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Abstract The leucine-rich repeat kinase 2 (LRRK2) phosphorylates a subset of RAB GTPases, and their phosphorylation levels are elevated by Parkinson’s disease (PD)-linked mutations of LRRK2. However, the precise function of the LRRK2-regulated RAB GTPase in the brain remains to be elucidated. Here, we identify RAB12 as a robust LRRK2 substrate in the mouse brain through phosphoproteomics profiling and solve the structure of RAB12-LRRK2 protein complex through Cryo-EM analysis. Mechanistically, RAB12 cooperates with LRRK2 to inhibit primary ciliogenesis and regulate centrosome homeostasis in astrocytes through enhancing the phosphorylation of RAB10 and recruiting RILPL1, while the functions of RAB12 require a direct interaction with LRRK2 and LRRK2 activity. Furthermore, the ciliary and centrosome defects caused by the PD-linked LRRK2-G2019S mutation are prevented by Rab12 deletion in astrocytes. Thus, our study reveals a physiological function of the RAB12-LRRK2 complex in regulating ciliogenesis and centrosome homeostasis. The RAB12-LRRK2 structure offers a guidance in the therapeutic development of PD by targeting the RAB12-LRRK2 interaction.

Abstract Background Neuropathic pain (NP), which results from injury or lesion of the somatosensory nervous system, is intimately associated with glial cells. The roles of microglia and astrocytes in NP have been broadly described, while studies on oligodendrocytes have largely focused on axonal myelination. The mechanisms of oligodendrocytes and their interactions with other glial cells in NP development remain uncertain. Methods To explore the function of the interaction of the three glial cells and their interactions on myelin development in NP, we evaluated changes in NP and myelin morphology after a chronic constriction injury (CCI) model in mice, and used single-cell sequencing to reveal the subpopulations characteristics of oligodendrocytes, microglia, and astrocytes in the spinal cord tissues, as well as their relationship with myelin lesions; the proliferation and differentiation trajectories of oligodendrocyte subpopulations were also revealed using pseudotime cell trajectory and RNA velocity analysis. In addition, we identified chemokine ligand-receptor pairs between glial cells by cellular communication and verified them using immunofluorescence. Results Our study showed that NP peaked on day 7 after CCI in mice, a time at which myelin lesions were present in both the spinal cord and sciatic nerve. Oligodendrocytes, microglia, and astrocytes subpopulations in spinal cord tissue were heterogeneous after CCI and all were involved in suppressing the process of immune defense and myelin production. In addition, the differentiation trajectory of oligodendrocytes involved a unidirectional lattice process of OPC-1-Oligo-9, which was arrested at the Oligo-2 stage under the influence of microglia and astrocytes. And the CADM1-CADM1, NRP1-VEGFA interactions between glial cells are enhanced after CCI and they had a key role in myelin lesions and demyelination. Conclusions Our study reveals the close relationship between the differentiation block of oligodendrocytes after CCI and their interaction with microglia and astrocytes-mediated myelin lesions and NP. CADM1/CADM1 and NRP-1/VEGFA may serve as potential therapeutic targets for use in the treatment of NP.

Abstract Amorphophallus is a perennial monocotyledonous herbaceous plant native to the southwestern region of China, widely used in various fields such as food processing, biomedicine and chemical agriculture. However, Amorphophallus is a typical thermolabile plant, and the continuous high temperature in summer have seriously affected the growth, development and economic yield of Amorphophallus in recent years. Calmodulin (CaM), a Ca2+ sensor ubiquitous in eukaryotes, is the most important multifunctional receptor protein in plant cells, which affects plant stress resistance by participating in the activities of a variety of signaling molecules. In this study, the key gene AaCaM3 for the Ca2+-CaM regulatory pathway was obtained from A. albus, the sequence analysis confirmed that it is a typical calmodulin. The qRT-PCR results demonstrated that with the passage of heat treatment time, the expression of AaCaM3 was significantly upregulated in A. albus leaves. Subcellular localization analysis revealed that AaCaM3 localized on the cytoplasm and nucleus. Meanwhile, heterologous transformation experiments have shown that AaCaM3 can significantly improve the heat tolerance of Arabidopsis under heat stress. The promoter region of AaCaM3 was sequenced 1,338 bp by FPNI-PCR and GUS staining assay showed that the promoter of AaCaM3 was a high-temperature inducible promoter. Yeast one-hybrid analysis and Luciferase activity reporting system analysis showed that the AaCaM3 promoter may interact with AaHSFA1, AaHSFA2c, AaHSP70, AaDREB2a and AaDREB2b. In conclusion, this study provides new ideas for further improving the signal transduction network of high-temperature stress in Amorphophallus.

