Biology subjects

Bai, D.

Publications and source records attributed to Bai, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Determining cellular phylogeny and migration at high resolution in spatial genomics

Cellular migration and tumor evolution are central to tissue homeostasis and cancer biology. Rapid advances in spatial genomics have raised the possibility of using somatic mutations to track these processes in situ in human tissues. However, frequent data dropouts in spatial genomics measurements make this challenging to implement. Here, we present StarTrak (SpaTial Analysis for lineage ReconsTRuction with somatic vAriant calling and tracKing), a framework for somatic variant calling and lineage reconstruction at single-pixel spatial resolution. StarTrak employs a neural network framework to integrate mutational evidence (from both nuclear and mitochondrial reads), spatial proximity, histological images, and transcriptomic states to identify spatially informative patterns of mutations. It performs robustly across tissue types and spatial-omics platforms (being particularly successful with spatial ATAC-seq). Applying StarTrak to tumor sections, we infer the migration of mutated tumor cells into adjacent non-malignant tissues and reconstruct distinct lineage trees associated with different spatial regions. Notably, we identify tumor regions with nearly identical transcriptomic states but distinct mutational profiles. Moreover, for skin sections, StarTrak identifies sunlight-associated mutations in non-malignant epidermis and evidence suggesting the migration of these mutant surface cells into deeper skin layers. Overall, by integrating mutation calling with spatial context, StarTrak enables the inference of spatially resolved cellular migration and cellular phylogeny.

bioinformatics↗

bioRxiv2026

Screening of Isolation and Culture Conditions of Lactic Acid Bacteria in Mongolian Horse Feces

ObjectiveThis study aimed to establish an efficient isolation, culture, and preservation system for lactic acid bacteria from Mongolian horse feces by systematically evaluating the effects of sampling methods, culture conditions, media types, and cryopreservation protocols. MethodsFecal samples were collected using rectal and natural defecation methods, and bacteria were isolated by the spread plate technique, with isolates subcultured and identified via 16S rRNA gene sequencing. The performance of five commercial media (A-E), aerobic versus anaerobic conditions, and different glycerol concentrations (10% and 30%), temperatures (-20 {degrees}C and -80 {degrees}C), and storage durations (7, 15, and 30 days) were compared. ResultsRectal sampling showed significantly higher lactic acid bacterial survival and greater species diversity (12 vs. 8). Anaerobic culture yielded substantially higher counts and diversity (707 strains, 12 species) compared to aerobic conditions (36 strains, 5 species). Medium C (M.R.S. AGAR) exhibited the best isolation performance, producing the highest number of strains (311) and species (11), with selective enrichment for both bacilli and cocci. Glycerol effectively improved strain survival during sample cryopreservation, with the optimal short-term storage ([≤]15 days) achieved at -20 {degrees}C with 30% glycerol. Functional screening of randomly selected strains from optimized conditions demonstrated promising growth, acid and bile salt tolerance, and antimicrobial activity. ConclusionRectal sampling combined with anaerobic incubation using Medium C is recommended for optimal isolation. For samples that cannot be processed immediately, short-term preservation at -20 {degrees}C with 30% glycerol prior to isolation is effective. This study provides practical technical references for the acquisition and preservation of equine intestinal lactic acid bacteria resources.

microbiology↗

bioRxiv2026

The molecular asynchrony of single cells

Integrating single-cell transcriptomic and epigenomic data provides a robust framework for investigating gene regulation mechanisms. Existing analyses typically treat these modalities as synchronized features that can be translated in a static manner; however, the temporal delays that underpin cellular kinetics are intrinsic to dynamic biological systems. To address this limitation, we propose utilizing the "molecular asynchrony" within regulatory hierarchies to determine the thermodynamic properties of individual cells. Here, we present SeqTag, a single-cell multiomics sequencing method that simultaneously profiles the transcriptome, chromatin accessibility, and histone modifications, supported by an analytical framework to identify asynchronous states across regulatory layers for characterization of single-cell kinetics. By measuring the epigenetic priming potential and remodeling rates during adult mouse oligodendrogenesis, we delineated a sequential program for bivalency resolution as maturing cells traverse Waddingtons landscape. This process becomes increasingly decoupled with age, a change linked to a drift in progenitor cell-fate probabilities. By identifying entropy-driving regulatory elements, we characterized the aging-related decline in cell identity across various cell types and proposed a dynamic model linking static genetic variants to the risk of late-onset diseases. In summary, our integrated approach established a unified framework for employing multimodal single-cell genomics to model the kinetics of complex cellular processes.

