Biology subjects

Yu, Q.

Publications and source records attributed to Yu, Q..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Membrane proteomics of the Drosophila circadian neural network

Circadian behaviors are controlled by dedicated brain pacemaker neurons, whose activity oscillate during the day and the night. The Drosophila brain contains ca. 240 such neurons. Their molecular clock is synchronized, but the phase of their rhythmic neural activity differs dramatically between functional groups. This explains how specific circadian neurons can for example promote morning or evening locomotor activity. To understand in depth how the circadian network functions, we surveyed its membrane proteome in the morning and evening, using in situ protein labeling and mass spectrometry. In addition to detecting known regulators of circadian behavior, we identified novel membrane or membrane-associated proteins present in circadian neurons. Through genetic screens, we found that many of these proteins regulate circadian behavior. In particular, Piezo regulates morning activity specifically under short photoperiod, and its loss compromises the structural plasticity of the clock neurons controlling locomotion at dawn. Our work thus illustrates the power of proteome-guided genetic screens to understand the mechanisms underlying circadian behavior.

neuroscience↗

bioRxiv2026

Systematic Characterization of Thermal Stability Assay Parameters and Application in Discovery of Peptide-Protein Interactions

Thermal proteome profiling (TPP) and its higher-throughput derivative, the proteome integral solubility alteration (PISA) assay, measure changes in protein thermal stability upon ligand binding or other perturbations and have been widely adopted in drug discovery and biomedical research. Though the PISA workflow is straightforward, key parameters, including detergent concentration, methods for removing denatured aggregates, and temperature range selection, vary across studies and can markedly influence assay outcomes. Yet these factors have not been systematically evaluated, limiting rational experimental design and data interpretation. Here, through a combined use of TPP, PISA, tandem mass tag (TMT)-based multiplexing, and computational simulation, we systematically characterize these parameters based on the melting behavior of [~]9,000 proteins. We find that reducing detergent concentration elevates apparent Tm by 1.5-2{degrees}C proteome-wide, and aggregate removal by filtration versus centrifugation further alters measurements. We leverage these observations to characterize how these parameters shape PISA, then apply selected conditions to identify the aminopeptidase NPEPPS as a previously uncharacterized binding partner of angiotensin II, a key vasoactive peptide hormone in blood pressure regulation. Together, this work provides a general framework for assay design and data interpretation, and extends the utility of PISA beyond small molecules to dissecting peptide-protein interactions, an increasingly important modality in drug discovery.

biochemistry↗

bioRxiv2026

Analysis of Confounding Factors in Reactive Cysteine Profiling Reveals Enhanced Chromatin-Protein Association via CDK7 Inhibition by THZ1

Recent advances in activity-based proteome profiling (ABPP) have enabled global mapping of cysteine ligandability, uncovering novel biological insights and opportunities for identifying disease vulnerabilities. While both live cell-based and native lysate-based ABPP have been applied, how cysteine ligandability differs between these systems and what factors influence these measurements remain unclear. Building on our previous development of a high-throughput TMT-ABPP workflow for native lysates, here we adapt the protocol for live cells and systematically compare cysteine ligandability across both platforms. Our analysis reveals three major contributors to the discrepancies: in-cellulo cysteine accessibility, protein abundance changes, and protein relocalization. Notably, we highlight that CDK7 inhibitor THZ1 induces substantial protein relocalization and promotes chromatin binding. Together, these results provide a practical framework for ABPP experimental design and data interpretation, supporting more accurate application of ABPP in functional proteomics and drug discovery.