Abstract Autophagy is a conserved, catabolic process essential for maintaining cellular homeostasis. Malfunctional autophagy contributes to neurodevelopmental and neurodegenerative diseases. However, the exact role and targets of autophagy in human neurons remain elusive. Here we report a systematic investigation of neuronal autophagy targets through integrated proteomics. Deep proteomic profiling of multiple autophagy-deficient lines of human induced neurons, mouse brains, and brain LC3-interactome reveals roles of neuronal autophagy in targeting proteins of multiple cellular organelles/pathways, including endoplasmic reticulum (ER), mitochondria, endosome, Golgi apparatus, synaptic vesicle (SV) for degradation. By combining phosphoproteomics and functional analysis in human and mouse neurons, we uncovered a function of neuronal autophagy in controlling cAMP-PKA and c-FOS-mediated neuronal activity through selective degradation of the protein kinase A - cAMP-binding regulatory (R)-subunit I (PKA-RI) complex. Lack of AKAP11 causes accumulation of the PKA-RI complex in the soma and neurites, demonstrating a constant clearance of PKA-RI complex through AKAP11-mediated degradation in neurons. Our study thus reveals the landscape of autophagy degradation in human neurons and identifies a physiological function of autophagy in controlling homeostasis of PKA-RI complex and specific PKA activity in neurons.

Most computational methods for predicting driver mutations have been trained using positive samples, while negative samples are typically derived from statistical methods or putative samples. The representativeness of these negative samples in capturing the diversity of passenger mutations remains to be determined. To tackle these issues, we curated a balanced dataset comprising driver mutations sourced from the COSMIC database and high-quality passenger mutations obtained from the Cancer Passenger Mutation database. Subsequently, we encoded the distinctive features of these mutations. Utilizing feature correlation analysis, we developed a cancer driver missense mutation predictor called CDMPred employing feature selection through the ensemble learning technique XGBoost. The proposed CDMPred method, utilizing the top 10 features and XGBoost, achieved an area under the receiver operating characteristic curve (AUC) value of 0.83 and 0.80 on the training and independent test sets, respectively. Furthermore, CDMPred demonstrated superior performance compared to existing state-of-the-art methods for cancer-specific and general diseases, as measured by AUC and area under the precision-recall curve. Including high-quality passenger mutations in the training data proves advantageous for CDMPred’s prediction performance. We anticipate that CDMPred will be a valuable tool for predicting cancer driver mutations, furthering our understanding of personalized therapy.

Abstract Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease and arises from dopamine (DA) neuron death selectively in the substantia nigra pars compacta (SNc). Rit2 is a reported PD risk allele, and recent single cell transcriptomic studies identified a major RIT2 cluster in PD DA neurons, potentially linking Rit2 expression loss to a PD patient cohort. However, it is still unknown whether Rit2 loss itself impacts DA neuron function and/or viability. Here we report that conditional Rit2 silencing in mouse DA neurons drove motor dysfunction that occurred earlier in males than females and was rescued at early stages by either inhibiting the DA transporter (DAT) or with L-DOPA treatment. Motor dysfunction was accompanied by decreased DA release, striatal DA content, phenotypic DAergic markers, DA neurons, and DAergic terminals, with increased pSer129-alpha synuclein and pSer935-LRRK2 expression. These results provide clear evidence that Rit2 loss is causal for SNc cell death and motor dysfunction, and reveal key sex-specific differences in the response to Rit2 loss.

Abstract With the increasing availability of large-scale biology data in crop plants, there is an urgent demand for a versatile platform that fully mines and utilizes the data for modern molecular breeding. We present Crop-GPA ( https://crop-gpa.aielab.net ), a comprehensive and functional open-source platform for crop gene-phenotype association data. The current Crop-GPA provides well-curated information on genes, phenotypes, and their associations (GPAs) to researchers through an intuitive interface, dynamic graphical visualizations, and efficient online tools. Two computational tools, GPA-BERT and GPA-GCN, are specifically developed and integrated into Crop-GPA, facilitating the automatic extraction of gene-phenotype associations from bio-crop literature and predicting unknown relations based on known associations. Through usage examples, we demonstrate how our platform enables the exploration of complex correlations between genes and phenotypes in crop plants. In summary, Crop-GPA serves as a valuable multi-functional resource, empowering the crop research community to gain deeper insights into the biological mechanisms of interest.

Abstract Aim The aim of this study was to synthesize qualitative research evidence on cancer survivors' experiences with reproductive concerns (RC). Methods We conducted a systematic search of qualitative studies and utilized the meta‐aggregation approach. The database searches were extended up to May 14, 2023, encompassing 12 databases, specifically MEDLINE, CINAHL, PubMed, EMBASE, Scopus, Web of Science (Core Collection), AMED, PsycINFO, The Cochrane Library, CNKI, Wan Fang Data, and VIP. Results Three overarching themes were synthesized from the analysis of 21 studies that explored cancer patients' awareness of reproductive concerns, their perceptions, needs, and coping styles. These themes encapsulate the multifaceted aspects of cancer patients' reproductive concerns: “Gender differences in fertility concerns among cancer patients: Perspectives from men and women”; “The influence of age: Experiences with fertility issues among cancer patients at different life stages”; “The impact of treatment stages on fertility concerns: The evolution of perception and coping strategies in the course of cancer treatment”. Conclusion Our study presents an in‐depth exploration of the reproductive concerns experienced by cancer patients from various perspectives. We found that the internal experiences of reproductive concerns, their perceptions, needs, and coping mechanisms differ based on their roles. This comprehensive understanding of the complex emotions and needs of cancer patients when confronted with fertility issues can guide clinicians in providing more effective medical assistance, psychological counseling, and fertility‐related information services.

