Biology subjects

Cui, W.

Publications and source records attributed to Cui, W..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Cholecystokinin input from the anterior cingulate cortex to the lateral periaqueductal gray mediates nocebo pain behavior in mice

The nocebo effect, the evil twin of the better-known placebo effect, in which anticipation of harm worsens pain and other symptoms, is increasingly thought to be responsible for poor clinical outcomes. In humans, nocebo hyperalgesia (i.e., increased pain sensitivity) is blocked by proglumide, a cholecystokinin (CCK) receptor antagonist. Yet, the neural circuitry underlying nocebo hyperalgesia remains unidentified, largely due to a lack of appropriate animal models. Independently, our two laboratories developed unique animal models of CCK-dependent nocebo hyperalgesia in which the expectation of pain was elicited by environmental or social cues. We find that both nocebo paradigms share a neural circuit involving CCK release from neurons projecting from the anterior cingulate cortex to the lateral periaqueductal gray. This previously unrecognized pathway could represent a promising target for therapeutic interventions in pain-related disorders. One-Sentence SummaryPain expectations, whether environmentally conditioned or socially transmitted, are mediated by a shared neural circuit involving cholecystokinin (CCK) projections from the anterior cingulate cortex (ACC) to the lateral periaqueductal gray (PAG).

neuroscience↗

bioRxiv2025

Epidermal Cell Dynamics Regulates Rice Lamina Joint Morphogenesis and Leaf Angle Formation through OsZHD1 and OsZHD2 Regulation

The lamina joint is a critical determinant of leaf angle and crop architecture. While epidermal cells play a fundamental role in organ morphogenesis, influencing the overall shape and function of plants, their impact on lamina joint morphology has been largely overlooked. Here, we tracked the cellular dynamics of the rice lamina joint epidermis during leaf angle formation. We found that the asymmetric elongation between the lateral and medial edges, determined by spatial differences in the longitudinal elongation and number of epidermal cells, was a key factor in leaf angle formation. Mutations in the homeobox genes OsZHD1 and OsZHD2 disrupted the growth patterns of epidermal cells in the lamina joint, resulting in a decreased leaf angle. Restoring OsZHD1 expression in the epidermis reverted the reduced leaf angle phenotype of oszhd1 oszhd2, highlighting the importance of epidermis development for lamina joint morphogenesis. Transcriptome data suggested that OsZHD1 and OsZHD2 were involved in auxin synthesis, which modulates leaf angle by inhibiting the growth of lamina joint epidermal cells. This study underscores the significance of epidermal cells in shaping the lamina joint and elucidates the critical role of OsZHD1 and OsZHD2 in regulating epidermal cell behavior and leaf angle formation.

plant biology↗

bioRxiv2024

scCompass: An integrated cross-species scRNA-seq database for AI-ready

Emerging single-cell sequencing technology has generated large amounts of data, allowing analysis of cellular dynamics and gene regulation at the single-cell resolution. Advances in artificial intelligence enhance life sciences research by delivering critical insights and optimizing data analysis processes. However, inconsistent data processing quality and standards remain to be a major challenge. Here we propose scCompass, which provides a data quality solution to build a large-scale, cross-species and model-friendly single-cell data collection. By applying standardized data pre-processing, scCompass integrates and curates transcriptomic data from 13 species and nearly 105 million single cells. Using this extensive dataset, we are able to archieve stable expression genes (SEGs) and organ-specific expression genes (OSGs) in human and mouse. We provide different scalable datasets that can be easily adapted for AI model training and the pretrained checkpoints with state-of-the-art (SOTA) single-cell foundataion models. In summary, the AI-readiness of scCompass, which combined with user-friendly data sharing, visualization and online analysis, greatly simplifies data access and exploitation for researchers in single cell biology(http://www.bdbe.cn/kun).

bioinformatics↗

bioRxiv2024

Development of a DNA-encoded library screening method DEL Zipper to empower the study of RNA-targeted chemical matter

