Biology subjects

Lee, S.

Publications and source records attributed to Lee, S..

At least 19 recordsLinked to original sources

bioRxiv2018

The whale shark genome reveals how genomic and physiological properties scale with body size

The endangered whale shark (Rhincodon typus) is the largest fish on Earth and is a long-lived member of the ancient Elasmobranchii clade. To characterize the relationship between genome features and biological traits, we sequenced and assembled the genome of the whale shark and compared its genomic and physiological features to those of 81 animals and yeast. We examined scaling relationships between body size, temperature, metabolic rates, and genomic features and found both general correlations across the animal kingdom and features specific to the whale shark genome. Among animals, increased lifespan is positively correlated to body size and metabolic rate. Several genomic features also significantly correlated with body size, including intron and gene length. Our large-scale comparative genomic analysis uncovered general features of metazoan genome architecture: GC content and codon adaptation index are negatively correlated, and neural connectivity genes are longer than average genes in most genomes. Focusing on the whale shark genome, we identified multiple features that significantly correlate with lifespan. Among these were very long gene length, due to large introns highly enriched in repetitive elements such as CR1-like LINEs, and considerably longer neural genes of several types, including connectivity, activity, and neurodegeneration genes. The whale sharks genome had an expansion of gene families related to fatty acid metabolism and neurogenesis, with the slowest evolutionary rate observed in vertebrates to date. Our comparative genomics approach uncovered multiple genetic features associated with body size, metabolic rate, and lifespan, and showed that the whale shark is a promising model for studies of neural architecture and lifespan.

genomics↗

bioRxiv2018

Tibanna: software for scalable execution of portable pipelines on the cloud

SummaryWe introduce Tibanna, an open-source software tool for automated execution of bioinformatics pipelines on Amazon Web Services (AWS). Tibanna accepts reproducible and portable pipeline standards including Common Workflow Language (CWL), Workflow Description Language (WDL) and Docker. It adopts a strategy of isolation and optimization of individual executions, combined with a serverless scheduling approach. Pipelines are executed and monitored using local commands or the Python Application Programming Interface (API) and cloud configuration is automatically handled. Tibanna is well suited for projects with a range of computational requirements, including those with large and widely fluctuating loads. Notably, it has been used to process terabytes of data for the 4D Nucleome (4DN) Network.\n\nAvailabilitySource code is available on GitHub at https://github.com/4dn-dcic/tibanna.

bioinformatics↗

bioRxiv2018

Drinking motives and alcohol use among college students with the alcohol flush reaction: A nationwide study

BackgroundThis study investigated the relationship between drinking motives and alcohol use among a nationally representative sample of college students with the alcohol flush reaction (AFR). We surveyed and analyzed the data of 2,245 male and 2,326 female college students in a nationally representative sample of 82 colleges in South Korea.\n\nMethodsOf our study population, 725 males (32.3%) and 812 females (34.9%) reported to currently suffering from AFR. Multiple regression analysis was used to identify the association between drinking motives and drinking behavior, measured via the AUDIT.\n\nResultsRelative to drinking because of peer pressure, students drinking for pleasure (males: {beta} = 2.622, p <.0001; females {beta} = 2.769, p <.0001) or stress/depression (males: {beta} = 2.479, p <.0001; females {beta} = 2.489, p <.0001) had higher AUDIT scores. Among students drinking because of stress/depression, seniors (males: {beta} = 3.603, p<.0001; females: {beta} = 3.791, p = 0.000), smokers (males: {beta} = 1.564, p = 0.000; females {beta} = 1.816, p = 0.007) and/or liberal arts students (males: {beta} = 6.1136, p<.0001; females {beta} = 4.2105, p <.0001) consumed more alcohol than their peers. Relative to conformity motives, enhancement and coping motives were found to have a greater influence on alcohol intake among college students with alcohol flush reaction.\n\nConclusionConsidering that the flush reaction can occur in AFR individuals after just one sip of wine, our results show that educators and policymakers must take action to deal with this problem.

