Biology subjects

Zhou, R.

Publications and source records attributed to Zhou, R..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Inhibition of CGRP receptor ameliorates AD pathology by reprogramming lipid metabolism through HDAC11/LXRβ/ABCA1 signaling

The Calcitonin gene-related peptide (CGRP) receptor has gained attention in Alzheimers Disease (AD) research due to its involvement in regulating neuroinflammation. However, its role and mechanism in AD pathology remain unclear. Here, we demonstrate that CALCRL, a core component of the CGRP receptor, is upregulated in the hippocampus of AD dementia patients and 5xFAD mice. Knockout of the CGRP receptor ligand Calca or pharmacological blockade using Rimegepant (Rim), reduces soluble A{beta}1-42 oligomer-induced neuronal death and glial inflammation. Rim treatment also rescues neurobehavioral impairments, neurodegeneration, and lipid metabolism dysfunction in 5xFAD mice. Mechanistically, these effects are mediated through HDAC11 inhibition, which enhances LXR{beta} acetylation and ABCA1 expression, promoting the reprogramming of neuronal lipid metabolism. Importantly, this CALCRL/HDAC11/LXR{beta}/ABCA1 axis is conserved across both humans and mice. Our findings uncover a novel mechanism underlying AD pathogenesis and highlight the therapeutic potential of targeting CGRP signaling in AD. HIGHLIGHTSInhibition of CGRP receptor ameliorates disease pathology in models of AD HDAC11 mediates CGRP receptor function in AD HDAC11 is a pivotal regulator in lipid metabolism by LXR{beta}/ABCA1 signaling The HDAC11/LXR{beta}/ABCA1 axis is conserved in AD humans and mice

neuroscience↗

bioRxiv2025

ANUBI: A Platform for Affinity Optimization of Proteins and Peptides in Drug Design

The increasing availability of computational power is opening unprecedented opportunities in computational biology and drug design. Computer simulations based on physical models can now reproduce or replace critical biophysical experiments such as binding affinity evaluations in the drug screening process. Here we present ANUBI (ANUBI Nexus for Understanding Binding Interactions), a software package that automates sequence space exploration and binding free energy calculations to optimize protein or peptide drug candidates for improved target binding. Starting from a user-provided molecular model of the drug-target interaction, ANUBI systematically evaluates point mutations in selected regions using Monte Carlo methodology, retaining favorable mutations based on calculated binding affinity differences. We demonstrate that this approach efficiently samples sequence space, generating dozens of optimized variants in timeframes comparable to experimental approaches at substantially reduced cost. As proof of concept, we applied ANUBI to an antibody-antigen complex and a peptide-protein interaction, identifying variants with significantly improved predicted binding energy (approximately 20 kcal/mol, calculated using the MMPBSA method), within 20 days of computation on a single GPU. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/683353v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@17fa242org.highwire.dtl.DTLVardef@75cf1dorg.highwire.dtl.DTLVardef@70888aorg.highwire.dtl.DTLVardef@14412d_HPS_FORMAT_FIGEXP M_FIG TOC GRAPHIC C_FIG

biophysics↗

bioRxiv2025

Origin and rapid evolution of minicircular and highly heteroplasmic mitogenome in the holoparasitic plant genus Rhopalocnemis

