Biology subjects

Kwon, E.

Publications and source records attributed to Kwon, E..

At least 19 recordsLinked to original sources

bioRxiv2026

Single-base mapping of m6A in lncRNAs reveals a distinct landscape linked to transposable elements and RNA processing

N6-methyladenosine (m6A) is the most abundant internal RNA modification with established roles in mRNA metabolism. Although m6A has been characterized in several well-known long noncoding RNAs (lncRNAs), its transcriptome-wide landscape and roles remain poorly understood. Here, we characterized the m6A landscape of lncRNAs at single-base resolution, identified m6A deposition-associated features, and investigated potential roles of m6A in lncRNA processing. Unlike in mRNAs, m6A sites are broadly distributed along lncRNAs. We further found that these differences in m6A patterns between lncRNAs and mRNAs may reflect contributions from transposable element-derived sequence to motif availability and local RNA structure, together with splicing-related constraints on m6A deposition near exon junctions. Additionally, m6A may be relevant to the regulation of lncRNA polyadenylation. Together, these findings define the single-base-resolution m6A landscape in lncRNAs, and connect lncRNA methylation to transposable elements, RNA structure, splicing, and polyadenylation. This study broadens our understanding of m6A in the lncRNA epitranscriptome.

genomics↗

bioRxiv2026

CMAC: A deep learning framework for absolute cardiomyocyte transcriptional age estimation

Cardiomyocyte maturation spans embryogenesis through postnatal life and involves coordinated transcriptional transitions that are disrupted in disease and incompletely recapitulated by stem cell-derived cardiomyocytes. However, no unified framework exists for assigning absolute transcriptional maturation age across datasets, platforms, and experimental conditions. Here, we developed CMAC (Cardiomyocyte Maturation Age Clock), integrating 18 murine single-cell RNA-sequencing datasets spanning embryonic and postnatal timepoints, into a batch-invariant probabilistic atlas using single cell variational inference (scVI) with a 100-dimensional latent representation. Analysis of the developmental trajectory revealed highly non-uniform transcriptional change, with 63.9% of the total transcriptional journey completed by birth and the neonatal transition representing the largest single transcriptional step. An XGBoost regressor trained on the CMAC latent space predicted absolute chronological age with a leave-one-dataset-out mean absolute error (MAE) of 4.09 days (median 3.27 days), Pearson r = 0.903, and Spearman {rho} = 0.908 across 18 datasets and six sequencing platforms, outperforming linear regression (MAE = 6.18 days) and PCA-based representations (MAE = 6.35 days). In an independent P14 cohort comprising 98,163 cardiomyocytes from six biological replicates, CMAC achieved a mouse-level MAE of 0.33 days, with all six mice predicted within 1.1 days of chronological age. Application of CMAC to a previously published PGC1/{beta} double-knockout model with established delayed cardiomyocyte maturation independently recapitulated this phenotype, quantifying maturation deficits of 4.77 to 8.60 days across P7 to P28, with the largest deficit at P14. Together, these results establish CMAC as a quantitative, deep learning framework for assigning absolute transcriptional maturation age and quantifying deviations from normal cardiomyocyte development.

genomics↗

bioRxiv2026

Comparative profiling of SARS-CoV-2 variant infections reveals diverse impacts on host cell RNA and RNA binding protein distribution and regulation

RNA viruses perturb cellular RNA metabolism to promote viral transcript expression and genome replication. However, the extent of host cell RNA reprogramming and the consequences on RNA binding protein (RBP) expression and localization remain poorly understood. Here, we utilized an integrated set of transcriptomics, proteomics, and high-content imaging approaches to compare the impact of different SARS-CoV-2 variants, including an early viral isolate and later emerging variants of concern (Alpha, Delta and Omicron) on the host cellular RNA and RBP landscapes. While all variants deeply remodelled the host transcriptome in a subcellular compartment-specific manner, we found that Omicron variants express lower levels of viral RNA products compared to earlier variants, while still driving efficient production of viral proteins. The surge in viral RNA expression correlated with altered subcellular RNA biotype distribution, cytoplasmic mRNA exclusion, the selective disruption of the localization of polyA-tail interacting proteins, and the nuclear accumulation of non-coding transcripts such as RN7SL family members and MALAT-1. Unexpectedly, we found many RBPs that exhibiting altered subcellular localization following abiotic innate immune stimulation with poly(I:C) but remained unaltered in cells infected with SARS-CoV-2 variants, revealing a capacity for these viruses to limit the overall impact on the RBP subcellular distribution. Our results further indicate that Omicron infection sustains higher expression levels of proteins components of the signal recognition particle and translation factors, which may enable a more effective production of immune response and viral components. Altogether, this work highlights the deep impact of SARS-CoV-2 infection on host cell RNA regulatory landscape and provides new insights to explain the differential impact of Omicron compared to early SARS-CoV-2 variants. HighlightsO_LISARS-CoV-2 variants drive varying degrees of viral RNA expression in infected Calu-3 cells C_LIO_LIInfection reshapes the host cell RNA landscape in a cell-compartment specific manner C_LIO_LIRN7SL RNA exhibits a strong increase in relative abundance and accumulates in the nucleus of infected cells C_LIO_LISARS-CoV-2 infections impact the localization of polyA-tail binding proteins while blocking the nuclear accumulation of immune response-sensitive RBPs C_LIO_LIOmicron infections are less disruptive to cellular function and sustain the production of translation factors and components of the SRP complex C_LI

