Biology subjects

Cao, Y.

Publications and source records attributed to Cao, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Epitope and functional classification of human neutralizing antibodies against SFTSV Gn

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a lethal bunyavirus lacking approved countermeasures. From SFTS survivors, we isolate 84 human monoclonal antibodies (mAbs) against the viral glycoproteins Gn and Gc. Gn-specific mAbs demonstrate superior neutralization breadth and potency compared to the restricted neutralizing activity observed with Gc. Using a high-throughput yeast display deep mutational scanning (DMS) platform, we classify Gn-head mAbs into eight epitope groups, among which four groups (IA, ID, IIIA, IIIB) conferring neutralization. Notably, mAbs BD70-4003 (group IA) and BD70-4017 (group IIIA) exhibit broad neutralization and provide 100% protection in a lethal mouse model. Cryo-EM structural analysis of these mAbs in complex with the Gn-head reveal their binding interfaces, directly validating the epitope residues identified by DMS. Our study delineates the antigenic landscape of SFTSV Gn, identifies potent therapeutic candidates, and establishes DMS coupled with structural validation as a powerful framework for antibody discovery against bunyavirus.

immunology↗

bioRxiv2025

Improved spike-in normalization clarifies the relationship between active histone modifications and transcription

Spike-in normalization enables quantitative analysis of ChIP-sequencing (ChIP-seq) signal. Here we introduce a novel robust dual-spike-in normalization approach for ChIP-seq (ChIP-wrangler). We identify optimal conditions, such as the ratio between the spike-in species and the target, demonstrate the ability of this approach to detect technical artefacts, and use ChIP-wrangler to revisit recent claims that active histone marks are dependent on transcription. Concerned that previous studies improperly used spike-in normalization to arrive at their conclusions, we used ChIP-wrangler to show that acute depletion of RNA polymerase II (RNAPII) has only a modest impact on the levels of H3K4me3 and H3K27ac. In line with other studies, our results provide proof that the maintenance of histone acetylation is not merely a consequence of ongoing transcription. Further, we show that promoters and enhancers are differentially impacted by inhibiting transcription. Specifically, of the 5.9% peaks that showed a decrease in H3K27ac following depletion of RNAPII, 82% are promoter-distal and contain enhancer-related DNA binding motifs. Further, the small subset of regions that gain acetylation (0.35%) were enriched for stress response motifs. Our innovative ChIP-seq normalization approach provides increased rigor and "guardrails" for successful spike-in normalization, and as applied here refines the understanding of the intricate crosstalk between RNAPII activity and histone marks associated with transcription.

genomics↗

bioRxiv2025

Inter-areal coupling for cognition through coincident oscillatory transients

How do large-scale functional brain networks dynamically emerge to enable cognition? Correlated oscillations, a mechanism for inter-areal interactions, can be expressed as phase coherence or correlated amplitude fluctuations. While the functional role of phase coherence has been addressed in the past, it remains unknown how large-scale amplitude coupling dynamically supports the rapid network reconfigurations necessary for adaptive behavior. Here, we demonstrate that cognitive processing relies on the temporal alignment of brief, high-amplitude oscillatory events across distant cortical regions, rather than sustained coupling of oscillations. Capitalizing on the spatio-temporal resolution of magnetoencephalography (MEG) during a task probing attention and decision-making, we show that oscillatory event coincidences form functionally relevant, transient networks: First, coincidences of high-amplitude oscillatory events in the alpha and beta frequency range increase prior to correct decisions within a parieto-frontal network. Second, transient theta/alpha oscillatory event coincidences within a medial parietal, temporo-parietal junction and lateral prefrontal network track the dynamics of spontaneous, covert spatial attention reallocation. In contrast, transient aperiodic and sustained network components exhibit only weak functional modulations, revealing a spatial and spectral dissociation between transient and sustained amplitude coupling. Overall, our findings demonstrate that efficient cognition relies on large-scale interactions rapidly formed through co-occurring transient oscillatory events. We propose that the brain-wide orchestration of high-amplitude oscillatory events can provide a new framework for understanding how the brain dynamically integrates information to guide flexible behavior.