epidemiology↗

bioRxiv2018

PUMILIO hyperactivity drives premature aging of Norad-deficient mice

Although numerous long noncoding RNAs (lncRNAs) have been identified, our understanding of their roles in mammalian physiology remains limited. Here we investigated the physiologic function of the conserved lncRNA Norad in vivo. Deletion of Norad in mice results in genomic instability and mitochondrial dysfunction, leading to a dramatic multi-system degenerative phenotype resembling premature aging. Loss of tissue homeostasis in Norad-deficient animals is attributable to augmented activity of PUMILIO proteins, which act as post-transcriptional repressors of target mRNAs to which they bind. Norad is the preferred RNA target of PUMILIO2 (PUM2) in mouse tissues and, upon loss of Norad, PUM2 hyperactively represses key genes required for mitosis and mitochondrial function. Remarkably, enforced Pum2 expression fully phenocopies Norad deletion, resulting in rapid-onset aging-associated phenotypes. These findings provide new insights and open new lines of investigation into the roles of noncoding RNAs and RNA binding proteins in normal physiology and aging.

molecular biology↗

bioRxiv2018

Cancer as a tissue anomaly: classifying tumor transcriptomes based only on healthy data

Since the turn of the century, researchers have sought to diagnose cancer based on gene expression signatures measured from the blood or biopsy as biomarkers. This task, known as classification, is typically solved using a suite of algorithms that learn a mathematical rule capable of discriminating one group (e.g., cases) from another (e.g., controls). However, discriminatory methods can only identify cancerous samples that resemble those that the algorithm already saw during training. As such, we argue that discriminatory methods are fundamentally ill-suited for the classification of cancer: because the possibility space of cancer is definitively large, the existence of a one-of-a-kind gene expression signature becomes very likely. Instead, we propose using an established surveillance method that detects anomalous samples based on their deviation from a learned normal steady-state structure. By transferring this method to transcriptomic data, we can create an anomaly detector for tissue transcriptomes, a \"tissue detector\", that is capable of identifying cancer without ever seeing a single cancer example. Using models trained on normal GTEx samples, we show that our \"tissue detector\" can accurately classify TCGA samples as normal or cancerous and that its performance is further improved by including more normal samples in the training set. We conclude this report by emphasizing the conceptual advantages of anomaly detection and by highlighting future directions for this field of study.

bioinformatics↗

bioRxiv2018

Sex-specific and pleiotropic effects underlying kidney function identified from GWAS meta-analysis

Chronic Kidney Disease (CKD) is a growing health burden currently affecting 10-15% of adults worldwide. Estimated glomerular filtration rate (eGFR) as a marker of kidney function is commonly used to diagnose CKD. Previous genome-wide association study (GWAS) meta-analyses of CKD and eGFR or related phenotypes have identified a number of variants associated with kidney function, but these only explain a fraction of the variability in kidney phenotypes attributed to genetic components. To extend these studies, we analyzed data from the Nord-Trondelag Health Study (HUNT), which is more densely imputed than previous studies, and performed a GWAS meta-analysis of eGFR with publicly available summary statistics, more than doubling the sample size of previous meta-analyses. We identified 147 loci (53 novel loci) associated with eGFR, including genes involved in transcriptional regulation, kidney development, cellular signaling, metabolism, and solute transport. Moreover, genes at these loci show enriched expression in urogenital tissues and highlight gene sets known to play a role in kidney function. In addition, sex-stratified analysis identified three regions (prioritized genes: PPM1J, MCL1, and SLC47A1) with more significant effects in women than men. Using genetic risk scores constructed from these eGFR meta-analysis results, we show that associated variants are generally predictive of CKD but improve detection only modestly compared with other known clinical risk factors. Collectively, these results yield additional insight into the genetic factors underlying kidney function and progression to CKD.

genomics↗

bioRxiv2018

A post-transcriptional program of chemoresistance by AU-rich elements/TTP in cancer quiescence

