Biology subjects

Yan, Y.

Publications and source records attributed to Yan, Y..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

DNA replication errors drive genome-wide small inverted triplication dynamics

Structural variants (SVs) have a profound impact on phenotype and diversity and are associated with human diseases. To explore the origination of SVs, we have analyzed 1,340 cancer genomes with annotation of 4,608 novel small inverted triplication (SIT) events and found that FEN1 is strongly associated with SIT incidence. Then, we performed long-read sequencing and developed PacBioR to annotate SITs in yeast FEN1 mutant cells. We found that SIT structures mimic classic inverted triplications but with a smaller DUP/IN/DUP structure of 184/160/184 bp on average, with a spacer sequence of 30 bp and breakpoint junction of 6 bp. We further showed that breakpoints of SITs preferentially occurred at nucleosome midpoints, aligned with Okazaki fragment termini, and those harbored in plasmids were precisely eliminated via DNA polymerase slippage over SIT-derived hairpin structures. This study provides mechanistic insight into SIT origination and offers practical tools for future studies on genome rearrangements.

genetics↗

bioRxiv2025

SPOmiAlign: A modality-agnostic framework for robust and scalable spatial multimodal alignment via feature matching

Multimodal spatial omics enables systematic characterization of tissue organization by jointly profiling molecular features across transcriptomic, proteomic, and metabolomic layers. However, integrative analysis across sections and modalities is frequently hindered by non-linear tissue distortions, mismatched spatial resolutions, and the absence of shared molecular features. To address these challenges, we introduce SPOmiAlign, a modality-agnostic framework based on uncertainty-aware dense feature matching for spatial multimodal alignment. The framework achieves second-level runtime efficiency and enables accurate alignment across heterogeneous spatial omics datasets, as well as between spatial omics and histology, without manual effort or modality-specific tuning. Across diverse datasets, SPOmiAlign consistently achieves higher alignment accuracy than existing state-of-the-art methods. We further demonstrate its utility through automated registration of spatial omics data to a common coordinate framework (CCF), enabling anatomical annotation. Applying SPOmiAlign to spatial multi-omic data demonstrates how accurate multimodal alignment is essential for integrative spatial multi-omic analysis, enabling the identification of coherent spatial domains across modalities and supporting a broad range of downstream spatial analysis.

bioinformatics↗

bioRxiv2025

Native extracellular vesicles display surface bound RNAs that are co-delivered to cells

Extracellular vesicles (EVs) can transport functional RNA between cells and therefore hold great potential for diagnostics and RNA-based therapeutics. Classically, RNA is believed to be encapsulated in the EV lumen. However, it has recently been demonstrated that cells present RNA on their surface. This RNA was found to be glycosylated, and although glycosylated tRNA was also found in EVs, its exact location remained elusive. Here, we demonstrate the presence of RNA on the surface of mesenchymal stem cell (MSC) derived EVs. By combining single-vesicle measurements with direct and selective visualization of RNA, we introduce surface RNA (surfRNA) as a new inherent component of EVs. RNA sequencing supports the surface localization of this RNA and further identifies tRNA fragments as primary constituent of surfRNA. Importantly, surfRNA is co-delivered to target cells together with EVs, suggesting a yet unrecognized uptake route of extracellular RNA. A deeper understanding of the surface-associated RNA may have significant implications for EV biogenesis, targeting, and downstream functional effects. We further envision that these findings are transferable to other nanoparticles and will thereby advance the field of therapeutic RNA delivery.

molecular biology↗

bioRxiv2025

Accurate Variant Classification in Tumour-Only Genomic Data Using Interpretable Tabular Models

Recent work has shown that machine learning can provide a reliable tool to classify somatic and rare germline variants in cancer studies where matched-normal samples are not available. Here, we present a workflow that combines an opensource pipeline with three machine-learning models, XGBoost, LightGBM, and TabNet, trained on eight types of features. Our approach substantially enhances the accuracy across all tested models providing accurate results irrespective of sample ancestry and tumour type. We build a parsimonious model and demonstrate that training on low-coverage data retains high accuracy when applied to high-coverage data and vice versa. In contrast to previous findings, our results indicate that XGBoost slightly outperforms LightGBM, achieving high classification accuracy even in the absence of copy-number information and allowing for the ancestry-unbiased calculation of the tumour mutational burden for different types of cancer.

