Biology subjects

Lee, J.-H.

Publications and source records attributed to Lee, J.-H..

At least 91 records · Page 5Linked to original sources

bioRxiv2020

ISG15-dependent Activation of the RNA Sensor MDA5 and its Antagonism by the SARS-CoV-2 papain-like protease

Activation of the RIG-I-like receptors, RIG-I and MDA5, establishes an antiviral state by upregulating interferon (IFN)-stimulated genes (ISGs). Among these is ISG15 whose mechanistic roles in innate immunity still remain enigmatic. Here we report that ISGylation is essential for antiviral IFN responses mediated by the viral RNA sensor MDA5. ISG15 conjugation to the caspase activation and recruitment domains of MDA5 promotes the formation of higher-order assemblies of MDA5 and thereby triggers activation of innate immunity against a range of viruses including coronaviruses, flaviviruses and picornaviruses. The ISG15-dependent activation of MDA5 is antagonized through direct de-ISGylation mediated by the papain-like protease (PLpro) of SARS-CoV-2, a recently emerged coronavirus that causes the COVID-19 pandemic. Our work demonstrates a crucial role for ISG15 in the MDA5-mediated antiviral response, and also identifies a novel immune evasion mechanism of SARS-CoV-2, which may be targeted for the development of new antivirals and vaccines to combat COVID-19.

immunology↗

bioRxiv2020

Poly-ADP-ribosylation drives loss of protein homeostasis in ATM and Mre11 deficiency

Loss of the ataxia-telangiectasia mutated (ATM) kinase causes cerebellum-specific neurodegeneration in humans. We previously demonstrated that deficiency in ATM activation via oxidative stress generates high levels of insoluble protein aggregates in human cells, reminiscent of protein dysfunction in common neurodegenerative disorders. Here we show that this process is driven by poly-ADP-ribose polymerases (PARPs) and that the insoluble protein species arise from intrinsically disordered proteins associating with PAR-associated genomic sites in ATM-deficient cells. The lesions implicated in this process are single-strand DNA breaks dependent on reactive oxygen species, transcription, and R-loops. Human cells expressing Mre11 A-T-like disorder (ATLD) mutants also show PARP-dependent aggregation identical to that of ATM deficiency. Lastly, analysis of A-T patient cerebellum samples shows widespread protein aggregation as well as loss of proteins known to be critical in human spinocerebellar ataxias. These results provide a new hypothesis for loss of protein integrity and cerebellum function in A-T.

molecular biology↗

bioRxiv2020

Protein hyperacylation links mitochondrial dysfunction with nuclear organization

Cellular metabolism is linked to epigenetics, but the biophysical effects of metabolism on chromatin structure and implications for gene regulation remain largely unknown. Here, using a broken tricarboxylic acid (TCA) cycle and disrupted electron transport chain (ETC) exemplified by succinate dehydrogenase subunit C (SDHC) deficiency, we investigated the effects of metabolism on chromatin architecture over multiple distance scales [nucleosomes ([~]102 bp), topologically-associated domains (TADs; [~]105 - 106 bp), and chromatin compartments (106 - 108 bp)]. Metabolically-driven hyperacylation of histones led to weakened nucleosome positioning in multiple types of chromatin, and we further demonstrate that lysine acylation directly destabilizes histone octamer-DNA interactions. Hyperacylation of cohesin subunits correlated with decreased mobility on interphase chromatin and increased TAD boundary strength, suggesting that cohesin is metabolically regulated. Erosion of chromatin compartment distinctions reveals metabolic regulation of chromatin liquid-liquid phase separation. The TCA cycle and ETC thus modulate chromatin structure over multiple distance scales.

cell biology↗

bioRxiv2020

Determinants of Real-Time fMRI Neurofeedback Performance and Improvement: a Machine Learning Mega-Analysis

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in Open Science and data sharing.