Abstract Dysfunctional autophagy and impairment of adult hippocampal neurogenesis (AHN) each contribute to the pathogenesis of major depressive disorder (MDD). However, whether dysfunctional autophagy is linked to aberrant AHN underlying MDD remains unclear. Here we demonstrate that the expression of nuclear receptor binding factor 2 (NRBF2), a component of autophagy-associated PIK3C3/VPS34-containing phosphatidylinositol 3-kinase complex, is attenuated in the dentate gyrus (DG) under chronic stress. NRBF2 deficiency inhibits the activity of the VPS34 complex and impairs autophagic flux in adult neural stem cells (aNSCs). Moreover, loss of NRBF2 disrupts the neurogenesis-related protein network and causes exhaustion of aNSC pool, leading to the depression-like phenotype. Strikingly, overexpressing NRBF2 in aNSCs of the DG is sufficient to rescue impaired AHN and depression-like phenotype of mice. Our findings reveal a significant role of NRBF2-dependent autophagy in preventing chronic stress-induced AHN impairment and suggest the therapeutic potential of targeting NRBF2 in MDD treatment.

Abstract Background Identification of hot spots in protein–DNA binding interfaces is extremely important for understanding the underlying mechanisms of protein–DNA interactions and drug design. Since experimental methods for identifying hot spots are time-consuming and expensive, and most of the existing computational methods are based on traditional protein–DNA features to predict hot spots, unable to make full use of the effective information in the features. Results In this work, a method named WTL-PDH is proposed for hot spots prediction. To deal with the unbalanced dataset, we used the Synthetic Minority Over-sampling Technique to generate minority class samples to achieve the balance of dataset. First, we extracted the solvent accessible surface area features and structural features, and then processed the traditional features using discrete wavelet transform and wavelet packet transform to extract the wavelet energy information and wavelet entropy information, and obtained a total of 175 dimensional features. In order to obtain the best feature subset, we systematically evaluate these features in various feature selection strategies. Finally, light gradient boosting machine (LightGBM) was used to establish the model. Conclusions Our method achieved good results on independent test set with AUC, MCC and F1 scores of 0.838, 0.533 and 0.750, respectively. WTL-PDH can achieve generally better performance in predicting hot spots when compared with state-of-the-art methods. The dataset and source code are available at https://github.com/chase2555/WTL-PDH .

Abstract Background Apicomplexa consist of numerous pathogenic parasitic protistan genera that invade host cells and reside and replicate within the parasitophorous vacuole (PV). Through this interface, the parasite exchanges nutrients and affects transport and immune modulation. During the intracellular life-cycle, the specialized secretory organelles of the parasite secrete an array of proteins, among which dense granule proteins (GRAs) play a major role in the modification of the PV. Despite this important role of GRAs, a large number of potential GRAs remain unidentified in Apicomplexa. Methods A multi-view attention graph convolutional network (MVA-GCN) prediction model with multiple features was constructed using a combination of machine learning and genomic datasets, and the prediction was performed on selected Neospora caninum protein data. The candidate GRAs were verified by a CRISPR/Cas9 gene editing system, and the complete NcGRA64(a,b) gene knockout strain was constructed and the phenotypes of the mutant were analyzed. Results The MVA-GCN prediction model was used to screen N. caninum candidate GRAs, and two novel GRAs (NcGRA64a and NcGRA64b) were verified by gene endogenous tagging. Knockout of complete genes of NcGRA64(a,b) in N. caninum did not affect the parasite's growth and replication in vitro and virulence in vivo. Conclusions Our study showcases the utility of the MVA-GCN deep learning model for mining Apicomplexa GRAs in genomic datasets, and the prediction model also has certain potential in mining other functional proteins of apicomplexan parasites. Graphical Abstract

Abstract Background MircoRNAs (miRNAs) play a central role in diverse biological processes of Camellia sinensis var.assamica (CSA) through their associations with target mRNAs, including CSA growth, development and stress response. However, although the experiment methods of CSA miRNA-target identifications are costly and time-consuming, few computational methods have been developed to tackle the CSA miRNA-target association prediction problem. Results In this paper, we constructed a heterogeneous network for CSA miRNA and targets by integrating rich biological information, including a miRNA similarity network, a target similarity network, and a miRNA-target association network. We then proposed a deep learning framework of graph convolution networks with layer attention mechanism, named MTAGCN. In particular, MTAGCN uses the attention mechanism to combine embeddings of multiple graph convolution layers, employing the integrated embedding to score the unobserved CSA miRNA-target associations. Discussion Comprehensive experiment results on two tasks (balanced task and unbalanced task) demonstrated that our proposed model achieved better performance than the classic machine learning and existing graph convolution network-based methods. The analysis of these results could offer valuable information for understanding complex CSA miRNA-target association mechanisms and would make a contribution to precision plant breeding.

Alzheimer's disease (AD) is a prevalent and deleterious neurodegenerative disorder characterized by an irreversible and progressive impairment of cognitive abilities as well as the formation of amyloid β (Aβ) plaques and neurofibrillary tangles (NFTs) in the brain. By far, the precise mechanisms of AD are not fully understood and no interventions are available to effectively slow down progression of the disease. Autophagy is a conserved degradation pathway that is crucial to maintain cellular homeostasis by targeting damaged organelles, pathogens, and disease-prone protein aggregates to lysosome for degradation. Emerging evidence suggests dysfunctional autophagy clearance pathway as a potential cellular mechanism underlying the pathogenesis of AD in affected neurons. Here we summarize the current evidence for autophagy dysfunction in the pathophysiology of AD and discuss the role of autophagy in the regulation of AD-related protein degradation and neuroinflammation in neurons and glial cells. Finally, we review the autophagy modulators reported in the treatment of AD models and discuss the obstacles and opportunities for potential clinical application of the novel autophagy activators for AD therapy.