cell biology↗

bioRxiv2026

Ribosome biogenesis bottlenecks reveal vulnerabilities in cancer

Cell growth requires elevated protein synthesis, which depends on the production of ribosomes. Ribosome biogenesis is a complex, multi-step pathway in which newly transcribed precursor ribosomal RNA (rRNA) undergoes coordinated processing and assembly in the nucleolus to produce the small and large ribosomal subunits (SSU and LSU).1-3 Oncogene activation stimulates rRNA transcription and processing, giving rise to enlarged nucleoli that produce thousands of ribosomes every minute.4,5 However, efficient ribosome production requires tight coordination across numerous maturation steps, and it remains unclear if elevated rDNA transcription is proportionally converted into mature ribosomes, or whether imperfect coordination constrains the output yield. Here, we quantify pre-rRNA transcription (input) and compare it with newly-assembled cytoplasmic ribosomes (output), revealing that oncogene activation reduces the efficiency of ribosome production. Using a quantitative pulse-chase sequencing approach with mathematical modeling to resolve rRNA maturation kinetics, we found that oncogene activation creates late-stage processing bottlenecks, characterized by delayed precursor maturation and increased degradation. Perturbation of late-stage ribosome biogenesis factors preferentially impaired oncogene-driven cell growth, and limited tumor growth in mouse models, suggesting that these bottlenecks represent selective vulnerabilities in cancer, created by imbalanced biosynthetic flux. Together, these findings reveal that oncogene-driven ribosome production is imperfectly coordinated across maturation steps, and suggest that capacity limits in multi-step assembly pathways may be therapeutically exploitable in cancer and other diseases.

cell biology↗

bioRxiv2026

A cortical hierarchical mechanism for subjective visual experience during working memory

Working memory (WM) provides a mental sketchpad for simulating sensory experiences associated with mnemonic content. A critical unresolved question is how the brain generates the subjective sensory experience of these internal simulations. Here, we studied individuals with aphantasia, who report a subjective inability to generate visual imagery despite normal WM performance, providing a unique dissociation between objective WM performance and conscious subjective experience. During functional MRI, typical imagers and aphantasic individuals generated and maintained WM content from distinct sources (perception, imagery, or illusion) at a specific spatial location. Time-resolved multivariate analyses revealed a cortical hierarchical mechanism underlying the emergence of subjective visual experience in WM. Rather than dysfunctions in a single brain region, we identified a breakdown in feedback along a cortical pathway from the intraparietal sulcus (IPS) through area V3AB to the early visual cortex (EVC) in aphantasia. The IPS showed impaired imagery generation signals and reduced functional connectivity with EVC, whereas the EVC exhibited a general deficit in feedback independent of voluntary control. These impairments together led to weakened and unstable delay-period representations and precluded the transition from visual to mnemonic codes along the hierarchy. Notably, this network mechanism was specific to imagery at contralateral spatial locations, as ipsilateral IPS maintained compensatory, non-visual representations to support successful task performance without accompanying subjective experience. These results collectively demonstrate that the cortical hierarchy from IPS to EVC is critical for conscious mental visualization of memory content during WM maintenance.

neuroscience↗

bioRxiv2026

Sustained Relief of Chronic Pain via a Nav1.7_Targeting ASO_siRNA Conjugate

Chronic pain affects billions globally, yet safe, long-lasting, and non-addictive analgesics remain lacking. Nav1.7 is a genetically validated pain target, but traditional small molecules have repeatedly failed. Therapeutic oligonucleotides-antisense oligonucleotides (ASOs) and siRNAs-offer selective, durable silencing. We developed N02C0702, an ASO-siRNA conjugate (ASC), achieving robust Nav1.7 knockdown and sustained analgesia without additional delivery vehicles. N02C0702 outperformed individual ASO (N02A114) and siRNA (N02S154) moieties at mRNA and protein levels and in pain relief. In CFA-induced inflammatory pain, a single intrathecal dose exceeded naproxen and suzetrigine, while in SNL neuropathic pain, efficacy persisted up to 56 days, comparable to or surpassing pregabalin. Genome-wide RNA sequencing confirmed minimal off-target effects. N02C0702 highlights Nav1.7 as a key analgesic target and demonstrates the ASC platforms potential for chronic pain and other CNS-related pathologies, offering durable, selective, and safe therapeutic effects.

neuroscience↗

bioRxiv2026

STING-STAT3-SOX18 Axis Drives EndMT and Epigenetic Reprogramming in SAVI Lung Fibrosis

