Biology subjects

Zhong, W.

Publications and source records attributed to Zhong, W..

At least 19 recordsLinked to original sources

bioRxiv2026

An expanded toolbox for genetic access to molecularly defined cortical intratelencephalic neuron subtypes

Among the multiple cortical glutamatergic neuron classes, intratelencephalic (IT) neurons represent the largest class and project within the cortex and striatum. IT neurons have been amplified and diversified throughout mammalian evolution and are thought to underlie increasingly complex mammalian cognition. However, despite their diversity and significance in cortical processes, few existing tools connect the molecular signatures to the projection patterns of distinct IT subtypes, limiting our ability to understand their organization and function at a subtype resolution. Here, we illustrate six novel gene knock-in mouse lines based on IT-specific markers, labeling subpopulations with unique cortico-cortical and corticostriatal projection patterns. These include two broad subpopulations with upper-layer (Cux1-Flp) versus lower-layer (Kcnh5-CreER) expression biases, two narrow upper-layer subpopulations with contrasting callosal (Wfs1-Flp) and local (Igfn1-Flp) projection patterns, and two narrow lower-layer subpopulations with contrasting bilateral (Deptor-CreER) versus ipsilateral-predominant (Ptprm-CreER) corticostriatal projection patterns. Upper-layer Wfs1+ and lower-layer Ptprm+ IT neurons also project to perirhinal/ectorhinal cortex with densities that vary across cortical areas. Finally, we use in vivo calcium imaging in mice performing a reach-withdraw-drink task to demonstrate subtype-specific temporal dynamics in upper-layer Wfs1+ versus lower-layer Deptor+ neurons. Our work expands the toolbox of transgenic mice to access molecularly defined IT neuron subpopulations.

neuroscience↗

bioRxiv2026

Monomeric TDP-43 binds GU-rich RNA via its NTD but only its oligomers block cryptic exon inclusion

TDP-43 aggregation is a pathological feature of several neurodegenerative diseases, resulting in nuclear loss of function and RNA dysregulation, including cryptic exon derepression. TDP-43 comprises two RNA recognition motifs required for canonical RNA binding, a low-complexity domain implicated in phase separation, and an N-terminal domain (NTD) that mediates oligomerization. While NTD-driven oligomerization is critical for TDP-43 splicing function, some studies suggest a direct interaction of NTD with RNA. Here, we investigated RNA binding by the NTD and its functional interplay with oligomerization. We show that the NTD preferentially binds UG-rich RNA via residues located at the oligomerization interface. The NTD engaged RNA only on monomeric TDP-43, as RNA binding and oligomerization compete for the same interface and rely on similar interaction modes. By disentangling these competing activities, we demonstrated that oligomerization, but not NTD-RNA interaction, is essential for TDP-43-dependent alternative splicing and repression of cryptic exons. Our findings uncover a previously unappreciated RNA-binding activity within the TDP-43 NTD that directly competes with oligomerization and establish oligomerization as a key determinant of TDP-43 cryptic exon repression.

molecular biology↗

bioRxiv2026

Deciphering interaction syntax via decoupling intrinsic lineages and niche pressure

Spatial transcriptomics enables the mapping of gene expression within intact tissues, yet a fundamental gap remains between knowing where cells are and understanding how they interact. A cells measured transcriptome reflects both its intrinsic lineage identity and niche pressure. Here we introduce TRINUS, a self-supervised model that deciphers interaction syntax by generative decoupling of a cells intrinsic lineage identity from the extrinsic niche pressure. TRINUS maintains a library of context-free cell prototypes to isolate lineage identity while modeling cooperative interaction dependencies among neighbors. We validated TRINUS on synthetic datasets with known interaction logic and benchmarked it against existing methods with superior performance in cell clustering and spatial domain detection. Applied across diverse platforms and biological systems, TRINUS resolves multi-level interaction syntax and maps tissue-wide interaction patterns in colorectal cancer, and identifies stage-specific signaling dependencies and time-dependent receptor windows during mouse organogenesis. We also show TRINUSs bidirectional in silico engineering capability in the ovarian tumor microenvironment, where forward perturbation revealed subtype-specific macrophage immunosuppressive programs via virtual transplantation and inverse design identified molecular modifications in macrophages predicted to rescue adjacent T-cell function. Collectively, TRINUS provides a practical tool for interaction syntax discovery and predictive tissue engineering on spatial transcriptomics data.

bioinformatics↗

bioRxiv2026

GATA transcription factors act as gatekeepers between the Wnt/β-catenin-mediated proliferation and differentiation in the intestinal epithelium