The rapid development and popularity of IoT technology has reshaped the way people interact with the real world. Many researchers have attempted to build natural language interfaces for IoT platforms, but have not produced much progress in parsing natural language commands that contain multiple operations and more complex logical structures. In this paper, we propose IoT-NLI, a natural language query and control interface for popular IoT platforms, which uses hierarchical semantic parsing algorithms and directed edge-tagged graph structures to efficiently parse natural language commands input by users, enabling them to perform multiple operations contained in one complex natural language command. Experiments in three domains, agriculture, industry, and smart home, show that IoT-NLI has excellent performance and reasonable response time. Finally, a IoT-NLI application was developed on the Android platform and integrated with the AliCloud platform. It enables users to query and control devices on Android phones through chat windows similar to instant messaging software.

Abstract Autophagy is a cell self-digestion pathway through lysosome and plays a critical role in maintaining cellular homeostasis and cytoprotection. Characterization of autophagy related genes in cell and animal models reveals diverse physiological functions of autophagy in various cell types and tissues. In central nervous system, by recycling injured organelles and misfolded protein complexes or aggregates, autophagy is integrated into synaptic functions of neurons and subjected to distinct regulation in presynaptic and postsynaptic neuronal compartments. A plethora of studies have shown the neuroprotective function of autophagy in major neurodegenerative diseases, such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD) and amyotrophic lateral sclerosis (ALS). Recent human genetic and genomic evidence has demonstrated an emerging, significant role of autophagy in human brain development and prevention of spectrum of neurodevelopmental disorders. Here we will review the evidence demonstrating the causal link of autophagy deficiency to congenital brain diseases, the mechanism whereby autophagy functions in neurodevelopment, and therapeutic potential of autophagy.

Microglia perform important supporting roles for neurons in the brain. Here, the authors show that microglia clear neuron-derived α-synuclein through selective autophagy (synucleinphagy) to prevent accumulation of misfolded α-synuclein and subsequent neurodegeneration in a mouse model of disease.

As an important step of synthetic aperture radar image interpretation, synthetic aperture radar image segmentation aims at segmenting an image into different regions in terms of homogeneity. Because of the deficiency of the labeled samples and the existence of speckling noise, synthetic aperture radar image segmentation is a challenging task. We present a new method for synthetic aperture radar image segmentation in this article. Due to the large size of the original synthetic aperture radar image, we first divide the input image into small slices. Then the image slices are input to the attention-based fully convolutional network for obtaining the segmentation results. Finally, the fully connected conditional random field is adopted for improving the segmentation performance of the network. The innovations of our method are as follows: 1) The attention-based fully convolutional network is embedded with the multiscale attention network which is capable of enhancing the extraction of the image features through three strategies, namely, multiscale feature extraction, channel attention extraction, and spatial attention extraction. 2) We design a new loss function for the attention fully convolutional network by combining Lovasz-Softmax and cross-entropy losses. The new loss allows us to simultaneously optimize the intersection over union and the pixel classification accuracy of the segmentation results. The experiments are performed on two airborne synthetic aperture radar image databases. It has been proved that our method is superior to other state-of- the-art image segmentation approaches.

Background A moonlighting protein refers to a protein that can perform two or more functions. Since the current moonlighting protein prediction tools mainly focus on the proteins in animals and microorganisms, and there are differences in the cells and proteins between animals and plants, these may cause the existing tools to predict plant moonlighting proteins inaccurately. Hence, the availability of a benchmark data set and a prediction tool specific for plant moonlighting protein are necessary. Methods This study used some protein feature classes from the data set constructed in house to develop a web-based prediction tool. In the beginning, we built a data set about plant protein and reduced redundant sequences. We then performed feature selection, feature normalization and feature dimensionality reduction on the training data. Next, machine learning methods for preliminary modeling were used to select feature classes that performed best in plant moonlighting protein prediction. This selected feature was incorporated into the final plant protein prediction tool. After that, we compared five machine learning methods and used grid searching to optimize parameters, and the most suitable method was chosen as the final model. Results The prediction results indicated that the eXtreme Gradient Boosting (XGBoost) performed best, which was used as the algorithm to construct the prediction tool, called IdentPMP (Identification of Plant Moonlighting Proteins). The results of the independent test set shows that the area under the precision-recall curve (AUPRC) and the area under the receiver operating characteristic curve (AUC) of IdentPMP is 0.43 and 0.68, which are 19.44% (0.43 vs. 0.36) and 13.33% (0.68 vs. 0.60) higher than state-of-the-art non-plant specific methods, respectively. This further demonstrated that a benchmark data set and a plant-specific prediction tool was required for plant moonlighting protein studies. Finally, we implemented the tool into a web version, and users can use it freely through the URL: http://identpmp.aielab.net/.