To date, RNA-targeted chemical matter is under explored due to a lack of robust screening assays. In this study, we present a novel RNA-targeted small molecule screening approach using a specialized DNA-encoded library (DEL). Our findings reveal that the specialized DEL library, called "DEL Zipper", can significantly reduce single-stranded DNA-RNA region interaction signals during various kinds of RNA selection. By performing the selection against both G-quadruplex, we have identified novel hits that interact with RNA targets and the results are validated through binding. This study demonstrates that the "DEL Zipper" method is a robust screening assay that has potential for discovering small molecule ligands for diverse RNA targets.

molecular biology↗

bioRxiv2024

DMRIntTk: integrating different DMR sets based on density peak clustering

BackgroundIdentifying differentially methylated regions (DMRs) is a basic task in DNA methylation analysis. However, due to the different strategies adopted, different DMR sets will be predicted on the same dataset, which poses a challenge in selecting a reliable and comprehensive DMR set for downstream analysis. ResultsHere, we develop DMRIntTk, a toolkit for integrating DMR sets predicted by different methods on a same dataset. In DMRIntTk, the genome is segmented into bins and the reliability of each DMR set at different methylation thresholds is evaluated. Then, the bins are weighted based on the covered DMR sets and integrated into DMRs by using a density peak clustering algorithm. To demonstrate the practicality of DMRIntTk, DMRIntTk was applied to different scenarios, including different tissues with relatively large methylation differences, cancer tissues versus normal tissues with medium methylation differences, and disease tissues versus normal tissues with subtle methylation differences. The results show that DMRIntTk can effectively trim the regions with small methylation differences in the original DMR sets and therefore it can enhance the proportion of DMRs with higher methylation differences. In addition, the overlap analysis suggests that the integrated DMR sets are quite comprehensive, and the functional analysis indicates the integrated disease-related DMR sets are significantly enriched in biological pathways, which are associated with the pathological mechanisms of the diseases. ConclusionsConclusively, DMRIntTk can help researchers obtaining a reliable and comprehensive DMR set from many prediction methods.

bioinformatics↗

bioRxiv2024

SMCHD1 maintains heterochromatin and genome compartments in human myoblasts

Mammalian genomes are subdivided into euchromatic A compartments that contain mostly active chromatin, and inactive, heterochromatic B compartments. However, it is unknown how A and B genome compartments are established and maintained. Here we studied SMCHD1, an SMC-like protein in human male myoblasts. SMCHD1 colocalizes with Lamin B1 and the heterochromatin mark H3K9me3. Loss of SMCHD1 leads to extensive heterochromatin depletion at the nuclear lamina and acquisition of active chromatin states along all chromosomes. In absence of SMCHD1, long range intra-chromosomal and inter-chromosomal contacts between B compartments are lost while many new TADs and loops are formed. Inactivation of SMCHD1 promotes numerous B to A compartment transitions accompanied by activation of silenced genes. SMCHD1 functions as an anchor for heterochromatin domains ensuring that these domains are inaccessible to epigenome modification enzymes that typically operate in active chromatin. Therefore, A compartments are formed by default when not prevented by SMCHD1.

genomics↗

bioRxiv2024

High-resolution chromosome-level genome provides molecular insights into adaptive evolution in crabs

Crabs thrive in diverse ecosystems, from coral reefs to hydrothermal vents and terrestrial habitats. Here, we report a comprehensive genomic analysis of the mud crab using ultralong sequencing technologies, achieving a high-quality chromosome-level assembly. The refined 1.21 Gb genome, with an impressive contig N50 of 11.45 Mb, offers a valuable genomic resource. Gene family analysis shows expansion in development-related pathways and contraction in metabolic pathways, indicating niche adaptations. Notably, Investigation into Hox gene regulation sheds light on their role in pleopod development, with the Abd-A gene identified as a linchpin. Posttranscriptional regulation involving novel-miR1317 negatively regulates Abd-A levels. Furthermore, the fru genes potential role in ovarian development and the identification of novel-miRNA-35 as a regulator of Spfru2 add complexity to gene regulatory networks. Comparative functional analysis across Decapoda species reveals neofunctionalization of the elovl6 gene in the synthesis of long-chain polyunsaturated fatty acids (LC-PUFA), suggesting its importance in environmental adaptation. These findings contribute significantly to our understanding of crab adaptability and evolutionary dynamics, offering a robust foundation for future investigations.