A high prevalence of early-onset interstitial lung disease, including pulmonary fibrosis, in pediatric patients with Stimulator of interferon genes (STING)-Associated Vasculopathy with onset in infancy (SAVI) suggests a critical role for the cGAS-STING pathway in the pathogenesis of pulmonary fibrosis. We identified an endothelial-to-mesenchymal transition (EndMT) signature in lesional lung biopsies from SAVI patients, marked by a loss of endothelial and acquisition of mesenchymal markers. Consistently, induced pluripotent stem cell-derived endothelial cells (iECs) from SAVI patients harboring gain-of-function STING1 mutations spontaneously undergo EndMT, a process rescued in isogenic-correction. In endothelial cells, STING activation induces IRF3-independent STAT3 phosphorylation, initiating a SLUG-dependent mesenchymal transcriptional program while repressing SOX18 and an epigenetically-regulated endothelial maintenance network. Our studies define a non-canonical cGAS-STING-STAT3 signaling axis that couples a mesenchymal transcriptional program with epigenetic silencing of an endothelial maintenance program, promoting TGF{beta}-independent STING-mediated EndMT and endothelial dysfunction, and suggesting STING as a therapeutic target for inflammatory pulmonary fibrosis.

cell biology↗

bioRxiv2026

Ribosome Molecular Aging Shapes Translation Dynamics

Cellular homeostasis relies on continual renewal of cellular components, yet some complexes like ribosomes persist for long periods, raising the question of whether extended molecular age impacts functional fidelity. Here, we introduce a spatiotemporal mapping strategy to resolve biomolecular life stages, and show that intracellular ribosome aging alters translational dynamics at specific transcripts. Molecularly aged ribosomes exhibit impaired elongation at basic amino acid-rich sequences, leading to increased pausing, premature termination, and ribosome collisions. By profiling ribosomal RNA modifications, we find that molecular aging increases the collision propensity of specific ribosome subpopulations. Consistent with our findings, enrichment of aged ribosomes in cells amplifies molecular age-dependent translation defects. In vivo labeling of ribosomes in aged C. elegans demonstrates that molecularly aged ribosomes shape translational dynamics during organismal aging. These findings identify ribosome molecular age as a determinant of translational dynamics, and link molecular aging of a core gene-expression complex to organismal aging. HIGHLIGHTSO_LIA pulse-chase labeling strategy enables mapping subcellular demographics of macromolecular complexes in space and time. C_LIO_LIMolecular aging of ribosomes drives differential mRNA translation and shapes elongation dynamics. C_LIO_LIThe collision propensity of specific ribosome subpopulations increases with molecular age. C_LIO_LIOlder ribosomes shape translation dynamics during organismal aging. C_LI

cell biology↗

bioRxiv2026

Integrative Multi-Scale Sequence-Structure Modeling for Antimicrobial Peptide Prediction and Design

Antimicrobial resistance (AMR) is accelerating worldwide, undermining frontline antibiotics and making the need for novel agents more urgent than ever. Antimicrobial peptides (AMPs) are promising therapeutics against multidrug-resistant pathogens, as they are less prone to inducing resistance. However, current AMP prediction approaches often treat sequence and structure in isolation and at a single scale, leading to mediocre performance. Here, we propose MultiAMP, a framework that integrates multi-level information for predicting AMPs. The model captures evolutionary and contextual information from sequences alongside global and fine-grained information from structures, synergistically combining these features to enhance predictive power. MultiAMP achieves state-of-the-art performance, outperforming existing methods by over 10% in MCC when identifying distant AMPs sharing less than 40% sequence identity with known AMPs. To discover novel AMPs, we applied MultiAMP to marine organism data, discovering 484 high-confidence peptides with sequences that are highly divergent from known AMPs. Notably, MultiAMP accurately recognizes various structural types of peptides. In addition, our approach reveals functional patterns of AMPs, providing interpretable insights into their mechanisms. Building on these findings, we employed a gradient-based strategy and achieved the design of AMPs with specific motifs. We believe MultiAMP empowers both the rational discovery and mechanistic understanding of AMPs, facilitating future experimental validation and therapeutic design. The codebase is available at https://github.com/jiayili11/multi-amp.

bioinformatics↗

bioRxiv2026

A spatiotemporal immune atlas of subarachnoid hemorrhage from single-cell and spatial transcriptomics

