Biology subjects

Ding, J.

Publications and source records attributed to Ding, J..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Activity-Dependent Remodeling of Corticostriatal Axonal Boutons During Motor Learning

Motor skill learning induces long-lasting synaptic plasticity at not only the inputs, such as dendritic spines1-4, but also at the outputs to the striatum of motor cortical neurons5,6. However, very little is known about the activity and structural plasticity of corticostriatal axons during learning in the adult brain. Here, we used longitudinal in vivo two-photon imaging to monitor the activity and structure of thousands of corticostriatal axonal boutons in the dorsolateral striatum in awake mice. We found that learning a new motor skill induces dynamic regulation of axonal boutons. The activities of motor corticostriatal axonal boutons exhibited selectivity for rewarded movements (RM) and un-rewarded movements (UM). Strikingly, boutons on the same axonal branches showed diverse responses during behavior. Motor learning significantly increased the fraction of RM boutons and reduced the heterogeneity of bouton activities. Moreover, motor learning-induced profound structural dynamism in boutons. By combining structural and functional imaging, we identified that newly formed axonal boutons are more likely to exhibit selectivity for RM and are stabilized during motor learning, while UM boutons are selectively eliminated. Our results highlight a novel form of plasticity at corticostriatal axons induced by motor learning, indicating that motor corticostriatal axonal boutons undergo dynamic reorganization that facilitates the acquisition and execution of motor skills.

neuroscience↗

bioRxiv2024

Targeting protein tyrosine phosphatase non-receptor type 2 with a novel inhibitor for AML therapy

Acute myeloid leukemia (AML) is a fatal disease characterized by a bleak prognosis. For over four decades, treatment options for AML have been constrained to administering high-dose cytotoxic chemotherapy. However, the emergence of drug resistance and the resultant toxic side effects have created an urgent necessity for identifying novel therapeutic targets. In this study, non-receptor protein tyrosine phosphatase type 2 (PTPN2) is highly expressed in AML. Remarkably, knock down of PTPN2 expression markedly mitigated AML burden both in vitro and in vivo. Additionally, we unveiled the direct interaction between PTPN2 and C-MYC, establishing C-MYC as a direct acting substrate of PTPN2. Then, we performed a small-molecule compound screening to identify K73, a selective inhibitor of PTPN2. At the same time, K73 showed a good safety profile and exhibited strong activity against AML in vivo. In conclusion, we have pinpointed a considerable therapeutic potential in targeting PTPN2 for AML treatment and discovered a novel class of selective PTPN2 inhibitors suitable for AML therapy.

cancer biology↗

bioRxiv2024

Curved light sheet microscopy for centimeter-scale cleared tissues imaging

Imaging large cleared tissues requires scaling the throughput of imaging techniques. Here we introduce curved light sheet microscope to perform optical sectioning with curved light sheets. This concept addresses the long-standing field curvature problem and lowers the barriers in designing high-throughput objectives. Leveraging a customized objective, the curved light sheet microscope achieves diffraction-limited resolution (1.0 m laterally and 2.5 m axially) and uniform contrast over a field of view of more than 1 x 1 cm2 and is compatible with various tissue clearing techniques. Imaging an entire intact cleared mouse brain at 0.625 x 0.625 x 1.25 m3 voxel size takes less than 3 hours and image tiling is not required. We share full optics description of the objective and report imaging neuronal and vascular networks and tracing brain-wide long-distance axonal projections in intact mouse brains.

bioengineering↗

bioRxiv2024

MtrAB two-component system is crucial for the intrinsic resistance and virulence of Mycobacterium abscessus

