Biology subjects

Chen, Z.

Publications and source records attributed to Chen, Z..

At least 127 records · Page 7Linked to original sources

bioRxiv2026

Targeting ALA3 with propiconazole regulates plant growth and enables discovery of promising inhibitor leads

Propiconazole (PCZ) is widely misused growth regulator in leafy Brassica vegetables. Developing green strategies for managing plant architecture has become an urgent agricultural priority. Here, we identified from a membrane-protein-defective yeast library a P4-ATP phospholipid flippase, aminophospholipid ATPase 3 (ALA3), as a target sensitive to PCZ. ALA3 exhibits high binding affinity for PCZ, which inhibits its ATPase activity. Knockdown of ALA3 rendered yeast, Arabidopsis, and Brassica rapa less sensitive to PCZ and conferred a growth-inhibited phenotype. This dwarfing phenotype is mediated through the interaction between ALA3 and CYP51G1 that jointly acts within the brassinosteroid regulatory pathway. Furthermore, we identified lead compounds A01 and A15 as ALA3-targeting agents, and compared to PCZ, they display superior binding affinity and reduced toxicity. Our work establishes ALA3 as a key mediator of PCZ-induced dwarfism and provides dual strategies--creating promising varieties through gene editing and developing targeted green pesticides--to reduce PCZ use. TeaserTargeting ALA3 reduces PCZ use through gene-edited varieties and green pesticides.

plant biology↗

bioRxiv2026

Gradient-specified optimization based on muscle surface mesh and moment arm as an effect-oriented approach of automated musculotendon path modeling

There is more to musculotendon path modeling than aligning a cable to reflect the geometric features of a musculotendon unit. From the perspective of simulation accuracy, the key is to replicate the length- and moment arm-joint angle relations of the target muscle. In this study, we propose an effect-oriented approach of automated path modeling, via hybrid calibration based on muscle surface mesh and moment arm. The task is formulated as a least-squares optimization problem with a threefold objective for the path to: (1) pass through multiple ellipses representing muscle cross-sections, (2) yield moment arms that match experimental measurements, and (3) yield moment arms in the expected functional directions. We demonstrate the performance of our optimization framework with the musculoskeletal surface mesh from the Visible Human Male and moment arm datasets from literature--producing 42 paths that are anatomically realistic and biomechanically accurate within 20.1 minutes. Our optimization framework is gradient-specified, which is faster and more accurate than using the default numerical gradient, making it applicable for large-scale subject-specific uses.

bioengineering↗

bioRxiv2026

Cardiac oxidative stress monitoring enabled by hierarchical mechanical adaptation

Soft bioelectronics have advanced cardiac monitoring through electrophysiological tracking, yet this alone cannot resolve the metabolic pathology essential to surgical decision-making. However, real-time molecular sensing on beating hearts remains unresolved due to deformation-induced sensor failure and stress-induced metabolite artifacts. This challenge is exemplified by ischemia-reperfusion injury (IRI), a major cardiac surgery complication characterized by reactive oxidative species (ROS) bursts, where true pathological ROS signals being confounded by mechanotransduction-induced ROS artifacts. Herein, we propose an enzymatic cardiac oxidative stress biosensor (E-cardiac) with hierarchical mechanical adaptation: macro-scale biofluid-mediated contact, micro-scale fiber reorganization, and nano-scale enzymatic confinement within gold nanoarches dissipate interfacial stress. This produces ultrathin ([~]460 nm), soft (0.79 kPa) E-cardiac with robust electrochemical stability (100% strain), low detection limit (380 nM), rapid adhesion (<3 s), stable biosensing on beating heart, as well as minimal invasive deployment capability. Mechanical analysis and cellular studies confirm mitigated stress-induced ROS and absent PIEZO channel activation. Validated across cardiomyocytes, ex vivo tissues, multi-species ischemia models (mouse, rat, rabbit, pig), rat ischemia-reperfusion injury, and Langendorff hearts simulating graded perfusion deficits, E-cardiac quantitatively differentiates IRI severity (sham < ischemia < reperfusion) as well as detecting the "ECG blind window". The E-cardiac platform provides real-time metabolic feedback for surgical guidance during cardiac procedures, enabling timely intervention before irreversible damage.

bioengineering↗

bioRxiv2026

Combination of engineered cell type-specific promoters and a high-efficiency AAV capsid restores hearing in adult DFNB1 mice model with demonstrated safety in nonhuman primate

