Biology subjects

Zhou, B.

Publications and source records attributed to Zhou, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Building virtual cell dynamics that evolve with biological measurements

Virtual cell models built from single-cell measurements need to predict how cells change over time, but new biological measurements often reveal dynamical relationships that existing models cannot express. Translating such measurements into dynamics therefore requires deciding what biological relation should be modeled, where it should enter the formulation and how its recovery should be validated. Here we present CellCompass, an agentic AI system that couples a scientific agent with an extensible dynamical engine for modeling state transitions and population change, along with fate and molecular readout. CellCompass reuses existing formulations when sufficient and designs, implements and refines new ones when experimental measurements introduce additional constraints. To assess this capability, we developed DynBench100, a benchmark of 100 simulated single-cell time-course scenarios with hidden dynamical ground truth. CellCompass achieved the highest aggregate performance among the tested general-purpose and biomedical agents across six dynamical tasks. Across four real single-cell studies, it retained an existing velocity-growth model to reconstruct context-dependent epithelial-mesenchymal transition and developed three new dynamical formulations for distinct experimental measurements. In drug-response data, incorporating metabolic RNA labeling reduced pulse-control identifiability error by 31.1%, revealing staged response programs and generating testable predictions for perturbing a candidate adaptive program. In hematopoietic lineage tracing, incorporating clonal barcodes improved clone-fate agreement by 54% over the strongest dynamical baseline, identifying early lineage priming among transcriptionally similar progenitors. Finally, in time-resolved CITE-seq data, CellCompass reduced future surface-protein distribution error by 13.2% for RNA-initialized trajectories, uncovering lineage-specific temporal offsets between transcriptional and protein programs. Together, CellCompass provides a framework in which virtual-cell dynamics can expand with the biological measurements used to constrain them.

bioinformatics↗

bioRxiv2026

Cortex-wide single-cell activity mapping in freely moving mice

How the cortex supports complex, naturalistic behavior can be revealed only in freely moving animals. Although head-mounted microscopes promise access to the neural dynamics underlying such behavior, fundamental trade-offs among field of view, spatial resolution, device weight, and background contamination have prevented cortex-wide single-neuron recording, leaving distributed cortical coordination largely inaccessible. To meet these challenges, we introduce COMET (Cortex-wide Observational Miniature Epifluorescence Technique), a 3.75-g head-mounted mesoscope that integrates an aberration-controlled wide-field optical design, uniform high-efficiency excitation and single-coaxial power-and-data transmission with an end-to-end denoising and signal-extraction pipeline. This enables cortex-wide calcium imaging at single-cell resolution in freely moving mice. COMET captures activity from >15,000 layer 2/3 neurons per 5-min recording over fields of view up to 10 mm in diameter while preserving natural behavior. Benchmarking against benchtop two-photon microscopy demonstrates high spatial concordance of detected neurons and matched event-level calcium dynamics. We apply COMET to social interaction to quantify region-specific engagement and to an auditory trace fear-conditioning task that requires natural movement and behavioral expression, revealing time-ordered changes in regional firing-rate structure and functional connectivity preceding a global conditioned response. COMET provides an open, lightweight hardware-software framework for linking single-neuron activity to cortex-scale network dynamics during freely expressed behaviors under changing internal or external conditions.

neuroscience↗

bioRxiv2026

Vritra: gene-specific reference construction for species-resolved functional profiling of metagenomic and metatranscriptomic data

Species-resolved profiling of microbial functional genes is important for linking microbial community composition to biological function, but existing functional profiling approaches are not designed to systematically define user-specified genes and resolve their contributing species. We developed Vritra (Versatile gene-guided Reads-identification with Impartial Taxonomic Refinement and Assignment), a framework for constructing gene-specific reference databases for metagenomic and metatranscriptomic data. Vritra expands and refines the UniRef-based sequence space for user-specified target genes using sequence-similarity network connectivity and functional annotations, retains related homologs as decoys to reduce assignment ambiguity, and links the resulting sequences to standardized microbial taxonomy. Across genes involved in oxalate, urate, and bile acid metabolism, Vritra recovered >97% of sequences represented by established annotation resources for most evaluated genes while substantially expanding the represented sequence space. In real microbiome datasets, the expanded references increased recovery of target-gene reads by up to threefold for poorly annotated genes while maintaining high sequence identity. Application to population-based and publicly available microbiome datasets enabled species-resolved profiling of functional genes and revealed gene-specific associations with microbial taxa, dietary factors, and disease-related phenotypes. Vritra provides a scalable framework for translating continuously expanding sequence resources into gene-specific, species-resolved references for microbiome studies.