genomics↗

bioRxiv2024

antiCD49d Ab treatment ameliorates age-associated inflammatory response and mitigates CD8 T cell cytotoxicity after traumatic brain injury

Patients aged 65 years and older account for an increasing proportion of patients with traumatic brain injury (TBI). Older TBI patients experience increased morbidity and mortality compared to their younger counterparts. Our prior data demonstrated that by blocking 4 integrin, anti-CD49d antibody (aCD49d Ab) abrogates CD8+ T-cell infiltration into the injured brain, improves survival, and attenuates neurocognitive deficits. Here, we aimed to uncover how aCD49d Ab treatment alters local cellular responses in the aged mouse brain. Consequently, mice incur age-associated toxic cytokine and chemokine responses long-term post-TBI. aCD49d Ab attenuates this response along with a T helper (Th)1/Th17 immunological shift and remediation of overall CD8+ T cell cytotoxicity. Furthermore, aCD49d Ab reduces CD8+ T cells exhibiting higher effector status, leading to reduced clonal expansion in aged, but not young, mouse brains with chronic TBI. Together, aCD49d Ab is a promising therapeutic strategy for treating TBI in the older people. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/596673v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@97311aorg.highwire.dtl.DTLVardef@18a86borg.highwire.dtl.DTLVardef@d9162forg.highwire.dtl.DTLVardef@3f8d06_HPS_FORMAT_FIGEXP M_FIG C_FIG Aged brains after TBI comprise two pools of CD8+ T cells. The aged brain has long been resided by a population of CD8+ T cells thats exhaustive and dysfunctional. Post TBI, due to BBB impairment, functional CD8+ T cells primarily migrate into the brain parenchyma. Aged, injury-associated microglia with upregulated MHC class I molecules can present neoantigens such as neuronal and/or myelin debris in the injured brains to functional CD8+ T, resulting in downstream CD8+ T cell cytotoxicity. aCD49d Ab treatment exerts its function by blocking the migration of functional effector CD8+ T cell population, leading to less cytotoxicity and resulting in improved TBI outcomes in aged mice.

immunology↗

bioRxiv2024

Direcred Micro-Ecology Application System: On-site One-step Fermentation Facilitating Microbial Application through Theoretical and Equipment Innovation

Functional microbial agents play a crucial role in various fields such as agriculture, feed fermentation, aquaculture, and environmental protection. However, traditional microbial agents were confronted with critical challenges such as limited shelf-life, reduced activity, and inconsistent efficacy. In this case, we innovatively proposed the concept of Directed Micro-Ecology (DME) and developed its application system, including a core module named DME intelligent fermentor (DME25). Over 40 functional strains, including bacterial strains and fungus strains, were successfully cultured to 10[~]50 x108 CFU/mL within 20[~]48 h and maintained a relatively low contamination rate (<2.5%). Finally, the stability and effectiveness of these DME-fermented strains were validated in different application areas, all of which exhibited perfect functional characteristics. Firstly, the bacillus strains inhibited the progression of wilt disease and significantly improved the growth of tomatoes. Secondly, all tested lactobacillus strains improved the nutrition and quality of fermented feed, complying with feed industry standards. Lastly, the ammonia nitrogen concentration, nitrite concentration of aquaculture water and phosphate concentration, COD of aquaculture tail water were significantly reduced within 1[~]4 d. The successful application of the DME intelligent fermentor in different fields marks a pivotal breakthrough in technological innovation of microbial agents on-site one-step fermentation. This technological advancement opens new avenues for enhancing the stability and effectiveness of microbial agents, infusing powerful impetus to the development of microbial application.