neuroscience↗

bioRxiv2020

ZNF416 is a pivotal transcriptional regulator of fibroblast mechano-activation

Matrix stiffness is a central regulator of fibroblast function. However, the transcriptional mechanisms linking matrix stiffness to changes in fibroblast phenotype are incompletely understood. Here, we evaluated the effect of matrix stiffness on genome-wide chromatin accessibility in freshly-isolated lung fibroblasts using assay for transposase-accessible chromatin followed by sequencing (ATAC-seq). We found higher matrix stiffness profoundly increased global chromatin accessibility relative to lower matrix stiffness, and these alterations were in close genomic proximity to known pro-fibrotic gene programs. Motif analysis of these regulated genomic loci identified ZNF416 as a putative mediator of fibroblast stiffness responses. Similarly, motif analysis of the promoters of differentially expressed genes observed in freshly sorted fibroblasts from an experimental bleomycin lung fibrosis model also identified ZNF416 as a putative mediator of in vivo fibroblast activation. Genome occupancy analysis using chromatin-immunoprecipitation followed by sequencing (ChIP-seq) confirmed that ZNF416 occupies a broad range of genes implicated in fibroblast activation and tissue-fibrosis, with relatively little overlap in genomic occupancy with other mechanoresponsive and pro-fibrotic transcriptional regulators. Using loss and gain of function studies we demonstrated that ZNF416 plays a critical role in fibroblast proliferation, extracellular matrix synthesis and contractile function. Together these observations identify ZNF416 as novel mechano-activated transcriptional regulator of fibroblast biology.

cell biology↗

bioRxiv2020

Reconstitution of Alveolar Regeneration via novel DATPs by Inflammatory Niches

Tissue regeneration involves a multi-step process composed of diverse cellular hierarchies and states that are also implicated in tissue dysfunction and pathogenesis. Here, we leveraged single-cell RNA sequencing analysis in combination with in vivo lineage tracing and organoid models to fine-map trajectories of alveolar lineage cells during injury repair and regeneration. We identified Damage-Associated Transient Progenitors (DATPs) as a distinct AT2-lineaged population arising during alveolar regeneration. Specifically, we found that IL-1{beta}, secreted by interstitial macrophages, primes a subset of Il1r1+AT2 cells for conversion into DATPs, via a Hif1a-mediated glycolysis pathway, that are functional mediators for mature AT1 cell differentiation. Importantly, we show that chronic inflammation mediated by IL-1{beta} prevents differentiation into AT1 cells, leading to aberrant accumulation of DATPs and impaired alveolar differentiation. Our step-wise fine-mapping of cell fate transitions demonstrates how the inflammatory niche impedes alveolar regeneration by directing stem cell fate behavior.

cell biology↗

bioRxiv2020

Molecular mapping of qBK1Z, a major QTL for bakanae disease resistance in rice

Bakanae disease is a fungal disease of rice (Oryza sativa L.) caused by the pathogen Gibberella fujikuroi (also known as Fusarium fujikuroi). Recently the disease incidence has increased in several Asian countries and continues to spread throughout the world. No rice varieties have been developed yet to be completely resistant to this disease. With increasing need to identify various genetic resources to impart resistance to local elite varieties, this study was carried out to identify novel quantitative trait loci (QTLs) from an indica variety Zenith. We performed a QTL mapping using 180 F2:9 recombinant inbred lines (RILs) derived from a cross between the resistant variety, Zenith, and the susceptible variety, Ilpum. A primary QTL study using the genotypes and phenotypes of the RILs indicated that the locus qBK1z conferring bakanae disease resistance from the Zenith was located in a 2.8 Mb region bordered by the two SSR markers, RM1331 and RM3530 on chromosome 1. The log of odds (LOD) score of qBK1z was 13.43, accounting for 30.9% of the total phenotypic variation. A finer localization of qBK1z was delimited at an approximate 730 kb interval in the physical map between Chr01_1435908 (1.43 Mbp) and RM10116 (2.16 Mbp). The development of a rice variety with a higher level of resistance against bakanae disease is a major challenge in many rice growing countries. Introducing qBK1z or pyramiding with other previously identified QTLs could provide effective genetic control of bakanae disease in rice.

plant biology↗

bioRxiv2020

Spatiotemporal contribution of neuromesodermal progenitor-derived neural cells in the elongation of developing mouse spinal cord

