Biology subjects

Lu, S.

Publications and source records attributed to Lu, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

HSC71 acetylation confers protection against Spiroplasma eriocheiris infection by inhibiting apoptosis and promoting ROS production in arthropods

Heat shock proteins (HSP) are increasingly recognized as pivotal regulators of host innate immunity. However, the role of HSP70 post-translational modifications in modulating the immunologic functions during pathogenic infection remains poorly understood. Here, we demonstrated that heat shock cognate 71 kDa protein (HSC71), a member of the HSP70 family, was deacetylated following infection with intracellular pathogen Spiroplasma eriocheiris. HSC71 deficiency exacerbated hemocyte apoptosis and increased host susceptibility to S. eriocheiris infection. Conversely, ectopic expression of hyperacetylation-mimetic HSC71(K579Q) in Drosophila S2 cells conferred robust protection against S. eriocheiris by suppressing apoptosis and augmenting reactive oxygen species (ROS) production. Mechanistically, carnitine O-acetyltransferase (Crat) was identified as the specific acetyltransferase for HSC71. Crat acetylated HSC71 at lysine 579 (K579), which in turn impeded its interaction with the E3 ubiquitin ligase CHIP, thereby stabilizing HSC71 by attenuating ubiquitin-mediated degradation. Crat deficiency induced apoptosis and reduced ROS levels in hemocytes, thereby exacerbating S. eriocheiris intracellular proliferation. Furthermore, acetylation of HSC71 at K579 weakened its binding to superoxide dismutase (SOD), resulting in impaired SOD activity and consequent accumulation of microbicidal ROS. Pharmacological inhibition of the deacetylase SIRT1 with EX-527 enhanced HSC71 acetylation and ROS production, conferring resistance to S. eriocheiris infection in crabs. Notably, EX-527 similarly enhanced the acetylation of Drosophila HSC71 homolog, HSPA8, which in turn impaired its interaction with SOD. This led to elevated ROS levels and restricted intracellular proliferation of S. eriocheiris in S2 cells, demonstrating evolutionary conservation of this mechanism among arthropods. Therefore, this study established the modulation of HSC71 acetylation as a promising strategy to enhance arthropod immunity. Author summaryMembers of the HSP70 family are indispensable components of host innate immunity, and their functions are finely tuned by post-translational modifications. This study investigated the mechanisms that underlie acetylation modification of HSC71 mediated resistance to S. eriocheiris infection in crab. Our results revealed that the acetyltransferase Crat and the antioxidant enzyme SOD directly interacted with HSC71. Mechanistically, Crat acetylated HSC71 at K579, which prevented its ubiquitination by promoting the disassociation of E3 ubiquitin ligase CHIP, thereby improving HSC71 stability. In HSC71-deficient or Crat-deficient crabs, hemocyte apoptosis was markedly enhanced, leading to higher host mortality upon S. eriocheiris challenge. Meanwhile, K579 acetylation on HSC71 weakened the interaction between HSC71 and SOD, resulting in the accumulation of intracellular ROS and thereby restricting S. eriocheiris propagation. Administration of the SIRT1 inhibitor EX-527 enhanced HSC71 acetylation, elevated ROS production and reduced host susceptibility to S. eriocheiris infection. These findings revealed a novel role for Crat-mediated acetylation of HSC71 in orchestrating host defense through two synergistic mechanisms: suppressing apoptosis and promoting ROS accumulation. Thus, targeting HSC71 acetylation may represent a promising avenue to combat S. eriocheiris infection.

immunology↗

bioRxiv2026

A biofidelic Goat Model of Traumatic Optic Neuropathy with Optic Canal Fracture via Transnasal Endoscopy