BackgroundQuiescence (G0) is a transient, cell cycle-arrested state. By entering G0, cancer cells survive unfavorable conditions such as chemotherapy and cause relapse. While G0 cells have been studied at the transcriptome level, how post-transcriptional regulation contributes to their chemoresistance remains unknown.\n\nResultsWe induced chemoresistant and quiescent (G0) leukemic cells by serum-starvation or chemotherapy treatment. To study post-transcriptional regulation in G0 leukemic cells, we systematically analyzed their transcriptome, translatome, and proteome. We find that our resistant G0 cells recapitulate gene expression profiles of in vivo chemoresistant leukemic and G0 models. In G0 cells, canonical translation initiation is inhibited; yet we find that inflammatory genes are highly translated, indicating alternative post-transcriptional regulation. Importantly, AU-rich elements (AREs) are significantly enriched in the up-regulated G0 translatome and transcriptome. Mechanistically, we find the stress-responsive p38 MAPK-MK2 signaling pathway stabilizes ARE mRNAs by phosphorylation and inactivation of mRNA decay factor, tristetraprolin (TTP) in G0. This permits expression of ARE-bearing TNF and DUSP1 that promote chemoresistance. Conversely, inhibition of TTP phophorylation by p38 MAPK inhibitors and non-phosphorylatable TTP mutant decreases ARE mRNAs and sensitizes leukemic cells to chemotherapy. Furthermore, co-inhibiting p38 MAPK and TNF--prior to or along with chemotherapy--substantially reduced chemoresistance in primary leukemic cells ex vivo and in vivo.\n\nConclusionsThese studies uncover post-transcriptional regulation underlying chemoresistance in leukemia. Our data reveal the p38 MAPK-MK2-TTP axis as a key regulator of expression of ARE bearing mRNAs that promote chemoresistance. By disrupting this pathway, we developed an effective combination therapy against chemosurvival.

cancer biology↗

bioRxiv2018

Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium

Cortical thickness, surface area and volumes (MRI cortical measures) vary with age and cognitive function, and in neurological and psychiatric diseases. We examined heritability, genetic correlations and genome-wide associations of cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprised 22,822 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the United Kingdom Biobank. Significant associations were replicated in the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium, and their biological implications explored using bioinformatic annotation and pathway analyses. We identified genetic heterogeneity between cortical measures and brain regions, and 161 genome-wide significant associations pointing to wnt/{beta}-catenin, TGF-{beta} and sonic hedgehog pathways. There was enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

genetics↗

bioRxiv2018

Loss of TLE3 Promotes Mitochondrial Program in Beige Adipocytes and Improves Glucose Metabolism

Prolonged cold exposure stimulates the recruitment of beige adipocytes within white adipose tissue. Beige adipocytes depend on mitochondrial oxidative phosphorylation to drive thermogenesis. The transcriptional mechanisms that promote remodeling in adipose tissue are not well understood. Here we demonstrate that the transcriptional coregulator TLE3 is induced with aging and inhibits mitochondrial gene expression in beige adipocytes. Conditional deletion of TLE3 in adipocytes prevents age- and diet-induced weight gain by promoting mitochondrial oxidative metabolism and increasing energy expenditure, thereby improving glucose control. Using chromatin immunoprecipitation and deep sequencing we found that TLE3 occupies distal enhancers in proximity to nuclear-encoded mitochondrial genes and that many of these enhancers are also enriched for EBF transcription factors. TLE3 interacts with EBF2 and blocks its ability to promote the thermogenic transcriptional program. Collectively, these studies demonstrate that TLE3 mediates age-dependent beige adipose thermogenic decline through inhibition of EBF2 transcriptional activity. Inhibition of TLE3 may provide a novel therapeutic approach for obesity and diabetes.

developmental biology↗

bioRxiv2018

Diagnosis and Prognosis Using Machine Learning Trained on BrainMorphometry and White Matter Connectomes

