Biology subjects

Gao, L.

Publications and source records attributed to Gao, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Activity induced GEM-4/Copine expression inhibits gap junctions and promotes thermosensory plasticity

Activity induced gene expression promotes behavioral plasticity (including several forms of learning and memory) by altering synaptic connectivity and neuron excitability. While several transcriptional targets modify synapses, little is known about targets regulating excitability. Here, we identify a single MEF-2 and CRH-1/CREB transcriptional target, gem-4/Copine, whose expression increases the excitability of C. elegans body muscles. In muscles, gem-4 expression is repressed by MEF-2 and is induced by CRH-1. GEM-4 expression in muscles decreases the number of gap junctions, thereby increasing membrane resistance and excitability. These results identify activity induced copine expression as a mechanism to control gap junction coupling and excitability.

neuroscience↗

bioRxiv2026

Sustained Relief of Chronic Pain via a Nav1.7_Targeting ASO_siRNA Conjugate

Chronic pain affects billions globally, yet safe, long-lasting, and non-addictive analgesics remain lacking. Nav1.7 is a genetically validated pain target, but traditional small molecules have repeatedly failed. Therapeutic oligonucleotides-antisense oligonucleotides (ASOs) and siRNAs-offer selective, durable silencing. We developed N02C0702, an ASO-siRNA conjugate (ASC), achieving robust Nav1.7 knockdown and sustained analgesia without additional delivery vehicles. N02C0702 outperformed individual ASO (N02A114) and siRNA (N02S154) moieties at mRNA and protein levels and in pain relief. In CFA-induced inflammatory pain, a single intrathecal dose exceeded naproxen and suzetrigine, while in SNL neuropathic pain, efficacy persisted up to 56 days, comparable to or surpassing pregabalin. Genome-wide RNA sequencing confirmed minimal off-target effects. N02C0702 highlights Nav1.7 as a key analgesic target and demonstrates the ASC platforms potential for chronic pain and other CNS-related pathologies, offering durable, selective, and safe therapeutic effects.

neuroscience↗

bioRxiv2026

DNA Traces on the Shroud of Turin: Metagenomics of the 1978 Official Sample Collection

This research provides original insights into the diversity of DNA extracted from samples collected in 1978 from the Turin Shroud, revealing its biological complexity through rigorous DNA and metagenomic analyses. Our findings highlight its preservation conditions and environmental interactions, offering valuable perspectives into the identified genetic variants, which originated from multiple biological sources. Several human mitochondrial DNA (mtDNA) lineages were identified, including K1a1b1a, which matches the 1978 official collectors mitogenome, H2a2 (i.e. the lineage of the mtDNA reference sequence rRCS), H1b, which is common in Western Eurasia, and H33, which is prevalent in the Near East and frequent among the Druze. Moreover, the reconstructed microbiome of the Shroud reveals a rich tapestry of multiple microbes commonly found on the human epidermis, as well as archaeal communities adapted to high salinity, and fungi including molds. This is indicative of the Shrouds preservation conditions over the centuries. Additionally, the presence of abundant Mediterranean endemic red coral, various cultivated plants (e.g. carrot, wheat, corn, bananas, and peanuts) and domesticated animals (e.g. cattle, pigs, chickens, dogs, and cats) provide a fascinating glimpse into the diverse biological sources of the contaminants that have accumulated on the Turin Shroud over time. Finally, radiocarbon dating of two distinct threads collected from the reliquary provides evidence of their use to repair the Shroud in the years 1534 and 1694 of the Common Era (CE). Significance statementAn in-depth metagenomic analysis was conducted on several linen strands collected from different areas of the body image of the Man of the Shroud during the official sampling in 1978. Our analyses revealed several human mtDNA lineages, including one common in Western Eurasia and another prevalent in the Near East. Additionally, the diversity of animal and plant species identified details the significant environmental contamination of the Shroud that likely occurred in recent centuries, particularly following the voyages of Marco Polo and Christopher Columbus. Radiocarbon dating of two distinct textile residuals from the Shrouds reliquary indicated a time range between 1451 and 1800 CE, overlapping with the period of its repair interventions.