bioinformatics↗

bioRxiv2025

Bioinformatic analysis of metastasis-associated metabolic landscape reveals an oncogenic role for the transsulfuration pathway

Cancer metastasis is a leading cause of cancer-related deaths, while its underlying mechanisms remain incompletely understood. To colonize distant organs, cancer cells reprogram their metabolism to adapt to diverse environmental challenges. Therefore, elucidating the metabolic pathways that drive cancer metastasis will uncover novel biomarkers and therapeutic targets. In this study, we integrated published datasets and systematically analyzed metabolites across multiple cancer cell lines. This large-scale bioinformatic analysis revealed distinct metabolites and metabolic pathways associated with organ-specific metastasis, and underscored the crucial role of tissue of origin in shaping the metabolic landscape of metastatic tumors. Notably, the transsulfuration pathway (also known as the cysteine and methionine metabolism) was strongly enriched in cancer cells with high metastatic potential. We validated this finding in pancreatic cancer, where the pathway enzyme cystathionine {beta}-synthase (CBS) and its metabolic products were highly expressed in metastatic cancer cells. Targeting the transsulfuration pathway either by methionine deprivation or pharmacological inhibition of CBS significantly impaired the migration and invasion of metastatic pancreatic cancer cells. Taken together, our study not only provides a global view of the altered metabolic landscape in metastasis, but also identifies the transsulfuration pathway as an oncogenic driver and a therapeutic target for pancreatic cancer metastasis.

cancer biology↗

bioRxiv2025

Anionic Lipid Trafficking and Cell Mechanics RegulateMembrane Electrical Potential in Non-Excitable Tissue Cells

1The membrane potential of eukaryotic cells, classically described by the Goldman-Hodgkin-Katz model, is conventionally attributed to the steady-state balance of transmembrane ionic fluxes. Here, we demonstrate that non-excitable cells maintain stable, spatially heterogeneous membrane voltage gradients. Using the ratiometric voltage indicator JEDI-2P-cyOFP1, we quantitatively map membrane potential in live cells and find that cellular protrusions are consistently depolarized, whereas lateral membrane regions are hyperpolarized. These voltage gradients strongly correlate with anisotropic distributions of anionic lipids, including phosphatidylserine (PS) and phosphatidylinositol 3,4,5-trisphosphate (PIP3). Perturbation of cytoskeletal integrity, the ion exchanger NHE1, or vesicular trafficking disrupts both voltage anisotropy and lipid polarization, revealing an uncharacterized electromechanical regulatory mechanism. Moreover, membrane potential dynamically responds to cell shape, substrate stiffness, external electric fields, and cell cycle progression. To account for these phenomena, we develop a quantitative model that integrates ionic fluxes and lipid charge distributions, thereby explaining the emergence of voltage gradients. This framework establishes that membrane potential is governed not solely by ionic currents but also by lipid dynamics and mechanical signaling. Collectively, these findings identify membrane voltage as a global integrator of electrochemical and mechanical cues in eukaryotic cells.

biophysics↗

bioRxiv2025

Hepatocyte FGFR2 Mediates the Antifibrotic Effects of FGF10 in Advanced Liver Fibrosis.

Fibroblast growth factor 10 (FGF10) supports epithelial repair, but its role in liver fibrogenesis remains uncertain. Here we found that hepatic FGF10 and its receptor FGFR2 decline with progression to advanced fibrosis in patient biopsies and in carbon tetrachloride (CCl4)- and diet-induced mouse models. Restoring hepatic FGF10 with recombinant human FGF10 or adeno-associated virus mediated liver-targeted expression attenuated and partially reversed established advanced bridging fibrosis, reduced inflammation, and decreased hepatocyte apoptosis, and these benefits required hepatocyte FGFR2 because hepatocyte-specific Fgfr2 deletion abolished protection. In primary hepatocytes, FGF10 activated FGFR2-FRS2, increased inhibitory GSK3{beta}(Ser9) phosphorylation, and suppressed NF-{kappa}B activation, reducing TGF-{beta}1 and other cytokines and thereby limiting paracrine hepatic stellate cells activation. The molecular and histologic benefits extended to metabolically primed steatohepatitis, supporting translatability beyond toxicant injury. Mechanistic signaling readouts confirm FGFR2 engagement, while the main text centers on the hepatocyte FGF10-FGFR2 axis as an intrinsic brake on fibrogenesis. Together, these data identify a hepatocyte-centric FGF10-FGFR2 axis as a negative regulator and potential regressor of fibrogenesis, highlighting it as a tractable therapeutic target in advanced liver fibrosis.