Traumatic optic neuropathy (TON) is a major cause of irreversible vision loss following blunt cranial trauma, yet the absence of clinically relevant large animal models that faithfully recapitulate human TON has significantly impeded translational research. Current rodent models do not reproduce optic canal fracture, a key injury mechanism in many patients with TON. Here, we combined high-fidelity finite element analysis (FEA) with iterative engineering to establish a reproducible goat model of TON. We first built a high-resolution human-head finite element model to characterize force transmission to the optic nerve. Across clinically relevant periorbital impacts, stress preferentially concentrated in the intracanalicular segment, reaching a peak force density of approximately 500 N/m2 at 50.6 ms, about fivefold higher than in the intraorbital segment. Simulations further showed that direct optic canal impact reproduced comparable intracanalicular stress with a markedly lower input force: 195 N, compared with 3900 N for periorbital impact. Guided by these insights, we developed transnasal endoscopic impact systems capable of inducing optic canal fractures in goats. TON was confirmed within 24 hours by a characteristic relative afferent pupillary defect (RAPD), and at 1 month post-injury goats (n = 14) exhibited a 10%-20% reduction in ganglion cell complex (GCC) thickness and 40%-65% reductions in flash visual evoked potential (FVEP) and pattern electroretinogram (PERG) amplitude ratios (all P [≤] 0.001), with structural and functional preservation of the fellow eye. This study presents a robust, standardized, and clinically relevant large-animal platform for investigating TON pathophysiology.

neuroscience↗

bioRxiv2026

Reproducible Tools and Enhanced Computational Workflows for Batch Effect Evaluation of High-Throughput Data Using BatchQC

Batch effect correction is a common and often necessary step in data analysis to reduce bias due to technical and experimental factors when combining multiple batches of data. The severity of the batch effects dictates the correction strategy; therefore, a careful assessment of each datasets batch effects is necessary. BatchQC is an R package that provides reproducible tools and visualizations for quantitatively and qualitatively addressing batch effects across a broad range of data types. BatchQC integrates with standardized Bioconductor data structures and features an object-oriented design, enabling the application of workflows that can freely evaluate and process data within and outside the package tools. Common batch evaluation methods, along with novel quantitative metrics, help determine the benefits of batch correction for each dataset and enable direct comparisons between methods. Here, we present BatchQC as the first comprehensive batch-correction R package, with independent tools, reproducible workflows, visualization, and novel statistics.

bioinformatics↗

bioRxiv2026

Spatial multi-omics unveils the monoclonal origin, neuroendocrine plasticity, and microenvironment niches in combined small cell lung cancer

Combined small-cell lung cancer (cSCLC) is a rare and aggressive subtype of small-cell lung cancer (SCLC) characterized by mixed histology comprising SCLC and non-small cell lung cancer (NSCLC) or large cell neuroendocrine carcinoma (LCNEC) components. Despite its histological heterogeneity and even poorer prognosis than de novo SCLC, cSCLC is clinically managed as pure SCLC, largely due to the lack of molecular insights into its biology, lineage plasticity, and tumor microenvironment (TME). Here, we perform multi-omics profiling, including spatially-resolved whole-exome sequencing (WES), spatial transcriptomics (ST) and single-nucleus RNA sequencing (snRNA-seq), across 19 treatment-naive cSCLC tumors spanning all major histological subtypes. Our analysis reveals that SCLC and NSCLC/LCNEC components share a monoclonal origin, with histological divergence characterized by distinct mutation and copy number alteration patterns. ST and snRNA-seq uncover spatially exclusive or interspersed tumor domains, with distinct TME compositions and immune landscapes. Notably, fibroblast-rich regions enriched for an aggressive fibroblast subtype form boundaries between tumor domains, potentially influencing immune TME and treatment responses. We identify extensive lineage plasticity within cSCLC, including active LUAD-to-SCLC transdifferentiation and SCLC subtype coexistence, suggesting transitional cellular states not captured by traditional diagnostics. Leveraging these insights, we developed the cSCLC Detector, a sensitive mutation-based diagnostic assay that improves the detection of cSCLC in tissue and liquid biopsy samples. Our findings offer critical insights into cSCLC lineage plasticity, cellular evolution, and microenvironmental interactions, underscoring the need for tailored treatment strategies and diagnostic frameworks for this aggressive cancer subtype.

cancer biology↗

bioRxiv2025

Single-molecule FRET with a minimalistic 3D-printed setup and dyes in the blue-green spectral region