genomics↗

bioRxiv2026

An SE(3)-equivariant Crystal Structure Prediction Framework for Prospective Identification and Development of Bioactive Nucleoside Self-Assembling Materials

Flexible organic small molecules can assemble into supramolecular biomaterials whose properties are intrinsically governed by their crystal structures, yet experimental structure determination remains difficult to scale during molecular modification and materials optimization. Crystal structure prediction (CSP) provides a potential solution, but its prospective power is limited for flexible molecules owing to incomplete conformational sampling and the difficulty of identifying experimentally realized structures from large candidate sets. Here, an SE(3)-equivariant deep-learning workflow, SE3CSP, is developed for organic crystal structure prediction. By learning molecular conformations, unit-cell parameters and packing patterns from experimentally resolved crystal structures and integrating these predictions with MACE-based structure optimization, SE3CSP establishes an end-to-end pipeline from two-dimensional molecular representations to three-dimensional crystal structures. Using nucleosides as representative flexible self-assembling building blocks, SE3CSP achieves an overall prediction accuracy of [~]57%, substantially outperforming the benchmark MACE-based Genarris 3.0 workflow ([~]14%). Furthermore, a prospective prediction strategy is developed in which an SE3CSP-predicted density window ({+/-} 0.15 g/cm3) is applied prior to energy ranking and structural deduplication, enabling all experimentally realized structure to be consistently ranked within the top 1-2% of all generated candidates. Beyond structure prediction, SE3CSP-derived energy landscapes provide insight into potential single-crystal-to-single-crystal transformations and enable the identification of a nucleoside supramolecular material with dynamic breathing porosity, which is further developed as an adsorptive platform for inflammatory mediator removal with excellent anti-inflammatory performance and biocompatibility. These results establish SE3CSP as a practical framework for prospective CSP and highlight its utility in guiding the discovery and design of bioactive self-assembled materials.

bioengineering↗

bioRxiv2026

Wnt/β-catenin signaling restrains developmental beiging and imprints long-term energy expenditure

Beige adipocytes that emerge during the peri-weaning period support sympathetic nervous system (SNS)-independent thermogenesis, yet the mechanisms governing this spontaneous beiging remain unclear. Here, by integrating transcriptomic profiling with adipocyte-targeted Ctnnb1 deletion in mice, we identify the canonical Wnt signaling as an endogenous brake on developmental beige thermogenesis. Peri-weaning inguinal fat from adipocyte Ctnnb1 knockout mice exhibits enhanced beige adipocyte biogenesis, with increased thermogenesis-related gene expression and mitochondrial oxidative capacity, which programs durable activation of adaptive thermogenesis and augmented whole-body energy expenditure into adulthood. Mechanistically, suppression of Wnt/{beta}-catenin signaling induces a non-canonical Wnt5a-Ca2-AMPK axis that promotes triglyceride lipolysis and subsequent PPAR-driven fatty acid oxidation, thereby fueling mitochondrial respiration. Genetic or pharmacological disruption of this axis blunts thermogenic responses induced by {beta}-catenin inhibition in both murine and human subcutaneous adipocytes, indicating that Wnt5a-Ca2-AMPK axis is required for the cell-autonomous activation of beige fat. These results reveal Wnt/{beta}-catenin signaling as a developmental constraint on beige adipocyte formation and suggest an SNS-independent route to sustainably raise energy expenditure and improve metabolic health.

physiology↗

bioRxiv2026

Nuclear blebs are composed of variable chromatin states but consistently enrich transcription initiation relative to elongation

