Biology subjects

Dong, K.

Publications and source records attributed to Dong, K..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Insights into the Absence of Lymphoma Despite Fulminant Epstein-Barr Virus Infection in Patients with XIAP Deficiency

X-linked Lymphoproliferative Syndromes (XLP), which arise from mutations in the SH2D1A or XIAP genes, are characterized by the inability to control Epstein-Barr Virus (EBV) infection. While primary EBV infection triggers severe diseases in each, lymphomas occur at high rates with XLP-1 but not with XLP-2. Why XLP-2 patients are apparently protected from EBV-driven lymphomagenesis, in contrast to all other described congenital conditions that result in heightened susceptibility to EBV, remains a key open question. To gain insights, we cross-compared newly EBV infected versus immune stimulated B-cells from XLP-2 patients or upon XIAP CRISPR knockout, relative to healthy controls. XIAP perturbation impeded outgrowth of newly EBV-infected primary human B-cells, though had no impact on proliferation of B-cells stimulated by CD40 ligand and interleukin-21 or upon established EBV-immortalized lymphoblastoid cell lines (LCLs). B-cells from XLP-2 patients or in which XIAP was depleted by CRISPR editing exhibited a markedly lower EBV transformation efficiency than healthy control B-cells. Mechanistically, nascent EBV infection activated p53-mediated apoptosis signaling, whose effects on transforming B-cell death were counteracted by XIAP. In the absence of XIAP, EBV infection triggered high rates of apoptosis, not seen with CD40L/IL-21 stimulation. Moreover, inflammatory cytokines are present at high levels in XLP-2 patient serum with fulminant EBV infection, which heightened apoptosis induction in newly EBV-infected cells. These findings highlight the crucial role of XIAP in supporting early stages of EBV-driven B-cell immortalization and provide insights into the absence of EBV+ lymphoma in XLP-2 patients. Key pointsO_LIXIAP loss-of-function markedly impairs EBV+ B-cells outgrowth over the first week post-infection, particularly in the presence of IFN-{gamma}. C_LIO_LIXIAP mutation impedes EBV-driven B-cell transformation by potentiating p53-driven caspase activation and apoptosis. C_LI

microbiology↗

bioRxiv2025

Dose-dependent sensitivity of human 3D chromatin to a heart disease-linked transcription factor

Dosage-sensitive transcription factors (TFs) underlie altered gene regulation in human developmental disorders, and cell-type specific gene regulation is linked to the reorganization of 3D chromatin during cellular differentiation. Here, we show dose-dependent regulation of chromatin organization by the congenital heart disease (CHD)- linked, lineage-restricted TF TBX5 in human cardiomyocyte differentiation. Genome organization, including compartments, topologically associated domains, and chromatin loops, are sensitive to reduced TBX5 dosage in a human model of CHD, with variations in response across individual cells. Regions normally bound by TBX5 are especially sensitive, while co-occupancy with CTCF partially protects TBX5-bound TAD boundaries and loop anchors. These results highlight the importance of lineage-restricted TF dosage in cell-type specific 3D chromatin dynamics, suggesting a new mechanism for TF-dependent disease.

genomics↗

bioRxiv2025

High-precision cell-type mapping and annotation of single-cell spatial transcriptomics with STAMapper

Recent advances in single-cell spatial transcriptomics (scST) have enabled the analysis of gene transcription levels in individual cells while preserving their spatial positions. Cell-type mapping and annotation are crucial in understanding the complex interactions between cells and their microenvironments within a spatial context. To this end, we develop a heterogeneous graph neural network, STAMapper, to transfer the cell-type labels from single-cell RNA-seq data to scST data. STAMapper captures both the expression similarity among cells and the expression relationships between cells and genes and adopts a graph attention classifier to conduct semi-supervised learning for more accurate cell-type prediction. We collected 81 scST datasets consisting of 344 slices and 16 paired scRNA-seq datasets from eight technologies and five tissues to validate the efficiency of STAMapper. STAMapper achieved the best performance on 75 out of 81 datasets compared to competing methods in accuracy. STAMapper demonstrated enhanced performance over manual annotations, particularly at the boundaries of cell clusters, enabled the unknown cell-type detection in scST data, and exhibited precise cell subtype annotations. Additionally, STAMapper provided biologically meaningful gene embeddings, facilitating the identification of shared or unique gene modules across datasets.