Wnt/{beta}-catenin signalling drives gene expression in a plethora of processes during development and tissue homeostasis. Yet, little is known about how {beta}-catenin, the transducer of the pathway, gives rise to context-specific transcriptional outcomes. For example, in the intestinal epithelium, stem cells and secretory cells lie adjacent to each other, are both exposed to and dependent on Wnt signals, but display divergent identities. We find that, in this tissue, GATA transcription factors functionally interact with Wnt/{beta}-catenin signaling to drive differential cell identity. This occurs because GATA selectively repress Wnt target secretory-lineage genes in stem cells. Mechanistically, we found that GATA factors physically engage with the {beta}-catenin transcriptional complex, and that this association is mediated by the bridge protein BCL9/9L. Our work implicates GATA factors as context dependent modulators of the Wnt/{beta}-catenin transcription, shows that the GATA/BCL9 module acts as a switch at the crossroads of cell identity decision, and uncovers how this epithelium maintains the fine balance between self-renewal and differentiation.

developmental biology↗

bioRxiv2026

Systems-level longitudinal immune profiling reveals individualized immunotypes and genetic associations

The human immune system exhibits substantial inter-individual variation, yet how this variability is coordinated across the system and persists over time remains incompletely defined. Here, we integrated whole-genome sequencing with longitudinal multi-omics immune profiling in 101 healthy individuals followed over two years, combining mass cytometry-based immune cell profiling, PBMC transcriptomics, plasma proteomics, and clinical measurements. Coordinated variation across cellular composition, gene expression, and circulating proteins revealed reproducible immune patterns within individuals across visits. Integrative analyses identified three major immunotypes: adaptive lymphoid (CD4 T cell and B cell enriched), myeloid-inflammation (monocyte and dendritic cell-driven), and cytotoxic (CD8 T cell-dominated), each associated with distinct metabolic and inflammatory profiles. Genome-wide association analyses identified cell-type-specific quantitative trait loci primarily affecting memory lymphocytes, and a polygenic score for memory B cells correlated with both cellular abundance and transcriptional activity. Together, these findings provide a systems-level view for understanding baseline immune heterogeneity in human populations. TeaserLongitudinally stable immune individuality reflects coordinated modules shaped by systemic physiology and genetics

systems biology↗

bioRxiv2026

lncRNAs contribute to caste differentiation as a regulatory layer in ants

Caste differentiation in ants represents one of the major evolutionary transitions and provides a unique model for studying developmental mechanisms underlying division of labor. Genetically identical individuals follow divergent epigenetically-regulated developmental trajectories that give rise to morphologically distinct phenotypes and specialized roles. While long non-coding RNAs (lncRNAs) are emerging as key epigenetic regulators across diverse biological systems, their specific contributions to caste development in social insects remain largely unexplored. Here, we conducted comprehensive transcriptomic analyses across major developmental stages of two evolutionarily and ecologically distinct ants Monomorium pharaonis and Acromyrmex echinatior, identifying over 10,000 lncRNAs. We demonstrated that lncRNAs exhibit dynamic, caste-specific expression patterns throughout development. We also identified a subset of lncRNAs displaying canalized expression patterns, characterized by progressively increasing caste bias and decreasing within-caste variation as development proceeds. Co-expression analyses revealed that canalized lncRNAs are functionally linked to canalized protein-coding genes, which are crucial regulators for caste differentiation. These canalized lncRNAs show striking tissue-specific enrichment consistent with canalized protein-coding genes. Functional validation through RNA interference revealed that canalized lncRNAs directly regulate caste-specific traits. Furthermore, juvenile hormone treatment capable of redirecting worker lncRNA expression profiles toward gyne-like patterns, with similar expression changes and tissue specificity to JH-responsive protein-coding genes, linking lncRNA regulation to established hormonal pathways controlling caste fate. Our findings establish lncRNAs as active architects of caste differentiation in social insects, demonstrating that these rapidly-evolving regulatory molecules contribute to the evolution and maintenance of social phenotypes through tissue-specific regulation of caste-associated developmental programs.

developmental biology↗

bioRxiv2025

Lysosomal escape and TMEM106B fibrillar core determine TDP-43 seeding outcomes

Frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-TDP) shows striking clinical and neuropathological heterogeneity, yet a systematic analysis of subtype-specific features and inter-patient variability was missing. We treated human neurons and neuron-like cells with 30 postmortem brain samples and quantified neoaggregate formation, loss of function and changes in the TDP-43 interactome to define determinants of seeding outcomes. Potent FTLD-TDP-A seeds drove a progressive collapse of physiological TDP-43 interactions accompanied by functional loss. Beyond the burden of pathological TDP-43, we identified the fibrillar core of the lysosomal protein TMEM106B as a critical pro-seeding factor. Transient lysosomal injury markedly enhanced neoaggregation and loss of function, likely by promoting fibril interactions with native TDP-43. Our work establishes a mechanistic link between TMEM106B and TDP-43 aggregation, identifies lysosomal escape as a key driver of pathology and introduces the strongest model yet for seeded TDP-43 aggregation and loss of function, to enable discovery of disease modifiers.

