Biology subjects

Luo, Y.

Publications and source records attributed to Luo, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

ORC binding to Heterochromatin Protein 1 through intrinsically disordered regions is required for heterochromatin structure and function

The Origin Recognition Complex (ORC) is known for initiating DNA replication in eukaryotic cells, but increasing evidence suggests that ORC has multiple functions. Here we show that the organization and function of two major nuclear components, heterochromatin and the nucleolus, depend on multivalent interactions between Orc1 and Heterochromatin Protein 1a (HP1a) in Drosophila melanogaster. Specifically, binding requires two short motifs (R1 and R2) in the intrinsically disordered region (IDR) of Orc1, and two motifs (HGM and CTE) located in the N- and C-terminal regions of HP1a. Pairing of these four motifs promotes ORC-HP1 interactions, which also requires HP1 dimerization. Disrupting ORC-HP1a interactions by mutating the R1/R2 motifs causes defects in heterochromatin functions, specifically suppression of Position-Effect Variegation (PEV), ribosomal DNA (rDNA) decondensation, increased rRNA transcription, and nucleolar expansion, without global loss of H3K9me2 epigenetic modifications. Our findings indicate that ORC acts as a structural regulator that organizes heterochromatic regions and promotes proper genome regulation through multivalent interactions with HP1 and chromatin.

molecular biology↗

bioRxiv2026

EndoAge Atlas: Non-linear dynamics of endothelial aging reveal organ-specific vascular trajectories in mice

Aging is a complex and multifactorial condition that leads to a gradual decline in organ functions and subsequent vulnerability to various diseases. Although the hallmarks of aging are well studied, the linear models developed based on these paradigms repeatedly fall short in capturing the dynamic, non-linear, and tissue-specific changes that occur because of aging. Furthermore, multi-organ level studies in humans are limited by the constraints of tissue availability and other confounding variables. This emphasises the importance of animal models in executing systemic investigations of aging. As the universal regulator of vascular function, endothelial cells (ECs) act as the initial responders to aging cues and undergo profound molecular and functional changes over time. This remodelling of the ECs is considered the central driver of multiple age-associated diseases. However, the global and tissue-specific molecular trajectories of aging in ECs are yet to be well characterised. Here, we introduce EndoAge atlas, a single-nucleus RNA-sequencing atlas comprising approximately 1.3 million ECs from 32 sex-balanced C57BL/6 mice across eight tissues and five distinct age groups. This atlas identifies tissue-specific endothelial heterogeneity, age-associated gene programs with distinct functional signatures, and uncovers non-linear gene expression trajectories across organs. Collectively, the EndoAge atlas constitutes a comprehensive reference for vascular aging across mammalian tissues, providing a foundational platform for developing targeted therapeutic strategies for age-related diseases.

bioinformatics↗

bioRxiv2026

CAR T cell foundation model predicts immunotherapy response

Single-cell transcriptomics resolves CAR T-cell states, yet translating heterogeneous cellular signals into patient-level therapeutic response remains challenging. Existing studies primarily identify response-associated genes or cell populations through experimental and statistical analyses, but few predictive frameworks integrate gene-level structure with clinical outcomes. Here, we present gANCHOR, a T-cell foundation model built on a hierarchical hypergraph attention framework combining biologically informed representation learning with patient-level response prediction. By encoding gene-pathway relationships, gANCHOR learns pathway-aware cell embeddings that improve biological conservation and batch robustness. A cell-to-patient attention module then aggregates cellular information to infer therapeutic response. Across benchmark datasets, gANCHOR achieved the strongest overall performance in biological conservation and batch-correction assessments. In response prediction across 161 patients from five CAR T-cell studies, gANCHOR achieved an F1 score of 0.87, outperforming benchmarked single-cell foundation models. gANCHOR also identified reproducible response- and non-response-associated gene programs, providing interpretable biological insights into CAR T-cell efficacy and resistance.

bioinformatics↗

bioRxiv2026

AI-enabled Spatial Profiling of Circulating Tumor-Immune Ecosystems Predicts Patient Outcomes Across Cancers

