Biology subjects

Mao, L.

Publications and source records attributed to Mao, L..

At least 19 recordsLinked to original sources

bioRxiv2026

WNT/β-catenin increases 3D chromatin mobility and reorganisation during posterior cell state transitions

Chromatin mobility, the exploration of 3D conformations by the chromatin fibre, is implicated in transcription and DNA repair, and is thought to decrease progressively as cells differentiate. Here, combining live-cell 3D single-nucleosome tracking with genomic approaches, we show that chromatin mobility instead changes in a cell-type-specific manner, increasing as pluripotent cells acquire posterior fates. This is accompanied by 3D genome reorganisation, including loss of Polycomb-associated interactions and emergence of CDX2-associated interactions. Withdrawal of posteriorising WNT/{beta}-catenin signalling rapidly reduces chromatin mobility and partially restores Polycomb-associated chromatin interactions, while Cdx1/2/4-null cells fail to acquire these WNT/{beta}-catenin-dependent changes. Together, our findings establish chromatin mobility as a regulated property of cell state, with WNT/{beta}-catenin signalling and CDX factors acting as mediators that fine-tune the sampling of 3D chromatin interactions during cell state transitions.

cell biology↗

bioRxiv2026

An Open Benchmark for Systems Vaccinology: Insights from the CMI-PB Challenges

Systems vaccinology approaches have identified factors affecting vaccine responses in multiple studies, but the ability of computational models to generalize these findings to unseen data remains unclear. We established a community resource to create and compare models predicting B. pertussis booster vaccination responses and put such modeling approaches to the test. We compiled multi-modal experimental training data from three independent cohorts (n=117 individuals), and asked investigators to predict vaccine responses in a cohort of 54 newly recruited individuals using only their pre-booster vaccination data. We benchmarked a total of 107 computational models. Top-performing models were characterized by workflows that prioritized rigorous data preprocessing, robust imputation of missing data, and the use of multi-omics integration or non-linear machine learning. We identified pre-existing antigen-specific antibody titers and baseline monocyte frequencies as the most consistent predictors of post-vaccination immunity, highlighting the dominant role of individual immune setpoints. We established the resulting datasets and evaluation framework as a community resource to advance predictive immunology and facilitate personalized vaccination strategies.

immunology↗

bioRxiv2026

Functional spatial transcriptomics uncover LMO7 as a fusion-regulated and clinically relevant driver of metastasis in Ewing sarcoma

Metastatic dissemination represents the major determinant of poor clinical outcome across cancer entities. Yet, how driver oncogenes shape transcriptional programs facilitating metastasis is poorly understood. In Ewing sarcoma (EwS) - a highly aggressive pediatric bone and soft-tissue sarcoma driven by chimeric FET::ETS transcription factors - low activity of the fusion oncoproteins is thought to promote metastasis, but the underlying molecular mechanisms remain largely elusive. Here, using spatially resolved functional transcriptomics in EwS patient tumors, we identify a distinct transcriptional state at the invasive tumor front, that in contrast to the tumor core, is characterized by lower FET::ETS activity and induction of the multifunctional shuttle LIM domain only protein 7 (LMO7). Integrating these data with clinical information reveals that high LMO7 expression is associated with poor outcomes. Gene network analysis of patient tumors and integrated proteomic and transcriptomic profiling of EwS cell lines following inducible LMO7 silencing highlight LMO7 as a central regulatory hub orchestrating epithelial-mesenchymal transition (EMT) and cytoskeletal remodeling in EwS. Functional experiments demonstrate that LMO7 silencing decreases clonogenicity and migratory capacity in vitro and suppresses primary tumor growth and metastatic dissemination in vivo. Collectively, these findings identify LMO7 as a clinically relevant effector of FET::ETS fusions in EwS, and illustrate how integrating functional, spatial and clinical data can uncover oncogene-driven effectors of metastasis.

cancer biology↗

bioRxiv2026

FET fusion proteins reshape splicing factor networks to drive oncogenic alternative splicing

