Biology subjects

He, Y.

Publications and source records attributed to He, Y..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Optimized Kakadu Plum Extracts Inhibit Intracellular Oxidative Stress in Canine Small Intestinal Cell Model

Kakadu plum (Terminalia ferdinandiana), an Australian native fruit, is among the richest known dietary sources of vitamin C and hydrolysable tannins, yet its capacity to protect the intestinal epithelium against oxidative stress remains largely unexplored. This study optimised the extraction of bioactive compounds from freeze-dried Kakadu plum powder and evaluated their antioxidant activity using both chemical and cellular antioxidant in vitro assay. Phenolic compounds were extracted using three solvents (water, 80% ethanol, and 80% methanol) combined with shaking, ultrasound, or microwave assistance. Solvent, rather than processing technique, was the dominant determinant of antioxidant capacity: ethanol and methanol maximised total phenolic content, total flavonoid content, and DPPH radical-scavenging activity, whereas water extracts showed the highest ferric-reducing antioxidant power. Twenty-four phenolic compounds identified by HPLC-ESI-QTOF-MS/MS were mapped by network pharmacology to nine core oxidative-stress targets, and cross-species molecular docking predicted conserved binding of key phenolics to canine orthologs of PTGS2 and MMP2. In an H2O2-induced oxidative-stress in vitro cell model using canine small intestinal epithelial cells, both water (less than 25 ug/mL) and ethanol (less than 250 ug/mL) extracts significantly suppressed intracellular reactive oxygen species (ROS) in a dose-dependent manner, with the ethanol extract effective across a wider concentration range. This work demonstrated that Kakadu plum extract could be a promising natural, multi-target antioxidant ingredient for canine intestinal health, and provided a reference for future in vivo research.

biochemistry↗

bioRxiv2026

Endothelial ANGPT2 insufficiency impairs retinal vascularization with ROP-like neovascular tufts

ANGPT2 is widely recognized as a critical regulator of pathological neovascularization. By analyzing scRNA-seq data from neonatal retinas, we demonstrate that Angpt2 transcripts are highly enriched in tip cells relative to other endothelial subtypes, where Angpt1/4 expression is absent. However, mechanisms underlying ANGPT2 function at angiogenic fronts remain inadequately understood. Here, we show that endothelial Angpt2 deletion severely disrupted retinal vascularization, characterized by neovascular tufts and micro-hemorrhage. Similar angiogenic defects also occurred in the brain, but were less evident in other tissues examined. Mechanistically, ANGPT2 insufficiency attenuated retinal tip cell invasion with aberrant mural cell coverage, compromising sprouting into non-vascularized tissues. Retinal RNA-seq analysis revealed that transcripts associated with endothelial migration and junction assembly were reduced in Angpt2 mutants compared to littermate controls, while upregulated genes were enriched in hypoxia-responsive pathways and mural cell development. Notably, abnormal mural-tip cell associations were detected within 48 hours post-Angpt2 deletion, displaying also a hypoxia-driven transcriptomic signature. These closely resemble the vascular pathologies observed in human retinopathy of prematurity. In contrast, Angpt1 insufficiency or Angpt4 deficiency primarily affected venous morphogenesis. Collectively, our findings imply that ANGPT2 is essential for driving tip cell invasion during sprouting angiogenesis, and that its insufficiency triggers hypoxia-driven vascular anomalies.

developmental biology↗

bioRxiv2026

A Conserved Flexible N-Terminal Domain Tunes the Calcium Sensitivity of Sorcin by Stabilizing Its Active Conformation