Circulating tumor cells (CTCs) and immune cells form dynamic multicellular ecosystems in blood, but their spatial organization and clinical relevance have not been systematically characterized. We developed the Cell and Cluster Identification Program (CCIP), an artificial intelligence-based framework that analyzes routine multiplex immunofluorescence blood scans to segment cells, identify CTCs and five immune lineages with high accuracy, and quantify multicellular clusters and tumor-immune interactions. Applying CCIP to 2,693 blood scans from 1,399 patients, we profiled over 60 million cells (>7 million multi-cell clusters) and linked imaging-derived features to patient outcomes. Correlated with circulating-tumor DNA mutation burdens, a 14-feature image model predicted overall survival in breast cancer, outperformed clinicopathologic variables and CTC enumeration, and generalized to prostate cancer. Prognostic imaging signatures were also associated with therapy response-related progression-free survival as well as with single-cell RNA sequencing-derived immune suppression states, connecting circulating tumor-immune architecture with systemic immune dysfunction.

cancer biology↗

bioRxiv2026

Distinct RNA engagements define genome import and replication elongation in alphaviruses

Membrane-associated replication complexes (RCs) are a hallmark of alphaviruses, yet the mechanisms by which viral RNA is delivered into these compartments and coordinated with RNA synthesis remain incompletely understood. Here, we present a cryo-electron microscopy (cryo-EM) structure of the Chikungunya virus (CHIKV) RC core, consisting of nsP1, nsP2, and nsP4, in complex with the replicative RNA substrates, revealing two spatially distinct RNA-binding sites. A single-stranded RNA (ssRNA) engages the nsP2 helicase and extends toward a pore formed at the nsP1-nsP4 interface, whereas a double-stranded RNA (dsRNA) is accommodated within the central catalytic pocket of the nsP4 polymerase in an elongation configuration. Structural analysis suggests a helicase-assisted RNA threading model in which the 5' end of the viral genome is guided toward the spherule lumen through the RC pore. Concurrently, the nsP4 polymerase engages dsRNA in a manner consistent with RNA synthesis. This work provides a structural framework for understanding RNA trafficking and enzymatic coordination in viral replication organelles. Significance StatementLike many positive-sense RNA viruses, alphavirus replication occurs within membrane-bound spherules, but how viral RNA is delivered into these compartments and coupled to RNA synthesis has remained unclear. Here, we show that the CHIKV RC core contains two functionally distinct RNA-engagement modules: an nsP2-associated ssRNA path directed toward the nsP1-nsP4 pore, and an nsP4-bound duplex RNA positioned in an elongation-like polymerase channel. These observations support a model in which alphavirus RCs integrate genome import and RNA synthesis within a single membrane-associated molecular machine. This work provides a structural framework for understanding RNA trafficking, replication-organelle function, and potential antiviral targeting of alphavirus replication.

microbiology↗

bioRxiv2026

Nuclear phylogenomics clarifies the family-level backbone and gene-tree conflict in Zingiberales

Zingiberales includes eight morphologically distinctive families, but its family-level backbone has remained unstable, especially around Musaceae, Heliconiaceae, Lowiaceae, and Strelitziaceae. We analysed 1566 low-copy nuclear genes from 52 samples, representing all eight families and Pontederia crassipes as outgroup. Concatenated maximum likelihood and multispecies coalescent analyses recovered the same backbone: ((Zingiberaceae, Costaceae), (Cannaceae, Marantaceae)) is sister to (Musaceae, (Heliconiaceae, (Lowiaceae, Strelitziaceae))). Penalized-likelihood dating placed the sampled crown group in the Late Cretaceous, with several deep family-level divergences occurring on short internodes. Analysis of 1248 rerooted gene trees showed that conflict is concentrated on these deep branches and in several shallow clades. HyDe tests of empirical and simulated matrices, each including 62,475 triples, did not support widespread ancient hybridization among the major family-level lineages after filtering against the simulated null model. The nuclear data recover a stable Zingiberales backbone, and the long-standing instability of several deep nodes is best explained by rapid early divergence and extensive incomplete lineage sorting.