A major challenge in gene therapy for GJB2-related hearing loss (DFNB1)--the most common form of hereditary deafness--is achieving efficient and precise connexin 26 delivery. Herein, we engineered two cell type-specific promoters (GJB2-1 and WFS1-2274) and developed an AAV capsid, AAV-MAS012, with enhanced transduction efficiency in mature cochlear cells. Our AAV-mediated gene therapy systems restored hearing of low-to-mid-frequencies in newborn Gjb2 cKO mice to wild-type levels and maintained for 45 weeks. Additionally, our therapeutic systems restored low-to-mid-frequencies hearing function to wild-type levels in adult Gjb2 cKO mice. A humanized version of the therapy, AAV-MAS012-WFS1-2274-hGJB2, rescued hearing function in two distinct Gjb2-deficient mouse models, and demonstrated a favorable safety profile in nonhuman primates. This study represents the first successful hearing restoration in adult Gjb2-deficient mice. The significant therapeutic efficacy of the humanized gene therapy system shows great potential for clinical translation in DFNB1 patients.

genetics↗

bioRxiv2026

Pseudomonas aeruginosa deploys competitor-specific antagonistic strategies

1Microbial competition shapes polymicrobial communities, yet it remains unclear whether bacteria deploy fixed or specific antagonistic strategies against different rivals. Here we show that Pseudomonas aeruginosa deploys distinct strategies to outcompete two clinically relevant species, Burkholderia cenocepacia and Staphylococcus aureus. Under matched conditions, competition with B. cenocepacia is mediated by contact-dependent Type VI secretion, whereas competition with S. aureus follows a staged diffusible program of alkyl quinolone-mediated growth inhibition followed by LasA-dependent lysis. Transcriptomic analysis supports a "Swiss Army knife" model of antagonism in which different competitive context triggers distinct subsets of P. aeruginosas arsenal. Minimal dynamical models verify that contact-dependent killing is effective against slower-growing competitors, whereas a staged strategy of growth inhibition followed by killing via diffusible factors is preferable against faster-growing rivals. Together, these results show that the competitive success of P. aeruginosa depends on competitor-specific antagonistic strategies.

microbiology↗

bioRxiv2026

A Brain-wide Neuronal Spiking and Behavior Dataset for Working Memory-Specific Activation and Reactivation in Mice

AbstractHow do millisecond-scale neural activities mediate multi-second behaviors such as working memory? This dataset provides brain-wide, high-spatiotemporal-resolution single-unit spiking activity recorded from 40 head-fixed mice performing an olfactory delayed paired-association (ODPA) task, encompassing 33,028 neurons across 62 anatomically defined brain regions. Utilizing this dataset enables the extraction of millisecond-scale within- and cross-region spike couplings enriched among memory-content-selective neurons. These couplings may be used to identify higher-order, hierarchically structured activity motifs. Because these multi-neuron patterns are captured both during active task performance and spontaneous inter-trial intervals, this dataset provides a resource for studying replay-related activity and for testing hypotheses about circuit-level processes associated with perceptual working memory. The dataset supports broad investigations into cross-regional spike organization, functional coupling, and temporal coding in working memory circuits.

neuroscience↗

bioRxiv2026

Dormant Bacteria's Fatal Attraction to RNA Bacteriophages

Phages are the most abundant biological entities on Earth, yet RNA phages are strikingly scarce compared to their DNA counterparts--a long-standing mystery in phage biology. Here, we use dsRNA phage phiYY as a model to demonstrate that while RNA phages efficiently infect growing bacteria, they are gradually eliminated inside dormant bacteria through weak and time-dependent ROS-mediated damage. The RNA phages decline over days rather than through immediate clearance inside dormant bacteria. Accordingly, scavenging ROS with mannitol or overexpressing ROS degradation enzymes AhpB/TrxB2 rescues RNA phages from elimination. Crucially, because the underlying ROS-mediated RNA damage is minimal, RNA phage survival hinges on genomic redundancy. In single-phage infections, the lone RNA genome is highly vulnerable to cumulative damage and is eventually inactivated. In contrast, during co-infection by multiple RNA phages, the presence of multiple genome copies provides functional redundancy, thereby allowing a fraction of RNA phages to survive inside dormant bacteria. Given that most environmental bacteria are dormant and subject to heterogeneous phage infection, this copy number-dependent vulnerability offers a possible explanation for the scarcity, but not perish, of RNA phages in nature.