neuroscience↗

bioRxiv2025

Nuclear N-Glycosylation Redefines the Glycoscape and Directs Cell Identity

Glycans modify nucleic acids, proteins and lipids in fundamental biological processes, but have long been considered confined to the secretory pathway and cell surface. Here, we challenge this view with evidence that N-glycosylation, a ubiquitous glycan modification, occurs within cell nuclei across tissues and species, exhibiting cell type-dependent abundance and localization patterns. Using a multi-faceted approach, we show that numerous classical membrane and secreted glycoproteins localize to the nucleus with N-glycan modifications, exemplified by the cell adhesion molecule L1CAM. Mechanistically, we show that the N-glycosylated L1CAM is transported to the nucleus by KPNB1, where it transcriptionally modulates neuronal differentiation. Moreover, this nuclear N-glycosylation event contributes to neurodevelopmental disorders and is pharmacologically reversible. These findings revise the cellular geography of N-glycosylation and expand the known routes of protein trafficking, and highlight nuclear N-glycosylation pathways as potential therapeutic entry points for developmental disorders.

cell biology↗

bioRxiv2025

Visuospatial attention exerts opposite modulatory effects on explicit and implicit audiovisual subjective synchrony via the frontoparietal network

Synchronization and integration constitute two essential subprocesses of audiovisual binding, commonly indexed by explicit subjective synchrony (ESS) and implicit subjective synchrony (ISS), respectively. Previous studies have shown that spontaneous fluctuations in visual attention are associated with ESS, and that ESS and ISS are negatively correlated, consistent with the temporal renormalization theory. However, it remains unknown whether controlled manipulations of visuospatial attention can causally modulate ESS and ISS in opposite directions via distinct neural mechanisms. To address this question, we conducted two complementary EEG experiments. In Experiment 1, ESS was assessed using a spatially cued beep-flash synchrony judgment task and the point of subjective simultaneity (PSS). In Experiment 2, ISS was measured using fusion and fission variants of the sound- induced flash illusion, with the peak illusion rate (PIR) as the behavioral index. This dual-paradigm design enabled direct comparison between explicit and implicit synchrony under matched attentional manipulations. Behaviorally, asymmetric allocation of visuospatial attention between auditory- and visual-leading conditions induced opposite shifts in PSS and PIR, specifically in the fusion variant. At the neural level, prestimulus frontal theta oscillations were associated with variations in PSS, whereas bilateral frontotemporal and left posterior beta oscillations were associated with variations in PIR. These results demonstrate that visuospatial attention exerts opposite modulatory effects on ESS and ISS through distinct oscillatory dynamics, providing causal evidence for the temporal renormalization theory and advancing understanding of how attentional control shapes multisensory temporal binding.

animal behavior and cognition↗

bioRxiv2025

Mechanisms of sex differences in acute and long COVID sequelae in mice

Males are more likely to suffer severe outcomes during acute COVID-19 and a greater proportion of females develop post-acute sequalae of COVID-19 (PASC). To identify mechanisms of PASC, mice were infected with SARS-CoV-2 and viral, inflammatory, and neurocognitive outcomes were evaluated through 84 days post-infection. Sex differences were not observed in virus replication or persistence of viral RNA in pulmonary or extrapulmonary tissues. After infectious virus clearance, females exhibited persistent neurocognitive impairments, and greater frequencies of inflammatory myeloid cells, neuroinflammation, and dysregulated T cells, including effector memory and Tregs. Sex differences in persistent inflammation and cognitive impairments during PASC were mediated by the presence of two X chromosomes and infection-induced upregulation of the X-linked genes Xist and Tlr7, which was reversed by pharmacological inhibition of TLR7 activity during the PASC phase. Sustained X-linked TLR7-mediated inflammation underlies how the burden of PASC is greater for females and provides a therapeutic target.

immunology↗

bioRxiv2025

SpaDiff: Denoising for Sequence-based Spatial Transcriptomics via Diffusion Process