pharmacology and toxicology↗

bioRxiv2025

Antibody feedback establishes an affinity brake in the germinal center

Recent advances in mRNA vaccine technology have opened the door to novel types of antigen display, but little is yet known as to how B cells recognize and respond to these formats. By delivering an mRNA-LNP encoded membrane-bound immunogen displaying three conserved HIV-1 Envelope (Env) epitopes to knock-in mouse models with B cell receptors (BCRs) of defined affinities, we investigated how epitope-specific competition shapes germinal center (GC) responses. Co-activation of B cells targeting different epitopes did not alter GC kinetics observed in individual activations, but a striking inverse correlation was observed between BCR affinity and GC residence time in either scenario: high-affinity B cells exhibited shorter persistence in GCs, while those with lower affinity to the antigen were maintained. Furthermore, B cells were able to engage in GC reactions at equivalent rates in the presence or absence of clonal lineages binding the same epitope with similar affinities, while higher-affinity clones suppressed lower-affinity counterparts targeting the same epitope. Spatial transcriptomics revealed plasma-like cells within and adjacent to the GC which, together with the detection of early IgG in draining lymph nodes, suggests that local antibody production from these cells may contribute to feedback-driven kinetics. These findings indicate that a self-modulated local antibody feedback loop may act as a "brake" on epitope-specific recognition--dampening further affinity enhancement for high-affinity B cells and facilitating epitope spreading by redirecting the response toward alternative epitopes.

immunology↗

bioRxiv2025

Cross-species connectome comparisons reveal the network attributes of memory capacity and time series prediction

The brains connectome provides a powerful blueprint for designing efficient neural networks, yet the impact of incorporating its intricate, non-random architecture into machine learning models remains underexplored. Here, we integrate empirical structural connectomes from four model species--fruit fly, mouse, rat, and macaque--as the recurrent layer in echo state networks (ESNs). We demonstrate that biologically realized networks, particularly the macaque connectome, achieve superior performance in chaotic time series prediction and exhibit higher memory capacity compared to randomly shuffled controls. This computational advantage correlates with small-world topology, which scales with phylogenetic level. Crucially, we identify that weakly connected but highly central nodes are essential for optimal network dynamics; their targeted perturbation significantly degrades performance. Furthermore, functional connectomes from Alzheimers disease patients show computational deficits resembling those induced by weak-tie disruption in healthy networks. Our findings establish that evolved connectome topology is fundamental to efficient information processing, providing key principles for bio-inspired artificial intelligence.

neuroscience↗

bioRxiv2025

XPF mediates 3' flap processing for FEN1-independent Okazaki fragment maturation

Okazaki fragment maturation (OFM), the process that removes RNA-DNA primers, is a major source of DNA replication stress and mutations. It involves Pol{delta}-mediated DNA strand displacement synthesis that produces 5 flaps, FEN1-mediated 5 flap cleavage, and LIG1-catalyzed nick ligation. Recently, we discovered that under stress conditions, yeast cells convert 5 flaps into 3 flaps, which are degraded by 3 flap nucleases to produce ligatable DNA nicks. However, little is known about this stress-induced, 3 flap-based OFM in human cells. Here, we report that 3 flaps frequently form in various human cancer cells, and that FEN1 deficiency significantly enhances 3 flap levels. XPF1 is recruited to the replication forks in FEN1 mutant or FEN1-chemically inhibited cells. Notably, XPF deficiency or inhibition in those defective cells leads to accumulation of 3 flaps, replication-related DNA strand breaks, and unique mutation signatures. Furthermore, XPF and FEN1 inhibitors show synergistic effects in killing human cancer cells. In summary, we demonstrate that 3 flap-based OFM is an important alternative of 5 flap-based OFM in mammalian cells. XPF is a key nuclease to degrade 3 flaps and complete OFM for survival. Targeting this compensatory mechanism could provide new therapeutic strategies to selectively impair cancer cell survival under pre-existed replication stress. HighlightsO_LIXPF is recruited to DNA replication forks in mouse or human cells of functional deficiency of FEN1 due to genetic mutations or chemical inhibition. C_LIO_LIXPF gene deficiency or chemical inhibition results in accumulation of 3 flaps and replicative DNA single-stranded breaks. C_LIO_LIFunctional deficiency of XPF and FEN1 displays a synergy in inducing genome instability and cell death in human cancer cells. C_LI