Nuclear blebs are herniations of the nucleus that occur in many human conditions including aging, heart disease, muscular dystrophy, and many cancers. Nuclear blebbing causes nuclear rupture and cellular dysfunction. However, understanding the formation, stability, and identification of nuclear blebs remains an ongoing challenge. Our previous studies reveal that nuclear blebs are best hallmarked by decreased DNA density. To determine if chromatin decompaction underlies decreased DNA density in nuclear blebs, we investigated the histone composition of nuclear blebs across multiple cell lines. Time lapse and immunofluorescence imaging revealed that global histone H2B and H3 levels are decreased in the nuclear bleb relative to the nuclear body. Next, we imaged histone modification states of euchromatin and heterochromatin, which respectively track decompact and compact states of chromatin. Overall, we find that nuclear blebs display variable histone modification state across cell lines, as euchromatin does not consistently enrich nor is heterochromatin consistently depleted. Nuclear blebs did consistently show active RNA Pol II initiation is enriched relative to elongation. Thus, we find that the local histone modification state is not an essential component of nuclear blebs while transcription initiation enrichment over elongation is reproducible across cell lines and conditions. Summary statementWe measured histones and their modification states in nuclear blebs. We find that chromatin state is variable while transcription initiation is consistently enriched relative to elongation in nuclear blebs.

cell biology↗

bioRxiv2025

PertAdapt: Unlocking Single-Cell Foundation Models for Genetic Perturbation Prediction via Condition-Sensitive Adaptation

Single-cell foundation models (FMs) pretrained on massive unlabeled scRNA-seq data show strong potential in predicting transcriptional responses to unseen genetic perturbations. However, existing approaches insufficiently transfer pretrained knowledge and overlook the imbalance between perturbation-sensitive and insensitive genes, yielding only marginal improvements over nonpretrained baselines. To address these limitations, we introduce PertAdapt, a framework that unlocks FMs to accurately predict genetic perturbation effects via integrating a plug-in perturbation adapter and an adaptive loss. The adapter employs a gene-similarity-masked attention mechanism to jointly encode perturbation conditions and contextualized representations of unperturbed cells, enabling more effective knowledge transfer. To better capture differential expression patterns, the adaptive loss dynamically reweights perturbation-sensitive genes relative to global transcriptomic signals. Extensive experiments across seven perturbation datasets, including both single- and double-gene settings, demonstrate that PertAdapt consistently outperforms non-pretrained and FM baselines. Moreover, PertAdapt demonstrates strong capacity for modeling multiplexed gene interactions, generalizing in limited-data regimes, and maintaining robustness across backbone sizes. AvailabilityCode and data are available at https://github.com/BaiDing1234/PertAdapt.

bioinformatics↗

bioRxiv2025

Electrostatic Interaction Determines the Docking Specificity and the Formation of Functional Cx36 Gap Junction Channels

Connexin36 (Cx36) is broadly expressed in neurons and serves as the principal protein that forms interneuronal gap junctions (GJs), also known as electrical synapses. Recent high-resolution structures of human Cx36 GJ have revealed crucial electrostatic interactions (ESIs) of charged residues between two docked Cx36 hemichannels at the second extracellular (E2) loops. Despite their structural importance, the mechanistic roles of these ESIs remain poorly understood. To investigate their significance, we systematically designed and tested a series of missense variants targeting key E2 interface residues, aiming to disrupt or modulate the electrostatic landscape at the docking interface. Based on the ESI pairs defined from the crystal structure, our combined computational calculations and dual patch-clamp experiments in engineered HEK293 cell pairs suggest that at least three ESI residual pairs per E2-E2 interface are required to support functional GJ formation. Furthermore, we found that these unique ESIs of Cx36 could play a role in its docking specificity to itself, as they rarely form heterotypic GJs with other brain connexins. Overall, these findings provide essential molecular and functional insights into the mechanisms governing Cx36 GJ formation and partner specificity, paving the way for future therapeutic approaches targeting connexin dysfunction in human diseases.