Gene fusions involving the FET gene family (FUS, EWSR1, and TAF15) act as drivers of numerous cancer subtypes. The resulting chimeric proteins are widely viewed as aberrant transcriptional regulators that promote malignant transformation through chromatin and enhancer reprogramming. Here, we show that FET fusion oncoproteins also function as regulators of alternative splicing across multiple sarcoma subtypes. Transcriptomic analyses revealed extensive but largely non-overlapping splicing programs driven by the EWSR1::FLI1, EWSR1::WT1, EWSR1::ATF1 and FUS::DDIT3 fusions that nevertheless converged on common oncogenic functions. Fusion-dependent splicing regulation was mechanistically separable from canonical transcriptional activity and was associated with extensive remodeling of cooperative RNA-binding protein (RBP) assemblies on target transcripts. Despite regulating distinct exons, different FET fusions engaged highly similar RBP interaction networks, consistent with a conserved mode of splicing regulation. Transcriptome-wide mapping of RBP occupancy revealed extensive reorganization of local RNA regulatory landscapes following fusion depletion. The requirement of RNA for FET fusion condensate formation, together with the inability of condensation-defective mutants to restore splicing regulation, further supported a role for higher-order assemblies in fusion-dependent alternative splicing (AS) control. Fusion-driven splicing programs stratified Ewing sarcoma patients independently of established clinical covariates, thereby underscoring their clinical relevance. AS of TFDP1 emerged as a common fusion-regulated splicing event required for sarcoma cell fitness and therapeutically actionable using antisense oligonucleotides. Together, our findings establish AS regulation as a conserved function of FET fusion oncoproteins that is mechanistically separable from their canonical transcriptional activity. More broadly, they support a model in which oncogenic fusion proteins can drive malignant phenotypes through large-scale remodeling of RNA regulatory networks.

molecular biology↗

bioRxiv2026

M6A-modified circEZH2 Protects Endothelial Cells from Senescence and Suppresses Atherosclerosis by Stabilizing ZNF326

BACKGROUNDEndothelial cell senescence induces endothelial dysfunction, thereby contributing to atherosclerosis progression. Circular RNAs (circRNAs) play diverse roles in multiple physiological and pathological processes. N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic RNAs and dynamically regulates RNA fate and function. However, the functions and therapeutic potential of m6A-modified circRNAs in endothelial cell senescence remain unknown. METHODSm6A-modified circRNAs associated with endothelial cell senescence were screened by circRNA expression and m6A-circRNA microarray profiling of endothelial cells and mouse aortic intima. circEZH2 expression was validated in endothelial cells, vascular tissues, and human atherosclerotic plaques by RT-qPCR, and RNA fluorescence in situ hybridization. The role of circEZH2 in endothelial senescence and atherosclerosis was assessed in vitro and in vivo. RNA pull-down, mass spectrometry, RNA immunoprecipitation, co-immunoprecipitation, ubiquitination assays, and rescue experiments were used to define the underlying mechanism. RESULTSWe identified A novel m6A-modified circRNA, circEZH2, that was downregulated in the aged aortic intima and advanced plaques. CircEZH2 was stabilized by m6A reader IGF2BP2. Endothelial cell-specific overexpression of circEZH2 delayed senescence and suppressed atherosclerosis progression. At the cellular level, circEZH2 overexpression delayed senescence, decreased p53/p21 levels and increased angiogenic activity of endothelial cells, while circEZH2 knockdown exhibited the opposite effect. Mechanistically, circEZH2 functions as a scaffold to promote USP37-mediated deubiquitination, thereby stabilizing ZNF326. Moreover, endothelial cell-specific knockdown of ZNF326 counteracts the anti-senescent and anti-atherosclerotic effects mediated by circEZH2 overexpression. CONCLUSIONSIn summary, the present study identifies circEZH2 as a novel suppressor of endothelial cell senescence, highlighting its potential as a therapeutic target for age-related atherosclerosis. GRAPHIC ABSTRACTA graphic abstract is available for this article. O_FIG O_LINKSMALLFIG WIDTH=177 HEIGHT=200 SRC="FIGDIR/small/730538v1_ufig1.gif" ALT="Figure 1"> View larger version (78K): org.highwire.dtl.DTLVardef@d3a586org.highwire.dtl.DTLVardef@1180c1forg.highwire.dtl.DTLVardef@1c3d832org.highwire.dtl.DTLVardef@a6d424_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic abstract.C_FLOATNO Schematic model of m6A-modified circEZH2 regulation in endothelial cell senescence and atherosclerosis. In young endothelial cells, IGF2BP2 is highly expressed and recognizes m6A-modified circEZH2, thereby maintaining its RNA stability. CircEZH2 stabilizes ZNF326 protein through USP37-mediated deubiquitination, which leads to suppression of p21 and p53, delays endothelial cell senescence, ameliorates endothelial dysfunction, and ultimately suppresses the progression of atherosclerosis. C_FIG What Are the Clinical Implications?This study identifies circEZH2 as a novel m6A-modified circular RNA that is reduced in the aged aortic intima and in endothelial cells within advanced atherosclerotic plaques. Endothelial circEZH2 overexpression delays endothelial cell senescence, preserves endothelial function, and suppresses atherosclerotic lesion formation, supporting an important role for circEZH2 in vascular aging-associated atherosclerosis. Mechanistically, circEZH2 acts as a scaffold to enhance USP37-mediated deubiquitination and stabilization of ZNF326, while endothelial ZNF326 knockdown counteracts the anti-senescent and anti-atherosclerotic effects of circEZH2. These findings reveal the circEZH2-ZNF326 axis as a previously unrecognized mechanism regulating endothelial senescence and atherosclerosis progression. Our work supports the potential of circEZH2-based gene therapy as a novel therapeutic approach for atherosclerosis.