During vertebrate development, the posterior end of the embryo progressively elongates in a head-to-tail direction to form the body plan. Recent lineage tracing experiments revealed that bi-potent progenitors, called neuromesodermal progenitors (NMPs), produce caudal neural and mesodermal tissues during axial elongation. However, their precise location and contribution to spinal cord development remain elusive. Here we used NMP-specific markers (Sox2 and BraT) and a genetic lineage tracing system to localize NMP progeny in vivo. NMPs were initially located at the tail tip, but were later found in the caudal neural tube, which is a unique feature of mouse development. In the neural tube, they produced neural stem cells (NSCs) and contributed to the spinal cord gradually along the AP axis during axial elongation. Interestingly, NMP-derived NSCs preferentially contributed to the ventral side first and later to the dorsal side at the lumbar spinal cord level, which may be associated with atypical junctional neurulation in mice. Our current observations detail the contribution of NMP progeny to spinal cord elongation and provide insights into how different species uniquely execute caudal morphogenesis.

developmental biology↗

bioRxiv2020

miTAR: a hybrid deep learning-based approach for predicting miRNA targets

microRNAs (miRNAs) are a major type of small RNA that alter gene expression at the post-transcriptional or translational level. They have been shown to play important roles in a wide range of biological processes. Many computational methods have been developed to predict targets of miRNAs in order to understand miRNAs function. However, the majority of the methods depend on a set of pre-defined features that require considerable effort and resources to compute, and these methods often do not effectively on the prediction of miRNA targets. Therefore, we developed a novel hybrid deep learning-based approach that is capable to predict miRNA targets at a higher accuracy. Our approach integrates two deep learning methods: convolutional neural networks (CNNs) that excel in learning spatial features, and recurrent neural networks (RNNs) that discern sequential features. By combining CNNs and RNNs, our approach has the advantages of learning both the intrinsic spatial and sequential features of miRNA:target. The inputs for the approach are raw sequences of miRNA and gene sequences. Data from two latest miRNA target prediction studies were used in our study: the DeepMirTar dataset and the miRAW dataset. Two models were obtained by training on the two datasets separately. The models achieved a higher accuracy than the methods developed in the previous studies: 0.9787 vs. 0.9348 for the DeepMirTar dataset; 0.9649 vs. 0.935 for the miRAW dataset. We also calculated a series of model evaluation metrics including sensitivity, specificity, F-score and Brier Score. Our approach consistently outperformed the current methods. In addition, we compared our approach with earlier developed deep learning methods, resulting in an overall better performance. Lastly, a unified model for both datasets was developed with an accuracy higher than the current methods (0.9545). We named the unified model miTAR for miRNA target prediction. The source code and executable are available at https://github.com/tjgu/miTAR.

bioinformatics↗

bioRxiv2020

Differential RNA editing between epithelial and mesenchymal tumors impacts mRNA abundance in immune response pathways

Recent studies revealed global shifts in RNA editing, the modification of RNA sequences, across many cancers. Besides a few sites implicated in tumorigenesis or metastasis, most tumor-associated sites, predominantly in noncoding regions, have unknown function. Here, we characterize editing profiles between epithelial (E) and mesenchymal (M) phenotypes in seven cancer types, as epithelial-mesenchymal transition (EMT) is a key paradigm for metastasis. We observe distinct editing patterns between E and M tumors and EMT induction upon loss of ADAR enzymes in cultured cells. E-M differential sites are highly enriched in genes involved in immune and viral processes, some of which regulate mRNA abundance of their respective genes. We identify a novel mechanism in which ILF3 preferentially stabilizes edited transcripts. Among editing-dependent ILF3 targets is the transcript encoding PKR, a crucial player in immune response. Our study demonstrates the broad impact of RNA editing in cancer and relevance of editing to cancer-related immune pathways.

cancer biology↗

bioRxiv2020

Undinarchaeota illuminate the evolution of DPANN archaea

Introductory paragraphThe evolution and diversification of Archaea is central to the history of life on Earth. Cultivation-independent approaches have revealed the existence of at least ten archaeal lineages whose members have small cell and genome sizes and limited metabolic capabilities and together comprise the tentative DPANN archaea. However, the phylogenetic diversity of DPANN and the placement of the various lineages of this group in the archaeal tree remain debated. Here, we reconstructed additional metagenome assembled genomes (MAGs) of a thus far uncharacterized archaeal phylum-level lineage UAP2 (Candidatus Undinarchaeota) affiliating with DPANN archaea. Comparative genome analyses revealed that members of the Undinarchaeota have small estimated genome sizes and, while potentially being able to conserve energy through fermentation, likely depend on partner organisms for the acquisition of vitamins, amino acids and other metabolites. Phylogenomic analyses robustly recovered Undinarchaeota as a major independent lineage between two highly supported clans of DPANN: one clan comprising Micrarchaeota, Altiarchaeota and Diapherotrites, and another encompassing all other DPANN. Our analyses also suggest that DPANN archaea may have exchanged core genes with their hosts by horizontal gene transfer (HGT), adding to the difficulty of placing DPANN in the archaeal tree. Together, our findings provide crucial insights into the origins and evolution of DPANN archaea and their hosts.