Forster Resonance Energy Transfer (FRET) is a powerful technique for the detection and characterization of biomolecular interactions and conformational changes with sub-nanometer spatial resolution and a temporal resolution down to the timescale of fluorescence. While the technique is widely adopted in structural biology and biophysics, the evolution of single-molecule FRET has led to experimental setups with sophisticated optical layouts, multi-laser excitation schemes and time-resolved detection electronics. We here present an accessible alternative towards single-molecule FRET based on Brick-MIC, a recently introduced 3D-printed micro-spectroscopy platform. The FRET-Brick uses continuous-wave excitation at 488 nm with a minimal set of opto-mechanical components and photomultiplier detectors (PMTs). With this we were able to significantly reduce the setup complexity retaining single-molecule sensitivity with dyes matching the sensitivity of PMTs. To maximize the photon output of Alexa488, ATTO488 (donors), Alexa555, ATTO542 and Cy3B (acceptors), we introduce ferrocene-derivatives as photostabilizers that increase both dye brightness and remove dark-states. We benchmark the performance of the FRET-Brick with fluorophore-labelled oligonucleotide reference structures also in comparison to accessible volume simulations, and by detecting conformational changes in bacterial substrate binding proteins. Our work demonstrates that qualitative and quantitative smFRET measurements are possible with the minimalistic and cost-effective FRET-Brick.

biophysics↗

bioRxiv2025

Vagal volume receptors in the heart compensate for blood loss and posture change

Cranial nerves densely innervate the heart and vasculature, with sensory neurons reporting on blood pressure, respiratory gases, and tissue damage1. The roles of arterial baroreceptors in systemic physiology are well appreciated2, but the functions of vagal cardiac mechanoreceptors have been more difficult to parse, in part due to the closed-loop structure of the cardiovascular system. Here, we use genetic tools for isolated study of vagal mechanoreceptors in the heart, finding that they are acutely sensitive to circulating blood volume and play key roles in compensating for decreased filling of the heart that occurs in an upright posture and during hemorrhage. Vagal PIEZO2 neurons form characteristic end-net endings in the heart and display blood volume-dependent responses with every heartbeat that are timelocked to atrial and ventricular systole. Vagal PIEZO2 knockout eliminates heartbeatcoupled nerve activity, and compromises carotid blood pressure when mice on a tilttable are rotated to an upright position. Vagal PIEZO2 knockout mice also display a lethal failure to sustain blood pressure during trauma-induced blood loss. Together, these findings demonstrate an essential function for vagal cardiac mechanoreceptors in sustaining the constancy of blood circulation.

neuroscience↗

bioRxiv2025

DTCFinder: a bench-to-bits toolkit for label-free, whole-spectrum analysis of disseminated and circulating tumor cells in liquid biopsies

Disseminated (DTCs) and circulating tumor cells (CTCs) are rare but pivotal in understanding cancer metastasis and advancing liquid biopsy-based diagnostics. Traditional detection approaches, hindered by their dependency on epithelial markers or morphological features, impair the accurate identification of varied DTC/CTC phenotypes within liquid biopsies. We describe DTCFinder, a bench-to-bits, label-free method integrating high-throughput single-cell RNA sequencing and machine learning, enabling unbiased detection, in-depth molecular characterization, and precise tissue-of-origin tracing of DTCs/CTCs across various types of liquid biopsies, even with ultra-scarce DTC/CTC presence in peripheral blood and low sequencing depth. DTCFinder offers a robust and versatile toolkit for liquid biopsy-based cancer diagnostics, enhancing our understanding of cancer metastasis.

cancer biology↗

bioRxiv2025

Genome-wide CRISPR screen reveals PEX11B as a host restriction factor against ORFV through membrane fluidity regulation

Host-pathogen interactions are shaped by cellular restriction factors that direct antiviral defenses. We built the first ovine genome-wide CRISPR knockout library in sheep testis (OA3.Ts) cells, targeting all protein-coding genes. Using this platform, we identified PEX11B, a peroxisomal membrane regulatory protein, as a strong restriction factor against orf virus (ORFV) infection. Removing PEX11B increased viral susceptibility and triggered severe cytopathic effects with membrane fusion and syncytia formation. Mechanistic studies showed that PEX11B knockout harmed peroxisomal integrity and disrupted lipid metabolism. This led to greater plasma membrane fluidity, creating a proviral environment that allowed more viral entry and replication. These results reveal a new antiviral function for PEX11B in blocking viral infection and underscore the importance of peroxisomal regulation in host-virus interactions.