microbiology↗

bioRxiv2026

Curvature-mediated prewetting organize mitochondrial nucleoid

The emergence of spatiotemporal order in diffusive cellular environments requires physical mechanisms to overcome the entropic drive toward disorder. While the organizing role of chemical signaling is well characterized, how complex membrane curvature regulate soluble molecular organization remains a fundamental open question. Here, we establish membrane curvature as a thermodynamic control parameter for the condensation of soluble proteins through prewetting. Using the mitochondrial transcription factor TFAM, we demonstrate that intrinsic membrane curvature locally drives a prewetting transitiona surface-mediated phase separation distinct from bulk condensation. By combining in vitro reconstitution, live-cell super-resolution imaging, cryo-electron tomography, and thermodynamic theory, we show that negatively high-curvature regions lower the nucleation energy barrier of Tfam, driving localized protein condensation at physiological concentrations. These results reveal that membrane curvature does not merely scaffold cellular machinery but manipulates the local free energy landscape, establishing a geometric principle for the spatial control of biological processes.

biophysics↗

bioRxiv2026

A critical role of epithelial MHCII in initiation of autoimmune tumorigenesis and sustaining premalignancy growth in the stomach

Autoimmunity is emerging as a new etiology for early-onset gastric cancer (GC). However, it remains unclear what molecular pathways drive the initiation and progression of autoimmune tumorigenesis. Given that Major Histocompatibility Complex Class II (MHCII) is the strongest genetic risk factor for many autoimmune diseases, we hypothesized that MHCII-mediated autoantigen presentation drives tumorigenic differentiation of epithelial cells. Here we show that epithelial MHCII, rather than MHCII from immune cells, plays an essential role in the initiation of autoimmunity-driven tumorigenic differentiation of gastric epithelial cells, which was characterized by increased expression of cancer-associated markers with immune-evasive and stem-like features that potentiate premalignant progression. In addition, we show that early gastric premalignancy is reversible upon the removal of epithelial MHCII. This study reveals that epithelial MHCII antigen presentation is essential in the early stages of autoimmune-driven gastric tumorigenesis and highlight epithelial MHCII as a potential biomarker or therapeutic target in early interventions of autoimmunity-driven cancer development.

immunology↗

bioRxiv2026

A conserved enhancer cluster regulates efnb2 expression in the vertebrate dorsal retina

The vertebrate retina is patterned along its dorsal-ventral (DV) axis by conserved signaling centers, yet the cis-regulatory architecture maintaining these territories remains unclear. Using the four-eyed fish Anableps anableps, which enables physical separation of dorsal and ventral retina, we integrated RNA-seq, ATAC-seq and Hi-C to map DV regulatory landscapes. We identify a 29-kb dorsal-enriched enhancer cluster within a gene poor region between efnb2a and gtpbp8, embedded in a conserved topologically associating domain spanning efnb2a-gtpbp8-slc10a2. Dorsal-biased chromatin contacts link this cluster to the efnb2a promoter. The orthologous human region contains a genome-wide significant association with retinal thickness (rs2575134; P = 2e-14). Leveraging the compact genome of Tetraodon nigroviridis, we cloned the orthologous interval and show that it drives dorsal retina-specific reporter expression in zebrafish and mouse. Together, these results identify an evolutionarily conserved regulatory domain controlling retinal axial identity and linking enhancer architecture to human ocular variation. Funding, National Science Foundation.

evolutionary biology↗

bioRxiv2026

Mechanical confinement drives monocyte-to-macrophage differentiation

Cells in vivo experience mechanically diverse microenvironments in which physical confinement is a pervasive but poorly understood regulator of their behavior and fate. Whether and how mechanical confinement governs immune cell differentiation remains unknown. Here, we reveal that a mechanical cue -- long-term confinement is sufficient to drive monocyte-to-macrophage differentiation through a mechanoepigenetic pathway. In vivo, differentiating monocytes exhibited flattened nuclei in the liver capsule, indicative of confinement by surrounding stromal and parenchymal structures. Using a custom cell confiner to recapitulate this confined niche, we found that confinement induces macrophage-like protrusive architectures, enhances motility, and upregulates macrophage-associated genes in RAW264.7 and THP-1 monocyte-lineage cells. Notably, extending this paradigm to primary murine bone-marrow, human umbilical-cord, and tissue-derived hepatic-associated monocytes yielded similar outcomes, thus enhancing phagocytic capacity, directly demonstrating that mechanical confinement can program monocytes into macrophages. Mechanistically, we found that confinement activates KDM6B, leading to H3K27me3 demethylation, which derepresses macrophage-specific transcriptional programs. Pharmacological inhibition of KDM6B with GSK-J4 restored H3K27me3 and blocked macrophage differentiation both in vitro and in vivo. These findings define a KDM6B-H3K27me3 axis that links nuclear mechanics to transcriptional reprogramming, positioning mechanical confinement as a "super-enhancer-like" cue for engineer macrophage function in therapeutic and bioengineering contexts.

