Biology subjects

Wu, Y.

Publications and source records attributed to Wu, Y..

At least 199 records · Page 11Linked to original sources

bioRxiv2025

Temporal single-cell profiling uncovers age-associated delays in immune resolution to respiratory viral infection

Aging is a major risk factor for increased morbidity and mortality following acute respiratory virus infections. To elucidate the immune determinants underlying viral pathogenesis and delayed lung repair in the aged lung, a comprehensive time-course study was conducted. Single-cell RNA sequencing (scRNAseq) and high-dimensional flow cytometry were utilized to compare lungs from young and aged mice infected with influenza A virus (IAV). Aged hosts displayed diminished alveolar macrophage (AM) and dendritic cell (DC) but elevated monocyte-derived macrophage (MoM) and interstitial macrophage (IM) presence following infection. Additionally, enhanced accumulation of adaptive immune cells, including CD4+ tissue-resident helper (TRH) cells, CD8+ tissue-resident memory (TRM) cells, and a B cell subset resembling age-associated B cells, was observed in the memory phase. Pathway analysis revealed that elevated type I and II interferon (IFN/{gamma}) signaling, especially in MoM/IM subsets, distinguished the aged hosts from the young. Inhibition of IFN/{gamma} signaling after viral clearance improved long-term respiratory outcomes and reduced both IM and TRH populations in aged mice. These findings highlight the pivotal role of IFN/{gamma} signaling, likely within MoM/IM subsets, in driving the exuberant persistence of adaptive immune cells and chronic immunopathology in the aged lung following acute viral infection.

immunology↗

bioRxiv2025

The Overlap Area as a Novel Measure of Effect Size in Neuroscience Research

In experimental biomedical research, a common concern is whether a manipulation produces a biologically meaningful effect. Another concern is whether effect sizes are reliable, statistically significant, and generalizable. Traditional effect size measures, such as Cohens d, quantify mean differences but ignore variance heterogeneity between groups. This can result in biased effect size estimates and a lack of thresholds for statistical significance testing. Motivated by this, we introduce a novel effect size measure, termed overlap area (OA), which quantifies the difference between the population distributions of the experimental and control groups. A robust Bayesian method estimated OA, and random resampling determined OA thresholds for statistical significance in single and replicated experiments. Simulations confirmed the approachs sensitivity and robustness. Applied to a real-world dataset, OA revealed that environmental enrichment affects the mouse brain synaptome. Moreover, we developed an open-source toolbox supporting OA as a powerful new measurement for conducting robust, reliable, and reproducible analyses of manipulation effects in neuroscience and related fields.

neuroscience↗

bioRxiv2025

Automation workflow for high-throughput arrayed plasmid DNA preparation and quantification.

High-throughput generation of arrayed plasmid DNA library using commercially available miniprep kits remains labor-intensive and costly. The yield and quality of plasmid preparations directly affect downstream applications, including arrayed viral library production and CRISPR library screening. Insufficient plasmid yield or DNA concentration often requires repeated preparations or additional DNA concentration steps to obtain adequate quantities. Similarly, higher variations in yield or quality across wells or plates can render an entire library unsuitable for subsequent experiments. To increase productivity and mitigate human intervention and errors, the present study established an automated workflow for high-throughput plasmid DNA preparation and quantification. The workflow was carried out by the Biomek i7 Hybrid automated workstation, synergizing a robotic liquid handler and multiple peripheral instruments to produce and measure plasmid DNA in a 96-well plate format. Bacterial competent cells were alkaline lysed and plasmid DNA was purified using magnetic beads, followed by quantification with the PicoGreen assay. The PicoGreen assay reported median and average yields of approximately 9.5 and 10 {micro}g per sample, respectively, which are equivalent to 7.6 and 8 {micro}g/mL of bacterial culture. Plasmid DNA concentrations measured by the PicoFluor fluorometer were consistently lower than those obtained using the NanoDrop UV spectrophotometer. The comparison demonstrated robust positive correlation between PicoGreen assay and NanoDrop measurements (R2 > 0.8). Among 480 plasmid DNA samples, average and median yields measured by the NanoDrop reached approximately 24 and 25 {micro}g per sample per well, corresponding to 19 and 20 {micro}g/mL of bacterial culture. Over 98% of samples exceeded the high-yield threshold of 10 {micro}g/mL of culture, with high plasmid quality validated through DNA gel electrophoresis. Collectively, this study demonstrated a robust, scalable, and cost-effective automation platform for high throughput arrayed plasmid library generation and quantification.