Sorcin is a penta-EF-hand Ca2+-binding protein that acts as a Ca2+ sensor and regulator of Ca2+ homeostasis. Although the structure and Ca2+-dependent activation of Sorcin is well characterized, the function of its flexible N-terminal domain (NTD) remains unclear. We combined sequence analysis, Ca2+-induced aggregation assays, multidimensional NMR spectroscopy, and long-timescale molecular dynamics (MD) simulations to define the NTDs role in Sorcin activation. Sequence comparisons showed that the NTD is conserved across vertebrates despite its intrinsic disorder, indicating functional importance. NTD deletion markedly reduced Ca2+ responsiveness. Relative to full-length Sorcin, the construct with NTD truncation required more than twofold higher Ca2+ concentrations and over tenfold higher protein concentrations to initiate aggregation, while aggregation kinetics slowed by nearly three orders of magnitude. Temperature-dependent measurements yielded an apparent activation energy of 36.7 kJ{middle dot}mol-1, consistent with aggregation driven by Ca2+-induced conformational activation rather than denaturation. NMR chemical shift perturbations localized the effects of NTD removal to the EF-hand Ca2+-binding loops and adjacent D-helix. Apo-state MD simulations revealed transient intra- and intermolecular NTD-SCBD contacts that explain some perturbations and support direct and allosteric regulation. Ca2+-bound simulations further showed that SCBD departs more readily from the crystallographic active conformation than full-length Sorcin, indicating that the NTD stabilizes the active state through dynamic contacts. Together, these findings establish the NTD as a critical regulator that enhances Ca2+ responsiveness by shifting Sorcins conformational equilibrium toward the active state and suggest that flexible N-terminal extensions regulate signaling within the penta-EF-hand protein family.

biophysics↗

bioRxiv2026

PlumageParts: A fine-grained avian plumage segmentation dataset and benchmark for ecological image analysis

Fine-grained localisation of plumage regions is a prerequisite for computational analyses of avian colouration, patterning and visual traits in ecological and evolutionary research. Progress is limited by the scarcity of image resources with annotations aligned to biologically meaningful anatomical units: existing avian benchmarks provide either landmark points or coarse part categories that do not capture ornithologically defined plumage regions. We present a curated dataset of 4,705 bird images annotated for nine plumage regions: head, throat, breast, belly, vent, back, coverts, remiges and tail. Spanning 39 avian orders and 222 families, the dataset provides a taxonomically broad resource for fine-grained avian image analysis. The dataset was built through an iterative model-assisted annotation workflow, in which model predictions were reviewed and corrected rather than drawn from scratch, improving the efficiency of region-level annotation. We benchmark classical segmentation architectures, SAM-based models and self-supervised foundation-model encoders on this task. A frozen DINOv3 encoder with a lightweight decoder achieved the highest performance on the held-out test set, reaching 84.01% mean Intersection over Union while requiring substantially less memory than end-to-end fine-tuning. The model generalised to external avian benchmarks, including the bird subset of PartImageNet and CUB-200-2011, and achieved competitive performance on the full PartImageNet part-segmentation benchmark, which includes diverse animal taxa. We provide a modular detect-track-segment pipeline as a proof-of-concept extension to video data. Together, these results show that anatomically grounded avian annotations can serve both as a resource for plumage phenotyping and as a benchmark for efficient, transferable biological part segmentation. Author SummaryBirds vary enormously in colour and pattern, but studying this variation at large scales requires more than identifying the bird in a photograph. Researchers often need to know where each colour or pattern occurs on the body, such as on the head, throat, breast, wing or tail. We created PlumageParts to make this kind of region-level analysis easier. The dataset contains 4,705 bird images annotated into nine biologically meaningful plumage regions, covering a wide range of bird families and orders. To build the dataset efficiently, we used a model-assisted workflow in which computer-generated masks were checked and corrected by researchers rather than drawn entirely by hand. We then tested several image-segmentation approaches and found that a frozen self-supervised vision model, combined with a lightweight decoder, provided accurate plumage-region predictions while requiring relatively modest computing resources. The same approach also performed well on a broader animal part-segmentation benchmark, suggesting that it may be useful beyond birds when suitable annotations are available. By releasing the annotations, code and trained model, we aim to support future studies of bird plumage and biologically meaningful image segmentation.

ecology↗

bioRxiv2026

Microbial evolution, biogeochemical functions, and environmental adaptations in a desert saline lake on the Qinghai-Tibet Plateau