Mycobacterium abscessus (Mab) poses serious therapeutic challenges, principally due to its intrinsic resistance to a wide array of antibiotics. The pressing issue of drug resistance has spurred an urgent need to explore novel targets and develop new therapeutic agents against Mab. The MtrAB two-component system, conserved among Actinobacteria, is pivotal for regulating various metabolic processes. Nevertheless, the role of MtrAB in Mab remains elusive. In this study, we uncovered that Mab strains with disrupted mtrA, mtrB or both exhibited heightened susceptibility to a variety of antibiotics with diverse mechanisms of action, in contrast to the wild-type strain. In a murine model, rifabutin, bedaquiline, and amikacin, which were inactive against the wild-type Mab strain, demonstrated efficacy against all the mtrA, mtrB and mtrAB knockout strains, significantly reducing pulmonary bacterial burdens compared to vehicle controls after ten days of treatment. Notably, the virulence of all the mtrA, mtrB, and mtrAB knockout strains was highly diminished in the murine model, as evidenced by a substantial decrease in bacterial load in the lungs of mice after 16 days. We observed that all three knockout strains exhibited a significantly reduced growth rate compared to the wild-type strain. We discovered that cells lacking mtrA, mtrB or both exhibited an elongated cell length and had multiple septa, suggesting that both MtrA and MtrB regulate cell division of Mab. Subsequently, an ethidium bromide accumulation assay disclosed that the absence of either mtrA or mtrB or both significantly increased cell envelope permeability. In summary, this study suggests that mtrA and mtrB play an important role in the intrinsic resistance and virulence of Mab by affecting cell division and altering cell permeability. Consequently, MtrA and MtrB represent promising targets for the discovery of anti-Mab drugs. HIGHLIGHTSO_LIKnockout of mtrA, mtrB or mtrAB leads to increased sensitivity of M. abscessus in vitro and in vivo. C_LIO_LIThe mtrA, mtrB or mtrAB knockout M. abscessus strains exhibit highly reduced virulence. C_LIO_LIMtrA and MtrB are potential targets for anti-M. abscessus drug discovery. C_LIO_LIKnockout of mtrA, mtrB or mtrAB results in defective cell division in M. abscessus. C_LI

microbiology↗

bioRxiv2024

Tonic dendritic GABA release by substantia nigra dopaminergic neurons

Recent studies have implicated dopaminergic signaling within the substantia nigra pars reticulata (SNr) in the emergence of Parkinsonian motor deficits. To better understand the mechanisms underlying this dependence, the ability of dopamine to modulate SNr neuron activity was studied in ex vivo mouse brain slices. In addition to presynaptically inhibiting phasic GABA release, D2 dopamine receptor (D2R) signaling unexpectedly suppressed a tonic, GABAA receptor-mediated inhibition of SNr neuron spiking. Our studies demonstrated that this tonic modulation was largely mediated by GAT-1-dependent GABA release from ALDH1A1-expressing dopaminergic neurons. In contrast, the ability of D2R agonists to disinhibit SNr neurons depended upon D2R-expressing astrocytes and stimulation of GAT-3 uptake of GABA from the extracellular space. In addition to underscoring the importance of dendritically released dopamine in modulating synaptic transmission, our studies demonstrate that dopaminergic modulation of astrocytes plays a key role in modulating SNr circuits and motor behavior. TeaserSNc dopaminergic neurons and astrocytes regulate tonic GABAergic inhibition of SNr neurons.

neuroscience↗

bioRxiv2024

SKP2-mediated FBXO2 proteasomal degradation drives hepatocellular carcinoma progression via stabilizing Hsp47

Accumulating studies highlight that dysregulated E3 ubiquitin ligases are associated with the onset and advancement of cancers. Nevertheless, the impact and mechanism of most E3 ubiquitin ligases on tumorigenesis and tumor metastasis remain poorly understood. Here, we show that loss of FBXO2, an E3 ubiquitin ligase, accelerates hepatocellular carcinoma (HCC) tumor growth and metastasis to the lung through stabilizing heat shock protein 47 (Hsp47). Downregulation of FBXO2, caused by DNA-PKcs-medicated phosphorylation at serine 17 and E3 ligase SKP2-mediated ubiquitination at lysine 79 and subsequent proteasomal degradation, is observed in tumor tissues compared to their parallel non-tumor tissues resected from patients with HCC. Patients whose tumors are enriched for SKP2 or Hsp47 or express low levels of FBXO2 have poor median survival compared to those whose tumors have reversed levels of SKP2, FBXO2 and Hsp47. Together, FBXO2 acts as a tumor suppressor in HCC development. The components of the SKP2-FBXO2-Hsp47 axis provide newly prognostic and therapeutic factors for anti-HCC.