The holoparasitic plant Rhopalocnemis phalloides displays unique features in mitogenome organization, sequence heteroplasmy, DNA replication and gene transcription. To understand the origin and evolution of these unique features, we compared the mitogenomes of three R. phalloides individuals and one individual of a newly discovered congeneric species. These mitogenomes comprise dozens of minicircular chromosomes ([~]2-8 kb), with fairly small mitogenome sizes between 121.1 and 147.5 kb. Each R. phalloides individual contains extremely conserved regions (CRs) on all chromosomes, yet these CRs vary significantly among individuals, suggesting rapid divergence in a concerted manner. In contrast, the congeneric species lacks such CRs. Although nearly identical gene and intron content, there is significant sequence divergence between the two species. Extremely high mitogenome heteroplasmy was observed in all three individuals of R. phalloides and all the variants of protein coding genes are transcribed, but few heteroplasmic variants are shared among the three individuals. No sequence heteroplasmy was detected in the congeneric species. PacBio sequencing revealed concatenated mitochondrial chromosomes in the two species, suggesting rolling circle replication of mitochondrial DNA. We infer that the origins of the CR and sequence heteroplasmy are later than the origin of all-minicircular chromosomes in Rhopalocnemis, and propose a plasmid incorporation model to explain the origin of the CR. The rapid intraspecific variation in mitogenome structure, sequence and heteroplasmy in R. phalloides may result from relaxed selective constraint. The striking heteroplasmy in the R. phalloides mitogenome can not be explained by mitochondrion-targeted DNA-RRR gene loss characterized in this study.

evolutionary biology↗

bioRxiv2025

Design of TCR-mimicking binders for pHLA with high potency

The rational design of high-specificity binders to peptide-HLA (pHLA) complexes remains a major challenge in personalized immunotherapy, particularly for shared neoantigens with single-point mutations. To address this, we have developed an integrated framework that combines knowledge-based deep learning with physics-based simulation for the design of highly specific pHLA binders. Applied to p53 R175H-HLA-A*02:01, molecular-dynamics-guided electrostatic filtering yielded nanomolar binders with >10-fold selectivity over wild type. Motivated by the challenge of KRAS G12V-HLA-A*03:01, which lacks electrostatic cues, we implemented message-passing neural network (MPNN)-based optimization strategies to broaden binder design beyond charge-dependent interfaces. When reapplied to p53 R175H, these strategies improved success rates from 2/5 to 5/5, with most candidates exhibiting minimal or no binding to the wild-type complex. Chimera-based and residue-retention approaches within the MPNN optimization further expanded the sequence-structure search space while preserving critical hotspot interactions. This integrated framework thus enables the design of nanomolar, mutation-selective binders to pHLA complexes, advancing next-generation personalized cancer immunotherapies.

biophysics↗

bioRxiv2025

Assessing computational strategies for the evaluation of antibody binding affinities.

Accurate evaluation of binding affinity is critical in drug discovery to identify molecules that bind strongly to their targets while minimizing off-target effects. Although binding affinity calculations are theoretically well-defined, they require exhaustive sampling of configurational space, a step that often requires significant computational resources. In this study, we compare different methods for calculating the binding energy of antibodies targeting a peptide derived from the N-terminus of CXCR2, a GPCR-family protein. Contrary to some previous reports, we find that equilibrium MMPBSA calculations yield better agreement with experimental binding affinities than non-equilibrium potential of mean force evaluations, underscoring the system-dependent performance of these methods. We also observed a modest improvement in accuracy when MMPBSA is combined with replica exchange molecular dynamics, albeit at a significantly higher computational cost. Calculation based on Rosetta force field, instead, produced results that did not correlate with the experimental data. We attribute these findings to two factors, which could limit the applicability of some methodologies that are widely used in the computation the binding energy: the high potency of the antibodies studied and the dominance of hydrophobic interactions between the antibodies and the peptide. Overall, this work provides important insights for optimizing in silico antibody screening strategies.

biophysics↗

bioRxiv2025

Total variation of quantitative phase map reveals cellular Young's modulus

Collective cell migration is a fundamental physiological process involved in wound healing, development, and tissue regeneration. Though the role of the environmental stiffness in collective cell migration has been extensively investigated, the effects of cellular stiffness have been less studied due to the lack of high-throughput in situ methods for characterizing cellular stiffness. Here, we characterize the cellular Youngs modulus in situ with a large field of view and in real time using use quantitative phase microscopy. We found that standard deviation and total variation of the phase are inversely related to the cellular Youngs modulus, while the total variation of phase has finer mechanical resolution. Integrating the total variation of phase with cell segmentation algorithms, we efficiently analyzed the cellular Youngs modulus for cells in a monolayer. Using this system, we found the cells at the wound frontier are much softer than that of the cells in the inner region of monolayer in in vitro wound healing assay. At single cellular level, the Youngs modulus of leader cells, boundary cells, and inner cells are significantly distinct from each other. To conclude, our method would help elucidate the essential role of cellular stiffness in collective cell migration and has the potential to further benefit the progress of mechanobiology.

