Biology subjects

Dai, W.

Publications and source records attributed to Dai, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Reliable and Efficient Agentic Protein Design with Toolset Harnessing

Computational protein design workflows require the orchestration of multiple tools, data formats, and analysis steps that are often fragmented. Here, we introduce Chaperone, a lightweight and customizable framework that enables seamless integration of RFdiffusion3 (RFD3) with downstream sequence design, structure prediction, and evaluation tools, including ProteinMPNN, AlphaFold3 (AF3), and more than 50 other protein design tools. By combining a programmable agent-friendly interface with parallelized execution on high-performance computing systems, Chaperone as a harness enables rapid iteration and scalable exploration of complex protein design workflows. Across an evaluation of nine biomolecular design tasks, we find using Chaperone reduces total token usage relative to baseline agents by 86% and GPU costs by 64%, while increasing the overall computational design pass rate. We demonstrate Chaperones utility for large-scale design-space exploration through a two-week end-to-end small-molecule binder design campaign, yielding low nanomolar binders to cortisol zero shot. We further demonstrate its versatility across distinct design challenges, including the design of a symmetric 12-subunit self-assembly nanoparticle and a linker that mediates interactions between C2- and D3-symmetric protein complexes to form crystalline assemblies. Together, these results demonstrate how agent harnesses built around standardized tool interfaces can substantially improve the efficiency and success of complex, long-horizon agentic design workflows in biology. We make Chaperone freely available to the community on GitHub: https://github.com/RosettaCommons/chaperone.

biochemistry↗

bioRxiv2026

Complex enzyme active site scaffolding by iteratively detuned catalytic guidance

De novo enzyme design requires sequences whose structures reproduce prescribed catalytic geometries. This remains challenging for active sites that couple multiple catalytic residues, cofactors and substrates. Here we introduce the Catalytic Guidance Engine (CaGE), which optimizes designed sequences to satisfy complex sets of functional constraints by alternating constraint guided structure prediction trajectories with sequence design, gradually fading the strength of the constraint information over cycles to nudge the designed sequence towards satisfying all the constraints. We train RF3 to accept atom-pair distances and other design conditions, and use classifier-free guidance to fade their influence over multiple design cycles. We also develop training-free motif guidance protocols which operate at inference time by directly adjusting selected atoms towards the design target geometry during diffusion sampling. CaGE improves catalytic-motif geometry across a diverse enzyme benchmark and yields sequences that recover complex target active sites in independent AF3 predictions. We experimentally demonstrate the power of CaGE by designing active enzymes with complex catalytic sites: a nonheme-iron design positions four active-site residues around an iron centre and a transition-state ligand, and a PLP-dependent design positions four catalytic residues around a PLP cofactor with multiple functional groups. Active site substitutions and a 2.7[A] crystal structure support the designed mechanisms and structures. Thus, CaGE provides a route to functional de novo enzymes with complex active sites.

bioengineering↗

bioRxiv2026

A Hymenoptera-restricted gene mediating ant castes co-opts deeply conserved machinery to control organ size

Lineage-specific genes are widespread and have been implicated as phenotypic innovation inducers, but how they acquire complex developmental functions remains poorly understood. Ant queens and workers develop dramatically different organ sizes from identical genomes under juvenile hormone (JH) control, yet the molecular effectors translating JH signalling into caste-specific organ growth remain unknown. Here we identify torch, a Hymenoptera-restricted gene, as the most consistently gyne-biased and JH-responsive gene across 68 ant species. Knockdown of torch in virgin queens of Monomorium pharaonis produces a worker-like, multi-organ growth-restricted phenotype. Mechanistically, torch harbours an E-box-like motif activated by the JH receptor Gce-Tai and acts as a GA-repeat-binding transcription factor that regulates Hippo signalling, the deeply conserved organ-size control pathway in animals. Expressing torch heterologously in mice and a growth-restricted Drosophila background shows that the gene retained its general growth-promoting activity across more than 700 million years of animal evolution in lineages that lack the gene, establishing that its function is mediated through conserved rather than ant-specific machinery. A lineage-specific gene can therefore acquire complex morphogenetic function by co-opting ancient organ-size circuitry, providing a general route by which novel genes can drive phenotypic innovation.