Accurate, reliable prediction of risk for Alzheimers disease (AD) is essential for early, disease-modifying therapeutics. Multimodal MRI, such as structural and diffusion MRI, is likely to contain complementary information of neurodegenerative processes in AD. Here we tested the utility of the multimodal MRI (T1-weighted structure and diffusion MRI), combined with high-throughput brain phenotyping--morphometry and structural connectomics--and machine learning, as a diagnostic tool for AD. We used, firstly, a clinical cohort at a dementia clinic (National Health Insurance Service-Ilsan Hospital [NHIS-IH]; N=211; 110 AD, 64 mild cognitive impairment [MCI], and 37 cognitively normal with subjective memory complaints [SMC]) to test the diagnostic models; and, secondly, Alzheimers Disease Neuroimaging Initiative (ADNI)-2 to test the generalizability. Our machine learning models trained on the morphometric and connectome estimates (number of features=34,646) showed optimal classification accuracy (AD/SMC: 97% accuracy, MCI/SMC: 83% accuracy; AD/MCI: 97% accuracy) in NHIS-IH cohort, outperforming a benchmark model (FLAIR-based white matter hyperintensity volumes). In ADNI-2 data, the combined connectome and morphometry model showed similar or superior accuracies (AD/HC: 96%; MCI/HC: 70%; AD/MCI: 75% accuracy) compared with the CSF biomarker model (t-tau, p-tau, and Amyloid {beta}, and ratios). In predicting MCI to AD progression in a smaller cohort of ADNI-2 (n=60), the morphometry model showed similar performance with 69% accuracy compared with CSF biomarker model with 70% accuracy. Our comparison of classifiers trained on structural MRI, diffusion MRI, FLAIR, and CSF biomarkers show the promising utility of the white matter structural connectomes in classifying AD and MCI in addition to the widely used structural MRI-based morphometry, when combined with machine learning.\n\nHighlightsO_LIWe showed the utility of multimodal MRI, combining morphometry and white matter connectomes, to classify the diagnosis of AD and MCI using machine learning.\nC_LIO_LIIn predicting the progression from MCI to AD, the morphometry model showed the best performance.\nC_LIO_LITwo independent clinical datasets were used in this study: one for model building, the other for generalizability testing.\nC_LI

neuroscience↗

bioRxiv2018

Real-time non-invasive intracranial state estimation using unscented Kalman filter

Intracranial pressure (ICP) monitoring is desirable as a first-line measure to assist decision-making in cases of increased ICP. Clinically, non-invasive ICP monitoring is also required to avoid infection and hemorrhage in patients. The relationships among the arterial blood pressure (Pa), ICP, cerebral blood flow, and its velocity (QCBFv) measured by transcranial Doppler ultrasound measurement have been reported. However, real-time non-invasive ICP estimation using these modalities is less well documented. Here, we present a novel algorithm for real-time and non-invasive ICP monitoring with QCBFv and Pa, called direct-current (DC)-ICP. This technique is compared with invasive ICP for 11 traumatic-brain-injury patients admitted to Cheju Halla Hospital and Gangnam Severance Hospital from July 2017 to June 2018. The inter-subject correlation coefficient between true and estimate was 0.70. The AUCs of the ROCs for prediction of increased ICP for the DC-ICP methods are 0.816. Thus, QCBFv monitoring can facilitate reliable real-time ICP tracking with our novel DC-ICP algorithm, which can provide valuable information under clinical conditions.

neuroscience↗

bioRxiv2018

Altitudinal range-size distribution of breeding birds and environmental factors for the determination of species richness: An empirical test of altitudinal Rapoports rule and rescue effect on a local scale

Range-size distributions are important for understanding species richness patterns and led to the development of the controversial Rapoports rule and Rapoport-rescue effect. This study aimed to understand the relationship between species richness and range-size distribution in relation to environmental factors. The present study tested the following: (1) altitudinal Rapoports rule, (2) climatic and ambient energy hypotheses, (3) non-directional rescue effect, and (4) effect of environmental factors on range-size group. Altitudinal species range-size distribution increased with increasing altitude and showed a negative relationship with climatic variables and habitat heterogeneity, and a positive relationship with primary productivity. These results support the altitudinal Rapoports rule and climatic hypothesis; however, they do not fully support the ambient energy hypothesis. Results from testing the non-directional rescue effect showed that the inflow intensity of species from both directions (high and low elevations) affected species richness. And we found that the 2nd and 3rd quartile species distribution were the main cause of a mid-peak of species richness and the non-directional rescue effect. Additionally, the 2nd quartile species richness was highly related to minimum temperature and possessed thermal specialist species features, and the 3rd quartile species richness was highly related to habitat heterogeneity and primary productivity. Although altitudinal range-size distribution results were similar to the altitudinal Rapoports rule, the mid-peak pattern of species richness could not be explained by the Rapoports-rescue effect; however, the non-directional rescue effect could explain a mid-peak pattern of species richness.