molecular biology↗

bioRxiv2025

Structural insights into autophosphorylation-mediated heat shock response by the protein-arginine kinase McsAB

McsAB is a protein-arginine kinase that activates heat shock genes by inhibiting the transcriptional repressor CtsR. However, the mechanism by which McsAB suppresses CtsR during heat shock remains unclear. Here, we present cryo-electron microscopy structures of Bacillus subtilis McsAZ2-McsB and its complex with CtsR. Our structural analyses reveal that McsAZ2-McsB forms a rod-shaped heterotetramer, with two of these heterotetramers assembling into an asymmetrically crossing shape through phosphorylated arginine residues (pArg194 and pArg333) of McsB. The CtsR dimer binds to the groove of the McsAZ2-McsB oligomer via pArg115 of McsA and pArg194 of McsB. Anisotropy experiments indicate that CtsR dissociates slowly from its operator during heat shock, and McsAB facilitates this process in an ATP-dependent manner. Furthermore, mutations in the arginine residues of McsAB reduce its ability to hijack CtsR during heat shock. These results demonstrate that autophosphorylation of McsAB is essential for a rapid and effective heat shock response.

biochemistry↗

bioRxiv2025

High-resolution cryo-EM structures of small protein-ligand complexes near the theoretical size limit

Cryo-electron microscopy (cryo-EM) is widely used to determine macromolecular structures at atomic resolution. The theoretical size lower limit of particles for cryo-EM analysis is 38 kDa, limited by factors such as contrast and particle alignment accuracy. To date, no cryo-EM structures have been reported for proteins near this size limit. This study presents cryo-EM structures of two protein-ligand complexes around 40 kDa. The structure of maltose-binding protein (43 kDa) was determined at 2.32 [A] resolution, clearly revealing the bound maltose and water molecules. Additionally, the kinase domain of human PLK1 (37 kDa), slightly below the theoretical limit, was determined at 3.04 [A] resolution, allowing the identification of the bound ligand, onvansertib. These findings demonstrate that cryo-EM can be effectively employed for structure determination and structure-based drug screening of small proteins or domains.

biophysics↗

bioRxiv2025

Preconditioning Matters: Enhancing or Impairing Antitumor Immunity with DC Vaccines

Preconditioning regimens are essential for the success of adoptive cell therapies like CAR T-cells due to effects on the T-cell response, yet they are underexplored and generally absent from cancer vaccine clinical trials. To address this gap, we evaluated the impact of various preconditioning strategies on dendritic cell (DC) vaccine efficacy in a murine tumor model. Mice bearing syngeneic KP tumors expressing ovalbumin received preconditioning with low-dose radiation (LD RT; whole body or tumor only), cyclophosphamide, paclitaxel, LD RT plus cyclophosphamide, or no preconditioning, followed by administration of antigen-loaded DC1s. Tumor growth, survival, and antigen-specific CD8+ T-cell responses were assessed. LD RT preconditioning, whether whole body or tumor-directed, significantly enhanced vaccine-induced antitumor CD8+ T-cell responses and improved survival compared to DC vaccine alone and all other groups. Cyclophosphamide preconditioning reduced vaccine efficacy and negated the benefits of LD RT, while paclitaxel had no significant effect. Notably, whole-body LD RT induced the strongest antigen-specific T-cell response. These findings demonstrate that, similar to CAR T-cell therapy, preconditioning regimens can significantly influence cancer vaccine outcomes. Rational selection of preconditioning agents may either maximize or minimize the therapeutic potential of DC cancer vaccines, and should be considered carefully in clinical trials.