evolutionary biology↗

bioRxiv2026

Disrupting Myeloid Persistence and Replenishment Enables Sustained Control of Esophageal Squamous Cell Carcinoma

Responses to macrophage-directed therapy can be transient because tumors preserve myeloid support through complementary persistence and replenishment. In esophageal squamous cell carcinoma (ESCC), CSF1R inhibition reduced established tumor-associated macrophages but was followed by expansion of Ly6C/CCR2-positive monocytic and Ly6G-positive granulocytic populations. Low-dose decitabine preferentially restricted recruited populations while sparing a LYVE1-associated macrophage state, exposing reciprocal pharmacologic blind spots. Combined treatment suppressed both arms and produced sustained control across patient-derived organoid xenograft, orthotopic, and immunocompetent models. Neutrophil depletion reproduced initial regression but not sustained control, indicating that the recruited escape arm extended beyond Ly6G-positive granulocytes. Single-cell profiling mapped these vulnerabilities onto a treatment-resolved myeloid architecture comprising a C1qa-positive TAM continuum, a C1qa-negative Ccr2/Ly6c2-high inflammatory monocytic-like compartment, and a LYVE1/MRC1-positive tissue-supportive macrophage state. Human ESCC contained corresponding macrophage programs and an adverse-outcome-associated LYVE1-rich niche. These findings identify state-aware coverage of complementary myeloid vulnerabilities as a strategy to overcome escape from macrophage-directed therapy.

cancer biology↗

bioRxiv2026

Hidden genetic diversity in 320 nearly-complete East Asian genome assemblies

East Asian populations, representing over 20% of the global population, remain critically underrepresented in human genomic studies, limiting our understanding of population-stratified genetic variation and its implications for health and disease. Here we present the first phase of the Asian Pan-Genome project (APG), comprising 320 nearly complete, fully phased haploid genome assemblies from 160 East Asian individuals. These assemblies achieve unprecedented quality, with an average contig N50 of 144.3 megabase pairs and an average quality value of 64.5. Leveraging these superior assemblies, we reveal previously uncharacterized diversity in human repeatome, including population-stratified patterns in centromere satellites and rDNA arrays. Compared to existing global human genome assemblies, the newly generated genomes supplement 152 million base pairs of novel sequences, 355 gene gains, 18,300 structural variation loci and 26 large euchromatic inversions missing from current human pangenomes. We perform population stratification analyses of structural variations, and further resolve the structural haplotypes of complex genomic regions such as Major Histocompatibility Complex and Survival Motor Neuron loci across global pangenomes, exemplifying tandem-duplicate and inversion-rich complex locus architectures in the human genome, respectively. This resource provides a critical foundation for human genetic studies, especially for East Asian populations, promoting more accurate variant discovery, reducing bias, and ultimately advancing the equity and efficacy of genomic medicine.

genomics↗

bioRxiv2026

Adipocyte Expression of O-Glycoprotein Procollagen C-Endopeptidase Enhancer Protein 2 (PCPE2): Mechanisms Linking Fibrosis and Beiging of White Adipose Tissue