cell biology↗

bioRxiv2026

SpaceExpander: Automated Drafting and Evaluation of Markush Claims for Chemical Space Expansion

Drafting Markush claims for chemical patents remains difficult because manual claim writing is slow, error prone, and often fails to capture related chemical space in a systematic manner. We developed SpaceExpander, a computational method that converts disclosed compounds into generalized Markush claims by extracting core scaffolds, defining variable positions, decomposing complex substituents, and expanding substituent space through fragment matching. We evaluated the method on 24 publicly available chemical patents and compared its performance with IntelliPatent. SpaceExpander achieved a mean atom level scaffold accuracy of 0.92 and exactly recovered the reference scaffold in 19 of 24 patents. By contrast, IntelliPatent could process only 2 patents from the same set, indicating more limited applicability to structurally diverse cases. We further examined practical claim coverage in a case study based on the Osimertinib patent. Using representative disclosed compounds as input, SpaceExpander drafted a Markush claim that covered 5 of 7 additional approved third-generation EGFR inhibitors beyond Osimertinib. These results show that SpaceExpander is a validated method for automated Markush claim drafting and chemical space expansion.

bioinformatics↗

bioRxiv2026

Toward Computationally Complete Spatial Omics

Multimodal spatial omics has transformed biology by mapping molecular complexity within intact tissues, yet current technologies remain limited in the number of modalities measured simultaneously and often produce lower-quality data than single-modality assays. We present COSIE, a computational framework that generates high-resolution, multilayered molecular landscapes across tissue sections, individuals, and platforms. COSIE integrates histology, epigenome, transcriptome, proteome, and metabolome into a unified representation. Applied to 12 datasets spanning 10 spatial technologies, eight modalities, and nine tissue types, ranging from thousands of spots to millions of cells, COSIE outperforms existing methods. It resolves tissue structures, enhances noisy measurements, predicts unmeasured modalities, and captures dynamic processes. In human tumors, COSIE identifies invasive subregions linked to clinical outcomes and predicts spatial gene expression in TCGA samples using only histology images. By transforming fragmented data into comprehensive spatial maps, COSIE advances computationally complete spatial omics and the creation of digital tissue twins for biomedicine.

genomics↗

bioRxiv2026

DynMoCo: a Novel AI Framework to Reveal Modular Substructures of Protein From Molecular Dynamics