microbiology↗

bioRxiv2024

mTORC2-mediated cell-cell interaction promote BMP4-induced WNT activation and mesoderm differentiation

The mechanistic target of rapamycin complex 2 (mTORC2) is essential for embryonic development but its underlying molecular mechanisms remain unclear. Here we show that disruption of mTORC2 in human embryonic stem cells (hESCs) considerably alters the Rho/Rac signaling dynamics and reduces cell adhesion. Despite this, mTORC2-deficient hESCs maintain self-renewal and expression of pluripotent markers when cultured in mouse-embryonic fibroblast conditioned medium supplemented with bFGF (MEF-CM). However, these hESCs exhibit significantly impaired mesoderm and endoderm differentiation in response to BMP4 and Activin, respectively, due to reduced WNT activation mediated by cell-cell interactions. Direct activation of the WNT pathway by a GSK3 inhibitor restores mesendoderm differentiation in mTORC2-deficient hESCs. Our study uncovers a novel mechanism by which mTORC2 regulates cell fate determination and highlights a critical link between the intercellular adhesion and the activation of canonical WNT genes.

cell biology↗

bioRxiv2024

Cell-Graph Compass: Modeling Single Cells with Graph Structure Foundation Model

Inspired by the advancements in pre-trained Large Language Models, there has been a surge of studies in the Life Sciences focusing on constructing foundation models with large scale single-cell RNA-seq data. These studies typically involve pre-training a transformer model on large-scale single-cell sequencing data, followed by fine-tuning for a variety of downstream tasks, achieving notable performance. However, these models all share a common short-coming: to utilize the transformer architecture, originally designed for textual data, they artificially impose a sequential structure on genes within cells, simplifying the complex interactions between genes. Furthermore, they focus solely on transcriptomic data, neglecting other relevant biological information. To address these issues, here we introduce Cell-Graph Compass (CGC), the first foundational model that leverages graph structures to model single cells and describes cells from multiple perspectives, including transcriptional profiles, gene text summaries, transcription factor regulatory networks, gene co-expression patterns, and gene positional relationships. By incorporating self-attention mechanisms, we pretrained the model on 50 million human single-cell sequencing data, resulting in a robust digital representation of cells. Extensive downstream experiments demonstrate that our approach can capture meaningful biological knowledge and achieve superior results in various problem scenarios, achieving the state-of-the-art (SOTA).

bioinformatics↗

bioRxiv2024

DeepPrep: An accelerated, scalable, and robust pipeline for neuroimaging preprocessing empowered by deep learning

Neuroimaging has entered the era of big data. However, the advancement of preprocessing pipelines falls behind the rapid expansion of data volume, causing significant computational challenges. Here, we present DeepPrep, a pipeline empowered by deep learning and workflow manager. Evaluated on over 55,000 scans, DeepPrep demonstrates a 11-fold acceleration, exceptional scalability, and robustness compared to the current state-of-the-art pipeline, providing a promising solution to meet the scalability requirements of neuroimaging.

neuroscience↗

bioRxiv2024

Combining machine learning algorithms and single-cell data to study the pathogenesis of Alzheimer's disease