bioinformatics↗

bioRxiv2026

Pressure-induced membrane tension mechanically opens the germinant receptor GerA ion channel to trigger bacterial spore germination

High pressure (HP) can trigger bacterial spore germination, acting either through germinant receptors (GRs) or the SpoVA channel. However, the mechanism by which HP activates these membrane-embedded proteins remains elusive. Here, using Bacillus subtilis, we demonstrate that the GerA germinant receptor (GR) is the primary target of moderate HP (50-300 MPa). Mutagenesis reveals that pore-lining residues within the GerA ion channel are essential for the pressure response, whereas canonical ligand-binding and intramembrane signaling residues are dispensable. We then propose a s tretch- t o- o pen (STO) model, in which HP differentially compresses the more compliant inner membrane (IM) relative to the rigid spore core, generating lateral membrane tension that promotes opening of the GerA channel. In situ membrane tension measurements indicate HP-induced compression of IM phospholipids and elevated membrane tension. This tension-dependent gating is further supported by the pressure-dependent phenotypic rescue of GerA channel mutants. Consistently, HP increases IM permeability to water-soluble and membrane-impermeable agents (propidium iodide and formaldehyde), an effect potentiated by GerA, indicating concomitant opening of GerA by HP. Furthermore, modulating IM fluidity via heat activation or decoating altered membrane physical properties and delayed HP-induced germination, establishing the IM as the critical mechanical transducer. Additionally, computational modeling and calculations support faster compression of the IM than of the core under HP, rationalizing the source of tensile stress. Together, our findings establish a novel mechanism of HP-induced GerA activation via the STO model: HP compresses the IM, generates lateral tension, and promotes opening of the GerA ion channel to trigger bacterial spore germination.

microbiology↗

bioRxiv2026

Reprogramming VHL with molecular glues enables selective degradation of caspase-2

Molecular glue degraders (MGDs) reprogram E3 ligases to eliminate neosubstrates, yet their application has largely been confined to CRBN. Here, we identify caspase-2 as a new neosubstrate for von Hippel-Lindau (VHL), expanding the scope of VHL-based MGDs. Guided by a focused VHL ligand library design, we employed TurboID-based proximity labeling to discover stereoisomeric compounds (dCASP2-1 and dCASP2-2) that selectively recruit caspase-2 to VHL and promote its ubiquitin-proteasome system-dependent degradation. Further structure-activity relationship (SAR) studies yielded dCASP2-3 and dCASP2-4, which enhanced degradation potency (by 622-fold relative to dCASP2-1) and abolished enantioselectivity. Mechanistic mapping localized the degrader-induced interface to a two-helix region of the caspase-2 CARD domain, with residues H33, P34, and D100 essential for VHL engagement. Degron-guided computational modeling of the VHL/MGD/caspase-2 ternary complex provided structural insight into neosubstrate recognition. Together, we report the development of VHL molecular glues that selectively and potently degrade caspase-2, offering chemical probes to interrogate its functions in apoptosis and stress responses, while broadening the substrate landscape of VHL-based MGDs.

biochemistry↗

bioRxiv2026

CENO: A Genome-Scale World Model for Evolutionary Sequence Interpretation and Programmable Regulatory Design