microbiology↗

bioRxiv2025

Computer Vision Methods for Spatial Transcriptomics: A Survey

Spatial transcriptomics (ST) enables the simultaneous measurement of gene expression and spatial localization within tissue sections, providing unprecedented opportunities to dissect tissue architecture and functional organization. As a relatively new omics technology, bioinformatics has driven much of the innovation in ST. However, within these frameworks, "spatial" information is often reduced to locations and relationships between molecular profiles, without fully leveraging the wealth of submicron morphological detail and histological knowledge available. Advances in computer vision-based artificial intelligence (AI) are opening exciting new avenues beyond conventional bioinformatics approaches by modeling complex histological patterns and linking morphology to molecular states. More excitingly, they bring fresh perspectives to potentially address key limitations of ST, including its high cost, limited clinical applicability, and reliance on twodimensional (2D) analysis of inherently three-dimensional (3D) tissues. For instance, models that predict ST directly from histology images enable "virtual sequencing," drastically reducing costs while integrating morphological insights from pathology with molecular biomarkers, thus accelerating clinical translation. Moreover, computer vision techniques can reconstruct pixel-aligned 3D tissue models, overcoming the technical barriers of 2D acquisition and advancing 3D spatial omics analytics. In this paper, we present the first systematic survey of computer vision AI models for ST analytics, categorizing approaches across architectures, learning paradigms, tasks, and datasets, and tracing their technological evolution. We highlight key challenges and future directions, offering a panoramic perspective on vision-driven ST and its potential to transform both basic research and clinical practice. The curated collection of vision-driven spatial transcriptomics papers is available at https://github.com/hrlblab/computer_vision_spatial_omics.

bioinformatics↗

bioRxiv2025

Enhancing Volatile Fatty Acid Accumulation in Seaweed-Arrested Anaerobic Digestion via a Two-Tier Framework of Engineering Diagnostics and Microbial Surveillance

This study presents a two-tier framework for brown seaweed-arrested anaerobic digestion (SW-AAD) by coupling engineering diagnostics (tier-1) with microbial surveillance (tier-2) to transform conventional digesters into volatile fatty acid (VFAs) biorefineries. In 70-day lab-scale batch tests (volume: 2 L), engineering diagnostics revealed that sequential additions of brown seaweed elevated salinity to 3.3% ash content, stabilized pH at 5.8-6.1, collapsed the CH/CO2 ratio from 2.98 to <0.04, suppressed biogas by 96%, and boosted carbon-conversion efficiency from 10% to 52%. More than half of the influent carbon was redirected from methane to a liquid-phase VFAs pool, dominated by butyrate, hexanoate, and acetate, peaking at 14.5 g L-{superscript 1}. Microbial surveillance using 16S rRNA sequencing presented a 10-fold decline in methanogens, alongside an increase in salt- and acid-tolerant acidogenic microbial families, including Lachnospiraceae, Ruminococcaceae, and Clostridiaceae, as well as seaweed-derived microbial families, including Psychromonadaceae, and Marinomonadaceae. Temporal synchrony and asynchrony-resolved analysis confirmed a strong correlation between two tiers, revealing an operational window featured with two patterns: a rapid engineering parameter response (where changes in engineering parameters were followed by a decline in methanogens within 0-3 days) and a slower microbial restructuring (where the surge in VFA concentration lagged the enrichment of seaweed-derived acidogens by 1-5 days). Based on this operation window, feedback control strategies were simulated for SW-AAD, indicating that cumulative VFAs (cVFAs) yield could be bolstered from 11.38 to 16.13 g COD L-{superscript 1} (+41.8%). A techno-economic assessment (TEA) revealed that this VFA-targeted SW-AAD can reduce capital expenditure by [~]20% compared to conventional AD. This study underscores the promise of asynchrony-resolved analysis of SW-AAD systems for robust and economically viable VFAs production from organic waste. Graphics O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/680780v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1dc596dorg.highwire.dtl.DTLVardef@1731cadorg.highwire.dtl.DTLVardef@5fe025org.highwire.dtl.DTLVardef@74d8d3_HPS_FORMAT_FIGEXP M_FIG C_FIG Environmental synopsisBrown seaweed-arrested anaerobic digestion (SW-AAD) leverages seaweed-driven salinity, and acidification to suppress methanogenesis, diverting >50% of carbon to VFAs (14.5 g COD L-{superscript 1}) while cutting methane by 99%. A two-tier framework couples engineering diagnostics with microbial surveillance and asynchrony-resolved analysis, enabling feedback control and low-emission waste valorization in digesters.