evolutionary biology↗

bioRxiv2020

Comparative analysis of primer-probe sets for the laboratory confirmation of SARS-CoV-2

Coronavirus disease 2019 (COVID-19) is newly emerging human infectious diseases, which is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2, also previously known as 2019-nCoV). Within two months of the outbreak, more than 80,000 cases of COVID-19 have been confirmed worldwide. Since the human to human transmission occurred easily and the human infection is rapidly increasing, the sensitive and early diagnosis is essential to prevent the global outbreak. Recently, World Health Organization (WHO) announced various primer and probe sets for SARS-CoV-2 previously developed in China, Germany, Hong Kong, Japan, Thailand, and USA. In this study, we compared the ability to detect SARS-CoV-2 RNA among the seven primer-probe sets for N gene and the three primer-probe sets for Orf1 gene. The result of the comparative analysis represented that the 2019-nCoV_N2, N3 of USA and the ORF1ab of China are the most sensitive primer-probe sets for N and Orf1 genes, respectively. Therefore, the appropriate combination from ORF1ab (China), 2019-nCoV_N2, N3 (USA), and NIID_2019-nCOV_N (Japan) sets should be selected for the sensitive and reliable laboratory confirmation of SARS-CoV-2.

microbiology↗

bioRxiv2020

Differential TM4SF5-mediated SIRT1 modulation and signaling for chronic liver disease

Here we show the roles of transmembrane 4 L six family member 5 (TM4SF5) in the progression of nonalcoholic steatosis (or NAFL) to steatohepatitis (NASH). The overexpression of TM4SF5 caused nonalcoholic steatosis and NASH in an age-dependent manner. Initially, TM4SF5-positive hepatocytes and livers exhibited lipid accumulation, decreased SIRT1, increased SREBPs levels, and inactive STAT3 via SOCS1/3 upregulation. In older animals, TM4SF5 under an inflammatory environment increased SIRT1 expression and STAT3 activity with no significant change to SOCSs and SREBPs levels, leading to active STAT3-mediated fibrotic extracellular matrix (ECM) production. Liver tissues from clinical human patients with NAFL or NASH also showed such a TM4SF5-SIRT1-STAT3-ECM relationship correlated with fibrosis score and age. Ligand-independent and TM4SF5-mediated STAT3 activity led to collagen I and laminins/laminin {gamma}2 expression in hepatic stellate cells and hepatocytes, respectively. Laminin {gamma}2 suppression abolished CCl4-mediated liver damage and ECM production and reduced SIRT1 and active-STAT3, but did not alter SREBP1 or SOCSs levels. These findings suggest that TM4SF5, CCL20, SIRT1, and/or laminin {gamma}2 may be promising therapeutic targets against liver disease.

cell biology↗

bioRxiv2020

Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large interindividual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pre-training functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pre-training activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

neuroscience↗

bioRxiv2019

Prediction-based highly sensitive CRISPR off-target validation using target-specific DNA enrichment

CRISPR effectors, which comprise a CRISPR-Cas protein and a guide (g)RNA derived from the bacterial immune system, are widely used to induce double-strand breaks in target DNA and activate the in-vivo DNA repair system for target-specific genome editing. When the gRNA recognizes genomic loci with sequences that are similar to the target, deleterious and often carcinogenic mutations can occur. Off-target mutations with a frequency below 0.5% remain mostly undetected by current genome-wide off-target detection techniques. In this study, we developed a method to effectively detect extremely small amounts of mutated DNA based on predicted off-target-specific amplification. We used various genome editors, including CRISPR-Cpf1, Cas9, and an adenine base editor, to induce intracellular genome mutations. The CRISPR amplification method detected off-target mutations at a significantly higher rate (1.6[~]984 fold increase) than did an existing targeted amplicon sequencing method. In the near future, CRISPR amplification in combination with genome-wide off-target detection methods will allow to detect genome editor-induced off-target mutations with high sensitivity and in a non-biased manner.