evolutionary biology↗

bioRxiv2026

Thymic Treg-derived T follicular regulatory cells prevent catastrophic humoral autoimmunity in response to TLR7-driven inflammation

T follicular regulatory cells (TFR) are a follicle-resident subset of regulatory T cells (TREG) that limit germinal center (GC) responses and enforce humoral tolerance. Although TFR are known to focus antibody responses to foreign antigens, how GC-specific regulation is maintained during inflammation remains unclear. Here, TLR7-driven inflammation unmasked a critical, non-redundant role for TFR in preserving immune tolerance. Selective loss of TFR caused severe autoimmunity and increased mortality, driven by inflammation-induced expansion of autoreactive B and T cell clones and epitope spreading. Autoreactivity resolved upon cessation of inflammation in TFR-sucicient mice but persisted in their absence. Mechanistically, TFR limited the establishment and expansion of spontaneous GCs in response to inflammation, and responding TFR displayed transcriptional, phenotypic, and clonal features of thymic TREG. This suggests that whereas TFH upregulate FoxP3 to shut down end-stage GCs, it is thymic TREG-derived TFR that safeguard GC integrity under inflammatory stress to prevent lethal autoimmunity.

immunology↗

bioRxiv2026

Hypermutability of ultraconserved histone genes and its contribution to human disease

Histone genes are among the most evolutionarily conserved sequences in eukaryotes, reflecting their essential role in nucleosome architecture. Intriguingly, our analysis reveals unexpectedly high germline mutation rates in replication-dependent histone genes across vertebrates. We provide multiple lines of evidence suggesting that this hypermutability is largely driven by off-target mutagenic effects of AID/APOBEC enzymes, representing an unintended fitness cost associated with vertebrate immune system innovation. To characterize the impact of these mutations, we develop HistMTR, a paralog-aware missense constraint framework that outperforms existing tools in predicting the pathogenicity of histone mutations. Applying this framework to large-scale human genomic data, we demonstrate that both coding and regulatory histone mutations contribute to a spectrum of diseases, including developmental disorders and reproductive failure. Analyses of allele transmission ratios and the distribution of fitness effects indicate intense ongoing negative selection against deleterious histone mutations in humans. Together, these findings uncover a hidden vulnerability of ultraconserved histone genes and establish HistMTR as an important framework for characterizing the underappreciated role of histone mutations in human disease.

evolutionary biology↗

bioRxiv2026

Convergent genome- and gene-level constraints shape repeated environmental adaptation in grasses

Grasses (Poaceae) dominate terrestrial ecosystems and sustain global food security, yet the genomic principles enabling their repeated adaptation to extreme environments remain unresolved. Combining dense phylogenomic sampling, global environmental data, and genomic large language models (gLLMs), we characterize the mutational targets underlying environmental adaptation across 707 genomes from 569 species spanning 17 climate zones. We identify 19-30 phylogenetically independent transitions into extreme temperature, water, and soil environments, accompanied by convergent shifts in genome-scale molecular properties, including the Nitrogen-to-Carbon balance and the biosynthetic cost of the proteome. Our gLLMs-informed phylogenetic mixed modeling framework identifies 330 genes that repeatedly underlie distinct axes of environmental adaptation, highlighting the importance of protein modification and localization within extracellular and organellar compartments. Overlaying independent convergent adaptation tests identifies 17 high-confidence candidates for further characterization. Together, our results show that grass adaptation is canalized by layered constraints at genome-wide and gene-specific scales, producing predictable evolutionary trajectories.

evolutionary biology↗

bioRxiv2026

Discovery of ARQ-501 as a potent PafA inhibitor that elevates KatG levels to potentiate isoniazid in mycobacteria