molecular biology↗

bioRxiv2025

Automatic binding of basic sensory features requires consciousness

Conscious awareness requires establishing coherent percepts. Yet, whether consciousness is necessary for initiating the integration of basic sensory features remains unclear. Competing theories implicate distinct functional regimes of consciousness in the process of feature binding and creating conscious percepts. We used a novel multi-feature oddball paradigm with intracranial stereo-electroencephalography (sEEG) recordings in awake and anesthetized states to investigate the functional boundary of consciousness. In the awake state, the auditory attributes of loudness and tone, as well as the binding of the two features, were automatically encoded without attention to the stimuli in a functionally localized sensory cortical network. In the anesthetized state, the cortical registration of single attributes was preserved, whereas the binding was abolished. Moreover, anesthesia mostly influenced later cortical processes after stimuli offset. These results reveal the borderline of exertion of consciousness between the encoding and manipulation of basic sensory features in local cortical circuits - the functional boundary of consciousness constrains the feedforward binding and recurrent process directly at local rather than global level computations.

neuroscience↗

bioRxiv2025

A high-throughput methods SNIPR-Nm reveals small RNA methylation ratio

Small RNAs regulate gene expression and genome stability, and their functions are shaped by 3'-terminal 2'-O-methylation (Nm). Although Nm is universal in plants and mainly marks animal piRNAs, recent evidence reveals Nm on mammalian miRNAs, highlighting broader regulatory roles. However, current sequencing underestimates Nm-modified RNAs due to ligation bias, and existing qPCR-based methods cannot simultaneously quantify abundance and modification, leaving Nm dynamics largely unexplored. We developed a unified enzymatic strategy that integrates poly(A) polymerase and a thermostable ligase to measure both small RNA abundance and 3'-end Nm status. Applied to mouse testis, it enables robust quantification of Nm ratios for piRNAs and miRNAs. Our method offers a versatile tool for dissecting small RNA methylation in development and disease.

genetics↗

bioRxiv2025

VIP-OT: Dissecting Single-Cell Biochemical State Dynamics under Perturbation via Vibrational Painting and Optimal Transport

Dissecting the heterogeneous response of individual cells towards genetic and chemical perturbations is central to understanding the dynamic functions of cells and multicellular systems. However, characterizing and modeling how individual cells transition between different states remains a major challenge. Vibrational imaging provides high-content, biochemically informative, label-free molecular fingerprints of single cells but it remains at its infancy for dynamic or predictive analysis of cell state transition. Here, we introduce Vibrational Painting-Optimal Transport (VIP-OT), an integrated experimental-computational framework that overcomes this fundamental limitation. VIP-OT couples multiplexed infrared (IR) and Raman imaging with optimal transport to computationally reconstruct single-cell perturbation trajectories from unpaired population snapshots. When applying to over 22,000 single-cell spectra profiles from human breast adenocarcinoma cells under 16 drug treatments, this framework can retrospectively trace drug response heterogeneity back to baseline metabolic states. We leverage the inferred cell pairings to develop a machine learning model that accurately predicts the full post-treatment metabolic state of individual cells from their pre-treatment spectra. Furthermore, by modeling transitions across dose gradients, we introduce the concept of Spectral Velocity to map dynamic response trajectories and resolve drug combination effects into distinct, path-dependent molecular routes. Together, VIP-OT opens a new direction for dissecting heterogeneous perturbation responses at single cell resolution and serves as a foundation for building virtual simulators of cells under perturbations through high-throughput, high-content, and low-cost vibrational imaging, as well as interpretable in silico modeling.