bioinformatics↗

bioRxiv2025

GENETIC ANALYSIS OF ARABIDOPSIS AUTOPHAGY-RELATED 8 FAMILY PROTEINS REVEALS THEIR REDUNDANT AND REGULATORY ROLES IN PLANT AUTOPHAGY

Autophagy, a critical process for the vacuolar degradation of proteins and organelles, is governed by multiple conserved autophagy-related (ATG) proteins. The central component of the ATG machinery is the ubiquitin-like protein ATG8, which is essential for multiple steps of the autophagy process, including phagophore expansion, autophagosome closure, trafficking and fusion with the lysosome/vacuole, and selective cargo recruitment. Currently, our understanding of the roles of ATG8 in plant autophagy and the functional specialization of ATG8 family members is limited due to genetic redundancy. To assess the roles of ATG8 genes in plant autophagy, here we used CRISPR/Cas9 technology to systematically knockout the Arabidopsis ATG8 genes. By analyzing the atg8 mutants, we found that in contrast to mammalian ATG8s, in which the LC3s and GABARAP subfamilies play distinct roles in the autophagic process, Arabidopsis ATG8s perform an overlapping function in controlling autophagic flux. Combinatorial mutations of Clade I and Clade II ATG8s resulted in severely impaired autophagy under nutrient-starved conditions. Furthermore, we found that RABG3 proteins, members of the RAB7/RABG GTPase family, interact with ATG8s through AIM-LDS interfaces, and that such interaction is essential for the association of RABG3 proteins with the autophagosomal membrane and probably for the fusion of autophagosome with the vacuole, but is not required for endosomal trafficking. With the collection of multiple high-order atg8 mutants generated in this study, we now provide a venue to study the roles of ATG8 genes in canonical autophagy and non-canonical autophagy in Arabidopsis.

plant biology↗

bioRxiv2024

Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina

Most genetic risk variants linked to ocular diseases are non-protein coding and presumably contribute to disease through dysregulation of gene expression, however, deeper understanding of their mechanisms of action has been impeded by an incomplete annotation of the transcriptional regulatory elements across different retinal cell types. To address this knowledge gap, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome and 3D chromatin architecture in human retina, macula, and retinal pigment epithelium (RPE)/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 sub-classes of retinal cells. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the rapid advancements in deep-learning techniques, we developed sequence-based predictors to interpret non-coding risk variants of retina diseases. Our study establishes retina-wide, single-cell transcriptome, epigenome, and 3D genome atlases, and provides a resource for studying the gene regulatory programs of the human retina and relevant diseases.

genomics↗

bioRxiv2024

Causal disentanglement for single-cell representations and controllable counterfactual generation

Conducting disentanglement learning on single-cell omics data offers a promising alternative to traditional black-box representation learning by separating the semantic concepts embedded in a biological process. We present CausCell, which incorporates the causal relationships among disentangled concepts within a diffusion model to perform disentanglement learning, with the aim of increasing the explainability, generalizability and controllability of single-cell data, including spatial and temporal omics data, relative to those of the existing black-box representation learning models. Two quantitative evaluation scenarios, i.e., disentanglement and reconstruction, are presented to conduct the first comprehensive single-cell disentanglement learning benchmark, which demonstrates that CausCell outperforms the state-of-the-art methods in both scenarios. Additionally, CausCell can implement controllable generation by intervening with the concepts of single-cell data when given a causal structure. It also has the potential to uncover biological insights by generating counterfactuals from small and noisy single-cell datasets.