BackgroundProcollagen C-endopeptidase enhancer protein 2 (Pcpe2) has been primarily investigated in collagen processing during wound healing and is assumed to function similarly to Pcpe1 in the extracellular matrix (ECM). Our studies suggest that Pcpe2 has unique structural and functional features not shared with Pcpe1. MethodsTo study the role of Pcpe2 in adipose tissue remodeling, we created adipose tissue-specific knockout of Pcpe2 (TgAd+Pcpe2KO) and adipose tissue-specific Pcpe2 overexpressing (TgAd+Pcpe2Ox) mice and performed in vivo and ex vivo experiments. ResultsWe show that TgAd+Pcpe2KO mice are resistant to WD-induced obesity and exhibit reductions in body and fat pad mass. Promethion cage studies showed no significant differences in lean mass or food intake, yet WD-fed TgAd+Pcpe2KO mice exhibited significantly higher energy expenditure than negative Cre littermate controls. WD-fed TgAd+Pcpe2KO mice also showed reduced plasma glucose and lipoprotein lipid concentrations compared to controls. While markers of adipose tissue inflammation were reduced in WD-fed TgAd+Pcpe2KO mice. Examination of mature adipocytes from white adipose tissue showed that WD consumption greatly stimulated Pcpe2 expression, while no change in Pcpe2 expression in the stromal vascular cells was noted. However, in VAT precursor cells (PCs), the CD140b+ population showed a shift from fibroadipogenic precursors towards adipocyte PCs in TgAd+Pcpe2KO mice. This shift in PCs may account for the attenuation of local inflammation and fibrosis in the absence of Pcpe2. Ex vivo differentiation of adipose PCs showed that loss of Pcpe2 enhanced adipocyte differentiation, reducing TGF{beta}-like signaling via pSmad2/3, and increasing mitochondrial function. Furthermore, unlike Pcpe1, Pcpe2 contains a mucin-like linker domain with nine sites of O-linked glycosylation which may regulate receptor signaling at the plasma membrane. ConclusionsOur results show the ECM O-glycoprotein Pcpe2 is a robust marker of unhealthy adipose tissue expansion in humans and mice and contributes to inflammation and fibrosis associated with WD-induced obesity.

cell biology↗

bioRxiv2026

Foundation Model RNAGAN Enhances Biomedical Insight of Nasopharyngeal Carcinoma Metastasis

RNAGAN (version 2.0, https://github.com/ZhaozhengHou-HKU/RNAGAN-2.0.git) is a published foundation model that analyzes single-cell and bulk-level RNA sequencing samples and enables multiple applications that enhance medical insights. Here we applied this model to Nasopharyngeal Carcinoma (NPC) as in-context few-short format (i.e., the model was never trained with any NPC data). We conducted all four supported functions, which include sample stratification, vectorization, pseudo data generation, and marker identification. The results were then used for identifying metastatic NPC and to investigate mechanisms associated with NPC metastasis. Examination with stratification showed that the accuracy of RNAGAN results for evaluating the metastasis risk in NPC patients are comparable to or outcompeted recently published risk estimation linear prediction model. Vectorization results present consistency across multiple cohorts and RNAGAN model versions. In the task of identifying markers and mechanisms related to NPC metastasis, incorporating pseudo data substantially enhanced the representativeness of single-cohort-based differential expression (DE) analysis. Moreover, RNAGAN identified metastasis-related marker genes based on single cohort, were concordant with the ground truth obtained across multiple cohorts (p=1.05e-9). Regarding biomedical mechanisms, RNAGAN enabled second-order feature extraction, unveiling a remarkable domination of the protective function of adaptive immune responses (as indicated by IL21R levels) over the hazardous function of chronic, non-resolving innate inflammation (as indicated by S100A8 levels) against NPC metastasis after first-line treatment. This association demonstrates a high degree of consistency with the external cohort. This study demonstrates the utility of the foundation model RNAGAN in uncovering therapeutic insights for novel cancer types without extra training. We reveal a critical spatial mechanism preventing distant metastasis via humoral anti-tumor immunity in NPC. High S100A8 expression by innate antigen-presenting cells (APCs) triggers an inflammatory cascade promoting epithelial-mesenchymal transition (EMT) and metastasis. However, when germinal center IL21R+ B cells simultaneously colocalize with these innate signals, they override this suppressive tissue stress. Spatial analysis shows that a high S100A8/IL21R intersection within tumor regions strictly distinguishes treatment responders, whereas non-responders display spatial mismatch or S100A8+ hyper-infiltration. This coordinated innate-adaptive cross-talk sustains functional tertiary lymphoid structures (TLS) that mature IgG-secreting plasma cells, which opsonize and eliminate emerging EMT tumor cells before systemic escape. Consequently, while S100A8 alone is an unreliable prognosticator, its spatial colocalization with IL21R is a robust protective indicator overlooked by conventional bulk analysis methods.

cancer biology↗

bioRxiv2026

SpatialCCCbench: Standardized Metrics for the Systematic Evaluation of Spatial Cell-Cell Communication Methods