cell biology↗

bioRxiv2025

Viral tRNA-like structure hijacks host ribosomes for poly(A)-independent translation

Positive-sense RNA viruses often use 3' tRNA-like structures (TLSs) instead of poly(A) tails to capture the host translation machinery. While TLSs resemble canonical tRNAs and engage host factors, their ability to directly recruit ribosomes has remained unresolved. Here, we present cryo-electron microscopy snapshots of the histidine-accepting TLS (TLSHis) from tobacco mosaic virus bound to the 60S subunit, the 80S ribosome, and the 80S-tRNAiMet initiation complex. Across these states, TLSHis is consistently anchored to the L1 stalk of 60S, even under cycloheximide treatment, yet remains dynamic on the 40S subunit. Structural analysis shows that TLSHis transitions from the E-site to an adjacent Z-site to accommodate initiator tRNA. Functional assays show that TLSHis preferentially associates with ribosomal subunits over polysomes and can substitute for a poly(A) tail to promote robust cap-dependent translation. Together, these findings reveal how a viral tRNA mimic hijacks host ribosomes to promote poly(A)-independent translation.

molecular biology↗

bioRxiv2025

Fluid-Squid: DIY Multiplexed Imaging of Cells and Tissues

Recent advances in multiplexed single-cell characterization have revolutionized our insight into cell biology, but many available technologies remain limited by high costs or a lack of customizability. To address these challenges, we developed Fluid-Squid, a cost-effective, quantitative imaging platform that integrates automated fluidics to support customizable, do-it-yourself multiplexed imaging workflows. Using Fluid-Squid, we successfully imaged fresh frozen human intestinal tissues with a 36-plex oligonucleotide-barcoded antibody panel and further demonstrated the feasibility of lyophilizing such multiplexed panels. We also adapted existing multiplexed imaging workflows to characterize individual cells to identify immune cell populations, phenotype, and antigen-specific cells from mouse splenocytes and human peripheral blood mononuclear cells (PBMCs) with a 39-antibody panel. To further expand its utility, we developed a barcoding strategy that allows for the pooling and simultaneous staining of multiple samples, reducing time, costs, and batch effects in single-cell experiments. This approach facilitated rapid titration to optimize antibody concentrations and assess the impact of various blood preparation methods on cell type retention. Overall, our work provides a new open-source framework for automated fluidics and microscopy in a flexible, cost-effective platform, empowering adaptable multiplexed characterization of both single cells and tissues.

bioengineering↗

bioRxiv2025

Functional interrogation uncovers a critical role for a high-plasticity cell state in lung adenocarcinoma

Plasticity--the ability of cells to undergo phenotypic transitions--drives cancer progression and therapy resistance1-3. To date, strategies targeting cancer plasticity have not advanced to the clinic due to a lack of fundamental understanding of the underlying mechanisms. Recent studies have suggested that plasticity in solid tumors is concentrated in a minority subset of cancer cells4-6, yet functional studies interrogating this high plasticity cell state (HPCS) in situ are lacking. Here, we developed mouse models enabling detection, longitudinal lineage tracing, and ablation of the HPCS in autochthonous lung tumors in vivo. Using lineage tracing, we uncover the HPCS cells are dedifferentiated but possess high capacity for cell state transitions, giving rise to both early neoplastic (differentiated) and advanced lung cancer cell states in situ. Longitudinal lineage tracing using secreted luciferases reveals HPCS-derived cells harbor high capacity for growth when compared to bulk cancer cells or another defined cancer cell state with features of differentiated lung epithelium. Suicide gene-mediated ablation of the HPCS in early neoplasias abrogates tumor progression. Ablating HPCS cells in established tumors by suicide gene or HPCS-directed CAR T cells robustly reduces tumor burden, whereas ablation of a differentiated lung cancer cell state had no effect. We further demonstrate that the HPCS gives rise to therapy-resistant cell states, whereas ablation of the HPCS abrogates resistance to chemotherapy and oncoprotein-targeted therapy. Interestingly, an HPCS-like state is ubiquitous in regenerating epithelia and in carcinomas of multiple other tissues, revealing a convergence of plasticity programs. Our work establishes the HPCS as a critical hub enabling reciprocal transitions between cancer cell states, including acquisition of states adapted to cancer therapies. Targeting the HPCS in lung cancer and in other carcinomas may suppress cancer progression and eradicate treatment resistance.