DNA encodes biological function across a continuum of sequence scales, from single-nucleotide and motif-level grammar to regulatory neighborhoods, chromatin-scale organization and evolutionary constraint. A useful model of genomes should therefore do more than classify short sequence windows: it should maintain nucleotide-resolution state over long contexts, score counterfactual mutations, condition on homologous sequence evidence and generate candidates that can be evaluated against structural or functional objectives. We define such a system operationally as a genomic world model: a general-purpose generative model of genome sequence space that unifies sequence understanding and sequence design through a shared state and likelihood interface. Here we introduce CENO, a family of long-context generative genomic world models designed to preserve local DNA grammar while extending usable context to regulatory and chromatin scales. CENO combines Mamba sequence-mixing layers, sparse attention layers and mixture-of-experts capacity in a single autoregressive backbone, and is trained at 300M, 600M and 1B parameter scales with a staged curriculum that progresses from 8k-token cross-domain genomic pretraining to 131k- and 1M-token whole-genome long-context continuation. We evaluate CENO under a unified world-model benchmark paradigm spanning retrieval, representation, counterfactual perturbation, reconstruction, evolutionary conditioning and design. CENO retains practical long-context inference and retrieves distal sequence in synthetic assays. In zero-shot long-context analyses, without task-specific fine-tuning, long-context continuation yields annotation- and chromatin-boundary-associated attention patterns and frozen-state representations that generalize across human cell types and mouse cell or tissue settings. To incorporate evolutionary information, we further post-train CENO on packed real multiple-sequence-alignment contexts and score variants by reference-mutant likelihood deltas, improving matched variant-effect prediction and producing evolutionary enrichment signals across species. Complementing these perturbation-based variant tests, we evaluate zero-shot long-sequence generation by partial-gene continuation, asking whether the model can recover withheld gene-scale sequence structure across eukaryotic, bacterial and archaeal species; recovery improves with model scale and later whole-genome long-context training. Finally, we use CENO as the backbone for a cell-type-specific enhancer design workflow in mouse cortex, coupling a CENO-based accessibility oracle with conditional supervised fine-tuning and oracle-guided reinforcement learning. Together, CENO provides a genome-scale sequence world-model framework for sequence interpretation, evolutionary reasoning, gene-scale reconstruction and programmable regulatory sequence generation.

genomics↗

bioRxiv2026

Computational reconstruction of hierarchical cis-regulatory networks reveals synergistic transcription control and disease-associated rewiring

Gene regulation emerges from coordinated interactions among dispersed cis-regulatory elements, yet how these elements integrate into functional regulatory networks and collectively regulate gene transcription remains poorly understood. Here, we present ORIGAMI, a multi-omics, gene-centric deep learning framework that reconstructs functional cis-regulatory networks constrained by transcriptional output. ORIGAMI formulates cis-regulatory modeling as a latent graph inference task, which integrates DNA sequence, epigenomic signals, and three-dimensional chromatin priors to infer denoised regulatory graphs that capture functional interactions rather than structural proximity alone. The inferred regulatory graphs exhibit distinct topological regimes, where hierarchical and modular organization encodes cell-state-specific functional demands and enables synergistic transcriptional control. Furthermore, we show that these regulatory architectures undergo measurable state-dependent rewiring across disease contexts. Finally, ORIGAMI accurately predicts the transcriptional consequences of both cis- and trans-regulatory perturbations and links the rearrangement of regulatory architecture to perturbation response. Together, ORIGAMI advances a network-based view of gene regulation and establishes a foundation for virtual cell modeling of regulatory dynamics.