biophysics↗

bioRxiv2025

A chemically inducible multimerization system for tunable and background-free RTK activation

Receptor tyrosine kinases (RTKs) are key regulators of diverse cellular processes, including differentiation, migration, proliferation, survival, and intracellular communications, by transducing extracellular cues into intracellular responses. Upon oligomerization at the plasma membrane, RTKs become activated and initiate major downstream signaling cascades, such as the ERK pathway, which modulates cytoskeletal dynamics through phosphorylation of cytoskeletal regulators, regulation of actin-binding proteins, and transcriptional activation of immediate-early genes involved in cell structure and motility. Light-inducible RTK systems have been developed to achieve spatiotemporal control of RTK clustering and activation for both basic cell biology research, and engineered applications, such as controlling cell migration, proliferation, or differentiation. However, these systems are limited by high basal RTK activation, where substantial RTK activation occurs even before induction, leading to unintended ERK activation and downstream effects. Here, we report a chemically inducible RTK platform that minimizes basal activation while enabling direct visualization of RTK clustering at the plasma membrane upon induction. Single-cell imaging reveals visible RTK clusters after induction, with total RTK abundance in the clusters correlating with ERK phosphorylation levels. Using this system, we achieved precise and rapid control over multiple ERK-dependent cellular processes, including disassembly of spectrin-based membrane skeleton and nuclear entry of transcription factors STAT3 and CREB, while maintaining minimal basal activity before induction. In contrast to previously developed inducible RTK systems, which can perturb cytoskeletal structures or transcription factor dynamics even without stimulation, our design preserves native cellular architecture and nuclear signaling until activation is intentionally triggered. Collectively, these results establish our system as a robust and versatile platform for dissecting RTK signaling dynamics and engineering cell behaviors with precise, on-demand spatiotemporal control.

bioengineering↗

bioRxiv2025

BioLab: End-to-End Autonomous Life Sciences Research with Multi-Agents System Integrating Biological Foundation Models

Scientific discovery in the life sciences remains hindered by fragmented workflows, narrow-scope computational models, and inefficient links between in silico prediction and wet-lab validation. We present BioLab, a multi-agent system that integrates domain-specialized foundation models to automate end-to-end biological research. BioLab comprises eight collaborating agents, including a Planner, Reasoner, and Critic, orchestrated through a Memory Agent that enables iterative refinement via retrieval-augmented generation and a suite of 219 computational xBio-Tools spanning five biological scales (DNA, RNA, protein, cell, and chemical). These tools are built on the xTrimo Universe, a collection of 104 models derived from six foundation models (xTrimoChem, Protein, RNA, DNA, Cell, and Text), the majority of which achieve state-of-the-art (91-100% SOTA ratios) on domain benchmarks. Across standard reasoning tasks (PubMedQA, MMLU-Pro/Biology, GPQA-diamond), BioLab consistently outperformed leading large language models, including GPT-4o, Gemini-2.5, and DeepSeek-R1. Beyond benchmarks, BioLab autonomously executed a fully computational pipeline for de novo macrophage-targeting antibody design, progressing from target mining to multi-objective antibody optimization, where molecular dynamics simulations revealed structural mechanisms underlying enhanced affinity of optimized variants. Closing the computational-experimental loop, BioLab designed optimized antibodies (Pem-MOO-1, Pem-MOO-2) that achieved IC50 values of 0.01-0.016 nM, markedly surpassing the parental Pembrolizumab (0.027 nM) for PD-1. Functional assays confirmed enhanced pathway blockade and improved multi-parameter performance profiles. Together, these results establish BioLab as a generalizable framework for AI-native scientific discovery, demonstrating how multi-agent systems coupled with foundation models can autonomously generate, execute, and experimentally validate novel biological hypotheses.