genomics↗

bioRxiv2026

Coordinated topoisomerase function shapes the fluoroquinolone response of Chlamydia trachomatis

DNA supercoiling is essential for the developmental cycle of Chlamydia trachomatis, yet its role in shaping antibiotic responses remains poorly understood. We investigated how the fluoroquinolone moxifloxacin (Mox) influenced C. trachomatis growth across developmental stages with its distinct supercoiling levels. Early Mox exposure completely halted bacterial growth, whereas treatment during mid-cycle produced enlarged, persistent forms and abolished formation of infectious progeny. These stage-specific outcomes coincided with inhibition of DNA replication, depletion of DNA gyrase, and transcriptional repression of ompA and omcB, accompanied by preserved or elevated expression of the stress-responsive groESL1 operon. Mox also elicited compensatory downregulation of topoisomerase I (TopA), consistent with attempts to rebalance intracellular supercoiling. Together, these data demonstrate that fluoroquinolone susceptibility in C. trachomatis reflects stage-dependent supercoiling levels. Perturbation of supercoiling homeostasis drives developmental arrest and persistence phenotypes, highlighting coordinated gyrase-TopA activity as a key determinant of fluoroquinolone tolerance and a potential target for overcoming persistent infection. ImportanceC. trachomatis, a medically significant bacterial pathogen, can persist under antimicrobial pressure, complicating treatment strategy. This study links supercoiling homeostasis to fluoroquinolone tolerance, offering mechanistic insights into chlamydial adaptation to antibiotic stress and identifying potential targets to overcome persistence--an urgent challenge in global reproductive health.

microbiology↗

bioRxiv2026

Integrated single-cell and spatial transcriptomic analysis of T cell exhaustion and immunometabolic remodeling in HPV-positive oropharyngeal squamous cell carcinoma

HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) harbors dense lymphocytic infiltration yet responds poorly to immune checkpoint blockade (ICB), a paradox whose mechanistic basis remains unresolved. Here we constructed an integrated single-cell and spatial transcriptomic atlas of HPV OPSCC (23,119 cells, 24 cell types), complemented by CRISPR-Cas9 functional validation in two HPV cell lines and multiplex immunofluorescence across independent cases. Pseudotime trajectory analysis placed TOXCD8 T cells, rather than canonically defined exhausted cells, at the terminal exhaustion endpoint, and uncovered a previously uncharacterized IEGCD8 effector memory population at a fate-decision juncture between activation and irreversible exhaustion. Actively cycling Tregs with broad co-stimulatory and co-inhibitory receptor expression underwent intratumoral immunosuppressive differentiation. Compartmentalized LDHA/MCT4 expression in cancer cells versus LDHB/MCT1 in T cells established a directional lactate flux model, and spatial deconvolution confirmed peripheral immune exclusion. We identified a KMT2D-KLF7-PD-L1 regulatory axis: KMT2D sustains KLF7 transcription through H3K4me1-dependent enhancer activation; KLF7 concurrently drives neural crest differentiation and upregulates PD-L1, thereby linking epigenetic remodeling to both neural programming and immune checkpoint expression. These findings define converging multi-scale mechanisms underlying ICB resistance in HPV OPSCC and nominate the KMT2D-KLF7-PD-L1 axis as a combinatorial therapeutic target.

cancer biology↗

bioRxiv2026

Tissue- and Age-Specific Transcriptomic and Metabolomic Analysis Reveals Regulatory Mechanisms of Ginsenoside Biosynthesis in Panax notoginseng