The Eboliang Hu saline lakes in the hyper-arid Qaidam Basin is a high-altitude, weakly acidic hypersaline system with strong environmental gradients and limited nitrogen availability. To resolve its microbial ecology and evolutionary context, we performed genome-resolved metagenomic sequencing across four distinct habitats, reconstructing 46 medium- to high-quality metagenome-assembled genomes (MAGs) and a comprehensive gene catalog. The community shows pronounced spatial heterogeneity and is dominated by Thermodesulfobacteriota, Pseudomonadota, Bacteroidota, and archaeal lineages. Phylogenomic placement and large-scale sequence comparisons indicate that multiple dominant taxa exhibit affinity to marine- and subsurface-associated reference lineages, consistent with long-term isolation of a marine-derived ecosystem about 10-11 million years ago. Functional reconstruction reveals a distributed metabolic system in which carbon, nitrogen, and sulfur cycling are partitioned across taxa. Notably, hydrogen oxidation and arsenite oxidation are recurrent energy-producing strategies across dominant lineages, indicating redox flexibility under oligotrophic conditions. Comparative genomics further suggests lineage-specific adaptations to osmotic stress, UV exposure, and nutrient limitation. Horizontal gene transfer and phylogenetic incongruence among key metabolic genes indicate that co-evolutionary processes and gene exchange have contributed to functional innovation. These findings provide a framework for understanding microbial persistence and evolution in isolated extreme environments and offer potential analogs for extraterrestrial habitability.

ecology↗

bioRxiv2026

Nicotinamide N-methyltransferase couples inflammation and epigenetic remodelling to hepatic fibrosis

Background & aimsChronic inflammation is a key driver of progression from benign steatosis to metabolic dysfunction-associated steatohepatitis (MASH) and liver fibrosis. The molecular mechanisms coupling inflammatory cytokine signaling to altered hepatocyte remodeling remain incompletely understood. Here, we report that nicotinamide N-methyltransferase (NNMT) is induced by specific inflammatory cytokines in hepatocytes and acts as a key hub to connect inflammation with fibrotic liver remodeling. Approach & resultsTranscriptomic profiling of primary human hepatocytes and human hepatoma cell lines identified NNMT as a selective downstream target of IL-1{beta} and IL-6, but not of TNF. Genetic silencing of NNMT markedly attenuated cytokine-induced inflammatory and fibrotic gene expression programs and partially reversed IL-6-mediated sensitization of IL-1{beta} responses. Integration of RNA-seq with ChIP-seq, CUT&Tag, and ATAC-seq revealed that inflammatory cytokines remodel the hepatocyte epigenome through coordinated changes in histone modifications. NNMT overexpression promoted selective remodeling of H3K4me2 chromatin landscapes, accompanied by activation of fibrosis-associated transcriptional programs. Nicotinamide supplementation partially suppressed inflammatory gene expression, supporting a role of NNMT-dependent NAD+ metabolism in this process. Importantly, cytokine-induced NNMT expression and its associated transcriptional program were conserved in primary human hepatocytes and 3D liver microtissues. ConclusionsNNMT functions as an inflammatory cytokine-inducible metabolic- epigenetic integrator that links IL-1{beta} and IL-6 signaling to chromatin remodeling and inflammatory transcriptional reprogramming in hepatocytes. These findings identify NNMT as a key regulator of inflammatory and profibrotic responses during MASLD progression and highlight NNMT as a potential therapeutic target for limiting liver inflammation and fibrosis. Impact and ImplicationsThis study identifies NNMT as a previously unrecognized metabolic-epigenetic integrator that selectively links IL-1{beta} and IL-6 signaling to chromatin remodeling and inflammatory transcriptional reprogramming in hepatocytes. Our findings establish a non-canonical mechanistic framework by which inflammatory cytokines drive profibrotic gene expression during MASLD progression through. By uncovering NNMT as a critical mediator of inflammatory-epigenetic crosstalk, this work broadens our understanding of hepatocyte-intrinsic mechanisms underlying liver fibrosis and highlights NNMT as a promising therapeutic target for preventing the transition from steatosis to progressive MASH and fibrosis. HighlightsO_LINNMT is selectively induced by IL-1{beta} and IL-6 in hepatocytes. C_LIO_LINNMT controls fibrogenic gene expression modules. C_LIO_LIIL-6 amplifies IL-1{beta} responses through an NNMT-dependent mechanism. C_LIO_LINNMT links inflammatory signaling to epigenetic remodeling in MASLD. C_LI