bioengineering↗

bioRxiv2025

Genome-wide SNP diversity in natural and cultivated populations informs restoration ecology with three Calamagrostis species from the Northwest Territories of Canada

There is growing demand for data-driven frameworks to guide robust plant restoration strategies in response to anthropogenic disturbances. Several seed-sourcing (i.e., provenancing) strategies have been proposed, which balance the use of locally adapted genotypes against mixed genotypes to reduce mutation load or assistant migration to anticipate future climate scenarios. However, taxonomic uncertainty and lack of data characterizing genetic differentiation and gene flow have hindered provenancing strategies for many ecologically important non-model plant species--especially those in remote but vulnerable regions like the boreal forests of northern Canada. To guide provenancing strategies following anthropogenic disturbance in Canadas Northwest Territories, we characterize species-specific markers, population structure, and hybridization among three Calamagrostis species. Double digest RAD sequencing (ddRAD) resulted in 2,951 polymorphic loci across 27 individuals, which we used to design loci for genotyping in thousands by sequencing (GT-seq), a cost-efficient target loci approach resulting in 256 polymorphic loci across 93 individuals from wild C. canadensis, C. stricta ssp. inexpansa and C. purpurascens populations. To help define the scale of local populations for seed sourcing, we characterized geographic variation and population structure among 57 wild collection sites. We also assessed genetic relationships of wild C. canadensis to 69 individuals across eight commercially maintained populations used in restoration projects. We found that GT-seq yields similar genetic differentiation patterns as common neutral molecular marker approaches like ddRAD-seq. Specifically, we resolve morphologically misidentified individuals, identify genetic hybrids, and characterize the scale of genetic isolation-by-distance. Finally, we determined that three cultivar seed sources were genetically similar to southern wild populations, whereas five cultivars aligned with northern wild populations of C. canadensis in the Northwest Territories of Canada. Overall, our results highlight the benefits of cost-effective methods for genome-wide multi-locus genotyping to inform provenancing best-practices and support more effective and sustainable restoration efforts.

genomics↗

bioRxiv2025

Normative modeling of brain morphology reveals neuroanatomical heterogeneity and biological subtypes in major depressive disorder

BACKGROUNDMajor Depressive Disorder (MDD) is characterized by high neurobiological heterogeneity, which hinders precise diagnosis and treatment. Traditional group-level neuroimaging analyses fail to capture individual differences, while normative modeling offer a promising approach to quantify individual deviations from healthy brain structure patterns, facilitating the identification of biological subtypes and offering a data-driven framework to dissect this heterogeneity. METHODSUsing 1,190 healthy controls, we constructed normative developmental trajectories of gray matter volume (GMV) across 246 Brainnetome-defined regions using Bayesian linear regression. Deviation maps were derived for 398 MDD patients. k-means clustering was employed to identify GMV-based biotypes. Then, the clinical characteristics and anatomical differences among these subtypes were explored, along with the post-treatment clinical features and treatment responses of participants who completed the 8-week antidepressant treatment within each subtype. RESULTSPatients with MDD exhibited widespread yet individually variable GMV deviations. Clustering analysis revealed two subtypes: Subtype 1 displayed predominantly negative deviations in sensorimotor and occipital cortices, whereas Subtype 2 showed widespread positive deviations in temporal and posterior cingulate regions. Subtype 1 had higher extraversion and symptom-linked deviation patterns; in Subtype 2, deviation burden correlated with generalized anxiety. Longitudinally, Subtype 1s GMV deviation changes predicted symptom improvement, while Subtype 2s deviations correlated with baseline severity. CONCLUSIONSNormative modeling of GMV reveals marked neuroanatomical heterogeneity in MDD and identifies subtypes with distinct clinical and treatment-related characteristics, laying a foundation for precision psychiatry and individualized interventions.