neuroscience↗

bioRxiv2025

Contrastive modelling of transcription and transcript abundance in legumes using PlanTT

Predicting the impacts of sequence variation on gene expression remains a challenging task. Further, in plants, we have a limited understanding of the relative contributions of different gene expression regulatory mechanisms. To address these limitations we generated a comparative multiomic dataset comprising matched 3-RNA-seq and PRO-seq data from matched tissues of reference genotypes of four legumes of the invert repeat lacking clade (Pisum sativum, Vicia faba, Lathyrus sativa and Medicago truncatula). Focused on the challenging task of predicting expression differences between ortholog pairs from unseen orthogroups, we used this dataset and a novel prediction framework to build contrastive models that predict quantitative differences (effect size differences) in transcription and transcript abundance.

bioinformatics↗

bioRxiv2025

Large Language Models for Accessible Reporting of Bioinformatics Analyses in Interdisciplinary Contexts

Health and life scientists frequently rely on quantitative experts to perform complex data analyses, yet interpretation of these results often becomes a bottleneck due to communication barriers across disciplines. Large Language Models (LLMs) have the potential to act as intermediaries that translate analytical outputs into accessible scientific narratives, but their ability to reliably interpret outputs from real-world biomedical data analyses across disciplines remains unclear. In this study, we investigate how state-of-the-art LLMs behave when integrated into real bioinformatics analysis workflows as report-generation assistants for interdisciplinary teams. We evaluated LLM-generated summaries using both automated and human evaluation frameworks to ensure holistic evaluation. Automated assessment employed multiple choice questions designed using Bloom's taxonomy to assess multiple levels of understanding, while human evaluation tasked scientists to score summaries for factual consistency, lack of harmfulness, comprehensiveness, and coherence. All generally produced readable and largely safe summaries, confirming their value for first-pass translation of technical analyses, however frequently misinterpreted visualisations, produced verbose summaries and rarely offered novel insights beyond what was already contained in the analytics. Our findings suggest that LLMs are best suited for easing interdisciplinary communication rather than replacing domain expertise and human oversight remains essential to guarantee accuracy, interpretative depth, and the generation of genuinely novel scientific insights.

bioinformatics↗

bioRxiv2025

Bronsted-basic small molecules activate GTP hydrolysis in Ras Q61 mutants

The RAS oncogenes (KRAS, HRAS, NRAS) are among the most frequently mutated genes in human cancer, affecting over three million patients annually. Therapeutic development has largely focused on inhibitors for KRAS codon 12 mutations (G12C/D/V/S/R) which are key drivers in lung, colorectal, and pancreatic cancers. In contrast, mutant-selective inhibitors for Q61 variants remain elusive. A common mechanistic feature of G12 and Q61 mutants is the impaired hydrolysis of GTP, which traps Ras in its active, signaling-competent state. We envisioned that an alternative therapeutic strategy - reactivation of GTP hydrolysis - could address this shared oncogenic mechanism. Here we report small molecules that accelerate GTP hydrolysis in K-Ras Q61 mutants. These compounds compensate for the loss of the catalytic residue Gln61 by introducing a general base into the active site, selectively enhancing hydrolysis of K-Ras Q61X (X = H, L, K, R) mutants by up to 20-fold while sparing the wild-type protein. In mutant cancer cell lines, these compounds reduce GTP-bound Ras levels and suppress downstream signaling. We show that the chemical design principles are generalizable to other Ras isoforms. This work establishes a mechanistic foundation for small-molecule "GTPase activators" and offers a new paradigm for targeting Ras-driven cancers.

cancer biology↗

bioRxiv2025

Captamer: A Novel Quantitative Protein Detecting Method Depending on Aptamer-activated Molecular Switches and RPA Signal Amplification