molecular biology↗

bioRxiv2026

Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models

Accurate predictions of transcriptomic responses to genetic perturbations could unlock our understanding of gene functions and regulatory networks. While a growing number of methods and benchmarks target this task, existing evaluations focus on mean expression accuracy alone. This overlooks differential expression (DE), which captures both mean and variance and forms the basis for biological interpretation and experimental follow-up. Here, we systematically evaluate a diverse set of deep learning and non-deep-learning methods for their ability to predict DE outcomes under two generalization regimes: unseen perturbations within the same cell line, and unseen cellular contexts across cell lines. We find that simple baselines, such as embedding-based nearest neighbors, are competitive and often outperform specialized deep learning models for DE classification across datasets and evaluation metrics. We further show that sparsity calibration, motivated by the structure of single-cell data, substantially improves DE classification for deep learning models that do not explicitly account for sparsity. Together, our findings establish practical baselines and evaluation principles for benchmarking perturbation models on DE prediction.

genomics↗

bioRxiv2026

Multidimensional variation and population stratification across 8000 complete human centromeres

Human centromeres are indispensable for the faithful segregation of chromosomes during cell division, yet their highly repetitive nature has historically precluded comprehensive characterization, leaving fundamental questions about their sequence diversity, evolution trajectories and function dynamics unresolved. Here, we generated 6,312 complete human centromere sequences from 320 phased genome assemblies in Asian Pan-Genome project phase 1. By integrating the assemblies from the Human Pangenome Reference Consortium (HPRC) and Human Genome Structural Variation Consortium (HGSVC), we constructed a multidimensional genetic variation map encompassing over 8,000 gapless centromeres. Centromeric satellite arrays account for 4.19% to 6.01% of the whole genome, with substantial variations in size and architecture across chromosomes. Using a refined alpha satellite clustering approach that captures global diversity, we identified 195 higher-order repeat (HOR) arrays, 56.4% of which are absent from the T2T-CHM13 reference genome. Extensive structural variations across multiple dimensions exhibit population stratification, including centromeric haplotypes (CenHaps), ultra-large pericentric inversions spanning up to 36.6 Mbp, and inter-chromosomal HOR sharing that reflects sequence exchange among chromosomes. Integrating CENP-A CUT&Tag experiments and long-read-based DNA methylation profiles, we demonstrate that 16.8% of centromeres harbor multiple potential kinetochore assembly sites, and CenHap-specific local HOR homogenization is associated with kinetochore positioning. Despite global suppression of recombination at centromeres, we observed asymmetric linkage disequilibrium flanking centromeres and an ancient recombination event within the centromere of chromosome 19. Furthermore, contrary to the prevailing assumption of high mutation rates in centromeres, our estimates based on stringent orthology reveal no significantly higher single-base substitution rates for centromeres relative to flanking pericentromeric regions with substantial variations across chromosomes, despite extraordinary structural plasticity. Collectively, these multi-scale centromeric variations provide a global view of human centromere diversity and population stratification, fundamentally redefine centromere evolution through a dual-track model balancing structural innovation with mutational constraint, and establish an essential resource for investigating centromere biology and a baseline reference for diagnosing centromere-associated disorders.

genomics↗

bioRxiv2026

Reconstructing sequence-grammar trajectories enables interpretable and tunable cis- regulatory element design

Designing synthetic cis-regulatory elements (CREs) with cell-type-specific activity remains challenging, and optimization is usually treated as a black box, obscuring how regulatory grammar emerges and why design trajectories fail. Here, we present GO-CRE (Guided Optimization of Cis-Regulatory Elements), which combines efficient sequence generation, predictor-guided reinforcement learning, and trajectory-level interpretation. GO-CRE reconstructs iterative sequence changes in a shared sequence-grammar landscape and identifies coordinated update programs corresponding to search, commitment, and optimization. Productive trajectories in HepG2 and K562 progressively acquired cell-type-associated grammar, whereas SK-N-SH trajectories remained confined to local basins. In HepG2, trajectory analysis revealed a low-complexity polyG trap; introducing a polyG penalty redirected optimization toward HNF/FOXA-associated features. Final designs retained sequence diversity while converging on cell-type-associated motif patterns. Lentiviral MPRA validated cell-type-specific activity in K562 and HepG2 and showed higher average activity of HepG2 designs than endogenous CREs. Together, these findings establish sequence-grammar trajectory reconstruction as a basis for interpretable and tunable synthetic CRE design.