Ginsenosides are the primary bioactive compounds in Panax notoginseng, but the transcriptional mechanisms governing their tissue- and age-dependent accumulation remain elusive. Here, we integrated targeted metabolomics with transcriptome profiling across four tissues (root, stem, leaf, and flower) and three developmental stages (1-3 years) to investigate the spatiotemporal regulation of ginsenoside biosynthesis. We observed distinct tissue- and age-specific accumulation patterns: roots exhibited a progressive increase in total ginsenoside content during the second and third years, while flowers preferentially accumulated rare protopanaxadiol-type ginsenosides such as Rg3-2. Transcriptomic analysis revealed extensive differential gene expression across tissues and stages, particularly in roots during late development. Clustering and transcription factor (TF) enrichment analyses identified multiple tissue-associated regulatory modules. Four TFs--AT3G12130, SPL9, MYB33, and SPL1--emerged as core candidates based on coordinated expression, promoter motif enrichment, and functional annotation of predicted target genes. Motif analysis further linked these TFs to key biosynthetic genes involved in triterpenoid oxidation and glycosylation, including CYP716A53v2 and CYP716A47. Together, these findings suggest that tissue-specific ginsenoside accumulation in P. notoginseng is associated with coordinated transcriptional regulation of biosynthetic enzymes. This study provides a transcriptomic framework for understanding spatial regulation in ginsenoside biosynthesis and identifies candidate regulators for future functional validation and metabolic engineering.

plant biology↗

bioRxiv2026

Process optimization and antidepression multi-target mechanisms of Total Flavonoids from Hemerocallis citrina Baroni: An integrated approach combining DES-UAE, network pharmacology, and experimental validation

ObjectiveThis study aimed to establish a green and efficient ultrasonic-assisted deep eutectic solvent (DES) extraction method for total flavonoids from Hemerocallis citrina Baroni (TFHC) and to elucidate its multi-target antidepressant mechanism using an integrated strategy of network pharmacology, molecular docking, and in vitro validation. MethodsAn ultrasonic-assisted DES extraction using choline chloride-ethylene glycol was optimized via response surface methodology. The TFHC extract was profiled by UPLC-ESI-MS/MS. A network pharmacology approach was employed to predict core targets and pathways of TFHC constituents against depression, with key interactions validated by molecular docking. The neuroprotective effects of TFHC were evaluated in vitro using a corticosterone (CORT)-induced injury model in PC-12 cells, assessing cell viability (MTT assay) and levels of 5-HT, BDNF, TNF-, and CORT (ELISA). ResultsThe optimized DES extraction yielded 16.63 {+/-} 0.13 mg/g of TFHC. UPLC-ESI-MS/MS identified fourteen flavonoids, with quercetin, kaempferol, and rutin being most abundant. Network pharmacology revealed six core targets (AKT1, TNF, IL6, IL1{beta}, TP53, PTGS2) and implicated pathways including PI3K-AKT and TNF. Molecular docking confirmed strong binding affinities ([≤] -4.25 kcal/mol) between major flavonoids and core targets. In vitro, TFHC significantly alleviated CORT-induced cytotoxicity, restored 5-HT and BDNF levels, and suppressed TNF- and CORT elevation, with effects comparable or superior to fluoxetine. ConclusionsTFHC exerts antidepressant-like effects through a multi-target mechanism involving neuroinflammation suppression, neurotrophic support, and HPA axis modulation. The green DES extraction combined with mechanistic insights positions TFHC as a promising candidate for phytotherapeutic antidepressant development.

pharmacology and toxicology↗

bioRxiv2026

Interactions between Submicron Carbon Particles, Escherichia coli and Humic acid with Plastic Surfaces

Plastic materials are widely used in engineered systems and increasingly accumulate in natural environments, where their surfaces interact with colloids, microorganisms, and dissolved organic matter. However, the relative roles of plastic surface properties versus particle-specific characteristics in governing organic matter retention remain poorly constrained. Here, attachment efficiency () was used to quantify intrinsic particle-collector affinity on three common thermoplastics (ABS, HDPE, HIPS) and glass beads as an inorganic reference. Surface chemistry, hydrophobicity, roughness, and charge were characterized, and interactions with submicron carbon particles (SCPs) and Escherichia coli were evaluated using column experiments. Extended DLVO (XDLVO) theory was applied to predict interaction energy barriers, and humic acid (HA) adsorption was quantified through batch isotherms. XDLVO modeling predicted higher affinity of particles for plastics relative to glass; however, experimentally measured attachment efficiencies were uniformly low ( < 0.05) across all materials. Attachment was primarily governed by particle size and surface charge rather than collector hydrophobicity, roughness, or surface chemistry. SCP consistently exhibited higher than bacteria, while differences among plastics were minor. Similarly, HA adsorption was weak and near-linear, with uptake following ABS {approx} HIPS > HDPE > glass, indicating reversible, partitioning-like association dominated by polymer-specific functionality rather than electrostatics. The absence of correlation between and XDLVO-predicted energy barriers further demonstrates limitations of classical physicochemical models in describing particle- plastic interactions. Collectively, these results indicate that pristine thermoplastic surfaces exhibit intrinsically low affinity for organic matter and that particle-specific properties dominate retention under low ionic strength conditions. Enhanced accumulation in environmental systems likely requires surface aging or conditioning processes not captured by classical interaction theory.