There are various protein assays for specific and quantitative detection and widely used for laboratory and clinic purposes, but current methods still have limitations. Immunoassays based on antibodies, like ELISA, suffer from slow response and a long antibody-screening period, while physical or electrochemical methods are generally restricted by high cost or the stringent requirement of equipment or operating skills. In this study, we developed an in vitro sensitive protein quantification method: Captamer. The Captamer system comprises a molecular switch derived from aptamer sequence and an exponential fluorescence signal amplification pathway based on recombinase polymerase amplification (RPA). We demonstrated the Captamer for SARS-CoV-2 nucleocapsid protein detection and obtained results from samples within 30 min, displaying a wide detection window from 0.2 pg/mL to 200 pg/mL with high specificity. Furthermore, we tested the Captamer for Tau441 protein (a potential Alzheimers disease biomarker) and thrombin (a classic aptamer-protein interaction model), showing the limit of detection as low as 1 ng/mL and 0.02pg/mL respectively, which suggested the capacity of Captamer to be applied to various aptamer-protein pairs. Compared with the most commonly used and recently reported protein quantification methods, Captamer stands out for its high sensitivity, short response time, low cost, and simplicity, indicating its great potential to be widely used in protein quantification. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/686180v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1e38ffaorg.highwire.dtl.DTLVardef@1019e72org.highwire.dtl.DTLVardef@1498b68org.highwire.dtl.DTLVardef@15f5ea2_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Genetic diversity in horseshoe bat ACE2 and sarbecovirus spike proteins mutually shape one another

Angiotensin-converting enzyme 2 (ACE2) serves as the entry receptor for a wide diversity of sarbecoviruses naturally harboured by horseshoe bats (genus Rhinolophus). Despite the extensive circulation of these viruses in many horseshoe bat species, the potential interactions between virus and receptor evolution remain poorly understood. We sampled individuals of the intermediate horseshoe bat (Rhinolophus affinis) across Vietnam and identified 15 genotypes of ACE2 proteins, 10 of which are previously unreported. Phylogenetic analysis and infectivity assays with a panel of 36 sarbecovirus spike proteins indicated that the R. affinis ACE2 phylogeny has geographic structuring and genotypes originating from different geographic regions exhibit distinct infectivity phenotypes. We detected site-specific positive selection on ACE2 site 24 with the associated substitutions largely affecting the receptors sarbecovirus infectivity profile. Together, our findings suggest that the R. affinis within-species ACE2 diversity has likely been shaped through selection by past sarbecovirus infection. Similarly on the virus end, we use mutagenesis assays and structural analysis through cryo-EM, to delineate the proximal evolution of the Ra22QT77 spike defined by specialization to the ACE2 genotypes of horseshoe bats found in and near southern Vietnam, where the virus was sampled. Our findings contribute to a better understanding of host-sarbecovirus co-evolution dynamics and provide valuable insights into the receptor usage determinants of these viruses. HighlightsO_LIWe identify a total of 15 ACE2 genotypes in R. affinis bats from Vietnam. C_LIO_LIACE2 intraspecific polymorphism is geographically separated and associated with distinct sarbecovirus infectivity. C_LIO_LISite 24 of R. affinis ACE2 experiences positive selection and controls susceptibility to sarbecoviruses. C_LIO_LIBat ACE2s and sarbecovirus spikes are bidirectionally shaped by each others evolution. C_LI

microbiology↗

bioRxiv2025

Predicting SARS-CoV-2 evolution dynamics with spatiotemporal resolution by DMS-empowered protein language model

Early identification of emerging dominant SARS-CoV-2 variants is essential for effective pandemic preparedness, yet existing methodologies face significant limitations. Experimental characterizations are costly and not feasible for real-time surveillance, whereas existing computational approaches cannot achieve satisfactory precision in predicting future dominant lineages and fail to capture the spatiotemporal dynamics of fitness under evolving host immune pressures. Here, we introduce DeepCoV (DMS-Empowered Evolution Prediction of CoronaVirus), a deep-learning framework for the dynamic identification of novel variants with high potential to become prevelent. It integrates deep mutational scanning (DMS)-derived mutation phenotypes with epidemiological surveillence data reflecting historical viral evolution and the dynamic fitness landscape. DeepCoV accurately forecasted the dominance of recently circulating lineages a month in advance, achieving a 90% reduction in false discovery rate while capturing temporal and geographic dynamics of variant spread and reconstructing their regional prevalence trajectories. Moreover, DeepCoV identified mutational hotspots of Omicron-derived backbones in silico, revealing convergent evolution trends. This scalable solution enables timely identification of immune-evasive variants and prospective alert of critical mutations, providing actionable insights for vaccine updates and pandemic surveillance.