bioinformatics↗

bioRxiv2025

A Novel 3D Visualization Method in Mice Identifies the Periportal Lamellar Complex (PLC) as a Key Regulator of Hepatic Ductal and Neuronal Branching Morphogenesis

The liver is a complex organ responsible for multiple functions, including metabolism, energy storage, detoxification, bile secretion, and immune regulation. Its highly organized vascular system plays a crucial role in maintaining functional zonation and tissue homeostasis. Within the liver, the hepatic artery, portal vein, hepatic vein, bile duct, and nerve networks intertwine to form an intricate three-dimensional architecture; however, traditional two-dimensional imaging fails to reveal their true spatial relationships, and current three-dimensional imaging methods remain insufficient to capture fine structural details. To achieve comprehensive visualization of these multi-ductal systems, we established a high-resolution three-dimensional imaging platform that combines multicolor perfusion of metallic compound nanoparticles (MCNPs) with an optimized tissue-clearing protocol (Liver-CUBIC), enabling simultaneous 3D reconstruction of the portal vein, hepatic artery, bile duct, and hepatic vein in mouse livers. Based on these data, we identified and defined a previously unrecognized structure located in the outer layer of the portal vein, termed the Periportal Lamellar Complex (PLC). The PLC encircles the portal vein between the vascular endothelium and the perisinusoidal region, exhibits low-permeability barrier characteristics, and contains a distinctive population of CD34Sca-1 endothelial cells. During liver fibrosis, the PLC extends from the portal vein toward the hepatic lobule, forming a structural scaffold that guides bile duct and nerve migration.

developmental biology↗

bioRxiv2025

Reengineering the antigen optimization process for superior neoantigen vaccine design

Identifying effective neoantigen sequences is essential for enhancing anti-tumor immunity. However, the vast sequence space (>109 possible peptides) and limited accuracy of existing immunogenicity predictors hinder efficient vaccine design for patient-specific human leukocyte antigens (HLAs). We present AlphaVacc, a deep reinforcement learning framework that integrates Monte Carlo Tree Search with a Transformer-based network to optimize antigenic peptides. AlphaVacc outperforms previous generative models in binding-affinity prediction. Experimental validation of 12 AlphaVacc-generated variants of the BING-4 peptide confirmed that 11 showed increased HLA-A*02:01 binding and 7 elicited significant T cell responses. Further testing of 16 single-mutation peptides confirmed computational predictions for 15 candidates, exhibiting a remarkable success rate. AlphaVacc thus provides a powerful tool for designing neoantigen-based cancer vaccines and may accelerate personalized immunotherapies.

bioinformatics↗

bioRxiv2025

FLEXTAG: A Small and Self-renewable Protein Labeling System for Anti-fading Multi-color Super-resolution Imaging

Super-resolution fluorescence imaging enables visualization of subcellular structures and molecular interactions at the nanoscale, but its broader application has been hindered by long-standing limitations in current protein tagging systems, including rapid photobleaching, tag-induced artifacts, poor post-fixation labeling efficiency, and restricted multiplexing capability. Here, we present FLEXTAG (Fluorescent Labeling for Exchangeable, X-resilient Tagging in Advanced Generic Nanoscopy), a comprehensive protein labeling system comprising three orthogonal, ultrasmall (12-18 kDa), and self-renewable protein tags that collectively overcome these major limitations of existing tagging systems, enabling optimized multi-color super-resolution imaging. Through continuous exchange of organic fluorophores, FLEXTAG supports unprecedented durations of high-resolution imaging in both live and fixed cells with minimal photobleaching. It is compatible with major super-resolution modalities, such as SIM, STED, STORM, and PAINT, and is applicable to a wide range of subcellular targets. To further address fixation-induced labeling inefficiency and background fluorescence, we developed a novel protection-based fixation method and chemical blocking strategies that significantly preserve tag accessibility and enhance signal-to-noise ratio, improvements that are broadly applicable to other protein tagging systems. Altogether, FLEXTAG enables long-term tracking of dynamic behaviors and interactions of subcellular targets, as well as mapping of nanoscale protein organizations and cellular architecture, advancing both basic research and translational applications in cell biology.