neuroscience↗

bioRxiv2025

Modeling Post-Gastrula Development via Bidirectional Pluripotent Stem Cells

The absence of stem cells capable of efficiently generating both trophoblast and epiblast lineages has hindered precise recapitulation of embryonic development. Through high-content chemical screening, we established an AL medium to generate mouse and human bidirectional pluripotent stem cells (BPSCs) characterized by concurrent OCT4/CDX2 expression. Mouse BPSCs demonstrated high plastic differentiation into trophoblast, epiblast and primitive endoderm lineages in vitro within 48 hours without exogenous induction factors and efficiently contributed to the embryo and extraembryonic tissues in vivo. Mechanistically, hyperactivation of the Wnt signaling pathway breaks the early lineage differentiation barrier by initiating a Lef1-dependent bypass. Remarkably, BPSCs can efficiently generated E8.5 embryoids that completed gastrulation and displayed advanced features such as brain development, a closed neural tube, a beating heart, somite formation, and primordial germ cells. These findings highlight BPSCs as a powerful tool for investigating early lineage specification and post-gastrulation embryonic development, with potential applications across multiple species.

developmental biology↗

bioRxiv2025

Multi-omic Characterization of HIV Effects at Single Cell Level across Human Brain Regions

HIV infection exerts profound and long-lasting neurodegenerative effects on the central nervous system (CNS) that can persist despite antiretroviral therapy (ART). Here, we used single-nucleus multiome sequencing to map the transcriptomic and epigenetic landscapes of postmortem human brains from 13 healthy individuals and 20 individuals with HIV who have a history of treatment with ART. Our study spanned three distinct regions--the prefrontal cortex, insular cortex, and ventral striatum--enabling a comprehensive exploration of region-specific and cross-regional perturbations. We found widespread and persistent HIV-associated transcriptional and epigenetic alterations across multiple cell types. Detailed analyses of microglia revealed state changes marked by immune activation and metabolic dysregulation, while integrative multiomic profiling of astrocytes identified multiple subpopulations, including a reactive subpopulation unique to HIV-infected brains. These findings suggest that cells from people with HIV exhibit molecular shifts that may underlie ongoing neuroinflammation and CNS dysfunction. Furthermore, cell-cell communication analyses uncovered dysregulated and pro-inflammatory interactions among glial populations, underscoring the multifaceted and enduring impact of HIV on the brain milieu. Collectively, our comprehensive atlas of HIV-associated brain changes reveals distinct glial cell states with signatures of pro-inflammatory signaling and metabolic dysregulation, providing a framework for developing targeted therapies for HIV-associated neurological dysfunction.

bioinformatics↗

bioRxiv2024

Expanding the Landscape of Aging via Orbitrap Astral Mass Spectrometry and Tandem Mass Tag (TMT) Integration

Aging results in a progressive decline in physiological function due to the deterioration of essential biological processes, such as transcription and RNA splicing, ultimately increasing mortality risk. Although proteomics is emerging as a powerful tool for elucidating the molecular mechanisms of aging, existing studies are constrained by limited proteome coverage and only observe a narrow range of lifespan. To overcome these limitations, we integrated the Orbitrap Astral Mass Spectrometer with the multiplex tandem mass tag (TMT) technology to profile the proteomes of three brain tissues (cortex, hippocampus, striatum) and kidney in the C57BL/6JN mouse model, achieving quantification of 8,954 to 9,376 proteins per tissue (cumulatively 12,749 across all tissues). Our sample population represents balanced sampling across both sexes and three age groups (3, 12, and 20 months), comprising young adulthood to early late life (approximately 20-60 years of age for human lifespan). To enhance quantitative accuracy, we developed a peptide filtering strategy based on resolution and signal-to-noise thresholds. Our analysis uncovered distinct tissue-specific patterns of protein abundance, with age and sex differences in the kidney, while brain tissues exhibit notable age changes and limited sex differences. In addition, we identified both proteomic changes that are linear with age (i.e., continuous) and that have a non-linear pattern (i.e., non-continuous), revealing complex protein dynamics over the adult lifespan. Integrating our findings with early developmental proteomic data from brain tissues highlighted further divergent age-related trajectories, particularly in synaptic proteins. This study not only provides a robust data analysis workflow for TMT datasets generated using the Orbitrap Astral mass spectrometer but also expands the proteomic landscape of aging, capturing proteins with age and sex effects with unprecedented depth.