Spatial transcriptomics (ST) enables transcriptome profiling with preserved spatial context, providing spatial dimensions that are essential for understanding complex intercellular signals in tissue architecture. ST-based CCC tools integrate spatial and molecular information to decipher intercellular interactions from a spatially informed perspective. Despite the rapid evolution of many CCC computational tools, a systematic assessment of their performance in handling ST-specific heterogeneity, utilizing spatial information efficiently, and robustness against technical or biological noise is still lacking. To address this gap, SpatialCCCbench incorporates classification accuracy, spatial signal features, robustness, and user-friendliness, aiming to guide the selection of optimal CCC inference tools across diverse spatial biology contexts. SpatialCCCbench systematically evaluates the scenario-specific applicability of ST-based CCC tools. It helps users select tools according to their analytical objectives and provides a practical benchmark for future method development. HighlightsO_LIEstablished a multi-dimensional benchmark suite to evaluate cell-cell communication (CCC) inference methods in spatial transcriptomics. C_LIO_LICharacterized the spatial patterns of CCC signals across diverse tissues using spatial autocorrelation and local diversity analysis. C_LIO_LISystematically assessed the robustness of CCC inference tools across six common experimental noise scenarios in spatial transcriptomics. C_LIO_LIIntegrated boundary-feature analysis, a mechanistically important component for biological interpretation, to uncover spatial preferences and algorithmic biases in CCC methods. C_LIO_LIProvided guidelines to assist in the selection of optimal CCC inference tools tailored to various spatial biology contexts. C_LI Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/724475v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@12bbc6aorg.highwire.dtl.DTLVardef@5eee6borg.highwire.dtl.DTLVardef@76d8f2org.highwire.dtl.DTLVardef@9d077e_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Dysregulation of a novel autophagosome-mitochondria contact contributes to autophagy dysfunction and neurodegeneration in tauopathy

Mitochondria engage in extensive communication with other organelles through membrane contacts. Perturbed mitochondria-organelle interactions are indicated in a variety of neurodegenerative diseases, but the underlying mechanisms remain poorly understood. Here, we report a new class of mitochondria-organelle communication: autophagosome/autophagic vacuole (AV)-mitochondria (Mito) contact, which exhibits hyper-tethering in tauopathy neurons, consequently hampering AV retrograde transport. Such defects are attributed to accelerated turnover of the contact release factor TBC1D15, triggered by mitochondrial bioenergetic deficit-induced hyperactivity of the AMP-activated protein kinase (AMPK). Increasing TBC1D15 levels or repressing AMPK activity normalizes AV-Mito contact release and restores retrograde transport of AVs, thereby increasing autophagic cargo clearance and reducing tau burden in tauopathy axons. Furthermore, overexpression of TBC1D15 enhances autophagic clearance and attenuates tau pathology, alleviating neurodegeneration and cognitive dysfunction in tauopathy mice. Taken together, our study provides new insights into AV-Mito contact dysregulation in tauopathy-related autophagy failure, laying the groundwork for the development of potential therapeutics to combat tauopathy diseases.

neuroscience↗

bioRxiv2026

RNAGAN: Train One and Get Four, Multipurpose Human RNA-Seq Analysis Tool with Enhanced Interpretability and Small Data Size Capability

The advent of artificial intelligence (AI) has brought revolutionary tools for biomedical transcriptomic (RNA-level) research. However, there are persistent constraints including limited interpretations with biomedical concepts such as functional pathways, small sample sizes and substantial time and computing power requirements for AI training. To overcome these limitations, we developed RNAGAN (https://github.com/ZhaozhengHou-HKU/RNAGAN-1.0.git), an AI tool with a generative adversarial network (GAN) structure with the objective of enhancing transcriptomic analysis. The network was established based on public human datasets comprising 4.6 million single cells from multiple organs and 5,900 sequenced samples of various cancer types with normal references. A specialized pathway neural layer was embedded to extract activities of predefined pathways from the Human Molecular Signatures Database (MSigDB), or newly learned pathways from single-cell data. The structure of RNAGAN (generator and discriminator) enables four applications after one shared training procedure: 1. single-cell and bulk-level patient stratification or differential diagnosis; 2. analysis of the gene and pathway markers in a selected disease; 3. pseudo data generation when sample size is limited for downstream analysis; 4. vectorization with gene and pathway-level features learned from multiple data sets. RNGAN contributes to the efficient utilization of limited data for transcriptomic studies.