microbiology↗

bioRxiv2025

Decoding Peripheral Tolerance: TCR Rules for pTreg differentiation in the Gut

Peripheral differentiation of regulatory T cells (pTregs) promoted by foreign antigens encountered in barrier tissues is considered a unique contributor to immunological tolerance to obligate non-self, like food or symbiotic microbes. The relative importance of adaptive recognition via the T cell receptor (TCR) vs environmental small-molecule or neuroimmune cues, is poorly understood. We leverage CRISPR-based TCR editing to perform in primary T cells in vivo, with a large panel of TCRs, a screen to assess pTreg differentiation induced by self, microbial, or dietary antigens. All antigen classes drive pTreg differentiation, which varies with the origin of the TCR: TCRs derived from Tregs enable pTreg differentiation much more effectively than those from Tconv. TCRs recognizing self, microbial, or dietary antigens elicit distinct pTreg phenotypes, Helios, ROR{gamma}, or both. Mechanistically, these trace to different types of antigen-presenting-cell involved. That Treg-derived TCRs preferentially drive tolerogenic fate speaks to preferential drivers of tolerogenic therapy.

immunology↗

bioRxiv2025

Targeting the host factor HGS-viral membrane protein interaction in coronavirus infection

While current antivirals primarily target viral proteins, host-directed strategies remain underexplored. Here, we performed a genome-wide CRISPRi screening to identify the host protein, Hepatocyte Growth Factor-Regulated Tyrosine Kinase Substrate (HGS), as essential for the pan-coronaviruses infection both in vitro and in vivo. Mechanistically, HGS directly interacts with the viral membrane (M) protein, facilitating its trafficking to the ER-Golgi intermediate compartment (ERGIC) for virion assembly. Conversely, HGS deficiency caused M retention in the ER, blocking assembly. Leveraging this interaction, we designed M-derived peptides and screened over 5,000 FDA-approved drugs, identifying riboflavin tetrabutyrate (RTB). Both the peptides and RTB bind HGS and disrupt its interaction with the M protein, leading to M retention in the ER and subsequent blockade of virion assembly. These agents demonstrated broad anti-pan-coronavirus activity in vitro and in vivo. Collectively, our findings establish HGS as a druggable host target and identify RTB as a promising broad-spectrum antiviral candidate.

microbiology↗

bioRxiv2025

DEEPReditor-CMG: A deep-learning-based predictive RNA editor for crop mitochondria genomes

C-to-U RNA editing is a pervasive phenomenon in crop mitochondria, playing a pivotal role in the processing of functional proteins encoded by mitochondrial genes and serving as a crucial regulatory mechanism for nuclear control over mitochondrial gene expression. However, identifying editing sites across the mitochondrial genome with high precision remains a formidable challenge. To address this challenge and uncover the potential regulatory patterns of C-to-U RNA editing, this study compiled a comprehensive dataset of mitochondrial genome sequences from 13 crops, including Arabidopsis thaliana, Lactuca sativa var. Capitata, Oryza sativa Japonica, and Zea mays, among others, annotated with editing sites from NCBI. Utilizing TensorFlow 2.0, we constructed a rigorous hyperparameter optimization framework, which facilitated the development of the DEEPReditor-CMG model, demonstrating superior predictive capabilities. Based on the DEEPReditor-CMG model and three interspecies relationship indices, we discovered that species with closer phylogenetic relationships exhibit more similar C-to-U RNA editing mechanisms, providing valuable insights into the evolutionary conservation of RNA editing mechanisms. We further developed executable programs for predicting C-to-U RNA editing sites in crop mitochondrial genomes, leveraging the conserved nature of the crop RNA editing machinery to maximize prediction reliability and uncover new editing sites with great potential. This research not only deepens our understanding of C-to-U RNA editing and post-transcriptional regulatory mechanisms in crop mitochondria but also paves a novel avenue for investigating RNA editing mechanisms. Experimental data, computational code, and applications are publicly accessible at https://github.com/Qinsidong/DEEPReditor-CMG. HighlightsHigh-precision prediction model for C-to-U RNA editing in crops--DEEPReditor-CMG Three interspecies relationship indices describing C to U RNA editing Prediction tools based on the conservation of crop RNA editing mechanisms Open-sourced experimental data, computational code, and applications