biochemistry↗

bioRxiv2026

A Systematic Benchmark for Peptide Property Prediction

Accurate prediction of peptide physicochemical properties and biological activities is critical for rational peptide design and high-throughput screening. However, current research is often constrained by heterogeneous data sources and inconsistent evaluation standards, which hinder fair comparisons and reliable assessments of model generalization. In this work, we present PPB, a peptide property prediction benchmark designed to evaluate model performance with an emphasis on realistic generalization across both classification and regression tasks. By applying unified biological filtering criteria, we systematically curated and standardized 15 datasets comprising 161,571 unique sequences, spanning a wide range of physicochemical properties and functional activities. We benchmarked seven representative architectures--encompassing traditional machine learning, deep learning, and pre-trained language models--alongside diverse feature encoding schemes. Furthermore, we investigated the impact of random versus homology-based (sequence similarity) data splitting strategies on model robustness. To facilitate community access, we developed the PPB web server (http://ppb.molmatrix.com/index.html), which provides centralized resources for standardized dataset downloads, interactive visualization of benchmark results, and detailed evaluation protocols. Author summaryPeptides are short amino acid chains essential for biological functions and drug discovery. While AI models have accelerated peptide property prediction, the field lacks a unified standard to fairly compare these methods, often leading to inconsistent results and overoptimistic performance estimates. In this study, we introduce the Peptide Property Benchmark (PPB), a comprehensive framework featuring 15 standardized datasets and over 160,000 sequences. We systematically evaluated diverse AI paradigms, including traditional machine learning and advanced protein language models. Our results demonstrate that large-scale pre-trained models--the biological equivalent of large language models--offer superior accuracy and stability, particularly for small or complex datasets. Crucially, our analysis reveals a "clustering bottleneck": standard tools used to group proteins based on similarity often fail when applied to short peptides, causing data to fragment excessively. This suggests that traditional strategies for testing model generalization may be less effective for peptides than previously assumed. To facilitate community progress, we provide an online platform for standardized data and evaluation. This work establishes a rigorous foundation for developing more reliable AI tools for the next generation of peptide-based therapeutics.

bioinformatics↗

bioRxiv2026

New insights into the evolution of spider silk proteins illuminated by long-read transcriptomes

Spider silk has long fascinated scientists because of its exceptional mechanical properties, yet the evolutionary origins and diversification of spider silk proteins (spidroins) remain incompletely understood. By analyzing long-read spidroin transcripts from spiders representing key evolutionary lineages, we identify two ancestral proteins present in basal spiders: an alanine-serine-rich (AS-type) protein and a glycine-serine-rich (GS-type) protein. These ancestral proteins likely served as primary evolutionary templates for the diversification of modern spider silks. We show that the AS-type ancestral spidroin remained relatively conserved and ultimately gave rise to the specialized tubuliform spidroin (TuSp) used in eggcase silk. In contrast, the GS-type protein underwent extensive functional radiation, evolving into differentiated minor ampullate spidroins (MiSp) through the acquisition of distinct terminal domains and {beta}-sheet-associated structural innovations. Our results further suggest that major ampullate spidroins (MaSp) may have originated from MiSp, with the GS motif representing an evolutionarily favorable genetic substrate for the emergence of high-performance silk proteins. Finally, we propose a revised evolutionary trajectory for flagelliform spidroins (Flag), suggesting that they were co-opted as components of ampullate silk during functional degeneration in modern non-web-weaving RTA clade spiders. Together, these findings provide a high-resolution framework for understanding the genetic innovations that drove the diversification of spider silk.