systems biology↗

bioRxiv2024

scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell Transcriptomics

Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of cellular heterogeneity by providing gene expression data at single-cell resolution, uncovering insights into rare cell populations, cell-cell interactions, and gene regulation. Foundation models pretrained on large-scale scRNA-seq datasets have shown great promise in analyzing such data, but existing approaches are often limited to modeling a small subset of highly expressed genes and lack the integration of external genespecific knowledge. To address these limitations, we present sc-Long, a billion-parameter foundation model pretrained on 48 million cells. sc-Long performs self-attention across the entire set of 28,000 genes in the human genome. This enables the model to capture long-range dependencies between all genes, including lowly expressed ones, which often play critical roles in cellular processes but are typically excluded by existing foundation models. Additionally, sc-Long integrates gene knowledge from the Gene Ontology using a graph convolutional network, enriching its contextual understanding of gene functions and relationships. In extensive evaluations, sc-Long surpasses both stateof-the-art scRNA-seq foundation models and task-specific models across diverse tasks, including predicting transcriptional responses to genetic and chemical perturbations, forecasting cancer drug responses, and inferring gene regulatory networks.

bioinformatics↗

bioRxiv2024

AttentionPert: Accurately Modeling Multiplexed Genetic Perturbations with Multi-scale Effects

Genetic perturbations (i.e. knockouts, variants) have laid the foundation for our understanding of many diseases, implicating pathogenic mechanisms and indicating therapeutic targets. However, experimental assays are fundamentally limited in the number of perturbation conditions they can measure. Computational methods can fill this gap by predicting perturbation effects under unseen conditions, but accurately predicting the transcriptional responses of cells to unseen perturbations remains a significant challenge. We address this by developing a novel attention-based neural network, AttentionPert, which accurately predicts gene expression under multiplexed perturbations and generalizes to unseen conditions. AttentionPert integrates global and local effects in a multi-scale model, representing both the non-uniform system-wide impact of the genetic perturbation and the localized disturbance in a network of gene-gene similarities, enhancing its ability to predict nuanced transcriptional responses to both single and multi-gene perturbations. In comprehensive experiments, AttentionPert demonstrates superior performance across multiple datasets outperforming the state-of-theart method in predicting differential gene expressions and revealing novel gene regulations. AttentionPert marks a significant improvement over current methods, particularly in handling the diversity of gene perturbations and in predicting out-of-distribution scenarios.

bioinformatics↗

bioRxiv2023

Phosphorylation Promotes DELLA Activity by Enhancing Its Binding to Histone H2A at Target Chromatin in Arabidopsis

DELLA proteins are conserved master growth regulators that play a central role in controlling plant development in response to internal and environmental cues. DELLAs function as transcription regulators, which are recruited to target promoters by binding to transcription factors (TFs) and histone H2A via its GRAS domain. Recent studies showed that DELLA stability is regulated post-translationally via two mechanisms, phytohormone gibberellin-induced polyubiquitination for its rapid degradation, and Small Ubiquitin-like Modifier (SUMO)- conjugation to alter its accumulation. Moreover, DELLA activity is dynamically modulated by two distinct glycosylations: DELLA-TF interactions are enhanced by O-fucosylation, but inhibited by O-linked N-acetylglucosamine (O-GlcNAc) modification. However, the role of DELLA phosphorylation remains unclear. Here, we identified phosphorylation sites in REPRESSOR OF ga1-3 (RGA, an AtDELLA) purified from Arabidopsis by tandem mass spectrometry analysis, and showed that phosphorylation of the RGA LKS-peptide in the poly- S/T region enhances RGA-H2A interaction and RGA association with target promoters. Interestingly, phosphorylation does not affect RGA-TF interactions. Our study has uncovered that phosphorylation is a new regulatory mechanism of DELLA activity.