cancer biology↗

bioRxiv2025

JMJD1B-mediated FEN1 demethylation allows timely switching of Okazaki fragment maturation core enzymes to avoid mutagenic flap ligation by PARP1-LIG3

Efficient and faithful Okazaki fragment maturation (OFM) depends on the PCNA-coordinated actions of core enzymes Pol{delta}, FEN1, and LIG1. We demonstrate that Pol{delta}, FEN1, and LIG1 sequentially but not simultaneously bind to PCNA in mammalian cells. The association of FEN1 with PCNA, which lies at the center of this orderly program, is mediated by FEN1 R192 methylation, which is also crucial for preventing premature loading of LIG1. Conversely, FEN1 demethylation by the recently identified arginine demethylase JMJD1B promotes FEN1 dissociation from PCNA and LIG1 recruitment. Disruption of the sequential PCNA binding program in R192Q or Jmjd1b-/- cells results in unprocessed 5 flaps that prevent OFM and induction of PARP1-dependent recruitment of LIG3, which has flap ligation activity to join incompletely processed OFs. This alternative OFM process supports cell survival but causes duplications and other DNA mutations. Our findings define fundamental and alternative DNA replication processes underlying mutagenesis and cell survival. HighlightsO_LIThe core enzymes involved in Okazaki fragment maturation (OFM), DNA polymerase {delta} (Pol{delta}), flap endonuclease 1 (FEN1), and ligase 1 (LIG1), sequentially bind to the scaffold protein PCNA for their concerted actions C_LIO_LIFEN1 R192 methylation enables FEN1 binding to PCNA; JMJD1B-mediated FEN1 arginine demethylation provokes FEN1 exit from PCNA and LIG1 recruitment C_LIO_LIFEN1 R192Q mutation and JMJD1B deficiency oppositely alter dynamic PCNA interactions with FEN1 and LIG1 and result in distinct OFM DNA intermediate structures C_LIO_LIActivation of PARP1 at replication forks due to disruption of the sequential PCNA binding program induces LIG3-mediated alternative mutagenic 5 flap ligation for survival. C_LI

cell biology↗

bioRxiv2025

In vitro evaluation of protein-protein interactions in the rice KAI2 ligand signaling complex

KARRIKIN INSENSITIVE 2 (KAI2)/DWARF14-LIKE (D14L) plays key roles in land plant development, environmental responses, and the establishment of arbuscular mycorrhizal symbiosis, likely acting as the receptor for unidentified signaling molecules termed KAI2 ligands (KLs). KL perception by KAI2/D14L promotes DWARF3 (D3)/MORE AXILLARY GROWTH2 (MAX2) F-box protein-mediated ubiquitination of SUPPRESSOR OF MAX2 1 (SMAX1) proteins, thereby transducing the KL signals. Although genetic and in vivo assays have demonstrated the functions of these components, the biochemical details of their interactions remain elusive. Here we investigated physical interactions between rice D14L, D3, and OsSMAX1 in vitro using desmethyl germinone (dMGer), a recently developed KL analog. dMGer elicited KL responses in rice with higher activity and pathway specificity than a widely used KL analog (-)-GR24. dMGer, but not (-)-GR24, directly bound to D14L and promoted the interaction between D14L and D3 in vitro. The interaction between D14L and OsSMAX1 was also enhanced by dMGer. Furthermore, we identified the domain of OsSMAX1 that distinguishes it from its paralog DWARF53 (D53), which is associated with the strigolactone signaling complex. These findings propose a model of the interactions among KL signaling components and highlight the role of the ligand in the signaling complex.