bioinformatics↗

bioRxiv2026

Experiment-free learning of exoskeleton assistance is not an unsolved problem

We present three quantitative methods: 1) estimation of exoskeleton mechanical power and energy ratio from published data, 2) a systematic review of the exoskeleton literature on reported energy ratios, and 3) timing correction analysis of the replication experiment, to address concerns raised by Collins et al. (2026) about Luo et al. (2024). Together, these analyses support the reported metabolic reductions and the validity of exoskeleton control via learning in simulation. The critique rests on an unsupported premise: that exoskeleton energy ratios above 4 are physiologically implausible. This premise of Collins et al. (2026) is not supported by the cited evidence, and the error originates in their own cited source. Sawicki and Ferris (2009), the paper they invoke as authority for the limit of 4, state explicitly that "reported values of the muscular efficiency range from 0.10 to 0.34, with many sources assuming an average of [~]0.25." The value of 4 corresponds to this average, it is not a physiological ceiling. Treating an average as a physiological upper limit is a fundamental error. The published exoskeleton literature further contradicts the claim, including work by the authors of the critique themselves (Collins et al., 2015: 4.3; Young et al., 2017: 5.0) and independent work (Malcolm et al., 2013: 4.8; Seo et al., 2017: 6.7). In contrast, our walking energy ratio is 2.4, calculated directly from Fig. 4 of our paper. Our device delivers higher peak torque (14.1 Nm vs. 10.9 Nm, Lim et al., 2019) and achieves a slightly larger metabolic reduction (24.3% vs. 21%). Independent groups have since demonstrated meaningful metabolic reductions using learning-in-simulation frameworks, including Barati et al. (2026, 15.2% mean and 22.5% maximum) and Zhou et al. (2025, [~]20% during running). The claim of Collins et al. (2026) that this problem "remains unsolved" is directly contradicted by these independent results. The experiment in the critique is not a valid replication of our method. Our controller is a neural network with [~]10,000 parameters learned through deep reinforcement learning in musculoskeletal simulation; the critique instead applies a pre-programmed fixed torque curve with no learnable parameters. Beyond this, the replication contains three methodological errors: 1) a heel-strike timing assumption producing offsets up to 30% of the gait cycle; 2) an averaged torque profile that discards subject-specific control; and 3) a device [~]50% heavier than ours (4.8 kg vs. 3.2 kg) without measuring the metabolic penalty of the added weight. The critique also misreports Samsung data, with reported values approximately double those in the original publication, errors that directly underpin their physiological limit argument.

bioengineering↗

bioRxiv2026

Cardiomyocytes Undergo a Mesenchymal-Like Fate Transition in Myocardial Fibrosis

BACKGROUNDMyocardial fibrosis, a pathological hallmark of adverse cardiac remodeling and heart failure, has been conventionally attributed to the activation of resident fibroblasts. Although recent studies suggest contributions from non-fibroblast lineages, direct in vivo genetic evidence that cardiomyocytes can undergo a mesenchymal-like fate transition during myocardial fibrosis remains absent. This study aims to investigate whether such a transition occurs and to elucidate the underlying regulatory mechanisms. METHODSHuman myocardial infarction (MI) tissues were analyzed by immunohistochemistry and integrated with public single-nucleus RNA sequencing (snRNA-seq) data to detect mesenchymal-like signatures in cardiomyocytes. Genetic lineage-tracing was performed in MI mice, and in cardiomyocyte-specific Hgs (hepatocyte growth factor-regulated tyrosine kinase substrate) gene knockout mice, to map the fate of cardiomyocyte-derived cells. Mechanistic insights were obtained through proteomic and snRNA-seq analysis of Hgs knockout hearts and validated through gain- and loss-of-function experiments targeting Aldh1a2 (aldehyde dehydrogenase 1 family member A2). RESULTSIn human MI samples, a subset of cardiomyocytes showed reduced expression of cardiomyocyte markers concurrent with acquisition of mesenchymal-associated markers. Genetic lineage tracing demonstrated that adult cardiomyocytes can adopt a mesenchymal-like cell fate during post-MI remodeling. We identify HGS as a factor constraining this transition. Hgs knockout in adult cardiomyocytes upregulated Aldh1a2, triggered the mesenchymal-like fate transition, and gave rise to cells expressing markers of activated fibroblasts or osteoblasts, accompanied by pronounced myocardial fibrosis and calcification. Forced Aldh1a2 overexpression in cardiomyocytes drove the mesenchymal-like fate transition in vitro and in vivo, whereas Aldh1a2 deletion in cardiomyocytes mitigated MI-induced myocardial fibrosis. CONCLUSIONSThis study provides in vivo genetic evidence that adult cardiomyocytes possess the capacity to undergo a mesenchymal-like fate transition under pathological conditions. Our data suggest that HGS and ALDH1A2 serve as regulators of the transition, offering a new basis for understanding cellular and molecular mechanisms of myocardial fibrosis. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABSO_LIMyocardial fibrosis is primarily driven by resident fibroblast activation, with additional contributions from cardiac CD34+ cells, pericytes, and macrophages. C_LIO_LIAdult cardiomyocytes exhibit phenotypic plasticity and transdifferentiate into epicardial-like or pacemaker cells under specific conditions. C_LI What New Information Does This Article Contribute?O_LIA subset of cardiomyocytes adopts a mesenchymal-like cell fate during myocardial fibrosis, marked by downregulation of cardiomyocyte identity markers and loss of aligned cell-cell contacts. C_LIO_LIThese cells acquire mesenchymal morphology and markers, ECM components, migratory gene signatures, and proliferative capacity. C_LIO_LIHGS and ALDH1A2 act as regulators of this mesenchymal-like fate transition. C_LI Myocardial fibrosis drives heart failure progression, yet the cellular sources of pathological fibroblasts remain incompletely defined. Here, we demonstrate that a subset of cardiomyocytes adopts a mesenchymal-like cell fate during myocardial fibrosis by using an integrated approach combining human MI samples, murine genetic lineage tracing, and snRNA-seq. Mechanistically, we identify HGS and ALDH1A2 as regulators of this transition. Cardiomyocyte-specific Hgs deletion upregulates Aldh1a2, triggering the mesenchymal-like fate transition. Furthermore, Aldh1a2 overexpression drives this transition, while its deletion attenuates MI-induced fibrosis. These findings reveal a previously unrecognized plasticity of adult cardiomyocytes and identify potential therapeutic targets for fibrotic heart disease.