neuroscience↗

bioRxiv2025

RamanOmics Decodes Spatial Vibrational-Molecular Architecture and Rewiring in Aging and Repair

Aging and tissue repair involve multilayered and spatially heterogeneous remodeling across transcriptional, biochemical, and cellular dimensions, yet prevailing definitions rely on isolated molecular markers that obscure how biochemical and transcriptional states co-evolve in tissues. Here we present RamanOmics, a multimodal framework that integrates single-nucleus RNA sequencing (snRNA-seq), spatial transcriptomics, and label-free Raman imaging to map the spatial vibrational-biochemical and molecular architecture of aging and senescence directly in intact tissues. Applied to mouse lung and skin, RamanOmics generates spatially resolved biochemical-molecular maps revealing tissue-specific programs: lung senescent cells are enriched for extracellular matrix (ECM) remodeling and TGF-{beta} signaling (Serpine1, Dab2, Igfbp7), whereas skin senescence is dominated by keratinization and barrier homeostasis modules (Krt10, Lor, Sbsn). Across tissues, we identify a conserved branched-chain fatty-acid-linked biochemical profile and Raman signature (1131-1135 cm-{superscript 1}) that robustly marks p21 senescent cells. To unify these layers, we develop a machine learning derived "multimodal barcode" that quantitatively integrates biochemical and transcriptional features, enabling non-destructive identification of senescence in situ. In a wound-healing model, RamanOmics further reveals coordinated reactivation of barrier-repair programs in senescent cells, marked by upregulation of Krt10, Lor, Sbsn, Sfn, and Dmkn together with matching increases in lipid-associated Raman signatures, confirming biological generalizability beyond steady-state aging. By directly integrating gene programs to spatial vibrational-biochemical states, RamanOmics provides a general framework and resource for scalable, multimodal profiling of cellular states.

systems biology↗

bioRxiv2025

IFN-I exacerbates the inflammatory response of epithelial cells to Chlamydia trachomatis infection by enhancing TLR3 expression

The inflammation induced by Chlamydia trachomatis infection in the female genital tract (FGT) can have severe consequences. Recent observations in women and mice infected with Chlamydia suggest that type I interferon (IFN-I) may have deleterious effects. This study aimed at elucidating the consequences of IFN-I production on C. trachomatis-induced inflammation in epithelial cells and the molecular pathway(s) involved. We showed that combination of IFN-I and Chlamydia resulted in a stronger induction of inflammation than Chlamydia alone, while IFN-I alone had no effect. Inhibiting AKT and mTOR, but not silencing STAT1, significantly attenuated the synergetic effect between IFN-I and bacteria on inflammation. Inhibition of ERK also blocked this synergistic effect, although ERK were not activated by IFN-I. We hypothesized that IFN-I enhanced the expression of a pathogen recognition receptor of the host, thereby potentiating detection of the bacteria and the subsequent inflammatory response. IFN-I, but not C. trachomatis infection, increased the expression of Toll-like receptor 3 (TLR3), and silencing or knocking-out TLR3 prevented the synergetic effect between infection and IFN-I. Furthermore, our data support the presence of dsRNA in infected cells and the activation of the MAPK/ERK and AP-1/ATF2 signaling cascades downstream of TLR3. Taken together, our data demonstrate that IFN-I exacerbates the host inflammatory response triggered by Chlamydia by increasing TLR3 expression and activation, leading to hyperinflammation. The identified signaling cascades represent potential targets for therapeutical intervention to limit tissue damage upon Chlamydia infection.

microbiology↗

bioRxiv2025

A tailored in vivo CRISPR screen identifies BAP1 as a potent tumor suppressor of soft tissue sarcoma