Proteins are dynamic molecular machines whose functions are determined by their structures. While static structures can offer initial insights or hypotheses about protein function, they are often insufficient for a detailed mechanistic understanding. Molecular dynamics (MD) simulations provide atomistic view of proteins dynamic motion and conformational change, but the resulting high-dimensional data are challenging to interpret. Traditional summary statistics and dimensionality-reduction methods often focus on global motions and can overlook regional, yet functionally critical motions. Inspired by approaches from social network science, we introduce a novel perspective for analyzing MD simulations through dynamic community detection, where molecules are modeled as time-evolving graphs, and communities of residues or atoms that move coherently or exhibit functional coupling are identified. We present DynMoCo, a novel deep learning framework that integrates graph convolutional networks with recurrent models for end-to-end dynamic community detection on molecular graphs. Given a MD trajectory, DynMoCo identifies spatially grounded substructures, tracks their evolution over time, and can incorporate structural knowledge to ensure physically meaningful communities. We provide a library of custom-written scripts to allow users to extract and visualize these communites on the MD simulated molecules in motion. We demonstrate the method on force-ramp and force-clamp steered MD simulations of three integrin systems, revealing modular substructures within known domains and characterizing their conformational rearrangements during force-induced unbending. By reducing high-dimensional MD data into interpretable communities, this approach offers new insights into the intrinsic organization and dynamic function of complex biomolecular systems. SIGNIFICANCEProteins often perform their functions through dynamic, locally coordinated motions. Molecular dynamics simulations provide detailed views of these motions but produce high-dimensional data that are challenging to analyze and interpret. We present a novel deep learning model that analyzes molecular dynamics simulations data and identifies structurally coherent and potentially functionally related communities, while tracking their temporal evolution. This analysis tool provides a novel way to analyze MD data transforming it into interpretable representations of modular dynamic, enabling discovery of new mechanistic insights and advancing our understanding of how molecular motions drive biological function.

biophysics↗

bioRxiv2026

Ripk1 Deficiency or K376R Mutation in Dendritic Cells Promotes Potent Antitumor Immunity

Dendritic cells (DCs) are critical for initiating adaptive immunity through antigen presentation and T cell priming. While immunogenic cell death (ICD) enhances anti-tumor immunity, how programmed cell death in DCs shapes tumor immune responses remains unclear. Receptor-interacting protein kinase 1 (RIPK1) regulates apoptosis, necroptosis, and inflammation. Here, we show that mice with disrupted RIPK1 ubiquitination on K376 (Ripk1fl/K376R Cd11c-Cre, Ripk1DC-KO/K376R) develop inflammation and autoimmunity, phenocopying DC-specific RIPK1-deficient(Ripk1fl/fl Cd11c-Cre, Ripk1DC-KO) mice. These phenotypes were rescued by the genetic ablation of Ripk3 or Mlkl, establishing that RIPK1 ubiquitination is essential for suppressing DC necroptosis to maintain immune homeostasis. Remarkably, both Ripk1DC-KO and Ripk1DC-KO/K376R mice exhibit robust resistance to tumor growth, characterized by significantly enhanced T cell infiltration and activation. Mechanistically, we show that Ripk1 deficiency or the loss of its K376 ubiquitination augments antigen-presenting capacity of DCs through both necroptosis-dependent and -independent pathways. Furthermore, adoptive transfer of T cells from Ripk1DC-KO mice further amplifies anti-tumor immunity in recipient hosts. These results identify RIPK1 as a critical immunological checkpoint in DCs that constrains their immunogenic potential. Targeting this pathway represents a promising therapeutic strategy to potentiate T cell-mediated cancer immunotherapy.

immunology↗

bioRxiv2026

HistoSweep enables cellular-resolution tissue quality control for gigapixel images in digital pathology and spatial omics

High-resolution histology images are indispensable for pathology and increasingly serve as the structural backbone for spatial omics. Yet whole-slide images (WSIs) frequently contain artifacts, acellular voids, and background regions that, when included in computational workflows, introduce noise, degrade model accuracy, and compromise biological interpretation. Existing tools provide only coarse foreground-background separation, leaving a gap in fine-grained quality control (QC). Here we present HistoSweep, a scalable framework that generates morphology-aware tissue masks at cellular resolution. By integrating density filtering, texture descriptors, and adaptive thresholding, HistoSweep systematically removes non-informative tissue regions while preserving biologically meaningful microstructures. It processes billion-pixel WSIs in minutes on standard CPUs, requiring no GPU acceleration, and is deployable across research and clinical settings. Across 25 WSIs spanning distinct tissues, disease states, and spatial omics platforms, HistoSweep consistently outperformed existing methods. It enhanced visualization and segmentation, improved virtual cell type predictions, and safeguarded spatial transcriptomics integrity by detecting transcript leakage and transcript-histology misalignment. By enabling fine-grained, scalable QC, HistoSweep provides a foundational preprocessing step for reliable and reproducible digital pathology and spatial omics analyses.