bioengineering↗

bioRxiv2025

Evidence for plastome loss in the holoparasitic Mystropetalaceae

Plastome loss is an extremely unusual phenomenon in land plants, even for those that lose their photosynthetic ability. To date, evidence for plastome loss has only been presented for two holoparasitic angiosperm lineages: two genera (Rafflesia and Sapria) of Rafflesiaceae and one section (Subulatae) of Cuscuta (Convolvulaceae). Here we propose plastome loss in holoparasitic Mystropetalaceae (Santalales), which consists of three monotypic genera: Dactylanthus, Hachettea, and Mystropetalon. Using Illumina DNA sequencing data, we successfully assembled the complete mitochondrial genomes of all three genera; however, we failed to recover any plastome sequences from them using reference-based and de novo assembly approaches. Illumina RNA sequencing data for Hachettea revealed the absence of plastid gene transcripts and losses of many nuclear-encoded genes with plastid function, including genes involved in DNA transcription, translation and protein degradation. Convergent loss of these key genes has also been documented in other plastome-less non-photosynthetic plant lineages. Taken together, we provided compelling evidence for plastome loss in the family Mystropetalaceae.

plant biology↗

bioRxiv2025

Cross-talk between RNA secondary and three-dimensional structure prediction: a comprehensive study

In recent years, various computational methods have been developed to predict the three-dimensional (3D) structures of RNAs. Due to its hierarchical folding property, RNA secondary (2D) structure is usually used as input for 3D structure prediction to improve accuracy and efficiency. However, the extent to which the accuracy of input 2D structure affects the performance of 3D structure prediction remains to be further investigated. Additionally, whether and how the input base-pairing interactions are modified during the 3D structure modeling process is another question worth exploring. To address these issues, here we comprehensively benchmark five representative 3D structure prediction models on extensive datasets, using 2D structures of varied accuracies as input. Our results indicate that there is a pervasive cross-talk between RNA 2D and 3D structure predictions, where the performance dependence of 3D structure prediction on the accuracy of input 2D structure is closely associated with the 3D models ability to modify the input base-pairing interactions during structure modeling. Furthermore, we also observed that RNA 3D structure prediction performance is more sensitive to the occurrence of false positive base pairs in the input 2D structure than to true positive base pairs, suggesting a worthy direction to further improve the model performance. Author summaryThree-dimensional (3D) structural modeling of RNAs with large sizes and complex topologies remains challenging despite the availability of (predicted) 2D structures as constraints. Exploring the potential cross-talk between 2D and 3D structure predictions is a worthy direction to improve the performance of RNA structure modeling. In this study, we found that all tested popular RNA 3D structure prediction models were able to modify the original base pairing interactions contained in the input 2D structure during the 3D modeling process. Especially, all of these models presented increased F1-score for the optimal combination of RNA 2D and 3D structure prediction models. The results suggest that a worthwhile direction to further improve the performance of RNA 3D structure prediction is to minimize the incidence of incorrectly predicted base pairing interactions during modeling process without compromising or even improving the presence of correct interactions in the input 2D structure.

biophysics↗

bioRxiv2025

Circle-Mediated HGT shapes the multichromosomal mitochondrial genome of the endoparasite Mitrastemon yamamotoi