genomics↗

bioRxiv2026

Necroptotic Signalling Diverts Keratinocyte Fate to Promote Differentiation and Slow Wound Healing

Necroptosis is best known as a lytic, proinflammatory cell-death pathway mediated by RIPK3 and MLKL. Effective wound repair requires the rapid resolution of inflammation, and ongoing necroptotic activity would only exacerbate tissue damage, delaying healing. However, damaged skin presents a trigger-rich environment for necroptotic signalling, an apparent paradox that remains unresolved. Using genetic ablation and pharmacological inhibition across multiple wound models, we show that inhibiting necroptosis accelerates wound closure, revealing that necroptotic signalling normally restrains repair. Surprisingly, we found that MLKL activation in wild-type keratinocytes induces differentiation and membrane repair rather than cell lysis. This adaptive, non-lethal mode of necroptotic signalling preserves barrier integrity but slows re-epithelialisation. Our findings redefine epidermal necroptotic signalling as a stress-responsive program that modulates keratinocyte fate in a trigger-rich environment. Temporarily dampening this pathway may enhance regeneration after barrier loss without compromising immune defence, revealing necroptosis as a tunable mechanism balancing tissue repair and inflammation.

cell biology↗

bioRxiv2026

Placental invasion mismatch underlines pregnancy disorders and cancers

Mammalian placentas vary dramatically in invasiveness, parallel aggressive cancers, and are dysregulated in pregnancy disorders, yet whether they share regulatory architecture remains unclear. We investigated single-cell transcriptomes of the maternal-fetal interface across nine mammals spanning all major placental morphotypes and integrated it with thirteen cancers and five pregnancy complications. A conserved cellular framework is deployed through three discrete regulatory programs: a cancer-like program in hemochorials, endothelial-cooperation program in endotheliochorials, and collagen-rich invasion-suppressing program in epitheliochorials. Aggressive cancers selectively converge on hemochorial program, and we functionally validated share invasion regulators including the VGLL3-TEAD1 interaction and APOE. Pregnancy disorders are partially, mismatched deployments of these programs; placental APOE knockdown in mice phenocopies preeclampsia with concurrent collapse of both M1/M2 macrophage programs. These findings unify placental diversity, cancer convergence, and obstetric disorders under a regulatory-mismatch principle, whereby evolved placental invasion programs becomes pathological when deployed outside their evolutionary context.

evolutionary biology↗

bioRxiv2026

PLANCK: super-multiplex optical imaging without labeling

Molecular information is vital for imaging technology. Optical imaging acquires molecular specificity almost exclusively via labeling strategy, which is fundamentally constrained by limited multiplexing capacity, high running costs, and experimental complexity. Conversely, label-free optical imaging offers substantial technical simplicity but is believed to have little true molecular specificity. Contrary to common belief, here we introduce super-multiplex optical imaging without labeling. By systematically studying paired vibrational spectroscopic imaging and mass spectrometry imaging, we discovered a surprisingly strong (more than 0.9) correlation between their latent space representations, supported by both experiments and theory. This insight prompts us to build supervised learning models to successfully predict spatial distribution of 100 molecular species directly from label-free vibrational images across diverse tissue systems. We developed this technology, named Prediction through Learning with AdvaNced Chemical Kaleidoscope (PLANCK), and demonstrated it with both infrared-based vibrational imaging of organ-scale tissues and Raman-based vibrational imaging of live tissues. Powered by AI, PLANCK decodes the exquisitely rich but otherwise hidden vibrational information into a surprisingly large number of ( [≥] 100) specific molecular species, providing a cost-effective and scalable solution for basic research and translation, including applications in live imaging.