bioinformatics↗

bioRxiv2026

BAF complex-independent gene activation by SS18::SSX

In synovial sarcoma, the BAF subunit SS18 is fused to SSX, a transcriptional repressor, generating the oncogenic SS18::SSX fusion protein. Incorporation of SS18::SSX into BAF complexes leads to their aberrant retargeting to Polycomb-repressed genes via SSX, while simultaneously altering their composition and activity. The presence of BAF at Polycomb target sites is widely assumed to be essential for gene activation. Here, we directly tested the requirement for BAF activity in synovial sarcoma cell survival and SS18::SSX-driven transcription. Using targeted degradation of BAF ATPase subunits and deletion of core components, we show that BAF loss has modest effects on sarcoma cell viability and does not impede SS18::SSX target gene expression. Consistently, deletion of the BAF ATPase subunit Smarca4 does not impair SS18::SSX-driven tumor formation in vivo. Using domain-specific SS18::SSX mutants, we further demonstrate that the fusion can activate oncogenic transcription independently of BAF interaction, and that this activity depends on the C-terminal QPGY-rich domain of SS18. Mechanistically, SS18::SSX promotes transcription by engaging the histone acetyltransferase EP300, independently of BAF. Accordingly, pharmacologic degradation of EP300/CREBBP suppresses SS18::SSX-driven transcriptional programs and impairs synovial sarcoma cell survival. Together, these findings challenge the view that BAF activity is required for SS18::SSX-mediated transcriptional activation and demonstrate that aberrant Polycomb target gene expression is sustained through recruitment of transcriptional coactivators in the absence of BAF. Our work reveals new therapeutic vulnerabilities in synovial sarcoma and suggests broader relevance for targeting coactivator-dependent transcription in fusion-driven cancers. HighlightsO_LIBAF degradation does not alter SS18::SSX-activated transcriptional programs C_LIO_LIDirect SS18::SSX transcriptional activation is independent of BAF interaction C_LIO_LIThe SS18 C-terminus engages the co-activator EP300 to promote gene expression C_LIO_LISmall molecule degraders of EP300/CREBBP abolish SS18::SSX-mediated transcription C_LI

cancer biology↗

bioRxiv2025

Multimodal Data Fusion Reveals Morpho-Genetic Variations in Human Cortical Neurons Associated with Tumor Infiltration

We introduce LetsACT (Light-Electron-Transcriptome synergistic ACTomography), a multimodal integration platform that overcomes the limitations of single-modality data acquisition and analysis of human brain cells while synergistically leveraging the strengths of each modality. Our approach enables the rapid sample preparation, cell injection, imaging, and multimodal integration of large-scale human neuronal datasets at single-cell resolution. By generating initial laser-scanning-microscopy based optical reconstruction of neuron morphologies followed by refining them using electron-microscopy derived morphological priors, we have assembled one of the largest human cortical morphology datasets to date: 8,398 neurons from 58 donors, with high cortical coverage. This platform is then applied to studying morphological impact of tumor infiltration. Pyramidal neurons in glioma-infiltrated tissues display clear volume shrinkage in somas and branches, tapering from the soma to nearby dendritic compartments. By integrating these morphological variations with spatial and bulk transcriptomic profiles, we find that glioblastoma tissues exhibit dysregulation of 15.29% of genes, including overexpression of TERT, whereas infiltrated tissues show 7.74% gene dysregulation, characterized by overexpression of tumor suppressors such as CDKN2A and TP53. Our analysis implies that pyramidal neurons observed in these infiltrated tissues may involve an active defense instead of undergoing passive apoptosis. Our finding also indicates that LetsACT establishes a valuable resource for the large-scale, comprehensive morpho-genetic analysis of human tissues.