cancer biology↗

bioRxiv2024

Graph Contrastive Learning of Subcellular-resolution Spatial Transcriptomics Improves Cell Type Annotation and Reveals Critical Molecular Pathways

Imaging based spatial transcriptomics (iST), such as MERFISH, CosMx SMI, and Xenium, quantify gene expression level across cells in space, but more importantly, they directly reveal the subcellular distribution of RNA transcripts at the single-molecule resolution. The subcellular localization of RNA molecules plays a crucial role in the compartmentalization-dependent regulation of genes within individual cells. Understanding the intracellular spatial distribution of RNA for a particular cell type thus not only improves the characterization of cell identity but also is of paramount importance in elucidating unique subcellular regulatory mechanisms specific to the cell type. However, current cell type annotation approaches of iST primarily utilize gene expression information while neglecting the spatial distribution of RNAs within cells. In this work, we introduce a semi-supervised graph contrastive learning method called Focus, the first method, to the best of our knowledge, that explicitly models RNAs subcellular distribution and community to improve cell type annotation. Focus first constructs gene neighborhood networks based on the subcellular colocalization relationship of RNA transcripts. Next, the subcellular graph of each cell can be augmented by adding important edges and nodes or removing trivial edges and nodes. Focus then aims to maximize the similarity between positive pairs from two augmented views of the same cell and minimize the similarity between negative pairs from different cells within a common batch. Guided by a limited amount of labeled data, Focus is capable of assigning cell type identities for the entire datasets at high accuracy. Extensive experiments demonstrate the effectiveness of Focus compared to existing state-of-the-art approaches across a range of spatial transcriptomics platforms and biological systems. Furthermore, Focus enjoys the advantages of revealing intricate cell type-specific subcellular spatial gene patterns and providing interpretable subcellular gene analysis, such as defining the gene importance score. Importantly, with the importance score, Focus identifies genes harboring strong relevance to cell type-specific pathways, indicating its potential in uncovering novel regulatory programs across numerous biological systems. Focus is freely accessible at https://github.com/OmicsML/focus.

bioinformatics↗

bioRxiv2024

Establishment of an Inhalation Administration Noninvasive Murine Model for Rapidly Testing Drug Activity against Mycobacterium tuberculosis

The efficacy of many compounds against Mycobacterium tuberculosis is often limited when administered via conventional oral or injection routes due to suboptimal pharmacokinetic characteristics. Inhalation delivery methods have been investigated to achieve high local therapeutic doses in the lungs. However, previous models, typically employing wild-type M. tuberculosis strains, were intricate, time-consuming, labor-intensive, and with poor repeatability. In this study, we developed an autoluminescence-based inhalation administration model to evaluate drug activity by quantifying relative light units (RLUs) emitted from live mice infected with autoluminescent M. tuberculosis. This novel approach has several improvements: it eliminates the need for anesthesia in mice during administration and simplifies the instrument manipulation; it is cost-effective by utilizing mice instead of larger animals; it shortens time from several months to 16 or 17 days for obtaining result; it is non-invasive by measuring the live RLUs of mice; up to six mice can be administrated daily and simultaneously, even 2-3 times/day; results are relatively objective and repeatable minimizing human factors. Proof-of-concept experiments demonstrated that inhalable rifampicin, isoniazid, and ethambutol showed anti-M. tuberculosis activity at concentrations as low as 0.5, 0.5, and 0.625 mg/mL, respectively, as evidenced by comparing the live RLUs of mice. Furthermore, consistency between RLUs and colony-forming units of the lungs reaffirms the reliability of RLUs as an indicator of drug efficacy, highlighting the potential of this approach for accurately assessing anti-M. tuberculosis activity in vivo. This autoluminescence-based and non-invasive inhalation model offers a substantial reduction in the time, effort, and cost required for evaluating the efficacy of screening new drugs and repurposing old drugs in vivo via inhalation administration.

microbiology↗

bioRxiv2024

Enhancing Plant Photosynthesis using Carbon Dots as Light Converter and Photosensitizer