Undifferentiated pleomorphic sarcoma (UPS) is one of the most common soft tissue sarcomas (STS) in adults. Despite decades of research, therapeutic advancements for STS, including UPS, have remained limited. The genetic complexity of UPS, characterized by the absence of recurrent driver oncogene mutations, has hindered the development of effective targeted therapies beyond conventional chemotherapy and immunotherapy. To address this challenge, we conducted a customized in vivo CRISPR/Cas9 screen in mice to systematically identify potential tumor suppressors involved in UPS development. Our screen revealed BRCA1-associated protein 1 (Bap1) as a potent tumor suppressor in STS. Using total RNA sequencing, multiplex immunohistochemistry, and flow cytometry, we found that Bap1-deficient mouse sarcomas exhibit significant immune suppression. Further analysis indicated that polo-like kinase 1 (Plk1) is essential for the survival of Bap1-deficient sarcomas. Treatment with volasertib, a Plk1 inhibitor, markedly inhibited tumor growth in both syngeneic and spontaneous mouse models of Bap1-loss sarcoma. In conclusion, our findings suggest that PLK1 inhibition, or combined with immunotherapy, may represent a promising targeted therapeutic strategy for tumors lacking BAP1.

cancer biology↗

bioRxiv2025

The Emergence of Novel Versus Known Three-Dimensional Structures from Random Sequences.

It has been hypothesized that while random sequences are unlikely to fold into proteins of the length of globular proteins, repeated random sequences are more likely to adopt stably folded structures, with implications for molecular evolution. We used structure prediction methods to determine the foldability of approximately 120-residue sequences composed of 5-to 60-residue random repeats. With repeats of less than 30-residues, sequences were frequently discovered (1-12%) that fold with high confidence. For less than 60-residue repeats, we frequently observe {beta}-solenoids, similar to those seen in natural proteins. We observe solenoids stabilized by apolar packing as well as ones stabilized by polar interactions with Ca2+ in the core of the structure as in natural RTX domains. Helical bundles were observed with high frequency when insertions or deletions (INDELs) were included between blocks of repeating sequences. We also observed a new super-secondary structure consisting of a tightly wound -helical screw, and experimentally confirmed its stability and structure by CD spectroscopy and X-ray crystallography. Thus, structure predictors can discover structures that are well out of the distribution of the data upon which they were trained. Beyond 40-residue repeat lengths very few sequences were predicted to fold. The small number of structures we observed were representative of well-established major classes of tertiary structures; greater sampling would be needed to discover novel structures from a random distribution. These studies illuminate dark matter regions of protein structure space and support previous predictions that proteins evolved through the assortment of shorter peptide sequences. Significance statementThe availability of powerful and accurate programs for predicting protein three-dimensional structures enables one to ask fundamental questions concerning the origin of folded functional proteins during evolution. We show that 120-residue proteins composed of random sequences repeated in tandem are predicted to be much more likely to fold than fully random proteins. These studies validate previous predictions that proteins evolved through the repetition and assortment of short peptide sequences. Also, some of the predicted structures represent novel conformations, which were confirmed experimentally. These findings advance our understanding of molecular evolution and have implications for design of novel proteins.

biophysics↗

bioRxiv2025

Organoid Pharmacotyping of Pancreatic Cancer Enables Functional Precision Oncology and Drug Repurposing

PurposePancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest malignancies, with limited benefit from current cytotoxic regimens and poor predictive value of genomics alone. Patient-derived organoids (PDOs) represent a promising platform for functional precision oncology, yet systematic pharmacotyping of genomically annotated PDAC PDOs remains sparse. Experimental DesignWe established a clinically annotated panel of ten treatment-naive PDAC PDOs spanning well-, moderately-, and poorly differentiated tumors. PDOs were evaluated for morphologic and genomic fidelity and screened against 1,813 clinically relevant small molecules in a high-throughput 384-well format. Drug sensitivities were quantified at the compound and drug-family levels and integrated with histologic grade, pathway-level mutational profiles, and available clinical treatment information. ResultsPDOs preserved hallmark tumor features, including glandular organization and subclonal mutational architecture. Pharmacotyping revealed both shared and subtype-specific vulnerabilities. Classical (well/moderately differentiated) PDOs showed enriched mutations in DNA repair, mitotic spindle, and chromatin-regulatory pathways and were preferentially sensitive to topoisomerase inhibitors, microtubule poisons, and HDAC inhibitors. In contrast, basal (poorly differentiated) PDOs displayed coordinated defects in mitochondrial function, vesicle trafficking, and ubiquitin-mediated proteostasis, at the pathway level, that conferred a previously unrecognized vulnerability to cardiac glycosides. Sensitivities to standard PDAC agents were heterogeneous across models, underscoring the limited predictive value of genotype alone and the need for functional drug testing. ConclusionsThis integrated genomic and pharmacologic analysis demonstrates that PDO pharmacotyping identifies biologically grounded, actionable vulnerabilities in PDAC, including novel therapeutic opportunities in basal, chemo-resistant tumors. These findings support PDO-guided functional profiling as a clinically relevant platform for refining drug selection and expanding treatment options for patients with PDAC. SignificancePDAC is dominated by chemoresistance and lacks reliable genomic predictors of therapy response. By integrating high-throughput drug screening with mutation-informed pathway analysis in patient-derived organoids, we identify differentiation-linked therapeutic liabilities, including a previously unrecognized vulnerability to cardiac glycosides in basal PDAC. These results highlight PDO pharmacotyping as a powerful functional complement to genomics for guiding treatment selection in pancreatic cancer.

cancer biology↗

bioRxiv2025

Disentangling Cephalopod Chromatophores Motor Units with Computer Vision

Cephalopod chromatophores are skin pigment organs that enable unmatched camouflage through rapid, flexible and neurally controlled deformation. Although their morphology is well known, the organization of their motor control is not entirely understood. Here, we combine high-resolution videography with a dedicated computer-vision pipeline (CHROMAS) to investigate chromatophore control and their likely innervation in Euprymna berryi and Sepia officinalis. By segmenting chromatophores into radial slices and analyzing anisotropic deformations, we applied dimensionality reduction (PCA) and source separation (ICA) to estimate the number and spatial influence of motor neurons responsible for the control of individual and groups of chromatophores. On average, four independent components were detected (suggesting innervation by four motor neurons), each forming contiguous petal-shaped domains rather than causing uniform expansion. Clustering thousands of components revealed motor units spanning multiple chromatophores, most involving fewer than 14 but occasionally spanning more widely. These motor units displayed a wide variety of geometries, ranging from compact local groups to elongated or fragmented structures; they often overlapped, with repeated co-innervation of chromatophore pairs occurring more often than expected by chance. Expansion was consistently faster and more stereotyped than relaxation, consistent with active contraction (corresponding to chromatophore expansion) and passive recoil (chromatophore contraction). Together, these results show that individual chromatophores are not singular or uniform pixels, but rather contrast elements that can be fractionated into smaller territories, themselves coordinated with those of other chromatophores. This geometry of neural control enables, among others, the generation of "virtual" chromatophores, i.e., functional groupings of adjacent chromatophore territories that act as single units, as well as that of noise in the distribution of pixel shapes.

neuroscience↗

bioRxiv2025

Integrative spatial multi-omics reveals prognostic tumor niches in female genital tumors