evolutionary biology↗

bioRxiv2026

Molecular determinants of antibody-mediated priming to enhance detection of ctDNA

Liquid biopsies can enable cancer detection and monitoring yet remain limited by low concentrations of ctDNA. To address this limitation, we previously introduced a monoclonal antibody (mAb) "priming agent" that transiently increased the concentration of ctDNA in blood. Here, we investigated the molecular features that drive this effect. In a panel of novel mAbs that bound cfDNA, both those targeting dsDNA and those targeting mononucleosomes increased the concentration of ctDNA. mAbs with high avidity to dsDNA performed best, suggesting dsDNA as the key binding target. One agent preserved short, biologically informative molecules of cfDNA typically depleted at baseline. The Fc domain was dispensable, as F(ab)2 fragments retained priming activity. Leveraging these insights, we engineered single-chain agents using the dsDNA binding domain sso7d, expanding priming strategies beyond immunoglobulins. This study identifies the molecular features and general design principles for mAb-based priming agents to enhance recovery and detection of ctDNA. SignificanceLow concentration of ctDNA limits the sensitivity of liquid biopsies in many applications. This study shows how engineered antibodies and other dsDNA-binding molecules can inhibit clearance of ctDNA from the bloodstream and increase concentration of ctDNA in a blood draw, and identifies the key features that enable this activity. Modulation of cfDNA in the bloodstream using these agents can increase recovery of ctDNA and improve the performance of liquid biopsies for cancer detection.

bioengineering↗

bioRxiv2026

Minimal Influence of Material Surface Properties on Initial Bacterial Attachment to Built Environment Surfaces

Biofilms in the built environment (BE) can harbor pathogens and have been linked with negative health outcomes, particularly in hospital environments. The formation of biofilms requires bacterial cell attachment on surfaces, such as hospital plumbing, which can have varying properties, including roughness, wettability, chemistry, and charge. Despite the importance of bacterial attachment to surfaces, the role of multiple surface properties has been minimally investigated. Using seven materials with differing surface characteristics, this work considers the initial attachment of Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, and Staphylococcus aureus to investigate the impact of several surface characteristics. Biofilm formation was evaluated to determine the impact of surface characteristics on longer-term attachment. The initial attachment of all bacterial species was not significantly influenced by material surface properties, with similar attachment seen across materials tested. Bacterial cell envelope morphology affected attachment, with Gram-negative species displaying greater attachment than Gram-positive species. Initial attachment was not related to biofilm formation, which was highest on stainless steel surfaces while differences between bacterial species remained.

microbiology↗

bioRxiv2026

fMRI-Based Prediction of Eye Gaze During Naturalistic Movie Viewing Reveals Eye-Movement-Related Brain Activity

BackgroundEye gaze provides crucial insights into perceptual and cognitive processes during naturalistic movie viewing, yet concurrent eye tracking is often unavailable in functional MRI (fMRI) research. While deep learning models can estimate gaze directly from fMRI eyeball signals, their out-of-the-box generalizability across heterogeneous datasets requires empirical evaluation. MethodsWe applied a specific pre-trained model from the DeepMReye framework in a zero-shot setting (without dataset-specific fine-tuning) to estimate gaze during movie watching across three independent fMRI datasets. Model accuracy was evaluated against camera-based eye-tracking data and via inter-subject correlations. Furthermore, we derived eye-movement-related time series from the predicted gaze signals to map their associated brain activation. ResultsAt the individual level, predicted gaze showed modest correspondence with measured ground-truth data (r {approx} 0.24-0.37), yielding brain activation maps largely restricted to the visual cortex. In contrast, group-averaged gaze predictions exhibited substantially higher reliability (r {approx} 0.73-0.84). First-level General Linear Models (GLMs) derived from group-averaged predictions successfully revealed widespread activation across established oculomotor control regions, including the frontal and parietal eye fields. Exploratory analyses of age-related effects on gaze prediction and brain activity yielded inconsistent results across datasets. ConclusionsUnder a zero-shot implementation, the pre-trained model exhibits limitations for individual-level inference, likely reflecting the absence of dataset-specific training. However, group-averaged fMRI-based gaze estimates successfully capture shared viewing behaviors and robustly support the investigation of eye-movement-related brain activity. These findings inform the appropriate use of fMRI-based gaze decoding for naturalistic neuroimaging datasets lacking ground-truth eye-tracking logs.