Spatial transcriptomics enables transcriptome-scale analysis with spatial resolution but suffers from spot-swapping, where RNA molecules drift from their true locations, introducing noise and reducing spatial specificity. We introduce SpaDiff, a denoising method that treats spot-swapping as a diffusion process. SpaDiff simulates the displacement of RNA molecules and reverses it to restore their original spatial distribution while preserving molecular counts. Evaluations on simulated and real data demonstrate that SpaDiff enhances spatial specificity of gene expression, improves data integrity, and supports more accurate downstream analyses such as clustering and spatial domain identification.

bioinformatics↗

bioRxiv2025

Optimal Gene Panel Selection for Targeted Spatial Transcriptomics Experiments

Spatial transcriptomics analysis is a powerful approach for dissecting the structure of tissue microenvironment and uncovering the mechanism of cell-cell communications. However, existing technologies are limited by either spatial resolution or gene coverage. Most single-cell resolution technologies target only a few hundreds of pre-selected genes, whose choice plays an important role in the overall analysis. It remains a challenge to optimally design a gene panel to maximize the utility of spatial transcriptomics profiling. To fill this gap, we introduce a novel method, named ReconST, to automatically design optimal gene panels for spatial transcriptomics profiling. ReconST leverages information from existing scRNA-seq data, and identifies the optimal subset of genes by using a gated autoencoder. By using a high-coverage mouse brain MERFISH dataset as the reference benchmark, we showed that ReconST outperforms existing methods in terms of both reconstruction accuracy and spatial pattern preservation. As such, ReconST provides a useful and generally-applicable tool for optimal gene panel design, which in turn can significantly enhance the utility of spatial transcriptomics profiling in a wide range of biomedical investigations.

bioinformatics↗

bioRxiv2025

HUBMet: An integrative database and analytical platform for human blood metabolites and metabolite-protein associations

Understanding human blood metabolites is essential for deciphering systemic physiology and disease mechanisms, yet remains challenging due to diverse origins and dynamic regulation. In this study, we developed HUBMet (https://hubmet.app.bio-it.tech/home), an open-access web server that includes 3,950 metabolites and 129,814 metabolite-protein associations, with four analytical modules: Over-Representation Analysis (ORA) for enrichment analysis; Metabolite Set Enrichment Analysis (MSEA) for quantitative data analysis; Tissue Specificity Analysis (TSA) for assessing metabolite-tissue relevance; Metabolite-Protein Network Analysis (MPNet) for identifying key metabolite-protein associations and functional modules. HUBMets utility is demonstrated through a COVID-19 case study revealing metabolic signatures associated with disease severity.

bioinformatics↗

bioRxiv2025

Sequence-Specific Installation of Aryl Groups in RNA via DNA-Catalyst Conjugates

Installing functional groups at specific sites in existing RNA molecules remains a challenge for modification, labeling, and therapeutic strategies. Here we describe the use of DNA oligonucleotides carrying a catalytic amine group to effect the aqueous SNAr arylation of 2'-OH groups at sequence-complementary sites in RNAs. Chloro-pyrimidine electrophiles are shown to react with amino-DNA conjugates, resulting in a proposed transient ammonium aryl intermediate that can react with RNA near the DNA binding site, delivering the heterocycle to the RNA in high yields. In a test of utility, we construct an aryl electrophile carrying an azide group, and apply this strategy to fluorescently label messenger RNAs locally at the polyA tail. We also employ the approach to direct in vitro arylation in the coding region of a messenger RNA, knocking down protein expression selectively in the presence of another coding RNA. This sequence-directed catalytic strategy enables multiple applications in RNA labeling and modification.

biochemistry↗

bioRxiv2025

Direct binding of TDP-43 and Tau drives their co-condensation, but suppresses Tau fibril formation and seeding

Neuronal Tau aggregates are a hallmark of Alzheimers disease (AD), but more than half of the patients exhibit additional TDP-43 inclusions and some have co-aggregates of both proteins. The presence of Tau/TDP-43 co-pathology is associated with increased disease severity, although the causal relationship remains unclear. Here we demonstrate that Tau and TDP-43 mutually promote each others condensation through direct interaction in vitro, forming irregularly shaped or multiphasic co-condensates with lower TDP-43 mobility, but higher Tau dynamics. While Tau promotes TDP-43 aggregation in vitro, TDP-43 suppresses formation of Tau fibrils and instead causes formation of oligomeric Tau and Tau/TDP-43 species. These co-assemblies hinder Tau seeding in a biosensor assay specific for proteopathic Tau seeds. Consistent with this data, SarkoSpin extracts from AD brains with Tau/TDP-43 co-pathology exhibit reduced Tau seeding compared to Tau-only AD brains. In contrast, patient-derived extracts from AD brains with Tau/TDP-43 co-pathology are highly potent in seeding TDP-43 neoaggregates in a TDP-43 reporter cell line. Our results suggest that direct interaction of TDP-43 and Tau may suppress Tau pathology, while promoting TDP-43 pathology. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/662960v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@1ed5dfaorg.highwire.dtl.DTLVardef@b4ef07org.highwire.dtl.DTLVardef@b8dbe8org.highwire.dtl.DTLVardef@6d9b49_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Effects of diffusion MRI spatial resolution on human brain short-range association fiber reconstruction and structural connectivity estimation