ecology↗

bioRxiv2018

Efficient variant set mixed model association tests for continuous and binary traits in large-scale whole genome sequencing studies

With advances in Whole Genome Sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and Sequence Kernel Association Test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally-efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-Set Mixed Model Association Tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institutes Trans-Omics for Precision Medicine (TOPMed) program. SMMAT tests share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be only fit once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMAT tests correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

genetics↗

bioRxiv2018

Dysregulation of EMT Drives the Progression to Clinically Aggressive Sarcomatoid Bladder Cancer

The sarcomatoid variant of urothelial bladder cancer (SARC) displays a high propensity for distant metastasis and is associated with short survival. We report a comprehensive genomic analysis of 28 cases of SARCs and 84 cases of conventional urothelial carcinomas (UCs), with the TCGA cohort of 408 muscle-invasive bladder cancers serving as the reference. SARCs showed a distinct mutational landscape with enrichment of TP53, RB1, and PIK3CA mutations. They were related to the basal molecular subtype of conventional UCs and could be divided into epithelial/basal and more clinically aggressive mesenchymal subsets based on TP63 and its target genes expression levels. Other analyses revealed that SARCs are driven by downregulation of homotypic adherence genes and dysregulation of cell cycle and EMT networks, and nearly half exhibited a heavily infiltrated immune phenotype. Our observations have important implications for prognostication and the development of more effective therapies for this highly lethal variant of bladder cancer.

genomics↗

bioRxiv2018

MYCN Amplification and ATRX Mutations are Incompatible in Neuroblastoma

Aggressive cancers often have activating mutations in growth-controlling oncogenes and inactivating mutations in tumor-suppressor genes. In neuroblastoma, amplification of the MYCN oncogene and inactivation of the ATRX tumor-suppressor gene correlate with high-risk disease and poor prognosis. Here we show that ATRX mutations and MYCN amplification are mutually exclusive across all ages and stages in neuroblastoma. Using human cell lines and mouse models, we found that elevated MYCN expression and ATRX mutations are incompatible. Elevated MYCN levels promote metabolic reprogramming, mitochondrial dysfunction, reactive-oxygen species generation, and DNA-replicative stress. The combination of replicative stress caused by defects in the ATRX-histone chaperone complex and that induced by MYCN-mediated metabolic reprogramming leads to synthetic lethality. Therefore, ATRX and MYCN represent an unusual example, where inactivation of a tumor-suppressor gene and activation of an oncogene are incompatible. This synthetic lethality may eventually be exploited to improve outcomes for patients with high-risk neuroblastoma.

cancer biology↗

bioRxiv2018

High-throughput retrieval of physical DNA for NGS-identifiable clones in phage display library

In antibody discovery, in-depth analysis of an antibody library and high-throughput retrieval of clones in the library are crucial to identifying and exploiting rare clones with different properties. However, existing methods have several technical limitations such as low process throughput from laborious cloning process and waste of the phenotypic screening capacity from unnecessary repetitive tests on the dominant clones. To overcome the limitations, we developed a new high-throughput platform for the identification and retrieval of clones in the library, TrueRepertoire. TrueRepertoire provides highly accurate sequences of the clones with linkage information between heavy and light chains of the antibody fragment. Additionally, the physical DNA of clones can be retrieved in high throughput based on the sequence information. We validated the high accuracy of the sequences and demonstrated that there is no platform-specific bias. Moreover, the applicability of TrueRepertoire was demonstrated by a phage-displayed single-chain variable fragment (scFv) library targeting human hepatocyte growth factor (hHGF) protein.

bioengineering↗

bioRxiv2018

Developmental-stage-specific proliferation and retinoblastoma genesis in RB-deficient human but not mouse cone precursors