neuroscience↗

bioRxiv2026

Spatiotemporal Mapping of Tertiary Lymphoid Structure Heterogeneity Shapes Immune Niches and Clinical Outcomes in Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy with limited therapeutic options. The spatial architecture and functional diversity of tertiary lymphoid structures (TLSs) in iCCA remain unclear. Here, we present a multimodal spatial atlas of TLSs and identified Intra-tumoral TLSs (iTLSs) as independent prognostic markers. Bulk proteomic profiling of 214 discovery and 155 validation cases identified a four-tier TLS-based TME classification system and supported development of a TLS-predictive random forest classifier. Imaging mass cytometry revealed that iTLS tumors harbor structured immune architectures, where M1-like tissue-resident macrophages (RTMs), dendritic cells, and CXCL13 CD4 T cells co-localize to form antigen-presenting neighborhoods (apc-CNs) spatially coupled to TLS core regions (TLScore-CNs). Single-cell spatial transcriptomics further resolved 61 TLSs into 14 spatial niches and defined a pseudo-temporal maturation continuum: aggregated, activated, and post-activated. Intra-niche communication, primarily mediated by ifnCAFs, iCAFs, and CXCL12 macrophages, evolved dynamically with maturation. Single-nucleus RNA-sequencing combined with Tangram-based spatial mapping revealed CXCL12 macrophages and iCAFs forming a peripheral band in aggregated TLSs, while ifnCAFs infiltrated TLS interiors during activation. These findings define TLS heterogeneity and provide insights for stroma-directed immunotherapy. TeaserAn atlas of tertiary lymphoid structures reveals immune-stroma interactions in Intrahepatic cholangiocarcinoma.

immunology↗

bioRxiv2025

Spatial 5mC-seq profiling of embryos and decidua after implantation in mammal

DNA methylation plays key roles in development and diseases. However, no spatial DNA methylation profiling technology has been reported until now. Here, we developed a spatial 5mC-seq method (SmC-seq) based on a microfluidic system. The SmC-seq can provide a non-biased genome-wide methylome at about single-cell scale (10 m in width per channel). We further applied this SmC-seq to explore the spatiotemporal dynamics of DNA methylation during post-implantation development in mouse. A clear spatial heterogeneous pattern of DNA methylation among inner cell mass-derived tissues can be observed. Additionally, we identified a two-layer organization in the ectoplacental cone at the E8.5 stage, characterized by distinct DNA methylation patterning and proliferation states. Unexpectedly, a portion of maternal tissue with low DNA methylation level, enriched for nutrient-supplier progenitor cell, is observed in the middle region of maternal decidua after implantation. The hypomethylated regions in the nutrient-supplier progenitor cell cluster are associated with cell proliferation. Interestingly, the genes associated with hypomethylated regions in the mature nutrient-supplier cell cluster are enriched in exocytosis and nutrient synthesis, which is associated with nutrient provision before functional placenta is formed to support mammalian embryogenesis. In summary, SmC-seq enables spatial mapping of DNA methylation and facilitates our understanding of various biological events.

genomics↗

bioRxiv2025

Infection Of Rhesus Macaques With Onyong-nyong Virus UVIR-O804 Recapitulates Key Aspects of Human Clinical Disease