biophysics↗

bioRxiv2026

Sphingosine 1-phosphate lyase expressed in pulmonary epithelial cells potentiates host innate defenses and alleviates influenza pathogenicity in mice

Influenza viruses circulate in humans, causing a substantial burden on global health. Investigation of influenza-host interactions could identify host factors that regulate influenza pathogenicity. Sphingosine 1-phosphate (S1P) is a bioactive lipid mediator and regulates crucial cellular processes. S1P lyase (SPL), an enzyme that mediates S1P degradation, was shown to display anti-influenza activity in a cell culture system. Here, we constructed a mouse model to demonstrate the antiviral function of SPL in respiratory epithelial cells during influenza in vivo. Deletion of SPL from lung epithelial cells exacerbated influenza-induced weight loss and mortality. Influenza virus began to propagate more effectively in the absence of SPL at the innate immune stage. Increased virus titers were sustained during influenza and associated with enhanced accumulation of multiple immune cell types in the lungs. Single-cell RNA sequencing was conducted to further define the function of SPL in lung epithelial cells. SPL deletion increased the proportion of alveolar type 1 (AT1) cells compared to alveolar type 2 (AT2) cells with alteration of the related signaling pathways, suggesting a role of SPL in AT1/AT2 programming. Importantly, host innate defense pathways were changed in SPL-deficient lung epithelial cells upon infection, which corroborates the antiviral function of SPL. This study elucidates the host protective function of SPL in lung epithelial cells during influenza and provides gene signature profiles critical for SPL-mediated alleviation of influenza pathogenicity. The findings may contribute to development of host-directed therapeutics to better control influenza.

microbiology↗

bioRxiv2026

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

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

cancer biology↗

bioRxiv2026

A Glutamine antagonist-modulated tumor microenvironment unleashes enzalutamides immunotherapeutic effects

Androgen receptor (AR) antagonists, such as enzalutamide, suppress prostate cancer (PCa) cells to achieve temporary therapeutic effects. In addition to tumor cell-autonomous suppressive function, AR antagonists can also potentially exert anti-tumor effects via mitigating cytotoxic T cells exhaustion. However, strategies for effectively harnessing enzalutamides immunotherapeutic effects remain elusive. In studying a recently described glutamine antagonist prodrug (DRP-104) in PCa models, we found that despite the initial response, tumors ultimately became resistant. Intriguingly, compared to the untreated (DRP-104 treatment-naive) tumors, the resistant tumors became highly susceptible to enzalutamide in vivo. Additionally, treating tumors with DRP-104 and enzalutamide simultaneously also yielded superior therapeutic efficacy. We demonstrated that DRP-104 therapy promoted the infiltration of CD8+ T cells as well as regulatory T cells (Treg) in responsive tumors, and the tumor-infiltrating Treg were mostly depleted upon enzalutamide treatments. Mechanistically, we showed that Treg differentiation from mouse CD4+ T cells was attenuated by enzalutamide. We further demonstrated that Treg induction was accompanied by the interaction between AR and aryl hydrocarbon receptor (AhR), the nuclear receptor indispensable for Treg differentiation, in the nuclei of CD4+ T cells, and this interaction was diminished by enzalutamide. In further support of AR signaling in Treg biogenesis, analysis of available gene expression datasets found that AR expression was elevated in Treg when compared to CD4+ T cells in human peripheral blood mononuclear cells (PBMCs). In addition, it was positively correlated with Treg module scores in several human cancer types. Finally, using an anti-GPC3 (Glypican 3) vaccination model, we demonstrated that CD4+ T cells subjected to Treg induction in the presence of enzalutamide were less effective in protecting GPC3-expressing tumor cells from CD8+ T cells cytotoxic killing. Collectively, these results suggest that AR promotes Treg s differentiation and/or immunosuppressive functions, and nominate enzalutamide as a Treg-mitigating agent for potentiating immunotherapies. Our results also demonstrate that an otherwise unintended, Treg-promoting property of DRP-104 can be leveraged to unleash the immune-regulatory function of enzalutamide for the treatment of PCa.