Most retinoblastomas initiate in response to the inactivation of the RB1 gene and loss of functional RB protein. The tumors may form without additional genomic changes and develop after a pre-malignant retinoma phase. Despite this seemingly straightforward etiology, mouse models have not recapitulated the genetic, cellular, and stage-specific features of human retinoblastoma genesis. For example, whereas human retinoblastomas appear to derive from cone photoreceptor precursors, current mouse models develop tumors that derive from other retinal cell types. To investigate the basis of the human cone-specific oncogenesis, we compared developmental-stage-specific cone precursor responses to RB loss in human and murine retina cultures and in cone-specific Rb1 knockout mice. We report that RB-depleted maturing (ARR3+) but not immature (ARR3-) human cone precursors enter the cell cycle, proliferate, and form retinoblastoma-like lesions characterized by Flexner-Wintersteiner rosettes, then form low or non-proliferative pre-malignant retinoma-like lesions with fleurettes and high p16INK4A and p130 expression, and finally form highly proliferative retinoblastoma-like masses. In contrast, in murine retina, only RB-depleted immature (Arr3-) cone precursors entered the cell cycle and they failed to progress from S to M phase. Moreover, whereas the intrinsically highly expressed MDM2 and MYCN contribute to RB-depleted maturing (ARR3+) human cone precursor proliferation, ectopic MDM2 and Mycn promoted only immature (Arr3-) murine cone precursor cell cycle entry. These findings demonstrate that developmental-stage-specific as well as speciesand cell-type-specific features sensitize to RB1 inactivation and reveal the human cone precursors capacity to model retinoblastoma initiation, proliferation, pre-malignant arrest, and tumor growth.\n\nSignificance StatementRetinoblastoma is a childhood tumor that forms in response to mutations in the RB1 gene and loss of functional RB protein. Prior studies suggested that retinoblastomas arise from cone photoreceptor precursors, whereas mouse models yield tumors deriving from other retinal cell types and lacking human retinoblastoma features. Here, we show that in cultured human retinae, retinoblastomas initiate from RB-depleted cone precursors that are in a specific maturation state and form pre-malignant \"retinomas\" prior to retinoblastoma lesions, as is believed to occur in retinoblastoma patients. In contrast, Rb-deficient mouse cone precursors of similar maturation state and supplemented with human-cone-precursor-specific oncoproteins fail to proliferate. Thus, human species-specific developmental features underlie retinoblastomagenesis and may challenge the production of accurate mouse retinoblastoma models.

cancer biology↗

bioRxiv2018

PTK2 regulates the UPS impairment via p62 phosphorylation in TDP-43 proteinopathy

TDP-43 proteinopathy is a common feature in a variety of neurodegenerative disorders including Amyotrophic lateral sclerosis (ALS) cases, Frontotemporal lobar degeneration (FTLD), and Alzheimers disease. However, the molecular mechanisms underlying TDP-43-induced neurotoxicity are largely unknown. In this study, we demonstrated that TDP-43 proteinopathy induces impairment in ubiquitin-proteasome system (UPS) evidenced by an accumulation of ubiquitinated proteins and reduction of proteasome activity in neuronal cells. Through kinase inhibitor screening, we identified PTK2 as a suppressor of neurotoxicity induced by UPS impairment. Importantly, PTK2 inhibition significantly reduces ubiquitin aggregates and attenuated TDP-43-induced cytotoxicity in Drosophila model of TDP-43 proteinopathy. We further identified that phosphorylation of p62 at serine 403 (p-p62S403), a key component in the autophagic degradation of poly-ubiquitinated proteins, is increased upon TDP-43 overexpression and dependent on activation of PTK2 in neuronal cells. Moreover, expressing a non-phosphorylated form of p62 (p62S403A) significantly represses accumulation of polyubiquitinated proteins and neurotoxicity induced by TDP-43 overexpression in neuronal cells. In addition, inhibition of TBK1, a kinase which phosphorylates S403 of p62, ameliorates neurotoxicity upon UPS impairment in neuronal cells. Taken together, our data suggest that activation of PTK2-TBK1-p62 axis plays a critical role in the pathogenesis of TDP-43 by regulating neurotoxicity induced by UPS impairment. Therefore, targeting PTK2-TBK1-p62 axis may represent a novel therapeutic intervention for neurodegenerative diseases with TDP-43 proteinopathy.

neuroscience↗