Female genital tumors (FGTs), including ovarian, endometrial, and cervical cancers, pose a major global health challenge, yet their spatial and molecular determinants of progression and therapy resistance remain poorly understood. Here we present a large-scale integrative spatial and multi-omics atlas of FGTs, combining exome, transcriptome, methylome, and miRNA sequencing with high-resolution Visium HD spatial transcriptomics, profiling over 62 million cells from 100 tumors. We show that HPV-driven suppression of TGF{beta} signaling in cervical cancer disrupts myofibroblast (myCAF) formation and reshapes immune infiltration, while serous tumors exhibit extensive oncogene amplifications that activate MYC and PI3K pathways, linking chromosomal instability (CIN) to proliferative, immune-cold phenotypes. In high-grade serous ovarian cancer, we identify a previously unrecognized malignant domain, the Proliferating Core Desert (PCD) niche, defined by CIN-high epithelial enrichment, immune exclusion, stromal protection, and chemotherapy resistance, maintained through crosstalk with macrophages and fibroblasts. Finally, we develop POWER, a pathology foundation model that predicts PCD niche abundance from routine H&E slides, enabling robust stratification of prognosis and anti-angiogenic therapy response.

genomics↗

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

Repurposed endogenous virus-like vesicles mediate dendritic cell long-range antigen presentation and T cell activation for enhanced cancer vaccination

Dendritic cells (DCs) release extracellular vesicles (DEVs) that amplify antigen presentation while incorporating patient-derived, rapidly evolving antigens. By enriching peptide-MHC and co-stimulatory ligands orders-of-magnitude above donor-cell levels, DEVs emerge as potent vesicle-vaccines, although efficacy remains limited by unclear mechanisms. We show that DCs repurpose viral components to generate endogenous virus-like vesicles (VLVs) that preferentially carry peptide-MHC and high-density co-stimulatory ligands, intensifying and extending antigen presentation. Upon antigen exposure, Arc partners with endogenous envelope proteins to assemble VLVs that directly engage T cells and trigger intrinsic adjuvanticity via viral mimicry. Arc-/- DEVs failed to prime antigen-specific T cell responses, whereas Arc overexpression with its 5'-UTR stem-loop shifted DEVs toward VLVs that trafficked to lymphoid organs, drove rapid CD4-assisted priming and durable CD8-biased memory, suppressed melanoma, and prolonged survival. These reveal a viral-mimicry mechanism enabling long-range immune activation and support Arc+ VLVs as an antigen-agnostic vaccine for cancer immunotherapy. HighlightsO_LIArc+ VLVs intensify and extend DC antigen presentation in vivo C_LIO_LIArc+ VLVs directly engage T cells and trigger viral-mimic adjuvanticity C_LIO_LIArc-/- DEVs fail to prime antigen-specific T cell responses C_LIO_LIEngineered Arc+ VLVs drive durable CD8-biased memory and tumor control C_LIO_LIArc+ VLV vaccination provides long-range and cross-tumor protection in vivo C_LI

bioengineering↗

bioRxiv2025

TAp73 mediates anti-tumor immunity through regulation of lipid metabolism in the lung tumor microenvironment

While immunotherapy has become the standard of care for lung adenocarcinoma (LUAD) patients without actionable genomic alterations, only a subset of patients benefits from a long-lasting response to immunotherapy. Activation of p53-related signals has emerged as a potential mediator of the lung tumor microenvironment (TME). Given that mutant-p53 interacts with p73 extensively and TAp73-deficient mice develop LUAD, we engineered a mouse model with conditional deletion of TAp73 to understand the interactions of the p53 family in the TME and in metabolic pathways that impact anti-tumor immunity. We demonstrated that TAp73 exerts a tumor-suppressive role in KrasG12D-driven LUAD by regulating lipid metabolism in the TME. We identified a TAp73-driven transcriptional signature involving genes in the arachidonic acid metabolism pathway operational in tumor-associated macrophages that favors T-cell activation and thus anti-tumor immunity. Similar transcriptional changes are seen in macrophages from LUAD patients with p53 mutations and in association with response to immunotherapy. SIGNIFICANCEThere is a need to understand how the LUAD TME impacts patient response to immunotherapy. We identified a transcriptional program enacted by TAp73 in tumor alveolar macrophages that supports T-cell activation. Transcriptional and metabolomic data from LUAD patients supports the relevance of this program in response to immune checkpoint inhibition.

cancer biology↗