immunology↗

bioRxiv2025

Structural analyses of gibberellin-mediated DELLA protein degradation

Gibberellin promotes plant growth by downregulating growth-repressor DELLA proteins. The gibberellin receptor GID1 binds to DELLA proteins in the presence of gibberellin, triggering their degradation through polyubiquitination by SCFSLY1/GID2 ubiquitin E3 ligase. Despite extensive studies, the molecular mechanisms by which DELLA proteins assemble with SCFSLY1/GID2 to regulate plant growth remain poorly understood. Here, we present two cryo-electron microscopy structures of the Arabidopsis thaliana DELLA protein RGA in complex with GID1A and GID1A-SLY1-ASK2, respectively. Structural analysis revealed that RGA interacts with GID1A and SLY1 through non-overlapping binding surfaces, stabilizing the proteins. This suggests that the SCFSLY1-RGA-GID1A complex assembles through stepwise stabilization induced by gibberellin. Furthermore, the structures indicate that RGA does not interact with IDD family transcription factors when bound to SLY1, suggesting that the binding of DELLA proteins to GID1/SLY1 and transcription factors is mutually exclusive. These findings provide insights into how DELLA proteins regulate transcription factor activity in response to gibberellin.

plant biology↗

bioRxiv2024

Investigating the Impacts of Sphingomyelinases on Extracellular Vesicle Cargo Sorting

Extracellular vesicles (EVs) form through regulated biogenesis processes involving sphingomyelinases (SMases), enzymes that metabolize sphingomyelin to produce ceramide--a lipid influencing membrane rigidity and essential for EV generation. This study explores the impact on EV protein and RNA cargoes resulting from inhibiting neutral SMase (NSM) and acid SMase (ASM) in human MCF7 cells. Our results revealed that NSM inhibition reduces EV nanoparticles and diminishes RNA and protein cargoes, including endosomal, spliceosomal, and translation-related proteins. Conversely, ASM inhibition increased RNA-binding proteins within and enhanced the expression of ribonucleoprotein complex-associated RNA in released EVs, including several snRNAs and 7SL RNA. Intriguingly, ASM-inhibited EVs enhanced the migration and translational activity of recipient MCF10A cells. These findings suggest an important role for SMase-dependent vesiculation in governing RNA and protein trafficking to the extracellular space, unveiling potential implications for cellular communication and function.

molecular biology↗

bioRxiv2024

Impact of preanalytical factors on liquid biopsy in the canine cancer model

While liquid biopsy has potential to transform cancer diagnostics through minimally-invasive detection and monitoring of tumors, the impact of preanalytical factors such as the timing and anatomical location of blood draw is not well understood. To address this gap, we leveraged pet dogs with spontaneous cancer as a model system, as their compressed disease timeline facilitates rapid diagnostic benchmarking. Key liquid biopsy metrics from dogs were consistent with existing reports from human patients. The tumor content of samples was higher from venipuncture sites closer to the tumor and from a central vein. Metrics also differed between lymphoma and non-hematopoietic cancers, urging cancer-type-specific interpretation. Liquid biopsy was highly sensitive to disease status, with changes identified soon after post chemotherapy administration, and trends of increased tumor fraction and other metrics observed prior to clinical relapse in dogs with lymphoma or osteosarcoma. These data support the utility of pet dogs with cancer as a relevant system for advancing liquid biopsy platforms.

genomics↗

bioRxiv2024

The collective application of shorebird tracking data to conservation

Addressing urgent conservation issues, like the drastic declines of North American migratory birds, requires creative, evidence-based, efficient, and collaborative approaches. Over 50% of monitored North American shorebird populations have lost over 50% of their abundance since 1980. To address these declines, we developed a partnership of scientists and practitioners called the Shorebird Science and Conservation Collective (hereinafter "the Collective"). Here, we present this successful case study as an example for others engaged in translational science. The Collective acts as an intermediary whereby dedicated staff collate and analyze data contributions from scientists to support knowledge requests from conservation practitioners. Data contributions from 74 organizations include over 6.7 million shorebird locations forming movement paths of 3,345 individuals representing 36 species tracked across the Americas. We describe the founding and structure of the Collective and conservation activities we supported in our first two years. As the volume of scientific data on animal movements continues to grow, groups like the Collective can be vital liaisons to rapidly integrate and interpret research to support conservation action.

ecology↗

bioRxiv2024

BAMBI: Integrative biostatistical and artificial-intelligence method discover coding and non-coding RNA genes as biomarkers