bioinformatics↗

bioRxiv2024

PITHD1: An Endogenous Inhibitor of the 26S Proteasome During Cellular Dormancy

Cellular dormancy represents a state of regulated growth arrest essential for diverse biological processes, from reproduction to cancer progression. While mechanisms controlling protein synthesis in dormant cells have been identified, how cells regulate protein degradation during dormancy remains unclear. Using zebrafish oocytes, eggs and embryos as a model system, we discovered PITHD1 as an endogenous inhibitor of the 26S proteasome. Our high-resolution cryoEM structure reveals that PITHD1 simultaneously blocks three crucial functional sites on the 19S regulatory particle which are required for ubiquitin recognition, processing, and substrate translocation. This triple-lock mechanism effectively prevents protein degradation in dormant cells. Given PITHD1s evolutionary conservation across species, this mechanism likely represents a general strategy for reversible proteasome regulation during cellular dormancy. Our findings establish a new paradigm for controlling proteostasis in quiescent states.

biochemistry↗

bioRxiv2024

Generation of a novel constitutive smooth muscle cell-specific Myh11-driven Cre mouse model

Dysfunction in either embryonic or postnatal vascular smooth muscle cells (SMCs) significantly contributes to the progression of various cardiovascular diseases. Therefore, elucidating the molecular mechanisms governing VSMC development and homeostasis is crucial. MYH11 is the most reliable lineage gene for SMCs and has been utilized to develop tamoxifen-inducible Cre driver lines for achieving SMC-specific gene manipulation by crossing with mice carrying the loxP-flanked gene, particularly in adult mice. For studies involving SMCs during embryogenesis, the commonly used constitutive Cre driver is controlled by the Tagln (Sm22) promoter. However, this Cre driver exhibits activity in multiple non-SMC populations, including cardiomyocytes and skeletal muscle precursors, introducing confounding effects. Additionally, most existing SMC-specific Cre drivers are generated using a transgenic approach, raising concerns about random site integration and variable gene copy numbers. To address these limitations, we report a novel Cre mouse model generated by knock-in (KI) of a nuclear-localized Cre recombinase into the Myh11 gene locus using homologous recombination. We confirmed that the Cre activity precisely recapitulates endogenous Myh11 expression by crossing with Rosa26 mTmG or tdTomato reporter mice. Moreover, Myh11-driven Cre can efficiently delete the floxed allele of the transcription factor Tead1 specifically in SMCs. The Tead1 SMC-specific knockout mice did not exhibit an overt phenotype, thereby circumventing the embryonic lethal phenotype mediated by Tagln-driven Cre, as we previously reported. These findings establish this novel Cre driver line as a robust tool for tracing the Myh11-positive SMC lineage and manipulating gene function specifically in SMCs during embryonic development in mice.

genetics↗

bioRxiv2024

Structural landscape of AAA+ ATPase motor states in the substrate-degrading human 26S proteasome reveals conformation-specific binding of TXNL1

The 26S proteasome targets many cellular proteins for degradation during general homeostasis, protein quality control, and the regulation of vital processes. A broad range of proteasome-interacting cofactors thereby modulates these functions and aids in substrate degradation. Here, we solved several high-resolution structures of the redox active cofactor TXNL1 bound to the human 26S proteasome at saturating and sub-stoichiometric concentrations by time resolved cryo-EM. We identified distinct binding modes of TXNL1 that depend on the proteasome conformational and ATPase motor states. Together with biophysical and biochemical experiments, our structural studies reveal that the resting-state proteasome prior to substrate engagement with the ATPase motor binds TXNL1 with low affinity and in variable positions on top of the Rpn11 deubiquitinase. In contrast, the actively degrading proteasome shows additional interactions leading to high-affinity TXNL1 binding, whereby TXNL1s C-terminal tail covers the catalytic groove of the Rpn11 deubiquitinase and coordinates the active-site Zn2+. Furthermore, these cryo-EM structures of the degrading proteasome capture the ATPase hexamer in all registers of spiral-staircase arrangements and thus visualize the complete ATP-hydrolysis cycle of the AAA+ motor, indicating temporally asymmetric hydrolysis and conformational changes in bursts during mechanical substrate unfolding and translocation. Remarkably, we catch the proteasome in the act of unfolding the beta-barrel mEos3.2 substrate while the ATPase hexamer is in a particular spiral staircase register. Our findings challenge current models for protein translocation through hexameric AAA+ motors and reveal how the proteasome uses its distinct but broad range of conformational states to coordinate cofactor binding and substrate processing. HighlightsO_LIHigh resolution structures of the redox active cofactor TXNL1 in complex with the human 26S proteasome solved by time-resolved cryo-EM. C_LIO_LITXNL1 binds the catalytic groove of the main proteasomal deubiquitinase Rpn11 and coordinates its active-site Zinc specifically in substrate-degrading states of the proteasome. C_LIO_LIVisualizing a partially unfolded intermediate of the mEos model substrate during processing. C_LIO_LIStructures of the actively degrading human proteasome reveal all spiral-staircase registers of the AAA+ ATPase hexamer with unexpected nucleotide occupancies that indicate asymmetric ATP hydrolysis mechanisms, conformational changes with burst phases, and thus new models for hand-over-hand substrate translocation. C_LI