Improving photosynthetic efficiency is pivotal for CO2-based biomanufacturing and agriculture purposes. Despite the progress on photosynthetic biohybrids integrating biocatalysts with synthetic materials, nanomaterials with improved optical and photoelectrochemical properties are still needed to increase the energy-conversion efficiency. Here, we present a novel approach using carbon dots (CDs) as both intracellular photosensitizers and light converters for enhancing solar energy utilization in photosynthetic organisms. The CDs were produced from cyanobacterial biomass and used to convert a broad spectrum of solar irradiation to red light. We demonstrated that the nanosized CDs were incorporated into cyanobacterial cells and transferred light-excited electrons into the photosynthetic electron transfer chain. The biohybrids consisting of the CDs and Synechococcus elongatus exhibited increased growth rates, enhanced activities of both photosystems, and accelerated linear electron transport, compared with the cyanobacterial cells only. The supplementation of the CDs increased CO2-fixation rate and CO2-to-glycerol production by 2.4-fold and 2.2-fold, respectively. Furthermore, the CDs were shown to enhance photosynthesis and promote growth of Arabidopsis thaliana. The fresh weight of plant was increased 1.8-fold by CDs addition. These results reveal that simultaneous photosensitization and spectral modification could substantially improve the efficiency of natural photosynthesis. This study presents CDs as an attractive nanomaterial with great application potential in agriculture and solar-powered biomanufacturing.

synthetic biology↗

bioRxiv2024

Transcriptome-wide quantitative profiling of PUS7-dependent pseudouridylation by nanopore direct long read RNA sequencing

Understanding the interactions between different RNA modifications is essential for unraveling their biological functions. Here, we report NanoPsiPy, a computational pipeline that employs nanopore direct RNA sequencing to identify pseudouridine ({Psi}) sites and quantify their levels at single-nucleotide resolution. We validated NanoPsiPy by transcriptome-wide profiling of PUS7-dependent {Psi} sites in poly-A RNA and rRNA. NanoPsiPy leverages {Psi}-induced U-to-C basecalling errors in nanopore sequencing data, allowing detection of both low and high stoichiometric {Psi} sites. We identified 8,624 PUS7-dependent {Psi} sites in 1,246 mRNAs encoding proteins associated with ribosome biogenesis, translation, and energy metabolism. Importantly, integrative analysis revealed that PUS7 knockdown increases global mRNA N6-methyladenosine (m6A) and 5-methylcytosine (m5C) levels, suggesting an antagonistic relationship between {Psi} and these modifications. Our study underscores the potential of nanopore direct RNA sequencing in revealing the co-regulation of RNA modifications and the capacity of NanoPsiPy in analyzing pseudouridylation and its impact on other RNA modifications.

cancer biology↗

bioRxiv2024

Disrupting Homologous Recombination or Single-Strand Annealing Significantly Hinders CRISPR-Cas12a-Assisted Nonhomologous End-Joining Gene Editing Efficiency in Mycobacterium abscessus

Mycobacterium abscessus, a fast-growing, non-tuberculous mycobacterium resistant to most antimicrobial drugs, causes many types of serious infections in humans, posing a significant public health challenge. Currently, effective genetic manipulation tools for M. abscessus are still being developed, which hampers research and therapeutic development. However, the clustered regularly interspaced short palindromic repeats (CRISPR) - associated protein (Cas) systems have emerged as promising methods for generating highly specific double-strand breaks (DSBs) in its genome. These DSBs can be repaired by the error-prone nonhomologous end joining (NHEJ) mechanism, facilitating targeted gene editing. Here, our study marks a pioneering application of the CRISPR-NHEJ strategy in M. abscessus. Additionally, we discovered that NrgA from Mycobacterium marinum is crucial for the repair of DSBs caused by the CRISPR-Cas system in M. abscessus. Finally, contrary to previous findings, our study also indicates that inhibiting or overexpressing homologous recombination/single-strand annealing significantly decreases the efficiency of NHEJ repair in M. abscessus. This discovery challenges established perspectives and suggests that the NHEJ repair in M. abscessus may require the involvement of components from homologous recombination and single-strand annealing, demonstrating the complex interactions among the three DSB repair pathways in M. abscessus. Impact statementThere are still very few genetic manipulation tools available for Mycobacterium abscessus. Here we report the successful application of CRISPR-Cas12a-assisted nonhomologous end joining (NHEJ) in efficient gene editing in M. abscessus. Contrary to previous research suggesting that homologous recombination (HR) inhibition may enhance such editing efficiency in other Mycobacterium species, our results showed that disruption or overexpression of either HR or single-strand annealing not only failed to enhance but also significantly reduced the gene editing efficiency in M. abscessus. This suggests that NHEJ repair in M. abscessus may require components from both HR and single-strand annealing, highlighting a complex interaction among the DSB repair pathways in M. abscessus.