plant biology↗

bioRxiv2025

NPAS2 attenuates VSMC phenotypic switching in ascending thoracic aortic aneurysm via LPCAT3/PC-PUFA2S-mediated ferroptosis

Ascending thoracic aortic aneurysm (ATAA) is a life-threatening disorder with limited therapeutic options, critically linked to vascular smooth muscle cell (VSMC) phenotypic switching. Neuronal PAS Domain Protein 2 (NPAS2), a circadian rhythm-related transcription factor, regulates diverse physiological processes. However, the biological functions and underlying regulatory mechanisms of NPAS2 in VSMCs during ATAA pathogenesis remain to be elucidated. NPAS2 expression decreased in ATAA patients, PDGF-BB-treated HASMCs and BAPN-administrated mice. NPAS2 depletion facilitated VSMC phenotype switching. VSMC-specific NPAS2 knockout (NPAS2SMKO) mice exhibited aggravated ATAA. Mechanistically, NPAS2 depletion attenuates its transcriptional repression of LPCAT3, subsequently elevating the accumulation of phosphatidylcholines with two polyunsaturated fatty acyl chains (PC-PUFA2S), thereby promoting ferroptosis-induced VSMC phenotype switching and accelerating ATAA progression. Targeting NPAS2 represents a potential therapeutic strategy for ATAA treatment.

molecular biology↗

bioRxiv2025

Myasthenia thymus reprograms class switched B cells into BAFF dependent survivors

Myasthenia gravis (MG) presents a clinical challenge where autoantibody titers against the neuromuscular junction fail to predict disease severity or treatment response, and thymectomy provides inconsistent benefit despite removing the source of autoreactive B cells. We hypothesized that thymic B cells acquire survival mechanisms that bypass normal tolerance checkpoints, enabling persistence independent of antigen-specific selection. Using single-cell RNA sequencing, V(D)J repertoire analysis, and spatial transcriptomics from human thymic samples, representing the largest MG atlas to date (237,661 cells), we discovered a previously unrecognized tolerance checkpoint swap in MG pathogenesis. Pathological class-switched B cells within thymic germinal centers exhibited reduced antigen presentation capacity (decreased CD74, CD1C expression) and diminished CD40 co-stimulation while upregulating TNFRSF17 to engage BAFF survival signals. This shift from T cell-dependent activation to BAFF-driven survival allowed polyclonal autoreactive B cells to persist without stringent selection and seed peripheral sites. T follicular helper cells supported this reprogramming through increased TNFSF13B and CHGB expression, the latter enabling dopamine-mediated acceleration of B cell synapses. These findings resolve longstanding clinical paradoxes in MG and identify the BAFF-BCMA axis as an actionable therapeutic target. Measuring serum BAFF and soluble BCMA could provide superior biomarkers to antibody titers, while BAFF inhibition or CD40 agonism could restore normal tolerance checkpoints, offering new therapeutic strategies for MG and potentially other autoimmune diseases. One Sentence SummaryMyasthenia gravis is characterized by a tolerance checkpoint swap where pathological B cells shift from requiring T cell help and antigen-specific selection to depending on BAFF for survival.

genomics↗

bioRxiv2025

PI-FC: Pre-training Individual-specific Functional Connectome through State-invariant Contrastive Learning

Functional MRI enables non-invasive mapping of brain connectivity, yet its clinical translation remains hindered by uncontrolled state-dependent variability that obscures individual-specific signatures during routine scanning. Here we introduce PI-FC -- a deep learning framework leveraging state-invariant contrastive learning to extract stable individual brain signatures across diverse arousal levels, cognitive states, and temporal scales spanning tens of seconds to hours. PI-FC achieves equivalent phenotypic prediction accuracy using substantially reduced scanning time, and eliminates state-dependent effects varying task demands and brain states. Trained on 36,119 subjects across 8 independent datasets, our model demonstrates superior cross-site generalization and outperforms traditional functional connectome (FC) in predicting neuropsychiatric conditions including schizophrenia, autism, depression, and anxiety. Furthermore, PI-FC enables zero-shot inference of brain age, biological sex, and cognitive ability without site-specific retraining. Overall, PI-FC represents a robust, clinically scalable framework that overcomes fundamental barriers to real-world deployment of precision functional neuroimaging.

neuroscience↗