genetics↗

bioRxiv2026

RAI1 safeguards fidelity and tempo of human neurodevelopmental gene expression

Human brain development proceeds on an unusually long timeline relative to other species, a feature that is thought to foster advanced cognitive abilities. The Retinoic Acid Induced 1 (RAI1) gene encodes a nucleosome-binding protein, and its haploinsufficiency is responsible for Smith-Magenis Syndrome (SMS), a neurodevelopmental disorder characterized by cognitive impairment with autistic features. However, the role of RAI1 in human neurodevelopment remains unexplored experimentally. Here, we generated isogenic heterozygous and homozygous RAI1 loss-of-function human embryonic stem cell lines and interrogated the roles of RAI1 in neurodevelopmental gene regulation. A longitudinal transcriptome analysis during in vitro cortical development revealed that RAI1 deficiency accelerates the progression of developmental gene expression. Single-cell RNA-seq analysis revealed that RAI1-deficient neuroprogenitors acquire a transient mesoderm-like gene expression signature, followed by a pro-neuronal maturation signature in postmitotic neurons. Unexpectedly, the developmental acceleration signature was exacerbated during NGN2-induced excitatory neuron differentiation, isolating the roles of RAI1 in neuronal differentiation from non-neuronal functions. Together, these results identify RAI1 as a suppressor of the mesodermal lineage program and as a brake that slows the tempo of human neurodevelopmental gene expression.

neuroscience↗

bioRxiv2026

Desert hedgehog enhances endothelial resilience and prevents atherosclerosis by mitigating PAI-1 signaling