The prokaryotic ubiquitin-like protein (Pup) conjugation system (PPS), which is essential for Mycobacterium tuberculosis (Mtb) virulence but absent in humans, presents an attractive drug target. Here, we report the discovery of ARQ-501, a quinone-based, covalent, substrate-competitive inhibitor of the Pup ligase PafA. ARQ-501 exhibited potent anti-mycobacterial activity against Mtb under host-mimicking stress conditions and within macrophages. We further identified the catalase-peroxidase KatG, essential for activation of the frontline prodrug isoniazid (INH), as a pupylation substrate. ARQ-501 inhibits KatG pupylation, causing its accumulation and creating a selective synergy with INH. This quantity over quality mechanism successfully rescued INH activation by the clinically prevalent KatG S315T mutant in enzymatic assays and enhanced INH efficacy against clinical S315T isolates to variable degrees. This work identifies a novel class of PafA inhibitors and a previously unrecognized role of pupylation in regulating KatG, offering a potential therapeutic avenue to combat drug-resistant tuberculosis.

microbiology↗

bioRxiv2026

Learning to See Like a Child: Why Viewpoint Diversity is Fundamental for Human-Aligned Object Recognition

Deep convolutional neural networks match human accuracy on standard object recognition tasks but fail to recognize familiar objects from novel view-points. Humans, however, develop viewpoint-invariant recognition at an early age through diverse visual experience. This gap in visual experience may explain why models diverge from humans in object recognition. Holding dataset size constant, we show that greater viewpoint diversity substantially improves generalization to novel views. Using a synthetic 3D dataset with systematically controlled viewpoints, we reveal a core trade-off: restricted-view training yields rapid learning and near-ceiling in-distribution accuracy but collapses on held-out viewpoints, whereas viewpoint-diverse training learns more gradually yet generalizes robustly. Increasing viewpoint diversity disrupts texture regularities while preserving global shape, driving networks to prioritize shape over texture - the same strategy that underlies human object recognition. Partitioned Grad-CAM analyses further show that viewpoint-diverse models maintain object-centered attention. These findings parallel developmental accounts of multi-view learning and identify viewpoint diversity as an important factor for robust, human-aligned vision.

neuroscience↗

bioRxiv2026

SynFit: Synergistic Contrastive Learning for Multi-Objective Protein Fitness Prediction and Optimization

Proteins function through a complex interplay of structural and biochemical properties, and mutations can reshape these properties to generate fitness landscapes spanning multiple functional objectives. A central challenge in protein engineering is the need to simultaneously optimize multiple properties. In biocatalysis, for example, practical enzyme development routinely requires the concurrent optimization of catalytic activity, selectivity, stability, and substrate generality. However, despite recent advances in computational protein design and fitness prediction, most existing approaches treat these properties independently and do not explicitly capture the dependencies and trade-offs that govern real-world protein performance. We present SynFit, a multi-objective learning framework that integrates pretrained protein language models with experimental fitness measurements for protein fitness prediction and engineering. SynFit learns both shared and property-specific protein sequence representations through a synergistic contrastive learning strategy, enabling the identification of variants that simultaneously optimize multiple functional properties. Across a large-scale multi-fitness deep mutational scanning benchmark, SynFit consistently outperforms state-of-the-art supervised models trained on individual objectives and more accurately identifies variants that balance competing functional constraints. We further applied SynFit to multi-objective enzyme design for a new-to-nature biocatalytic enantioselective borylation reaction, providing a diverse array of novel cytochrome c sextuple variants in a single round of design with simultaneously improved catalytic activity and enantioselectivity that rival the best variants obtained through directed evolution. Together, these results establish SynFit as a general framework for multidimensional protein fitness prediction and highlight its potential to enable efficient multi-objective optimization in protein engineering, particularly in biocatalysis.

bioinformatics↗

bioRxiv2026

Novel Muscle-Tropic AAV Capsids with Dramatically Enhanced Transduction and Safety Profiles in Non-Human Primates