biochemistry↗

bioRxiv2024

IGF2 mediates Hippo signaling to control liver size

The Hippo pathway is a central mechanism in organ size control, but the mediator for its function remains elusive. Here, we show that the expression of insulin-like growth factor II (IGF2) is directly induced by YAP/TAZ transcription cofactors of the Hippo pathway in a developmental stage- and cell type-specific manner. In mouse livers, Igf2 expression is sustained by YAP/TAZ in hepatoblasts and immature hepatocytes at fetal and neonatal stages, coupling with rapid cell proliferation and liver size expansion, whereas turned off in matured hepatocytes following YAP/TAZ inactivation to prevent liver overgrowth. In contrast, YAP/TAZ fails to regulate Igf2 expression in cholangiocytes and diverse liver mesenchymal cells where epigenetic barriers, including DNA and histone methylation, are implanted near Igf2 promoters. Furthermore, IGF2 activates IGF1R signaling and promotes normal and neoplastic liver growth, while the inactivation of IGF2 or IGF1R effectively blocks YAP/TAZ-induced hepatomegaly and hepatoblastoma. In conclusion, our findings reveal that IGF2 is a bona fide mediator of the Hippo pathway, indicating a fundamental role of the Hippo-IGF2-IGF1R signaling axis in organ size regulation and malignancies.

cell biology↗

bioRxiv2024

Epigenetic and 3D genome reprogramming during the aging of human hippocampus

Age-related cognitive decline is associated with altered physiology of the hippocampus. While changes in gene expression have been observed in aging brain, the regulatory mechanisms underlying these changes remain underexplored. We generated single-nucleus gene expression, chromatin accessibility, DNA methylation, and 3D genome data from 40 human hippocampal tissues spanning adult lifespan. We observed a striking loss of astrocytes, OPC, and endothelial cells during aging, including astrocytes that play a role in regulating synapses. Microglia undergo a dramatic switch from a homeostatic state to a primed inflammatory state through DNA methylome and 3D genome reprogramming. Aged cells experience erosion of their 3D genome architecture. Our study identifies age-associated changes in cell types/states and gene regulatory features that provide insight into cognitive decline during human aging.

genomics↗

bioRxiv2024

Shape transformation of vesicles induced by orientational arrangement of membrane proteins

Vesicles of lipid bilayer can adopt a variety of shapes due to different coating proteins. The ability of proteins to reshape membrane is typically characterized by inducing spontaneous curvature of the membrane at the coated area. BAR family proteins are known to have a crescent shape and can induce membrane curvature along its concaved body axis but not in the perpendicular direction. We model this type of proteins as a rod-shaped molecule with an orientation and induce normal curvature along its orientation in the tangential plane of the membrane surface. We show how a ring of these proteins reshape an axisymmetric vesicle when the protein curvature or orientation is varied. A discontinuous shape transformation from a protrusion shape without a neck to a one with a neck is found. Increasing the rigidity of the protein ring is able to smooth out the transition. Furthermore, we show that varying the protein orientation is able to induce an hourglass-shaped neck, which is significantly narrower than the reciprocal of the protein curvature. Our results offer a new angle to rationalize the helical structure formed by many proteins that carry out membrane fission functions.

biophysics↗

bioRxiv2024

Episodic Transport of Protein Aggregates Achieves a Positive Size Selectivity in Aggresome Formation