Parkinson’s disease (PD) is characterized by neurodegeneration associated with loss of dopaminergic (DA) neurons and deposition of Lewy bodies. Here, Wang et al. use co-expression network analysis to pinpoint disease pathways and propose reduced expression of STMN2 as a cause of presynaptic function loss in PD.

Abstract Background Dysfunctional autophagy is implicated in Alzheimer’s Disease (AD) pathogenesis. The alterations in the expression of many autophagy related genes (ATGs) have been reported in AD brains; however, the disparity of the changes confounds the role of autophagy in AD. Methods To further understand the autophagy alteration in AD brains, we analyzed transcriptomic (RNAseq) datasets of several brain regions (BA10, BA22, BA36 and BA44 in 223 patients compared to 59 healthy controls) and measured the expression of 130 ATGs. We used autophagy-deficient mouse models to assess the impact of the identified ATGs depletion on memory, autophagic activity and amyloid-β (Aβ) production. Results We observed significant downregulation of multiple components of two autophagy kinase complexes BECN1-PIK3C3 and ULK1/2-FIP200 specifically in the parahippocampal gyrus (BA36). Most importantly, we demonstrated that deletion of NRBF2, a component of the BECN1-PIK3C3 complex, which also associates with ULK1/2-FIP200 complex, impairs memory in mice, alters long-term potentiation (LTP), reduces autophagy in mouse hippocampus, and promotes Aβ accumulation. Furthermore, AAV-mediated NRBF2 overexpression in the hippocampus not only rescues the impaired autophagy and memory deficits in NRBF2-depleted mice, but also reduces β-amyloid levels and improves memory in an AD mouse model. Conclusions Our data not only implicates NRBF2 deficiency as a risk factor for cognitive impairment associated with AD, but also support the idea of NRBF2 as a potential therapeutic target for AD.

Parkinson's disease (PD) is a debilitating neurodegenerative disorder that profoundly affects one's motor functions. The disease is characterized pathologically by denervation of dopaminergic (DAergic) nigrostriatal terminal and degeneration of DAergic neurons in the substantia nigra par compacta (SNpc); however, the precise molecular mechanism underlying disease pathogenesis remains poorly understood. Animal studies in both toxin-induced and genetic PD models suggest that presynaptic impairments may underlie the early stage of DA depletion and neurodegeneration (reviewed in Schirinzi, T., et al. 2016). Supporting this notion, human genetic studies and genomic analysis have identified an increasing number of PD risk variants that are associated with synaptic vesicle (SV) trafficking, regulation of synaptic function and autophagy/lysosomal system (Chang, D., et al. 2017, reviewed in Trinh, J. & Farrer, M. 2013; Singleton, A.B., et al. 2013). Although the precise mechanism for autophagy regulation in neurons is currently unclear, many studies demonstrate that autophagosomes form at the presynaptic terminal (Maday, S. & Holzbaur, E.L. 2014; Vanhauwaert, R., et al. 2017; reviewed in Yue, Z. 2007). Growing evidence has revealed overlapping genes involved in both SV recycling and autophagy, suggesting that the two membrane trafficking processes are inter-connected. Here we will review emergent evidence linking SV endocytic genes and autophagy genes at the presynaptic terminal. We will discuss their potential relevance to PD pathogenesis.

Abstract Introduction Synaptic damage is a key pathology of Alzheimer's disease (AD). The mechanism underlying synaptic vulnerability in AD remains elusive. Methods Using a large‐scale transcriptomic dataset, we analyzed the neurogranin‐centered integrative gene network and assessed the correlation of neurogranin (NRGN) gene expression with AD pathology in post mortem brains. We studied the association of NRGN expression with Clinical Dementia Rating (CDR) and neuropathological diagnosis of AD. Results We find that the genes positively correlated with NRGN expression in AD are involved in synaptic transmission and cation channel pathways. NRGN expression is correlated with amyloid and tau pathology in the perirhinal cortex of post mortem brains. NRGN expression is associated with the diagnosis of AD and correlated with CDR. Discussion Transcriptional regulation of the gene encoding for synaptic protein is involved in selective synaptic damage in AD. Identifying the genes associated with synaptic damage pathways in AD may provide targets for intervention.

Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor. Radiotherapy (RT) is an important treatment for HNSCC, but not all patients derive survival benefit from RT due to the individual differences on radiosensitivity. A prediction model of radiosensitivity based on multiple omics data might solve this problem. Compared with single omics data, multiple omics data can illuminate more systematical associations between complex molecular characteristics and cancer phenotypes. In this study, we obtained 122 differential expression genes by analyzing the gene expression data of HNSCC patients with RT (N = 287) and without RT (N = 189) downloaded from The Cancer Genome Atlas. Then, HNSCC patients with RT were randomly divided into a training set (N = 149) and a test set (N = 138). Finally, we combined multiple omics data of 122 differential genes with clinical outcomes on the training set to establish a 12-gene signature by two-stage regularization and multivariable Cox regression models. Using the median score of the 12-gene signature on the training set as the cutoff value, the patients were divided into the high- and low-score groups. The analysis revealed that patients in the low-score group had higher radiosensitivity and would benefit from RT. Furthermore, we developed a nomogram to predict the overall survival of HNSCC patients with RT. We compared the prognostic value of 12-gene signature with those of the gene signatures based on single omics data. It suggested that the 12-gene signature based on multiple omics data achieved the best ability for predicting radiosensitivity. In conclusion, the proposed 12-gene signature is a promising biomarker for estimating the RT options in HNSCC patients.