Horizontal gene transfer (HGT), a well-established driver of genome evolution in prokaryotes, was historically considered rare in plants. However, accumulating genomic evidence supports its occurrence in angiosperms, impacting both nuclear and mitochondrial genomes, particularly in parasitic species that establish vascular connections with their hosts. Despite the increasing recognition of HGT in a few clades of parasitic plants (e.g., Balanophoraceae, Rafflesiaceae, and Cynomoriaceae), the underlying mechanisms and evolutionary consequences of these transfers are still not fully understood. Mitrastemon yamamotoi, a holoparasitic endoparasite in the order Ericales, invades the roots of host trees in the Fagaceae family, creating favorable conditions for HGT. In this study, we assembled for the first time the mtDNA of Mitrastemon, revealing a multipartite structure consisting of 51 circular-mapping chromosomes. Phylogenetic and comparative genomic analyses uncovered extensive HGT from Fagaceae hosts, affecting both coding and non-coding regions. Notably, more than 60% of the Mitrastemon mtDNA is of foreign origin, and seven chromosomes are entirely foreign, with structural signatures in the donor mtDNA consistent with the recently proposed circle-mediated HGT model. Additionally, we detected six protein-coding genes of foreign origin and one chimeric gene. Remarkably, a foreign atp1 gene has replaced the missing native copy and represents a rare event of functional HGT in plant mitochondria. These results position Mitrastemon as a valuable model for studying mtDNA evolution and deepening our understanding of the HGT process. Our findings expand the range of lineages in which circle-mediated HGT has been documented, suggesting it is a more widespread and fundamental mode of mitochondrial HGT in plants. Significant StatementParasitic plants form intimate connections with their hosts, but how these interactions influence genome evolution remains poorly understood. Our study shows that Mitrastemon yamamotoi has acquired over 60% of its mitochondrial DNA from its host through horizontal gene transfer, including entire foreign chromosomes. These findings provide strong support for a recently proposed mechanism, circle-mediated HGT, and suggest that this process may be a more widespread driver of mitochondrial genome evolution in flowering plants.

evolutionary biology↗

bioRxiv2025

In silico design and validation of high-affinity RNA aptamers for SARS-CoV-2 comparable to neutralizing antibodies

Nucleic acid aptamers hold promise for clinical applications, yet understanding their molecular binding mechanisms to target proteins and efficiently optimizing their binding affinities remain challenging. Here, we present CAAMO (Computer-Aided Aptamer Modeling and Optimization), which integrates in silico aptamer design with experimental validation to accelerate the development of aptamer-based RNA therapeutics. Starting from the sequence information of a reported RNA aptamer, Ta, for the SARS-CoV-2 spike protein, our CAAMO method first determines its binding mode with the spike proteins receptor binding domain (RBD) through a multi-strategy computational approach. We then optimize its binding affinity via structure-based rational design. Among the six designed candidates, five were experimentally verified and exhibited enhanced binding affinities compared to the original Ta sequence. Furthermore, we directly compared the binding properties of the RNA aptamers to neutralizing antibodies, and found that the designed aptamer TaG34C demonstrated a comparable binding affinity to the RBD compared to the representative neutralizing antibodies analyzed in this study. This highlights its potential as an alternative to existing COVID-19 antibodies. Our work provides a robust approach for the efficient design of a relatively large number of high-affinity aptamers with complicated topologies. This approach paves the way for the development of aptamer-based RNA diagnostics and therapeutics.

biophysics↗

bioRxiv2025

CD163+/Dab2+ Macrophages Alleviate Cardiac Hypertrophy via Nrg2/ErbB4-Mediated Mitochondrial Reprogramming