Eukaryotic cells direct toxic misfolded proteins to various protein quality control pathways based on their chemical features and aggregation status. Aggregated proteins are targeted to selective autophagy or specifically sequestered into the "aggresome," a perinuclear inclusion at the microtubule-organizing center (MTOC). However, the mechanism for selectively sequestering protein aggregates into the aggresome remains unclear. To investigate aggresome formation, we reconstituted MTOC-directed aggregate transport in Xenopus laevis egg extract using AgDD, a chemically inducible aggregation system. High-resolution single-particle tracking revealed that dynein-mediated transport of aggregates was highly episodic, with average velocity positively correlated with aggregate size. Our mechanistic model suggests that the recurrent formation of the dynein transport complex biases larger aggregates towards the active transport state, compensating for the slowdown due to viscosity. Both episodic transport and positive size selectivity are specifically associated with aggresome-dynein adaptors. Coupling conventional dynein-activating adaptors to the aggregates perturbs aggresome formation and reverses size selectivity.

cell biology↗

bioRxiv2024

Uncovering topologically associating domains from three-dimensional genome maps with TADGATE

Topologically associating domains (TADs) emerge as indispensable units in three-dimensional (3D) genome organization, playing a critical role in gene regulation. However, accurately identifying TADs from sparse chromatin contact maps and exploring the structural and functional elements within TADs remain challenging. To this end, we develop a graph attention auto-encoder, TADGATE, to accurately identify TADs even from ultra-sparse contact maps and generate the imputed maps while preserving or enhancing the underlying topological structures. TADGATE can capture specific attention patterns, pointing to two types of units with different characteristics in TADs. Moreover, we find that the organization of TADs is closely associated with chromatin compartmentalization, and TAD boundaries in different compartmental environments exhibit distinct biological properties. We also utilize a two-layer Hidden Markov Model to functionally annotate the TADs and their internal regions, revealing the overall properties of TADs and the distribution of the structural and functional elements within TADs. At last, we apply TADGATE to highly sparse and noisy Hi-C contact maps from 21 human tissues or cell lines, enhancing the clarity of TAD structures, investigating the nature of conserved and cell type-specific boundaries, and unveiling the cell type-specific transcriptional regulatory mechanisms associated with topological domains.

bioinformatics↗

bioRxiv2024

A domain-swapped CaMKII conformation facilitates linker-mediated allosteric regulation

Memory formation, fertilization, and cardiac function rely on precise Ca2+ signaling and subsequent Ca2+/calmodulin-dependent protein kinase II (CaMKII) activation. Ca2+ sensitivity of the four CaMKII paralogs in mammals has been linked to the length of the variable linker region that is a hot spot for alternative splicing. In this study, we determined that the position of charged residues within the linker modulates the Ca2+/CaM sensitivity. We present an X-ray crystal structure of the full-length CaMKII{delta} holoenzyme consisting of domain-swapped dimers within a dodecameric complex. In this structure, the kinase domain of one subunit is docked onto the hub domain of an adjacent subunit, providing an additional interface within the holoenzyme. Mutations at the hub equatorial and lateral interfaces led to alterations in the stoichiometry of CaMKII holoenzyme as well as Ca2+/CaM sensitivity. Using molecular dynamics (MD) to compare domain-swapped to non-domain-swapped CaMKIIs, we demonstrate that the domain-swapped conformation facilitates an interaction between the calmodulin binding region and the linker region. Based on MD simulations and small-angle X-ray scattering (SAXS) measurements, we propose a model where the position of charges on the linker region drives an interaction with the regulatory segment that modulates the degree of autoinhibition. Finally, we use live-cell imaging to show that the activation profiles we observe in vitro are recapitulated in cells. Our findings provide a new framework for understanding allosteric regulation of CaMKII by the linker region in Ca2+-sensitive cells.

biochemistry↗

bioRxiv2024

Deep Learning Behavioral Phenotyping System in the Diagnosis of Parkinson's Disease with Drosophila melanogaster