plant biology↗

bioRxiv2023

Role of C2-domain protein CAR1 in the plasma membrane ABA signaling response

Plasma membrane (PM)-associated abscisic acid (ABA) signal transduction is an important component of ABA signaling. The C2-domain ABA-related (CAR) proteins have been reported to play a crucial role in recruiting ABA receptor PYR1/PYL/RCAR (PYLs) to the PM. However, the molecular details of the involvement of CAR proteins in membrane-delimited ABA signal transduction remain unclear. Here, the GUS-tagged materials for all Arabidopsis CAR members were used to comprehensively visualize the extensive expression patterns of the CAR family genes. Based on the specificity of CAR1s response to ABA, we determined to use it as a target to study the function of CAR proteins in PM-associated ABA signaling. Single-particle tracking showed that ABA affected the spatiotemporal dynamics of CAR1. The presence of ABA prolonged the dwell time of CAR1 on the membrane and showed faster lateral mobility. Surprisingly, we verified that CAR1 could directly recruit Hypersensitive to ABA1 (HAB1) and SNF1-related protein kinase 2.2 (SnRK2.2) to the PM at both the bulk and single-molecule levels. Furthermore, PM localization of CAR1 was demonstrated to be related to membrane microdomains. Collectively, our study revealed that CARs recruited the three main components of ABA signaling to the PM to respond positively to ABA. This study deepens our understanding of ABA signal transduction.

biophysics↗

bioRxiv2022

Structure of IgG-Fc hexamer reveals a mutual lock-and-key mode of Fc-Fc interaction

IgG exists mainly as monomer, but recent studies suggest that IgG forms hexamer to mediate antibody functions. Although many structures of IgG monomer and its fragments are determined, there is no IgG hexamer structure at atomic level due to the weak Fc-Fc interactions. Here we engineered a hexameric IgG with IgM tailpiece fusion and determined the structure by cryo-EM. IgG-Fc hexamer forms hexagon symmetry with the six Fcs lie in a plane with Fc-Fc interaction in a mutual lock-and-key mode. This structure provides structural insights into Fc-Fc interaction of IgG and reveals molecular basis for its function.

biophysics↗

bioRxiv2021

Essential role for Ggct in erythrocyte antioxidant defense

GGCT encodes {gamma}-glutamyl cyclotransferase enzyme activity, and its expression is up-regulated in various human cancers. {gamma}-glutamyl cyclotransferase enzyme activity was originally purified from human red blood cells (RBCs), however physiological function of GGCT in RBCs is still not clear. Here we reported that Ggct deletion in mouse leads to splenomegaly and progressive anemia phenotypes, due to elevated oxidative damage and shortened life span of Ggct-/- RBCs. Ggct-/- RBCs have increased reactive oxygen species (ROS), and are more sensitive to H2O2 induced damage compared to control RBCs. Glutathione (GSH) and GSH synthesis precursor L-cysteine are decreased in Ggct-/- RBCs. Our study suggests a critical function of Ggct in RBC redox balance and life span maintenance through regulating GSH metabolism.

genetics↗

bioRxiv2021

A novel Wnt/beta-catenin signaling driven adipocyte population that is required for beiging

Wnt/{beta}-catenin signaling has been well established as a potent inhibitor of adipogenesis. Here, we identified a population of adipocytes that exhibit persistent activity of Wnt/{beta}-catenin signaling, as revealed by the Tcf/Lef-Gfp reporter allele, in embryonic and adult mouse fat depots, named as Wnt+ adipocytes. We showed that the {beta}-catenin-mediated signaling activation in these cells is Wnt ligand- and receptor-independent but relies on AKT/mTOR pathway and is essential for cell survival. Such adipocytes are distinct from classical ones in transcriptomic and genomic signatures and can be induced from various sources of mesenchymal stromal cells including human cells. Genetic lineage-tracing and targeted cell ablation studies revealed that these adipocytes convert into beige adipocytes directly and are also required for beige fat recruitment under thermal challenge, demonstrating both cell autonomous and non-cell autonomous roles in adaptive thermogenesis. Furthermore, mice bearing targeted ablation of these adipocytes exhibited glucose intolerance, while mice receiving exogenously supplied such cells manifested enhanced glucose utilization. Our studies uncover a unique adipocyte population in regulating beiging in adipose tissues and systemic glucose homeostasis.

physiology↗