BACKGROUNDAtherosclerotic cardiovascular disease remains the leading cause of death worldwide. Most current pharmacotherapies target conventional risk factors that promote atherosclerosis (e.g., hyperlipidemia) rather than intrinsic resilience factors that protect against atherosclerosis in the face of risk factors. Here, we investigated the role of desert hedgehog (DHH), a canonical ligand of the hedgehog signaling pathway, as a novel resilience factor that restrains endothelial mesenchymal transition (EndoMT) and protects against atherosclerosis. METHODSSingle-cell RNA sequencing (scRNA-seq) was performed on atheroprone and atheroprotective regions of the ApoE knockout mouse aorta to identify mechanoresponsive genes associated with atherosclerosis. Endothelial cell-specific Dhh knockout mice were subjected to partial carotid ligation and hypercholesterolemic conditions to investigate the role of endothelial Dhh in atherosclerosis progression. scRNA-seq, bulk RNA sequencing, endothelial lineage tracing, immunoprecipitation-coupled mass spectrometry, and surface plasmon resonance were used to in-vestigate the role and mechanism of DHH in EndoMT. Pharmacological interventions and recombinant DHH administration were performed in vivo to evaluate therapeutic potential of DHH targeting. DHH expression was also examined in human atherosclerotic arteries and serum samples from patients with coronary artery disease. RESULTSDHH protein expression was enriched in arterial endothelium from mice, porcine, and humans. However, DHH expression was significantly reduced in atherosclerotic arteries and serum from patients with coronary artery disease. scRNA-seq of atheroprone and atheroresistant region of mouse aorta identified Dhh as a novel mechanoresponsive gene enriched in aortic regions exposed to unidirectional laminar flow. Endothelial cell-specific Dhh knockout (DhhecKO) mice exhibited increased atherosclerotic lesion area, large necrotic cores, and reduced collagen content following partial carotid ligation. Similarly, under hypercholesterolemic conditions, both male and female DhhecKO mice showed aggravated atherosclerosis progression. scRNA-seq of DhhecKO mouse aortas revealed an increased proportion of endothelial cells undergoing mesenchymal transition, indicating enhanced EndoMT. These findings were corroborated by bulk RNA-sequencing of DHH depleted HUVECs and endothelial lineage tracing in inducible DhhecKO mice. Mechanistically, DHH directly interacted with plasminogen activator inhibitor type 1 (PAI-1) and suppressed PAI-1-induced EndoMT. PAI-1 promoted EndoMT in ECs through activation of canonical TGF-{beta} signaling (SMAD2/3) and noncanonical AKT/ERK1/2 signaling via interaction with low-density lipoprotein receptor-related protein (LRP1). Neutralization of PAI-1 or inhibition of LRP1, AKT/ERK1/2, or SMAD3 signaling abolished DHH deficiency-induced EndoMT. DHH competitively inhibited PAI-1 binding to LRP1, thereby attenuating downstream pro-EndoMT signaling. Intriguingly, treatment with PAI-1 inhibitor TM5275 mitigated endothelial Dhh deficiency induced EndoMT in vivo. Of translational relevance, recombinant mouse DHH protein administration reduced atherosclerosis progression, stabilized plaque, and decreased the expression of EndoMT markers in ApoE knockout mice. CONCLUSIONSDesert hedgehog (DHH) is an intrinsic endothelial cell-enriched resilience factor that protects against EndoMT and atherosclerosis by preventing PAI-1 signaling. The present study implicates endothelial DHH as a potential therapeutic target for atherosclerotic cardiovascular disease. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=163 SRC="FIGDIR/small/729715v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@194c8a3org.highwire.dtl.DTLVardef@1004d52org.highwire.dtl.DTLVardef@d47c73org.highwire.dtl.DTLVardef@368866_HPS_FORMAT_FIGEXP M_FIG C_FIG Desert hedgehog (DHH) is an intrinsic endothelial cell-enriched resilience factor that protects against EndoMT and atherosclerosis by preventing PAI-1 binding to LRP1 and downstream AKT/ERK, as well as SMAD2/3 signaling. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSO_LIDHH was identified as a flow-responsive resilience gene that is downregulated by disturbed flow in endothelial cells. C_LIO_LIEndothelial-specific deletion of Dhh promoted endothelial-to-mesenchymal transition (En-doMT) and atherosclerosis. C_LIO_LIDHH directly interacts with PAI-1 and preclude PAI-1 mediated pro-EndoMT signaling. C_LI What Are the Clinical Implications?O_LIDHH maintains endothelial homeostasis during atherosclerosis. C_LIO_LITargeting endothelial DHH-PAI-1 axis may represent a potential therapeutic strategy to reduce EndoMT and limit plaque progression. C_LIO_LILower circulating DHH level may serve as a potential biomarker of endothelial dysfunction and plaque vulnerability in atherosclerotic disease. C_LI

biochemistry↗

bioRxiv2026

DOC Release and Physiological Response of Zostera marina Under Light and Nutrient Gradients

The seagrass bed, known as an important blue carbon ecosystem, not only has robust carbon sequestration capacity, but also releases the fixed organic carbon into the water column in the form of dissolved organic carbon (DOC). Zostera marina is the main constructive species of the seagrass meadows of northern China, but the regulatory mechanism of its DOC release in response to environmental changes still remains unclear. Adult Z. marina was used as the experimental material in this research to investigate the effects of light intensity and nutrient concentration on its DOC release, and to observe its physiological responses. By using a total organic carbon (TOC) analyzer, dissolved oxygen monitoring, transmission electron microscopy (TEM), and transcriptome analysis, we explored how light and nutrients affect DOC release and the underlying physiological mechanisms in Z. marina. The results showed that both elevated light intensity and short-term nutrient enrichment promoted organic carbon release from Z. marina to the environment. Increased light enhanced the net primary productivity (NPP) of Z. marina, while the magnitude of DOC release increased more than NPP itself. Nutrient enrichment reduced NPP while raising the proportion of DOC released by Z. marina. Transcriptome analysis showed that nutrient enrichment significantly affected pathways, including flavonoid biosynthesis and fatty acid degradation. This study demonstrated that changes in light and nutrients can significantly influence DOC release and carbon allocation patterns in Z. marina, providing a theoretical basis for blue carbon accounting and ecological restoration evaluation in seagrass beds.