cell biology↗

bioRxiv2026

Single-cell spatiotemporal transcriptomics reveals the developmental dynamics and regulatory network of poplar seed fibers

Poplar seed fibers cause environmental and health concerns, yet their developmental mechanisms remain poorly understood. Here, we constructed a high-resolution spatiotemporal transcriptomic atlas of female poplar capsules by integrating single-nucleus and spatial transcriptomics. We delineated the developmental trajectory of seed fibers, confirming their origin from placenta cells, and identified three functionally distinct fiber cell subtypes involved in initiation, metabolic support, and elongation. Weighted gene co-expression network analysis (WGCNA) identified several hub transcription factors, including PtoMYB, PtoHDT1, PtoEIF6 and PtoPDF2, that may serve as key regulators of fiber development. Our study provides a cellular-resolution framework for understanding trichome development in woody perennials and offers candidate targets for functional characterization toward breeding low-fluff poplar cultivars. HighlightsO_LIA spatiotemporal transcriptomic atlas of poplar capsule development is constructed at single-cell resolution C_LIO_LIFiber cells originate from placenta cells and comprise three functionally distinct subtypes C_LIO_LIProvides molecular targets for breeding low-fluff poplar cultivars to mitigate environmental pollution C_LI

plant biology↗

bioRxiv2026

ClumPyCells resolves spatial aggregation in complex tissues overcoming size biases

The spatial arrangement of cells within a tissue microenvironment shapes their interactions and cell states, which are essential for tissue development, homeostasis, and disease. Spatial -omics technologies can precisely map the location of each cell within complex tissue structures, while also profiling their protein content and transcriptional diversity. Various approaches have been developed to analyze spatial patterns of cell aggregation, repulsion, or random distribution within tissues. However, differences in cell morphology within a tissue can introduce significant bias. Cell size in particular is not accounted for and introduces challenges when quantifying the aggregation of cells or their molecular features. To overcome such limitations, we present ClumPyCells: a statistical framework that measures cell and marker aggregation within tissue while correcting for size morphology. ClumPyCells enables interpretation of cell aggregation, bypassing interfering cell types or tissue regions unrelated to the desired spatial correlation. We demonstrate the capabilities of ClumPyCells across several tumor types, including melanoma and colorectal cancer, and spatial -omics technologies such as spatial transcriptomics and proteomics, while benchmarking how cell-size differences contribute to misinterpretations. By correcting for disruptive cell types within a region of interest, ClumPyCells will determine new tissue patterns and structures without morphological interference.

bioinformatics↗

bioRxiv2026

EthoClaw: An Integrated AI Workflow Platform for Automated Analysis in Neuroethology

Computational methods have advanced the analysis of animal behavior, yet significant challenges remain in data standardization, analytical reproducibility, and workflow integration. Existing computational solutions often demand extensive programming proficiency or compel users to navigate a highly fragmented ecosystem of disconnected tools for tracking, statistical analysis, and visualization. Here, we present EthoClaw, an open-source, artificial intelligence-driven workflow platform built upon the OpenClaw agentic framework, functioning as a locally deployable AI assistant for behavioral research. EthoClaw provides an integrated computational infrastructure that seamlessly bridges the gap between raw behavioral video acquisitions and publishable scientific results. In this study, we demonstrate the platforms capacity to natively ingest video data via a dual-mode tracking architecture: utilizing ultra-fast image processing for rapid object detection, and leveraging the SuperAnimal methods for precise, markerless postural tracking. To ensure maximal interoperability, EthoClaw automatically converts various tracking data formats into DeepLabCut-compatible formats, enabling high-throughput phenotyping by generating publication-quality visualizations alongside rigorous multidimensional statistical profiling. Furthermore, the platform incorporates a large language model (LLM)-driven reporting module that dynamically synthesizes analytical documents, ensuring methodological transparency. Through an open field test, we validate the practical usability of EthoClaw while accelerating computational throughput by localizing heavy video processing to circumvent cloud bandwidth bottlenecks. Operating via an omnichannel natural language interface that integrates seamlessly with ubiquitous instant messaging software, EthoClaw democratizes advanced computational behavioral analysis, offering a holistic, highly efficient ecosystem that enforces experimental reproducibility and open science principles.

animal behavior and cognition↗

bioRxiv2026

Keeping time with the host: reconstructing the developmental rhythms of malaria parasites