microbiology↗

bioRxiv2024

MATES: A Deep Learning-Based Model for Locus-specific Quantification of Transposable Elements in Single Cell

Transposable elements (TEs) are crucial for genetic diversity and gene regulation. Current single-cell quantification methods often align multi-mapping reads to either best-mapped or random-mapped locations and categorize them at subfamily levels, overlooking the biological necessity for accurate, locus-specific TE quantification. Moreover, these existing methods are primarily designed for and focused on transcriptomics data, which restricts their adaptability to single-cell data of other modalities. To address these challenges, here we introduce MATES, a deep-learning approach that accurately allocates multi-mapping reads to specific loci of TEs, utilizing context from adjacent read alignments flanking the TE locus. When applied to diverse single-cell omics datasets, MATES shows improved performance over existing methods, enhancing the accuracy of TE quantification and aiding in the identification of marker TEs for identified cell populations. This development facilitates the exploration of single-cell heterogeneity and gene regulation through the lens of TEs, offering an effective transposon quantification tool for the single-cell genomics community.

bioinformatics↗

bioRxiv2023

scHiCyclePred: a deep learning framework for predicting cell cycle phases from single-cell Hi-C data using multi-scale interaction information

While scRNA-seq offers gene expression snapshots, it misses the spatial context of chromatin organization crucial for cell cycle regulation. Single-cell Hi-C, capturing chromatins three-dimensional (3D) architecture, fills this void, revealing interactions between genomic regions that transcript-only data might overlook. We introduce scHiCyclePred, a model that utilizes single-cell Hi-Cs multi-scale interaction data to predict cell cycle phases by extracting chromatins 3D features. This fusion-prediction model integrates three feature sets into a unified vector. Remarkably, scHiCyclePred outperforms methods like NAGANO and CIRCLET and traditional machine learning techniques across various metrics. Our insights into 3D chromatin dynamics during the cell cycle further underscore its utility. By offering a more comprehensive view of cell cycle dynamics through chromatin structure, scHiCyclePred stands to significantly advance our understanding in cellular biology and holds potential to catalyze breakthroughs in disease research. Access scHiCyclePred at github.com/HaoWuLab-Bioinformatics/scHiCyclePred.

bioinformatics↗

bioRxiv2023

The Lateral Ganglionic Eminence Does Not Generate Cortical Oligodendrocytes

The emergence of myelinating oligodendrocytes represents a pivotal developmental milestone in vertebrates, given their capacity to ensheath axons and facilitate the swift conduction of action potentials. It is widely accepted that cortical oligodendrocyte progenitor cells (OPCs) arise from medial ganglionic eminence (MGE), lateral/caudal ganglionic eminence (LGE/CGE) and cortical radial glial cells (RGCs). Here, we used two different fate mapping strategies to challenge the established notion that the LGE generates cortical OPCs. Furthermore, we used a Cre/loxP-dependent exclusion strategy to reveal that the LGE/CGE-derived OPCs are minimal. Additionally, we showed that specifically eliminating MGE-derived OPCs leads to a significant reduction of cortical OPCs. Together, our findings indicate that the contribution of OPCs from LGE/CGE is minimal, contrary to previous beliefs. These findings provide a new view of the developmental origins of cortical OPCs and a valuable foundation for future research on both normal development and oligodendrocyte-related disease.

developmental biology↗

bioRxiv2023

scGeneRythm: Using Neural Networks and Fourier Transformation to Cluster Genes by Time-Frequency Patterns in Single-Cell Data