neuroscience↗

bioRxiv2025

Tibetan near-complete pangenome reveals complex variants underlying high-altitude adaptation

Genomic diversity in indigenous populations offers critical insights into human evolution and population-specific adaptation. Here, we generated 70 near-complete, fully phased genome assemblies from 35 high-altitude Tibetan trios and identified 4.55 million small variants and 63,031 structural variants (SVs) absent from the current global pangenome reference. Comparative analyses with a 595 globally diverse long-read genome dataset revealed 207 previously uncharacterized Tibetan-enriched SVs spanning 275 genes implicated in high-altitude physiological adaptation. Genotyping these SVs in 1,164 Tibetan and Han individuals with 88 physiological traits reveals five variants significantly associated with cardiopulmonary and hematological phenotypes central to hypoxia adaptation. We further map 2.45 Gb of archaic hominin sequences in Tibetans and uncover 18 previously unrecognized introgressed regions enriched in Tibetans with genes related to hematopoiesis and lung function. These regions harbor five Tibetan-enriched SVs, indicating that archaic introgression contributed SVs relevant to human adaptation. Together, these findings reveal substantial uncharacterized genomic diversity in Tibetans and highlight a previously underappreciated role of SVs and archaic SVs in shaping human evolution and high-altitude adaptation.

genomics↗

bioRxiv2025

Going Against the Grain: Investigating the C4 Wheat Hypothesis with Spatial Transcriptomics

The possibility of a C4 photosynthetic pathway present in the developing grain of wheat, a C3 plant, has been the source of scientific debate. Wheat is critical to food security and may benefit greatly from the biological advantages conferred by C4 photosynthesis under heat and drought stress. Therefore, significant research has gone towards engineering wheat to use C4 biochemistry, resulting in the discovery of a unique photosynthetic pathway in the grain that has been suggested to be C4 specific. Here, we employed a spatial transcriptomics analysis of the developing wheat grain to further investigate the spatial expression patterns of C4 specific genes. Our results showed that most of the genes related to C4 photosynthesis were expressed in the grain in the theorised tissue locations, including phosphoenolpyruvate carboxylase (ppc) and pyruvate orthophosphate dikinase (ppdk). The photosynthetic pericarp cells were the site of ppc synthesis while the endosperm was the site of ppc carboxylation activity. Notably, isoforms of aspartate aminotransferase, alanine aminotransferase and malate dehydrogenase exhibited spatially distinct expression patterns, with tissue specificity, possibly linked to the unique functions of individual isoforms. As wheat performance under stress has been associated with the levels of expression of these C4 genes, confirmation of an active C4 pathway in the grain would have significant agronomic implications. Our results provide novel gene expression data for key genes related to photosynthesis, which could contribute to future development of highly productive, climate change resilient wheat varieties.

genetics↗

bioRxiv2025

ProTDyn: a foundation Protein language model for Thermodynamics and Dynamics generation

AO_SCPLOWBSTRACTC_SCPLOWMolecular dynamics (MD) simulation has long been the principal computational tool for exploring protein conformational landscapes and dynamics, but its application is limited by high computational cost. We present ProTDyn, a foundation protein language model that unifies conformational ensemble generation and multi-timescale dynamics modeling within a single framework. Unlike prior approaches that treat these tasks separately, ProTDyn allows flexible independent and identically distributed (i.i.d.) ensemble sampling and dynamic trajectory simulation. Across diverse protein systems, ProTDyn yields thermodynamically consistent ensembles, faithfully reproduces dynamical properties over multiple timescales, and generalizes to proteins beyond its training data. It offers a scalable and efficient alternative to conventional MD simulations. Code is available at: https://github.com/Harrydirk41/ProTDyn.

biochemistry↗

bioRxiv2025

The Pulmonary Microbial Signatures of Early Stages of Severe Infection in Children