Drosophila Melanogaster is widely used as animal models for Parkinsons disease (PD) research. Because of the complexity of MoCap and quantitative assessment among Drosophila Melanogaster, however, there is a technical issue that identify PD symptoms within drosophila based on objective spontaneous behavioral characteristics. Here, we developed a deep learning framework generated from kinematic features of body posture and motion between wildtype and SNCAE46K mutant drosophila genetically modeled {square}-Syn, supporting clustering and classification of PD individuals. We record locomotor activity in a 3D-printed trap, and utilize the pre-analysis pose estimation software DeepLabCut (DLC) to calculate and generate numerical data representing the motion speed, tremor frequency, and limb motion of Drosophila Melanogaster. By plugging these data as the input, the diagnosis result (1/0) representing PD or WT as the output. Our result provides a toolbox which would be valuable in the investigation of PD progressing and pharmacotherapeutic drug development.

neuroscience↗

bioRxiv2024

Prevalence and preferred niche of small eukaryotes with mixotrophic potentials in the global ocean

Unicellular eukaryotes that are capable of phago-mixotrophy in the ocean compete for inorganic nutrients and light with autotrophs, and for bacterial prey with heterotrophs. In this study, we ask what are the overall prevalence of eukaryotic mixotrophs in vast open oceans, and how the availability of inorganic nutrients, light, and prey affects their relative success. We utilized the Tara Oceans eukaryotic 18S rRNA gene and environmental context variables dataset to conduct large-scale field analysis. We also performed isolate-based culture experiments to verify growth and nutritional resource relationships for representative mixotrophic taxa. The field analysis suggested that the overall prevalence of mixotrophs was negatively correlated with nutrient concentrations and positively associated with light availability. Concentrations of bacterial prey also presented somewhat correlation with mixotrophs but to a less extent. In comparison, the culture experiments demonstrated a taxa-specific relationship between mixotrophic growth and nutrition resources, i.e., the growth of one group was significantly dependent on light availability while the other group was less affected by light when they received sufficient prey. Both groups were capable of growing efficiently with low inorganic nutrients when receiving sufficient prey and light. Therefore, our field analysis and culture experiments both suggest that phago-mixotrophy for ocean eukaryotes is seemingly to be an efficient strategy to compensate nutrient deficiency but unnecessarily light limitation. This study collectively revealed a close relationship between abiotic and biotic nutritional resources and the prevalence of trophic strategies, shedding light on the importance of light and nutrients for determining the competitive success of mixotrophs versus autotrophic and heterotrophic eukaryotes in the ocean.

microbiology↗

bioRxiv2024

Toward subtask decomposition-based learning and benchmarking for genetic perturbation outcome prediction and beyond

Deciphering cellular responses to genetic perturbations is fundamental for a wide array of biomedical applications, ranging from uncovering gene roles and interactions to unraveling effective therapeutics. Accurately predicting the transcriptional outcomes of genetic perturbations is indispensable for optimizing experimental perturbations and deciphering cellular response mechanisms; however, three scenarios present principal challenges, i.e., predicting single genetic perturbation outcomes, predicting multiple genetic perturbation outcomes and predicting genetic outcomes across cell lines. In this study, we introduce SubTAsk decomposition Modeling for genetic Perturbation prediction (STAMP), a conceptually novel computational strategy for genetic perturbation outcome prediction and downstream applications. STAMP innovatively formulates genetic perturbation prediction as a subtask decomposition (STD) problem by resolving three progressive subtasks in a divide-and-conquer manner, i.e., identifying differentially expressed gene (DEG) postperturbations, determining the regulatory directions of DEGs and finally estimating the magnitudes of gene expression changes. In addition to facilitating perturbation prediction, STAMP also serves as a robust and generalizable benchmark guide for evaluating various genetic perturbation prediction models. As a result, STAMP exhibits a substantial improvement in terms of its genetic perturbation prediction ability over the existing approaches on three subtasks and beyond, including revealing the ability to identify key regulatory genes and pathways on small samples and to reveal precise genetic interactions. Overall, STAMP serves as a fundamentally novel and effective prediction and generalizable benchmarking strategy that can facilitate genetic perturbation prediction, guide the design of perturbation experiments, and broaden the understanding of perturbation mechanisms.

bioinformatics↗