1.Onyong-nyong virus (ONNV) is a mosquito-borne alphavirus first isolated in Uganda in 1959. Since its discovery, ONNV has caused several outbreaks in Africa, manifesting clinically as fever, rash, and joint/muscle pain lasting months. Currently, we have a limited understanding of ONNV infection and disease in relevant animal models, which restricts the evaluation of vaccines and therapeutics. In 1967, Binn et al. reported that infection of rhesus macaques (RMs) with ONNV failed to induce viremia in two animals. This may be attributed to the potential attenuation of the virus through extensive passaging. To mitigate this issue, we constructed an infectious clone from the sequence of ONNV-UVRI0804 (ONNV0804), a 2017 clinical isolate from a febrile patient in Uganda. This strain demonstrated high pathogenicity in immunocompetent mice, resulting in an earlier and more severe onset of disease and significantly higher viremia compared to a highly passaged control strain ONNVUgMP30. In the current study, three male and three female rhesus macaques were subcutaneously inoculated with ONNV0804. All animals became viremic at 2 days post inoculation (dpi). Both classical and nonclassical monocytes were activated (CD169+), peaking at 3 dpi, which corresponded with the peak of viremia. Additionally, CD4+ and CD8+ effector memory T cells and memory B cells began proliferating in peripheral blood by day 7, peaking at day 10, which also corresponded to the timing of neutralizing antibody development, indicating a robust adaptive immune response to ONNV0804. Finally, key clinical disease manifestations were recapitulated, including lymphadenopathy and histological features of early-stage arthritis. Taken together, rhesus macaque infection with ONNV0804 clinical isolate is a promising model for investigating immune responses to alphaviruses and evaluating vaccines to protect against future epidemics. 2. Author summaryOnyong-nyong virus (ONNV) is a mosquito-transmitted alphavirus that causes fever, rash, and prolonged joint and muscle pain, similar to chikungunya virus and other arthritogenic alphaviruses. Despite its capacity to cause outbreaks in Africa, ONNV remains understudied, and there are currently no approved vaccines or therapeutics to prevent or treat infection and disease. A major barrier to advancing ONNV research has been the lack of suitable animal models to study the virus and investigate host immune responses. We engineered an ONNV infectious clone of a recent clinical isolate sequenced from a patient in Uganda (ONNV0804) that causes robust infection and disease in immunocompetent mice. In the current study, we provide data demonstrating that this contemporary ONNV strain infects rhesus macaques. Notably, rhesus macaques developed detectable viremia, rash, lymphadenopathy, joint and muscle inflammation, and strong innate and adaptive immune responses following subcutaneous ONNV0804 infection. These findings suggest that ONNV0804 infection in macaques is a promising model for studying ONNV pathogenesis and immunity. This model will be instrumental for evaluating future vaccine and therapeutic candidates aimed at preventing ONNV infection and related viral disease.

microbiology↗

bioRxiv2025

Ethylene receptors are functionally conserved in calcium permeability across the green lineage

The gaseous hormone ethylene plays a key role in regulating plant growth and stress responses. Although Ca{superscript 2} has long been implicated in ethylene signaling, the identity of molecules controlling Ca{superscript 2} permeability involved has remained elusive. Here we show that Arabidopsis ethylene receptors ETR1 and ERS1 are Ca2+ permeable, and that ETR1 mediates ethylene-induced cytosolic Ca2+ increase and regulates hypocotyl elongation. Homologs of ETR1 from eight land plant and algal species also exhibit Ca{superscript 2} permeability, suggesting an evolutionarily conserved function. We further demonstrate ethylene enhances the Ca2+ permeability of ETR1 and its homologue from the charophyte Klebsormidium flaccidum. These findings uncover a previously unrecognized but conserved role of ethylene receptors in Ca{superscript 2} permeability regulation in the green lineage, with broad implications for Ca{superscript 2} signaling in plant development and environmental adaptation.

plant biology↗

bioRxiv2025

BandHiC: a memory-efficient and user-friendly Python package for organizing and analyzing Hi-C matrices down to sub-kilobase resolution

Recent advances in high-resolution Hi-C and Micro-C technologies have enabled finer-scale characterization of 3D genome architecture, but they also introduce substantial computational challenges, as the size of dense contact matrices scales quadratically with resolution, resulting in prohibitive memory demands. To address this, we developed BandHiC, a memory-efficient and user-friendly Python package for organizing and analyzing Hi-C matrices down to sub-kilobase resolution. BandHiC adopts a banded storage strategy that preserves only a configurable diagonal bandwidth of the dense contact matrix, reducing memory usage by up to 99% while maintaining fast random access and intuitive indexing operations. In addition, it provides flexible masking mechanisms to handle missing values, outliers, and unmappable regions, and supports efficient vectorized operations optimized with NumPy, thereby enabling scalable analysis of ultra-high-resolution Hi-C datasets.

bioinformatics↗