bioinformatics↗

bioRxiv2025

Machine learning-based definition of cellular senescence reveals pro-senescence potential implication in lung adenocarcinoma

Despite growing evidence implicating cellular senescence in tumor progression, methodological challenges in objectively quantifying senescent cell burden across cancer types continue to limit mechanistic studies and clinical translation. To address this, we developed the Predictive Cellular Senescence Model (PreCSenM), a machine learning-based tool that assigns a CS score by integrating senescence-associated features across 888 samples. Benchmarking analyses confirmed that PreCSenM markedly outperforms existing methodologies in reliably predicting senescent states within both normal and cancerous transcriptomic datasets. In lung adenocarcinoma (LUAD), PreCSenM identified the CS score as a robust predictor of clinical outcomes. Multi-omics analyses further revealed that lower CS levels correlate with decreased genomic stability and enhanced immune responses, aligning with clinical observations. Notably, drug discovery using PreCSenM identified histone deacetylase inhibitors (HDACis) as potent inducers of CS in LUAD. Transcriptional and epigenetic profiling of HDACi-treated cells pinpointed FOSB as a core transcription factor driving CS, and FOSB knockdown blocked HDACi-induced senescence. Overall, our study establishes PreCSenM as a multidimensional senescence quantification tool, bridging computational prediction with clinical relevance and mechanistic validation to enable senescence-directed therapies in precision oncology.

bioinformatics↗

bioRxiv2025

Conformational Variability of HIV-1 Env Trimer and Viral Vulnerability

HIV-1 envelope glycoprotein (Env) is critical for viral fusion and entry into host cells and remains a primary target for vaccine and antiviral drug development. Advances in soluble gp140 trimer design have provided insight into the ectodomain structure and dynamics. While structural information is available for the membrane-proximal external region (MPER) and transmembrane domain (TMD), these regions remain comparatively understudied. Furthermore, high-resolution structural information for the cytoplasmic tail (CT), particularly within the context of the intact trimer, is limited and largely uncertain. Additionally, previous studies have typically treated the ectodomain and TMD as separate entities. To investigate the trimeric gp120-gp41 as a complete entity and its structural flexibility, we built a full-length model of the gp120-gp41 trimer that is fully glycosylated with N-linked glycans and embedded in a lipid bilayer, and performed all-atom molecular dynamics simulations. Our results show that the ectodomain maintains a rigid internal structure stable in the prefusion state, whereas the intrinsic flexibility of the MPER enables the ectodomain to adopt a range of tilted orientations, potentially enhancing spatial alignment for receptor engagement. The centrally positioned R696 residue in the TMD interacts with lipid headgroups, ions, and CT residues, resulting in conformational variability in the TMD and perturbations in the surrounding membrane that may facilitate the fusion process. Finally, we demonstrate how simulation trajectories can be leveraged to evaluate the accessibility of antibody epitopes across different regions of the protein.

biophysics↗

bioRxiv2025

A dual information seeking strategy improves imprecise human inferences outside the explore-exploit tradeoff