Theory predicts that pathogenic organisms benefit from aligning to host circadian rhythms, but observable data provide an incomplete picture of infection rhythms. Models are needed to reconstruct unobservable dynamics and uncover fitness impacts, challenges typified in malaria infections. Malaria parasites often synchronize their development to multiples of 24 hours and reschedule their developmental rhythms following perturbation. Yet it remains uncertain how parasites reschedule--including any cost to parasite multiplication rates--due to the diffculty of detecting parasites in all phases of their development. As parasites mature, the red blood cells they occupy adhere to blood vessel walls (sequestration, an immune evasion tactic) where they cannot be readily sampled. Existing methods cannot determine sequestration timing in vivo nor how that timing varies when misaligned to within-host environments. To address these challenges, we fit a mathematical model tracking parasite development and sequestration to high-resolution time series from the rodent malaria parasite Plasmodium chabaudi. We show that parasites hasten late development--but not sequestration--to realign with host rhythms. That rescheduling reduces multiplication rates, a result only apparent from model-reconstructed dynamics. Our novel approach recovers the timing of development and sequestration, providing insight into the consequences of circadian rhythms for parasite fitness.

ecology↗

bioRxiv2026

Decoding Immunomodulatory Hydrogels for Arthritis: Comparative Insights from Predictive Machine Learning and Large Language Models

Hydrogels are increasingly recognized as promising therapeutics for arthritic joints, extending their traditional role as mechanical lubricants to modulators of joint immunity. However, the rational design of these materials remains challenging, with progress largely driven by empirical experimentation. To address this, we curated a comprehensive database of 220 hydrogel formulations from 317 published studies and applied an interpretable machine learning (ML) framework to uncover the relationships between hydrogel design parameters and the arthritis severity score. Using a Random Forest algorithm, our model achieved an external validation accuracy of 0.67 in predicting effective hydrogel therapies for arthritis. Analysis revealed a clear hierarchy of design principles: the choice of functional agent, base polymer, and elastic modulus were the most influential predictors of therapeutic efficacy, with composite agents, protein-based polymers, and softer hydrogels most strongly associated with positive therapeutic outcomes. Mechanistic investigations further demonstrated that successful hydrogels promote an anti-inflammatory M2 macrophage phenotype. Benchmarking against classical statistical methods and a large language model framework showed that our ML approach provided more robust, nuanced insights into complex feature interactions. This data-driven framework offers a generalizable blueprint for the rational design of next-generation immunomodulatory hydrogels, paving the way for more effective arthritis therapies.

bioengineering↗

bioRxiv2026

Spatial multi-omics of multiple myeloma uncovers niche-dependent pro-myeloma and immunosuppressive signaling in the bone marrow and extramedullary lesions

Multiple myeloma (MM) is a plasma cell malignancy shaped by dynamic interactions between MM cells and non-malignant cells in the immune microenvironment. To spatially profile the influence of cellular context on MM and immune cell expression, we developed a multimodal framework integrating 10x Genomics Visium HD, 10x Genomics Xenium, and clinically annotated single-cell RNA (scRNA-seq) sequencing datasets. Visium HD enabled unbiased, whole transcriptome, spatial discovery at 16 {micro}m resolution, Xenium provided orthogonal validation at single-cell resolution, and scRNA-seq extended findings by mapping spatial labels and leveraging the greater sequencing depth. We developed a custom framework for cell type annotation within Visium HD spatial bins. Our approach enabled identification of plasma cell-dense niches enriched for non-canonical Wnt signaling, associated with gene expression supporting cell adhesion mediated drug resistance, inferior progression-free survival, and extramedullary lesions. Immune cells within these neighborhoods exhibited suppressed transcriptional states, including increased inhibitory receptor expression such as LAG3. Utilizing the niche-driven transcriptional states in MM and immune cells, we were able to develop a 15-gene signature independently predictive of progression free survival (HR = 2.00, p < 0.0001). Collectively, this study demonstrates the potential of integrated spatial and single-cell transcriptomics to define niche-specific programs supporting MM progression.

cancer biology↗

bioRxiv2026

Comprehensive bioinformatic analysis reveals novel potential diagnostic biomarkers associated with monocytes in osteoporosis

Osteoporosis affects millions of women globally. In this study, we applied bioinformatics methods to screen for novel diagnostic biomarkers of osteoporosis in women using the GSE62402 and GSE56814 datasets. PCSK5, ZNF225, and H1FX were used to construct a diagnostic model. ROC, calibration, and decision curve analyses were performed to assess the diagnostic performance on the training (GSE56814) and external (GSE56815) datasets. The expression level of model genes was validated in GEO datasets. Furthermore, five transcription factors (ETS1, NOTCH1, MAZ, ERG, and FLI1) were identified as common upstream regulators of model genes. PCSK5, ZNF225, and H1FX serve as novel diagnostic biomarkers, providing new insights into the pathogenesis of and treatment strategies for osteoporosis in women.

genetics↗