). Pqbp1-deficient striatal progenitors exhibit declined proliferation and increased differentiation, resulting in a reduced striatal progenitor pool. We further reveal that PQBP1 associates with components in splicing machinery. The alternative splicing profiles identify that PQBP1 promotes the exon 9 inclusion of Numb, a variant that mediates progenitor proliferation. These findings identify PQBP1 as a regulator in balancing striatal progenitor proliferation and differentiation and provide alternative insights into the pathogenic mechanisms underlying Renpenning syndrome.