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene are the most frequent cause of familial Parkinson’s disease (PD). Several genetic manipulations of the LRRK2 gene have been developed in animal models such as rodents, Drosophila, Caenorhabditis elegans, and zebrafish. These models can help us further understand the biological function and derive potential pathological mechanisms for LRRK2. Here we discuss common phenotypic themes found in LRRK2-associated PD animal models, highlight several issues that should be addressed in future models, and discuss emerging areas to guide their future development.

Autophagy is a genetically regulated process of adaptation to metabolic stress and was recently shown to be involved in the treatment response of chronic myeloid leukemia (CML). However, in vivo data are limited and the molecular mechanism of autophagy regulators in the process of leukemogenesis is not completely understood. Here we show that Beclin-1 knockdown, but not Atg5 deletion in a murine CML model leads to a reduced leukemic burden and results in a significantly prolonged median survival of targeted mice. Further analyses of murine cell lines and primary patient material indicate that active BCR-ABL directly interacts with BECLIN-1 and phosphorylates its tyrosine residues 233 and 352, resulting in autophagy suppression. By using phosphorylation-deficient and phosphorylation-mimic mutants, we identify BCR-ABL induced BECLIN-1 phosphorylation as a crucial mechanism for BECLIN-1 complex formation: interaction analyses exhibit diminished binding of the positive autophagy regulators UVRAG, VPS15, ATG14 and VPS34 and enhanced binding of the negative regulator Rubicon to BCR-ABL-phosphorylated BECLIN-1. Taken together, our findings show interaction of BCR-ABL and BECLIN-1 thereby highlighting the importance of BECLIN-1-mediated autophagy in BCR-ABL+ cells.

Increased levels of the Yap oncoprotein stimulate liver growth and promote hepatocarcinogenesis. Here the authors show that hepatocyte-specific loss of Atg7 in mice leads to decreased autophagic degradation of Yap and liver overgrowth, and further establish this association in human liver cancer tissues.

Mutations in the parkin, an ubiquitin ligase, are linked to Parkinson’s disease. Here the authors show that synaptotagmin-11 is a parkin substrate and that its upregulation affects dopamine release, triggers degeneration, and causes motor impairment.

Abstract Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are neurodegenerative disorders that share genetic risk factors and pathological hallmarks. Intriguingly, these shared factors result in a high rate of comorbidity of these diseases in patients. Intracellular protein aggregates are a common pathological hallmark of both diseases. Emerging evidence suggests that impaired RNA processing and disrupted protein homeostasis are two major pathogenic pathways for these diseases. Indeed, recent evidence from genetic and cellular studies of the etiology and pathogenesis of ALS-FTD has suggested that defects in autophagy may underlie various aspects of these diseases. In this review, we discuss the link between genetic mutations, autophagy dysfunction, and the pathogenesis of ALS-FTD. Although dysfunction in a variety of cellular pathways can lead to these diseases, we provide evidence that ALS-FTD is, in many cases, an autophagy disease.

Genetic leukoencephalopathies (gLEs) are a group of heterogeneous disorders with white matter abnormalities affecting the central nervous system (CNS). The causative mutation in ~50% of gLEs is unknown. Using whole exome sequencing (WES), we identified homozygosity for a missense variant, VPS11: c.2536T>G (p.C846G), as the genetic cause of a leukoencephalopathy syndrome in five individuals from three unrelated Ashkenazi Jewish (AJ) families. All five patients exhibited highly concordant disease progression characterized by infantile onset leukoencephalopathy with brain white matter abnormalities, severe motor impairment, cortical blindness, intellectual disability, and seizures. The carrier frequency of the VPS11: c.2536T>G variant is 1:250 in the AJ population (n = 2,026). VPS11 protein is a core component of HOPS (homotypic fusion and protein sorting) and CORVET (class C core vacuole/endosome tethering) protein complexes involved in membrane trafficking and fusion of the lysosomes and endosomes. The cysteine 846 resides in an evolutionarily conserved cysteine-rich RING-H2 domain in carboxyl terminal regions of VPS11 proteins. Our data shows that the C846G mutation causes aberrant ubiquitination and accelerated turnover of VPS11 protein as well as compromised VPS11-VPS18 complex assembly, suggesting a loss of function in the mutant protein. Reduced VPS11 expression leads to an impaired autophagic activity in human cells. Importantly, zebrafish harboring a vps11 mutation with truncated RING-H2 domain demonstrated a significant reduction in CNS myelination following extensive neuronal death in the hindbrain and midbrain. Thus, our study reveals a defect in VPS11 as the underlying etiology for an autosomal recessive leukoencephalopathy disorder associated with a dysfunctional autophagy-lysosome trafficking pathway.