bioinformatics↗

bioRxiv2026

Programming Biomolecular Interactions with All-Atom Generative Model

Biomolecular interactions lie at the core of cellular life, spanning diverse molecular modalities from small molecules to nucleic acids and proteins. Nevertheless, design strategies remain separated despite shared physicochemical principles of molecular recognition. Here we present AnewOmni, a unified generative framework trained on more than 5 million biomolecular complexes, that enables transferable molecular design across molecular scales by assembling chemically meaningful building blocks at atomic resolution. We further introduce programmable graph prompts to support user-defined chemical, topological, and geometric steering during generation, exploring hybrid and unconventional chemistries beyond canonical structures. We demonstrate that transferable learning of interaction patterns and physical constraints across molecular modalities is possible, via an atom-to-block latent space capturing both atomic details and structural priors. The framework successfully designed small molecules, peptides, and nanobodies targeting the challenging KRAS G12D switch II pocket, as well as orthosteric peptides and allosteric small-molecule inhibitors for PCSK9 in the absence of known binding site, achieving 23%-75% success with only low-throughput validation, bypassing modality-specific high-throughput screening. AnewOmni is the first to succeed in functional molecular design across all scales, from small chemical entities to large biologics, and represents a stepstone towards general molecular reasoning engines, advocating a generative foundation model for biomolecular interactions to enter regimes where data and human intuition remain limited.

bioengineering↗

bioRxiv2026

Placental prostaglandin signaling disrupts barrier integrity and relays an acute inflammatory signal to the fetus.

Maternal inflammation during pregnancy is a major risk factor for adverse neurodevelopmental outcomes, yet the mechanisms linking maternal immune activation (MIA) to placenta-fetal brain axis dysfunction remain unclear. Using a poly-(I:C) mouse model, we show that MIA rapidly disrupts placental-blood barrier (PBB) integrity by disrupting pericyte-endothelium coupling within 48 hours, leading to increased placental permeability detected by in vivo MRI. We identify a prostaglandin E2 (PGE2)-dependent pathway involving cyclooxygenase-2 (COX2) and prostaglandin E-synthase (mPGES1) as a key mediator of this effect. Pharmacological inhibition of COX2 prevented MIA-induced structural and functional changes. In vitro explant studies confirmed that PGE2 acts via the EP3 receptor to disrupt pericyte-endothelium interactions, while ex vivo perfusion demonstrated that in addition to its local effects on PBB structure, placenta-derived PGE2 enters the fetal circulation. Finally, similar vascular alterations were observed in human placentas from pregnancies with severe maternal inflammation. These findings reveal a conserved inflammatory mechanism that compromises PBB integrity and may relay signals to the fetal brain, highlighting potential therapeutic targets for neuroprotection during prenatal inflammation. One Sentence SummaryMaternal immune activation during pregnancy disrupts placental vascular integrity through a COX2-dependent prostaglandin E2 pathway, which compromises the placenta-blood barrier and relays inflammatory signals to the fetus, identifying potential therapeutic targets for neuroprotection.

developmental biology↗

bioRxiv2026

A vagal gut-brain axis for feeding induced gastric secretion

Feeding begins with food-seeking and ends with nutrient absorption and waste elimination. Although meal-related sensory cues are known to shape feeding behavior, how they engage neural circuits to control digestion remains unclear. We dissected vagal gut-brain-gut pathways that mediate meal-induced gastric secretion. Vagal afferent neurons innervating the stomach were necessary and sufficient for secretion. Among those, Glp1r and Sst neurons robustly drove acid, pepsin, and gastrin secretion, whereas Oxtr and Vip neurons had little effect. Piezo2 was expressed in Glp1r mechanosensory afferents, and conditional deletion of Piezo channels attenuated distension-evoked secretion. On the efferent limb, genetically defined vagal motor neuron subsets differentially recruited secretory outputs: Cck neurons broadly increased acid, pepsin, and gastrin, whereas Grp neurons preferentially drove acid secretion. Finally, enteric circuit dissection revealed modular output control: Calb2 enteric neurons potently drove secretion with minimal motility effects, Grp enteric neurons coupled secretion to motility, and Cysltr2 enteric neurons selectively modulated acid output. Together, these results define a cell-type resolved vagal-enteric architecture for gastric control and show that secretory and motor programs can be segregated across dedicated enteric neuron subtypes.