molecular biology↗

bioRxiv2019

Comprehensive identification of HSP70/HSC70 Chaperone Clients in Human Cells

The HSP70 family of chaperones are the front-line of protection from stress-induced misfolding and aggregation of polypeptides in most organisms and are responsible for promoting the stability, folding, and degradation of clients to maintain cellular protein homeostasis. Here we demonstrate quantitative identification of HSP70 and HSC70 clients using an ubiquitin-mediated proximity tagging strategy and show that, despite their high degree of similarity, these enzymes have largely non-overlapping specificities. Both proteins show a preference for association with newly synthesized polypeptides but each responds differently to changes in the stoichiometry of proteins in obligate multi-subunit complexes. In addition, expression of an ALS-associated SOD1 mutant protein induces changes in HSP70 and HSC70 client association and aggregation toward polypeptides with predicted disorder, indicating that there are global effects from a single misfolded protein that extend to many clients within chaperone networks. Together these findings show that the ubiquitin-mediated UBAIT fusion system can efficiently isolate the complex interactome of HSP chaperone family proteins under normal and stress conditions.

molecular biology↗

bioRxiv2019

Liver cells and PBMC secrete Tumor-suppressive Plasma Extracellular Vesicles in Melanoma patients

Before and after surgery melanoma patients harbor elevated levels of extracellular vesicles in plasma (pEV), but their cellular origin is obscure. Here we suggest that these pEV are secreted in part by tumor cells, but particularly by liver and peripheral blood mononuclear cells (PBMC), which strongly suppressed tumor cell activity. As the cellular origin of pEV is difficult to determine, we mimicked the interaction of tumor cells with liver cells and PBMC in vitro, and compared newly secreted EV-associated miRNAs and protein factors with those detected in melanoma patients pEV. The results identified factors that could be associated either with tumor cell activity or the counteracting immune system and liver cells. Notably, the presence/absence of these factors correlated with the clinical stage and tumor relapse. Our study provides new insights into the innate immune defense against tumor cells and implies that residual tumor cells may be more active than previously thought.\n\nSummary blurbPlasma extracellular vesicles (pEV) in melanoma patients are a mix of cancer cell-suppressive vesicles from liver cells and PBMC, but derive also from residual cancer cells.

cancer biology↗

bioRxiv2019

Dose assessment in dental cone beam computed tomography: comparison of optically stimulated luminescence dosimetry with the Monte Carlo method

The usage and the model variety of CBCT machine has been rapidly increasing, the dose evaluation of individual devices became an important issue. Patient dose from CBCT was assessed with two different methods, optically stimulated luminescence dosimeter (OSLD) measured and monte carlo (MC) simulation, in four different examination modes. Through the measurement process and obtained value, more practical and efficient method in acquiring CBCT effective dose would be suggested. Twenty-five OSLD were calibrated and equipped in human phantom of head and neck organs. This was exposed on 2 CBCT units, CS9300 (Carestream Dental LLC, Atlanta, Georgia) and RAYSCAN + (Ray Co. Ltd, Hwaseong-si, Korea) with 2 different examination modes. Dose recorded in dosimetry was obtained and organ dose as well as an effective dose were obtained in each units of examination modes. Those values were also calculated using MC software, PCXMC (STUK, Helsinki, Finland). The organ doses and effective doses from both methods were compared by each examination mode of individual unit. OSLD measured effective dose value was higher than that obtained with MC method in each examination mode, except dual jaw mode of CS9300. The percent difference of effective dose between the two methods were ranged from 4.0 to 14.3 %. The dose difference between the methods was decreased as the examination FOV decreased. Organ dose values were varied according to the method, while overall trend was similar in both methods. The organs showing high dose were mostly consistent in both methods. In this study, the effective dose obtained by OSLD measurement and MC simulation were compared and both methods were described in detail. Consequently, as relatively efficient and easy-handling method, we carefully suggest MC simulation for further dose evaluation.

scientific communication and education↗