Background and PurposeSubarachnoid hemorrhage (SAH) triggers a complex immune response that critically influences early brain injury (EBI) and long-term outcomes. However, the precise spatiotemporal dynamics and heterogeneity of immune cell infiltration and microglial reprogramming remain poorly understood. We aimed to construct a high-resolution immune atlas to delineate cell states, lineage trajectories, and spatial niches following SAH. MethodsWe integrated single-cell RNA sequencing (scRNA-seq) of CD45+ immune cells with spatial transcriptomics (ST) in a murine endovascular perforation SAH model. Immune landscapes were profiled at 24 hours (acute phase) and 72 hours (subacute phase) post-injury, compared with sham controls. Advanced bioinformatics integrated transcriptional signatures with spatial localization to map macrophage, neutrophil, and microglial dynamics. ResultsOur atlas reveals a coordinated immune transition from acute inflammation to reparative processing. We identified five macrophage, four neutrophil, and eight microglial subsets with distinct spatiotemporal patterns. Notably, we discovered a SAH-specific inflammatory microglial population (MG_03; Spp1+/Lpl+) that clusters at the rupture site during the acute phase. This subset is transcriptionally distinct from disease-associated microglia (DAM) in other neurodegenerative conditions. Trajectory analysis suggests MG_03 acts as a signaling hub for immune recruitment before transitioning toward proliferative and reparative states (MG_06-08) that disperse into the parenchyma by 72 hours. ConclusionsThis study provides the first comprehensive spatiotemporal immune atlas of SAH, highlighting the distinct role of the Spp1+ MG_03 subpopulation in early injury sensing. These findings offer a roadmap for identifying precise therapeutic windows and targeting specific immune subsets to mitigate EBI. Graphical AbstractExperimental workflow for single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) in a mouse SAH model induced by endovascular perforation. Brain tissue from the ipsilateral (injured) hemisphere was collected from sham and at 24 h and 72 h post-SAH. For scRNA-seq, CD45 immune cells were isolated prior to library preparation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/703421v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@4a1bc9org.highwire.dtl.DTLVardef@16664c4org.highwire.dtl.DTLVardef@1619725org.highwire.dtl.DTLVardef@a0d34_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

Diversity and evolution of a phase-variable multi-locus antigen in Neisseria gonorrhoeae

Neisseria gonorrhoeae is a sexually transmitted bacterial pathogen that deploys multiple mechanisms to evade the immune system, including rapid variation in surface antigens. One of the most abundant and diverse antigens is the Opacity (Opa) protein, a surface protein that mediates gonococcal attachment to host receptors. Studies of Opa diversity and evolution have been limited by the inability of short-read sequencing to resolve the multiple copies of opa in each genome, preventing a comprehensive understanding of antigenic variation for vaccine design and immunology studies. We assembled a dataset of 219 complete genomes from diverse clinical isolates using long-read sequencing and developed bioinformatics and phylogenetics tools to assess opa variation quantitatively. Each genome had on average 7 distinct opa alleles at 9 to 12 opa loci, and almost all isolates had at least one pair of identical or near-identical opa genes. Fewer opa genes were in frame, and thus inferred to be expressed, than expected due to chance. While genomic distance between isolates correlated with overall opa allele sequence similarity, opa genes were on average 74 times more diverse than the rest of the genome. One opa locus evolved more rapidly than the other loci. There was little evidence that interspecies recombination contributed to N. gonorrhoeae opa diversity. Our findings reveal a continuously evolving opa repertoire that leads to diverse opa alleles even in closely related strains and indicate that there are likely unknown biological factors modulating opa expression. Author SummaryThe rising levels of antibiotic resistance in Neisseria gonorrhoeae make controlling the spread of this sexually transmitted pathogen a public health priority. N. gonorrhoeae rapidly varies surface proteins to evade recognition by the human adaptive immune system. Understanding how these proteins evolve may help us design better vaccines and control measures for curbing the spread of gonorrhea. One of the most abundant surface proteins is the Opacity protein (Opa), which helps N. gonorrhoeae bind to host cells upon colonization. Research efforts to understand the evolution of Opa have been limited because it is encoded by multiple genes in the genome that are not resolved by short-read sequencing technologies. Here, we resolved the genes that encode Opa using a dataset of 132 publicly available complete genomes and 87 genomes that we completed using long-read sequencing of diverse clinical isolates. We found that Opa evolves rapidly to generate different versions of the protein in the same isolate, but very few of these protein versions appear expressed. We also found evidence that there may be other, uncharacterized mechanisms that control how these proteins evolve over longer timescales.

evolutionary biology↗

bioRxiv2026

Protein aggregation inhibitors induce divergent transcriptional responses in a cellular model of a-synuclein seeded aggregation