neuroscience↗

bioRxiv2025

Laminar-specific control of response gain and orientation-tuning byparvalbumin-expressing inhibitory interneurons in primate visual cortex

Understanding the role of the different types of inhibitory interneurons in cortical computations is central to elucidating how the neocortex processes sensory information. The emergence of orientation tuning in primate primary visual cortex (V1) is a canonical model for studying how cortical sensory circuits and inhibitory interneurons compute relevant stimulus features. The selective feedforward convergence of non-orientation-selective thalamic afferents establishes initial orientation tuning in the granular V1 input layer. As signals propagate through the cortical microcircuit, orientation tuning sharpens in extra-granular layers, yet the underlying mechanisms and the contribution of specific inhibitory neuron subtypes within V1 remain unresolved. To study the role of the largest cortical inhibitory neuron subclass, parvalbumin-expressing (PV+) interneurons, in this V1 computation, we combined laminar extracellular recordings with bidirectional optogenetic manipulations of PV+ cells in marmoset V1. Our results reveal a striking laminar specificity: in granular layers, PV+ cells implement divisive/ multiplicative linear gain control, whereas in extra-granular layers they exert tuned nonlinear suppression that enhances orientation tuning. Computational modeling suggests that PV+ neurons can control gain by changing a neurons spiking threshold, and orientation tuning by changing a neurons input noise, which regulates the neurons input-output function. Our findings reconcile divergent results from previous rodent studies and establish a framework for understanding layer-dependent inhibitory computations in the primate cortex.

neuroscience↗

bioRxiv2025

Bridging Evolution and Design: Mapping the Diversity of LOV Photosensors

Light-sensitive proteins allow organisms to perceive and respond to their environment, and have diversified over billions of years. Among these, Light-Oxygen-Voltage (LOV) domains are widely distributed photosensors that control diverse physiological processes. Despite their broad biological roles and increasing use in optogenetics, the functional diversity of natural LOV domains and the evolutionary constraints shaping their dynamics remain poorly resolved. A key unresolved problem is how evolution modulates the timescales and efficiencies of LOV photocycles and how this kinetic flexibility relates to biological function. Here we systematically map the photodynamics of 21 natural LOV domains - including 18 previously uncharacterized variants - and one de novo photosensor generated by artificial intelligence-guided protein design. We uncover an exceptional kinetic diversity spanning picoseconds to days and identify distinct functional classes within the LOV family. These patterns holistically reveal that billion years of evolutionary adaptation led to branching photocycle kinetics, matching physiological requirements. Moreover, by extending the natural catalog of LOV photosensors with a de novo designed LOV variant, we demonstrate how computational protein design can access new biophysical niches. This work expands the optogenetic toolkit and offers a framework to dissect and harness the evolutionary design principles of light-responsive proteins.

biophysics↗

bioRxiv2025

Hyperbolic Wavelet Interaction Network (HyWinNet): Multi-Scale Geometric Learning for Interpretable Protein-Protein Interaction Prediction