Clustering genes in single-cell RNA sequencing plays a pivotal role in unraveling a plethora of biological processes, from cell differentiation to disease progression and metabolic pathways. Traditional time-domain methods are instrumental in certain analyses, yet they may overlook intricate relationships. For instance, genes that appear distinct in the time domain might exhibit striking similarities in the frequency domain. Recognizing this, we present scGeneRhythm, an innovative deep learning technique that employs Fourier transformation. This approach captures the rich tapestry of gene expression from both the time and frequency domains. When evaluated across a spectrum of single-cell datasets, scGeneRhythm consistently outperforms conventional approaches. The gene clusters it identifies not only demonstrate heightened statistical significance in enriched pathways but also bring to light underlying gene relationships previously obscured. Through integrating frequency-domain data, scGeneRhythm not only refines gene grouping but also uncovers pivotal biological insights, such as nuanced gene rhythmicity. By deploying scGeneRhythm, we foster a richer, multi-dimensional understanding of gene expression dynamics, enriching the potential avenues of cellular and molecular biology research.

bioinformatics↗

bioRxiv2023

scCross: Bridging Modalities in Single-cell Multi-omics - Seamless Integration, Cross-modal Synthesis, and In-silico Exploration

Single-cell multi-omics illuminate intricate cellular states, yielding transformative insights into cellular dynamics and disease. Yet, while the potential of this technology is vast, the integration of its multifaceted data presents challenges. Some modalities have not reached the robustness or clarity of established scRNA-seq. Coupled with data scarcity for newer modalities and integration intricacies, these challenges limit our ability to maximize single-cell omics benefits. We introduce scCross: a tool adeptly engineered using variational autoencoder, generative adversarial network principles, and the Mutual Nearest Neighbors (MNN) technique for modality alignment. This synergy ensures seamless integration of varied single-cell multi-omics data. Beyond its foundational prowess in multi-omics data integration, scCross excels in single-cell cross-modal data generation, multi-omics data simulation, and profound in-silico cellular perturbations. Armed with these capabilities, scCross is set to transform the field of single-cell research, establishing itself in the nuanced integration, generation, and simulation of complex multi-omics data.

bioinformatics↗

bioRxiv2023

scSniper: Single-cell Deep Neural Network-based Identification of Prominent Biomarkers

Discovering disease biomarkers at the single-cell level is crucial for advancing our understanding of diseases and improving diagnostic accuracy. However, current computational methods often have limitations, such as a reliance on prior knowledge, constraints to unimodal data, and the use of conventional statistical tests for feature selection. To address these issues, we introduce scSniper, a novel approach that employs a specialized deep neural network framework tailored for robust single-cell multiomic biomarker detection. A standout feature of scSniper is the mimetic attention block, enhancing alignment across multi-modal data types. Moreover, scSniper utilizes sensitivity analysis based on a deep neural network for feature selection and uncovers intricate gene regulatory networks without requiring prior knowledge. Comprehensive evaluations on real-world datasets, including COVID-19 CITE-Seq and LUAD scRNA-Seq, demonstrate scSnipers exceptional ability to identify critical biomarkers consistently outperforming traditional methods like MAST, Wilcox, and DESeq2. The scSniper tool and related experimental codes are publicly accessible at https://github.com/mcgilldinglab/scSniper.

bioinformatics↗

bioRxiv2023

Unveiling the Impact of Arsenic Toxicity on Immune Cells in Atherosclerotic Plaques: Insights from Single-Cell Multi-Omics Profiling.

Millions worldwide are exposed to elevated levels of arsenic. This significantly increases their risk of developing atherosclerosis, a pathology primarily driven by immune cells. While the impact of arsenic on immune cell populations in atherosclerotic plaques has been broadly characterized, cellular heterogeneity is a substantial barrier to in-depth examinations of the cellular dynamics for varying immune cell populations. Here, we present one of the first single-cell multi-omics profiling of atherosclerotic plaques in apolipoprotein E knockout (apoE-/-) mice to understand the transcriptomic and epigenetic changes in various immune cells induced by arsenic. Our data reveal that arsenic alters the transcriptional profile of macrophages in a subtype-specific manner with implicated shifts in cell-cell interaction and cell fate predictions. Additionally, our data suggest that arsenic-mediated changes in chromosome accessibility are more profound than their effects on the transcriptome, hence revealing markers of arsenic exposure and potential targets of interventions. TeaserArsenic changes gene expression and epigenome primarily of macrophages in atherosclerotic plaque, suggesting intervention targets.

pharmacology and toxicology↗