plant biology↗

bioRxiv2026

A Continuum of Atrial Peristalsis Initiates the Bicuspid to Quadricuspid Valve Transition

How chamber-specific hemodynamic shear forces coordinate the spatial and temporal patterning of cardiac valves remains poorly understood. The zebrafish atrioventricular (AV) valve transitions from 2-cusp to 4-cusp at 14 days post-fertilization (dpf) through commissural remodeling, differential cell proliferation, and chondrogenic matrix secretion. Orthogonal valvular axes are present at 25 hpf (hours), preceding endocardial cushion formation. AV canal remodeling aligns the shear stress with leaflet formation at 48 hpf and 14 dpf. At 28 hpf, the ventricle develops functional syncytium, while the atrial peristalsis remains and is necessary for the Klf2a-Snai1b signaling in Notch-negative and ccm1-positive endocardial cells. Without atrial contraction, the 2-to 4-cusp transition (86.7%) fails to occur. In the absence of ventricular contraction and relaxation, the formation of the first pair of leaflets (100%) does not initiate. As a corollary, we demonstrate that KLF4/SNAI1 expression at the commissure is conserved in the mammalian AV 2- to 4-cushion transition.

developmental biology↗

bioRxiv2026

A three-dimensional carbon-nutrient functional balance model explains the formation of Root Economics Space

Root carbon (C)-nutrient functional balance underpins root economic strategies, yet previous models neglected the root-length dimension. Here, we develop a three-dimensional C-nutrient functional balance model for first-order roots that explicitly incorporates root length, and validates it using a global root trait dataset. For subtropical woody species, root cortex volume x root length scaled isometrically with the fourth power of stele diameter (slope{approx}1.0), supporting the model. Herbaceous species from the Qinghai-Tibetan plateau showed a significantly lower slope (0.61), likely due to extreme environmental impacts on transport or metabolism. Woody species preferentially invest in cortical area (thicker roots), supporting mycorrhizal symbiosis, whereas herbaceous species favor root length extension for autonomous soil exploration. By integrating root length, this model provides a novel mechanistic explanation for the formation of both the collaboration and conservation axes within the root economics space, advancing the theoretical framework of root functional strategies.

ecology↗

bioRxiv2026

Defects in CD8+ T cell suppression by Foxp3-ΔE2 expressing regulatory T cells

AbstractRegulatory T cells (Tregs) prevent autoimmunity through suppressive functions largely programmed by the transcription factor FOXP3. Healthy humans express approximately equivalent levels of two major alternatively spliced isoforms of FOXP3: a full-length version containing all coding exons (FOXP3-FL) and a version lacking exon 2 (FOXP3-{Delta}E2). However, sole FOXP3-{Delta}E2 expression causes lethal IPEX syndrome, and the FOXP3-{Delta}E2 isoform is elevated in several autoimmune diseases. These observations strongly suggest defects in suppression by FOXP3-{Delta}E2 Tregs which we investigated here using Foxp3-{Delta}E2 mice. In an influenza virus infection model, Foxp3-{Delta}E2 mice had an increased magnitude of the CD8+ T cell response during acute and memory formation phases of infection. Transcriptomic and chromatin accessibility analyses of homeostatic Foxp3-{Delta}E2 Tregs revealed impaired Treg programming, including reduced expression of inhibitory molecules such as Il2ra and chemokine receptors. Decreased cell surface CD25 expression on Foxp3-{Delta}E2 Tregs was associated with reduced IL-2 responsiveness in Foxp3-{Delta}E2 Tregs and, reciprocally, increased IL-2 responsiveness in CD8+ T cells from Foxp3-{Delta}E2 mice. Additionally, altered chemokine receptor expression resulted in diminished localization of Foxp3-{Delta}E2 Tregs to the T cell zone of the inflamed lymph node. Thus, Treg programming by the Foxp3-{Delta}E2 isoform impairs suppressive function, resulting in failure to restrain CD8+ T cells and aberrant immune responses. One Sentence SummaryFoxp3-{Delta}E2 expressing regulatory T cells have altered cellular programming which impairs their IL-2 sink function and co-localization with conventional T cells during priming, enhancing CD8+ T cell responses.