Short-range association fibers (SAFs) are critical for cortical communications but are often underestimated in conventional resolution diffusion magnetic resonance imaging (dMRI) since they locate within a [~]1.5mm thin layer of superficial white matter. With the emergence of high-resolution diffusion imaging techniques, this study timely evaluated the effects of image spatial resolution on SAF reconstruction using simulation data and multi-resolution (2, 1.5, and 0.96 mm iso.) empirical data acquired on the same 20 healthy subjects using the gSlider sequence and 20 widely used tractography approaches. Resolution effects were qualitatively assessed through model fitting and tractography results and quantitatively evaluated using global and regional short-range connectivity strength (SCS). It is found that lower resolution systematically reduces SCS across all methods in a spatially varying manner. Moreover, tractography methods exhibit significant differences in resolution sensitivity, with diffusion tensor imaging (DTI) based single-tissue single-fiber tractography showing greater vulnerability than constrained spherical deconvolution (CSD)-based multi-tissue multi-fiber tractography. Probabilistic tracking with anatomical constraints (ACT) and filtering (SIFT) improves robustness. Finally, up-sampling data to nominally higher resolution partially mitigates resolution-induced degradation and improves SAF reconstruction accuracy, particularly for DTI tractography. Based on these findings, higher resolution and multi-shell imaging is recommended if possible. For a given dataset, data up-sampling and DTI-based probabilistic tracking with ACT is recommended for single-shell low b-value data. CSD-based probabilistic tracking with ACT and SIFT is recommended for single-shell higher b-value data and multi-shell data. In summary, this study systematically and quantitatively evaluated resolution effects on SAF reconstruction and structural connectivity estimation and provided practical guidelines for more accurate mapping of SAFs. These advances hold promises to improve the characterization of healthy and diseased human brains in a wide range of neuroscientific and clinical applications.

neuroscience↗

bioRxiv2025

Bimodality in pan-cancer proteomics reveals new opportunities for biomarker discovery

Bimodal protein expression, characterized by the distribution of protein expression with two modes, is linked to phenotypic variation across various biological systems. Whereas previous studies focused on RNA expression data, we developed a bimodality model tailored for proteomics to enhance the identification of cancer-associated biomarkers and targets, facilitating precision oncology. We analyzed proteomics data from various cancer types and identified 2401 tumor-associated bimodal proteins. These proteins were evaluated for pathway enrichment, revealing significant associations with critical cancer pathways, such as metabolism of non-essential amino acids, interaction between the extracellular matrix and its receptors on the cell surface, and central carbon metabolism in cancer. Utilizing an AI-enhanced knowledge graph, we further delineated common patterns among pan-cancer tumor-associated bimodal proteins. A case study on the bimodal expression of TROP2 in colon adenocarcinoma highlighted upregulation of MYC and WNT/{beta}-catenin signaling pathways and down-regulation of inflammatory and interferon-related pathways in the TROP2-high group. The biological difference between TROP2-high and TROP2-low groups underscored its significance in determining cancer heterogeneity and differences in cancer vulnerability, which can inform treatment decisions. Our findings show the value of proteomics in uncovering novel biomarkers and advancing precision medicine, setting a precedent for further multi-omics integration and clinical validation.

bioinformatics↗

bioRxiv2024

Random Tree Model of Meaningful Memory

Traditional studies of memory for meaningful narratives focus on specific stories and their semantic structures but do not address common quantitative features of recall across different narratives. We introduce a statistical ensemble of random trees to represent narratives as hierarchies of key points, where each node is a compressed representation of its descendant leaves, which are the original narrative segments. Recall is modeled as constrained by working memory capacity from this hierarchical structure. Our analytical solution aligns with observations from large-scale narrative recall experiments. Specifically, our model explains that (1) average recall length increases sublinearly with narrative length, and (2) individuals summarize increasingly longer narrative segments in each recall sentence. Additionally, the theory predicts that for sufficiently long narratives, a universal, scale-invariant limit emerges, where the fraction of a narrative summarized by a single recall sentence follows a distribution independent of narrative length.

neuroscience↗