Adeno-associated virus (AAV) gene therapy holds immense promise for treating muscular dystrophies, yet its efficacy and safety are constrained by the suboptimal tissue tropism of natural serotypes. Here, we employed the REACH platform, which combines rational design and directed evolution, to engineer muscle targeting vectors. Systemic administration in non-human primates (NHPs) revealed that lead candidate M1 mediates a >10-fold increase in skeletal muscle transduction compared to the AAV9 and 2-3 fold higher than MyoAAV, while concurrently achieving a remarkable 183-fold reduction in liver distribution. Furthermore, M1 exhibited significant de-targeting from key off-target tissues, including dorsal root ganglia (11 fold), lung (27 fold), spleen (2 fold), and kidney (2 fold). These findings demonstrate that the REACH platform can generate AAV capsids with simultaneously enhanced muscle tropism and favorable safety profiles, addressing a critical bottleneck in muscle-directed gene therapy.

bioengineering↗

bioRxiv2026

In the Drosophila germline H2Av and Arp6 suppress transposons by driving piRNA pathway expression

The spatiotemporal control of transcription and the maintenance of germline genome integrity depend on dynamic chromatin architecture. In Drosophila, the actin-related protein Arp6--a core subunit of the SWR1-like Domino chromatin remodeling complex--mediates the deposition of the histone variant H2Av. Previous studies have established H2Av as a key transcriptional regulator that modulates the +1 nucleosome barrier to promote RNA Polymerase II (Pol II) pause release and productive elongation. Conversely, H2Av is also integral to heterochromatin assembly and gene silencing. Here we demonstrate that Arp6 and H2Av are essential for female fertility and the global repression of transposable elements (TEs) in the Drosophila ovary. Rather than repressing TEs directly, we show that Arp6 and H2Av maintain genomic stability indirectly by driving the transcription of core PIWI-interacting RNA (piRNA) pathway genes. Depletion of either chromatin factor leads to a significant loss of piRNAs and reduced non-canonical transcription of dual-strand piRNA clusters. This defect stems from a failure to express the Rhino-Deadlock-Cutoff (RDC) complex, alongside the downregulation of multiple other piRNA biogenesis factors. Genomic profiling confirms that H2Av acts predominantly as an activating signal at host gene promoters. Upon H2Av or Arp6 depletion, genes that rely on H2Av for their expression exhibit a distinct upstream shift and more precise spatial localization of the Pol II peak at the TSS, indicating an impaired transition from transcription initiation into productive elongation. Together, our findings build upon the known transcriptional activation functions of the Arp6-H2Av axis, revealing that this established chromatin mechanism is critical for licensing piRNA-mediated genome defense and ensuring germline maintenance.

molecular biology↗

bioRxiv2026

GABA antagonises ABA perception and signalling in plants

Abscisic acid (ABA) is a central regulator of plant growth and stress responses. However, it also negatively impact germination, growth, and reproductive performance, highlighting the need for mechanisms that fine-tune its signalling. Here, we identify {gamma}-aminobutyric acid (GABA) as an endogenous antagonist of plant ABA receptor. We show that GABA binds the clade A protein phosphatase-ABI1, disrupting its association with the ABA receptor PYL1, blocking ABA binding, thereby attenuating ABA signalling. GABA modulates ABA-control of stomatal aperture and seed germination, demonstrating its broad physiological influence. Notably, GABA accumulation during stress coincides with the subsequent decline in ABA, consistent with a delayed feedback signal of ABA activity. Together, this work identifies GABA as an antagonist of ABA and provides a mechanism balancing plant stress resilience and growth.

plant biology↗

bioRxiv2026

Receptor-Anchored Olfaction Representation through Perception-Consistent Metric Learning

Olfactory perception arises from distributed activation across hundreds of olfactory receptors (ORs), yet our understanding of this landscape remains constrained by the scarcity of OR affinity measurements. Here, we present Receptor-Anchored Metric Supervision (RAMS), a transfer learning framework using perceptual consistency as weak supervision to predict OR activation spectra. RAMS fine-tunes a pretrained drug-target affinity model by imposing constraints derived from olfactory perception, where similar odorants are encouraged to exhibit similar OR activations. It transfers protein-ligand interaction knowledge learned from large-scale pharmacological data into the olfactory domain and reshapes it toward OR activation prediction. Evaluations against experimental measurements show that RAMS improves the accuracy of receptor-spectrum prediction and yields biologically plausible activation patterns. The predicted spectra show concordance between receptor discriminative capacity and expression level, and highlight the understudied OR52 family as a potential contributor to primary odor recognition. Together, RAMS provides a scalable framework for reconstructing receptor-anchored olfactory representations.