bioengineering↗

bioRxiv2025

Astrocytes and neurons encode natural stimuli with partially shared but distinct composite receptive fields

Astrocytes are increasingly recognized as active participants in sensory processing, but whether they show selective responses to stimulus features, analogous to neuronal receptive fields, is not yet established. To address this, we used two-photon calcium imaging in the auditory cortex of anesthetized mice during presentation of natural ultrasonic vocalizations. Our aim was to compare astrocytic responses with those of neighboring neurons and to determine whether astrocytes exhibit feature-selective receptive fields. Event detection showed that astrocytic calcium activity is highly heterogeneous, but only a minority of events were consistently stimulus-linked. To examine this stimulus-driven subset, we estimated receptive field features using maximum noise entropy modeling and compared them with those of concurrently recorded neurons. Despite qualitative similarities in receptive-field features, analysis of modulation spectra and principal angles showed that astrocytic and neuronal receptive fields overlap but occupy distinct regions of feature space. This indicates that astrocytes and neurons encode partially shared, but not identical, dimensions of the sensory stimulus. Our findings indicate that astrocytes encode diverse sensory features, providing an additional contribution to neuronal encoding. This suggests that astrocytic calcium activity is not simply a reflection of neuronal firing, but instead represents a distinct component of cortical sensory processing. New and noteworthyWe used two-photon imaging to record calcium activity in astrocytes and neighboring neurons during presentation of natural ultrasonic vocalizations. We show that astrocyte activity is highly heterogeneous across spatial and temporal scales. Further analyses indicate that a subset of astrocyte calcium activity is stimulus-linked and encodes dimensions of the stimulus that partially overlap but are not identical to those encoded by neurons.

neuroscience↗

bioRxiv2025

Programming Microbe-Computer Interaction for Customized Life-Nonlife and Cross-Life Communication

This extension of human-computer interaction (HCI) paradigm to the non-intelligent microbe-computer interaction (MCI) is attractive for building generalized life-nonlife communication. Main challenges lie in how to construct biohybrid interface within individual MCI unit and thereafter program cross-life communication based on these MCI units. Here, we propose the design and construction of opto-interfaced MCI unit composed of engineered microbes and computer terminals, for enabling quantifiable transduction between microbial signals and digital signals. These units were able to serve as biohybrid sensors, actuators and transceivers, supporting biomonitoring, bio-actuation and microbe-centric bidirectional operations. Based on these functional units, we established programmable cross-life communication architectures capable of unicast, multicast, and logic-gate-driven communication with temporal dynamic control. The architectures were validated in biomedical scenarios including tumor hypoxia biomarking, epidermal heavy metal detoxification, and colitis intervention, demonstrating robust performance in closed-loop diagnostic-therapeutic applications. Additionally, we integrated MCI with an unmanned surface vessel for environmental monitoring, highlighting its cross-domain potential. Collectively, we provide a scalable strategy for building customized life-nonlife and cross-life communication, which is expected as an important complement to internet of things (IoT).

synthetic biology↗

bioRxiv2025

A cross model spatial and single-cell atlas reveals the conserved involvement of osteopontin in polycystic kidney disease