Parkinsons disease (PD), dementia with Lewy Bodies (DLB) and multiple system atrophy (MSA) are progressive neurodegenerative disorders marked by the pathological aggregation of alpha-synuclein ([a]Syn). Despite significant research efforts, effective therapeutic interventions remain elusive due to limited understanding of the cellular effects of [a]Syn aggregation and propagation. This study presents the development of a scalable cellular seeding assay for screening small molecules targeting cellular [a]Syn seeded aggregation. By leveraging a fluorescent reporter of [a]Syn and phenotypic screening, the assay enables high-throughput evaluation of potential inhibitors in a cellular environment mimicking disease pathology. We evaluated three different Syn aggregation inhibitors tested in clinical trials for PD: Minzasolmin, Emrusolmin and EGCG and profiled gene expression using multiplexed single cell RNA sequencing in order to examine their distinct effects on cellular pathways associated with [a]Syn overexpression or seeded aggregation. Two cellular activities were prominently affected: lipid metabolism and rRNA processing. Notably, while EGCG effects were confined to cells with aggregated Syn, Minzasolmin and Emrusolmin also produced transcriptional changes in cells without aggregated Syn. Each of the compounds tested induced a partial reversal of transcriptional effects resulting from Syn seeded aggregation. We identified 391 genes that were no longer significantly differentially expressed upon addition of compound, relative to cells with seeded aggregation. This platform bridges phenotypic screening and molecular pathway analysis, providing insights into druggable pathways for synucleinopathies. The molecular signatures identified here can assist in testing and benchmarking future drug discovery leads.

neuroscience↗

bioRxiv2026

Borrelia Burgdorferi binds Serum Amyloid A and Modulates Subcutaneous Adipose Tissue Immune Signaling

Borrelia burgdorferi causes over 470,000 infections annually [1]. Following a tick bite, Borrelia spirochetes replicate in human skin and disseminate through tissues, including subcutaneous adipose tissue. Adipose tissue is a complex organ containing non-immune and immune cells that play a significant role in the immune response [2], yet little is known about adipose tissue signaling after Borrelia infection. We investigated the landscape of immune signaling within adipose tissue-resident cells during Borrelia infection in human tissue (skin and adipose tissue) ex vivo. Immune pathways overall were downregulated in adipose tissue during Borrelia infection. Despite this, adipose stem/progenitor cells exhibited increased pro-inflammatory and extracellular matrix (ECM)-related signaling (IL-6, MIF, collagen, laminin, fibronectin), positioning them as key hubs of intercellular communication during infection. Myeloid lineage cells showed cluster-specific upregulation of immune genes such as IL1B and TNF. Network analyses highlighted laminin, and strong outgoing MIF signals in all adipose-resident cell clusters. Among the identified genes modulated after Borrelia infection, we observed reduced expression levels of serum amyloid A in adipose tissue-resident cells, a marker typically elevated in Lyme disease patient serum during acute infection. Here, we show that human serum amyloid A1 and serum amyloid A2 directly bind B. burgdorferi spirochetes, using flow cytometry. Functionally, serum amyloid A2 reduces spirochete viability in vitro in a dose-dependent manner and enhances opsonization and phagocytosis by macrophages. Together, these findings show that adipose tissue is a site of active immune signaling in the setting of Borrelia infection and identifies SAA as a host defense factor against Borrelia.

immunology↗

bioRxiv2026

A dual neural system supporting multi-tasking cognitive flexibility

One ubiquitous feature of human intelligence is the ability to flexibly switch between multiple tasks. Abstract task representations provide a basis for task learning, switching, and generalization, yet how the brain coordinates multiple task representations to support multitasking and task-switching remains poorly understood. We recorded functional MRI activity in human participants while they concurrently held multiple task rules in working memory and prioritized different rules for stimulus processing across trials. Our results reveal two distinct coding schemes for task prioritization. First, an active coding scheme supports the spatial separation of prioritized and unprioritized task rules: prioritized rules are represented across a distributed cortical network, whereas unprioritized rules are only found in the posterior cortex. Second, besides this active scheme, subregions of the default mode network, including the medial prefrontal cortex and hippocampus, contribute to offloading task representations into an unprioritized state and subsequently maintain sustained representations of these rules across trials via latent neural codes. Behavioral predictions using on-task, trial-wise and sustained, block-wise representations further support the neural dissociation. These findings unveil a dual neural system with distinct coding schemes that jointly enable cognitive flexibility for task implementation and switching.