bioinformatics↗

bioRxiv2026

Single-cell Transcriptomics Analyses Reveal Specialized Microglial Subsets with Oligodendrocyte-like Signatures

BackgroundMicroglial heterogeneity is a fundamental feature of brain homeostasis and pathology. The purpose of this study was to investigate the complexity of microglial plasticity by characterizing specialized oligodendrocyte-like microglial subsets. MethodsThe study was performed utilizing single-cell transcriptomics analyses and immunofluorescence staining to identify and profile microglial subpopulations. Additionally, spatial transferring and morphological analyses were conducted to determine the anatomical distribution and structural features of these specific cells. ResultsWe identified a distinct microglial subset termed dual-phenotype microglia (DPM), which co-expresses microglial and oligodendrocyte markers. DPM consisted of two subtypes with distinct functions: myelin-associated DPM (mDPM) and neuron-associated DPM (nDPM). Spatial and morphological evaluations revealed that mDPMs were sparsely distributed across the whole brain and exhibited a highly ramified architecture, whereas nDPMs were enriched in the hippocampal dentate gyrus. Mechanistically, we found that mDPM function was driven by the Sox10 regulon to modulate myelin maintenance and axonal ensheathment, while nDPM was orchestrated by Glis2, facilitating essential neuron-glia crosstalk and synaptic regulation. Furthermore, we demonstrated that nDPM and mDPM were predicted to undergo significant alterations in multiple sclerosis and Alzheimers disease. Notably, mDPMs were selectively enriched in active multiple sclerosis lesions, revealing that DPM were closely related to neuropsychiatric disorders. ConclusionsBy comprehensively characterizing the morphology, molecular signatures, and spatial logic of these oligodendrocyte-like microglial subsets, our study elucidated the complexity of microglial plasticity. These findings provided new insights into their diverse roles in central nervous system health and disease. Graphical abstractIdentification, Molecular Profiling, and Functional Modeling of Dual-Phenotype Microglia (DPM). (1) Discovery: Identification of the dual-phenotype microglia (DPM) population through single-cell transcriptomics. (2) Molecular Signatures: The transcriptomic identity of DPM subtypes is governed by specific regulatory networks. (3) Distribution & Pathology: Spatial mapping reveals divergent anatomical logic and disease relations for DPM subtypes. (4) Mechanism/Theory: A proposed functional model of mDPMs as "metabolic relay" and support units. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/724239v2_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@b7db1dorg.highwire.dtl.DTLVardef@9265e7org.highwire.dtl.DTLVardef@1605d82org.highwire.dtl.DTLVardef@19b048f_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

piRNA direct the chromatin reader to its genomic targets

The chromatin reader Rhino (Rhi) is an HP1-paralog and master regulator of piRNA biogenesis in Drosophila that drives the transcription of piRNA precursors. While Rhi binds the heterochromatic mark H3K9me3, this interaction is insufficient to explain its specific occupancy, as Rhi is excluded from the majority of H3K9me3-enriched loci. Instead, we find that Rhi recruitment is orchestrated by several competing pathways, including the piRNA-guided protein Panoramix (Panx) and the DNA-binding protein Kipferl (Kipf). We demonstrate that Panx functions as a piRNA-guided modular scaffold that directs Rhi to its targets through a dual-mode mechanism: its N-terminus recruits the H3K9 methyltransferase machinery, while its C-terminus directly binds the Rhi chromodomain. While H3K9me3 deposition provides a necessary foundation, it acts in synergy with the direct Panx-Rhi physical bridge to drive robust Rhi occupancy. Furthermore, Rhi recruitment is amplified by the cytoplasmic inheritance of maternal piRNAs, forming a transgenerational feed-forward loop. Our results reveal that the piRNA pathway imparts sequence-specificity to the H3K9me3 code, utilizing a direct physical bridge to program the genomic distribution of the chromatin reader Rhi.

molecular biology↗