cancer biology↗

bioRxiv2026

Single-Cell Transcriptomic Analysis of the Immune Response to CHIKVInfection

BackgroundThe Chikungunya virus (CHIKV), a re-emerging mosquito-borne alphavirus, is responsible for acute febrile illness and severe polyarthralgia. Although both innate and adaptive immune responses influence the disease outcomes, the detailed cellular immunopathogenesis of CHIKV in peripheral blood is not yet fully elucidated. MethodsWe conducted single-cell RNA sequencing (scRNA-seq) on peripheral blood mononuclear cells (PBMCs) obtained from patients acutely infected with CHIKV and from healthy control subjects. Cellular interactions were inferred, and the transcriptomic results were orthogonally validated through quantitative real-time PCR (qPCR) and Enzyme-Linked Immunosorbent Assay (ELISA) to assess systemic interferon-stimulated responses. Furthermore, a comparative analysis was performed using publicly available single-cell data from Dengue virus (DENV) infections. ResultsCHIKV infection significantly altered the immune system, increasing monocytes and dendritic cells while reducing T and B lymphocytes. Monocytes and NK cells showed strong activation of interferon-stimulated genes (ISGs). Monocytes were identified as key in driving inflammatory and immune responses. In adaptive immunity, CHIKV led B cells to become plasmablasts with antiviral immunoglobulins and caused T cells and NK-like T cells to show signs of cytotoxicity and exhaustion. Validation showed increased levels of IFN-{gamma}, IFN-{beta}1, MX1, and ISG15. CHIKV triggered a more intense, monocyte-driven interferon response than DENV. ConclusionsAcute CHIKV infection induces a systemic interferon response predominantly centered on monocytes, accompanied by significant alterations in adaptive immunity. Circulating ISG products, including MX1 and ISG15, reflect the transcriptomic activation and may serve as potential biomarkers for assessing the early intensity of innate antiviral responses.

immunology↗

bioRxiv2026

The TIRR–53BP1 axis controls PLK1 spatiotemporal regulation during mitosis

p53-binding protein 1 (53BP1) is a key mediator of the DNA damage response and genome stability. While its interphase function is well-characterized, its mitotic role remains less understood. Here we show that aberrant activation of 53BP1 through the loss of its negative regulator, TIRR, leads to mitotic abnormalities including altered spindle geometry, kinetochore-microtubule (k-MT) attachment errors and whole chromosome missegregation. We demonstrate that loss of TIRR results in excess interaction between 53BP1 and the key mitotic kinase Polo-like kinase 1 (PLK1), altering PLK1s activation, spatial distribution, and its interaction with known PLK1 substrates at multiple mitotic stages. Moreover, due to PLK1s established role in CENP-A loading, hyperactivation of 53BP1 compromises CENP-A loading, triggers gradual loss of CENP-A from centromeres and generates severe kinetochore assembly defects. These findings uncover a non-canonical mitotic function of 53BP1 as a key regulator of PLK1 activity and chromosome segregation fidelity.

Cell Biology↗

bioRxiv2026

False discovery rate control for trustworthy AI-based de novo peptide sequencing

AI-based de novo peptide sequencing predicts peptide sequences from tandem mass spectra, enabling identification beyond predefined databases but leaving prediction reliability difficult to assess, particularly with respect to false discovery rate (FDR). In database search, FDR control is provided by target-decoy competition over a finite search space, whereas de novo predictions are generated in open sequence space and lack naturally matched sequence-level decoys. Here we introduce Counterpart Calibration Theory (CCT), a theory-guided framework that reframes de novo FDR control as a four-group score-ranking and threshold-selection problem over target-side predictions and matched counterpart-side comparators. Implemented in {pi}-NovoQC, CCT provides dual-level FDR control at the peptide-spectrum match and peptide levels. Across models, datasets, instruments and acquisition modes, {pi}-NovoQC achieves stable FDR control while preserving identification yield. In large-scale proteomic applications, {pi}-NovoQC recovers low-abundance in-database peptides missed by database search and provides de novo-supported protein-group and variant evidence.

bioinformatics↗