A mutation in the coding region of the Tor1A gene, resulting in a deletion of a glutamic acid residue in the torsinA protein (∆ETorA), is the major cause of the inherited autosomal-dominant early onset torsion dystonia (DYT1). The pathophysiological consequences of this amino acid loss are still not understood.Currently available animal models for DYT1 dystonia provided important insights into the disease; however, they differ with respect to key features of torsinA associated pathology.We developed transgenic rat models harboring the full length human mutant and wildtype Tor1A gene. A complex phenotyping approach including classical behavioral tests, electrophysiology and neuropathology revealed a progressive neurological phenotype in ∆ETorA expressing rats. Furthermore, we were able to replicate key pathological features of torsinA associated pathology in a second species, such as nuclear envelope pathology, behavioral abnormalities and plasticity changes. We therefore suggest that this rat model represents an appropriate new model suitable to further investigate the pathophysiology of ∆ETorA and to test for therapeutic approaches.

Natural products play a significant role in cancer chemotherapy. They are likely to provide many lead structures, which can be used as templates for the construction of novel drugs with enhanced antitumor activity. Traditional research approaches studied structure-activity relationship of natural products and obtained key structural properties, such as chemical bond or group, with the purpose of ascertaining their effect on a single cell line or a single tissue type. Here, for the first time, we develop a machine learning method to comprehensively predict natural products responses against a panel of cancer cell lines based on both the gene expression and the chemical properties of natural products. The results on two datasets, training set and independent test set, show that this proposed method yields significantly better prediction accuracy. In addition, we also demonstrate the predictive power of our proposed method by modeling the cancer cell sensitivity to two natural products, Curcumin and Resveratrol, which indicate that our method can effectively predict the response of cancer cell lines to these two natural products. Taken together, the method will facilitate the identification of natural products as cancer therapies and the development of precision medicine by linking the features of patient genomes to natural product sensitivity.

Disruption of proteostasis, or protein homeostasis, is often associated with aberrant accumulation of misfolded proteins or protein aggregates. Autophagy offers protection to cells by removing toxic protein aggregates and injured organelles in response to proteotoxic stress. However, the exact mechanism whereby autophagy recognizes and degrades misfolded or aggregated proteins has yet to be elucidated. Mounting evidence demonstrates the selectivity of autophagy, which is mediated through autophagy receptor proteins (e.g. p62/SQSTM1) linking autophagy cargos and autophagosomes. Here we report that proteotoxic stress imposed by the proteasome inhibition or expression of polyglutamine expanded huntingtin (polyQ-Htt) induces p62 phosphorylation at its ubiquitin-association (UBA) domain that regulates its binding to ubiquitinated proteins. We find that autophagy-related kinase ULK1 phosphorylates p62 at a novel phosphorylation site S409 in UBA domain. Interestingly, phosphorylation of p62 by ULK1 does not occur upon nutrient starvation, in spite of its role in canonical autophagy signaling. ULK1 also phosphorylates S405, while S409 phosphorylation critically regulates S405 phosphorylation. We find that S409 phosphorylation destabilizes the UBA dimer interface, and increases binding affinity of p62 to ubiquitin. Furthermore, lack of S409 phosphorylation causes accumulation of p62, aberrant localization of autophagy proteins and inhibition of the clearance of ubiquitinated proteins or polyQ-Htt. Therefore, our data provide mechanistic insights into the regulation of selective autophagy by ULK1 and p62 upon proteotoxic stress. Our study suggests a potential novel drug target in developing autophagy-based therapeutics for the treatment of proteinopathies including Huntington's disease.

Deficiency of autophagy protein beclin 1 is implicated in tumorigenesis and neurodegenerative diseases, but the molecular mechanism remains elusive. Previous studies showed that Beclin 1 coordinates the assembly of multiple VPS34 complexes whose distinct phosphatidylinositol 3-kinase III (PI3K-III) lipid kinase activities regulate autophagy at different steps. Recent evidence suggests a function of beclin 1 in regulating multiple VPS34-mediated trafficking pathways beyond autophagy; however, the precise role of beclin 1 in autophagy-independent cellular functions remains poorly understood. Herein we report that beclin 1 regulates endocytosis, in addition to autophagy, and is required for neuron viability in vivo. We find that neuronal beclin 1 associates with endosomes and regulates EEA1/early endosome localization and late endosome formation. Beclin 1 maintains proper cellular phosphatidylinositol 3-phosphate (PI(3)P) distribution and total levels, and loss of beclin 1 causes a disruption of active Rab5 GTPase-associated endosome formation and impairment of endosome maturation, likely due to a failure of Rab5 to recruit VPS34. Furthermore, we find that Beclin 1 deficiency causes complete loss of the UVRAG-VPS34 complex and associated lipid kinase activity. Interestingly, beclin 1 deficiency impairs p40phox-linked endosome formation, which is rescued by overexpressed UVRAG or beclin 1, but not by a coiled-coil domain-truncated beclin 1 (a UVRAG-binding mutant), Atg14L or RUBICON. Thus, our study reveals the essential role for beclin 1 in neuron survival involving multiple membrane trafficking pathways including endocytosis and autophagy, and suggests that the UVRAG-beclin 1 interaction underlies beclin 1's function in endocytosis.