BackgroundPathological cardiac hypertrophy is a hallmark of numerous cardiovascular diseases, yet effective targeted therapies remain elusive in current clinical practice. Cardiac macrophages contribute to disease progression, but the underlying mechanisms have not been fully elucidated. MethodsSingle-nucleus RNA-sequencing, bulk RNA-sequencing, proteomics, metabolomics, and a mouse model of pressure overload were employed to investigate cardiac remodeling. We identified a macrophage subset co-expressing CD163 and Dab2 and examined its role using immunofluorescence, flow cytometry, and functional assays. We further assessed the Nrg2/ErbB4 signaling axis through genetic and pharmacological modulation. ResultsCD163/Dab2 macrophages were reduced in hypertrophic hearts and positively correlated with Nrg2 expression. These macrophages alleviated cardiomyocyte hypertrophy in vitro, an effect abolished by Nrg2 knockdown. In vivo, recombinant Nrg2 treatment mitigated cardiac hypertrophy, preserved mitochondrial structure, and restored bioenergetics via the ErbB4 receptor. Transcriptomic analyses confirmed enhanced expression of genes involved in mitochondrial oxidative phosphorylation. Furthermore, CD163+/Dab2+ macrophages improved mitochondrial dysfunction by the Nrg2/ErbB4 pathway in vitro. ConclusionsWe identified a CD163/Dab2 macrophage subset that protects against pathological cardiac hypertrophy by promoting mitochondrial function through Nrg2/ErbB4 signaling. This axis may offer a promising therapeutic target for interventions in pathological cardiac hypertrophy.

cell biology↗

bioRxiv2025

Vitamin A is necessary for acquisition, but not for expression or progression, of CNS autoimmunity

Vitamin A (VitA) and its derivative retinoic acid (RA) are essential for immunological responses. In VitA deficient (VAD) mice, acquisition of effector responses is impeded, but little is known about maintenance and expression of previously acquired effector function under the VAD conditions. We examined the impact of VAD on progression of autoimmune diseases using two models of uveitis, experimental autoimmune uveitis (EAU) induced by active immunization and spontaneous uveitis in retina-specific T cell receptor transgenic (R161H) mice, and in the model of experimental autoimmune encephalomyelitis (EAE). VAD was induced by dietary lack of VitA from before birth, or by daily injections of a pan-RA receptor inhibitor BMS493 in adult mice fed with the standard diet. VAD mice were essentially resistant to induction of EAU or EAE and displayed impaired effector T cell responses. Defective priming/acquisition of effector function by VAD T cells was also evident. By contrast, spontaneously uveitic R161H mice fed with VAD diet, in which priming of pathogenic T cells occurs before onset of full VAD, only moderately attenuated uveitis compared to VitA sufficient R161H mice. To reconcile somewhat different results between induced model and spontaneous model of uveitis, we examined EAU in partial VAD mice or adoptive transfer into VAD hosts. The results supported that effector T cells primed in VitA-sufficient environment were able to function in VAD environment and induced EAU. We conclude that although priming of naive T cells in the VAD environment is defective, effector function acquired under VitA sufficient conditions is maintained and can be expressed under VAD conditions. Because dietary lack of VitA is rarely profound and may be seasonal, our findings may shed light on immunity and autoimmunity in geographical regions where dietary VitA is limiting.

immunology↗

bioRxiv2025

Roles of histone chaperone Nap1 and histone acetylation in regulating phase-separation of chromatin arrays

Chromatin condensation is dynamically regulated throughout the cell cycle and plays key roles in modulating gene accessibility at the highest physical level in a cell. The DNA-histone dynamics in short- and long-range inter-nucleosomal interactions are central to the regulation mechanisms of chromatin condensation which remain under active investigation. We employed 12-mer nucleosome arrays to investigate the roles of histone chaperone Nap1, and histone H3 and H4 N-terminal tails and their acetylation in regulating the formation and the properties of phase-separated chromatin condensates. These arrays form liquid-like condensate droplets under a physiological salt condition of 150 mM NaCl. According to our results from bright-field microscopy, fluorescence recovery after photobleaching, optical super-resolution imaging, and microrheology with optical tweezers, histone H4 tail lysine residues are the main drivers of liquid-liquid phase separation of chromatin arrays. We also found that the condensed liquid-like droplets contain both a mobile fraction and a relatively immobile structural scaffold and that histone chaperone Nap1 and histone H3 tail acetylation facilitate DNA-histone dynamics within the structural scaffold to lower the overall viscosity of the droplets. These results suggest that histone chaperone and histone H3/H4 tails play critical roles in regulating chromatin condensation and gene accessibility in condensed chromatin.

biophysics↗