immunology↗

bioRxiv2026

CHORD: a framework for cross-species single-cell integration across gene, cell and cell-type levels

Quantifying cross-species relationships among cell types from single-cell transcriptomic data can reveal both conserved and divergent patterns of cell-type hierarchies. However, existing cross-species integration methods can be limited in modeling genes beyond orthologs by leveraging cell-type-resolved transcriptional context, or in learning explicit type-level representations. Here we present CHORD, a cross-species integration framework that jointly learns representations of genes, cells and cell types. We demonstrate that CHORD can integrate cross-species single-cell atlases and support cell-type annotation with unknown cell-type detection. In the frog-zebrafish embryogenesis and mammalian motor cortex atlases, CHORD infers cell-type trees that place conserved cell types from different species in relative proximity and summarize hierarchical relationships among cell types. CHORD also supports cross-species comparison of continuous phenotypic variation by placing embryonic cells along an aligned developmental timeline. CHORD further yields gene embeddings that capture orthologous and functional relationships, and gene importance scores linking genes to cell types.

bioinformatics↗

bioRxiv2026

TopicVI: A Knowledge-guided deep interpretable model for resolving context-specific gene programs

Mechanistic insights from single-cell and spatial transcriptomics largely rely on cell clustering, differential expression analysis, and interpretation through prior biological knowledge. However, this approach is often limited by the reliance on curated biological priors that fail to capture context-specific gene programs, particularly in complex disease states. To address this gap, we introduce TopicVI, a deep interpretable model that integrates established biological knowledge with data-driven refinement to discover context-dependent gene programs in single-cell and spatial transcriptomic data. TopicVI jointly infers cell clusters and gene topics using optimal transport to flexibly align prior gene programs with observed data while permitting context-specific refinements. Comprehensive benchmarking demonstrates that TopicVI outperforms existing methods in biological conservation, batch correction, topic coherence, and rare cell identification. TopicVI effectively disentangles multiple sources of biological variation, such as separating anatomy-specific expression patterns from disease-associated signatures in spatial transcriptomics. Applying TopicVI to glioblastoma datasets, we identify gene topics related to cell cycle regulation and EGFR signaling that reveal convergent tumor states across distinct drug perturbations. By integrating prior knowledge with data-driven discovery, TopicVI enables identification of interpretable gene programs that illuminate biological processes and therapeutic mechanisms in complex transcriptomics data.

bioinformatics↗

bioRxiv2026

MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization

Computational drug discovery, particularly the complex workflows of drug molecule screening and optimization, requires orchestrating dozens of specialized tools in multi-step workflows, yet current AI agents struggle to maintain robust performance and consistently underperform in these high-complexity scenarios. Here we present MolClaw, an autonomous agent that leads drug molecule evaluation, screening, and optimization. It unifies over 30 specialized domain resources through a three-tier hierarchical skill architecture (70 skills in total) that facilitates agent long-term interaction at runtime: tool-level skills standardize atomic operations, workflow-level skills compose them into validated pipelines with quality check and reflection, and a discipline-level skill supplies scientific principles governing planning and verification across all scenarios in the field. Additionally, we introduce MolBench, a benchmark comprising molecular screening, optimization, and end-to-end discovery challenges spanning 8 to 50+ sequential tool calls. MolClaw achieves state-of-the-art performance across all metrics, and ablation studies confirm that gains concentrate on tasks that demand structured workflows while vanishing on those solvable with ad hoc scripting, establishing workflow orchestration competence as the primary capability bottleneck for AI-driven drug discovery.

bioinformatics↗