The respiratory tract related diseases are the main causes of death in children. Child pulmonary severe infection is the most important inducement for Respiratory tract related diseases. Therefore, it is necessary to understand the composition of the microbial community and the species correlation in children with severe pulmonary infection. In this study, the bronchoalveolar lavage fluid (BALF), blood and cerebrospinal fluid (CSF) samples of 782 children with severe infection in the early stage were systematically analyzed by amplicon-sequencing technology to reveal the distribution of microbial community and its clinical correlation. Results reveal significantly higher bacterial abundance in BALF than in blood/cerebrospinal fluid, with community structures shaped by tissue microenvironments, geographical disparities, age, and clinical symptoms. Neonatal BALF harbors simplified microbiota dominated by probiotics, while diversity increases with age, showing marked differences between 1-3 and 6-12-year-olds. Sepsis samples exhibit reduced microbial diversity, with Staphylococcus and Moraxella enrichments in the CST-4 cluster. Respiratory symptom progression correlates with microbiota succession from oral colonizers to respiratory pathogens. Third-generation sequencing-derived co-occurrence networks illustrate synergistic interactions among opportunistic pathogens, providing a basis for ecological targeted therapy. This study provides a key basis for breaking through the limitations of traditional diagnosis, establishing a precise diagnosis and treatment system based on third-generation sequencing, and developing ecological targeted treatment strategies.

pathology↗

bioRxiv2025

RNALens: Study on 5' UTR Modeling and Cell-Specificity

Recently, the Transformer architecture has been applied to predict the structure, function, and regulatory activity of biological sequences. Predicting the cell-specific regulatory impact of 5 untranslated regions (5 UTRs) on mRNA expression and translation remains a key challenge for rational mRNA design. Existing studies such as UTR-LM, RNABERT, and RNA-FM train transformer-based models solely on 5 UTR sequences with fixed nucleotide tokenization schemes and auxiliary structural features. These models pay less attention to the integration of broader genomic context and thermodynamic objectives, which limits their ability to generalize across diverse cell types and accurately predict both mRNA expression level (EL) and translation efficiency (TE). In this paper, we propose RNALens, a foundation model pre-trained in two stages on multispecies genomic sequences and curated 5 UTR data using masked language modeling augmented with secondary structure prediction and minimum free energy regression. RNALens employs byte-pair encoding to capture variable-length nucleotide motifs. It is then fine-tuned on high-throughput reporter assay datasets from HEK293T, PC3, and muscle tissues to yield specialized predictors for EL and TE in each cellular context. Experiment results on benchmark datasets demonstrate that RNALens achieves superior performance than existing machine learning methods for both expression and translation predictions across cell-specific and cross-context tests, offering an efficient in silico platform for guiding the design of mRNA therapeutics with precise cellular targeting.1

bioinformatics↗

bioRxiv2025

cIAP1 inhibitor of apoptosis is a tumor suppressor in Ewing sarcoma

Ewing sarcoma (EwS) is a highly aggressive pediatric malignancy driven by EWSR1::ETS fusion oncoproteins -primarily EWSR1::FLI1- which deregulate genes essential for differentiation, proliferation, and cell survival. To uncover key downstream targets of this fusion involved in cell differentiation, we combined transcriptomic profiling of EwS cell lines following EWSR1::FLI1 inhibition with gene ontology analysis, a clinically annotated gene expression dataset derived from EwS patient material and network analyses. This integrative approach identified inhibitor of apoptosis protein 1 (cIAP1, alias BIRC2) as an EWSR1::FLI1-suppresed gene. Despite its known oncogenic role in many cancers, cIAP1 showed minimal expression in EwS. Using inducible cIAP1 re-expression models in EwS cells, we demonstrated that cIAP1 re-expression suppresses proliferation, clonogenic growth, and 3D spheroid formation in vitro. Transcriptomic and proteomic analyses revealed that low cIAP1 expression enhances proliferation-related gene signatures, which are inhibited upon cIAP1 re-expression. In vivo xenograft models revealed that cIAP1 re-expression significantly reduces tumor growth, mitotic activity, and Ki-67 positivity, while increasing tumor necrosis and apoptosis. These findings highlight an unexpected tumor-suppressive role for cIAP1 in fusion-driven sarcomas, contrasting with its pro-survival function in other cancers. Collectively, our results identify cIAP1 as a prognostically relevant, EWSR1::FLI1-regulated hub whose re-expression disrupts tumor progression, offering a potential therapeutic strategy to restore tumor-suppressive pathways in EwS.

cancer biology↗