Accurate disease diagnosis and prognosis are crucial for effective treatment management and improving patient outcomes. However, accurately detecting early signs of certain diseases or recurrence remains challenging. Existing machine-learning methods for identifying gene expression biomarkers have several limitations, including poor performance on independent test datasets, inability to directly process omics data, and difficulty in identifying noncoding RNA genes as biomarkers. Additionally, these methods may not provide sufficient biological interpretation of their results, and the panel biomarkers they identify may not be suitable for clinical application. To address these limitations, we have developed a new computational method called BAMBI, which integrates multiple machine-learning algorithms and statistical approaches to identify putative coding and noncoding genes as biomarkers for disease diagnosis and prognosis. We evaluated BAMBI ability to identify diagnostic and prognostic biomarkers by analyzing multiple RNA-seq datasets from cancerous and non-cancerous diseases at population levels. The results from BAMBI demonstrate significant biological interpretability and state-of-the-art prediction performance. When the singular gene identified by BAMBI is used as a diagnostic biomarker, it achieves a balance accuracy exceeding 95% in studies of both breast cancer and psoriasis. Additionally, the prognostic biomarkers that BAMBI identifies from RNA-seq data of Acute Myeloid Leukemia (AML) patients significantly correlate with the survival rates in an independent AML patient cohort. Additionally, BAMBI outperforms existing methods by delivering more robust results, identifying biomarkers with fewer genes, and simultaneously achieving superior prediction accuracy. We have implemented BAMBI into user-friendly software for the research community. In summary, BAMBI serves as a more reliable pipeline for identifying both coding and noncoding genes as biosignature markers, enhancing the accuracy of disease diagnosis and prognosis. BAMBI is available via https://github.com/CZhouLab/BAMBI.

bioinformatics↗

bioRxiv2023

Reduced histone gene copy number disrupts Drosophila Polycomb function

The chromatin of animal cells contains two types of histones: canonical histones that are expressed during S phase of the cell cycle to package the newly replicated genome, and variant histones with specialized functions that are expressed throughout the cell cycle and in non-proliferating cells. Determining whether and how canonical and variant histones cooperate to regulate genome function is integral to understanding how chromatin-based processes affect normal and pathological development. Here, we demonstrate that variant histone H3.3 is essential for Drosophila development only when canonical histone gene copy number is reduced, suggesting that coordination between canonical H3.2 and variant H3.3 expression is necessary to provide sufficient H3 protein for normal genome function. To identify genes that depend upon, or are involved in, this coordinate regulation we screened for heterozygous chromosome 3 deficiencies that impair development of flies bearing reduced H3.2 and H3.3 gene copy number. We identified two regions of chromosome 3 that conferred this phenotype, one of which contains the Polycomb gene, which is necessary for establishing domains of facultative chromatin that repress master regulator genes during development. We further found that reduction in Polycomb dosage decreases viability of animals with no H3.3 gene copies. Moreover, heterozygous Polycomb mutations result in de-repression of the Polycomb target gene Ubx and cause ectopic sex combs when either canonical or variant H3 gene copy number is also reduced. We conclude that Polycomb-mediated facultative heterochromatin function is compromised when canonical and variant H3 gene copy number falls below a critical threshold.

genetics↗

bioRxiv2022

Flnc: Machine Learning Improves the Identification of Novel Full-length Long Noncoding RNAs from RNA Sequencing Data Without Transcriptional Initiation Profiles

Long noncoding RNAs (lncRNAs) play critical regulatory roles in human development and disease. However, many lncRNAs have yet to be annotated. The conventional approach to identifying novel lncRNAs from RNA sequencing (RNA-seq) data is to find transcripts without coding potential. This approach has a false discovery rate of 30-75%. The majority of these misidentified lncRNAs are RNA fragments or transcriptional noise and lack defined transcription start sites, which are marked by H3K4me3 histone modifications. Therefore, the accuracy of lncRNA identification can be improved by incorporating H3K4me3 chromatin immunoprecipitation sequencing (ChIP-seq) data. However, because of cost, time, and limited sample availability, most RNA-seq data lacks such data. This paucity of H3K4me3 data greatly hinders the efforts to accurately identify novel lncRNAs. To address this problem, we have developed software, Flnc, to identify both novel and annotated full-length lncRNAs from RNA-seq data without H3K4me3 profiles. Flnc integrates machine learning models built incorporating four types of features: transcript length, promoter signature, multiple exons, and genomic location. Flnc achieves state-of-the-art prediction power with an AUROC score over 0.92. Flnc significantly improves the prediction accuracy from less than 50% using the conventional approach to over 85%. Flnc is available via https://github.com/CZhouLab/Flnc.