Understanding the multi-scale organization of protein-protein interactions (PPIs) is fundamental to deciphering cellular signaling, allosteric regulation, and disease mechanisms, yet existing computational approaches fail to simultaneously resolve atomic-scale binding interfaces and pathway-level coordination. We present HyWinNet, a geometric deep learning framework that unifies Lorentzian hyperbolic graph neural networks with spectral graph wavelet transforms to intrinsically model the hierarchical architecture of biological interactions. The core innovation lies in three synergistic components: (1) Hyperbolic embeddings that preserve evolutionary-conserved topological relationships through negatively curved space projections, capturing scale-free properties of protein networks; (2) Multi-scale wavelet decomposition operating at biologically grounded resolutions to jointly analyze local residue contacts and global pathway dynamics; (3) Contrastive learning with stochastic feature dropout that mimics natural binding interface plasticity. Benchmarked against state-of-the-art methods, HyWinNet demonstrates superior performance in recovering known interactions while predicting previously unannotated functional sites validated through independent structural and biochemical studies. By bridging hyperbolic geometry with graph signal processing, this work establishes a new paradigm for analyzing multi-scale biological networks, offering both interpretable computational predictions and testable hypotheses for experimental validation. The frameworks ability to map hierarchical relationships from atomic details to system-level modules provides a transformative tool for drug discovery and mechanistic studies of complex diseases.

bioinformatics↗

bioRxiv2025

Spatial Coordination between Leaf Gradient and Temperature Response in Barley

The linear shape of cereal leaves creates distinct longitudinal zones that coordinate tissue maturation and resource allocation. Under abiotic stress such as heat, these longitudinal zones may differentially activate protective pathways, revealing hidden heterogeneity in stress response that remains poorly understood. Barley (Hordeum vulgare), a cold-adapted crop particularly sensitive to elevated temperatures, can serve as an ideal model for studying region-specific heat responses in leaves. Using chlorophyll fluorescence imaging, we found that non-photochemical quenching (NPQ) kinetics captured additional physiological changes beyond those detected by SPAD, highlighting the added value of chlorophyll fluorescence-based assessments. NPQ kinetics traits displayed consistent spatial gradients from tip to base, with heat stress reducing NPQ induction across leaf gradients. Genome-wide association analysis of traits derived from chlorophyll fluorescence imaging across leaf gradients identified significant SNPs within multiple candidate genes, including HORVU.MOREX.r3.3HG0262630 that was consistently detected in over 90% resampling iterations under heat stress, suggesting its key role during heat responses. Transcriptomic profiling along the leaf axis revealed both conserved and region-specific heat responses between leaf regions. Conserved activations highlighted conserved heat response pathways, including the reactivation of the Arabidopsis thermomemory module FtsH6-HSP21. In contrast, the region-by-temperature interaction analysis identified 40 genes with spatial responses indicative of resource reallocation from growth to defense, including those involved in growth and transport. The integration between spatially resolved phenotyping and transcriptional profiling underscores region-specific variation in response to heat along the leaf axis, guiding targeted strategies to enhance heat resilience in barley and other cereal crops.

plant biology↗

bioRxiv2025

Brain cholesterol metabolites cause significant neurodegeneration in human iPSC-derived neurons

Disrupted cholesterol metabolism is increasingly recognised as a contributing factor in neurodegeneration; however, the specific effects of key brain-derived cholesterol metabolites, 24S-hydroxycholesterol (24S-HC) and 27-hydroxycholesterol (27-HC), remain poorly understood. Using human iPSC-derived i3 cortical neurons, we demonstrate that both 24S-HC and 27-HC significantly impair neuronal calcium signalling by elevating resting calcium levels, reducing spike amplitude, and disrupting network synchrony. These functional deficits are accompanied by widespread organelle dysfunction. Both oxysterols induce mitochondrial fragmentation, decrease spare respiratory capacity, and impair lysosomal degradation. Notably, 27-HC uniquely triggers lysosomal swelling and membrane permeabilisation. Additional signs of cellular stress, including axonal swellings and elevated endoplasmic reticulum calcium levels, were also observed. Furthermore, both 24S-HC and 27-HC were found to directly interact with alpha-synuclein (aSyn), promoting its accumulation in cellular models. In contrast, cholesterol itself had minimal impact, highlighting the distinct toxicity of its hydroxylated metabolites. Together, these findings reveal a mechanistic link between oxysterol accumulation and neuronal dysfunction, supporting the hypothesis that elevated levels of 24S-HC and 27-HC, commonly observed in Parkinsons and Alzheimers disease, may actively drive neurodegenerative processes. Targeting oxysterol metabolism may therefore represent a promising therapeutic avenue for intervention in neurodegenerative disorders.

neuroscience↗