Mutations in leucine-rich repeat kinase 2 (LRRK2) underlie an autosomal-dominant form of Parkinson's disease (PD) that is clinically indistinguishable from idiopathic PD. The function of LRRK2 is not well understood, but it has become widely accepted that LRRK2 levels or its kinase activity, which is increased by the most commonly observed mutation (G2019S), regulate neurite growth. However, growth has not been measured; it is not known whether mean differences in length correspond to altered rates of growth or retraction, whether axons or dendrites are impacted differentially or whether effects observed are transient or sustained. To address these questions, we compared several developmental milestones in neurons cultured from mice expressing bacterial artificial chromosome transgenes encoding mouse wildtype-LRRK2 or mutant LRRK2-G2019S, Lrrk2 knockout mice and non-transgenic mice. Over the course of three weeks of development on laminin, the data show a sustained, negative effect of LRRK2-G2019S on dendritic growth and arborization, but counter to expectation, dendrites from Lrrk2 knockout mice do not elaborate more rapidly. In contrast, young neurons cultured on a slower growth substrate, poly-L-lysine, show significantly reduced axonal and dendritic motility in Lrrk2 transgenic neurons and significantly increased motility in Lrrk2 knockout neurons with no significant changes in length. Our findings support that LRRK2 can regulate patterns of axonal and dendritic growth, but they also show that effects vary depending on growth substrate and stage of development. Such predictable changes in motility can be exploited in LRRK2 bioassays and guide exploration of LRRK2 function in vivo.

Altered protein homeostasis underlies degenerative diseases triggered by misfolded proteins, including spinal and bulbar muscular atrophy (SBMA), a neuromuscular disorder caused by a CAG/glutamine expansion in the androgen receptor. Here we show that the unfolded protein response (UPR), an ER protein quality control pathway, is induced in skeletal muscle from SBMA patients, AR113Q knock-in male mice, and surgically denervated wild-type mice. To probe the consequence of UPR induction, we deleted CHOP (C/EBP homologous protein), a transcription factor induced following ER stress. CHOP deficiency accentuated atrophy in both AR113Q and surgically denervated muscle through activation of macroautophagy, a lysosomal protein quality control pathway. Conversely, impaired autophagy due to Beclin-1 haploinsufficiency decreased muscle wasting and extended lifespan of AR113Q males, producing a significant and unexpected amelioration of the disease phenotype. Our findings highlight critical cross-talk between the UPR and macroautophagy, and they indicate that autophagy activation accentuates aspects of the SBMA phenotype.

Recent studies show that mutations in Leucine Rich Repeat Kinase 2 (LRRK2) are the cause of the most common inherited and some sporadic forms of Parkinson's disease (PD). The molecular mechanism underlying the pathogenic role of LRRK2 mutations in PD remains unknown.Using affinity purification and mass spectrometric analysis, we investigated phosphorylation sites and binding proteins of LRRK2 purified from mouse brain. We identified multiple phosphorylation sites at N-terminus of LRRK2 including S910, S912, S935 and S973. Focusing on the high stoichiometry S935 phosphorylation site, we developed an anti-pS935 specific antibody and showed that LRRK2 is constitutively phosphorylated at S935 in various tissues (including brain) and at different ages in mice. We find that 14-3-3 proteins (especially isoforms γ and η) bind LRRK2 and this binding depends on phosphorylation of S935. The binding of 14-3-3, with little effect on dimer formation of LRRK2, confers protection of the phosphorylation status of S935. Furthermore, we show that protein kinase A (PKA), but not LRRK2 kinase itself, can cause the phosphorylation of LRRK2 at S935 in vitro and in cell culture, suggesting that PKA is a potential upstream kinase that regulates LRRK2 function. Finally, our study indicates that the common PD-related mutations of LRRK2, R1441G, Y1699C and G2019S, decrease homeostatic phosphorylation levels of S935 and impair 14-3-3 binding of LRRK2.LRRK2 is extensively phosphorylated in vivo, and the phosphorylation of specific sites (e.g. S935) determines 14-3-3 binding of LRRK2. We propose that 14-3-3 is an important regulator of LRRK2-mediated cellular functions. Our study suggests that PKA, a cAMP-dependent kinase involved in regulating dopamine physiology, is a potential upstream kinase that phosphorylates LRRK2 at S935. Furthermore, the reduction of phosphorylation/14-3-3 binding of LRRK2 due to the common familial PD-related mutations provides novel insight into the pathogenic mechanism of LRRK2-linked PD.

Infantile neuroaxonal dystrophy (INAD) is a progressive, autosomal recessive neurodegenerative disease characterized by axonal dystrophy, abnormal iron deposition and cerebellar atrophy. This disease was recently mapped to PLA2G6, which encodes group VI Ca(2+)-independent phospholipase A(2) (iPLA(2) or iPLA(2)β). Here we show that genetic ablation of PLA2G6 in mice (iPLA(2)β(-/-)) leads to the development of cerebellar atrophy by the age of 13 months. Atrophied cerebella exhibited significant loss of Purkinje cells, as well as reactive astrogliosis, the activation of microglial cells, and the pronounced up-regulation of the pro-inflammatory cytokines tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β). Moreover, glial cell activation and the elevation in TNF-α and IL-1β expression occurred before apparent cerebellar atrophy. Our findings indicate that the absence of PLA2G6 causes neuroinflammation and Purkinje cell loss and ultimately leads to cerebellar atrophy. Our study suggests that iPLA(2)β(-/-) mice are a valuable model for cerebellar atrophy in INAD and that early anti-inflammatory therapy may help slow the progression of cerebellar atrophy in this deadly neurodegenerative disease.