bioinformatics↗

bioRxiv2022

Crystal structure and biochemical analysis suggest that YjoB ATPase is a substrate-specific molecular chaperone

AAA+ ATPases are ubiquitous proteins associated with most cellular processes, including DNA unwinding and protein unfolding. Their functional and structural properties are typically determined by domains and motifs added to the conserved ATPases domain. Currently, the molecular function and structure of many ATPases remain elusive. Here, we report the crystal structure and biochemical analyses of YjoB, a Bacillus subtilis AAA+ protein. The crystal structure revealed that the YjoB hexamer forms a bucket hat-shaped structure with a porous chamber. Biochemical analyses showed that YjoB prevents the aggregation of vegetative catalase KatA and gluconeogenesis-specific glyceraldehyde-3 phosphate dehydrogenase GapB, but not citrate synthase, a conventional substrate. Structural and biochemical analyses further showed that the internal chamber of YjoB is necessary for the chaperone activity. Our results suggest that YjoB, conserved in the class Bacilli, is a molecular chaperone acting in the starvation/stationary phases of B. subtilis growth.

biochemistry↗

bioRxiv2020

A New Form of Decellularized Extracellular Matrix Hydrogel for Treating Ischemic Tissue via Intravascular Infusion

Biomaterials, such as extracellular matrix (ECM) hydrogels, have been widely used in preclinical studies as injectable tissue engineering therapies; however, injectable therapies are limited as they can cause localized trauma or organ perforation. We have developed a new ECM therapy, the low molecular weight fraction derived from decellularized, digested ECM, for intravascular infusion. This new form of ECM can be infused after injury, specifically localize to injured tissues by coating the leaky microvasculature, and promote cell survival and tissue repair. In this study, we show the feasibility and targeting of intravascular ECM infusions using models of acute myocardial infarction (MI), traumatic brain injury, and pulmonary arterial hypertension. Furthermore, safety and efficacy were demonstrated in small and large animal models of acute MI following intracoronary infusion, which included using a clinically-relevant catheter in the large animal model. Functional improvements, specifically reduced left ventricular volumes and improved wall motion scores were observed after ECM infusions post-MI. Genes related to tissue repair and inflammation were differential expressed in response to ECM infusions. This study shows proof-of-concept for a new paradigm of delivering pro-healing ECM biomaterials via intravascular infusion to heal tissue from the inside out.

bioengineering↗

bioRxiv2019

No evidence for disruption of global patterns of nest predation in shorebirds

Kubelka et al. (Science, 9 November 2018, p. 680-683) claim that climate change has disrupted patterns of nest predation in shorebirds. They report that predation rates have increased since the 1950s, especially in the Arctic. We describe methodological problems with their analyses and argue that there is no solid statistical support for their claims.

ecology↗

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

B7-H1(PD-L1) confers chemoresistance through ERK and p38 MAPK pathway in tumor cells

Development of resistance to chemotherapy and immunotherapy is a major obstacle in extending the survival of patients with cancer. Although several molecular mechanisms have been identified that can contribute to chemoresistance, the role of immune checkpoint molecules in tumor chemoresistance remains underestimated. It has been recently observed that overexpression of B7-H1(PD-L1) confers chemoresistance in human cancers, however the underlying mechanisms are unclear. Here we show that the development of chemoresistance depends on the increased activation of ERK pathway in tumor cells overexpressing B7-H1. Conversely, B7-H1 deficiency renders tumor cells susceptible to chemotherapy in a cell-context dependent manner through activation of the p38 MAPK pathway. B7-H1 in tumor cells associates with the catalytic subunit of a DNA-dependent serine / threonine protein kinase (DNA-PKcs). DNA-PKcs is required for the activation of ERK or p38 MAPK in tumors expressing B7-H1, but not in B7-H1 negative or B7-H1 deficient tumors. Ligation of B7-H1 by anti-B7-H1 monoclonal antibody (H1A) increased the sensitivity of human triple negative breast tumor cells to cisplatin therapy in vivo. Our results suggest that B7-H1(PD-L1) expression in cancer cells modifies their chemosensitivity towards certain drugs and targeting B7-H1 intracellular signaling pathway is a new way to overcome cancer chemoresistance.

cancer biology↗