Polycystic kidney disease (PKD) arises from mutations in cilia-associated genes, such as PKD1 and PKD2, expressed in renal epithelial cells, leading to progressive kidney dysfunction and end- stage kidney disease (ESKD). PKD patients exhibit significant heterogeneity in disease progression, largely due to genetic and environmental modifiers. Like patients, mouse models of PKD also exhibit significant heterogeneity with regards to the gene mutated, age of disease onset, and rate of disease progression. To elucidate the cellular and molecular consequences of these variables, we constructed an integrated single-cell and spatial transcriptomics atlas across mouse models of PKD, mapping changes in cell type composition, gene expression, and intercellular signaling networks across the whole atlas and within individual models. Consistently across models, single cell RNA sequencing (scRNAseq) data revealed increased Spp1 (osteopontin) expression and signaling from PKD-enriched clusters to Ly6clo monocytes. Global deletion of Spp1 in Pkd1RC/RC mice resulted in reduced cyst severity, improved kidney function, and reduced Ly6clo monocyte numbers, suggesting that SPP1 signaling to Ly6clo monocytes promotes PKD progression. We also created a freely available, searchable website (https://bmblx.bmi.osumc.edu/scPKD/) that can be used to identify cross- and intra-model specific changes in gene expression, guiding researchers to new therapeutic targets for treating PKD.

bioinformatics↗

bioRxiv2025

RhoV Promotes Proliferation, Migration, and MAPK Activation in Pancreatic Ductal Adenocarcinoma

Background and AimsPancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy characterized by diagnosis at advanced stages, limited therapeutic options, and frequent resistance to therapies. Although oncogenic KRAS mutations are central drivers of PDAC, alternative pathways indisputably contribute to its tumorigenesis and progression. RhoV, a member of the Rho family of small GTPases, has been implicated in tumor development in other cancer types, such as breast cancer and lung adenocarcinoma; however, its role in PDAC remains unclear. MethodsIn this study, we investigated the expression and functional impact of RhoV on PDAC. Analysis of publicly available datasets and immunohistochemical profiling of 114 PDAC patient specimens were used to evaluate the expression of RhoV in PDAC and its prognostic impact. Overexpression and CRISPR-Cas9-mediated knockout of RhoV were established in three pancreatic cancer cell lines. Functional analyses, such as cell proliferation, migration, invasion, colony formation, spheroid growth, and mouse xenograft, were used to evaluate the role of RhoV in PDAC cells. ResultsRhoV overexpression was associated with reduced overall and recurrence-free survival in public datasets and our own patient cohort. Functional assays demonstrated that RhoV overexpression promoted PDAC cell proliferation, colony formation, and spheroid growth, whereas knockout of RhoV suppressed these changes. Moreover, RhoV enhanced PDAC cell migration and invasion in vitro, accompanied by downregulation of E-cadherin and upregulation of N-cadherin and vimentin, indicating induction of epithelial-mesenchymal transition. Mechanistically, RhoV overexpression activated key MAPK pathway components, including phosphorylation of ERK, JNK, and p38. In vivo, xenograft models confirmed that RhoV drives tumor growth and increases tumor burden. ConclusionThese results establish RhoV as a novel oncogenic factor in PDAC progression and highlight its potential as a biomarker and therapeutic target, warranting further investigation into combinatorial targeting strategies to overcome KRAS inhibitor resistance.

cancer biology↗

bioRxiv2025

MetaScope: A High-Resolution Framework for Species-Level 16S Metataxonomic Classification

Accurate species-level classification of microbial communities remains a major challenge in microbiome analysis, particularly when using traditional 16S rRNA amplicon sequencing pipelines such as QIIME2 and DADA2. These methods often fail to resolve taxonomy beyond the genus level due to limitations in clustering algorithms and ambiguous marker genes. To address this, we present MetaScope, a modular, R-based software package that reimplements and extends the PathoScope 2.0 framework for high-resolution microbial classification. MetaScope introduces two key innovations: (1) the integration of user-defined or empirical prior weights into the Bayesian read reassignment algorithm to improve abundance estimation, and (2) MetaBlast, a secondary BLAST-based validation module for refining species-level assignments. Benchmarking against mock and clinical datasets demonstrates that MetaScope significantly outperforms QIIME2 and DADA2, achieving up to 93.6% species-level classification accuracy. This translates to offering enhanced resolution for downstream analyses such as ecological diversity metrics. These results highlight MetaScope as a powerful tool for advancing microbial community profiling in both research and clinical settings.