Extracting valuable insights from high-throughput biological data of Alzheimers disease to enhance understanding of its pathogenesis is becoming increasingly important. We engaged in a comprehensive collection and assessment of Alzheimers microarray datasets GSE5281 and GSE122063 and single-cell data from GSE157827 from the NCBI GEO database. The datasets were selected based on stringent screening criteria: a P-value of less than 0.05 and an absolute log fold change (|logFC|) greater than 1. Our methodology involved utilizing machine learning algorithms, efficiently identified characteristic genes. This was followed by an in-depth immune cell infiltration analysis of these genes, gene set enrichment analysis (GSEA) to elucidate differential pathways, and exploration of regulatory networks. Subsequently, we applied the Connectivity Map (cMap) approach for drug prediction and undertook single-cell expression analysis. The outcomes revealed that the top four characteristic genes, selected based on their accuracy, exhibited a profound correlation with the Alzheimers disease (AD) group in terms of immune infiltration levels and pathways. These genes also showed significant associations with multiple AD-related genes, enhancing the potential pathogenic mechanisms through regulatory network analysis and single-cell expression profiling. Identified three subpopulations of astrocytes in late-stage of AD Prefrontal cortex dataset. Discovering dysregulation of the expression of the AD disease-related pathway maf/nrf2 in these cell subpopulations Ultimately, we identified a potential therapeutic drug score, offering promising avenues for future Alzheimers disease treatment strategies.

bioinformatics↗

bioRxiv2024

Individual connectivity-based parcellations reflect functional properties of human auditory cortex

Neuroimaging studies of the functional organization of human auditory cortex have focused on group-level analyses to identify tendencies that represent the typical brain. Here, we mapped auditory areas of the human superior temporal cortex (STC) in 30 participants by combining functional network analysis and 1-mm isotropic resolution 7T functional magnetic resonance imaging (fMRI). Two resting-state fMRI sessions, and one or two auditory and audiovisual speech localizer sessions, were collected on 3-4 separate days. We generated a set of functional network-based parcellations from these data. Solutions with 4, 6, and 11 networks were selected for closer examination based on local maxima of Dice and Silhouette values. The resulting parcellation of auditory cortices showed high intraindividual reproducibility both between resting state sessions (Dice coefficient: 69-78%) and between resting state and task sessions (Dice coefficient: 62-73%). This demonstrates that auditory areas in STC can be reliably segmented into functional subareas. The interindividual variability was significantly larger than intraindividual variability (Dice coefficient: 57%-68%, p<0.001), indicating that the parcellations also captured meaningful interindividual variability. The individual-specific parcellations yielded the highest alignment with task response topographies, suggesting that individual variability in parcellations reflects individual variability in auditory function. Connectional homogeneity within networks was also highest for the individual-specific parcellations. Furthermore, the similarity in the functional parcellations was not explainable by the similarity of macroanatomical properties of auditory cortex. Our findings suggest that individual-level parcellations capture meaningful idiosyncrasies in auditory cortex organization.

neuroscience↗

bioRxiv2024

Prediction of Post Traumatic Epilepsy using MRI-based Imaging Markers

Post-traumatic Epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic brain injury (TBI). Despite the high prevalence of PTE, current methods for predicting its occurrence remain limited. In this study, we aimed to identify imaging-based markers for the prediction of PTE using machine learning. Specifically, we examined three imaging features: lesion volumes and resting-state fMRI-based measures of functional connectivity and amplitude of low-frequency fluctuation (ALFF). We employed three machine learning methods, namely, kernel support vector machine (KSVM), random forest, and a neural network, to develop predictive models. Our results showed that the KSVM classifier, with all three feature types as input, achieved the best prediction accuracy of 0.78 AUC (Area Under the Receiver Operating Characteristic (ROC) curve) using nested cross-validation. Furthermore, we performed voxel-wise and lobe-wise group difference analyses to investigate the specific brain regions and features that the model found to be most helpful in distinguishing PTE from non-PTE populations. Our statistical analysis uncovered significant differences in bilateral temporal lobes and cerebellum between PTE and non-PTE groups. Overall, our findings demonstrate the complementary prognostic value of MR-based markers in PTE prediction and provide new insights into the underlying structural and functional alterations associated with PTE.

neuroscience↗

bioRxiv2023

GeneCompass: Deciphering Universal Gene Regulatory Mechanisms with Knowledge-Informed Cross-Species Foundation Model