neuroscience↗

bioRxiv2026

The evolution of genetic drift over 50,000 generations

Random variation in reproductive success-genetic drift-profoundly shapes genetic diversity and evolutionary trajectories. The strength of drift depends on the variance in descendant number, [Formula], which governs key evolutionary outcomes: for instance, the establishment probability of a beneficial mutation scales inversely with [Formula]. However, whether [Formula] itself evolves over long timescales has remained unclear, because allele-frequency fluctuations depend on drift only through the effective population size, [Formula], which blends census population size with descendant-number variance. Here, we disentangle these components by using model-based Bayesian inference combined with joint tracking of (i) frequency fluctuations of neutrally barcoded lineages and (ii) census population sizes across growth cycles in theE. coliLong-Term Evolution Experiment (LTEE). Analyzing 33 clones spanning the ancestor through 50,000 generations in two replicate populations (Ara-2 and Ara+2), we find that the strength of genetic drift evolved markedly-and divergently-between the two replicate populations. Both census size and [Formula] changed substantially through time, with most variation in Ne driven by shifts in [Formula] rather than census size. After approximately 2,000 generations, the [Formula] of the two populations diverged sharply: Ara+2 generally remained close to a bottleneck-only null expectation, whereas Ara-2 exhibited 1.5-5x stronger drift, consistent with an evolved increase in stochasticity during growth. These results imply that mutations can alter both the mean and the variance of the descendant-number distribution, and we show that the joint distribution of mutational effects on fitness and on [Formula] can substantially modulate the rate of adaptation. The key parameter governing genetic drift can therefore itself evolve in the LTEE, with direct consequences for adaptation.

evolutionary biology↗

bioRxiv2026

High-Affinity Protein Binder Design via Flow Matching and In Silico Maturation

The de novo design of high-affinity protein binders remains a central challenge in protein engineering and therapeutic discovery. While deep generative models have advanced backbone generation and interface design, achieving picomolar or nanomolar binding affinities typically demands extensive experimental screening or iterative in vitro maturation. A general computational approach for the direct production of high-affinity binders has remained elusive. Here, we introduce an integrated framework that synergizes PPIFlow, a flow-matching-based generative model, with a novel in silico maturation strategy. PPIFlow employs a pairformer architecture to explicitly reason over pair-wise geometric and chemical interactions, modeling protein backbone rigid-body transformations as continuous flows. To bridge the affinity gap, we implement a dedicated in silico affinity maturation stage that combines interface rotamer enrichment with partial flow refinement to optimize energetic packing. This pipeline is further accelerated by AF3Score, a score-only adaptation of AlphaFold3 that enables high-fidelity and computationally efficient candidate prioritization. Across a diverse set of therapeutic targets, this synergistic approach consistently produces picomolar and nanomolar affinity binders without experimental affinity maturation. Notably, the framework proves highly effective for the de novo design of single-domain antibodies (VHHs), producing sub-nanomolar binders across multiple targets. These results establish that coupling robust backbone generation with focused in silico maturation renders the purely computational design of high-affinity binders feasible.

biochemistry↗

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

A flexible coding scheme underlying working memory generalization in human parietal and frontal cortices

Humans can rapidly extract abstract, common knowledge from distinct experiences, enabling generalization of this knowledge across tasks within working memory (WM) to guide behavior. Although task-specific representations of WM have been observed in a distributed network encompassing sensory, parietal, and frontal cortices, whether these regions construct task-generalizable representations and whether such representations can be dynamically shaped by task demands remain unclear. Across two functional MRI experiments, we investigated WM generalization across distinct WM tasks (location and object tasks) based on shared underlying task structures. Trial-specific task demands varied between passive maintenance and active, rule-guided manipulation of mnemonic stimuli. The posterior parietal cortex (PPC) demonstrated task-generalizable stimulus representations during both maintenance and manipulation. In contrast, the lateral (LFC) and medial (MFC) frontal cortices supported manipulation- and maintenance-based generalization, respectively. Critically, manipulation-based generalization in the PPC and LFC emerged even when participants did not explicitly learn the mapping between task spaces, indicating that active exploration of task structure can spontaneously facilitate generalization across tasks. Together, these findings reveal that flexible generalization for goal-directed behavior is achieved via a distributed WM network, with distinct regions serving active versus passive task demands.

neuroscience↗