Everyday decisions aim not only to earn rewards but also to learn about the world. Across three studies (total N = 702), we examined how people gather epistemic information stripped of rewarding value, and compared their strategy with reward seeking in otherwise matched conditions. Computational modeling of human behavior revealed a two-stage information-seeking policy, where participants first repeatedly sample each novel option in turn to test provisional hypotheses, a process we call streaking, before transitioning to uncertainty-guided exploration. While artificial neural networks trained to optimize inference accuracy acquired uncertainty-guided exploration but not early streaking, this two-stage policy improves human inference accuracy under noisy belief updating. Streaking and uncertainty-guided exploration tend to be co-expressed in the same individuals but map onto distinct psychological traits. Together, these results offer a novel account of human information seeking, clarifying its motives and benefits in epistemic contexts beyond the reward-centric explore-exploit tradeoff.

neuroscience↗

bioRxiv2025

Nutritional hyperketonemia by dietary medium-chain fatty acids is driven by the liver without contribution from the intestine

Saturated medium-chain fatty acids (MCFAs) are ketogenic nutrients, and their dietary intake has been linked to health benefits such as improved energy balance and increased insulin sensitivity. Here, we tested the hypothesis that MCFA-mediated hyperketonemia is required for these benefits. Using tissue-specific 3-hydroxy-3-methylglutaryl-CoA synthase 2 (Hmgcs2) knockout mouse models, we show that the hyperketonemia induced by oral administration of triacylglycerols with the MCFA octanoic acid (C8:0-MCT) is mediated by hepatic, but not intestinal, ketogenesis. Remarkably, acute reductions in food intake and body weight induced by C8:0-MCT in obese mice were independent of hepatic ketogenesis; likewise, chronic protection against weight gain and marked improvements in insulin sensitivity elicited by MCFA-rich diets did not require hepatic ketogenesis. These data demonstrate that dietary MCFAs are potent bioactive lipids capable of inducing metabolic benefits independently of their ketogenic properties.

physiology↗

bioRxiv2025

BenchHub enables an inclusive and transparent ecosystem for community-focused benchmarking in computational biology

The rapid growth of computational methods for the computational biology field highlights the critical role of benchmarking in guiding method selection. However, there is no standardised data structure that effectively links and stores datasets, performance metrics and available ground truth. Without such a unified and shareable structure, it is difficult for the community to contribute, update and extend existing benchmarking studies to ensure long-term relevancy. To address this challenge, we present BenchHub, a community-oriented ecosystem with a modular R6-based structure that enables "living benchmarking." BenchHub comprises three key components: (i) a Trio database that links datasets, performance metrics, and supporting evidence (e.g. ground truth), (ii) a BenchmarkStudy structure that captures the different benchmark study designs, and (iii) a series of tools together with vignettes and interactive platform that allow users to gain insights from the benchmarking results. Together, these components streamline the benchmarking process for benchmark study developers, methods contributors, and benchmark consumers, promoting reproducibility, comparability, and long-term sustainability in computational biology.

bioinformatics↗

bioRxiv2025

Fetal and maternal immune cells exhibit tandem maturation across gestation and dysregulation in preterm birth

Appropriate regulation of maternal immune cells in the pregnant uterus is essential for successful pregnancy, yet the impact of immune cells in placental villi (PV) on placental health remain understudied. We enriched immune cells from term and preterm PV for transcriptomic and functional analyses. Maternal and fetal immune cells were abundant, with maternal chimerism increasing at term. Fetal lymphocytes displayed enhanced prostaglandin-D signatures, while maternal lymphocytes were enriched for antigen presentation pathways. Inflammatory cytokines and expanded maternal and fetal T cell clones peaked at term but did not induce cytotoxicity in placental organoids, whereas expanded T cells from idiopathic preterm cases impaired trophoblast growth and endocrine function ex vivo. These findings reveal significant immune chimerism within PV in both health and disease yet implicate PV T cells in idiopathic preterm birth. One Sentence SummaryFetal-maternal immune chimerism is characteristic of all placental villi, yet unchecked T cells and cytokines can hinder trophoblast growth and potentially precipitate preterm birth.

immunology↗