Deciphering the universal gene regulatory mechanisms in diverse organisms holds great potential to advance our knowledge of fundamental life process and facilitate research on clinical applications. However, the traditional research paradigm primarily focuses on individual model organisms, resulting in limited collection and integration of complex features on various cell types across species. Recent breakthroughs in single-cell sequencing and advancements in deep learning techniques present an unprecedented opportunity to tackle this challenge. In this study, we developed GeneCompass, the first knowledge-informed, cross-species foundation model pre-trained on an extensive dataset of over 120 million single-cell transcriptomes from human and mouse. During pre-training, GeneCompass effectively integrates four types of biological prior knowledge to enhance the understanding of gene regulatory mechanisms in a self-supervised manner. Fine-tuning towards multiple downstream tasks, GeneCompass outperforms competing state-of-the-art models in multiple tasks on single species and unlocks new realms of cross-species biological investigation. Overall, GeneCompass marks a milestone in advancing knowledge of universal gene regulatory mechanisms and accelerating the discovery of key cell fate regulators and candidate targets for drug development.

bioinformatics↗

bioRxiv2023

CellPolaris: Decoding Cell Fate through Generalization Transfer Learning of Gene Regulatory Networks

Cell fate changes are determined by gene regulatory network (GRN), a sophisticated system regulating gene expression in precise spatial and temporal patterns. However, existing methods for reconstructing GRNs suffer from inherent limitations, leading to compromised accuracy and application generalizability. In this study, we introduce CellPolaris, a computational system that leverages transfer learning algorithms to generate high-quality, cell-type-specific GRNs. Diverging from conventional GRN inference models, which heavily rely on integrating epigenomic data with transcriptomic information or adopt causal strategies through gene co-expression networks, CellPolaris employs high-confidence GRN sources for model training, relying exclusively on transcriptomic data to generate previously unknown cell-type-specific GRNs. Applications of CellPolaris demonstrate remarkable efficacy in predicting master regulatory factors and simulating in-silico perturbations of transcription factors during cell fate transition, attaining state-of-the-art performance in accurately predicting candidate key factors and outcomes in cell reprogramming and spermatogenesis with validated datasets. It is worth noting that, with a transfer learning framework, CellPolaris can perform GRN based predictions in all cell types even across species. Together, CellPolaris represents a significant advancement in deciphering the mechanisms of cell fate regulation, thereby enhancing the precision and efficiency of cell fate manipulation at high resolution.

bioinformatics↗

bioRxiv2023

CD36-Pyruvate Kinase M2 Signaling Promotes Macrophage Phagocytosis Through Mitochondrial Reactive Oxygen Species

Macrophage efferocytosis, the process by which phagocytes engulf and remove apoptotic cells (ACs), plays a critical role in maintaining tissue homeostasis. Efficient efferocytosis prevents secondary necrosis, mitigates chronic inflammation, and impedes atherosclerosis progression. However, the regulatory mechanisms of efferocytosis under atherogenic conditions remain poorly understood. We previously demonstrated that oxidized LDL (oxLDL), an atherogenic lipoprotein, induces mitochondrial reactive oxygen species (mtROS) in macrophages via CD36. In this study, we demonstrate that macrophage mtROS facilitate continual efferocytosis through a positive feedback mechanism. However, oxLDL disrupts continual efferocytosis by dysregulating the internalization of ACs. This disruption is mediated by an overproduction of mtROS. Mechanistically, oxLDL/CD36 signaling promotes the translocation of cytosolic PKM2 to mitochondria, facilitated by the chaperone GRP75. Mitochondrial PKM2 then binds to Complex III of the electron transport chain, inducing mtROS production. This study elucidates a novel regulatory mechanism of efferocytosis in atherosclerosis, providing potential therapeutic targets for intervention. SUMMARYMacrophages clear apoptotic cells through a process called efferocytosis, which involves mitochondrial ROS. However, the atherogenic oxidized LDL overstimulates mitochondrial ROS via the CD36-PKM2 pathway, disrupting continual efferocytosis. This finding elucidates a novel molecular mechanism that explains defects in efferocytosis, driving atherosclerosis progression.

immunology↗