bioinformatics↗

bioRxiv2025

Self-Reactive B Cells in Artery Tertiary Lymphoid Organs Encode Pathogenic High Affinity Autoantibody in Atherosclerosis

Artery tertiary lymphoid organs (ATLOs) emerge in atherosclerosis which is a chronic inflammatory artery disease with an autoimmune component. However, whether disease-relevant autoimmune B cells emerge in ATLOs and their impacts remains unknown. To map atherosclerosis-specific humoral autoimmunity and define its roles, we isolated germinal-center (GC) B cells from ATLOs and lymph-nodes, expression-cloned 60 autoantibodies and screened them for arterial wall reactivity. ATLO-derived autoantibodies markedly skewed to atherosclerosis-relevant autoantigens versus those of lymph-nodes. One ATLO GC-derived autoantibody bound to histone 2B (H2B) with high-affinity ([~]25 nM). Moreover, vaccination with H2B or adoptive transfer of its cognate autoantibody markedly accelerated atherosclerosis suggesting that ATLOs fail to delete pathogenic high-affinity self-reactive B cells. In a human cohort, total circulating anti H2B antibody titers positively correlated with aortic and coronary artery calcification. We conclude that ATLOs harbor a dysregulated immune tolerance environment permissive for autoreactive B cells that express pathogenic autoantibodies driving atherosclerosis.

immunology↗

bioRxiv2025

MultiAlloDriver: a multi-model method to predict and identify cancer driver mutations

A minority of driver mutations in cancer significantly alter protein structure and key functionalities, thereby driving cancer progression. Consequently, the prediction and identification of driver mutations hold critical implications for targeted cancer therapy. This study introduces MultiAlloDriver, a novel multi-modal machine learning model based on an attention mechanism, which for the first time, incorporates protein surface information. By integrating information from three dimensions-protein sequence, structure, and surface-the model achieves high-accuracy driver target prediction with an accuracy exceeding 93%. Notably, we utilized this tool to predict and identify the driver effect of the F90S mutation in the PTEN tumor suppressor gene, uncovering mutations associated with cancer signaling mechanisms. Overall, MultiAlloDriver contributes to elucidating the underlying mechanisms of cancer development and progression, providing a robust framework for the identification of driver targets.

bioinformatics↗

bioRxiv2025

Klf4-dependent pivotal role of smooth muscle-derived Gli1+ lineage progenitor cells in lung cancer progression

Lung cancer remains the leading cause of cancer-related deaths worldwide. Despite the remarkable efficacy of immune checkpoint inhibitors, only a subset of lung adenocarcinoma (LUAD) patients respond and many eventually progress, underscoring the need to develop novel combination therapies. The interaction between cancer cells and the tumor microenvironment (TME), a complex niche including cells of the innate and adaptive immune system, cancer-associated fibroblasts (CAFs), vascular cells, and extracellular matrix (ECM) plays a vital role in tumorigenesis and cancer progression. Using fate mapping, we previously identified a novel subpopulation of resident vascular stem cells derived from vascular smooth muscle cells, designated AdvSca1-SM (vascular Adventitial location, Stem cell antigen-1 expression, SMooth muscle origin) cells. AdvSca1-SM cells are the predominant cell type responding to vessel wall dysfunction and their selective differentiation to myofibroblasts promotes vascular fibrosis. SMC-to-AdvSca1-SM cell reprogramming is dependent on SMC induction of the transcription factor KLF4, and KLF4 is essential for maintenance of the stem cell phenotype. The function of AdvSca1-SM cells in LUAD tumorigenesis has not been explored. Using an orthotopic immunocompetent mouse model of LUAD, we demonstrate that AdvSca1-SM cells are a major component of lung tumors, significantly contributing to cancer associated fibroblasts (CAFs). Compared to AdvSca1-SM cells, CAFs have altered ECM gene expression with a reduction of a stemness signature. AdvSca1-SM-specific genetic ablation of Klf4 altered their phenotype resulting in inhibition of communication between cancer cells and CAFs, decreases in innate immunosuppressive populations, and increased T cell infiltration into the tumor. Targeting this population may represent a novel strategy to improve the response to immunotherapy.

cancer biology↗